Frequency of the first feature in action sequences influences feature binding.

PubMed

Mattson, Paul S; Fournier, Lisa R; Behmer, Lawrence P

2012-10-01

We investigated whether binding among perception and action feature codes is a preliminary step toward creating a more durable memory trace of an action event. If so, increasing the frequency of a particular event (e.g., a stimulus requiring a movement with the left or right hand in an up or down direction) should increase the strength and speed of feature binding for this event. The results from two experiments, using a partial-repetition paradigm, confirmed that feature binding increased in strength and/or occurred earlier for a high-frequency (e.g., left hand moving up) than for a low-frequency (e.g., right hand moving down) event. Moreover, increasing the frequency of the first-specified feature in the action sequence alone (e.g., "left" hand) increased the strength and/or speed of action feature binding (e.g., between the "left" hand and movement in an "up" or "down" direction). The latter finding suggests an update to the theory of event coding, as not all features in the action sequence equally determine binding strength. We conclude that action planning involves serial binding of features in the order of action feature execution (i.e., associations among features are not bidirectional but are directional), which can lead to a more durable memory trace. This is consistent with physiological evidence suggesting that serial order is preserved in an action plan executed from memory and that the first feature in the action sequence may be critical in preserving this serial order.

A multiscale interaction model for the origin of the tropospheric QBO

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

Goswami, B.N.

1995-03-01

A conceptual model for the origin of the tropospheric quasi-biennial oscillation (QBO) is presented. It is argued that the tropospheric QBO may not be a fundamental mode of oscillation of the tropical coupled system. It is proposed that it may arise due to multiscale interactions between high-frequency synoptic and intraseasonal oscillations of the atmosphere and a low-frequency oscillation of the couple system in the presence of the annual cycle. This is demonstrated using a conceptual low-order system consisting of three variables representing the nonlinear atmospheric oscillations and a linear oscillator representing the low-frequency coupled mode. The annual cycle and couplingmore » to the low-frequency linear oscillator provide slowly varying forcings for the atmospheric high-frequency oscillations. The atmospheric oscillations go through a chaotic regime during a certain part of the slowly varying forcing. Such variable forcing introduces a low-frequency tail in the spectrum of the atmospheric high-frequency oscillations. The low-frequency tail resonantly interacts with the low-frequency oscillation and produces the QBO in addition to broadening the spectrum of the low-frequency oscillator. The conceptual model simulates features similar to many observed features of the tropospheric QBO but depends on the assumption that there is an inherent low-frequency El Nino-Southern Oscillation oscillation with a four-year period that occurs independently of the high-frequency forcing or the QBO.« less

Precession feature extraction of ballistic missile warhead with high velocity

NASA Astrophysics Data System (ADS)

Sun, Huixia

2018-04-01

This paper establishes the precession model of ballistic missile warhead, and derives the formulas of micro-Doppler frequency induced by the target with precession. In order to obtain micro-Doppler feature of ballistic missile warhead with precession, micro-Doppler bandwidth estimation algorithm, which avoids velocity compensation, is presented based on high-resolution time-frequency transform. The results of computer simulations confirm the effectiveness of the proposed method even with low signal-to-noise ratio.

Vibrational tug-of-war: The pKA dependence of the broad vibrational features of strongly hydrogen-bonded carboxylic acids

NASA Astrophysics Data System (ADS)

Van Hoozen, Brian L.; Petersen, Poul B.

2018-04-01

Medium and strong hydrogen bonds give rise to broad vibrational features frequently spanning several hundred wavenumbers and oftentimes exhibiting unusual substructures. These broad vibrational features can be modeled from first principles, in a reduced dimensional calculation, that adiabatically separates low-frequency modes, which modulate the hydrogen bond length, from high-frequency OH stretch and bend modes that contribute to the vibrational structure. Previously this method was used to investigate the origin of an unusual vibrational feature frequently found in the spectra of dimers between carboxylic acids and nitrogen-containing aromatic bases that spans over 900 cm-1 and contains two broad peaks. It was found that the width of this feature largely originates from low-frequency modes modulating the hydrogen bond length and that the structure results from Fermi resonance interactions. In this report, we examine how these features change with the relative acid and base strength of the components as reflected by their aqueous pKA values. Dimers with large pKA differences are found to have features that can extend to frequencies below 1000 cm-1. The relationships between mean OH/NH frequency, aqueous pKA, and O-N distance are examined in order to obtain a more rigorous understanding of the origin and shape of the vibrational features. The mean OH/NH frequencies are found to correlate well with O-N distances. The lowest OH stretch frequencies are found in dimer geometries with O-N distances between 2.5 and 2.6 Å. At larger O-N distances, the hydrogen bonding interaction is not as strong, resulting in higher OH stretch frequencies. When the O-N distance is smaller than 2.5 Å, the limited space between the O and N determines the OH stretch frequency, which gives rise to frequencies that decrease with O-N distances. These two effects place a lower limit on the OH stretch frequency which is calculated to be near 700 cm-1. Understanding how the vibrational features of strongly hydrogen-bonded structures depend on the relative pKA and other structural parameters will guide studies of biological structures and analysis of proton transfer studies using photoacids.

Unprecedentedly Strong and Narrow Electromagnetic Emissions Stimulated by High-Frequency Radio Waves in the Ionosphere

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

Norin, L.; Leyser, T. B.; Nordblad, E.

2009-02-13

Experimental results of secondary electromagnetic radiation, stimulated by high-frequency radio waves irradiating the ionosphere, are reported. We have observed emission peaks, shifted in frequency up to a few tens of Hertz from radio waves transmitted at several megahertz. These emission peaks are by far the strongest spectral features of secondary radiation that have been reported. The emissions are attributed to stimulated Brillouin scattering, long predicted but hitherto never unambiguously identified in high-frequency ionospheric interaction experiments. The experiments were performed at the High-Frequency Active Auroral Research Program (HAARP), Alaska, USA.

Unprecedentedly strong and narrow electromagnetic emissions stimulated by high-frequency radio waves in the ionosphere.

PubMed

Norin, L; Leyser, T B; Nordblad, E; Thidé, B; McCarrick, M

2009-02-13

Experimental results of secondary electromagnetic radiation, stimulated by high-frequency radio waves irradiating the ionosphere, are reported. We have observed emission peaks, shifted in frequency up to a few tens of Hertz from radio waves transmitted at several megahertz. These emission peaks are by far the strongest spectral features of secondary radiation that have been reported. The emissions are attributed to stimulated Brillouin scattering, long predicted but hitherto never unambiguously identified in high-frequency ionospheric interaction experiments. The experiments were performed at the High-Frequency Active Auroral Research Program (HAARP), Alaska, USA.

Topology optimization of two-dimensional elastic wave barriers

NASA Astrophysics Data System (ADS)

Van hoorickx, C.; Sigmund, O.; Schevenels, M.; Lazarov, B. S.; Lombaert, G.

2016-08-01

Topology optimization is a method that optimally distributes material in a given design domain. In this paper, topology optimization is used to design two-dimensional wave barriers embedded in an elastic halfspace. First, harmonic vibration sources are considered, and stiffened material is inserted into a design domain situated between the source and the receiver to minimize wave transmission. At low frequencies, the stiffened material reflects and guides waves away from the surface. At high frequencies, destructive interference is obtained that leads to high values of the insertion loss. To handle harmonic sources at a frequency in a given range, a uniform reduction of the response over a frequency range is pursued. The minimal insertion loss over the frequency range of interest is maximized. The resulting design contains features at depth leading to a reduction of the insertion loss at the lowest frequencies and features close to the surface leading to a reduction at the highest frequencies. For broadband sources, the average insertion loss in a frequency range is optimized. This leads to designs that especially reduce the response at high frequencies. The designs optimized for the frequency averaged insertion loss are found to be sensitive to geometric imperfections. In order to obtain a robust design, a worst case approach is followed.

Alcohol marketing in televised international football: frequency analysis.

PubMed

Adams, Jean; Coleman, James; White, Martin

2014-05-20

Alcohol marketing includes sponsorship of individuals, organisations and sporting events. Football (soccer) is one of the most popular spectator sports worldwide. No previous studies have quantified the frequency of alcohol marketing in a high profile international football tournament. The aims were to determine: the frequency and nature of visual references to alcohol in a representative sample of EURO2012 matches broadcast in the UK; and if frequency or nature varied between matches broadcast on public service and commercial channels, or between matches that did and did not feature England. Eight matches selected by stratified random sampling were recorded. All visual references to alcohol were identified using a tool with high inter-rater reliability. 1846 visual references to alcohol were identified over 1487 minutes of broadcast--an average of 1.24 references per minute. The mean number of references per minute was higher in matches that did vs did not feature England (p = 0.004), but did not differ between matches broadcast on public service vs commercial channels (p = 0.92). The frequency of visual references to alcohol was universally high and higher in matches featuring the only UK home team--England--suggesting that there may be targeting of particularly highly viewed matches. References were embedded in broadcasts, and not particular to commercial channels including paid-for advertising. New UK codes-of-conduct on alcohol marketing at sporting events will not reduce the level of marketing reported here.

Nonlinear acoustic spectroscopy of cracked flaws and disbonds: Fundamentals, techniques, and applications

NASA Astrophysics Data System (ADS)

Maev, R. Gr.; Solodov, I. Yu.

2000-05-01

Classical nonlinear acoustics of solids operates with distributed material nonlinearity related to unharmonicity of molecular interaction forces. Weakening of molecular bonds in a defect area or intermittent lack of elastic coupling between the faces of a vibrating crack or unbond ("clapping") results in anomalously high local contact acoustic nonlinearity (CAN). CAN properties and spectral features are different from those of the classical analog and important to develop new acoustic NDE techniques. Three approaches to nonlinear NDE methodology have been experimentally verified: low-frequency (hundreds of Hz) vibration technique, intermediate-frequency (hundreds of kHz) standing wave and high-frequency (tens of MHz) propagation modes. Low-frequency nonlinear contact vibrations revealed multiple sub- and super-harmonics generation featuring non-monotonous (sinx/x type) spectra. Parametric instability observed in resonator with a nonlinear contact leads to the output spectrum splitting up into successive sub-harmonics as the wave amplitude increases. High-frequency experiments demonstrated abnormal increases in the third harmonic amplitude: 3 or 4 order enhancement of the 3-ω nonlinear parameter was measured for the nonlinear contact. The CAN spectral features in both acoustic and vibration modes were used for nonlinear NDE of simulated and realistic flaws in glass, metal welds, etc. The sensitivities of the techniques are compared and their practical applicability assessed.

A Close Look At The Relationship Between WMAP (ILC) Small-Scale Features And Galactic HI Structure

NASA Astrophysics Data System (ADS)

Verschuur, Gerrit L.

2012-05-01

Galactic HI emission profiles surrounding two pairs of features located where large-scale filaments at very different velocities overlap were decomposed into Gaussian components. Families of components defined by similarity of center velocities and line widths were identified and found to be spatially related. Each of the two pairs of HI peaks straddle a high-frequency continuum source revealed in the WMAP survey data. It is suggested that where filamentary HI features are directly interacting high-frequency continuum radiation is being produced. The previously hypothesized mechanism for producing high-frequency continuum radiation involving free-free emission from electrons in the interstellar medium, in this case created where HI filaments interact to produce fractional ionizations of order 5 to 15%, fit the data very closely. The results confirm that WMAP data on small-scale structures believed to be cosmological in origin are in fact compromised by the presence of intervening galactic sources of interstellar electrons clumped on scales typical of interstellar HI structure.

Simple method enabling pulse on command from high power, high frequency lasers

NASA Astrophysics Data System (ADS)

Baer, David J.; Marshall, Graham D.; Coutts, David W.; Mildren, Richard P.; Withford, Michael J.

2006-09-01

A method for addressing individual laser pulses in high repetition frequency systems using an intracavity optical chopper and novel electronic timing system is reported. This "pulse on command" capability is shown to enable free running and both subharmonic pulse rate and burst mode operation of a high power, high pulse frequency copper vapor laser while maintaining a fixed output pulse energy. We demonstrate that this technique can be used to improve feature finish when laser micromachining metal.

Electromagnetic perception and individual features of human beings.

PubMed

Lebedeva, N N; Kotrovskaya, T I

2001-01-01

An investigation was made of the individual reactions of human subjects exposed to electromagnetic fields. We performed the study on 86 volunteers separated into two groups. The first group was exposed to the electromagnetic field of infralow frequencies, whereas the second group was exposed to the electromagnetic field of extremely high frequencies. We found that the electromagnetic perception of human beings correlated with their individual features, such as EEG parameters, the critical frequency of flash merging, and the electric current sensitivity. Human subjects who had a high-quality perception of electromagnetic waves showed an optimal balance of cerebral processes, an excellent functional state of the central nervous system, and a good decision criterion.

A time-frequency classifier for human gait recognition

NASA Astrophysics Data System (ADS)

Mobasseri, Bijan G.; Amin, Moeness G.

2009-05-01

Radar has established itself as an effective all-weather, day or night sensor. Radar signals can penetrate walls and provide information on moving targets. Recently, radar has been used as an effective biometric sensor for classification of gait. The return from a coherent radar system contains a frequency offset in the carrier frequency, known as the Doppler Effect. The movements of arms and legs give rise to micro Doppler which can be clearly detailed in the time-frequency domain using traditional or modern time-frequency signal representation. In this paper we propose a gait classifier based on subspace learning using principal components analysis(PCA). The training set consists of feature vectors defined as either time or frequency snapshots taken from the spectrogram of radar backscatter. We show that gait signature is captured effectively in feature vectors. Feature vectors are then used in training a minimum distance classifier based on Mahalanobis distance metric. Results show that gait classification with high accuracy and short observation window is achievable using the proposed classifier.

Vibrational tug-of-war: The pKA dependence of the broad vibrational features of strongly hydrogen-bonded carboxylic acids.

PubMed

Van Hoozen, Brian L; Petersen, Poul B

2018-04-07

Medium and strong hydrogen bonds give rise to broad vibrational features frequently spanning several hundred wavenumbers and oftentimes exhibiting unusual substructures. These broad vibrational features can be modeled from first principles, in a reduced dimensional calculation, that adiabatically separates low-frequency modes, which modulate the hydrogen bond length, from high-frequency OH stretch and bend modes that contribute to the vibrational structure. Previously this method was used to investigate the origin of an unusual vibrational feature frequently found in the spectra of dimers between carboxylic acids and nitrogen-containing aromatic bases that spans over 900 cm -1 and contains two broad peaks. It was found that the width of this feature largely originates from low-frequency modes modulating the hydrogen bond length and that the structure results from Fermi resonance interactions. In this report, we examine how these features change with the relative acid and base strength of the components as reflected by their aqueous pK A values. Dimers with large pK A differences are found to have features that can extend to frequencies below 1000 cm -1 . The relationships between mean OH/NH frequency, aqueous pK A , and O-N distance are examined in order to obtain a more rigorous understanding of the origin and shape of the vibrational features. The mean OH/NH frequencies are found to correlate well with O-N distances. The lowest OH stretch frequencies are found in dimer geometries with O-N distances between 2.5 and 2.6 Å. At larger O-N distances, the hydrogen bonding interaction is not as strong, resulting in higher OH stretch frequencies. When the O-N distance is smaller than 2.5 Å, the limited space between the O and N determines the OH stretch frequency, which gives rise to frequencies that decrease with O-N distances. These two effects place a lower limit on the OH stretch frequency which is calculated to be near 700 cm -1 . Understanding how the vibrational features of strongly hydrogen-bonded structures depend on the relative pK A and other structural parameters will guide studies of biological structures and analysis of proton transfer studies using photoacids.

The formation method of the feature space for the identification of fatigued bills

NASA Astrophysics Data System (ADS)

Kang, Dongshik; Oshiro, Ayumu; Ozawa, Kenji; Mitsui, Ikugo

2014-10-01

Fatigued bills make a trouble such as the paper jam in a bill handling machine. In the discrimination of fatigued bills using an acoustic signal, the variation of an observed bill sound is considered to be one of causes in misclassification. Therefore a technique has demanded in order to make the classification of fatigued bills more efficient. In this paper, we proposed the algorithm that extracted feature quantity of bill sound from acoustic signal using the frequency difference, and carried out discrimination experiment of fatigued bill money by Support Vector Machine(SVM). The feature quantity of frequency difference can represent the frequency components of an acoustic signal is varied by the fatigued degree of bill money. The generalization performance of SVM does not depend on the size of dimensions of the feature space, even in a high dimensional feature space such as bill-acoustic signals. Furthermore, SVM can induce an optimal classifier which considers the combination of features by the virtue of polynomial kernel functions.

Design and calibration of a high-frequency oscillatory ventilator.

PubMed

Simon, B A; Mitzner, W

1991-02-01

High-frequency ventilation (HFV) is a modality of mechanical ventilation which presents difficult technical demands to the clinical or laboratory investigator. The essential features of an ideal HFV system are described, including wide frequency range, control of tidal volume and mean airway pressure, minimal dead space, and high effective internal impedance. The design and performance of a high-frequency oscillatory ventilation system is described which approaches these requirements. The ventilator utilizes a linear motor regulated by a closed loop controller and driving a novel frictionless double-diaphragm piston pump. Finally, the ventilator performance is tested using the impedance model of Venegas [1].

Alcohol marketing in televised international football: frequency analysis

PubMed Central

2014-01-01

Background Alcohol marketing includes sponsorship of individuals, organisations and sporting events. Football (soccer) is one of the most popular spectator sports worldwide. No previous studies have quantified the frequency of alcohol marketing in a high profile international football tournament. The aims were to determine: the frequency and nature of visual references to alcohol in a representative sample of EURO2012 matches broadcast in the UK; and if frequency or nature varied between matches broadcast on public service and commercial channels, or between matches that did and did not feature England. Methods Eight matches selected by stratified random sampling were recorded. All visual references to alcohol were identified using a tool with high inter-rater reliability. Results 1846 visual references to alcohol were identified over 1487 minutes of broadcast - an average of 1.24 references per minute. The mean number of references per minute was higher in matches that did vs did not feature England (p = 0.004), but did not differ between matches broadcast on public service vs commercial channels (p = 0.92). Conclusions The frequency of visual references to alcohol was universally high and higher in matches featuring the only UK home team - England - suggesting that there may be targeting of particularly highly viewed matches. References were embedded in broadcasts, and not particular to commercial channels including paid-for advertising. New UK codes-of-conduct on alcohol marketing at sporting events will not reduce the level of marketing reported here. PMID:24885718

Multifrequency Raman amplifiers

NASA Astrophysics Data System (ADS)

Barth, Ido; Fisch, Nathaniel J.

2018-03-01

In its usual implementation, the Raman amplifier features only one pump carrier frequency. However, pulses with well-separated frequencies can also be Raman amplified while compressed in time. Amplification with frequency-separated pumps is shown to hold even in the highly nonlinear, pump-depletion regime, as derived through a fluid model, and demonstrated via particle-in-cell simulations. The resulting efficiency is similar to single-frequency amplifiers, but, due to the beat-wave waveform of both the pump lasers and the amplified seed pulses, these amplifiers feature higher seed intensities with a shorter spike duration. Advantageously, these amplifiers also suffer less noise backscattering, because the total fluence is split between the different spectral components.

The 67 Hz Feature in the Black Hole Candidate GRS 1915+105 as a Possible Diskoseismic Mode

NASA Technical Reports Server (NTRS)

Nowak, Michael A.; Wagoner, Robert V.; Begelman, Mitchell C.; Lehr, Dana E.

1997-01-01

The Rossi X-Ray Timing Explorer has made feasible for the first time the search for high-frequency (greater than or equal to 100 Hz) periodic features in Black Hole Candidate (BHC) systems. Such a feature, with a 67 Hz frequency, recently has been discovered in the BHC GRS 1915+105 (Morgan, Remillard, & Greiner). This feature is weak (rms variability approx. 0.3%-1.6%), stable in frequency (to within approx. 2 Hz) despite appreciable luminosity fluctuations, and narrow (quality factor Q approx. 20). Several of these properties are what one expects for a 'diskoseismic' g-mode in an accretion disk about a 10.6 M(solar mass) (nonrotating) to 36.3 M(solar mass) (maximally rotating) black hole (if we are observing the fundamental-mode frequency). We explore this possibility by considering the expected luminosity modulation, as well as possible excitation and growth mechanisms-including turbulent excitation, damping, and 'negative' radiation damping. We conclude that a diskoseismic interpretation of the observations is viable.

Tissue classification using depth-dependent ultrasound time series analysis: in-vitro animal study

NASA Astrophysics Data System (ADS)

Imani, Farhad; Daoud, Mohammad; Moradi, Mehdi; Abolmaesumi, Purang; Mousavi, Parvin

2011-03-01

Time series analysis of ultrasound radio-frequency (RF) signals has been shown to be an effective tissue classification method. Previous studies of this method for tissue differentiation at high and clinical-frequencies have been reported. In this paper, analysis of RF time series is extended to improve tissue classification at the clinical frequencies by including novel features extracted from the time series spectrum. The primary feature examined is the Mean Central Frequency (MCF) computed for regions of interest (ROIs) in the tissue extending along the axial axis of the transducer. In addition, the intercept and slope of a line fitted to the MCF-values of the RF time series as a function of depth have been included. To evaluate the accuracy of the new features, an in vitro animal study is performed using three tissue types: bovine muscle, bovine liver, and chicken breast, where perfect two-way classification is achieved. The results show statistically significant improvements over the classification accuracies with previously reported features.

Clinical and epidemiological features of extrapulmonary tuberculosis in a high incidence region.

PubMed

Pérez-Guzmán, Carlos; Vargas, Mario H; Arellano-Macías, María del Rosario; Hernández-Cobos, Silvia; García-Ituarte, Aurea Zelindabeth; Serna-Vela, Francisco Javier

2014-04-01

To describe the clinical features of extrapulmonary tuberculosis (EXPTB) and to evaluate epidemiological data to search for potential explanations for its high frequency in the state of Aguascalientes, Mexico. Clinical records of all patients with tuberculosis seen in Aguascalientes in 2008 were reviewed, and official databases were analyzed. EXPTB comprised 60.5% of the 86 cases evaluated, being lymph nodes the main site affected. Patients with EXPTB were younger and more obese than subjects with pulmonary tuberculosis (PTB). One third of cases in either group had diabetes, a frequency much higher than expected. Epidemiological analysis showed that PTB incidence, but not EXPTB incidence, decreases as geographical altitude increases, and had a descendent trend from 1997 to 2011. The lower frequency of PTB (due to its inverse relationship with altitude and its descendent trend in last years) might explain the high frequency of EXPTB. Obesity appeared to protect against developing pulmonary involvement, and diabetes was more frequent than expected among PTB and EXPTB cases.

Elemental Study on Auscultaiting Diagnosis Support System of Hemodialysis Shunt Stenosis by ANN

NASA Astrophysics Data System (ADS)

Suzuki, Yutaka; Fukasawa, Mizuya; Mori, Takahiro; Sakata, Osamu; Hattori, Asobu; Kato, Takaya

It is desired to detect stenosis at an early stage to use hemodailysis shunt for longer time. Stethoscope auscultation of vascular murmurs is useful noninvasive diagnostic approach, but an experienced expert operator is necessary. Some experts often say that the high-pitch murmurs exist if the shunt becomes stenosed, and some studies report that there are some features detected at high frequency by time-frequency analysis. However, some of the murmurs are difficult to detect, and the final judgment is difficult. This study proposes a new diagnosis support system to screen stenosis by using vascular murmurs. The system is performed using artificial neural networks (ANN) with the analyzed frequency data by maximum entropy method (MEM). The author recorded vascular murmurs both before percutaneous transluminal angioplasty (PTA) and after. Examining the MEM spectral characteristics of the high-pitch stenosis murmurs, three features could be classified, which covered 85 percent of stenosis vascular murmurs. The features were learnt by the ANN, and judged. As a result, a percentage of judging the classified stenosis murmurs was 100%, and that of normal was 86%.

Noninvasive Diagnosis of Coronary Artery Disease Using 12-Lead High-Frequency Electrocardiograms

NASA Technical Reports Server (NTRS)

Schlegel, Todd T.; Arenare, Brian

2006-01-01

A noninvasive, sensitive method of diagnosing certain pathological conditions of the human heart involves computational processing of digitized electrocardiographic (ECG) signals acquired from a patient at all 12 conventional ECG electrode positions. In the processing, attention is focused on low-amplitude, high-frequency components of those portions of the ECG signals known in the art as QRS complexes. The unique contribution of this method lies in the utilization of signal features and combinations of signal features from various combinations of electrode positions, not reported previously, that have been found to be helpful in diagnosing coronary artery disease and such related pathological conditions as myocardial ischemia, myocardial infarction, and congestive heart failure. The electronic hardware and software used to acquire the QRS complexes and perform some preliminary analyses of their high-frequency components were summarized in Real-Time, High-Frequency QRS Electrocardiograph (MSC- 23154), NASA Tech Briefs, Vol. 27, No. 7 (July 2003), pp. 26-28. To recapitulate, signals from standard electrocardiograph electrodes are preamplified, then digitized at a sampling rate of 1,000 Hz, then analyzed by the software that detects R waves and QRS complexes and analyzes them from several perspectives. The software includes provisions for averaging signals over multiple beats and for special-purpose nonrecursive digital filters with specific low- and high-frequency cutoffs. These filters, applied to the averaged signal, effect a band-pass operation in the frequency range from 150 to 250 Hz. The output of the bandpass filter is the desired high-frequency QRS signal. Further processing is then performed in real time to obtain the beat-to-beat root mean square (RMS) voltage amplitude of the filtered signal, certain variations of the RMS voltage, and such standard measures as the heart rate and R-R interval at any given time. A key signal feature analyzed in the present method is the presence versus the absence of reduced-amplitude zones (RAZs). In terms that must be simplified for the sake of brevity, an RAZ comprises several cycles of a high-frequency QRS signal during which the amplitude of the high-frequency oscillation in a portion of the signal is abnormally low (see figure). A given signal sample exhibiting an interval of reduced amplitude may or may not be classified as an RAZ, depending on quantitative criteria regarding peaks and troughs within the reduced-amplitude portion of the high-frequency QRS signal. This analysis is performed in all 12 leads in real time.

Recent Observations and Modeling of Narrowband Stimulated Electromagnetic Emissions SEEs at the HAARP Facility

NASA Astrophysics Data System (ADS)

Scales, Wayne; Bernhardt, Paul; McCarrick, Michael; Briczinski, Stanley; Mahmoudian, Alireza; Fu, Haiyang; Ranade Bordikar, Maitrayee; Samimi, Alireza

There has been significant interest in so-called narrowband Stimulated Electromagnetic Emission SEE over the past several years due to recent discoveries at the High Frequency Active Auroral Research Program HAARP facility near Gakone, Alaska. Narrowband SEE (NSEE) has been defined as spectral features in the SEE spectrum typically within 1 kHz of the transmitter (or pump) frequency. SEE is due to nonlinear processes leading to re-radiation at frequencies other than the pump wave frequency during heating the ionospheric plasma with high power HF radio waves. Although NSEE exhibits a richly complex structure, it has now been shown after a substantial number of observations at HAARP, that NSEE can be grouped into two basic classes. The first are those spectral features, associated with Stimulated Brillouin Scatter SBS, which typically occur when the pump frequency is not close to electron gyro-harmonic frequencies. Typically, these spectral features are within roughly 50 Hz of the pump wave frequency where it is to be noted that the O+ ion gyro-frequency is roughly 50 Hz. The second class of spectral features corresponds to the case when the pump wave frequency is typically within roughly 10 kHz of electron gyro-harmonic frequencies. In this case, spectral features ordered by harmonics of ion gyro-frequencies are typically observed, and termed Stimulated Ion Bernstein Scatter SIBS. There is also important parametric behavior on both classes of NSEE depending on the pump wave parameters including the field strength, antenna beam angle, and electron gyro-harmonic number. This presentation will first provide an overview of the recent NSEE experimental observations at HAARP. Both Stimulated Brillouin Scatter SBS and Stimulated Ion Bernstein Scatter SIBS observations will be discussed as well as their relationship to each other. Possible theoretical formulation in terms of parametric decay instabilities will be provided. Computer simulation model results will be presented to provide insight into associated higher order nonlinear effects including particle acceleration and wave-wave processes. Both theory and model results will be put into the context of the experimental observations. Finally, possible applications of NSEE will be pointed out including triggering diagnostics for artificial ionization layer formation, proton precipitation event diagnostics, and electron temperature measurements in the heated volume.

Complementary spectroscopic studies of materials of security interest

NASA Astrophysics Data System (ADS)

Burnett, Andrew; Fan, Wenhui; Upadhya, Prashanth; Cunningham, John; Edwards, Howell; Munshi, Tasnim; Hargreaves, Michael; Linfield, Edmund; Davies, Giles

2006-09-01

We demonstrate that, through coherent measurement of the transmitted terahertz frequency electric fields, broadband (0.3 - 8 THz) time-domain spectroscopy can be used to measure far-infrared vibrational modes of a range of drugs-of-abuse and high explosives that are of interest to the forensic and security services. Our results indicate that absorption features in these materials are highly sensitive to the structural and spatial arrangement of the molecules. Terahertz frequency spectra are also compared with high-resolution low-frequency Raman spectra to assist in understanding the low-frequency inter- and intra-molecular vibrational modes of the molecules.

Global Model for Asymmetric, Diode-Type Dual Frequency Capacitive Discharge

NASA Astrophysics Data System (ADS)

Kim, Jisoo; Lieberman, M. A.; Lichtenberg, A. J.

2003-10-01

Dual frequency capacitive reactors can have desirable properties for dielectric etch: low cost, robust uniformity over large areas, and control of dissociation. In the ideal case, the high frequency power controls the plasma density (ion flux) and the low frequency voltage controls the ion bombarding energy. Typical operating conditions are: discharge radius 15-30 cm, length 1-3 cm, pressure 30-200 mTorr, high frequency 27.1-160 MHz, low frequency 2-13.6 MHz, and powers of 500-3000 W for both high and low frequencies. The decoupling of the high and low frequencies is an important feature of dual frequency capacitive discharges. In this work, we describe a global (volume-averaged) model having different top and bottom plate areas that incorporates particle balance, and ohmic and stochastic heating for high and low frequencies. The model is used to obtain the decoupling of high and low frequencies and to investigate limitations to ideal decoupling. Support provided by Lam Research, NSF Grant ECS-0139956, California industries, and UC-SMART Contract SM99-10051.

Multifrequency Raman amplifiers

DOE PAGES

Barth, Ido; Fisch, Nathaniel J.

2018-03-08

In its usual implementation, the Raman amplifier features only one pump carrier frequency. However, pulses with well-separated frequencies can also be Raman amplified while compressed in time. Amplification with frequency-separated pumps is shown to hold even in the highly nonlinear, pump-depletion regime, as derived through a fluid model, and demonstrated via particle-in-cell (PIC) simulations. The resulting efficiency is similar to single-frequency amplifiers, but, due to the beat-wave waveform of both the pump lasers and the amplified seed pulses, these amplifiers feature higher seed intensities with a shorter spike duration. Advantageously, these amplifiers also suffer less noise backscattering, because the totalmore » fluence is split between the different spectral components.« less

Multifrequency Raman amplifiers

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

Barth, Ido; Fisch, Nathaniel J.

In its usual implementation, the Raman amplifier features only one pump carrier frequency. However, pulses with well-separated frequencies can also be Raman amplified while compressed in time. Amplification with frequency-separated pumps is shown to hold even in the highly nonlinear, pump-depletion regime, as derived through a fluid model, and demonstrated via particle-in-cell (PIC) simulations. The resulting efficiency is similar to single-frequency amplifiers, but, due to the beat-wave waveform of both the pump lasers and the amplified seed pulses, these amplifiers feature higher seed intensities with a shorter spike duration. Advantageously, these amplifiers also suffer less noise backscattering, because the totalmore » fluence is split between the different spectral components.« less

Whole-genome phylogeny of Escherichia coli/Shigella group by feature frequency profiles (FFPs)

PubMed Central

Sims, Gregory E.; Kim, Sung-Hou

2011-01-01

A whole-genome phylogeny of the Escherichia coli/Shigella group was constructed by using the feature frequency profile (FFP) method. This alignment-free approach uses the frequencies of l-mer features of whole genomes to infer phylogenic distances. We present two phylogenies that accentuate different aspects of E. coli/Shigella genomic evolution: (i) one based on the compositions of all possible features of length l = 24 (∼8.4 million features), which are likely to reveal the phenetic grouping and relationship among the organisms and (ii) the other based on the compositions of core features with low frequency and low variability (∼0.56 million features), which account for ∼69% of all commonly shared features among 38 taxa examined and are likely to have genome-wide lineal evolutionary signal. Shigella appears as a single clade when all possible features are used without filtering of noncore features. However, results using core features show that Shigella consists of at least two distantly related subclades, implying that the subclades evolved into a single clade because of a high degree of convergence influenced by mobile genetic elements and niche adaptation. In both FFP trees, the basal group of the E. coli/Shigella phylogeny is the B2 phylogroup, which contains primarily uropathogenic strains, suggesting that the E. coli/Shigella ancestor was likely a facultative or opportunistic pathogen. The extant commensal strains diverged relatively late and appear to be the result of reductive evolution of genomes. We also identify clade distinguishing features and their associated genomic regions within each phylogroup. Such features may provide useful information for understanding evolution of the groups and for quick diagnostic identification of each phylogroup. PMID:21536867

Nullomers and High Order Nullomers in Genomic Sequences

PubMed Central

Vergni, Davide; Santoni, Daniele

2016-01-01

A nullomer is an oligomer that does not occur as a subsequence in a given DNA sequence, i.e. it is an absent word of that sequence. The importance of nullomers in several applications, from drug discovery to forensic practice, is now debated in the literature. Here, we investigated the nature of nullomers, whether their absence in genomes has just a statistical explanation or it is a peculiar feature of genomic sequences. We introduced an extension of the notion of nullomer, namely high order nullomers, which are nullomers whose mutated sequences are still nullomers. We studied different aspects of them: comparison with nullomers of random sequences, CpG distribution and mean helical rise. In agreement with previous results we found that the number of nullomers in the human genome is much larger than expected by chance. Nevertheless antithetical results were found when considering a random DNA sequence preserving dinucleotide frequencies. The analysis of CpG frequencies in nullomers and high order nullomers revealed, as expected, a high CpG content but it also highlighted a strong dependence of CpG frequencies on the dinucleotide position, suggesting that nullomers have their own peculiar structure and are not simply sequences whose CpG frequency is biased. Furthermore, phylogenetic trees were built on eleven species based on both the similarities between the dinucleotide frequencies and the number of nullomers two species share, showing that nullomers are fairly conserved among close species. Finally the study of mean helical rise of nullomers sequences revealed significantly high mean rise values, reinforcing the hypothesis that those sequences have some peculiar structural features. The obtained results show that nullomers are the consequence of the peculiar structure of DNA (also including biased CpG frequency and CpGs islands), so that the hypermutability model, also taking into account CpG islands, seems to be not sufficient to explain nullomer phenomenon. Finally, high order nullomers could emphasize those features that already make simple nullomers useful in several applications. PMID:27906971

Performance Analysis of AN Engine Mount Featuring ER Fluids and Piezoactuators

NASA Astrophysics Data System (ADS)

Choi, S. H.; Choi, Y. T.; Choi, S. B.; Cheong, C. C.

Conventional rubber mounts and various types of passive or semi-active hydraulic engine mounts for a passenger vehicle have their own functional aims on the limited frequency band in the broad engine operating frequency range. In order to achieve high system performance over all frequency ranges of the engine operation, a new type of engine mount featuring electro-rheological(ER) fluids and piezoactuators is proposed in this study. A mathematical model of the proposed engine mount is derived using the bond graph method which is inherently adequate to model the interconnected hydromechanical system. In the low frequency domain, the ER fluid is activated upon imposing an electric field for vibration isolation while the piezoactuator is activated in the high frequency domain. A neuro-control algorithm is utilized to determine control electric field for the ER fluid, and H∞ control technique is adopted for the piezoactuator Comparative works between the proposed and single-actuating(ER fluid only or piezoactuator only) engine mounts are undertaken by evaluating force transmissibility over a wide operating frequency range.

Pose Invariant Face Recognition Based on Hybrid Dominant Frequency Features

NASA Astrophysics Data System (ADS)

Wijaya, I. Gede Pasek Suta; Uchimura, Keiichi; Hu, Zhencheng

Face recognition is one of the most active research areas in pattern recognition, not only because the face is a human biometric characteristics of human being but also because there are many potential applications of the face recognition which range from human-computer interactions to authentication, security, and surveillance. This paper presents an approach to pose invariant human face image recognition. The proposed scheme is based on the analysis of discrete cosine transforms (DCT) and discrete wavelet transforms (DWT) of face images. From both the DCT and DWT domain coefficients, which describe the facial information, we build compact and meaningful features vector, using simple statistical measures and quantization. This feature vector is called as the hybrid dominant frequency features. Then, we apply a combination of the L2 and Lq metric to classify the hybrid dominant frequency features to a person's class. The aim of the proposed system is to overcome the high memory space requirement, the high computational load, and the retraining problems of previous methods. The proposed system is tested using several face databases and the experimental results are compared to a well-known Eigenface method. The proposed method shows good performance, robustness, stability, and accuracy without requiring geometrical normalization. Furthermore, the purposed method has low computational cost, requires little memory space, and can overcome retraining problem.

An Improved Iris Recognition Algorithm Based on Hybrid Feature and ELM

NASA Astrophysics Data System (ADS)

Wang, Juan

2018-03-01

The iris image is easily polluted by noise and uneven light. This paper proposed an improved extreme learning machine (ELM) based iris recognition algorithm with hybrid feature. 2D-Gabor filters and GLCM is employed to generate a multi-granularity hybrid feature vector. 2D-Gabor filter and GLCM feature work for capturing low-intermediate frequency and high frequency texture information, respectively. Finally, we utilize extreme learning machine for iris recognition. Experimental results reveal our proposed ELM based multi-granularity iris recognition algorithm (ELM-MGIR) has higher accuracy of 99.86%, and lower EER of 0.12% under the premise of real-time performance. The proposed ELM-MGIR algorithm outperforms other mainstream iris recognition algorithms.

Calculation of selective filters of a device for primary analysis of speech signals

NASA Astrophysics Data System (ADS)

Chudnovskii, L. S.; Ageev, V. M.

2014-07-01

The amplitude-frequency responses of filters for primary analysis of speech signals, which have a low quality factor and a high rolloff factor in the high-frequency range, are calculated using the linear theory of speech production and psychoacoustic measurement data. The frequency resolution of the filter system for a sinusoidal signal is 40-200 Hz. The modulation-frequency resolution of amplitude- and frequency-modulated signals is 3-6 Hz. The aforementioned features of the calculated filters are close to the amplitudefrequency responses of biological auditory systems at the level of the eighth nerve.

Automated target classification in high resolution dual frequency sonar imagery

NASA Astrophysics Data System (ADS)

Aridgides, Tom; Fernández, Manuel

2007-04-01

An improved computer-aided-detection / computer-aided-classification (CAD/CAC) processing string has been developed. The classified objects of 2 distinct strings are fused using the classification confidence values and their expansions as features, and using "summing" or log-likelihood-ratio-test (LLRT) based fusion rules. The utility of the overall processing strings and their fusion was demonstrated with new high-resolution dual frequency sonar imagery. Three significant fusion algorithm improvements were made. First, a nonlinear 2nd order (Volterra) feature LLRT fusion algorithm was developed. Second, a Box-Cox nonlinear feature LLRT fusion algorithm was developed. The Box-Cox transformation consists of raising the features to a to-be-determined power. Third, a repeated application of a subset feature selection / feature orthogonalization / Volterra feature LLRT fusion block was utilized. It was shown that cascaded Volterra feature LLRT fusion of the CAD/CAC processing strings outperforms summing, baseline single-stage Volterra and Box-Cox feature LLRT algorithms, yielding significant improvements over the best single CAD/CAC processing string results, and providing the capability to correctly call the majority of targets while maintaining a very low false alarm rate. Additionally, the robustness of cascaded Volterra feature fusion was demonstrated, by showing that the algorithm yields similar performance with the training and test sets.

Resonance-Based Time-Frequency Manifold for Feature Extraction of Ship-Radiated Noise.

PubMed

Yan, Jiaquan; Sun, Haixin; Chen, Hailan; Junejo, Naveed Ur Rehman; Cheng, En

2018-03-22

In this paper, a novel time-frequency signature using resonance-based sparse signal decomposition (RSSD), phase space reconstruction (PSR), time-frequency distribution (TFD) and manifold learning is proposed for feature extraction of ship-radiated noise, which is called resonance-based time-frequency manifold (RTFM). This is suitable for analyzing signals with oscillatory, non-stationary and non-linear characteristics in a situation of serious noise pollution. Unlike the traditional methods which are sensitive to noise and just consider one side of oscillatory, non-stationary and non-linear characteristics, the proposed RTFM can provide the intact feature signature of all these characteristics in the form of a time-frequency signature by the following steps: first, RSSD is employed on the raw signal to extract the high-oscillatory component and abandon the low-oscillatory component. Second, PSR is performed on the high-oscillatory component to map the one-dimensional signal to the high-dimensional phase space. Third, TFD is employed to reveal non-stationary information in the phase space. Finally, manifold learning is applied to the TFDs to fetch the intrinsic non-linear manifold. A proportional addition of the top two RTFMs is adopted to produce the improved RTFM signature. All of the case studies are validated on real audio recordings of ship-radiated noise. Case studies of ship-radiated noise on different datasets and various degrees of noise pollution manifest the effectiveness and robustness of the proposed method.

Resonance-Based Time-Frequency Manifold for Feature Extraction of Ship-Radiated Noise

PubMed Central

Yan, Jiaquan; Sun, Haixin; Chen, Hailan; Junejo, Naveed Ur Rehman; Cheng, En

2018-01-01

In this paper, a novel time-frequency signature using resonance-based sparse signal decomposition (RSSD), phase space reconstruction (PSR), time-frequency distribution (TFD) and manifold learning is proposed for feature extraction of ship-radiated noise, which is called resonance-based time-frequency manifold (RTFM). This is suitable for analyzing signals with oscillatory, non-stationary and non-linear characteristics in a situation of serious noise pollution. Unlike the traditional methods which are sensitive to noise and just consider one side of oscillatory, non-stationary and non-linear characteristics, the proposed RTFM can provide the intact feature signature of all these characteristics in the form of a time-frequency signature by the following steps: first, RSSD is employed on the raw signal to extract the high-oscillatory component and abandon the low-oscillatory component. Second, PSR is performed on the high-oscillatory component to map the one-dimensional signal to the high-dimensional phase space. Third, TFD is employed to reveal non-stationary information in the phase space. Finally, manifold learning is applied to the TFDs to fetch the intrinsic non-linear manifold. A proportional addition of the top two RTFMs is adopted to produce the improved RTFM signature. All of the case studies are validated on real audio recordings of ship-radiated noise. Case studies of ship-radiated noise on different datasets and various degrees of noise pollution manifest the effectiveness and robustness of the proposed method. PMID:29565288

Sexual Violence among Men in the Military in South Korea

ERIC Educational Resources Information Center

Kwon, Insook; Lee, Dong-Ok; Kim, Elli; Kim, Hyun-Young

2007-01-01

This research is about sexual violence among men in the military in South Korea. The authors investigated the frequencies, causes, and circumstances surrounding sexual violence and looked for characteristic features of sexual violence among men in the military in South Korea. They found a high frequency of physical sexual violence and a high level…

Cuprate High Temperature Superconductors and the Vision for Room Temperature Superconductivity

NASA Astrophysics Data System (ADS)

Newns, Dennis M.; Martyna, Glenn J.; Tsuei, Chang C.

Superconducting transition temperatures of 164 K in cuprate high temperature superconductors (HTS) and recently 200 K in H3S under high pressure encourage us to believe that room temperature superconductivity (RTS) might be possible. In considering paths to RTS, we contrast conventional (BCS) SC, such as probably manifested by H3S, with the unconventional superconductivity (SC) in the cuprate HTS family. Turning to SC models, we show that in the presence of one or more van Hove singularities (vHs) near the Fermi level, SC mediated by classical phonons (kBTc>ℏ×phonon frequency) can occur. The phonon frequency in the standard Tc formula is replaced by an electronic cutoff, enabling a much higher Tc independent of phonon frequency. The resulting Tc and isotope shift plot versus doping strongly resembles that seen experimentally in HTS. A more detailed theory of HTS, which involves mediation by classical phonons, satisfactorily reproduces the chief anomalous features characteristic of these materials. We propose that, while a path to RTS through an H3S-like scenario via strongly-coupled ultra-high frequency phonons is attractive, features perhaps unavailable at ordinary pressures, a route involving SC mediated by classical phonons which can be low frequency may be found.

Features of Heart Rate Variability Capture Regulatory Changes During Kangaroo Care in Preterm Infants.

PubMed

Kommers, Deedee R; Joshi, Rohan; van Pul, Carola; Atallah, Louis; Feijs, Loe; Oei, Guid; Bambang Oetomo, Sidarto; Andriessen, Peter

2017-03-01

To determine whether heart rate variability (HRV) can serve as a surrogate measure to track regulatory changes during kangaroo care, a period of parental coregulation distinct from regulation within the incubator. Nurses annotated the starting and ending times of kangaroo care for 3 months. The pre-kangaroo care, during-kangaroo care, and post-kangaroo care data were retrieved in infants with at least 10 accurately annotated kangaroo care sessions. Eight HRV features (5 in the time domain and 3 in the frequency domain) were used to visually and statistically compare the pre-kangaroo care and during-kangaroo care periods. Two of these features, capturing the percentage of heart rate decelerations and the extent of heart rate decelerations, were newly developed for preterm infants. A total of 191 kangaroo care sessions were investigated in 11 preterm infants. Despite clinically irrelevant changes in vital signs, 6 of the 8 HRV features (SD of normal-to-normal intervals, root mean square of the SD, percentage of consecutive normal-to-normal intervals that differ by >50 ms, SD of heart rate decelerations, high-frequency power, and low-frequency/high-frequency ratio) showed a visible and statistically significant difference (P <.01) between stable periods of kangaroo care and pre-kangaroo care. HRV was reduced during kangaroo care owing to a decrease in the extent of transient heart rate decelerations. HRV-based features may be clinically useful for capturing the dynamic changes in autonomic regulation in response to kangaroo care and other changes in environment and state. Copyright © 2016 Elsevier Inc. All rights reserved.

Performances of OsO(4) stabilized CO(2) lasers as optical frequency standards near 29 THz.

PubMed

Daussy, C; Ducos, F; Rovera, G D; Acef, O

2000-01-01

In this paper, we report on the metrological capabilities of CO (2)/OsO(4) optical frequency standards operating around 29 THz. Those frequency standards are currently involved in various fields, such as frequency metrology, high resolution spectroscopy, and Rydberg constant measurements. The most impressive features of the standards lies in the 10(-15) level frequency stability allied to a long-term reproducibility (1 yr) of 1.3x10 (-13).

Time-domain terahertz spectroscopy and applications on drugs and explosives

NASA Astrophysics Data System (ADS)

Fan, W. H.; Zhao, W.; Cheng, G. H.; Burnett, A. D.; Upadhya, P. C.; Cunningham, J. E.; Linfield, E. H.; Davies, A. G.

2008-03-01

Many materials of interest to the forensic and security services, such as explosives, drugs and biological agents, exhibit characteristic spectral features in the terahertz (THz) frequency range. These spectral features originate from inter-molecular interactions, involving collective motions of molecules. Broadband THz time-domain spectroscopy (THz-TDS) system have been used to analyze a number of drugs-of-abuse and explosives that are of interest to the forensic and security services. These samples ranged from crystalline powders, pressed into pellets, to thin sheets of plastic explosives, and all being measured in transmission geometry in the frequency range 0.1 - 8 THz. To well understand the nature of the observed spectral features and the effects of thermal broadening on these far-infrared signatures, temperature-dependent THz-TDS measurements have also been performed at temperatures as low as 4 K, especially for two types of cocaine. Well-resolved low-frequency absorption peaks were observed in the frequency range 0.1 - 3 THz with high resolution. Some of absorption peaks were found clearly to become more intense and shift to higher frequencies as the temperature was reduced. The results confirm that the low-frequency collective modes are highly sensitive to the structural and spatial arrangement of molecules. Furthermore, a number of common postal packaging materials made from paper, cardboard, even several types of plastic, have been tested with drug sample to assess the ability of THz-TDS in a hostile detection environment.

Agonistic sounds in the skunk clownfish Amphiprion akallopisos: size-related variation in acoustic features.

PubMed

Colleye, O; Frederich, B; Vandewalle, P; Casadevall, M; Parmentier, E

2009-09-01

Fourteen individuals of the skunk clownfish Amphiprion akallopisos of different sizes and of different sexual status (non-breeder, male or female) were analysed for four acoustic features. Dominant frequency and pulse duration were highly correlated with standard length (r = 0.97), and were not related to sex. Both the dominant frequency and pulse duration were signals conveying information related to the size of the emitter, which implies that these sound characteristics could be useful in assessing size of conspecifics.

Frequency-Swept Integrated Solid Effect.

PubMed

Can, Thach V; Weber, Ralph T; Walish, Joseph J; Swager, Timothy M; Griffin, Robert G

2017-06-06

The efficiency of continuous wave dynamic nuclear polarization (DNP) experiments decreases at the high magnetic fields used in contemporary high-resolution NMR applications. To recover the expected signal enhancements from DNP, we explored time domain experiments such as NOVEL which matches the electron Rabi frequency to the nuclear Larmor frequency to mediate polarization transfer. However, satisfying this matching condition at high frequencies is technically demanding. As an alternative we report here frequency-swept integrated solid effect (FS-ISE) experiments that allow low power sweeps of the exciting microwave frequencies to constructively integrate the negative and positive polarizations of the solid effect, thereby producing a polarization efficiency comparable to (±10 % difference) NOVEL. Finally, the microwave frequency modulation results in field profiles that exhibit new features that we coin the "stretched" solid effect. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Spatial Frequency Account of the Detriment that Local Processing of Navon Letters Has on Face Recognition

ERIC Educational Resources Information Center

Hills, Peter J.; Lewis, Michael B.

2009-01-01

Five minutes of processing the local features of a Navon letter causes a detriment in subsequent face-recognition performance (Macrae & Lewis, 2002). We hypothesize a perceptual after effect explanation of this effect in which face recognition is less accurate after adapting to high-spatial frequencies at high contrasts. Five experiments were…

[EEG features during olfactory stimulation in drug dependence persons].

PubMed

Batukhtina, E I; Nevidimova, T I; Vetlugina, T P; Kokorina, N P; Bokhan, N A

2013-01-01

Power spectra analysis EEG was used for baseline interval and during olfactory stimulation in drug dependence and healthy persons. Intergroup differences of EEG spectra were related with enhancement of cortex biopotential power in narcological patients at parietal and temporal sites. Interhemispheres features of frequency bands contribution in EEG spectra were identified. Increased biopotential power in drug dependence persons was observed at left temporal hemisphere in high-frequency bands in baseline interval and during olfactory stimulation. Increased power of alpha activity was typical for right temporal hemisphere in narcological patients as compare to healthy persons. Detected neurophysiological patterns may be related with psychological and behavioral features of addictive disorders.

Advanced RF and microwave functions based on an integrated optical frequency comb source.

PubMed

Xu, Xingyuan; Wu, Jiayang; Nguyen, Thach G; Shoeiby, Mehrdad; Chu, Sai T; Little, Brent E; Morandotti, Roberto; Mitchell, Arnan; Moss, David J

2018-02-05

We demonstrate advanced transversal radio frequency (RF) and microwave functions based on a Kerr optical comb source generated by an integrated micro-ring resonator. We achieve extremely high performance for an optical true time delay aimed at tunable phased array antenna applications, as well as reconfigurable microwave photonic filters. Our results agree well with theory. We show that our true time delay would yield a phased array antenna with features that include high angular resolution and a wide range of beam steering angles, while the microwave photonic filters feature high Q factors, wideband tunability, and highly reconfigurable filtering shapes. These results show that our approach is a competitive solution to implementing reconfigurable, high performance and potentially low cost RF and microwave signal processing functions for applications including radar and communication systems.

Fault diagnosis for analog circuits utilizing time-frequency features and improved VVRKFA

NASA Astrophysics Data System (ADS)

He, Wei; He, Yigang; Luo, Qiwu; Zhang, Chaolong

2018-04-01

This paper proposes a novel scheme for analog circuit fault diagnosis utilizing features extracted from the time-frequency representations of signals and an improved vector-valued regularized kernel function approximation (VVRKFA). First, the cross-wavelet transform is employed to yield the energy-phase distribution of the fault signals over the time and frequency domain. Since the distribution is high-dimensional, a supervised dimensionality reduction technique—the bilateral 2D linear discriminant analysis—is applied to build a concise feature set from the distributions. Finally, VVRKFA is utilized to locate the fault. In order to improve the classification performance, the quantum-behaved particle swarm optimization technique is employed to gradually tune the learning parameter of the VVRKFA classifier. The experimental results for the analog circuit faults classification have demonstrated that the proposed diagnosis scheme has an advantage over other approaches.

Effects of excitation frequency on high-order terahertz sideband generation in semiconductors

NASA Astrophysics Data System (ADS)

Xie, Xiao-Tao; Zhu, Bang-Fen; Liu, Ren-Bao

2013-10-01

We theoretically investigate the effects of the excitation frequency on the plateau of high-order terahertz sideband generation (HSG) in semiconductors driven by intense terahertz (THz) fields. We find that the plateau of the sideband spectrum strongly depends on the detuning between the near-infrared laser field and the band gap. We use the quantum trajectory theory (three-step model) to understand the HSG. In the three-step model, an electron-hole pair is first excited by a weak laser, then driven by the strong THz field, and finally recombined to emit a photon with energy gain. When the laser is tuned below the band gap (negative detuning), the electron-hole generation is a virtual process that requires quantum tunneling to occur. When the energy gained by the electron-hole pair from the THz field is less than 3.17 times the ponderomotive energy (Up), the electron and the hole can be driven to the same position and recombined without quantum tunneling, so that the HSG will have large probability amplitude. This leads to a plateau feature of the HSG spectrum with a high-frequency cutoff at about 3.17Up above the band gap. Such a plateau feature is similar to the case of high-order harmonics generation in atoms where electrons have to overcome the binding energy to escape the atomic core. A particularly interesting excitation condition in HSG is that the laser can be tuned above the band gap (positive detuning), corresponding to the unphysical ‘negative’ binding energy in atoms for high-order harmonic generation. Now the electron-hole pair is generated by real excitation, but the recombination process can be real or virtual depending on the energy gained from the THz field, which determines the plateau feature in HSG. Both the numerical calculation and the quantum trajectory analysis reveal that for positive detuning, the HSG plateau cutoff depends on the frequency of the excitation laser. In particular, when the laser is tuned more than 3.17Up above the band gap, the HSG spectrum presents no plateau feature but instead sharp peaks near the band edge and near the excitation frequency.

Distributed acoustic cues for caller identity in macaque vocalization.

PubMed

Fukushima, Makoto; Doyle, Alex M; Mullarkey, Matthew P; Mishkin, Mortimer; Averbeck, Bruno B

2015-12-01

Individual primates can be identified by the sound of their voice. Macaques have demonstrated an ability to discern conspecific identity from a harmonically structured 'coo' call. Voice recognition presumably requires the integrated perception of multiple acoustic features. However, it is unclear how this is achieved, given considerable variability across utterances. Specifically, the extent to which information about caller identity is distributed across multiple features remains elusive. We examined these issues by recording and analysing a large sample of calls from eight macaques. Single acoustic features, including fundamental frequency, duration and Weiner entropy, were informative but unreliable for the statistical classification of caller identity. A combination of multiple features, however, allowed for highly accurate caller identification. A regularized classifier that learned to identify callers from the modulation power spectrum of calls found that specific regions of spectral-temporal modulation were informative for caller identification. These ranges are related to acoustic features such as the call's fundamental frequency and FM sweep direction. We further found that the low-frequency spectrotemporal modulation component contained an indexical cue of the caller body size. Thus, cues for caller identity are distributed across identifiable spectrotemporal components corresponding to laryngeal and supralaryngeal components of vocalizations, and the integration of those cues can enable highly reliable caller identification. Our results demonstrate a clear acoustic basis by which individual macaque vocalizations can be recognized.

Distributed acoustic cues for caller identity in macaque vocalization

PubMed Central

Doyle, Alex M.; Mullarkey, Matthew P.; Mishkin, Mortimer; Averbeck, Bruno B.

2015-01-01

Individual primates can be identified by the sound of their voice. Macaques have demonstrated an ability to discern conspecific identity from a harmonically structured ‘coo’ call. Voice recognition presumably requires the integrated perception of multiple acoustic features. However, it is unclear how this is achieved, given considerable variability across utterances. Specifically, the extent to which information about caller identity is distributed across multiple features remains elusive. We examined these issues by recording and analysing a large sample of calls from eight macaques. Single acoustic features, including fundamental frequency, duration and Weiner entropy, were informative but unreliable for the statistical classification of caller identity. A combination of multiple features, however, allowed for highly accurate caller identification. A regularized classifier that learned to identify callers from the modulation power spectrum of calls found that specific regions of spectral–temporal modulation were informative for caller identification. These ranges are related to acoustic features such as the call’s fundamental frequency and FM sweep direction. We further found that the low-frequency spectrotemporal modulation component contained an indexical cue of the caller body size. Thus, cues for caller identity are distributed across identifiable spectrotemporal components corresponding to laryngeal and supralaryngeal components of vocalizations, and the integration of those cues can enable highly reliable caller identification. Our results demonstrate a clear acoustic basis by which individual macaque vocalizations can be recognized. PMID:27019727

Contrast in Terahertz Images of Archival Documents—Part II: Influence of Topographic Features

NASA Astrophysics Data System (ADS)

Bardon, Tiphaine; May, Robert K.; Taday, Philip F.; Strlič, Matija

2017-04-01

We investigate the potential of terahertz time-domain imaging in reflection mode to reveal archival information in documents in a non-invasive way. In particular, this study explores the parameters and signal processing tools that can be used to produce well-contrasted terahertz images of topographic features commonly found in archival documents, such as indentations left by a writing tool, as well as sieve lines. While the amplitude of the waveforms at a specific time delay can provide the most contrasted and legible images of topographic features on flat paper or parchment sheets, this parameter may not be suitable for documents that have a highly irregular surface, such as water- or fire-damaged documents. For analysis of such documents, cross-correlation of the time-domain signals can instead yield images with good contrast. Analysis of the frequency-domain representation of terahertz waveforms can also provide well-contrasted images of topographic features, with improved spatial resolution when utilising high-frequency content. Finally, we point out some of the limitations of these means of analysis for extracting information relating to topographic features of interest from documents.

Is recurrence in major depressive disorder related to bipolarity and mixed features? Results from the BRIDGE-II-Mix study.

PubMed

Mazzarini, Lorenzo; Kotzalidis, Georgios D; Piacentino, Daria; Rizzato, Salvatore; Angst, Jules; Azorin, Jean-Michel; Bowden, Charles L; Mosolov, Sergey; Young, Allan H; Vieta, Eduard; Girardi, Paolo; Perugi, Giulio

2018-03-15

Current classifications separate Bipolar (BD) from Major Depressive Disorder (MDD) based on polarity rather than recurrence. We aimed to determine bipolar/mixed feature frequency in a large MDD multinational sample with (High-Rec) and without (Low-Rec) >3 recurrences, comparing the two subsamples. We measured frequency of bipolarity/hypomanic features during current depressive episodes (MDEs) in 2347 MDD patients from the BRIDGE-II-mix database, comparing High-Rec with Low-Rec. We used Bonferroni-corrected Student's t-test for continuous, and chi-squared test, for categorical variables. Logistic regression estimated the size of the association between clinical characteristics and High-Rec MDD. Compared to Low-Rec (n = 1084, 46.2%), High-Rec patients (n = 1263, 53.8%) were older, with earlier depressive onset, had more family history of BD, more atypical features, suicide attempts, hospitalisations, and treatment resistance and (hypo)manic switches when treated with antidepressants, higher comorbidity with borderline personality disorder, and more hypomanic symptoms during current MDE, resulting in higher rates of mixed depression according to both DSM-5 and research-based diagnostic (RBDC) criteria. Logistic regression showed age at first symptoms < 30 years, current MDE duration ≤ 1 month, hypomania/mania among first-degree relatives, past suicide attempts, treatment-resistance, antidepressant-induced swings, and atypical, mixed, or psychotic features during MDE to associate with High-Rec. Number of MDEs for defining recurrence was arbitrary; cross-sectionality did not allow assessment of conversion from MDD to BD. High-Rec MDD differed from Low-Rec group for several clinical/epidemiological variables, including bipolar/mixed features. Bipolarity specifier and RBDC were more sensitive than DSM-5 criteria in detecting bipolar and mixed features in MDD. Copyright © 2017. Published by Elsevier B.V.

Frequency Dependence of Single-Event Upset in Highly Advanced PowerPC Microprocessors

NASA Technical Reports Server (NTRS)

Irom, Farokh; Farmanesh, Farhad; White, Mark; Kouba, Coy K.

2006-01-01

Single-event upset effects from heavy ions were measured for Motorola silicon-on-insulator (SOI) microprocessor with 90 nm feature sizes at three frequencies of 500, 1066 and 1600 MHz. Frequency dependence of single-event upsets is discussed. The results of our studies suggest the single-event upset in registers and D-Cache tend to increase with frequency. This might have important implications for the overall single-event upset trend as technology moves toward higher frequencies.

Pulsed gas laser

DOEpatents

Anderson, Louis W.; Fitzsimmons, William A.

1978-01-01

A pulsed gas laser is constituted by Blumlein circuits wherein space metal plates function both as capacitors and transmission lines coupling high frequency oscillations to a gas filled laser tube. The tube itself is formed by spaced metal side walls which function as connections to the electrodes to provide for a high frequency, high voltage discharge in the tube to cause the gas to lase. Also shown is a spark gap switch having structural features permitting a long life.

Rectal bleeding, fecal incontinence, and high stool frequency after conformal radiotherapy for prostate cancer: Normal tissue complication probability modeling

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

Peeters, Stephanie; Hoogeman, Mischa S.; Heemsbergen, Wilma D.

2006-09-01

Purpose: To analyze whether inclusion of predisposing clinical features in the Lyman-Kutcher-Burman (LKB) normal tissue complication probability (NTCP) model improves the estimation of late gastrointestinal toxicity. Methods and Materials: This study includes 468 prostate cancer patients participating in a randomized trial comparing 68 with 78 Gy. We fitted the probability of developing late toxicity within 3 years (rectal bleeding, high stool frequency, and fecal incontinence) with the original, and a modified LKB model, in which a clinical feature (e.g., history of abdominal surgery) was taken into account by fitting subset specific TD50s. The ratio of these TD50s is the dose-modifyingmore » factor for that clinical feature. Dose distributions of anorectal (bleeding and frequency) and anal wall (fecal incontinence) were used. Results: The modified LKB model gave significantly better fits than the original LKB model. Patients with a history of abdominal surgery had a lower tolerance to radiation than did patients without previous surgery, with a dose-modifying factor of 1.1 for bleeding and of 2.5 for fecal incontinence. The dose-response curve for bleeding was approximately two times steeper than that for frequency and three times steeper than that for fecal incontinence. Conclusions: Inclusion of predisposing clinical features significantly improved the estimation of the NTCP. For patients with a history of abdominal surgery, more severe dose constraints should therefore be used during treatment plan optimization.« less

Analysis of drugs-of-abuse and explosives using terahertz time-domain and Raman spectroscopy

NASA Astrophysics Data System (ADS)

Burnett, Andrew; Fan, Wenhui; Upadhya, Prashanth; Cunningham, John; Linfield, Edmund; Davies, Giles; Edwards, Howell; Munshi, Tasnim; O'Neil, Andrew

2006-02-01

We demonstrate that, through coherent measurement of the transmitted terahertz electric fields, broadband (0.3-8THz) time-domain spectroscopy can be used to measure far-infrared vibrational modes of a range of illegal drugs and high explosives that are of interest to the forensic and security services. Our results show that these absorption features are highly sensitive to the structural and spatial arrangement of the molecules. Terahertz frequency spectra are also compared with high-resolution low-frequency Raman spectra to assist in understanding the low frequency inter- and intra-molecular vibrational modes of the molecules.

Automatic Modulation Classification of Common Communication and Pulse Compression Radar Waveforms using Cyclic Features

DTIC Science & Technology

2013-03-01

intermediate frequency LFM linear frequency modulation MAP maximum a posteriori MATLAB® matrix laboratory ML maximun likelihood OFDM orthogonal frequency...spectrum, frequency hopping, and orthogonal frequency division multiplexing ( OFDM ) modulations. Feature analysis would be a good research thrust to...determine feature relevance and decide if removing any features improves performance. Also, extending the system for simulations using a MIMO receiver or

Toward a Mobility-Driven Architecture for Multimodal Underwater Networking

DTIC Science & Technology

2017-02-01

applications. By equipping AUVs with short-range, high -bandwidth underwater wireless communications , which feature lower energy-per-bit cost than acoustic...protocols. They suffer from significant transmission path losses at high frequencies , long propagation delays, low and distance-dependent bandwidth, time...of data preprocessing, data compression, and either tethering to a surface buoy able to use radio frequency (RF) communications or using undersea

Low-power coprocessor for Haar-like feature extraction with pixel-based pipelined architecture

NASA Astrophysics Data System (ADS)

Luo, Aiwen; An, Fengwei; Fujita, Yuki; Zhang, Xiangyu; Chen, Lei; Jürgen Mattausch, Hans

2017-04-01

Intelligent analysis of image and video data requires image-feature extraction as an important processing capability for machine-vision realization. A coprocessor with pixel-based pipeline (CFEPP) architecture is developed for real-time Haar-like cell-based feature extraction. Synchronization with the image sensor’s pixel frequency and immediate usage of each input pixel for the feature-construction process avoids the dependence on memory-intensive conventional strategies like integral-image construction or frame buffers. One 180 nm CMOS prototype can extract the 1680-dimensional Haar-like feature vectors, applied in the speeded up robust features (SURF) scheme, using an on-chip memory of only 96 kb (kilobit). Additionally, a low power dissipation of only 43.45 mW at 1.8 V supply voltage is achieved during VGA video procession at 120 MHz frequency with more than 325 fps. The Haar-like feature-extraction coprocessor is further evaluated by the practical application of vehicle recognition, achieving the expected high accuracy which is comparable to previous work.

Research of the Electron Cyclotron Emission with Vortex Property excited by high power high frequency Gyrotron

NASA Astrophysics Data System (ADS)

Goto, Yuki; Kubo, Shin; Tsujimura, Tohru; Takubo, Hidenori

2017-10-01

Recently, it has been shown that the radiation from a single electron in cyclotron motion has vortex property. Although the cyclotron emission exists universally in nature, the vortex property has not been featured because this property is normally cancelled out due to the randomness in gyro-phase of electrons and the development of detection of the vortex property has not been well motivated. In this research, we are developing a method to generate the vortex radiation from electrons in cyclotron motion with controlled gyro-phase. Electron that rotates around the uniform static magnetic field is accelerated by right-hand circular polarized (RHCP) radiation resonantly when the cyclotron frequency coincides with the applied RHCP radiation frequency. A large number of electrons can be coherently accelerated in gyro-phase by a RHCP high power radiation so that these electrons can radiate coherent emission with vortex feature. We will show that vortex radiation created by purely rotating electrons for the first time.

The Monitoring Case of Ground-Based Synthetic Aperture Radar with Frequency Modulated Continuous Wave System

NASA Astrophysics Data System (ADS)

Zhang, H. Y.; Zhai, Q. P.; Chen, L.; Liu, Y. J.; Zhou, K. Q.; Wang, Y. S.; Dou, Y. D.

2017-09-01

The features of the landslide geological disaster are wide distribution, variety, high frequency, high intensity, destructive and so on. It has become a natural disaster with harmful and wide range of influence. The technology of ground-based synthetic aperture radar is a novel deformation monitoring technology developed in recent years. The features of the technology are large monitoring area, high accuracy, long distance without contact and so on. In this paper, fast ground-based synthetic aperture radar (Fast-GBSAR) based on frequency modulated continuous wave (FMCW) system is used to collect the data of Ma Liuzui landslide in Chongqing. The device can reduce the atmospheric errors caused by rapidly changing environment. The landslide deformation can be monitored in severe weather conditions (for example, fog) by Fast-GBSAR with acquisition speed up to 5 seconds per time. The data of Ma Liuzui landslide in Chongqing are analyzed in this paper. The result verifies that the device can monitor landslide deformation under severe weather conditions.

[The Value of High Frequency Color Doppler Ultrasonography in the Diagnosis of Solid Skin Tumorsa-a Preliminary Study].

PubMed

Zhong, Lin; Tang, Yuan-Jiao; Yang, Yu-Jia; Qiu, Li

2017-01-01

To explore the value of high frequency color doppler ultrasonography in differentiating benign and malignant skin solid tumors. Clinical and ultrasonic data of cutaneous solid tumors confirmed by pathology in our hospital were collected. The differences in clinical and sonographic features between benign and malignant tumors were statistically analyzed. A total of 512 patients, involving 527 cases of skin solid tumors, were enrolled in this study. The ultrasonic detected 99.43% of the cases, with 99.02% accuracy in locating the lesions. The benign and malignant tumors showed differences in patient age, location, multiple occurance, location and depth, surface skin condition, tumor size, echo, morphology, uniformity, calcification, blood flow status, tumor rear area and peripheral echo, and pathological requests ( P <0.05). High frequency ultrasound has excellent detection rate of skin tumors, which can locate invasion depth of skin accurately. Benign and malignant skin tumors show differences in a number of clinical and ultrasound features.

Frequency optimization in the eddy current test for high purity niobium

NASA Astrophysics Data System (ADS)

Joung, Mijoung; Jung, Yoochul; Kim, Hyungjin

2017-01-01

The eddy current test (ECT) is frequently used as a non-destructive method to check for the defects of high purity niobium (RRR300, Residual Resistivity Ratio) in a superconducting radio frequency (SRF) cavity. Determining an optimal frequency corresponding to specific material properties and probe specification is a very important step. The ECT experiments for high purity Nb were performed to determine the optimal frequency using the standard sample of high purity Nb having artificial defects. The target depth was considered with the treatment step that the niobium receives as the SRF cavity material. The results were analysed via the selectivity that led to a specific result, depending on the size of the defects. According to the results, the optimal frequency was determined to be 200 kHz, and a few features of the ECT for the high purity Nb were observed.

Surface electromyography based muscle fatigue detection using high-resolution time-frequency methods and machine learning algorithms.

PubMed

Karthick, P A; Ghosh, Diptasree Maitra; Ramakrishnan, S

2018-02-01

Surface electromyography (sEMG) based muscle fatigue research is widely preferred in sports science and occupational/rehabilitation studies due to its noninvasiveness. However, these signals are complex, multicomponent and highly nonstationary with large inter-subject variations, particularly during dynamic contractions. Hence, time-frequency based machine learning methodologies can improve the design of automated system for these signals. In this work, the analysis based on high-resolution time-frequency methods, namely, Stockwell transform (S-transform), B-distribution (BD) and extended modified B-distribution (EMBD) are proposed to differentiate the dynamic muscle nonfatigue and fatigue conditions. The nonfatigue and fatigue segments of sEMG signals recorded from the biceps brachii of 52 healthy volunteers are preprocessed and subjected to S-transform, BD and EMBD. Twelve features are extracted from each method and prominent features are selected using genetic algorithm (GA) and binary particle swarm optimization (BPSO). Five machine learning algorithms, namely, naïve Bayes, support vector machine (SVM) of polynomial and radial basis kernel, random forest and rotation forests are used for the classification. The results show that all the proposed time-frequency distributions (TFDs) are able to show the nonstationary variations of sEMG signals. Most of the features exhibit statistically significant difference in the muscle fatigue and nonfatigue conditions. The maximum number of features (66%) is reduced by GA and BPSO for EMBD and BD-TFD respectively. The combination of EMBD- polynomial kernel based SVM is found to be most accurate (91% accuracy) in classifying the conditions with the features selected using GA. The proposed methods are found to be capable of handling the nonstationary and multicomponent variations of sEMG signals recorded in dynamic fatiguing contractions. Particularly, the combination of EMBD- polynomial kernel based SVM could be used to detect the dynamic muscle fatigue conditions. Copyright © 2017 Elsevier B.V. All rights reserved.

Signal processing for the profoundly deaf.

PubMed

Boothyroyd, A

1990-01-01

Profound deafness, defined here as a hearing loss in excess of 90 dB, is characterized by high thresholds, reduced hearing range in the intensity and frequency domains, and poor resolution in the frequency and time domains. The high thresholds call for hearing aids with unusually high gains or remote microphones that can be placed close to the signal source. The former option creates acoustic feedback problems for which digital signal processing may yet offer solutions. The latter option calls for carrier wave technology that is already available. The reduced frequency and intensity ranges would appear to call for frequency and/or amplitude compression. It might also be argued, however, that any attempts to compress the acoustic signal into the limited hearing range of the profoundly deaf will be counterproductive because of poor frequency and time resolution, especially when the signal is present in noise. In experiments with a 2-channel compression system, only 1 of 9 subjects showed an improvement of perception with the introduction of fast-release (20 ms) compression. The other 8 experienced no benefit or a slight deterioration of performance. These results support the concept of providing the profoundly deaf with simpler, rather than more complex, patterns, perhaps through the use of feature extraction hearing aids. Data from users of cochlear implants already employing feature extraction techniques also support this concept.

Mechanical monolithic compact sensors for real-time linear and angular broadband low frequency monitoring and control of spacecrafts and satellites

NASA Astrophysics Data System (ADS)

Barone, F.; Giordano, G.

2017-09-01

In this paper we describe the characteristics and performances of a monolithic sensor designed for low frequency motion measurement of spacecrafts and satellites, whose mechanics is based on the UNISA Folded Pendulum. The latter, developed for ground-based applications, exhibits unique features (compactness, lightness, scalability, low resonance frequency and high quality factor), consequence of the action of the gravitational force on its inertial mass. In this paper we introduce and discuss the general methodology used to extend the application of ground-based folded pendulums to space, also in total absence of gravity, still keeping all their peculiar features and characteristics.

Broadband and high-efficiency vortex beam generator based on a hybrid helix array.

PubMed

Fang, Chaoqun; Wu, Chao; Gong, Zhijie; Zhao, Song; Sun, Anqi; Wei, Zeyong; Li, Hongqiang

2018-04-01

The vortex beam which carries the orbital angular momentum has versatile applications, such as high-resolution imaging, optical communications, and particle manipulation. Generating vortex beams with the Pancharatnam-Berry (PB) phase has drawn considerable attention for its unique spin-to-orbital conversion features. Despite the PB phase being frequency independent, an optical element with broadband high-efficiency circular polarization conversion feature is still needed for the broadband high-efficiency vortex beam generation. In this work, a broadband and high-efficiency vortex beam generator based on the PB phase is built with a hybrid helix array. Such devices can generate vortex beams with arbitrary topological charge. Moreover, vortex beams with opposite topological charge can be generated with an opposite handedness incident beam that propagates backward. The measured efficiency of our device is above 65% for a wide frequency range, with the relative bandwidth of 46.5%.

Interpreting Quasi-Thermal Effects in Ultrafast Spectroscopy of Hydrogen-Bonded Systems.

PubMed

Stingel, Ashley M; Petersen, Poul B

2018-03-15

Vibrational excitation of molecules in the condensed phase relaxes through vibrational modes of decreasing energy to ultimately generate an equilibrium state in which the energy is distributed among low-frequency modes. In ultrafast vibrational spectroscopy, changes in the vibrational features of hydrogen-bonded NH and OH stretch modes are typically observed to persist long after these high-frequency vibrations have relaxed. Due to the resemblance to the spectral changes caused by heating the sample, these features are typically described as arising from a hot ground state. However, these spectral features appear on ultrafast time scales that are much too fast to result from a true thermal state, and significant differences between the thermal difference spectrum and the induced quasi-thermal changes in ultrafast spectroscopy are often observed. Here, we examine and directly compare the thermal and quasi-thermal responses of the hydrogen-bonded homodimer of 7-azaindole with temperature-dependent FTIR spectroscopy and ultrafast mid-IR continuum spectroscopy. We find that the thermal difference spectra contain contributions from both dissociation of the hydrogen bonds and from frequency shifts due to changes in the thermal population of low-frequency modes. The transient spectra in ultrafast vibrational spectroscopy are also found to contain two contributions: initial frequency shifts over 2.3 ± 0.11 ps associated with equilibration of the initial excitation, and frequency shifts associated with the excitation of several fingerprint modes, which decay over 21.8 ± 0.11 ps, giving rise to a quasi-thermal response caused by a distribution of fingerprint modes being excited within the sample ensemble. This resembles the thermal frequency shifts due to population changes of low-frequency modes, but not the overall thermal spectrum, which is dominated by features caused by dimer dissociation. These findings provide insight into the changes in the vibrational spectrum from different origins and are important for assigning, analyzing, and comparing features in thermal and ultrafast vibrational spectroscopy of hydrogen-bonded complexes.

Feature Selection Method Based on Neighborhood Relationships: Applications in EEG Signal Identification and Chinese Character Recognition

PubMed Central

Zhao, Yu-Xiang; Chou, Chien-Hsing

2016-01-01

In this study, a new feature selection algorithm, the neighborhood-relationship feature selection (NRFS) algorithm, is proposed for identifying rat electroencephalogram signals and recognizing Chinese characters. In these two applications, dependent relationships exist among the feature vectors and their neighboring feature vectors. Therefore, the proposed NRFS algorithm was designed for solving this problem. By applying the NRFS algorithm, unselected feature vectors have a high priority of being added into the feature subset if the neighboring feature vectors have been selected. In addition, selected feature vectors have a high priority of being eliminated if the neighboring feature vectors are not selected. In the experiments conducted in this study, the NRFS algorithm was compared with two feature algorithms. The experimental results indicated that the NRFS algorithm can extract the crucial frequency bands for identifying rat vigilance states and identifying crucial character regions for recognizing Chinese characters. PMID:27314346

The effects of behavioral and structural assumptions in artificial stock market

NASA Astrophysics Data System (ADS)

Liu, Xinghua; Gregor, Shirley; Yang, Jianmei

2008-04-01

Recent literature has developed the conjecture that important statistical features of stock price series, such as the fat tails phenomenon, may depend mainly on the market microstructure. This conjecture motivated us to investigate the roles of both the market microstructure and agent behavior with respect to high-frequency returns and daily returns. We developed two simple models to investigate this issue. The first one is a stochastic model with a clearing house microstructure and a population of zero-intelligence agents. The second one has more behavioral assumptions based on Minority Game and also has a clearing house microstructure. With the first model we found that a characteristic of the clearing house microstructure, namely the clearing frequency, can explain fat tail, excess volatility and autocorrelation phenomena of high-frequency returns. However, this feature does not cause the same phenomena in daily returns. So the Stylized Facts of daily returns depend mainly on the agents’ behavior. With the second model we investigated the effects of behavioral assumptions on daily returns. Our study implicates that the aspects which are responsible for generating the stylized facts of high-frequency returns and daily returns are different.

Nanoconstriction spin-Hall oscillator with perpendicular magnetic anisotropy

NASA Astrophysics Data System (ADS)

Divinskiy, B.; Demidov, V. E.; Kozhanov, A.; Rinkevich, A. B.; Demokritov, S. O.; Urazhdin, S.

2017-07-01

We experimentally study spin-Hall nano-oscillators based on [Co/Ni] multilayers with perpendicular magnetic anisotropy. We show that these devices exhibit single-frequency auto-oscillations at current densities comparable to those for in-plane magnetized oscillators. The demonstrated oscillators exhibit large magnetization precession amplitudes, and their oscillation frequency is highly tunable by the electric current. These features make them promising for applications in high-speed integrated microwave circuits.

Versatile mid-infrared frequency-comb referenced sub-Doppler spectrometer

NASA Astrophysics Data System (ADS)

Gambetta, A.; Vicentini, E.; Coluccelli, N.; Wang, Y.; Fernandez, T. T.; Maddaloni, P.; De Natale, P.; Castrillo, A.; Gianfrani, L.; Laporta, P.; Galzerano, G.

2018-04-01

We present a mid-IR high-precision spectrometer capable of performing accurate Doppler-free measurements with absolute calibration of the optical axis and high signal-to-noise ratio. The system is based on a widely tunable mid-IR offset-free frequency comb and a Quantum-Cascade-Laser (QCL). The QCL emission frequency is offset locked to one of the comb teeth to provide absolute-frequency calibration, spectral-narrowing, and accurate fine frequency tuning. Both the comb repetition frequency and QCL-comb offset frequency can be modulated to provide, respectively, slow- and fast-frequency-calibrated scanning capabilities. The characterisation of the spectrometer is demonstrated by recording sub-Doppler saturated absorption features of the CHF3 molecule at around 8.6 μm with a maximum signal-to-noise ratio of ˜7 × 103 in 10 s integration time, frequency-resolution of 160 kHz, and accuracy of less than 10 kHz.

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.

Impact of Hearing Aid Technology on Outcomes in Daily Life III: Localization.

PubMed

Johnson, Jani A; Xu, Jingjing; Cox, Robyn M

Compared to basic-feature hearing aids, premium-feature hearing aids have more advanced technologies and sophisticated features. The objective of this study was to explore the difference between premium-feature and basic-feature hearing aids in horizontal sound localization in both laboratory and daily life environments. We hypothesized that premium-feature hearing aids would yield better localization performance than basic-feature hearing aids. Exemplars of premium-feature and basic-feature hearing aids from two major manufacturers were evaluated. Forty-five older adults (mean age 70.3 years) with essentially symmetrical mild to moderate sensorineural hearing loss were bilaterally fitted with each of the four pairs of hearing aids. Each pair of hearing aids was worn during a 4-week field trial and then evaluated using laboratory localization tests and a standardized questionnaire. Laboratory localization tests were conducted in a sound-treated room with a 360°, 24-loudspeaker array. Test stimuli were high frequency and low frequency filtered short sentences. The localization test in quiet was designed to assess the accuracy of front/back localization, while the localization test in noise was designed to assess the accuracy of locating sound sources throughout a 360° azimuth in the horizontal plane. Laboratory data showed that unaided localization was not significantly different from aided localization when all hearing aids were combined. Questionnaire data showed that aided localization was significantly better than unaided localization in everyday situations. Regarding the difference between premium-feature and basic-feature hearing aids, laboratory data showed that, overall, the premium-feature hearing aids yielded more accurate localization than the basic-feature hearing aids when high-frequency stimuli were used, and the listening environment was quiet. Otherwise, the premium-feature and basic-feature hearing aids yielded essentially the same performance in other laboratory tests and in daily life. The findings were consistent for both manufacturers. Laboratory tests for two of six major manufacturers showed that premium-feature hearing aids yielded better localization performance than basic-feature hearing aids in one out of four laboratory conditions. There was no difference between the two feature levels in self-reported everyday localization. Effectiveness research with different hearing aid technologies is necessary, and more research with other manufacturers' products is needed. Furthermore, these results confirm previous observations that research findings in laboratory conditions might not translate to everyday life.

High-fidelity numerical simulation of the flow field around a NACA-0012 aerofoil from the laminar separation bubble to a full stall

NASA Astrophysics Data System (ADS)

ElJack, Eltayeb

2017-05-01

In the present work, large eddy simulations of the flow field around a NACA-0012 aerofoil near stall conditions are performed at a Reynolds number of 5 × 104, Mach number of 0.4, and at various angles of attack. The results show the following: at relatively low angles of attack, the bubble is present and intact; at moderate angles of attack, the laminar separation bubble bursts and generates a global low-frequency flow oscillation; and at relatively high angles of attack, the laminar separation bubble becomes an open bubble that leads the aerofoil into a full stall. Time histories of the aerodynamic coefficients showed that the low-frequency oscillation phenomenon and its associated physics are indeed captured in the simulations. The aerodynamic coefficients compared to previous and recent experimental data with acceptable accuracy. Spectral analysis identified a dominant low-frequency mode featuring the periodic separation and reattachment of the flow field. At angles of attack α ≤ 9.3°, the low-frequency mode featured bubble shedding rather than bubble bursting and reformation. The underlying mechanism behind the quasi-periodic self-sustained low-frequency flow oscillation is discussed in detail.

High-throughput formation and control of monodisperse liquid crystals droplets driven by an alternating current electric field in a microfluidic device

NASA Astrophysics Data System (ADS)

Belloul, M.; Bartolo, J.-F.; Ziraoui, B.; Coldren, F.; Taly, V.; El Abed, A. I.

2013-07-01

We investigate the effect of an applied ac high voltage on a confined stable nematic liquid crystal (LC) in a microfluidic device and show that this actuation leads to the formation of highly monodisperse microdroplets with an unexpected constant mean size over a large interval of the forcing frequency F and with a droplets production frequency f ≃2F. We show also that despite the nonlinear feature of the droplets formation mechanism, droplets size, and size distribution are governed simply by the LC flow rate Qd and the forcing frequency F.

Feature extraction for document text using Latent Dirichlet Allocation

NASA Astrophysics Data System (ADS)

Prihatini, P. M.; Suryawan, I. K.; Mandia, IN

2018-01-01

Feature extraction is one of stages in the information retrieval system that used to extract the unique feature values of a text document. The process of feature extraction can be done by several methods, one of which is Latent Dirichlet Allocation. However, researches related to text feature extraction using Latent Dirichlet Allocation method are rarely found for Indonesian text. Therefore, through this research, a text feature extraction will be implemented for Indonesian text. The research method consists of data acquisition, text pre-processing, initialization, topic sampling and evaluation. The evaluation is done by comparing Precision, Recall and F-Measure value between Latent Dirichlet Allocation and Term Frequency Inverse Document Frequency KMeans which commonly used for feature extraction. The evaluation results show that Precision, Recall and F-Measure value of Latent Dirichlet Allocation method is higher than Term Frequency Inverse Document Frequency KMeans method. This shows that Latent Dirichlet Allocation method is able to extract features and cluster Indonesian text better than Term Frequency Inverse Document Frequency KMeans method.

The high frequency characteristics of laser reflection and visible light during solid state disk laser welding

NASA Astrophysics Data System (ADS)

Gao, Xiangdong; You, Deyong; Katayama, Seiji

2015-07-01

Optical properties are related to weld quality during laser welding. Visible light radiation generated from optical-induced plasma and laser reflection is considered a key element reflecting weld quality. An in-depth analysis of the high-frequency component of optical signals is conducted. A combination of a photoelectric sensor and an optical filter helped to obtain visible light reflection and laser reflection in the welding process. Two groups of optical signals were sampled at a high sampling rate (250 kHz) using an oscilloscope. Frequencies in the ranges 1-10 kHz and 10-125 kHz were investigated respectively. Experimental results showed that there was an obvious correlation between the high-frequency signal and the laser power, while the high-frequency signal was not sensitive to changes in welding speed. In particular, when the defocus position was changed, only a high frequency of the visible light signal was observed, while the high frequency of the laser reflection signal remained unchanged. The basic correlation between optical features and welding status during the laser welding process is specified, which helps to provide a new research focus for investigating the stability of welding status.

Localized mold heating with the aid of selective induction for injection molding of high aspect ratio micro-features

NASA Astrophysics Data System (ADS)

Park, Keun; Lee, Sang-Ik

2010-03-01

High-frequency induction is an efficient, non-contact means of heating the surface of an injection mold through electromagnetic induction. Because the procedure allows for the rapid heating and cooling of mold surfaces, it has been recently applied to the injection molding of thin-walled parts or micro/nano-structures. The present study proposes a localized heating method involving the selective use of mold materials to enhance the heating efficiency of high-frequency induction heating. For localized induction heating, a composite injection mold of ferromagnetic material and paramagnetic material is used. The feasibility of the proposed heating method is investigated through numerical analyses in terms of its heating efficiency for localized mold surfaces and in terms of the structural safety of the composite mold. The moldability of high aspect ratio micro-features is then experimentally compared under a variety of induction heating conditions.

High frequency vibration characteristics of electric wheel system under in-wheel motor torque ripple

NASA Astrophysics Data System (ADS)

Mao, Yu; Zuo, Shuguang; Wu, Xudong; Duan, Xianglei

2017-07-01

With the introduction of in-wheel motor, the electric wheel system encounters new vibration problems brought by motor torque ripple excitation. In order to analyze new vibration characteristics of electric wheel system, torque ripple of in-wheel motor based on motor module and vector control system is primarily analyzed, and frequency/order features of the torque ripple are discussed. Then quarter vehicle-electric wheel system (QV-EWS) dynamics model based on the rigid ring tire assumption is established and the main parameters of the model are identified according to tire free modal test. Modal characteristics of the model are further analyzed. The analysis indicates that torque excitation of in-wheel motor is prone to arouse horizontal vibration, in which in-phase rotational, anti-phase rotational and horizontal translational modes of electric wheel system mainly participate. Based on the model, vibration responses of the QV-EWS under torque ripple are simulated. The results show that unlike vertical low frequency (lower than 20 Hz) vibration excited by road roughness, broadband torque ripple will arouse horizontal high frequency (50-100 Hz) vibration of electric wheel system due to participation of the three aforementioned modes. To verify the theoretical analysis, the bench experiment of electric wheel system is conducted and vibration responses are acquired. The experiment demonstrates the high frequency vibration phenomenon of electric wheel system and the measured order features as well as main resonant frequencies agree with simulation results. Through theoretical modeling, analysis and experiments this paper reveals and explains the high frequency vibration characteristics of electric wheel system, providing references for the dynamic analysis, optimal design of QV-EWS.

A search for two types of transverse excitations in liquid polyvalent metals at ambient pressure: An ab initio molecular dynamics study of collective excitations in liquid Al, Tl and Ni

NASA Astrophysics Data System (ADS)

Bryk, Taras; Demchuk, Taras; Jakse, Noël; Wax, Jean-François

2018-02-01

Recent findings of pressure-induced emergence of unusual high-frequency contribution to transverse current spectral functions in several simple liquid metals at high pressures raised a question whether similar features can be observed in liquid metals at ambient conditions. We report here analysis of ab initio molecular dynamics-derived longitudinal (L) and transverse (T) current spectral functions and corresponding dispersions of collective excitations in liquid polyvalent metals Al, Tl, Ni. We have not found evidences of the second branch of high-frequency transverse modes in liquid Al and Ni, while in the case of liquid Tl they were clearly present in transverse dynamics. The vibrational density of states for liquid Tl has a pronounced high-frequency shoulder, which is located right in the frequency range of the second high-frequency transverse branch, while for liquid Al and Ni the vibrational density of states has only a weak indication of possible high-frequency shoulder. The origin of specific behavior of transverse excitations in liquid Tl is discussed.

Gear fault diagnosis based on the structured sparsity time-frequency analysis

NASA Astrophysics Data System (ADS)

Sun, Ruobin; Yang, Zhibo; Chen, Xuefeng; Tian, Shaohua; Xie, Yong

2018-03-01

Over the last decade, sparse representation has become a powerful paradigm in mechanical fault diagnosis due to its excellent capability and the high flexibility for complex signal description. The structured sparsity time-frequency analysis (SSTFA) is a novel signal processing method, which utilizes mixed-norm priors on time-frequency coefficients to obtain a fine match for the structure of signals. In order to extract the transient feature from gear vibration signals, a gear fault diagnosis method based on SSTFA is proposed in this work. The steady modulation components and impulsive components of the defective gear vibration signals can be extracted simultaneously by choosing different time-frequency neighborhood and generalized thresholding operators. Besides, the time-frequency distribution with high resolution is obtained by piling different components in the same diagram. The diagnostic conclusion can be made according to the envelope spectrum of the impulsive components or by the periodicity of impulses. The effectiveness of the method is verified by numerical simulations, and the vibration signals registered from a gearbox fault simulator and a wind turbine. To validate the efficiency of the presented methodology, comparisons are made among some state-of-the-art vibration separation methods and the traditional time-frequency analysis methods. The comparisons show that the proposed method possesses advantages in separating feature signals under strong noise and accounting for the inner time-frequency structure of the gear vibration signals.

Comparing the Lexical Features of EAP Students' Essays by Prompt and Rating

ERIC Educational Resources Information Center

Lavallée, Maxime; McDonough, Kim

2015-01-01

Previous research has shown that high frequency lexical items, such as AWL words and formulaic expressions, may differentiate between texts written by expert and novice writers (Chen & Baker, 2010; Hancioglu, 2009), and that lexical features related to breadth, depth, and accessibility differentiate among texts from L2 writers of different…

Image features dependant correlation-weighting function for efficient PRNU based source camera identification.

PubMed

Tiwari, Mayank; Gupta, Bhupendra

2018-04-01

For source camera identification (SCI), photo response non-uniformity (PRNU) has been widely used as the fingerprint of the camera. The PRNU is extracted from the image by applying a de-noising filter then taking the difference between the original image and the de-noised image. However, it is observed that intensity-based features and high-frequency details (edges and texture) of the image, effect quality of the extracted PRNU. This effects correlation calculation and creates problems in SCI. For solving this problem, we propose a weighting function based on image features. We have experimentally identified image features (intensity and high-frequency contents) effect on the estimated PRNU, and then develop a weighting function which gives higher weights to image regions which give reliable PRNU and at the same point it gives comparatively less weights to the image regions which do not give reliable PRNU. Experimental results show that the proposed weighting function is able to improve the accuracy of SCI up to a great extent. Copyright © 2018 Elsevier B.V. All rights reserved.

Voice characteristics in the progression of Parkinson's disease.

PubMed

Holmes, R J; Oates, J M; Phyland, D J; Hughes, A J

2000-01-01

This study examined the acoustic and perceptual voice characteristics of patients with Parkinson's disease according to disease severity. The perceptual and acoustic voice characteristics of 30 patients with early stage PD and 30 patients with later stage PD were compared with data from 30 normal control subjects. Voice recordings consisted of prolongation of the vowel /a/, scale singing, and a 1-min monologue. In comparison with controls and previously published normative data, both early and later stage PD patients' voices were characterized perceptually by limited pitch and loudness variability, breathiness, harshness and reduced loudness. High modal pitch levels also characterized the voices of males in both early and later stages of PD. Acoustically, the voices of both groups of PD patients demonstrated lower mean intensity levels and reduced maximum phonational frequency ranges in comparison with normative data. Although less clear, the present data also suggested that the PD patients' voices were characterized by excess jitter, a high-speaking fundamental frequency for males and a reduced fundamental frequency variability for females. While several of these voice features did not appear to deteriorate with disease progression (i.e. harshness, high modal pitch and speaking fundamental frequency in males, fundamental frequency variability in females, low intensity and jitter), breathiness, monopitch and monoloudness, low loudness and reduced maximum phonational frequency range were all worse in the later stages of PD. Tremor was the sole voice feature which was associated only with later stage PD.

Competition between Langmuir and upper-hybrid turbulence in a high-frequency-pumped ionosphere.

PubMed

Thidé, B; Sergeev, E N; Grach, S M; Leyser, T B; Carozzi, T D

2005-12-16

We show how the secondary escaping radiation, also known as stimulated electromagnetic emission (SEE), from the ionosphere irradiated by a high-intensity radio beam, can be used to study both reflection altitude ponderomotive parametric instabilities and upper-hybrid altitude thermal parametric instabilities. This has allowed us to observe the transfer of energy from smaller to higher sideband frequency offsets and to identify a new transient SEE feature.

Time-frequency feature representation using multi-resolution texture analysis and acoustic activity detector for real-life speech emotion recognition.

PubMed

Wang, Kun-Ching

2015-01-14

The classification of emotional speech is mostly considered in speech-related research on human-computer interaction (HCI). In this paper, the purpose is to present a novel feature extraction based on multi-resolutions texture image information (MRTII). The MRTII feature set is derived from multi-resolution texture analysis for characterization and classification of different emotions in a speech signal. The motivation is that we have to consider emotions have different intensity values in different frequency bands. In terms of human visual perceptual, the texture property on multi-resolution of emotional speech spectrogram should be a good feature set for emotion classification in speech. Furthermore, the multi-resolution analysis on texture can give a clearer discrimination between each emotion than uniform-resolution analysis on texture. In order to provide high accuracy of emotional discrimination especially in real-life, an acoustic activity detection (AAD) algorithm must be applied into the MRTII-based feature extraction. Considering the presence of many blended emotions in real life, in this paper make use of two corpora of naturally-occurring dialogs recorded in real-life call centers. Compared with the traditional Mel-scale Frequency Cepstral Coefficients (MFCC) and the state-of-the-art features, the MRTII features also can improve the correct classification rates of proposed systems among different language databases. Experimental results show that the proposed MRTII-based feature information inspired by human visual perception of the spectrogram image can provide significant classification for real-life emotional recognition in speech.

High spectral resolution lidar based on quad mach zehnder interferometer for aerosols and wind measurements on board space missions

NASA Astrophysics Data System (ADS)

Mariscal, Jean-François; Bruneau, Didier; Pelon, Jacques; Van Haecke, Mathilde; Blouzon, Frédéric; Montmessin, Franck; Chepfer, Hélène

2018-04-01

We present the measurement principle and the optical design of a Quad Mach Zehnder (QMZ) interferometer as HSRL technique, allowing simultaneous measurements of particle backscattering and wind velocity. Key features of this concept is to operate with a multimodal laser and do not require any frequency stabilization. These features are relevant especially for space applications for which high technical readiness level is required.

Multiple feature extraction and classification of electroencephalograph signal for Alzheimers' with spectrum and bispectrum

NASA Astrophysics Data System (ADS)

Wang, Ruofan; Wang, Jiang; Li, Shunan; Yu, Haitao; Deng, Bin; Wei, Xile

2015-01-01

In this paper, we have combined experimental neurophysiologic recording and statistical analysis to investigate the nonlinear characteristic and the cognitive function of the brain. Spectrum and bispectrum analyses are proposed to extract multiple effective features of electroencephalograph (EEG) signals from Alzheimer's disease (AD) patients and further applied to distinguish AD patients from the normal controls. Spectral analysis based on autoregressive Burg method is first used to quantify the power distribution of EEG series in the frequency domain. Compared to the control group, the relative power spectral density of AD group is significantly higher in the theta frequency band, while lower in the alpha frequency bands. In addition, median frequency of spectrum is decreased, and spectral entropy ratio of these two frequency bands undergoes drastic changes at the P3 electrode in the central-parietal brain region, implying that the electrophysiological behavior in AD brain is much slower and less irregular. In order to explore the nonlinear high order information, bispectral analysis which measures the complexity of phase-coupling is further applied to P3 electrode in the whole frequency band. It is demonstrated that less bispectral peaks appear and the amplitudes of peaks fall, suggesting a decrease of non-Gaussianity and nonlinearity of EEG in ADs. Notably, the application of this method to five brain regions shows higher concentration of the weighted center of bispectrum and lower complexity reflecting phase-coupling by bispectral entropy. Based on spectrum and bispectrum analyses, six efficient features are extracted and then applied to discriminate AD from the normal in the five brain regions. The classification results indicate that all these features could differentiate AD patients from the normal controls with a maximum accuracy of 90.2%. Particularly, different brain regions are sensitive to different features. Moreover, the optimal combination of features obtained by discriminant analysis may improve the classification accuracy. These results demonstrate the great promise for scape EEG spectral and bispectral features as a potential effective method for detection of AD, which may facilitate our understanding of the pathological mechanism of the disease.

Multiple feature extraction and classification of electroencephalograph signal for Alzheimers' with spectrum and bispectrum.

PubMed

Wang, Ruofan; Wang, Jiang; Li, Shunan; Yu, Haitao; Deng, Bin; Wei, Xile

2015-01-01

In this paper, we have combined experimental neurophysiologic recording and statistical analysis to investigate the nonlinear characteristic and the cognitive function of the brain. Spectrum and bispectrum analyses are proposed to extract multiple effective features of electroencephalograph (EEG) signals from Alzheimer's disease (AD) patients and further applied to distinguish AD patients from the normal controls. Spectral analysis based on autoregressive Burg method is first used to quantify the power distribution of EEG series in the frequency domain. Compared to the control group, the relative power spectral density of AD group is significantly higher in the theta frequency band, while lower in the alpha frequency bands. In addition, median frequency of spectrum is decreased, and spectral entropy ratio of these two frequency bands undergoes drastic changes at the P3 electrode in the central-parietal brain region, implying that the electrophysiological behavior in AD brain is much slower and less irregular. In order to explore the nonlinear high order information, bispectral analysis which measures the complexity of phase-coupling is further applied to P3 electrode in the whole frequency band. It is demonstrated that less bispectral peaks appear and the amplitudes of peaks fall, suggesting a decrease of non-Gaussianity and nonlinearity of EEG in ADs. Notably, the application of this method to five brain regions shows higher concentration of the weighted center of bispectrum and lower complexity reflecting phase-coupling by bispectral entropy. Based on spectrum and bispectrum analyses, six efficient features are extracted and then applied to discriminate AD from the normal in the five brain regions. The classification results indicate that all these features could differentiate AD patients from the normal controls with a maximum accuracy of 90.2%. Particularly, different brain regions are sensitive to different features. Moreover, the optimal combination of features obtained by discriminant analysis may improve the classification accuracy. These results demonstrate the great promise for scape EEG spectral and bispectral features as a potential effective method for detection of AD, which may facilitate our understanding of the pathological mechanism of the disease.

Classification of EEG signals to identify variations in attention during motor task execution.

PubMed

Aliakbaryhosseinabadi, Susan; Kamavuako, Ernest Nlandu; Jiang, Ning; Farina, Dario; Mrachacz-Kersting, Natalie

2017-06-01

Brain-computer interface (BCI) systems in neuro-rehabilitation use brain signals to control external devices. User status such as attention affects BCI performance; thus detecting the user's attention drift due to internal or external factors is essential for high detection accuracy. An auditory oddball task was applied to divert the users' attention during a simple ankle dorsiflexion movement. Electroencephalogram signals were recorded from eighteen channels. Temporal and time-frequency features were projected to a lower dimension space and used to analyze the effect of two attention levels on motor tasks in each participant. Then, a global feature distribution was constructed with the projected time-frequency features of all participants from all channels and applied for attention classification during motor movement execution. Time-frequency features led to significantly better classification results with respect to the temporal features, particularly for electrodes located over the motor cortex. Motor cortex channels had a higher accuracy in comparison to other channels in the global discrimination of attention level. Previous methods have used the attention to a task to drive external devices, such as the P300 speller. However, here we focus for the first time on the effect of attention drift while performing a motor task. It is possible to explore user's attention variation when performing motor tasks in synchronous BCI systems with time-frequency features. This is the first step towards an adaptive real-time BCI with an integrated function to reveal attention shifts from the motor task. Copyright © 2017 Elsevier B.V. All rights reserved.

Model reductions using a projection formulation

NASA Technical Reports Server (NTRS)

De Villemagne, Christian; Skelton, Robert E.

1987-01-01

A new methodology for model reduction of MIMO systems exploits the notion of an oblique projection. A reduced model is uniquely defined by a projector whose range space and orthogonal to the null space are chosen among the ranges of generalized controllability and observability matrices. The reduced order models match various combinations (chosen by the designer) of four types of parameters of the full order system associated with (1) low frequency response, (2) high frequency response, (3) low frequency power spectral density, and (4) high frequency power spectral density. Thus, the proposed method is a computationally simple substitute for many existing methods, has an extreme flexibility to embrace combinations of existing methods and offers some new features.

Component isolation for multi-component signal analysis using a non-parametric gaussian latent feature model

NASA Astrophysics Data System (ADS)

Yang, Yang; Peng, Zhike; Dong, Xingjian; Zhang, Wenming; Clifton, David A.

2018-03-01

A challenge in analysing non-stationary multi-component signals is to isolate nonlinearly time-varying signals especially when they are overlapped in time and frequency plane. In this paper, a framework integrating time-frequency analysis-based demodulation and a non-parametric Gaussian latent feature model is proposed to isolate and recover components of such signals. The former aims to remove high-order frequency modulation (FM) such that the latter is able to infer demodulated components while simultaneously discovering the number of the target components. The proposed method is effective in isolating multiple components that have the same FM behavior. In addition, the results show that the proposed method is superior to generalised demodulation with singular-value decomposition-based method, parametric time-frequency analysis with filter-based method and empirical model decomposition base method, in recovering the amplitude and phase of superimposed components.

The signature of positive selection at randomly chosen loci.

PubMed

Przeworski, Molly

2002-03-01

In Drosophila and humans, there are accumulating examples of loci with a significant excess of high-frequency-derived alleles or high levels of linkage disequilibrium, relative to a neutral model of a random-mating population of constant size. These are features expected after a recent selective sweep. Their prevalence suggests that positive directional selection may be widespread in both species. However, as I show here, these features do not persist long after the sweep ends: The high-frequency alleles drift to fixation and no longer contribute to polymorphism, while linkage disequilibrium is broken down by recombination. As a result, loci chosen without independent evidence of recent selection are not expected to exhibit either of these features, even if they have been affected by numerous sweeps in their genealogical history. How then can we explain the patterns in the data? One possibility is population structure, with unequal sampling from different subpopulations. Alternatively, positive selection may not operate as is commonly modeled. In particular, the rate of fixation of advantageous mutations may have increased in the recent past.

Hydrologic Modeling and Flood Frequency Analysis for Ordinary High Water Mark Delineation

DTIC Science & Technology

2016-02-01

that may have adjacent floodplains and terraces. Each of these geomorphic features may have different characteristic sediment grain sizes, different...relationship between streamflow recurrence intervals and ERDC/CRREL TR-16-2 7 geomorphic features observed in the field. The bankfull channel is the cu... geomorphic features is one of many reasons described in this document why a specific recurrence interval cannot be used to determine the OHWM. At the same

Description and Evaluation of a Four-Channel, Coherent 100-kHz Sidescan Sonar

DTIC Science & Technology

2004-12-01

document contains color images. 14. ABSTRACT This report documents the design and features of a new, four-channel, coherent 100-kHz sidescan sonar...Atlantic Technical Memorandum DRDC Atlantic TM 2004-204 December 2004 Abstract This report documents the design and features of a new...Results This report documents the design and features of this new high-frequency sonar system. These initial field trial results demonstrate some of

Migraine disability assessment (MIDAS) score: relation to headache frequency, pain intensity, and headache symptoms.

PubMed

Stewart, Walter F; Lipton, Richard B; Kolodner, Ken

2003-03-01

To determine the extent to which variation in the Migraine Disability Assessment (MIDAS) score is associated with headache frequency, pain intensity, headache symptoms, gender, and employment status. The MIDAS questionnaire is a 7-item questionnaire (with 5 scored items) designed to measure headache-related disability, to improve physician-patient communication, and to identify patients with high treatment needs. Data from 3 population-based studies (total sample, n = 397) conducted in the United States and the United Kingdom were used to evaluate the relationship between headache features (attack frequency, pain intensity, pain quality, and associated symptoms) and MIDAS score. Data on headache features were collected by telephone using a standardized interview. The MIDAS questionnaire was completed shortly after the telephone interview. General linear models were used to determine the extent to which population variation in the MIDAS score was explained by headache features. Using linear regression, variables for all headache features (ie, headache frequency, pain intensity, pain quality, and associated symptoms) and demographic characteristics explained only 22% of the variation in MIDAS scores. Almost all (19.9%) the explained variance was accounted for by average pain intensity (12.0%), number of headache days (6.1%), and exacerbation of pain with movement (1.8%). When pain intensity and headache frequency were included in the model, no statistically significant differences in MIDAS scores were observed by gender or employment status. Although explaining only 2.1% of the variance, age was significantly associated with MIDAS scores, with those under 25 years demonstrating higher MIDAS scores than other age groups. No other variables (ie, frequency of occurrence of associated symptoms and other measures of quality of pain) were associated with MIDAS scores. Challenges to the utility of the MIDAS as a measure include whether headache-related disability is largely a function of other routine headache features and whether MIDAS is inherently biased based on work status and gender. While the MIDAS score was associated with headache frequency and average pain score, these two headache features explain only a modest proportion of the variation in MIDAS scores. Additionally, gender and work status were not related to MIDAS scores. These findings suggest that the MIDAS score captures information about disability that is not inherent to other headache features and is independent of gender and work status.

a Robust Descriptor Based on Spatial and Frequency Structural Information for Visible and Thermal Infrared Image Matching

NASA Astrophysics Data System (ADS)

Fu, Z.; Qin, Q.; Wu, C.; Chang, Y.; Luo, B.

2017-09-01

Due to the differences of imaging principles, image matching between visible and thermal infrared images still exist new challenges and difficulties. Inspired by the complementary spatial and frequency information of geometric structural features, a robust descriptor is proposed for visible and thermal infrared images matching. We first divide two different spatial regions to the region around point of interest, using the histogram of oriented magnitudes, which corresponds to the 2-D structural shape information to describe the larger region and the edge oriented histogram to describe the spatial distribution for the smaller region. Then the two vectors are normalized and combined to a higher feature vector. Finally, our proposed descriptor is obtained by applying principal component analysis (PCA) to reduce the dimension of the combined high feature vector to make our descriptor more robust. Experimental results showed that our proposed method was provided with significant improvements in correct matching numbers and obvious advantages by complementing information within spatial and frequency structural information.

Research on fusion algorithm of polarization image in tetrolet domain

NASA Astrophysics Data System (ADS)

Zhang, Dexiang; Yuan, BaoHong; Zhang, Jingjing

2015-12-01

Tetrolets are Haar-type wavelets whose supports are tetrominoes which are shapes made by connecting four equal-sized squares. A fusion method for polarization images based on tetrolet transform is proposed. Firstly, the magnitude of polarization image and angle of polarization image can be decomposed into low-frequency coefficients and high-frequency coefficients with multi-scales and multi-directions using tetrolet transform. For the low-frequency coefficients, the average fusion method is used. According to edge distribution differences in high frequency sub-band images, for the directional high-frequency coefficients are used to select the better coefficients by region spectrum entropy algorithm for fusion. At last the fused image can be obtained by utilizing inverse transform for fused tetrolet coefficients. Experimental results show that the proposed method can detect image features more effectively and the fused image has better subjective visual effect

Theoretical and practical aspects of application of a low-energy electromagnetic radiation of the extremely high-frequency range in medicine

NASA Astrophysics Data System (ADS)

Lyapina, Elena P.; Chesnokov, Igor A.; Bushuev, Nikolay A.; Kuzyutkina, Svetlana E.; Shuldjakov, Andrey A.

2006-02-01

The questions concerning the mechanism of action of a low-energy electromagnetic radiation of the extremely high frequency range (EMR EHF) are considered. Also the features of biological effects are considered in their application as therapeutic actions. As an example the advantages of EHF treatment of patients with chronic brucellosis are shown, the algorithm of a choice of the scheme of treatment using EMR EHF is offered.

Turbine bucket natural frequency tuning rib

DOEpatents

Wang, John Zhiqiang; Norton, Paul Francis; Barb, Kevin Joseph; Jacala, Ariel Caesar-Prepena

2002-01-01

A tuning rib is added preferably in the aft cavity of a cored turbine bucket to alter the bucket's natural frequencies. The tuning rib may be a solid rib or a segmented rib and is particularly suited for altering high order frequency modes such as 2T, 4F and 1-3S. As such, detrimental crossings of natural bucket frequencies and gas turbine stimuli can be avoided to thereby improve the reliability of a gas turbine without impacting other features of the bucket that are important to the performance of the gas turbine.

Uyghur face recognition method combining 2DDCT with POEM

NASA Astrophysics Data System (ADS)

Yi, Lihamu; Ya, Ermaimaiti

2017-11-01

In this paper, in light of the reduced recognition rate and poor robustness of Uyghur face under illumination and partial occlusion, a Uyghur face recognition method combining Two Dimension Discrete Cosine Transform (2DDCT) with Patterns Oriented Edge Magnitudes (POEM) was proposed. Firstly, the Uyghur face images were divided into 8×8 block matrix, and the Uyghur face images after block processing were converted into frequency-domain status using 2DDCT; secondly, the Uyghur face images were compressed to exclude non-sensitive medium frequency parts and non-high frequency parts, so it can reduce the feature dimensions necessary for the Uyghur face images, and further reduce the amount of computation; thirdly, the corresponding POEM histograms of the Uyghur face images were obtained by calculating the feature quantity of POEM; fourthly, the POEM histograms were cascaded together as the texture histogram of the center feature point to obtain the texture features of the Uyghur face feature points; finally, classification of the training samples was carried out using deep learning algorithm. The simulation experiment results showed that the proposed algorithm further improved the recognition rate of the self-built Uyghur face database, and greatly improved the computing speed of the self-built Uyghur face database, and had strong robustness.

Non-contact feature detection using ultrasonic Lamb waves

DOEpatents

Sinha, Dipen N [Los Alamos, NM

2011-06-28

Apparatus and method for non-contact ultrasonic detection of features on or within the walls of hollow pipes are described. An air-coupled, high-power ultrasonic transducer for generating guided waves in the pipe wall, and a high-sensitivity, air-coupled transducer for detecting these waves, are disposed at a distance apart and at chosen angle with respect to the surface of the pipe, either inside of or outside of the pipe. Measurements may be made in reflection or transmission modes depending on the relative position of the transducers and the pipe. Data are taken by sweeping the frequency of the incident ultrasonic waves, using a tracking narrow-band filter to reduce detected noise, and transforming the frequency domain data into the time domain using fast Fourier transformation, if required.

Phonon spectrum of single-crystalline FeSe probed by high-resolution electron energy-loss spectroscopy

NASA Astrophysics Data System (ADS)

Zakeri, Khalil; Engelhardt, Tobias; Le Tacon, Matthieu; Wolf, Thomas

2018-06-01

Utilizing high-resolution electron energy-loss spectroscopy (HREELS) we measure the phonon frequencies of β-FeSe(001), cleaved under ultra-high vacuum conditions. At the zone center (Γ bar-point) three prominent loss features are observed at loss energies of about ≃ 20.5 and 25.6 and 40 meV. Based on the scattering selection rules we assign the observed loss features to the A1g, B1g, and A2u phonon modes of β-FeSe(001). The experimentally measured phonon frequencies do not agree with the results of density functional based calculations in which a nonmagnetic, a checkerboard or a strip antiferromagnetic order is assumed for β-FeSe(001). Our measurements suggest that, similar to the other Fe-based materials, magnetism has a profound impact on the lattice dynamics of β-FeSe(001).

High Q-factor metasurfaces based on miniaturized asymmetric single split resonators

NASA Astrophysics Data System (ADS)

Al-Naib, Ibraheem A. I.; Jansen, Christian; Koch, Martin

2009-04-01

We introduce asymmetric single split rectangular resonators as bandstop metasurfaces, which exhibit very high Q-factors in combination with low passband losses and a small electrical footprint. The effect of the degree of asymmetry on the frequency response is thoroughly studied. Furthermore, complementary structures, which feature a bandpass behavior, were derived by applying Babinet's principle and investigated with regards to their transmission characteristics. In future, asymmetric single split rectangular resonators could provide efficient unit cells for frequency selective surface devices, such as thin-film sensors or high performance filters.

[Evolution of nodular scleritis with ultrasound biomicroscopy: case report].

PubMed

Martinez, Andrea Alejandra Gonzalez; Matos, Kimble Teixeira Fonseca; Trevisani, Virgínia; Hirai, Alcides; Allemann, Norma

2013-01-01

To establish evolutionary pattern of a case of nodular scleritis with high frequency ultrasound during treatment. Twenty-seven year old female, initial manifestation of intermediate uveitis, bilateral macular edema after clinical treatment with topical and oral steroids. After four months, we observed the formation of a scleral nodule in the right eye when patient underwent high frequency ultrasound (Paradigm, 50 MHz transducer, immersion technique). The lesion in right eye was characterized at high frequency ultrasound as a nodular lesion located at the anterior inferior temporal wall associated with localized reduction of scleral thickness. After intravitreal injection of triamcinolone for treatment of macular edema, clinical regression of the scleral nodule was observed in right eye, maintaining reduced scleral thickness. High frequency ultrasound assisted in the diagnosis of nodular scleritis during the phases of treatment and in the identify its characteristic sequel feature, the scleral thinning.

Artificially intelligent recognition of Arabic speaker using voice print-based local features

NASA Astrophysics Data System (ADS)

Mahmood, Awais; Alsulaiman, Mansour; Muhammad, Ghulam; Akram, Sheeraz

2016-11-01

Local features for any pattern recognition system are based on the information extracted locally. In this paper, a local feature extraction technique was developed. This feature was extracted in the time-frequency plain by taking the moving average on the diagonal directions of the time-frequency plane. This feature captured the time-frequency events producing a unique pattern for each speaker that can be viewed as a voice print of the speaker. Hence, we referred to this technique as voice print-based local feature. The proposed feature was compared to other features including mel-frequency cepstral coefficient (MFCC) for speaker recognition using two different databases. One of the databases used in the comparison is a subset of an LDC database that consisted of two short sentences uttered by 182 speakers. The proposed feature attained 98.35% recognition rate compared to 96.7% for MFCC using the LDC subset.

Increased fusiform area activation in schizophrenia during processing of spatial frequency-degraded faces, as revealed by fMRI.

PubMed

Silverstein, S M; All, S D; Kasi, R; Berten, S; Essex, B; Lathrop, K L; Little, D M

2010-07-01

People with schizophrenia demonstrate perceptual organization impairments, and these are thought to contribute to their face processing difficulties. We examined the neural substrates of emotionally neutral face processing in schizophrenia by investigating neural activity under three stimulus conditions: faces characterized by the full spectrum of spatial frequencies, faces with low spatial frequency information removed [high spatial frequency (HSF) condition], and faces with high spatial frequency information removed [low spatial frequency (LSF) condition]. Face perception in the HSF condition is more reliant on local feature processing whereas perception in the LSF condition requires greater reliance on global form processing. Past studies of perceptual organization in schizophrenia indicate that patients perform relatively more poorly with degraded stimuli but also that, when global information is absent, patients may perform better than controls because of their relatively increased ability to initially process individual features. Therefore, we hypothesized that people with schizophrenia (n=14) would demonstrate greater face processing difficulties than controls (n=13) in the LSF condition, whereas they would demonstrate a smaller difference or superior performance in the HSF condition. In a gender-discrimination task, behavioral data indicated high levels of accuracy for both groups, with a trend toward an interaction involving higher patient performance in the HSF condition and poorer patient performance in the LSF condition. Patients demonstrated greater activity in the fusiform gyrus compared to controls in both degraded conditions. These data suggest that impairments in basic integration abilities may be compensated for by relatively increased activity in this region.

Time-Frequency Feature Representation Using Multi-Resolution Texture Analysis and Acoustic Activity Detector for Real-Life Speech Emotion Recognition

PubMed Central

Wang, Kun-Ching

2015-01-01

The classification of emotional speech is mostly considered in speech-related research on human-computer interaction (HCI). In this paper, the purpose is to present a novel feature extraction based on multi-resolutions texture image information (MRTII). The MRTII feature set is derived from multi-resolution texture analysis for characterization and classification of different emotions in a speech signal. The motivation is that we have to consider emotions have different intensity values in different frequency bands. In terms of human visual perceptual, the texture property on multi-resolution of emotional speech spectrogram should be a good feature set for emotion classification in speech. Furthermore, the multi-resolution analysis on texture can give a clearer discrimination between each emotion than uniform-resolution analysis on texture. In order to provide high accuracy of emotional discrimination especially in real-life, an acoustic activity detection (AAD) algorithm must be applied into the MRTII-based feature extraction. Considering the presence of many blended emotions in real life, in this paper make use of two corpora of naturally-occurring dialogs recorded in real-life call centers. Compared with the traditional Mel-scale Frequency Cepstral Coefficients (MFCC) and the state-of-the-art features, the MRTII features also can improve the correct classification rates of proposed systems among different language databases. Experimental results show that the proposed MRTII-based feature information inspired by human visual perception of the spectrogram image can provide significant classification for real-life emotional recognition in speech. PMID:25594590

Reversible Nerve Conduction Block Using Kilohertz Frequency Alternating Current

PubMed Central

Kilgore, Kevin L.; Bhadra, Niloy

2013-01-01

Objectives The features and clinical applications of balanced-charge kilohertz frequency alternating currents (KHFAC) are reviewed. Preclinical studies of KHFAC block have demonstrated that it can produce an extremely rapid and reversible block of nerve conduction. Recent systematic analysis and experimentation utilizing KHFAC block has resulted in a significant increase in interest in KHFAC block, both scientifically and clinically. Materials and Methods We review the history and characteristics of KHFAC block, the methods used to investigate this type of block, the experimental evaluation of block, and the electrical parameters and electrode designs needed to achieve successful block. We then analyze the existing clinical applications of high frequency currents, comparing the early results with the known features of KHFAC block. Results Although many features of KHFAC block have been characterized, there is still much that is unknown regarding the response of neural structures to rapidly fluctuating electrical fields. The clinical reports to date do not provide sufficient information to properly evaluate the mechanisms that result in successful or unsuccessful treatment. Conclusions KHFAC nerve block has significant potential as a means of controlling nerve activity for the purpose of treating disease. However, early clinical studies in the use of high frequency currents for the treatment of pain have not been designed to elucidate mechanisms or allow direct comparisons to preclinical data. We strongly encourage the careful reporting of the parameters utilized in these clinical studies, as well as the development of outcome measures that could illuminate the mechanisms of this modality. PMID:23924075

Design and development of an F/A-18 inlet distortion rake: A cost and time saving solution

NASA Technical Reports Server (NTRS)

Yuhas, Andrew J.; Ray, Ronald J.; Burley, Richard R.; Steenken, William G.; Lechtenberg, Leon; Thornton, Don

1995-01-01

An innovative inlet total pressure distortion measurement rake has been designed and developed for the F/A-18 A/B/C/D aircraft inlet. The design was conceived by NASA and General Electric Aircraft Engines personnel. This rake has been flight qualified and flown in the F/A-18 High Alpha Research Vehicle at NASA Dryden Flight Research Center, Edwards, California. The eight-legged, one-piece, wagon wheel design of the rake was developed at a reduced cost and offered reduced installation time compared to traditional designs. The rake features 40 dual-measurement ports for low- and high-frequency pressure measurements with the high-frequency transducer mounted at the port. This high-frequency transducer offers direct absolute pressure measurements from low to high frequencies of interest, thereby allowing the rake to be used during highly dynamic aircraft maneuvers. Outstanding structural characteristics are inherent to the design through its construction and use of lightweight materials.

Design and characterization of very high frequency pulse tube prototypes

NASA Astrophysics Data System (ADS)

Lopes, Diogo; Duval, Jean-Marc; Charles, Ivan; Butterworth, James; Trollier, Thierry; Tanchon, Julien; Ravex, Alain; Daniel, Christophe

2012-06-01

Weight and size are important features of a cryocooler when it comes to space applications. Given their reliability and low level of exported vibrations (due to the absence of moving cold parts), pulse tubes are good candidates for spatial purposes and their miniaturization has been the focus of many studies. We report on the design and performance of a small-scale very high frequency pulse tube prototype, modeled after two previous prototypes which were optimized with a numerical code.

Figure/ground segregation from temporal delay is best at high spatial frequencies.

PubMed

Kojima, H

1998-12-01

Two experiments investigated the role of spatial frequency in performance of a figure/ground segregation task based on temporal cues. Figure orientation was much easier to judge when figure and ground portions of the target were defined exclusively by random texture composed entirely of high spatial frequencies. When target components were defined by low spatial frequencies only, the task was nearly impossible except with long temporal delay between figure and ground. These results are inconsistent with the hypothesis that M-cell activity is primarily responsible for figure/ground segregation from temporal delay. Instead, these results point to a distinction between temporal integration and temporal differentiation. Additionally, the present results can be related to recent work on the binding of spatial features over time.

Modulations of eye movement patterns by spatial filtering during the learning and testing phases of an old/new face recognition task.

PubMed

Lemieux, Chantal L; Collin, Charles A; Nelson, Elizabeth A

2015-02-01

In two experiments, we examined the effects of varying the spatial frequency (SF) content of face images on eye movements during the learning and testing phases of an old/new recognition task. At both learning and testing, participants were presented with face stimuli band-pass filtered to 11 different SF bands, as well as an unfiltered baseline condition. We found that eye movements varied significantly as a function of SF. Specifically, the frequency of transitions between facial features showed a band-pass pattern, with more transitions for middle-band faces (≈5-20 cycles/face) than for low-band (≈<5 cpf) or high-band (≈>20 cpf) ones. These findings were similar for the learning and testing phases. The distributions of transitions across facial features were similar for the middle-band, high-band, and unfiltered faces, showing a concentration on the eyes and mouth; conversely, low-band faces elicited mostly transitions involving the nose and nasion. The eye movement patterns elicited by low, middle, and high bands are similar to those previous researchers have suggested reflect holistic, configural, and featural processing, respectively. More generally, our results are compatible with the hypotheses that eye movements are functional, and that the visual system makes flexible use of visuospatial information in face processing. Finally, our finding that only middle spatial frequencies yielded the same number and distribution of fixations as unfiltered faces adds more evidence to the idea that these frequencies are especially important for face recognition, and reveals a possible mediator for the superior performance that they elicit.

Perception of stochastically undersampled sound waveforms: a model of auditory deafferentation

PubMed Central

Lopez-Poveda, Enrique A.; Barrios, Pablo

2013-01-01

Auditory deafferentation, or permanent loss of auditory nerve afferent terminals, occurs after noise overexposure and aging and may accompany many forms of hearing loss. It could cause significant auditory impairment but is undetected by regular clinical tests and so its effects on perception are poorly understood. Here, we hypothesize and test a neural mechanism by which deafferentation could deteriorate perception. The basic idea is that the spike train produced by each auditory afferent resembles a stochastically digitized version of the sound waveform and that the quality of the waveform representation in the whole nerve depends on the number of aggregated spike trains or auditory afferents. We reason that because spikes occur stochastically in time with a higher probability for high- than for low-intensity sounds, more afferents would be required for the nerve to faithfully encode high-frequency or low-intensity waveform features than low-frequency or high-intensity features. Deafferentation would thus degrade the encoding of these features. We further reason that due to the stochastic nature of nerve firing, the degradation would be greater in noise than in quiet. This hypothesis is tested using a vocoder. Sounds were filtered through ten adjacent frequency bands. For the signal in each band, multiple stochastically subsampled copies were obtained to roughly mimic different stochastic representations of that signal conveyed by different auditory afferents innervating a given cochlear region. These copies were then aggregated to obtain an acoustic stimulus. Tone detection and speech identification tests were performed by young, normal-hearing listeners using different numbers of stochastic samplers per frequency band in the vocoder. Results support the hypothesis that stochastic undersampling of the sound waveform, inspired by deafferentation, impairs speech perception in noise more than in quiet, consistent with auditory aging effects. PMID:23882176

Eddy current imaging with an atomic radio-frequency magnetometer

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

Wickenbrock, Arne, E-mail: wickenbr@uni-mainz.de; Leefer, Nathan; Blanchard, John W.

2016-05-02

We use a radio-frequency {sup 85}Rb alkali-vapor cell magnetometer based on a paraffin-coated cell with long spin-coherence time and a small, low-inductance driving coil to create highly resolved conductivity maps of different objects. We resolve sub-mm features in conductive objects, we characterize the frequency response of our technique, and by operating at frequencies up to 250 kHz we are able to discriminate between differently conductive materials based on the induced response. The method is suited to cover a wide range of driving frequencies and can potentially be used for detecting non-metallic objects with low DC conductivity.

Device and method for imaging of non-linear and linear properties of formations surrounding a borehole

DOEpatents

Johnson, Paul A; Tencate, James A; Le Bas, Pierre-Yves; Guyer, Robert; Vu, Cung Khac; Skelt, Christopher

2013-10-08

In some aspects of the disclosure, a method and an apparatus is disclosed for investigating material surrounding the borehole. The method includes generating within a borehole an intermittent low frequency vibration that propagates as a tube wave longitudinally to the borehole and induces a nonlinear response in one or more features in the material that are substantially perpendicular to a longitudinal axis of the borehole; generating within the borehole a sequence of high frequency pulses directed such that they travel longitudinally to the borehole within the surrounding material; and receiving, at one or more receivers positionable in the borehole, a signal that includes components from the low frequency vibration and the sequence of high frequency pulses during intermittent generation of the low frequency vibration, to investigate the material surrounding the borehole.

On-Chip Power-Combining for High-Power Schottky Diode-Based Frequency Multipliers

NASA Technical Reports Server (NTRS)

Chattopadhyay, Goutam; Mehdi, Imran; Schlecht, Erich T.; Lee, Choonsup; Siles, Jose V.; Maestrini, Alain E.; Thomas, Bertrand; Jung, Cecile D.

2013-01-01

A 1.6-THz power-combined Schottky frequency tripler was designed to handle approximately 30 mW input power. The design of Schottky-based triplers at this frequency range is mainly constrained by the shrinkage of the waveguide dimensions with frequency and the minimum diode mesa sizes, which limits the maximum number of diodes that can be placed on the chip to no more than two. Hence, multiple-chip power-combined schemes become necessary to increase the power-handling capabilities of high-frequency multipliers. The design presented here overcomes difficulties by performing the power-combining directly on-chip. Four E-probes are located at a single input waveguide in order to equally pump four multiplying structures (featuring two diodes each). The produced output power is then recombined at the output using the same concept.

A piecewise probabilistic regression model to decode hand movement trajectories from epidural and subdural ECoG signals

NASA Astrophysics Data System (ADS)

Farrokhi, Behraz; Erfanian, Abbas

2018-06-01

Objective. The primary concern of this study is to develop a probabilistic regression method that would improve the decoding of the hand movement trajectories from epidural ECoG as well as from subdural ECoG signals. Approach. The model is characterized by the conditional expectation of the hand position given the ECoG signals. The conditional expectation of the hand position is then modeled by a linear combination of the conditional probability density functions defined for each segment of the movement. Moreover, a spatial linear filter is proposed for reducing the dimension of the feature space. The spatial linear filter is applied to each frequency band of the ECoG signals and extract the features with highest decoding performance. Main results. For evaluating the proposed method, a dataset including 28 ECoG recordings from four adult Japanese macaques is used. The results show that the proposed decoding method outperforms the results with respect to the state of the art methods using this dataset. The relative kinematic information of each frequency band is also investigated using mutual information and decoding performance. The decoding performance shows that the best performance was obtained for high gamma bands from 50 to 200 Hz as well as high frequency ECoG band from 200 to 400 Hz for subdural recordings. However, the decoding performance was decreased for these frequency bands using epidural recordings. The mutual information shows that, on average, the high gamma band from 50 to 200 Hz and high frequency ECoG band from 200 to 400 Hz contain significantly more information than the average of the rest of the frequency bands ≤ft( p<0.001 \\right) for both subdural and epidural recordings. The results of high resolution time-frequency analysis show that ERD/ERS patterns in all frequency bands could reveal the dynamics of the ECoG responses during the movement. The onset and offset of the movement can be clearly identified by the ERD/ERS patterns. Significance. Reliable decoding the kinematic information from the brain signals paves the way for robust control of external devices.

Comparison of spatial frequency domain features for the detection of side attack explosive ballistics in synthetic aperture acoustics

NASA Astrophysics Data System (ADS)

Dowdy, Josh; Anderson, Derek T.; Luke, Robert H.; Ball, John E.; Keller, James M.; Havens, Timothy C.

2016-05-01

Explosive hazards in current and former conflict zones are a threat to both military and civilian personnel. As a result, much effort has been dedicated to identifying automated algorithms and systems to detect these threats. However, robust detection is complicated due to factors like the varied composition and anatomy of such hazards. In order to solve this challenge, a number of platforms (vehicle-based, handheld, etc.) and sensors (infrared, ground penetrating radar, acoustics, etc.) are being explored. In this article, we investigate the detection of side attack explosive ballistics via a vehicle-mounted acoustic sensor. In particular, we explore three acoustic features, one in the time domain and two on synthetic aperture acoustic (SAA) beamformed imagery. The idea is to exploit the varying acoustic frequency profile of a target due to its unique geometry and material composition with respect to different viewing angles. The first two features build their angle specific frequency information using a highly constrained subset of the signal data and the last feature builds its frequency profile using all available signal data for a given region of interest (centered on the candidate target location). Performance is assessed in the context of receiver operating characteristic (ROC) curves on cross-validation experiments for data collected at a U.S. Army test site on different days with multiple target types and clutter. Our preliminary results are encouraging and indicate that the top performing feature is the unrolled two dimensional discrete Fourier transform (DFT) of SAA beamformed imagery.

Synthetic aperture radar target detection, feature extraction, and image formation techniques

NASA Technical Reports Server (NTRS)

Li, Jian

1994-01-01

This report presents new algorithms for target detection, feature extraction, and image formation with the synthetic aperture radar (SAR) technology. For target detection, we consider target detection with SAR and coherent subtraction. We also study how the image false alarm rates are related to the target template false alarm rates when target templates are used for target detection. For feature extraction from SAR images, we present a computationally efficient eigenstructure-based 2D-MODE algorithm for two-dimensional frequency estimation. For SAR image formation, we present a robust parametric data model for estimating high resolution range signatures of radar targets and for forming high resolution SAR images.

A Support Vector Machine-Based Gender Identification Using Speech Signal

NASA Astrophysics Data System (ADS)

Lee, Kye-Hwan; Kang, Sang-Ick; Kim, Deok-Hwan; Chang, Joon-Hyuk

We propose an effective voice-based gender identification method using a support vector machine (SVM). The SVM is a binary classification algorithm that classifies two groups by finding the voluntary nonlinear boundary in a feature space and is known to yield high classification performance. In the present work, we compare the identification performance of the SVM with that of a Gaussian mixture model (GMM)-based method using the mel frequency cepstral coefficients (MFCC). A novel approach of incorporating a features fusion scheme based on a combination of the MFCC and the fundamental frequency is proposed with the aim of improving the performance of gender identification. Experimental results demonstrate that the gender identification performance using the SVM is significantly better than that of the GMM-based scheme. Moreover, the performance is substantially improved when the proposed features fusion technique is applied.

Electrically tunable transport and high-frequency dynamics in antiferromagnetic S r3I r2O7

NASA Astrophysics Data System (ADS)

Seinige, Heidi; Williamson, Morgan; Shen, Shida; Wang, Cheng; Cao, Gang; Zhou, Jianshi; Goodenough, John B.; Tsoi, Maxim

2016-12-01

We report dc and high-frequency transport properties of antiferromagnetic S r3I r2O7 . Temperature-dependent resistivity measurements show that the activation energy of this material can be tuned by an applied dc electrical bias. The latter allows for continuous variations in the sample resistivity of as much as 50% followed by a reversible resistive switching at higher biases. Such a switching is of high interest for antiferromagnetic applications in high-speed memory devices. Interestingly, we found the switching behavior to be strongly affected by a high-frequency (microwave) current applied to the sample. The microwaves at 3-7 GHz suppress the dc switching and produce resonancelike features that we tentatively associated with the dissipationless magnonics recently predicted to occur in antiferromagnetic insulators subject to ac electric fields. We have characterized the effects of microwave irradiation on electronic transport in S r3I r2O7 as a function of microwave frequency and power, strength and direction of external magnetic field, strength and polarity of applied dc bias, and temperature. Our observations support the potential of antiferromagnetic materials for high-speed/high-frequency spintronic applications.

Realizing one-dimensional quantum and high-frequency transport features in aligned single-walled carbon nanotube ropes

NASA Astrophysics Data System (ADS)

Ncube, Siphephile; Chimowa, George; Chiguvare, Zivayi; Bhattacharyya, Somnath

2014-07-01

The superiority of the electronic transport properties of single-walled carbon nanotube (SWNT) ropes over SWNT mats is verified from low temperature and frequency-dependent transport. The overall change of resistance versus in nanotube mats shows that 3D variable range hopping is the dominant conduction mechanism within the 2-300 K range. The magneto-resistance (MR) is found to be predominantly negative with a parabolic nature, which can also be described by the hopping model. Although the positive upturn of the MR at low temperatures establishes the contribution from quantum interference, the inherent quantum transport in individual tubes is suppressed at elevated temperatures. Therefore, to minimize multi-channel effects from inter-tube interactions and other defects, two-terminal devices were fabricated from aligned SWNT (extracted from a mat) for low temperature transport as well as high-frequency measurements. In contrast to the mat, the aligned ropes exhibit step-like features in the differential conductance within the 80-300 K temperature range. The effects of plasmon propagation, unique to one dimension, were identified in electronic transport as a non-universal power-law dependence of the differential conductance on temperature and source-drain voltage. The complex impedance showed high power transmission capabilities up to 65 GHz as well as oscillations in the frequency range up to 30 GHz. The measurements suggest that aligned SWNT ropes have a realistic potential for high-speed device applications.

The myositis autoantibody phenotypes of the juvenile idiopathic inflammatory myopathies.

PubMed

Rider, Lisa G; Shah, Mona; Mamyrova, Gulnara; Huber, Adam M; Rice, Madeline Murguia; Targoff, Ira N; Miller, Frederick W

2013-07-01

The juvenile idiopathic inflammatory myopathies (JIIM) are systemic autoimmune diseases characterized by skeletal muscle weakness, characteristic rashes, and other systemic features. In follow-up to our study defining the major clinical subgroup phenotypes of JIIM, we compared demographics, clinical features, laboratory measures, and outcomes among myositis-specific autoantibody (MSA) subgroups, as well as with published data on adult idiopathic inflammatory myopathy patients enrolled in a separate natural history study. In the present study, of 430 patients enrolled in a nationwide registry study who had serum tested for myositis autoantibodies, 374 had either a single specific MSA (n = 253) or no identified MSA (n = 121) and were the subject of the present report. Following univariate analysis, we used random forest classification and exact logistic regression modeling to compare autoantibody subgroups. Anti-p155/140 autoantibodies were the most frequent subgroup, present in 32% of patients with juvenile dermatomyositis (JDM) or overlap myositis with JDM, followed by anti-MJ autoantibodies, which were seen in 20% of JIIM patients, primarily in JDM. Other MSAs, including anti-synthetase, anti-signal recognition particle (SRP), and anti-Mi-2, were present in only 10% of JIIM patients. Features that characterized the anti-p155/140 autoantibody subgroup included Gottron papules, malar rash, "shawl-sign" rash, photosensitivity, cuticular overgrowth, lowest creatine kinase (CK) levels, and a predominantly chronic illness course. The features that differed for patients with anti-MJ antibodies included muscle cramps, dysphonia, intermediate CK levels, a high frequency of hospitalization, and a monocyclic disease course. Patients with anti-synthetase antibodies had higher frequencies of interstitial lung disease, arthralgia, and "mechanic's hands," and had an older age at diagnosis. The anti-SRP group, which had exclusively juvenile polymyositis, was characterized by high frequencies of black race, severe onset, distal weakness, falling episodes, Raynaud phenomenon, cardiac involvement, high CK levels, chronic disease course, frequent hospitalization, and wheelchair use. Characteristic features of the anti-Mi-2 subgroup included Hispanic ethnicity, classic dermatomyositis and malar rashes, high CK levels, and very low mortality. Finally, the most common features of patients without any currently defined MSA or myositis-associated autoantibodies included linear extensor erythema, arthralgia, and a monocyclic disease course. Several demographic and clinical features were shared between juvenile and adult idiopathic inflammatory myopathy subgroups, but with several important differences. We conclude that juvenile myositis is a heterogeneous group of illnesses with distinct autoantibody phenotypes defined by varying clinical and demographic characteristics, laboratory features, and outcomes.

The Myositis Autoantibody Phenotypes of the Juvenile Idiopathic Inflammatory Myopathies

PubMed Central

Shah, Mona; Mamyrova, Gulnara; Huber, Adam M.; Rice, Madeline Murguia; Targoff, Ira N.; Miller, Frederick W.

2013-01-01

Abstract The juvenile idiopathic inflammatory myopathies (JIIM) are systemic autoimmune diseases characterized by skeletal muscle weakness, characteristic rashes, and other systemic features. In follow-up to our study defining the major clinical subgroup phenotypes of JIIM, we compared demographics, clinical features, laboratory measures, and outcomes among myositis-specific autoantibody (MSA) subgroups, as well as with published data on adult idiopathic inflammatory myopathy patients enrolled in a separate natural history study. In the present study, of 430 patients enrolled in a nationwide registry study who had serum tested for myositis autoantibodies, 374 had either a single specific MSA (n = 253) or no identified MSA (n = 121) and were the subject of the present report. Following univariate analysis, we used random forest classification and exact logistic regression modeling to compare autoantibody subgroups. Anti-p155/140 autoantibodies were the most frequent subgroup, present in 32% of patients with juvenile dermatomyositis (JDM) or overlap myositis with JDM, followed by anti-MJ autoantibodies, which were seen in 20% of JIIM patients, primarily in JDM. Other MSAs, including anti-synthetase, anti-signal recognition particle (SRP), and anti-Mi-2, were present in only 10% of JIIM patients. Features that characterized the anti-p155/140 autoantibody subgroup included Gottron papules, malar rash, “shawl-sign” rash, photosensitivity, cuticular overgrowth, lowest creatine kinase (CK) levels, and a predominantly chronic illness course. The features that differed for patients with anti-MJ antibodies included muscle cramps, dysphonia, intermediate CK levels, a high frequency of hospitalization, and a monocyclic disease course. Patients with anti-synthetase antibodies had higher frequencies of interstitial lung disease, arthralgia, and “mechanic’s hands,” and had an older age at diagnosis. The anti-SRP group, which had exclusively juvenile polymyositis, was characterized by high frequencies of black race, severe onset, distal weakness, falling episodes, Raynaud phenomenon, cardiac involvement, high CK levels, chronic disease course, frequent hospitalization, and wheelchair use. Characteristic features of the anti-Mi-2 subgroup included Hispanic ethnicity, classic dermatomyositis and malar rashes, high CK levels, and very low mortality. Finally, the most common features of patients without any currently defined MSA or myositis-associated autoantibodies included linear extensor erythema, arthralgia, and a monocyclic disease course. Several demographic and clinical features were shared between juvenile and adult idiopathic inflammatory myopathy subgroups, but with several important differences. We conclude that juvenile myositis is a heterogeneous group of illnesses with distinct autoantibody phenotypes defined by varying clinical and demographic characteristics, laboratory features, and outcomes. PMID:23877355

Effective and extensible feature extraction method using genetic algorithm-based frequency-domain feature search for epileptic EEG multiclassification

PubMed Central

Wen, Tingxi; Zhang, Zhongnan

2017-01-01

Abstract In this paper, genetic algorithm-based frequency-domain feature search (GAFDS) method is proposed for the electroencephalogram (EEG) analysis of epilepsy. In this method, frequency-domain features are first searched and then combined with nonlinear features. Subsequently, these features are selected and optimized to classify EEG signals. The extracted features are analyzed experimentally. The features extracted by GAFDS show remarkable independence, and they are superior to the nonlinear features in terms of the ratio of interclass distance and intraclass distance. Moreover, the proposed feature search method can search for features of instantaneous frequency in a signal after Hilbert transformation. The classification results achieved using these features are reasonable; thus, GAFDS exhibits good extensibility. Multiple classical classifiers (i.e., k-nearest neighbor, linear discriminant analysis, decision tree, AdaBoost, multilayer perceptron, and Naïve Bayes) achieve satisfactory classification accuracies by using the features generated by the GAFDS method and the optimized feature selection. The accuracies for 2-classification and 3-classification problems may reach up to 99% and 97%, respectively. Results of several cross-validation experiments illustrate that GAFDS is effective in the extraction of effective features for EEG classification. Therefore, the proposed feature selection and optimization model can improve classification accuracy. PMID:28489789

Effective and extensible feature extraction method using genetic algorithm-based frequency-domain feature search for epileptic EEG multiclassification.

PubMed

Wen, Tingxi; Zhang, Zhongnan

2017-05-01

In this paper, genetic algorithm-based frequency-domain feature search (GAFDS) method is proposed for the electroencephalogram (EEG) analysis of epilepsy. In this method, frequency-domain features are first searched and then combined with nonlinear features. Subsequently, these features are selected and optimized to classify EEG signals. The extracted features are analyzed experimentally. The features extracted by GAFDS show remarkable independence, and they are superior to the nonlinear features in terms of the ratio of interclass distance and intraclass distance. Moreover, the proposed feature search method can search for features of instantaneous frequency in a signal after Hilbert transformation. The classification results achieved using these features are reasonable; thus, GAFDS exhibits good extensibility. Multiple classical classifiers (i.e., k-nearest neighbor, linear discriminant analysis, decision tree, AdaBoost, multilayer perceptron, and Naïve Bayes) achieve satisfactory classification accuracies by using the features generated by the GAFDS method and the optimized feature selection. The accuracies for 2-classification and 3-classification problems may reach up to 99% and 97%, respectively. Results of several cross-validation experiments illustrate that GAFDS is effective in the extraction of effective features for EEG classification. Therefore, the proposed feature selection and optimization model can improve classification accuracy.

Incorporating High-Frequency Physiologic Data Using Computational Dictionary Learning Improves Prediction of Delayed Cerebral Ischemia Compared to Existing Methods.

PubMed

Megjhani, Murad; Terilli, Kalijah; Frey, Hans-Peter; Velazquez, Angela G; Doyle, Kevin William; Connolly, Edward Sander; Roh, David Jinou; Agarwal, Sachin; Claassen, Jan; Elhadad, Noemie; Park, Soojin

2018-01-01

Accurate prediction of delayed cerebral ischemia (DCI) after subarachnoid hemorrhage (SAH) can be critical for planning interventions to prevent poor neurological outcome. This paper presents a model using convolution dictionary learning to extract features from physiological data available from bedside monitors. We develop and validate a prediction model for DCI after SAH, demonstrating improved precision over standard methods alone. 488 consecutive SAH admissions from 2006 to 2014 to a tertiary care hospital were included. Models were trained on 80%, while 20% were set aside for validation testing. Modified Fisher Scale was considered the standard grading scale in clinical use; baseline features also analyzed included age, sex, Hunt-Hess, and Glasgow Coma Scales. An unsupervised approach using convolution dictionary learning was used to extract features from physiological time series (systolic blood pressure and diastolic blood pressure, heart rate, respiratory rate, and oxygen saturation). Classifiers (partial least squares and linear and kernel support vector machines) were trained on feature subsets of the derivation dataset. Models were applied to the validation dataset. The performances of the best classifiers on the validation dataset are reported by feature subset. Standard grading scale (mFS): AUC 0.54. Combined demographics and grading scales (baseline features): AUC 0.63. Kernel derived physiologic features: AUC 0.66. Combined baseline and physiologic features with redundant feature reduction: AUC 0.71 on derivation dataset and 0.78 on validation dataset. Current DCI prediction tools rely on admission imaging and are advantageously simple to employ. However, using an agnostic and computationally inexpensive learning approach for high-frequency physiologic time series data, we demonstrated that we could incorporate individual physiologic data to achieve higher classification accuracy.

Reducing Sweeping Frequencies in Microwave NDT Employing Machine Learning Feature Selection

PubMed Central

Moomen, Abdelniser; Ali, Abdulbaset; Ramahi, Omar M.

2016-01-01

Nondestructive Testing (NDT) assessment of materials’ health condition is useful for classifying healthy from unhealthy structures or detecting flaws in metallic or dielectric structures. Performing structural health testing for coated/uncoated metallic or dielectric materials with the same testing equipment requires a testing method that can work on metallics and dielectrics such as microwave testing. Reducing complexity and expenses associated with current diagnostic practices of microwave NDT of structural health requires an effective and intelligent approach based on feature selection and classification techniques of machine learning. Current microwave NDT methods in general based on measuring variation in the S-matrix over the entire operating frequency ranges of the sensors. For instance, assessing the health of metallic structures using a microwave sensor depends on the reflection or/and transmission coefficient measurements as a function of the sweeping frequencies of the operating band. The aim of this work is reducing sweeping frequencies using machine learning feature selection techniques. By treating sweeping frequencies as features, the number of top important features can be identified, then only the most influential features (frequencies) are considered when building the microwave NDT equipment. The proposed method of reducing sweeping frequencies was validated experimentally using a waveguide sensor and a metallic plate with different cracks. Among the investigated feature selection techniques are information gain, gain ratio, relief, chi-squared. The effectiveness of the selected features were validated through performance evaluations of various classification models; namely, Nearest Neighbor, Neural Networks, Random Forest, and Support Vector Machine. Results showed good crack classification accuracy rates after employing feature selection algorithms. PMID:27104533

Task-induced frequency modulation features for brain-computer interfacing.

PubMed

Jayaram, Vinay; Hohmann, Matthias; Just, Jennifer; Schölkopf, Bernhard; Grosse-Wentrup, Moritz

2017-10-01

Task-induced amplitude modulation of neural oscillations is routinely used in brain-computer interfaces (BCIs) for decoding subjects' intents, and underlies some of the most robust and common methods in the field, such as common spatial patterns and Riemannian geometry. While there has been some interest in phase-related features for classification, both techniques usually presuppose that the frequencies of neural oscillations remain stable across various tasks. We investigate here whether features based on task-induced modulation of the frequency of neural oscillations enable decoding of subjects' intents with an accuracy comparable to task-induced amplitude modulation. We compare cross-validated classification accuracies using the amplitude and frequency modulated features, as well as a joint feature space, across subjects in various paradigms and pre-processing conditions. We show results with a motor imagery task, a cognitive task, and also preliminary results in patients with amyotrophic lateral sclerosis (ALS), as well as using common spatial patterns and Laplacian filtering. The frequency features alone do not significantly out-perform traditional amplitude modulation features, and in some cases perform significantly worse. However, across both tasks and pre-processing in healthy subjects the joint space significantly out-performs either the frequency or amplitude features alone. This result only does not hold for ALS patients, for whom the dataset is of insufficient size to draw any statistically significant conclusions. Task-induced frequency modulation is robust and straight forward to compute, and increases performance when added to standard amplitude modulation features across paradigms. This allows more information to be extracted from the EEG signal cheaply and can be used throughout the field of BCIs.

Monolithic THz Frequency Multipliers

NASA Technical Reports Server (NTRS)

Erickson, N. R.; Narayanan, G.; Grosslein, R. M.; Martin, S.; Mehdi, I.; Smith, P.; Coulomb, M.; DeMartinez, G.

2001-01-01

Frequency multipliers are required as local oscillator sources for frequencies up to 2.7 THz for FIRST and airborne applications. Multipliers at these frequencies have not previously been demonstrated, and the object of this work was to show whether such circuits are really practical. A practical circuit is one which not only performs as well as is required, but also can be replicated in a time that is feasible. As the frequency of circuits is increased, the difficulties in fabrication and assembly increase rapidly. Building all of the circuit on GaAs as a monolithic circuit is highly desirable to minimize the complexity of assembly, but at the highest frequencies, even a complete monolithic circuit is extremely small, and presents serious handling difficulty. This is compounded by the requirement for a very thin substrate. Assembly can become very difficult because of handling problems and critical placement. It is very desirable to make the chip big enough to that it can be seen without magnification, and strong enough that it may be picked up with tweezers. Machined blocks to house the chips present an additional challenge. Blocks with complex features are very expensive, and these also imply very critical assembly of the parts. It would be much better if the features in the block were as simple as possible and non-critical to the function of the chip. In particular, grounding and other electrical interfaces should be done in a manner that is highly reproducible.

Dipole Excitation With A Paul Ion Trap Mass Spectrometer

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

MacAskill, J. A.; Madzunkov, S. M.; Chutjian, A.

Preliminary results are presented for the use of an auxiliary radiofrequency (rf) excitation voltage in combination with a high purity, high voltage rf generator to perform dipole excitation within a high precision Paul ion trap. These results show the effects of the excitation frequency over a continuous frequency range on the resultant mass spectra from the Paul trap with particular emphasis on ion ejection times, ion signal intensity, and peak shapes. Ion ejection times are found to decrease continuously with variations in dipole frequency about several resonant values and show remarkable symmetries. Signal intensities vary in a complex fashion withmore » numerous resonant features and are driven to zero at specific frequency values. Observed intensity variations depict dipole excitations that target ions of all masses as well as individual masses. Substantial increases in mass resolution are obtained with resolving powers for nitrogen increasing from 114 to 325.« less

Evolutionary Algorithm Based Feature Optimization for Multi-Channel EEG Classification.

PubMed

Wang, Yubo; Veluvolu, Kalyana C

2017-01-01

The most BCI systems that rely on EEG signals employ Fourier based methods for time-frequency decomposition for feature extraction. The band-limited multiple Fourier linear combiner is well-suited for such band-limited signals due to its real-time applicability. Despite the improved performance of these techniques in two channel settings, its application in multiple-channel EEG is not straightforward and challenging. As more channels are available, a spatial filter will be required to eliminate the noise and preserve the required useful information. Moreover, multiple-channel EEG also adds the high dimensionality to the frequency feature space. Feature selection will be required to stabilize the performance of the classifier. In this paper, we develop a new method based on Evolutionary Algorithm (EA) to solve these two problems simultaneously. The real-valued EA encodes both the spatial filter estimates and the feature selection into its solution and optimizes it with respect to the classification error. Three Fourier based designs are tested in this paper. Our results show that the combination of Fourier based method with covariance matrix adaptation evolution strategy (CMA-ES) has the best overall performance.

Single trial detection of hand poses in human ECoG using CSP based feature extraction.

PubMed

Kapeller, C; Schneider, C; Kamada, K; Ogawa, H; Kunii, N; Ortner, R; Pruckl, R; Guger, C

2014-01-01

Decoding brain activity of corresponding highlevel tasks may lead to an independent and intuitively controlled Brain-Computer Interface (BCI). Most of today's BCI research focuses on analyzing the electroencephalogram (EEG) which provides only limited spatial and temporal resolution. Derived electrocorticographic (ECoG) signals allow the investigation of spatially highly focused task-related activation within the high-gamma frequency band, making the discrimination of individual finger movements or complex grasping tasks possible. Common spatial patterns (CSP) are commonly used for BCI systems and provide a powerful tool for feature optimization and dimensionality reduction. This work focused on the discrimination of (i) three complex hand movements, as well as (ii) hand movement and idle state. Two subjects S1 and S2 performed single `open', `peace' and `fist' hand poses in multiple trials. Signals in the high-gamma frequency range between 100 and 500 Hz were spatially filtered based on a CSP algorithm for (i) and (ii). Additionally, a manual feature selection approach was tested for (i). A multi-class linear discriminant analysis (LDA) showed for (i) an error rate of 13.89 % / 7.22 % and 18.42 % / 1.17 % for S1 and S2 using manually / CSP selected features, where for (ii) a two class LDA lead to a classification error of 13.39 % and 2.33 % for S1 and S2, respectively.

High-frequency source radiation during the 2011 Tohoku-Oki earthquake, Japan, inferred from KiK-net strong-motion seismograms

NASA Astrophysics Data System (ADS)

Kumagai, Hiroyuki; Pulido, Nelson; Fukuyama, Eiichi; Aoi, Shin

2013-01-01

investigate source processes of the 2011 Tohoku-Oki earthquake, we utilized a source location method using high-frequency (5-10 Hz) seismic amplitudes. In this method, we assumed far-field isotropic radiation of S waves, and conducted a spatial grid search to find the best fitting source locations along the subducted slab in each successive time window. Our application of the method to the Tohoku-Oki earthquake resulted in artifact source locations at shallow depths near the trench caused by limited station coverage and noise effects. We then assumed various source node distributions along the plate, and found that the observed seismograms were most reasonably explained when assuming deep source nodes. This result suggests that the high-frequency seismic waves were radiated at deeper depths during the earthquake, a feature which is consistent with results obtained from teleseismic back-projection and strong-motion source model studies. We identified three high-frequency subevents, and compared them with the moment-rate function estimated from low-frequency seismograms. Our comparison indicated that no significant moment release occurred during the first high-frequency subevent and the largest moment-release pulse occurred almost simultaneously with the second high-frequency subevent. We speculated that the initial slow rupture propagated bilaterally from the hypocenter toward the land and trench. The landward subshear rupture propagation consisted of three successive high-frequency subevents. The trenchward propagation ruptured the strong asperity and released the largest moment near the trench.

High-frequency applications of high-temperature superconductor thin films

NASA Astrophysics Data System (ADS)

Klein, N.

2002-10-01

High-temperature superconducting thin films offer unique properties which can be utilized for a variety of high-frequency device applications in many areas related to the strongly progressing market of information technology. One important property is an exceptionally low level of microwave absorption at temperatures attainable with low power cryocoolers. This unique property has initiated the development of various novel type of microwave devices and commercialized subsystems with special emphasis on application in advanced microwave communication systems. The second important achievement related to efforts in oxide thin and multilayer technology was the reproducible fabrication of low-noise Josephson junctions in high-temperature superconducting thin films. As a consequence of this achievement, several novel nonlinear high-frequency devices, most of them exploiting the unique features of the ac Josephson effect, have been developed and found to exhibit challenging properties to be utilized in basic metrology and Terahertz technology. On the longer timescale, the achievements in integrated high-temperature superconductor circuit technology may offer a strong potential for the development of digital devices with possible clock frequencies in the range of 100 GHz.

There's More to Groove than Bass in Electronic Dance Music: Why Some People Won't Dance to Techno.

PubMed

Wesolowski, Brian C; Hofmann, Alex

2016-01-01

The purpose of this study was to explore the relationship between audio descriptors for groove-based electronic dance music (EDM) and raters' perceived cognitive, affective, and psychomotor responses. From 198 musical excerpts (length: 15 sec.) representing 11 subgenres of EDM, 19 low-level audio feature descriptors were extracted. A principal component analysis of the feature vectors indicated that the musical excerpts could effectively be classified using five complex measures, describing the rhythmical properties of: (a) the high-frequency band, (b) the mid-frequency band, and (c) the low-frequency band, as well as overall fluctuations in (d) dynamics, and (e) timbres. Using these five complex audio measures, four meaningful clusters of the EDM excerpts emerged with distinct musical attributes comprising music with: (a) isochronous bass and static timbres, (b) isochronous bass with fluctuating dynamics and rhythmical variations in the mid-frequency range, (c) non-isochronous bass and fluctuating timbres, and (d) non-isochronous bass with rhythmical variations in the high frequencies. Raters (N = 99) were each asked to respond to four musical excerpts using a four point Likert-Type scale consisting of items representing cognitive (n = 9), affective (n = 9), and psychomotor (n = 3) domains. Musical excerpts falling under the cluster of "non-isochronous bass with rhythmical variations in the high frequencies" demonstrated the overall highest composite scores as evaluated by the raters. Musical samples falling under the cluster of "isochronous bass with static timbres" demonstrated the overall lowest composite scores as evaluated by the raters. Moreover, music preference was shown to significantly affect the systematic patterning of raters' responses for those with a musical preference for "contemporary" music, "sophisticated" music, and "intense" music.

Comparison of Frequency-Domain Array Methods for Studying Earthquake Rupture Process

NASA Astrophysics Data System (ADS)

Sheng, Y.; Yin, J.; Yao, H.

2014-12-01

Seismic array methods, in both time- and frequency- domains, have been widely used to study the rupture process and energy radiation of earthquakes. With better spatial resolution, the high-resolution frequency-domain methods, such as Multiple Signal Classification (MUSIC) (Schimdt, 1986; Meng et al., 2011) and the recently developed Compressive Sensing (CS) technique (Yao et al., 2011, 2013), are revealing new features of earthquake rupture processes. We have performed various tests on the methods of MUSIC, CS, minimum-variance distortionless response (MVDR) Beamforming and conventional Beamforming in order to better understand the advantages and features of these methods for studying earthquake rupture processes. We use the ricker wavelet to synthesize seismograms and use these frequency-domain techniques to relocate the synthetic sources we set, for instance, two sources separated in space but, their waveforms completely overlapping in the time domain. We also test the effects of the sliding window scheme on the recovery of a series of input sources, in particular, some artifacts that are caused by the sliding window scheme. Based on our tests, we find that CS, which is developed from the theory of sparsity inversion, has relatively high spatial resolution than the other frequency-domain methods and has better performance at lower frequencies. In high-frequency bands, MUSIC, as well as MVDR Beamforming, is more stable, especially in the multi-source situation. Meanwhile, CS tends to produce more artifacts when data have poor signal-to-noise ratio. Although these techniques can distinctly improve the spatial resolution, they still produce some artifacts along with the sliding of the time window. Furthermore, we propose a new method, which combines both the time-domain and frequency-domain techniques, to suppress these artifacts and obtain more reliable earthquake rupture images. Finally, we apply this new technique to study the 2013 Okhotsk deep mega earthquake in order to better capture the rupture characteristics (e.g., rupture area and velocity) of this earthquake.

The P Wave Time-Frequency Variability Reflects Atrial Conduction Defects before Paroxysmal Atrial Fibrillation.

PubMed

Alcaraz, Raúl; Martínez, Arturo; Rieta, José J

2015-09-01

The study of atrial conduction defects associated with the onset of paroxysmal atrial fibrillation (PAF) can be addressed by analyzing the P wave from the surface electrocardiogram (ECG). Traditionally, signal-averaged ECGs have been mostly used for this purpose. However, this alternative hinders the possibility to quantify every single P wave, its variability over time, as well as to obtain complimentary and evolving information about the arrhythmia. This work analyzes the time progression of several time and frequency P wave features as potential indicators of atrial conduction variability several hours preceding the onset of PAF. The longest sinus rhythm interval from 24-hour Holter recordings of 46 PAF patients was selected. Next, the 2 hours before the onset of PAF were extracted and divided into two 1-hour periods. Every single P wave was automatically delineated and characterized by 16 time and frequency metrics, such as its duration, absolute energy in several frequency bands and high-to-low-frequency energy ratios. Finally, the P wave variability over each 1-hour period was estimated from the 16 features making use of a least-squares linear fitting. As a reference, the same parameters were also estimated from a set of 1-hour ECG segments randomly chosen from a control group of 53 healthy subjects age-, gender-, and heart rate-matched. All the analyzed metrics provided an increasing P wave variability trend as the onset of PAF approximated, being P wave duration and P wave high-frequency energy the most significant individual metrics. The linear fitting slope α associated with P wave duration was (2.48 ± 1.98)×10(-2) for healthy subjects, (23.8 ± 14.1)×10(-2) for ECG segments far from PAF and for (81.8 ± 48.7)×10(-2) ECG segments close to PAF p = 6.96×10(-22) . Similarly, the P wave high-frequency energy linear fitting slope was (2.42 ± 4.97)×10(-9) , (54.2 ± 107.1)×10(-9) and (274.2 ± 566.1)×10(-9) , respectively (p = 2.85×10(-20) ). A univariate discriminant analysis provided that both P wave duration and P wave high-frequency energy could discern among the three ECG sets with diagnostic ability around 80%, which was improved up to 88% by combining these metrics in a multivariate discriminant analysis. Alterations in atrial conduction can be successfully quantified several hours before the onset of PAF by estimating variability over time of several time and frequency P wave features. © 2014 Wiley Periodicals, Inc.

MMIC Replacement for Gunn Diode Oscillators

NASA Technical Reports Server (NTRS)

Crowe, Thomas W.; Porterfield, David

2011-01-01

An all-solid-state replacement for high-frequency Gunn diode oscillators (GDOs) has been proposed for use in NASA s millimeter- and submillimeter-wave sensing instruments. Highly developed microwave oscillators are used to achieve a low-noise and highly stable reference signal in the 10-40-GHz band. Compact amplifiers and high-power frequency multipliers extend the signal to the 100-500-GHz band with minimal added phase noise and output power sufficient for NASA missions. This technology can achieve improved output power and frequency agility, while maintaining phase noise and stability comparable to other GDOs. Additional developments of the technology include: a frequency quadrupler to 145 GHz with 18 percent efficiency and 15 percent fixed tuned bandwidth; frequency doublers featuring 124, 240, and 480 GHz; an integrated 874-GHz subharmonic mixer with a mixer noise temperature of 3,000 K DSB (double sideband) and mixer conversion loss of 11.8 dB DSB; a high-efficiency frequency tripler design with peak output power of 23 mW and 14 mW, and efficiency of 16 and 13 percent, respectively; millimeter-wave integrated circuit (MMIC) power amplifiers to the 30-40 GHz band with high DC power efficiency; and an 874-GHz radiometer suitable for airborne observation with state-of-the-art sensitivity at room temperature and less than 5 W of total power consumption.

Feature selection and classifier parameters estimation for EEG signals peak detection using particle swarm optimization.

PubMed

Adam, Asrul; Shapiai, Mohd Ibrahim; Tumari, Mohd Zaidi Mohd; Mohamad, Mohd Saberi; Mubin, Marizan

2014-01-01

Electroencephalogram (EEG) signal peak detection is widely used in clinical applications. The peak point can be detected using several approaches, including time, frequency, time-frequency, and nonlinear domains depending on various peak features from several models. However, there is no study that provides the importance of every peak feature in contributing to a good and generalized model. In this study, feature selection and classifier parameters estimation based on particle swarm optimization (PSO) are proposed as a framework for peak detection on EEG signals in time domain analysis. Two versions of PSO are used in the study: (1) standard PSO and (2) random asynchronous particle swarm optimization (RA-PSO). The proposed framework tries to find the best combination of all the available features that offers good peak detection and a high classification rate from the results in the conducted experiments. The evaluation results indicate that the accuracy of the peak detection can be improved up to 99.90% and 98.59% for training and testing, respectively, as compared to the framework without feature selection adaptation. Additionally, the proposed framework based on RA-PSO offers a better and reliable classification rate as compared to standard PSO as it produces low variance model.

Frequency organization and responses to complex sounds in the medial geniculate body of the mustached bat.

PubMed

Wenstrup, J J

1999-11-01

The auditory cortex of the mustached bat (Pteronotus parnellii) displays some of the most highly developed physiological and organizational features described in mammalian auditory cortex. This study examines response properties and organization in the medial geniculate body (MGB) that may contribute to these features of auditory cortex. About 25% of 427 auditory responses had simple frequency tuning with single excitatory tuning curves. The remainder displayed more complex frequency tuning using two-tone or noise stimuli. Most of these were combination-sensitive, responsive to combinations of different frequency bands within sonar or social vocalizations. They included FM-FM neurons, responsive to different harmonic elements of the frequency modulated (FM) sweep in the sonar signal, and H1-CF neurons, responsive to combinations of the bat's first sonar harmonic (H1) and a higher harmonic of the constant frequency (CF) sonar signal. Most combination-sensitive neurons (86%) showed facilitatory interactions. Neurons tuned to frequencies outside the biosonar range also displayed combination-sensitive responses, perhaps related to analyses of social vocalizations. Complex spectral responses were distributed throughout dorsal and ventral divisions of the MGB, forming a major feature of this bat's analysis of complex sounds. The auditory sector of the thalamic reticular nucleus also was dominated by complex spectral responses to sounds. The ventral division was organized tonotopically, based on best frequencies of singly tuned neurons and higher best frequencies of combination-sensitive neurons. Best frequencies were lowest ventrolaterally, increasing dorsally and then ventromedially. However, representations of frequencies associated with higher harmonics of the FM sonar signal were reduced greatly. Frequency organization in the dorsal division was not tonotopic; within the middle one-third of MGB, combination-sensitive responses to second and third harmonic CF sonar signals (60-63 and 90-94 kHz) occurred in adjacent regions. In the rostral one-third, combination-sensitive responses to second, third, and fourth harmonic FM frequency bands predominated. These FM-FM neurons, thought to be selective for delay between an emitted pulse and echo, showed some organization of delay selectivity. The organization of frequency sensitivity in the MGB suggests a major rewiring of the output of the central nucleus of the inferior colliculus, by which collicular neurons tuned to the bat's FM sonar signals mostly project to the dorsal, not the ventral, division. Because physiological differences between collicular and MGB neurons are minor, a major role of the tecto-thalamic projection in the mustached bat may be the reorganization of responses to provide for cortical representations of sonar target features.

Multi-Feature Based Information Extraction of Urban Green Space Along Road

NASA Astrophysics Data System (ADS)

Zhao, H. H.; Guan, H. Y.

2018-04-01

Green space along road of QuickBird image was studied in this paper based on multi-feature-marks in frequency domain. The magnitude spectrum of green along road was analysed, and the recognition marks of the tonal feature, contour feature and the road were built up by the distribution of frequency channels. Gabor filters in frequency domain were used to detect the features based on the recognition marks built up. The detected features were combined as the multi-feature-marks, and watershed based image segmentation were conducted to complete the extraction of green space along roads. The segmentation results were evaluated by Fmeasure with P = 0.7605, R = 0.7639, F = 0.7622.

Dual frequency parametric excitation of a nonlinear, multi degree of freedom mechanical amplifier with electronically modified topology

NASA Astrophysics Data System (ADS)

Dolev, A.; Bucher, I.

2018-04-01

Mechanical or electromechanical amplifiers can exploit the high-Q and low noise features of mechanical resonance, in particular when parametric excitation is employed. Multi-frequency parametric excitation introduces tunability and is able to project weak input signals on a selected resonance. The present paper addresses multi degree of freedom mechanical amplifiers or resonators whose analysis and features require treatment of the spatial as well as temporal behavior. In some cases, virtual electronic coupling can alter the given topology of the resonator to better amplify specific inputs. An analytical development is followed by a numerical and experimental sensitivity and performance verifications, illustrating the advantages and disadvantages of such topologies.

[An Extraction and Recognition Method of the Distributed Optical Fiber Vibration Signal Based on EMD-AWPP and HOSA-SVM Algorithm].

PubMed

Zhang, Yanjun; Liu, Wen-zhe; Fu, Xing-hu; Bi, Wei-hong

2016-02-01

Given that the traditional signal processing methods can not effectively distinguish the different vibration intrusion signal, a feature extraction and recognition method of the vibration information is proposed based on EMD-AWPP and HOSA-SVM, using for high precision signal recognition of distributed fiber optic intrusion detection system. When dealing with different types of vibration, the method firstly utilizes the adaptive wavelet processing algorithm based on empirical mode decomposition effect to reduce the abnormal value influence of sensing signal and improve the accuracy of signal feature extraction. Not only the low frequency part of the signal is decomposed, but also the high frequency part the details of the signal disposed better by time-frequency localization process. Secondly, it uses the bispectrum and bicoherence spectrum to accurately extract the feature vector which contains different types of intrusion vibration. Finally, based on the BPNN reference model, the recognition parameters of SVM after the implementation of the particle swarm optimization can distinguish signals of different intrusion vibration, which endows the identification model stronger adaptive and self-learning ability. It overcomes the shortcomings, such as easy to fall into local optimum. The simulation experiment results showed that this new method can effectively extract the feature vector of sensing information, eliminate the influence of random noise and reduce the effects of outliers for different types of invasion source. The predicted category identifies with the output category and the accurate rate of vibration identification can reach above 95%. So it is better than BPNN recognition algorithm and improves the accuracy of the information analysis effectively.

Relationship Between Frequency and Deflection Angle in the DNA Prism

PubMed Central

Chen, Zhen; Dorfman, Kevin D.

2013-01-01

The DNA prism is a modification of the standard pulsed-field electrophoresis protocol to provide a continuous separation, where the DNA are deflected at an angle that depends on their molecular weight. The standard switchback model for the DNA prism predicts a monotonic increase in the deflection angle as a function of the frequency for switching the field until a plateau regime is reached. However, experiments indicate that the deflection angle achieves a maximum value before decaying to a size-independent value at high frequencies. Using Brownian dynamics simulations, we show that the maximum in the deflection angle is related to the reorientation time for the DNA and the decay in deflection angle at high frequencies is due to inadequate stretching. The generic features of the dependence of the deflection angle on molecular weight, switching frequency, and electric field strength explain a number of experimental phenomena. PMID:23410375

Analysis of Biological Features Associated with Meiotic Recombination Hot and Cold Spots in Saccharomyces cerevisiae

PubMed Central

Hansen, Loren; Kim, Nak-Kyeong; Mariño-Ramírez, Leonardo; Landsman, David

2011-01-01

Meiotic recombination is not distributed uniformly throughout the genome. There are regions of high and low recombination rates called hot and cold spots, respectively. The recombination rate parallels the frequency of DNA double-strand breaks (DSBs) that initiate meiotic recombination. The aim is to identify biological features associated with DSB frequency. We constructed vectors representing various chromatin and sequence-based features for 1179 DSB hot spots and 1028 DSB cold spots. Using a feature selection approach, we have identified five features that distinguish hot from cold spots in Saccharomyces cerevisiae with high accuracy, namely the histone marks H3K4me3, H3K14ac, H3K36me3, and H3K79me3; and GC content. Previous studies have associated H3K4me3, H3K36me3, and GC content with areas of mitotic recombination. H3K14ac and H3K79me3 are novel predictions and thus represent good candidates for further experimental study. We also show nucleosome occupancy maps produced using next generation sequencing exhibit a bias at DSB hot spots and this bias is strong enough to obscure biologically relevant information. A computational approach using feature selection can productively be used to identify promising biological associations. H3K14ac and H3K79me3 are novel predictions of chromatin marks associated with meiotic DSBs. Next generation sequencing can exhibit a bias that is strong enough to lead to incorrect conclusions. Care must be taken when interpreting high throughput sequencing data where systematic biases have been documented. PMID:22242140

Dynamics of Active Separation Control at High Reynolds Numbers

NASA Technical Reports Server (NTRS)

Pack, LaTunia G.; Seifert, Avi

2000-01-01

A series of active flow control experiments were recently conducted at high Reynolds numbers on a generic separated configuration. The model simulates the upper surface of a 20% thick Glauert-Goldschmied type airfoil at zero angle of attack. The flow is fully turbulent since the tunnel sidewall boundary layer flows over the model. The main motivation for the experiments is to generate a comprehensive data base for validation of unsteady numerical simulation as a first step in the development of a CFD design tool, without which it would not be possible to effectively utilize the great potential of unsteady flow control. This paper focuses on the dynamics of several key features of the baseline as well as the controlled flow. It was found that the thickness of the upstream boundary layer has a negligible effect on the flow dynamics. It is speculated that separation is caused mainly by the highly convex surface while viscous effects are less important. The two-dimensional separated flow contains unsteady waves centered on a reduced frequency of 0.9, while in the three dimensional separated flow, frequencies around a reduced frequency of 0.3 and 1 are active. Several scenarios of resonant wave interaction take place at the separated shear-layer and in the pressure recovery region. The unstable reduced frequency bands for periodic excitation are centered on 1.5 and 5, but these reduced frequencies are based on the length of the baseline bubble that shortens due to the excitation. The conventional works well for the coherent wave features. Reproduction of these dynamic effects by a numerical simulation would provide benchmark validation.

Large scale modulation of high frequency acoustic waves in periodic porous media.

PubMed

Boutin, Claude; Rallu, Antoine; Hans, Stephane

2012-12-01

This paper deals with the description of the modulation at large scale of high frequency acoustic waves in gas saturated periodic porous media. High frequencies mean local dynamics at the pore scale and therefore absence of scale separation in the usual sense of homogenization. However, although the pressure is spatially varying in the pores (according to periodic eigenmodes), the mode amplitude can present a large scale modulation, thereby introducing another type of scale separation to which the asymptotic multi-scale procedure applies. The approach is first presented on a periodic network of inter-connected Helmholtz resonators. The equations governing the modulations carried by periodic eigenmodes, at frequencies close to their eigenfrequency, are derived. The number of cells on which the carrying periodic mode is defined is therefore a parameter of the modeling. In a second part, the asymptotic approach is developed for periodic porous media saturated by a perfect gas. Using the "multicells" periodic condition, one obtains the family of equations governing the amplitude modulation at large scale of high frequency waves. The significant difference between modulations of simple and multiple mode are evidenced and discussed. The features of the modulation (anisotropy, width of frequency band) are also analyzed.

Inter-annual and decadal changes in teleconnections drive continental-scale synchronization of tree reproduction.

PubMed

Ascoli, Davide; Vacchiano, Giorgio; Turco, Marco; Conedera, Marco; Drobyshev, Igor; Maringer, Janet; Motta, Renzo; Hacket-Pain, Andrew

2017-12-20

Climate teleconnections drive highly variable and synchronous seed production (masting) over large scales. Disentangling the effect of high-frequency (inter-annual variation) from low-frequency (decadal trends) components of climate oscillations will improve our understanding of masting as an ecosystem process. Using century-long observations on masting (the MASTREE database) and data on the Northern Atlantic Oscillation (NAO), we show that in the last 60 years both high-frequency summer and spring NAO, and low-frequency winter NAO components are highly correlated to continent-wide masting in European beech and Norway spruce. Relationships are weaker (non-stationary) in the early twentieth century. This finding improves our understanding on how climate variation affects large-scale synchronization of tree masting. Moreover, it supports the connection between proximate and ultimate causes of masting: indeed, large-scale features of atmospheric circulation coherently drive cues and resources for masting, as well as its evolutionary drivers, such as pollination efficiency, abundance of seed dispersers, and natural disturbance regimes.

A study of some features of ac and dc electric power systems for a space station

NASA Technical Reports Server (NTRS)

Hanania, J. I.

1983-01-01

This study analyzes certain selected topics in rival dc and high frequency ac electric power systems for a Space Station. The interaction between the Space Station and the plasma environment is analyzed, leading to a limit on the voltage for the solar array and a potential problem with resonance coupling at high frequencies. Certain problems are pointed out in the concept of a rotary transformer, and further development work is indicated in connection with dc circuit switching, special design of a transmission conductor for the ac system, and electric motors. The question of electric shock hazards, particularly at high frequency, is also explored. and a problem with reduced skin resistance and therefore increased hazard with high frequency ac is pointed out. The study concludes with a comparison of the main advantages and disadvantages of the two rival systems, and it is suggested that the choice between the two should be made after further studies and development work are completed.

Use of Sine Shaped High-Frequency Rhythmic Visual Stimuli Patterns for SSVEP Response Analysis and Fatigue Rate Evaluation in Normal Subjects

PubMed Central

Keihani, Ahmadreza; Shirzhiyan, Zahra; Farahi, Morteza; Shamsi, Elham; Mahnam, Amin; Makkiabadi, Bahador; Haidari, Mohsen R.; Jafari, Amir H.

2018-01-01

Background: Recent EEG-SSVEP signal based BCI studies have used high frequency square pulse visual stimuli to reduce subjective fatigue. However, the effect of total harmonic distortion (THD) has not been considered. Compared to CRT and LCD monitors, LED screen displays high-frequency wave with better refresh rate. In this study, we present high frequency sine wave simple and rhythmic patterns with low THD rate by LED to analyze SSVEP responses and evaluate subjective fatigue in normal subjects. Materials and Methods: We used patterns of 3-sequence high-frequency sine waves (25, 30, and 35 Hz) to design our visual stimuli. Nine stimuli patterns, 3 simple (repetition of each of above 3 frequencies e.g., P25-25-25) and 6 rhythmic (all of the frequencies in 6 different sequences e.g., P25-30-35) were chosen. A hardware setup with low THD rate (<0.1%) was designed to present these patterns on LED. Twenty two normal subjects (aged 23–30 (25 ± 2.1) yrs) were enrolled. Visual analog scale (VAS) was used for subjective fatigue evaluation after presentation of each stimulus pattern. PSD, CCA, and LASSO methods were employed to analyze SSVEP responses. The data including SSVEP features and fatigue rate for different visual stimuli patterns were statistically evaluated. Results: All 9 visual stimuli patterns elicited SSVEP responses. Overall, obtained accuracy rates were 88.35% for PSD and > 90% for CCA and LASSO (for TWs > 1 s). High frequency rhythmic patterns group with low THD rate showed higher accuracy rate (99.24%) than simple patterns group (98.48%). Repeated measure ANOVA showed significant difference between rhythmic pattern features (P < 0.0005). Overall, there was no significant difference between the VAS of rhythmic [3.85 ± 2.13] compared to the simple patterns group [3.96 ± 2.21], (P = 0.63). Rhythmic group had lower within group VAS variation (min = P25-30-35 [2.90 ± 2.45], max = P35-25-30 [4.81 ± 2.65]) as well as least individual pattern VAS (P25-30-35). Discussion and Conclusion: Overall, rhythmic and simple pattern groups had higher and similar accuracy rates. Rhythmic stimuli patterns showed insignificantly lower fatigue rate than simple patterns. We conclude that both rhythmic and simple visual high frequency sine wave stimuli require further research for human subject SSVEP-BCI studies. PMID:29892219

Use of Sine Shaped High-Frequency Rhythmic Visual Stimuli Patterns for SSVEP Response Analysis and Fatigue Rate Evaluation in Normal Subjects.

PubMed

Keihani, Ahmadreza; Shirzhiyan, Zahra; Farahi, Morteza; Shamsi, Elham; Mahnam, Amin; Makkiabadi, Bahador; Haidari, Mohsen R; Jafari, Amir H

2018-01-01

Background: Recent EEG-SSVEP signal based BCI studies have used high frequency square pulse visual stimuli to reduce subjective fatigue. However, the effect of total harmonic distortion (THD) has not been considered. Compared to CRT and LCD monitors, LED screen displays high-frequency wave with better refresh rate. In this study, we present high frequency sine wave simple and rhythmic patterns with low THD rate by LED to analyze SSVEP responses and evaluate subjective fatigue in normal subjects. Materials and Methods: We used patterns of 3-sequence high-frequency sine waves (25, 30, and 35 Hz) to design our visual stimuli. Nine stimuli patterns, 3 simple (repetition of each of above 3 frequencies e.g., P25-25-25) and 6 rhythmic (all of the frequencies in 6 different sequences e.g., P25-30-35) were chosen. A hardware setup with low THD rate (<0.1%) was designed to present these patterns on LED. Twenty two normal subjects (aged 23-30 (25 ± 2.1) yrs) were enrolled. Visual analog scale (VAS) was used for subjective fatigue evaluation after presentation of each stimulus pattern. PSD, CCA, and LASSO methods were employed to analyze SSVEP responses. The data including SSVEP features and fatigue rate for different visual stimuli patterns were statistically evaluated. Results: All 9 visual stimuli patterns elicited SSVEP responses. Overall, obtained accuracy rates were 88.35% for PSD and > 90% for CCA and LASSO (for TWs > 1 s). High frequency rhythmic patterns group with low THD rate showed higher accuracy rate (99.24%) than simple patterns group (98.48%). Repeated measure ANOVA showed significant difference between rhythmic pattern features ( P < 0.0005). Overall, there was no significant difference between the VAS of rhythmic [3.85 ± 2.13] compared to the simple patterns group [3.96 ± 2.21], ( P = 0.63). Rhythmic group had lower within group VAS variation (min = P25-30-35 [2.90 ± 2.45], max = P35-25-30 [4.81 ± 2.65]) as well as least individual pattern VAS (P25-30-35). Discussion and Conclusion: Overall, rhythmic and simple pattern groups had higher and similar accuracy rates. Rhythmic stimuli patterns showed insignificantly lower fatigue rate than simple patterns. We conclude that both rhythmic and simple visual high frequency sine wave stimuli require further research for human subject SSVEP-BCI studies.

Cloud and convection frequencies over the southeast United States as related to small-scale geographic features

NASA Technical Reports Server (NTRS)

Gibson, Harold M.; Vonder Haar, Thomas H.

1990-01-01

Based on relatively high spatial and temporal resolution satelite data collected at 0700 CST and at each hour from 1000 CST to 1700 CST during the summer of 1986, cloud and convection variations over the area from Mississippi east to Georgia and from the Gulf of Mexico north to Tennessee are discussed. The data analyses show an average maximum cloud frequency over the land areas at 1400 local time and a maximum of deep convection one hour later. Both cloudiness and deep convection are found to be at a maximum during the nocturnal hours over the Gulf of Mexico. Cloud frequency shows a strong relationship to small terrain features. Small fresh water bodies have cloud minima relative to the surroundings in the afternoon hours. Higher, steep terrain shows cloud maxima and the adjacent lower terrain exhibits afternoon cloud minima due to a divergence of mountain breeze caused by the valley.

Improving Thin Bed Identification in Sarawak Basin Field using Short Time Fourier Transform Half Cepstrum (STFTHC) method

NASA Astrophysics Data System (ADS)

Nizarul, O.; Hermana, M.; Bashir, Y.; Ghosh, D. P.

2016-02-01

In delineating complex subsurface geological feature, broad band of frequencies are needed to unveil the often hidden features of hydrocarbon basin such as thin bedding. The ability to resolve thin geological horizon on seismic data is recognized to be a fundamental importance for hydrocarbon exploration, seismic interpretation and reserve prediction. For thin bedding, high frequency content is needed to enable tuning, which can be done by applying the band width extension technique. This paper shows an application of Short Time Fourier Transform Half Cepstrum (STFTHC) method, a frequency bandwidth expansion technique for non-stationary seismic signal in increasing the temporal resolution to uncover thin beds and improve characterization of the basin. A wedge model and synthetic seismic data is used to quantify the algorithm as well as real data from Sarawak basin were used to show the effectiveness of this method in enhancing the resolution.

First observations of stimulated electromagnetic emission in the ionosphere modified by the spear heating facility on Spitsbergen

NASA Astrophysics Data System (ADS)

Tereshchenko, E. D.; Yurik, R. Yu.; Yeoman, T. K.; Robinson, T. R.

2008-11-01

We present the first results of observations of the stimulated electromagnetic emission (SEE) in the ionosphere modified by the Space Plasma Exploration by Active Radar (SPEAR) heating facility. Observation of the SEE is the key method of ground-based diagnostics of the ionospheric plasma disturbances due to high-power HF radiation. The presented results were obtained during the heating campaign performed at the SPEAR facility in February-March 2007. Prominent SEE special features were observed in periods in which the critical frequency of the F 2 layer was higher than the pump-wave frequency (4.45 MHz). As an example, such special features as the downshifted maximum and the broad continuum in the region of negative detunings from the pump-wave frequency are presented. Observations clearly demonstrate that the ionosphere was efficiently excited by the SPEAR heating facility despite the comparatively low pump-wave power.

Task-induced frequency modulation features for brain-computer interfacing

NASA Astrophysics Data System (ADS)

Jayaram, Vinay; Hohmann, Matthias; Just, Jennifer; Schölkopf, Bernhard; Grosse-Wentrup, Moritz

2017-10-01

Objective. Task-induced amplitude modulation of neural oscillations is routinely used in brain-computer interfaces (BCIs) for decoding subjects’ intents, and underlies some of the most robust and common methods in the field, such as common spatial patterns and Riemannian geometry. While there has been some interest in phase-related features for classification, both techniques usually presuppose that the frequencies of neural oscillations remain stable across various tasks. We investigate here whether features based on task-induced modulation of the frequency of neural oscillations enable decoding of subjects’ intents with an accuracy comparable to task-induced amplitude modulation. Approach. We compare cross-validated classification accuracies using the amplitude and frequency modulated features, as well as a joint feature space, across subjects in various paradigms and pre-processing conditions. We show results with a motor imagery task, a cognitive task, and also preliminary results in patients with amyotrophic lateral sclerosis (ALS), as well as using common spatial patterns and Laplacian filtering. Main results. The frequency features alone do not significantly out-perform traditional amplitude modulation features, and in some cases perform significantly worse. However, across both tasks and pre-processing in healthy subjects the joint space significantly out-performs either the frequency or amplitude features alone. This result only does not hold for ALS patients, for whom the dataset is of insufficient size to draw any statistically significant conclusions. Significance. Task-induced frequency modulation is robust and straight forward to compute, and increases performance when added to standard amplitude modulation features across paradigms. This allows more information to be extracted from the EEG signal cheaply and can be used throughout the field of BCIs.

Routes to spatiotemporal chaos in Kerr optical frequency combs.

PubMed

Coillet, Aurélien; Chembo, Yanne K

2014-03-01

We investigate the various routes to spatiotemporal chaos in Kerr optical frequency combs, obtained through pumping an ultra-high Q-factor whispering-gallery mode resonator with a continuous-wave laser. The Lugiato-Lefever model is used to build bifurcation diagrams with regards to the parameters that are externally controllable, namely, the frequency and the power of the pumping laser. We show that the spatiotemporal chaos emerging from Turing patterns and solitons display distinctive dynamical features. Experimental spectra of chaotic Kerr combs are also presented for both cases, in excellent agreement with theoretical spectra.

High-frequency effects in antiferromagnetic Sr3Ir2O7

NASA Astrophysics Data System (ADS)

Williamson, Morgan; Seinige, Heidi; Shen, Shida; Wang, Cheng; Cao, Gang; Zhou, Jianshi; Goodenough, John; Tsoi, Maxim

Antiferromagnetic (AFM) spintronics is one of many promising routes for `beyond the CMOS' technologies where unique properties of AFM materials are exploited to achieve new and improved functionalities. AFMs are especially interesting for high-speed memory applications thanks to their high natural frequencies. Here we report the effects of high-frequency (microwave) currents on transport properties of antiferromagnetic Mott insulator Sr3Ir2O7. The microwaves at 3-7 GHz were found to affect the material's current-voltage characteristic and produce resonance-like features that we tentatively associate with the dissipationless magnonics recently predicted to occur in antiferromagnetic insulators subject to ac electric fields. Our observations support the potential of antiferromagnetic materials for high-speed/high-frequency spintronic applications. This work was supported in part by C-SPIN, one of six centers of STARnet, a Semiconductor Research Corporation program, sponsored by MARCO and DARPA, by NSF Grants DMR-1207577, DMR-1265162, DMR-1600057, and DMR-1122603, and by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award No. OSR-2015-CRG4-2626.

Classification of radiological errors in chest radiographs, using support vector machine on the spatial frequency features of false- negative and false-positive regions

NASA Astrophysics Data System (ADS)

Pietrzyk, Mariusz W.; Donovan, Tim; Brennan, Patrick C.; Dix, Alan; Manning, David J.

2011-03-01

Aim: To optimize automated classification of radiological errors during lung nodule detection from chest radiographs (CxR) using a support vector machine (SVM) run on the spatial frequency features extracted from the local background of selected regions. Background: The majority of the unreported pulmonary nodules are visually detected but not recognized; shown by the prolonged dwell time values at false-negative regions. Similarly, overestimated nodule locations are capturing substantial amounts of foveal attention. Spatial frequency properties of selected local backgrounds are correlated with human observer responses either in terms of accuracy in indicating abnormality position or in the precision of visual sampling the medical images. Methods: Seven radiologists participated in the eye tracking experiments conducted under conditions of pulmonary nodule detection from a set of 20 postero-anterior CxR. The most dwelled locations have been identified and subjected to spatial frequency (SF) analysis. The image-based features of selected ROI were extracted with un-decimated Wavelet Packet Transform. An analysis of variance was run to select SF features and a SVM schema was implemented to classify False-Negative and False-Positive from all ROI. Results: A relative high overall accuracy was obtained for each individually developed Wavelet-SVM algorithm, with over 90% average correct ratio for errors recognition from all prolonged dwell locations. Conclusion: The preliminary results show that combined eye-tracking and image-based features can be used for automated detection of radiological error with SVM. The work is still in progress and not all analytical procedures have been completed, which might have an effect on the specificity of the algorithm.

Multidimensional analysis of the abnormal neural oscillations associated with lexical processing in schizophrenia.

PubMed

Xu, Tingting; Stephane, Massoud; Parhi, Keshab K

2013-04-01

The neural mechanisms of language abnormalities, the core symptoms in schizophrenia, remain unclear. In this study, a new experimental paradigm, combining magnetoencephalography (MEG) techniques and machine intelligence methodologies, was designed to gain knowledge about the frequency, brain location, and time of occurrence of the neural oscillations that are associated with lexical processing in schizophrenia. The 248-channel MEG recordings were obtained from 12 patients with schizophrenia and 10 healthy controls, during a lexical processing task, where the patients discriminated correct from incorrect lexical stimuli that were visually presented. Event-related desynchronization/synchronization (ERD/ERS) was computed along the frequency, time, and space dimensions combined, that resulted in a large spectral-spatial-temporal ERD/ERS feature set. Machine intelligence techniques were then applied to select a small subset of oscillation patterns that are abnormal in patients with schizophrenia, according to their discriminating power in patient and control classification. Patients with schizophrenia showed abnormal ERD/ERS patterns during both lexical encoding and post-encoding periods. The top-ranked features were located at the occipital and left frontal-temporal areas, and covered a wide frequency range, including δ (1-4 Hz), α (8-12 Hz), β (12-32 Hz), and γ (32-48 Hz) bands. These top features could discriminate the patient group from the control group with 90.91% high accuracy, which demonstrates significant brain oscillation abnormalities in patients with schizophrenia at the specific frequency, time, and brain location indicated by these top features. As neural oscillation abnormality may be due to the mechanisms of the disease, the spectral, spatial, and temporal content of the discriminating features can offer useful information for helping understand the physiological basis of the language disorder in schizophrenia, as well as the pathology of the disease itself.

Functional feature embedded space mapping of fMRI data.

PubMed

Hu, Jin; Tian, Jie; Yang, Lei

2006-01-01

We have proposed a new method for fMRI data analysis which is called Functional Feature Embedded Space Mapping (FFESM). Our work mainly focuses on the experimental design with periodic stimuli which can be described by a number of Fourier coefficients in the frequency domain. A nonlinear dimension reduction technique Isomap is applied to the high dimensional features obtained from frequency domain of the fMRI data for the first time. Finally, the presence of activated time series is identified by the clustering method in which the information theoretic criterion of minimum description length (MDL) is used to estimate the number of clusters. The feasibility of our algorithm is demonstrated by real human experiments. Although we focus on analyzing periodic fMRI data, the approach can be extended to analyze non-periodic fMRI data (event-related fMRI) by replacing the Fourier analysis with a wavelet analysis.

Protein attributes contribute to halo-stability, bioinformatics approach

PubMed Central

2011-01-01

Halophile proteins can tolerate high salt concentrations. Understanding halophilicity features is the first step toward engineering halostable crops. To this end, we examined protein features contributing to the halo-toleration of halophilic organisms. We compared more than 850 features for halophilic and non-halophilic proteins with various screening, clustering, decision tree, and generalized rule induction models to search for patterns that code for halo-toleration. Up to 251 protein attributes selected by various attribute weighting algorithms as important features contribute to halo-stability; from them 14 attributes selected by 90% of models and the count of hydrogen gained the highest value (1.0) in 70% of attribute weighting models, showing the importance of this attribute in feature selection modeling. The other attributes mostly were the frequencies of di-peptides. No changes were found in the numbers of groups when K-Means and TwoStep clustering modeling were performed on datasets with or without feature selection filtering. Although the depths of induced trees were not high, the accuracies of trees were higher than 94% and the frequency of hydrophobic residues pointed as the most important feature to build trees. The performance evaluation of decision tree models had the same values and the best correctness percentage recorded with the Exhaustive CHAID and CHAID models. We did not find any significant difference in the percent of correctness, performance evaluation, and mean correctness of various decision tree models with or without feature selection. For the first time, we analyzed the performance of different screening, clustering, and decision tree algorithms for discriminating halophilic and non-halophilic proteins and the results showed that amino acid composition can be used to discriminate between halo-tolerant and halo-sensitive proteins. PMID:21592393

Signal recognition and parameter estimation of BPSK-LFM combined modulation

NASA Astrophysics Data System (ADS)

Long, Chao; Zhang, Lin; Liu, Yu

2015-07-01

Intra-pulse analysis plays an important role in electronic warfare. Intra-pulse feature abstraction focuses on primary parameters such as instantaneous frequency, modulation, and symbol rate. In this paper, automatic modulation recognition and feature extraction for combined BPSK-LFM modulation signals based on decision theoretic approach is studied. The simulation results show good recognition effect and high estimation precision, and the system is easy to be realized.

Flow and Acoustic Features of a Mach 0.9 Free Jet Using High-Frequency Excitation

NASA Astrophysics Data System (ADS)

Upadhyay, Puja; Alvi, Farrukh

2016-11-01

This study focuses on active control of a Mach 0.9 (ReD = 6 ×105) free jet using high-frequency excitation for noise reduction. Eight resonance-enhanced microjet actuators with nominal frequencies of 25 kHz (StD 2 . 2) are used to excite the shear layer at frequencies that are approximately an order of magnitude higher than the jet preferred frequency. The influence of control on mean and turbulent characteristics of the jet is studied using Particle Image Velocimetry. Additionally, far-field acoustic measurements are acquired to estimate the effect of pulsed injection on noise characteristics of the jet. Flow field measurements revealed that strong streamwise vortex pairs, formed as a result of control, result in a significantly thicker initial shear layer. This excited shear layer is also prominently undulated, resulting in a modified initial velocity profile. Also, the distribution of turbulent kinetic energy revealed that forcing results in increased turbulence levels for near-injection regions, followed by a global reduction for all downstream locations. Far-field acoustic measurements showed noise reductions at low to moderate frequencies. Additionally, an increase in high-frequency noise, mostly dominated by the actuators' resonant noise, was observed. AFOSR and ARO.

Learning Scene Categories from High Resolution Satellite Image for Aerial Video Analysis

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

Cheriyadat, Anil M

2011-01-01

Automatic scene categorization can benefit various aerial video processing applications. This paper addresses the problem of predicting the scene category from aerial video frames using a prior model learned from satellite imagery. We show that local and global features in the form of line statistics and 2-D power spectrum parameters respectively can characterize the aerial scene well. The line feature statistics and spatial frequency parameters are useful cues to distinguish between different urban scene categories. We learn the scene prediction model from highresolution satellite imagery to test the model on the Columbus Surrogate Unmanned Aerial Vehicle (CSUAV) dataset ollected bymore » high-altitude wide area UAV sensor platform. e compare the proposed features with the popular Scale nvariant Feature Transform (SIFT) features. Our experimental results show that proposed approach outperforms te SIFT model when the training and testing are conducted n disparate data sources.« less

Discriminative spatial-frequency-temporal feature extraction and classification of motor imagery EEG: An sparse regression and Weighted Naïve Bayesian Classifier-based approach.

PubMed

Miao, Minmin; Zeng, Hong; Wang, Aimin; Zhao, Changsen; Liu, Feixiang

2017-02-15

Common spatial pattern (CSP) is most widely used in motor imagery based brain-computer interface (BCI) systems. In conventional CSP algorithm, pairs of the eigenvectors corresponding to both extreme eigenvalues are selected to construct the optimal spatial filter. In addition, an appropriate selection of subject-specific time segments and frequency bands plays an important role in its successful application. This study proposes to optimize spatial-frequency-temporal patterns for discriminative feature extraction. Spatial optimization is implemented by channel selection and finding discriminative spatial filters adaptively on each time-frequency segment. A novel Discernibility of Feature Sets (DFS) criteria is designed for spatial filter optimization. Besides, discriminative features located in multiple time-frequency segments are selected automatically by the proposed sparse time-frequency segment common spatial pattern (STFSCSP) method which exploits sparse regression for significant features selection. Finally, a weight determined by the sparse coefficient is assigned for each selected CSP feature and we propose a Weighted Naïve Bayesian Classifier (WNBC) for classification. Experimental results on two public EEG datasets demonstrate that optimizing spatial-frequency-temporal patterns in a data-driven manner for discriminative feature extraction greatly improves the classification performance. The proposed method gives significantly better classification accuracies in comparison with several competing methods in the literature. The proposed approach is a promising candidate for future BCI systems. Copyright © 2016 Elsevier B.V. All rights reserved.

Robust spike classification based on frequency domain neural waveform features.

PubMed

Yang, Chenhui; Yuan, Yuan; Si, Jennie

2013-12-01

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

Distinguishing mechanisms of gamma frequency oscillations in human current source signals using a computational model of a laminar neocortical network

PubMed Central

Lee, Shane; Jones, Stephanie R.

2013-01-01

Gamma frequency rhythms have been implicated in numerous studies for their role in healthy and abnormal brain function. The frequency band has been described to encompass as broad a range as 30–150 Hz. Crucial to understanding the role of gamma in brain function is an identification of the underlying neural mechanisms, which is particularly difficult in the absence of invasive recordings in macroscopic human signals such as those from magnetoencephalography (MEG) and electroencephalography (EEG). Here, we studied features of current dipole (CD) signals from two distinct mechanisms of gamma generation, using a computational model of a laminar cortical circuit designed specifically to simulate CDs in a biophysically principled manner (Jones et al., 2007, 2009). We simulated spiking pyramidal interneuronal gamma (PING) whose period is regulated by the decay time constant of GABAA-mediated synaptic inhibition and also subthreshold gamma driven by gamma-periodic exogenous excitatory synaptic drive. Our model predicts distinguishable CD features created by spiking PING compared to subthreshold driven gamma that can help to disambiguate mechanisms of gamma oscillations in human signals. We found that gamma rhythms in neocortical layer 5 can obscure a simultaneous, independent gamma in layer 2/3. Further, we arrived at a novel interpretation of the origin of high gamma frequency rhythms (100–150 Hz), showing that they emerged from a specific temporal feature of CDs associated with single cycles of PING activity and did not reflect a separate rhythmic process. Last we show that the emergence of observable subthreshold gamma required highly coherent exogenous drive. Our results are the first to demonstrate features of gamma oscillations in human current source signals that distinguish cellular and circuit level mechanisms of these rhythms and may help to guide understanding of their functional role. PMID:24385958

Nothing more than a pair of curvatures: A common mechanism for the detection of both radial and non-radial frequency patterns.

PubMed

Schmidtmann, Gunnar; Kingdom, Frederick A A

2017-05-01

Radial frequency (RF) patterns, which are sinusoidal modulations of a radius in polar coordinates, are commonly used to study shape perception. Previous studies have argued that the detection of RF patterns is either achieved globally by a specialized global shape mechanism, or locally using as cue the maximum tangent orientation difference between the RF pattern and the circle. Here we challenge both ideas and suggest instead a model that accounts not only for the detection of RF patterns but also for line frequency patterns (LF), i.e. contours sinusoidally modulated around a straight line. The model has two features. The first is that the detection of both RF and LF patterns is based on curvature differences along the contour. The second is that this curvature metric is subject to what we term the Curve Frequency Sensitivity Function, or CFSF, which is characterized by a flat followed by declining response to curvature as a function of modulation frequency, analogous to the modulation transfer function of the eye. The evidence that curvature forms the basis for detection is that at very low modulation frequencies (1-3 cycles for the RF pattern) there is a dramatic difference in thresholds between the RF and LF patterns, a difference however that disappears at medium and high modulation frequencies. The CFSF feature on the other hand explains why thresholds, rather than continuously declining with modulation frequency, asymptote at medium and high modulation frequencies. In summary, our analysis suggests that the detection of shape modulations is processed by a common curvature-sensitive mechanism that is subject to a shape-frequency-dependent transfer function. This mechanism is independent of whether the modulation is applied to a circle or a straight line. Copyright © 2017 Elsevier Ltd. All rights reserved.

High-frequency chaotic dynamics enabled by optical phase-conjugation

PubMed Central

Mercier, Émeric; Wolfersberger, Delphine; Sciamanna, Marc

2016-01-01

Wideband chaos is of interest for applications such as random number generation or encrypted communications, which typically use optical feedback in a semiconductor laser. Here, we show that replacing conventional optical feedback with phase-conjugate feedback improves the chaos bandwidth. In the range of achievable phase-conjugate mirror reflectivities, the bandwidth increase reaches 27% when compared with feedback from a conventional mirror. Experimental measurements of the time-resolved frequency dynamics on nanosecond time-scales show that the bandwidth enhancement is related to the onset of self-pulsing solutions at harmonics of the external-cavity frequency. In the observed regime, the system follows a chaotic itinerancy among these destabilized high-frequency external-cavity modes. The recorded features are unique to phase-conjugate feedback and distinguish it from the long-standing problem of time-delayed feedback dynamics. PMID:26739806

Femtosecond Raman-Induced Kerr Effect Study of Temperature-Dependent Intermolecular Dynamics in Molten Bis(trifluoromethylsulfonyl)amide Salts: Effects of Cation Species.

PubMed

Kakinuma, Shohei; Shirota, Hideaki

2018-05-25

In this study, we have investigated the effects of cation structures on the temperature dependence of the intermolecular vibrational dynamics of ionic liquids using femtosecond Raman-induced Kerr effect spectroscopy. The ionic liquids used in this study are bis(trifluoromethylsulfonyl)amide [NTf 2 ] - salts of the cations 1-butyl-3-methylimidazolium [C 4 MIm] + , 1-butyl-1-methylpyrrolidinium [Pyrr 14 ] + , 1-butylpyridinium [C 4 Py] + , butyldiethylmethylammonium [N 1224 ] + , triethyloctylammonium [N 2228 ] + , and triethyloctylphosphonium [P 2228 ] + . All of the ionic liquids show temperature-dependent low-frequency spectra. A difference in the temperature dependence between the spectra of the aromatic and nonaromatic cation based ionic liquids is especially significant. In the case of the aromatic cation based ionic liquids [C 4 MIm][NTf 2 ] and [C 4 Py][NTf 2 ], the spectral intensities in the low-frequency region below ca. 50 cm -1 increase and the high-frequency components at ca. 80 cm -1 shift to lower frequencies with rising temperature. In contrast, the ionic liquids based on nonaromatic cations only exhibit an increase in the low-frequency region below ca. 50 cm -1 with increasing temperature, while the high-frequency region of the spectra above ca. 50 cm -1 shows little change with variation of the temperature. These results suggest that the presence or absence of aromatic rings is the main factor in determining the temperature-dependent spectral features, particularly in the high-frequency region. We also found that the alkyl chain length and central atoms of the nonaromatic quaternary cations do not have much influence on the temperature-dependent spectral features. The first moments of the aromatic cation based ionic liquids are a little more sensitive to temperature than those of the nonaromatic cation based ionic liquids. The temperature-dependent viscosities and fragilities of the ionic liquids have also been examined.

Exploring the time-frequency content of high frequency oscillations for automated identification of seizure onset zone in epilepsy.

PubMed

Liu, Su; Sha, Zhiyi; Sencer, Altay; Aydoseli, Aydin; Bebek, Nerse; Abosch, Aviva; Henry, Thomas; Gurses, Candan; Ince, Nuri Firat

2016-04-01

High frequency oscillations (HFOs) in intracranial electroencephalography (iEEG) recordings are considered as promising clinical biomarkers of epileptogenic regions in the brain. The aim of this study is to improve and automatize the detection of HFOs by exploring the time-frequency content of iEEG and to investigate the seizure onset zone (SOZ) detection accuracy during the sleep, awake and pre-ictal states in patients with epilepsy, for the purpose of assisting the localization of SOZ in clinical practice. Ten-minute iEEG segments were defined during different states in eight patients with refractory epilepsy. A three-stage algorithm was implemented to detect HFOs in these segments. First, an amplitude based initial detection threshold was used to generate a large pool of HFO candidates. Then distinguishing features were extracted from the time and time-frequency domain of the raw iEEG and used with a Gaussian mixture model clustering to isolate HFO events from other activities. The spatial distribution of HFO clusters was correlated with the seizure onset channels identified by neurologists in seven patient with good surgical outcome. The overlapping rates of localized channels and seizure onset locations were high in all states. The best result was obtained using the iEEG data during sleep, achieving a sensitivity of 81%, and a specificity of 96%. The channels with maximum number of HFOs identified epileptogenic areas where the seizures occurred more frequently. The current study was conducted using iEEG data collected in realistic clinical conditions without channel pre-exclusion. HFOs were investigated with novel features extracted from the entire frequency band, and were correlated with SOZ in different states. The results indicate that automatic HFO detection with unsupervised clustering methods exploring the time-frequency content of raw iEEG can be efficiently used to identify the epileptogenic zone with an accurate and efficient manner.

Prediction of cause of death from forensic autopsy reports using text classification techniques: A comparative study.

PubMed

Mujtaba, Ghulam; Shuib, Liyana; Raj, Ram Gopal; Rajandram, Retnagowri; Shaikh, Khairunisa

2018-07-01

Automatic text classification techniques are useful for classifying plaintext medical documents. This study aims to automatically predict the cause of death from free text forensic autopsy reports by comparing various schemes for feature extraction, term weighing or feature value representation, text classification, and feature reduction. For experiments, the autopsy reports belonging to eight different causes of death were collected, preprocessed and converted into 43 master feature vectors using various schemes for feature extraction, representation, and reduction. The six different text classification techniques were applied on these 43 master feature vectors to construct a classification model that can predict the cause of death. Finally, classification model performance was evaluated using four performance measures i.e. overall accuracy, macro precision, macro-F-measure, and macro recall. From experiments, it was found that that unigram features obtained the highest performance compared to bigram, trigram, and hybrid-gram features. Furthermore, in feature representation schemes, term frequency, and term frequency with inverse document frequency obtained similar and better results when compared with binary frequency, and normalized term frequency with inverse document frequency. Furthermore, the chi-square feature reduction approach outperformed Pearson correlation, and information gain approaches. Finally, in text classification algorithms, support vector machine classifier outperforms random forest, Naive Bayes, k-nearest neighbor, decision tree, and ensemble-voted classifier. Our results and comparisons hold practical importance and serve as references for future works. Moreover, the comparison outputs will act as state-of-art techniques to compare future proposals with existing automated text classification techniques. Copyright © 2017 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Joint High-Order Synchrosqueezing Transform and Multi-Taper Empirical Wavelet Transform for Fault Diagnosis of Wind Turbine Planetary Gearbox under Nonstationary Conditions.

PubMed

Hu, Yue; Tu, Xiaotong; Li, Fucai; Meng, Guang

2018-01-07

Wind turbines usually operate under nonstationary conditions, such as wide-range speed fluctuation and time-varying load. Its critical component, the planetary gearbox, is prone to malfunction or failure, which leads to downtime and repair costs. Therefore, fault diagnosis and condition monitoring for the planetary gearbox in wind turbines is a vital research topic. Meanwhile, the signals measured by the vibration sensors mounted in the gearbox exhibit time-varying and nonstationary features. In this study, a novel time-frequency method based on high-order synchrosqueezing transform (SST) and multi-taper empirical wavelet transform (MTEWT) is proposed for the wind turbine planetary gearbox under nonstationary conditions. The high-order SST uses accurate instantaneous frequency approximations to obtain a sharper time-frequency representation (TFR). As the acquired signal consists of many components, like the meshing and rotating components of the gear and bearing, the fault component may be masked by other unrelated components. The MTEWT is used to separate the fault feature from the masking components. A variety of experimental signals of the wind turbine planetary gearbox under nonstationary conditions have been analyzed to demonstrate the effectiveness and robustness of the proposed method. Results show that the proposed method is effective in diagnosing both gear and bearing faults.

Joint High-Order Synchrosqueezing Transform and Multi-Taper Empirical Wavelet Transform for Fault Diagnosis of Wind Turbine Planetary Gearbox under Nonstationary Conditions

PubMed Central

Li, Fucai; Meng, Guang

2018-01-01

Wind turbines usually operate under nonstationary conditions, such as wide-range speed fluctuation and time-varying load. Its critical component, the planetary gearbox, is prone to malfunction or failure, which leads to downtime and repair costs. Therefore, fault diagnosis and condition monitoring for the planetary gearbox in wind turbines is a vital research topic. Meanwhile, the signals measured by the vibration sensors mounted in the gearbox exhibit time-varying and nonstationary features. In this study, a novel time-frequency method based on high-order synchrosqueezing transform (SST) and multi-taper empirical wavelet transform (MTEWT) is proposed for the wind turbine planetary gearbox under nonstationary conditions. The high-order SST uses accurate instantaneous frequency approximations to obtain a sharper time-frequency representation (TFR). As the acquired signal consists of many components, like the meshing and rotating components of the gear and bearing, the fault component may be masked by other unrelated components. The MTEWT is used to separate the fault feature from the masking components. A variety of experimental signals of the wind turbine planetary gearbox under nonstationary conditions have been analyzed to demonstrate the effectiveness and robustness of the proposed method. Results show that the proposed method is effective in diagnosing both gear and bearing faults. PMID:29316668

Absolute S- and P-plane polarization efficiencies for high frequency holographic gratings in the VUV

NASA Technical Reports Server (NTRS)

Caruso, A. J.; Woodgate, B. E.; Mount, G. H.

1981-01-01

High frequency plane gratings (3500 and 3600 gr/mm) have been holographically ruled and blazed for the VUV spectral region. All gratings were coated with 70 nm Al + 25 nm MgF2. Absolute unpolarized and S- and P-plane polarization efficiencies have been measured for the first and second orders in the 120- to 450-nm spectral region at 18.5 and 30 deg angles of deviation. For deep grooves, anomalous features are more pronounced for the P-plane polarization efficiency than for the S-plane polarization efficiency. Holographic gratings can be tailored to produce high polarization or low polarization in the VUV. For comparison, efficiencies and polarization of the best conventional high frequency gratings were also determined. Measurements show that scattered light is significantly lower for holographic gratings in the VUV when compared with the conventional gratings.

Searching for oscillations in the primordial power spectrum. II. Constraints from Planck data

NASA Astrophysics Data System (ADS)

Meerburg, P. Daniel; Spergel, David N.; Wandelt, Benjamin D.

2014-03-01

In this second of two papers we apply our recently developed code to search for resonance features in the Planck CMB temperature data. We search both for log-spaced oscillations or linear-spaced oscillations and compare our findings with results of our WMAP9 analysis and the Planck team analysis [P. A. R. Ade et al. (Planck Collaboration>), arXiv:1303.5082]. While there are hints of log-spaced resonant features present in the WMAP9 data, the significance of these features weaken with more data. With more accurate small scale measurements, we also find that the best-fit frequency has shifted and the amplitude has been reduced. We confirm the presence of a several low frequency peaks, earlier identified by the Planck team, but with a better improvement of fit (Δχeff2˜12). We further investigate this improvement by allowing the lensing potential to vary as well, showing mild correlation between the amplitude of the oscillations and the lensing amplitude. We find that the improvement of the fit increases even more (Δχeff2˜14) for the low frequencies that modify the spectrum in a way that mimics the lensing effect. Since these features were not present in the WMAP data, they are primarily due to better measurements of Planck at small angular scales. For linear-spaced oscillations we find a maximum Δχeff2˜13 scanning two orders of magnitude in frequency space, and the biggest improvements are at extremely high frequencies. Again, we recover a best-fit frequency very close to the one found in WMAP9, which confirms that the fit improvement is driven by low ℓ. Further comparisons with WMAP9 show Planck contains many more features, both for linear- and log-spaced oscillations, but with a smaller improvement of fit. We discuss the improvement as a function of the number of modes and study the effect of the 217 GHz map, which appears to drive most of the improvement for log-spaced oscillations. Two points strongly suggest that the detected features are fitting a combination of the noise and the dip at ℓ˜1800 in the 217 GHz map: the fit improvement mostly comes from a small range of ℓ, and comparison with simulations shows that the fit improvement is consistent with a statistical fluctuation. We conclude that none of the detected features are statistically significant.

A Semi-supervised Heat Kernel Pagerank MBO Algorithm for Data Classification

DTIC Science & Technology

2016-07-01

financial predictions, etc. and is finding growing use in text mining studies. In this paper, we present an efficient algorithm for classification of high...video data, set of images, hyperspectral data, medical data, text data, etc. Moreover, the framework provides a way to analyze data whose different...also be incorporated. For text classification, one can use tfidf (term frequency inverse document frequency) to form feature vectors for each document

Sharpening coarse-to-fine stereo vision by perceptual learning: asymmetric transfer across the spatial frequency spectrum

PubMed Central

Tran, Truyet T.; Craven, Ashley P.; Leung, Tsz-Wing; Chat, Sandy W.; Levi, Dennis M.

2016-01-01

Neurons in the early visual cortex are finely tuned to different low-level visual features, forming a multi-channel system analysing the visual image formed on the retina in a parallel manner. However, little is known about the potential ‘cross-talk’ among these channels. Here, we systematically investigated whether stereoacuity, over a large range of target spatial frequencies, can be enhanced by perceptual learning. Using narrow-band visual stimuli, we found that practice with coarse (low spatial frequency) targets substantially improves performance, and that the improvement spreads from coarse to fine (high spatial frequency) three-dimensional perception, generalizing broadly across untrained spatial frequencies and orientations. Notably, we observed an asymmetric transfer of learning across the spatial frequency spectrum. The bandwidth of transfer was broader when training was at a high spatial frequency than at a low spatial frequency. Stereoacuity training is most beneficial when trained with fine targets. This broad transfer of stereoacuity learning contrasts with the highly specific learning reported for other basic visual functions. We also revealed strategies to boost learning outcomes ‘beyond-the-plateau’. Our investigations contribute to understanding the functional properties of the network subserving stereovision. The ability to generalize may provide a key principle for restoring impaired binocular vision in clinical situations. PMID:26909178

Sequence and facies architecture of the upper Blackhawk Formation and the Lower Castlegate Sandstone (Upper Cretaceous), Book Cliffs, Utah, USA

NASA Astrophysics Data System (ADS)

Yoshida, S.

2000-11-01

High-frequency stratigraphic sequences that comprise the Desert Member of the Blackhawk Formation, the Lower Castlegate Sandstone, and the Buck Tongue in the Green River area of Utah display changes in sequence architecture from marine deposits to marginal marine deposits to an entirely nonmarine section. Facies and sequence architecture differ above and below the regionally extensive Castlegate sequence boundary, which separates two low-frequency (106-year cyclicity) sequences. Below this surface, high-frequency sequences are identified and interpreted as comprising the highstand systems tract of the low-frequency Blackhawk sequence. Each high-frequency sequence has a local incised valley system on top of the wave-dominated delta, and coastal plain to shallow marine deposits are preserved. Above the Castlegate sequence boundary, in contrast, a regionally extensive sheet sandstone of fluvial to estuarine origin with laterally continuous internal erosional surfaces occurs. These deposits above the Castlegate sequence boundary are interpreted as the late lowstand to early transgressive systems tracts of the low-frequency Castlegate sequence. The base-level changes that generated both the low- and high-frequency sequences are attributed to crustal response to fluctuations in compressive intraplate stress on two different time scales. The low-frequency stratigraphic sequences are attributed to changes in the long-term regional subsidence rate and regional tilting of foreland basin fill. High-frequency sequences probably reflect the response of anisotropic basement to tectonism. Sequence architecture changes rapidly across the faulted margin of the underlying Paleozoic Paradox Basin. The high-frequency sequences are deeply eroded and stack above the Paradox Basin, but display less relief and become conformable updip. These features indicate that the area above the Paradox Basin was more prone to vertical structural movements during formation of the Blackhawk-Lower Castlegate succession.

High-frequency predictions for number counts and spectral properties of extragalactic radio sources. New evidence of a break at mm wavelengths in spectra of bright blazar sources

NASA Astrophysics Data System (ADS)

Tucci, M.; Toffolatti, L.; de Zotti, G.; Martínez-González, E.

2011-09-01

We present models to predict high-frequency counts of extragalactic radio sources using physically grounded recipes to describe the complex spectral behaviour of blazars that dominate the mm-wave counts at bright flux densities. We show that simple power-law spectra are ruled out by high-frequency (ν ≥ 100 GHz) data. These data also strongly constrain models featuring the spectral breaks predicted by classical physical models for the synchrotron emission produced in jets of blazars. A model dealing with blazars as a single population is, at best, only marginally consistent with data coming from current surveys at high radio frequencies. Our most successful model assumes different distributions of break frequencies, νM, for BL Lacs and flat-spectrum radio quasars (FSRQs). The former objects have substantially higher values of νM, implying that the synchrotron emission comes from more compact regions; therefore, a substantial increase of the BL Lac fraction at high radio frequencies and at bright flux densities is predicted. Remarkably, our best model is able to give a very good fit to all the observed data on number counts and on distributions of spectral indices of extragalactic radio sources at frequencies above 5 and up to 220 GHz. Predictions for the forthcoming sub-mm blazar counts from Planck, at the highest HFI frequencies, and from Herschel surveys are also presented. Appendices are available in electronic form at http://www.aanda.org

A low jitter PLL clock used for phase change memory

NASA Astrophysics Data System (ADS)

Xiao, Hong; Houpeng, Chen; Zhitang, Song; Daolin, Cai; Xi, Li

2013-02-01

A fully integrated low-jitter, precise frequency CMOS phase-locked loop (PLL) clock for the phase change memory (PCM) drive circuit is presented. The design consists of a dynamic dual-reset phase frequency detector (PFD) with high frequency acquisition, a novel low jitter charge pump, a CMOS ring oscillator based voltage-controlled oscillator (VCO), a 2nd order passive loop filter, and a digital frequency divider. The design is fabricated in 0.35 μm CMOS technology and consumes 20 mW from a supply voltage of 5 V. In terms of the PCM's program operation requirement, the output frequency range is from 1 to 140 MHz. For the 140 MHz output frequency, the circuit features a cycle-to-cycle jitter of 28 ps RMS and 250 ps peak-to-peak.

Coherent radio-frequency detection for narrowband direct comb spectroscopy.

PubMed

Anstie, James D; Perrella, Christopher; Light, Philip S; Luiten, Andre N

2016-02-22

We demonstrate a scheme for coherent narrowband direct optical frequency comb spectroscopy. An extended cavity diode laser is injection locked to a single mode of an optical frequency comb, frequency shifted, and used as a local oscillator to optically down-mix the interrogating comb on a fast photodetector. The high spectral coherence of the injection lock generates a microwave frequency comb at the output of the photodiode with very narrow features, enabling spectral information to be further down-mixed to RF frequencies, allowing optical transmittance and phase to be obtained using electronics commonly found in the lab. We demonstrate two methods for achieving this step: a serial mode-by-mode approach and a parallel dual-comb approach, with the Cs D1 transition at 894 nm as a test case.

Defect detection of helical gears based on time-frequency analysis and using multi-layer fusion network

NASA Astrophysics Data System (ADS)

Ebrahimi Orimi, H.; Esmaeili, M.; Refahi Oskouei, A.; Mirhadizadehd, S. A.; Tse, P. W.

2017-10-01

Condition monitoring of rotary devices such as helical gears is an issue of great significance in industrial projects. This paper introduces a feature extraction method for gear fault diagnosis using wavelet packet due to its higher frequency resolution. During this investigation, the mother wavelet Daubechies 10 (Db-10) was applied to calculate the coefficient entropy of each frequency band of 5th level (32 frequency bands) as features. In this study, the peak value of the signal entropies was selected as applicable features in order to improve frequency band differentiation and reduce feature vectors' dimension. Feature extraction is followed by the fusion network where four different structured multi-layer perceptron networks are trained to classify the recorded signals (healthy/faulty). The robustness of fusion network outputs is greater compared to perceptron networks. The results provided by the fusion network indicate a classification of 98.88 and 97.95% for healthy and faulty classes, respectively.

Major features of immunesenescence, including reduced thymic output, are ameliorated by high levels of physical activity in adulthood.

PubMed

Duggal, Niharika Arora; Pollock, Ross D; Lazarus, Norman R; Harridge, Stephen; Lord, Janet M

2018-04-01

It is widely accepted that aging is accompanied by remodelling of the immune system including thymic atrophy and increased frequency of senescent T cells, leading to immune compromise. However, physical activity, which influences immunity but declines dramatically with age, is not considered in this literature. We assessed immune profiles in 125 adults (55-79 years) who had maintained a high level of physical activity (cycling) for much of their adult lives, 75 age-matched older adults and 55 young adults not involved in regular exercise. The frequency of naïve T cells and recent thymic emigrants (RTE) were both higher in cyclists compared with inactive elders, and RTE frequency in cyclists was no different to young adults. Compared with their less active counterparts, the cyclists had significantly higher serum levels of the thymoprotective cytokine IL-7 and lower IL-6, which promotes thymic atrophy. Cyclists also showed additional evidence of reduced immunesenescence, namely lower Th17 polarization and higher B regulatory cell frequency than inactive elders. Physical activity did not protect against all aspects of immunesenescence: CD28 -ve CD57 +ve senescent CD8 T-cell frequency did not differ between cyclists and inactive elders. We conclude that many features of immunesenescence may be driven by reduced physical activity with age. © 2018 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd.

Fatigue level estimation of monetary bills based on frequency band acoustic signals with feature selection by supervised SOM

NASA Astrophysics Data System (ADS)

Teranishi, Masaru; Omatu, Sigeru; Kosaka, Toshihisa

Fatigued monetary bills adversely affect the daily operation of automated teller machines (ATMs). In order to make the classification of fatigued bills more efficient, the development of an automatic fatigued monetary bill classification method is desirable. We propose a new method by which to estimate the fatigue level of monetary bills from the feature-selected frequency band acoustic energy pattern of banking machines. By using a supervised self-organizing map (SOM), we effectively estimate the fatigue level using only the feature-selected frequency band acoustic energy pattern. Furthermore, the feature-selected frequency band acoustic energy pattern improves the estimation accuracy of the fatigue level of monetary bills by adding frequency domain information to the acoustic energy pattern. The experimental results with real monetary bill samples reveal the effectiveness of the proposed method.

Examination of the high-frequency capability of carbon nanotube FETs

NASA Astrophysics Data System (ADS)

Pulfrey, David L.; Chen, Li

2008-09-01

New results are added to a recent critique of the high-frequency performance of carbon nanotube field-effect transistors (CNFETs). On the practical side, reduction of the number of metallic tubes in CNFETs fashioned from multiple nanotubes has allowed the measured fT to be increased to 30 GHz. On the theoretical side, the opinion that the band-structure-determined velocity limits the high-frequency performance has been reinforced by corrections to recent simulation results for doped-contact CNFETs, and by the ruling out of the possibility of favourable image-charge effects. Inclusion in the simulations of the features of finite gate-metal thickness and source/drain contact resistance has given an indication of likely practical values for fT. A meaningful comparison between CNFETs with doped-contacts and metallic contacts has been made.

Predation by killer whales (Orcinus orca) and the evolution of whistle loss and narrow-band high frequency clicks in odontocetes.

PubMed

Morisaka, T; Connor, R C

2007-07-01

A disparate selection of toothed whales (Odontoceti) share striking features of their acoustic repertoires including the absence of whistles and high frequency but weak (low peak-to-peak source level) clicks that have a relatively long duration and a narrow bandwidth. The non-whistling, high frequency click species include members of the family Phocoenidae, members of one genus of delphinids, Cephalorhynchus, the pygmy sperm whale, Kogia breviceps, and apparently the sole member of the family Pontoporiidae. Our review supports the 'acoustic crypsis' hypothesis that killer whale predation risk was the primary selective factor favouring an echolocation and communication system in cephalorhynchids, phocoenids and possibly Pontoporiidae and Kogiidae restricted to sounds that killer whales hear poorly or not at all (< 2 and > 100 kHz).

Single frequency thermal wave radar: A next-generation dynamic thermography for quantitative non-destructive imaging over wide modulation frequency ranges.

PubMed

Melnikov, Alexander; Chen, Liangjie; Ramirez Venegas, Diego; Sivagurunathan, Koneswaran; Sun, Qiming; Mandelis, Andreas; Rodriguez, Ignacio Rojas

2018-04-01

Single-Frequency Thermal Wave Radar Imaging (SF-TWRI) was introduced and used to obtain quantitative thickness images of coatings on an aluminum block and on polyetherketone, and to image blind subsurface holes in a steel block. In SF-TWR, the starting and ending frequencies of a linear frequency modulation sweep are chosen to coincide. Using the highest available camera frame rate, SF-TWRI leads to a higher number of sampled points along the modulation waveform than conventional lock-in thermography imaging because it is not limited by conventional undersampling at high frequencies due to camera frame-rate limitations. This property leads to large reduction in measurement time, better quality of images, and higher signal-noise-ratio across wide frequency ranges. For quantitative thin-coating imaging applications, a two-layer photothermal model with lumped parameters was used to reconstruct the layer thickness from multi-frequency SF-TWR images. SF-TWRI represents a next-generation thermography method with superior features for imaging important classes of thin layers, materials, and components that require high-frequency thermal-wave probing well above today's available infrared camera technology frame rates.

Single frequency thermal wave radar: A next-generation dynamic thermography for quantitative non-destructive imaging over wide modulation frequency ranges

NASA Astrophysics Data System (ADS)

Melnikov, Alexander; Chen, Liangjie; Ramirez Venegas, Diego; Sivagurunathan, Koneswaran; Sun, Qiming; Mandelis, Andreas; Rodriguez, Ignacio Rojas

2018-04-01

Single-Frequency Thermal Wave Radar Imaging (SF-TWRI) was introduced and used to obtain quantitative thickness images of coatings on an aluminum block and on polyetherketone, and to image blind subsurface holes in a steel block. In SF-TWR, the starting and ending frequencies of a linear frequency modulation sweep are chosen to coincide. Using the highest available camera frame rate, SF-TWRI leads to a higher number of sampled points along the modulation waveform than conventional lock-in thermography imaging because it is not limited by conventional undersampling at high frequencies due to camera frame-rate limitations. This property leads to large reduction in measurement time, better quality of images, and higher signal-noise-ratio across wide frequency ranges. For quantitative thin-coating imaging applications, a two-layer photothermal model with lumped parameters was used to reconstruct the layer thickness from multi-frequency SF-TWR images. SF-TWRI represents a next-generation thermography method with superior features for imaging important classes of thin layers, materials, and components that require high-frequency thermal-wave probing well above today's available infrared camera technology frame rates.

Application of the wavelet packet transform to vibration signals for surface roughness monitoring in CNC turning operations

NASA Astrophysics Data System (ADS)

García Plaza, E.; Núñez López, P. J.

2018-01-01

The wavelet packet transform method decomposes a time signal into several independent time-frequency signals called packets. This enables the temporary location of transient events occurring during the monitoring of the cutting processes, which is advantageous in monitoring condition and fault diagnosis. This paper proposes the monitoring of surface roughness using a single low cost sensor that is easily implemented in numerical control machine tools in order to make on-line decisions on workpiece surface finish quality. Packet feature extraction in vibration signals was applied to correlate the sensor signals to measured surface roughness. For the successful application of the WPT method, mother wavelets, packet decomposition level, and appropriate packet selection methods should be considered, but are poorly understood aspects in the literature. In this novel contribution, forty mother wavelets, optimal decomposition level, and packet reduction methods were analysed, as well as identifying the effective frequency range providing the best packet feature extraction for monitoring surface finish. The results show that mother wavelet biorthogonal 4.4 in decomposition level L3 with the fusion of the orthogonal vibration components (ax + ay + az) were the best option in the vibration signal and surface roughness correlation. The best packets were found in the medium-high frequency DDA (6250-9375 Hz) and high frequency ADA (9375-12500 Hz) ranges, and the feed acceleration component ay was the primary source of information. The packet reduction methods forfeited packets with relevant features to the signal, leading to poor results for the prediction of surface roughness. WPT is a robust vibration signal processing method for the monitoring of surface roughness using a single sensor without other information sources, satisfactory results were obtained in comparison to other processing methods with a low computational cost.

Rare Central Pacific El Niño Events Caused by Interdecadal Tropical Pacific Variability

NASA Astrophysics Data System (ADS)

Zhong, Wenxiu; Zheng, Xiaotong; Cai, Wenju

2017-04-01

The frequency of Central Pacific (CP) El Niño events displays strong decadal-variability but the associated dynamics is still not clear. The Inter-decadal Pacific Oscillation (IPO) and the Tropical Pacific Decadal Variability (TPDV) are two dominant modes of the Pacific low-frequency variability that can modify high-frequency behaviors. Using a 500-year control integration of Geophysical Fluid Dynamics Laboratory Earth System Model simulation, we find that the mean state, determined by the two independent modes of tropical Pacific decadal variability, strongly affects CP El Niño frequency and the associated developing processes. A positive TPDV features a shallow thermocline and cool sea surface temperature anomalies (SSTAs) across the central-to-western tropical Pacific, and a negative IPO features cool SSTAs and strong trade winds along the equatorial Pacific. The combination of a positive TPDV and a negative IPO generates a decadal mean state, in which the climatological zonal temperature gradient is reduced, equatorward and westward current anomalies are harder to be generated over the central-to-western tropical Pacific, resulting in the lack of CP El Niño.

Investigation of Dual-Mode Microstrip Bandpass Filter Based on SIR Technique

PubMed Central

Mezaal, Yaqeen S.; Ali, Jawad K.

2016-01-01

In this paper, a new bandpass filter design has been presented using simple topology of stepped impedance square loop resonator. The proposed bandpass filter has been simulated and fabricated using a substrate with an insulation constant of 10.8, thickness of 1.27mm and loss tangent of 0.0023 at center frequency of 5.8 GHz. The simulation results have been evaluated using Sonnet simulator that is extensively adopted in microwave analysis and implementation. The output frequency results demonstrated that the proposed filter has high-quality frequency responses in addition to isolated second harmonic frequency. Besides, this filter has very small surface area and perceptible narrow band response features that represent the conditions of recent wireless communication systems. Various filter specifications have been compared with different magnitudes of perturbation element dimension. Furthermore, phase scattering response and current intensity distribution of the proposed filter have been discussed. The simulated and experimental results are well-matched. Lastly, the features of the proposed filter have been compared with other designed microstrip filters in the literature. PMID:27798675

High spectral purity Kerr frequency comb radio frequency photonic oscillator

PubMed Central

Liang, W.; Eliyahu, D.; Ilchenko, V. S.; Savchenkov, A. A.; Matsko, A. B.; Seidel, D.; Maleki, L.

2015-01-01

Femtosecond laser-based generation of radio frequency signals has produced astonishing improvements in achievable spectral purity, one of the basic features characterizing the performance of an radio frequency oscillator. Kerr frequency combs hold promise for transforming these lab-scale oscillators to chip-scale level. In this work we demonstrate a miniature 10 GHz radio frequency photonic oscillator characterized with phase noise better than −60 dBc Hz−1 at 10 Hz, −90 dBc Hz−1 at 100 Hz and −170 dBc Hz−1 at 10 MHz. The frequency stability of this device, as represented by Allan deviation measurements, is at the level of 10−10 at 1–100 s integration time—orders of magnitude better than existing radio frequency photonic devices of similar size, weight and power consumption. PMID:26260955

Combining high-speed SVM learning with CNN feature encoding for real-time target recognition in high-definition video for ISR missions

NASA Astrophysics Data System (ADS)

Kroll, Christine; von der Werth, Monika; Leuck, Holger; Stahl, Christoph; Schertler, Klaus

2017-05-01

For Intelligence, Surveillance, Reconnaissance (ISR) missions of manned and unmanned air systems typical electrooptical payloads provide high-definition video data which has to be exploited with respect to relevant ground targets in real-time by automatic/assisted target recognition software. Airbus Defence and Space is developing required technologies for real-time sensor exploitation since years and has combined the latest advances of Deep Convolutional Neural Networks (CNN) with a proprietary high-speed Support Vector Machine (SVM) learning method into a powerful object recognition system with impressive results on relevant high-definition video scenes compared to conventional target recognition approaches. This paper describes the principal requirements for real-time target recognition in high-definition video for ISR missions and the Airbus approach of combining an invariant feature extraction using pre-trained CNNs and the high-speed training and classification ability of a novel frequency-domain SVM training method. The frequency-domain approach allows for a highly optimized implementation for General Purpose Computation on a Graphics Processing Unit (GPGPU) and also an efficient training of large training samples. The selected CNN which is pre-trained only once on domain-extrinsic data reveals a highly invariant feature extraction. This allows for a significantly reduced adaptation and training of the target recognition method for new target classes and mission scenarios. A comprehensive training and test dataset was defined and prepared using relevant high-definition airborne video sequences. The assessment concept is explained and performance results are given using the established precision-recall diagrams, average precision and runtime figures on representative test data. A comparison to legacy target recognition approaches shows the impressive performance increase by the proposed CNN+SVM machine-learning approach and the capability of real-time high-definition video exploitation.

There’s More to Groove than Bass in Electronic Dance Music: Why Some People Won’t Dance to Techno

PubMed Central

2016-01-01

The purpose of this study was to explore the relationship between audio descriptors for groove-based electronic dance music (EDM) and raters’ perceived cognitive, affective, and psychomotor responses. From 198 musical excerpts (length: 15 sec.) representing 11 subgenres of EDM, 19 low-level audio feature descriptors were extracted. A principal component analysis of the feature vectors indicated that the musical excerpts could effectively be classified using five complex measures, describing the rhythmical properties of: (a) the high-frequency band, (b) the mid-frequency band, and (c) the low-frequency band, as well as overall fluctuations in (d) dynamics, and (e) timbres. Using these five complex audio measures, four meaningful clusters of the EDM excerpts emerged with distinct musical attributes comprising music with: (a) isochronous bass and static timbres, (b) isochronous bass with fluctuating dynamics and rhythmical variations in the mid-frequency range, (c) non-isochronous bass and fluctuating timbres, and (d) non-isochronous bass with rhythmical variations in the high frequencies. Raters (N = 99) were each asked to respond to four musical excerpts using a four point Likert-Type scale consisting of items representing cognitive (n = 9), affective (n = 9), and psychomotor (n = 3) domains. Musical excerpts falling under the cluster of “non-isochronous bass with rhythmical variations in the high frequencies” demonstrated the overall highest composite scores as evaluated by the raters. Musical samples falling under the cluster of “isochronous bass with static timbres” demonstrated the overall lowest composite scores as evaluated by the raters. Moreover, music preference was shown to significantly affect the systematic patterning of raters’ responses for those with a musical preference for “contemporary” music, “sophisticated” music, and “intense” music. PMID:27798645

Dynamics of Active Separation Control at High Reynolds Numbers

NASA Technical Reports Server (NTRS)

Pack, LaTunia G.; Seifert, Avi

2000-01-01

A series of active flow control experiments were recently conducted at high Reynolds numbers on a generic separated configuration. The model simulates the upper surface of a 20% thick Glauert-Goldschmied type airfoil at zero angle of attack. The flow is fully turbulent since the tunnel sidewall boundary layer flows over the model. The main motivation for the experiments is to generate a comprehensive data base for validation of unsteady numerical simulation as a first step in the development of a CFD design tool, without which it would not be possible to effectively utilize the great potential of unsteady flow control. This paper focuses on the dynamics of several key features of the baseline as well as the controlled flow. It was found that the thickness of the upstream boundary layer has a negligible effect on the flow dynamics. It is speculated that separation is caused mainly by the highly convex surface while viscous effects are less important. The two-dimensional separated flow contains unsteady waves centered on a reduced frequency of 0.8, while in the three dimensional separated flow, frequencies around a reduced frequency of 0.3 and 1 are active. Several scenarios of resonant wave interaction take place at the separated shear-layer and in the pressure recovery region. The unstable reduced frequency bands for periodic excitation are centered on 1.5 and 5, but these reduced frequencies are based on the length of the baseline bubble that shortens due to the excitation. The conventional swept wing-scaling works well for the coherent wave features. Reproduction of these dynamic effects by a numerical simulation would provide benchmark validation.

Feature Selection and Classifier Parameters Estimation for EEG Signals Peak Detection Using Particle Swarm Optimization

PubMed Central

Adam, Asrul; Mohd Tumari, Mohd Zaidi; Mohamad, Mohd Saberi

2014-01-01

Electroencephalogram (EEG) signal peak detection is widely used in clinical applications. The peak point can be detected using several approaches, including time, frequency, time-frequency, and nonlinear domains depending on various peak features from several models. However, there is no study that provides the importance of every peak feature in contributing to a good and generalized model. In this study, feature selection and classifier parameters estimation based on particle swarm optimization (PSO) are proposed as a framework for peak detection on EEG signals in time domain analysis. Two versions of PSO are used in the study: (1) standard PSO and (2) random asynchronous particle swarm optimization (RA-PSO). The proposed framework tries to find the best combination of all the available features that offers good peak detection and a high classification rate from the results in the conducted experiments. The evaluation results indicate that the accuracy of the peak detection can be improved up to 99.90% and 98.59% for training and testing, respectively, as compared to the framework without feature selection adaptation. Additionally, the proposed framework based on RA-PSO offers a better and reliable classification rate as compared to standard PSO as it produces low variance model. PMID:25243236

A Deep Learning Approach for Fault Diagnosis of Induction Motors in Manufacturing

NASA Astrophysics Data System (ADS)

Shao, Si-Yu; Sun, Wen-Jun; Yan, Ru-Qiang; Wang, Peng; Gao, Robert X.

2017-11-01

Extracting features from original signals is a key procedure for traditional fault diagnosis of induction motors, as it directly influences the performance of fault recognition. However, high quality features need expert knowledge and human intervention. In this paper, a deep learning approach based on deep belief networks (DBN) is developed to learn features from frequency distribution of vibration signals with the purpose of characterizing working status of induction motors. It combines feature extraction procedure with classification task together to achieve automated and intelligent fault diagnosis. The DBN model is built by stacking multiple-units of restricted Boltzmann machine (RBM), and is trained using layer-by-layer pre-training algorithm. Compared with traditional diagnostic approaches where feature extraction is needed, the presented approach has the ability of learning hierarchical representations, which are suitable for fault classification, directly from frequency distribution of the measurement data. The structure of the DBN model is investigated as the scale and depth of the DBN architecture directly affect its classification performance. Experimental study conducted on a machine fault simulator verifies the effectiveness of the deep learning approach for fault diagnosis of induction motors. This research proposes an intelligent diagnosis method for induction motor which utilizes deep learning model to automatically learn features from sensor data and realize working status recognition.

The perceptual features of vocal fatigue as self-reported by a group of actors and singers.

PubMed

Kitch, J A; Oates, J

1994-09-01

Performers (10 actors/10 singers) rated via a self-report questionnaire the severity of their voice-related changes when vocally fatigued. Similar frequency patterns and perceptual features of vocal fatigue were found across subjects. Actors rated "power" aspects (e.g., voice projection) and singers rated vocal dynamic aspects (e.g., pitch range) of their voices as most affected when vocally fatigued. Vocal fatigue was evidenced by changes in kinesthetic/proprioceptive sensations and vocal dynamics. The causes and context of vocal fatigue were vocal misuse, being "run down," high performance demands, and using high pitch/volume levels. Further research is needed to delineate the perceptual features of "normal" levels of vocal fatigue and its possible causes.

Altered cerebral blood flow velocity features in fibromyalgia patients in resting-state conditions

PubMed Central

Rodríguez, Alejandro; Tembl, José; Mesa-Gresa, Patricia; Muñoz, Miguel Ángel; Montoya, Pedro

2017-01-01

The aim of this study is to characterize in resting-state conditions the cerebral blood flow velocity (CBFV) signals of fibromyalgia patients. The anterior and middle cerebral arteries of both hemispheres from 15 women with fibromyalgia and 15 healthy women were monitored using Transcranial Doppler (TCD) during a 5-minute eyes-closed resting period. Several signal processing methods based on time, information theory, frequency and time-frequency analyses were used in order to extract different features to characterize the CBFV signals in the different vessels. Main results indicated that, in comparison with control subjects, fibromyalgia patients showed a higher complexity of the envelope CBFV and a different distribution of the power spectral density. In addition, it has been observed that complexity and spectral features show correlations with clinical pain parameters and emotional factors. The characterization features were used in a lineal model to discriminate between fibromyalgia patients and healthy controls, providing a high accuracy. These findings indicate that CBFV signals, specifically their complexity and spectral characteristics, contain information that may be relevant for the assessment of fibromyalgia patients in resting-state conditions. PMID:28700720

Altered cerebral blood flow velocity features in fibromyalgia patients in resting-state conditions.

PubMed

Rodríguez, Alejandro; Tembl, José; Mesa-Gresa, Patricia; Muñoz, Miguel Ángel; Montoya, Pedro; Rey, Beatriz

2017-01-01

The aim of this study is to characterize in resting-state conditions the cerebral blood flow velocity (CBFV) signals of fibromyalgia patients. The anterior and middle cerebral arteries of both hemispheres from 15 women with fibromyalgia and 15 healthy women were monitored using Transcranial Doppler (TCD) during a 5-minute eyes-closed resting period. Several signal processing methods based on time, information theory, frequency and time-frequency analyses were used in order to extract different features to characterize the CBFV signals in the different vessels. Main results indicated that, in comparison with control subjects, fibromyalgia patients showed a higher complexity of the envelope CBFV and a different distribution of the power spectral density. In addition, it has been observed that complexity and spectral features show correlations with clinical pain parameters and emotional factors. The characterization features were used in a lineal model to discriminate between fibromyalgia patients and healthy controls, providing a high accuracy. These findings indicate that CBFV signals, specifically their complexity and spectral characteristics, contain information that may be relevant for the assessment of fibromyalgia patients in resting-state conditions.

Consciousness Indexing and Outcome Prediction with Resting-State EEG in Severe Disorders of Consciousness.

PubMed

Stefan, Sabina; Schorr, Barbara; Lopez-Rolon, Alex; Kolassa, Iris-Tatjana; Shock, Jonathan P; Rosenfelder, Martin; Heck, Suzette; Bender, Andreas

2018-04-17

We applied the following methods to resting-state EEG data from patients with disorders of consciousness (DOC) for consciousness indexing and outcome prediction: microstates, entropy (i.e. approximate, permutation), power in alpha and delta frequency bands, and connectivity (i.e. weighted symbolic mutual information, symbolic transfer entropy, complex network analysis). Patients with unresponsive wakefulness syndrome (UWS) and patients in a minimally conscious state (MCS) were classified into these two categories by fitting and testing a generalised linear model. We aimed subsequently to develop an automated system for outcome prediction in severe DOC by selecting an optimal subset of features using sequential floating forward selection (SFFS). The two outcome categories were defined as UWS or dead, and MCS or emerged from MCS. Percentage of time spent in microstate D in the alpha frequency band performed best at distinguishing MCS from UWS patients. The average clustering coefficient obtained from thresholding beta coherence performed best at predicting outcome. The optimal subset of features selected with SFFS consisted of the frequency of microstate A in the 2-20 Hz frequency band, path length obtained from thresholding alpha coherence, and average path length obtained from thresholding alpha coherence. Combining these features seemed to afford high prediction power. Python and MATLAB toolboxes for the above calculations are freely available under the GNU public license for non-commercial use ( https://qeeg.wordpress.com ).

Deinterlacing using modular neural network

NASA Astrophysics Data System (ADS)

Woo, Dong H.; Eom, Il K.; Kim, Yoo S.

2004-05-01

Deinterlacing is the conversion process from the interlaced scan to progressive one. While many previous algorithms that are based on weighted-sum cause blurring in edge region, deinterlacing using neural network can reduce the blurring through recovering of high frequency component by learning process, and is found robust to noise. In proposed algorithm, input image is divided into edge and smooth region, and then, to each region, one neural network is assigned. Through this process, each neural network learns only patterns that are similar, therefore it makes learning more effective and estimation more accurate. But even within each region, there are various patterns such as long edge and texture in edge region. To solve this problem, modular neural network is proposed. In proposed modular neural network, two modules are combined in output node. One is for low frequency feature of local area of input image, and the other is for high frequency feature. With this structure, each modular neural network can learn different patterns with compensating for drawback of counterpart. Therefore it can adapt to various patterns within each region effectively. In simulation, the proposed algorithm shows better performance compared with conventional deinterlacing methods and single neural network method.

Ionospheric modifications in high frequency heating experiments

NASA Astrophysics Data System (ADS)

Kuo, Spencer P.

2015-01-01

Featured observations in high-frequency (HF) heating experiments conducted at Arecibo, EISCAT, and high frequency active auroral research program are discussed. These phenomena appearing in the F region of the ionosphere include high-frequency heater enhanced plasma lines, airglow enhancement, energetic electron flux, artificial ionization layers, artificial spread-F, ionization enhancement, artificial cusp, wideband absorption, short-scale (meters) density irregularities, and stimulated electromagnetic emissions, which were observed when the O-mode HF heater waves with frequencies below foF2 were applied. The implication and associated physical mechanism of each observation are discussed and explained. It is shown that these phenomena caused by the HF heating are all ascribed directly or indirectly to the excitation of parametric instabilities which instigate anomalous heating. Formulation and analysis of parametric instabilities are presented. The results show that oscillating two stream instability and parametric decay instability can be excited by the O-mode HF heater waves, transmitted from all three heating facilities, in the regions near the HF reflection height and near the upper hybrid resonance layer. The excited Langmuir waves, upper hybrid waves, ion acoustic waves, lower hybrid waves, and field-aligned density irregularities set off subsequent wave-wave and wave-electron interactions, giving rise to the observed phenomena.

Cortical theta wanes for language.

PubMed

Hermes, Dora; Miller, Kai J; Vansteensel, Mariska J; Edwards, Erik; Ferrier, Cyrille H; Bleichner, Martin G; van Rijen, Peter C; Aarnoutse, Erik J; Ramsey, Nick F

2014-01-15

The role of low frequency oscillations in language areas is not yet understood. Using ECoG in six human subjects, we studied whether different language regions show prominent power changes in a specific rhythm, in similar manner as the alpha rhythm shows the most prominent power changes in visual areas. Broca's area and temporal language areas were localized in individual subjects using fMRI. In these areas, the theta rhythm showed the most pronounced power changes and theta power decreased significantly during verb generation. To better understand the role of this language-related theta decrease, we then studied the interaction between low frequencies and local neuronal activity reflected in high frequencies. Amplitude-amplitude correlations showed that theta power correlated negatively with high frequency activity, specifically across verb generation trials. Phase-amplitude coupling showed that during control trials, high frequency power was coupled to theta phase, but this coupling decreased significantly during verb generation trials. These results suggest a dynamic interaction between the neuronal mechanisms underlying the theta rhythm and local neuronal activity in language areas. As visual areas show a pronounced alpha rhythm that may reflect pulsed inhibition, language regions show a pronounced theta rhythm with highly similar features. © 2013.

Deconstructing continuous flash suppression

PubMed Central

Yang, Eunice; Blake, Randolph

2012-01-01

In this paper, we asked to what extent the depth of interocular suppression engendered by continuous flash suppression (CFS) varies depending on spatiotemporal properties of the suppressed stimulus and CFS suppressor. An answer to this question could have implications for interpreting the results in which CFS influences the processing of different categories of stimuli to different extents. In a series of experiments, we measured the selectivity and depth of suppression (i.e., elevation in contrast detection thresholds) as a function of the visual features of the stimulus being suppressed and the stimulus evoking suppression, namely, the popular “Mondrian” CFS stimulus (N. Tsuchiya & C. Koch, 2005). First, we found that CFS differentially suppresses the spatial components of the suppressed stimulus: Observers' sensitivity for stimuli of relatively low spatial frequency or cardinally oriented features was more strongly impaired in comparison to high spatial frequency or obliquely oriented stimuli. Second, we discovered that this feature-selective bias primarily arises from the spatiotemporal structure of the CFS stimulus, particularly within information residing in the low spatial frequency range and within the smooth rather than abrupt luminance changes over time. These results imply that this CFS stimulus operates by selectively attenuating certain classes of low-level signals while leaving others to be potentially encoded during suppression. These findings underscore the importance of considering the contribution of low-level features in stimulus-driven effects that are reported under CFS. PMID:22408039

Deconstructing continuous flash suppression.

PubMed

Yang, Eunice; Blake, Randolph

2012-03-08

In this paper, we asked to what extent the depth of interocular suppression engendered by continuous flash suppression (CFS) varies depending on spatiotemporal properties of the suppressed stimulus and CFS suppressor. An answer to this question could have implications for interpreting the results in which CFS influences the processing of different categories of stimuli to different extents. In a series of experiments, we measured the selectivity and depth of suppression (i.e., elevation in contrast detection thresholds) as a function of the visual features of the stimulus being suppressed and the stimulus evoking suppression, namely, the popular "Mondrian" CFS stimulus (N. Tsuchiya & C. Koch, 2005). First, we found that CFS differentially suppresses the spatial components of the suppressed stimulus: Observers' sensitivity for stimuli of relatively low spatial frequency or cardinally oriented features was more strongly impaired in comparison to high spatial frequency or obliquely oriented stimuli. Second, we discovered that this feature-selective bias primarily arises from the spatiotemporal structure of the CFS stimulus, particularly within information residing in the low spatial frequency range and within the smooth rather than abrupt luminance changes over time. These results imply that this CFS stimulus operates by selectively attenuating certain classes of low-level signals while leaving others to be potentially encoded during suppression. These findings underscore the importance of considering the contribution of low-level features in stimulus-driven effects that are reported under CFS.

High frequency inductive lamp and power oscillator

DOEpatents

MacLennan, Donald A.; Dymond, Jr., Lauren E.; Gitsevich, Aleksandr; Grimm, William G.; Kipling, Kent; Kirkpatrick, Douglas A.; Ola, Samuel A.; Simpson, James E.; Trimble, William C.; Tsai, Peter; Turner, Brian P.

2001-01-01

A high frequency inductively coupled electrodeless lamp includes an excitation coil with an effective electrical length which is less than one half wavelength of a driving frequency applied thereto, preferably much less. The driving frequency may be greater than 100 MHz and is preferably as high as 915 MHz. Preferably, the excitation coil is configured as a non-helical, semi-cylindrical conductive surface having less than one turn, in the general shape of a wedding ring. At high frequencies, the current in the coil forms two loops which are spaced apart and parallel to each other. Configured appropriately, the coil approximates a Helmholtz configuration. The lamp preferably utilizes an bulb encased in a reflective ceramic cup with a pre-formed aperture defined therethrough. The ceramic cup may include structural features to aid in alignment and I or a flanged face to aid in thermal management. The lamp head is preferably an integrated lamp head comprising a metal matrix composite surrounding an insulating ceramic with the excitation integrally formed on the ceramic. A novel solid-state oscillator preferably provides RF power to the lamp. The oscillator is a single active element device capable of providing over 70 watts of power at over 70% efficiency. Various control circuits may be employed to adjust the driving frequency of the oscillator.

A study on the prenatal zone of ultrasonic guided waves in plates

NASA Astrophysics Data System (ADS)

Thomas, Tibin; Balasubramaniam, Krishnan

2017-02-01

Low frequency guided wave based inspection is an extensively used method for asset management with the advantage of wide area coverage from a single location at the cost of spatial resolution. With the advent of high frequency guided waves, short range inspections with high spatial resolution for monitoring corrosion under pipe supports and tank annular plates has gained widespread interest and acceptance. One of the major challenges in the application of high frequency guided waves in a short range inspection is to attain the desired modal displacements with respect to the application. In this paper, an investigation on the generation and formation of fundamental S0 mode is carried out through numerical simulation and experiments to establish a prenatal zone for guided waves. The effect of frequency, thickness of the plate and frequency-thickness (f*d) is studied. The investigation reveals the existence of a rudimentary form with similar modal features to the fully developed mode. This study helps in the design and development of a high frequency guided wave generator for particular applications which demands waves with very less sensitivity to the surface and loading during the initial phase which immediately evolves to a more sensitive wave towards the surface on propagation for the detection of shallow defects.

Explore the advantage of High-frequency Water Quality Data in Urban Surface Water: A Case Study in Bristol, UK

NASA Astrophysics Data System (ADS)

Chen, Y.; Han, D.

2017-12-01

Water system is an essential component in a smart city for its sustainability and resilience. The freshness and beauty of the water body would please people as well as benefit the local aquatic ecosystems. Water quality monitoring approach has evolved from the manual lab-based monitoring approach to the manual in-situ monitoring approach, and finally to the latest wireless-sensor-network (WSN) based solutions in recent decades. The development of the in-situ water quality sensors enable humans to collect high-frequency and real-time water quality data. This poster aims to explore the advantages of the high-frequency water quality data over the low-frequency data collected manually. The data is collected by a remote real-time high-frequency water quality monitor system based on the cutting edge smart city infrastructure in Bristol - `Bristol Is Open'. The water quality of Bristol Floating Harbour is monitored which is the focal area of Bristol with new buildings and features redeveloped in the past decades. This poster will first briefly introduce the water quality monitoring system, followed by the analysis of the advantages of the sub-hourly water quality data. Thus, the suggestion on the monitoring frequency will be given.

Guided wave phased array sensor tuning for improved defect detection and characterization

NASA Astrophysics Data System (ADS)

Philtron, Jason H.; Rose, Joseph L.

2014-03-01

Ultrasonic guided waves are finding increased use in a variety of Nondestructive Evaluation and Structural Health Monitoring applications due to their efficiency in defect detection using a sensor at a single location to inspect a large area of a structure and an ability to inspect hidden and coated areas for example. With a thorough understanding of guided wave mechanics, researchers can predict which guided wave modes will have a high probability of success in a particular nondestructive evaluation application. For example, in a sample problem presented here to access bond integrity, researchers may choose to use a guided wave mode which has high in-plane displacement, stress, or other feature at the interface. However, since material properties used for modeling work may not be precise for the development of dispersion curves, in many cases guided wave mode and frequency selection should be adjusted for increased inspection efficiency in the field. In this work, a phased array comb transducer is used to sweep over phase velocity - frequency space to tune mode excitation for improved defect characterization performance. A thin polycarbonate layer bonded to a thick metal plate is considered with a contaminated surface prior to bonding. Physicallybased features are used to correlate wave signals with defect detection. Features assessed include arrival time and the frequency of maximum amplitude. A pseudo C-scan plot is presented which can be used to simplify data analysis. Excellent results are obtained.

Inertial Response of Wind Power Plants: A Comparison of Frequency-Based Inertial Control and Stepwise Inertial Control

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

Wang, Xiao; Gao, Wenzhong; Wang, Jianhui

The frequency regulation capability of a wind power plant plays an important role in enhancing frequency reliability especially in an isolated power system with high wind power penetration levels. A comparison of two types of inertial control methods, namely frequency-based inertial control (FBIC) and stepwise inertial control (SIC), is presented in this paper. Comprehensive case studies are carried out to reveal features of the different inertial control methods, simulated in a modified Western System Coordination Council (WSCC) nine-bus power grid using real-time digital simulator (RTDS) platform. The simulation results provide an insight into the inertial control methods under various scenarios.

A space system for high-accuracy global time and frequency comparison of clocks

NASA Technical Reports Server (NTRS)

Decher, R.; Allan, D. W.; Alley, C. O.; Vessot, R. F. C.; Winkler, G. M. R.

1981-01-01

A Space Shuttle experiment in which a hydrogen maser clock on board the Space Shuttle will be compared with clocks on the ground using two-way microwave and short pulse laser signals is described. The accuracy goal for the experiment is 1 nsec or better for the time transfer and 10 to the minus 14th power for the frequency comparison. A direct frequency comparison of primary standards at the 10 to the minus 14th power accuracy level is a unique feature of the proposed system. Both time and frequency transfer will be accomplished by microwave transmission, while the laser signals provide calibration of the system as well as subnanosecond time transfer.

The optional selection of micro-motion feature based on Support Vector Machine

NASA Astrophysics Data System (ADS)

Li, Bo; Ren, Hongmei; Xiao, Zhi-he; Sheng, Jing

2017-11-01

Micro-motion form of target is multiple, different micro-motion forms are apt to be modulated, which makes it difficult for feature extraction and recognition. Aiming at feature extraction of cone-shaped objects with different micro-motion forms, this paper proposes the best selection method of micro-motion feature based on support vector machine. After the time-frequency distribution of radar echoes, comparing the time-frequency spectrum of objects with different micro-motion forms, features are extracted based on the differences between the instantaneous frequency variations of different micro-motions. According to the methods based on SVM (Support Vector Machine) features are extracted, then the best features are acquired. Finally, the result shows the method proposed in this paper is feasible under the test condition of certain signal-to-noise ratio(SNR).

Frequency spectrum of tantalum at temperatures of 293-2300 K

NASA Astrophysics Data System (ADS)

Semenov, V. A.; Kozlov, Zh. A.; Krachun, L.; Mateescu, G.; Morozov, V. M.; Oprea, A. I.; Oprea, K.; Puchkov, A. V.

2010-05-01

The temperature dependence of the frequency spectrum of tantalum in the temperature range from room temperature to 2300 K has been studied for the first time using inelastic slow-neutron scattering. The inelastic slow-neutron scattering spectra have been measured at different temperatures on a DIN-2PI time-of-flight spectrometer installed at the IBR-2 nuclear reactor (Joint Institute for Nuclear Research, Dubna, Russia) with the use of a TS3000K high-temperature thermostat. From the measured spectra, the frequency spectra of the tantalum crystal lattice have been determined at temperatures of 293, 1584, and 2300 K by the iteration method. As the temperature increases, the frequency spectrum, on the whole, is softened and the specific features manifested themselves at room temperature are smoothed. The variations observed have been explained by the increase in the role of the effects of vibration anharmonism at high temperatures.

Low Frequency Variants, Collapsed Based on Biological Knowledge, Uncover Complexity of Population Stratification in 1000 Genomes Project Data

PubMed Central

Moore, Carrie B.; Wallace, John R.; Wolfe, Daniel J.; Frase, Alex T.; Pendergrass, Sarah A.; Weiss, Kenneth M.; Ritchie, Marylyn D.

2013-01-01

Analyses investigating low frequency variants have the potential for explaining additional genetic heritability of many complex human traits. However, the natural frequencies of rare variation between human populations strongly confound genetic analyses. We have applied a novel collapsing method to identify biological features with low frequency variant burden differences in thirteen populations sequenced by the 1000 Genomes Project. Our flexible collapsing tool utilizes expert biological knowledge from multiple publicly available database sources to direct feature selection. Variants were collapsed according to genetically driven features, such as evolutionary conserved regions, regulatory regions genes, and pathways. We have conducted an extensive comparison of low frequency variant burden differences (MAF<0.03) between populations from 1000 Genomes Project Phase I data. We found that on average 26.87% of gene bins, 35.47% of intergenic bins, 42.85% of pathway bins, 14.86% of ORegAnno regulatory bins, and 5.97% of evolutionary conserved regions show statistically significant differences in low frequency variant burden across populations from the 1000 Genomes Project. The proportion of bins with significant differences in low frequency burden depends on the ancestral similarity of the two populations compared and types of features tested. Even closely related populations had notable differences in low frequency burden, but fewer differences than populations from different continents. Furthermore, conserved or functionally relevant regions had fewer significant differences in low frequency burden than regions under less evolutionary constraint. This degree of low frequency variant differentiation across diverse populations and feature elements highlights the critical importance of considering population stratification in the new era of DNA sequencing and low frequency variant genomic analyses. PMID:24385916

Radio Frequency Ultrasound Time Series Signal Analysis to Evaluate High-intensity Focused Ultrasound Lesion Formation Status in Tissue.

PubMed

Mobasheri, Saeedeh; Behnam, Hamid; Rangraz, Parisa; Tavakkoli, Jahan

2016-01-01

High-intensity focused ultrasound (HIFU) is a novel treatment modality used by scientists and clinicians in the recent decades. This modality has had a great and significant success as a noninvasive surgery technique applicable in tissue ablation therapy and cancer treatment. In this study, radio frequency (RF) ultrasound signals were acquired and registered in three stages of before, during, and after HIFU exposures. Different features of RF time series signals including the sum of amplitude spectrum in the four quarters of the frequency range, the slope, and intercept of the best-fit line to the entire power spectrum and the Shannon entropy were utilized to distinguish between the HIFU-induced thermal lesion and the normal tissue. We also examined the RF data, frame by frame to identify exposure effects on the formation and characteristics of a HIFU thermal lesion at different time steps throughout the treatment. The results obtained showed that the spectrum frequency quarters and the slope and intercept of the best fit line to the entire power spectrum both increased two times during the HIFU exposures. The Shannon entropy, however, decreased after the exposures. In conclusion, different characteristics of RF time series signal possess promising features that can be used to characterize ablated and nonablated tissues and to distinguish them from each other in a quasi-quantitative fashion.

Effects of Sound Frequency on Audiovisual Integration: An Event-Related Potential Study.

PubMed

Yang, Weiping; Yang, Jingjing; Gao, Yulin; Tang, Xiaoyu; Ren, Yanna; Takahashi, Satoshi; Wu, Jinglong

2015-01-01

A combination of signals across modalities can facilitate sensory perception. The audiovisual facilitative effect strongly depends on the features of the stimulus. Here, we investigated how sound frequency, which is one of basic features of an auditory signal, modulates audiovisual integration. In this study, the task of the participant was to respond to a visual target stimulus by pressing a key while ignoring auditory stimuli, comprising of tones of different frequencies (0.5, 1, 2.5 and 5 kHz). A significant facilitation of reaction times was obtained following audiovisual stimulation, irrespective of whether the task-irrelevant sounds were low or high frequency. Using event-related potential (ERP), audiovisual integration was found over the occipital area for 0.5 kHz auditory stimuli from 190-210 ms, for 1 kHz stimuli from 170-200 ms, for 2.5 kHz stimuli from 140-200 ms, 5 kHz stimuli from 100-200 ms. These findings suggest that a higher frequency sound signal paired with visual stimuli might be early processed or integrated despite the auditory stimuli being task-irrelevant information. Furthermore, audiovisual integration in late latency (300-340 ms) ERPs with fronto-central topography was found for auditory stimuli of lower frequencies (0.5, 1 and 2.5 kHz). Our results confirmed that audiovisual integration is affected by the frequency of an auditory stimulus. Taken together, the neurophysiological results provide unique insight into how the brain processes a multisensory visual signal and auditory stimuli of different frequencies.

A decadal tropical Pacific condition unfavorable to central Pacific El Niño

NASA Astrophysics Data System (ADS)

Zhong, Wenxiu; Zheng, Xiao-Tong; Cai, Wenju

2017-08-01

The frequency of central Pacific (CP) El Niño events displays strong decadal variability but the associated dynamics are unclear. The Interdecadal Pacific Oscillation (IPO) and the tropical Pacific decadal variability (TPDV) are two dominant modes of tropical Pacific decadal variability that can interact with high-frequency activities. Using a 500 year control integration from the Geophysical Fluid Dynamics Laboratory Earth System Model, we find that the difference in mean state between the low-frequency and high-frequency CP El Niño periods is similar to the decadal background condition concurrently contributed by a negative IPO and a positive TPDV. This decadal state features strengthened trade winds west of the International Date Line and anomalous cool sea surface temperatures across the central tropical Pacific. As such, positive zonal advection feedback is difficult to be generated over the central to western tropical Pacific during the CP El Niño developing season, resulting in the low CP El Niño frequency.

Phase-locking to a free-space terahertz comb for metrological-grade terahertz lasers.

PubMed

Consolino, L; Taschin, A; Bartolini, P; Bartalini, S; Cancio, P; Tredicucci, A; Beere, H E; Ritchie, D A; Torre, R; Vitiello, M S; De Natale, P

2012-01-01

Optical frequency comb synthesizers have represented a revolutionary approach to frequency metrology, providing a grid of frequency references for any laser emitting within their spectral coverage. Extending the metrological features of optical frequency comb synthesizers to the terahertz domain would be a major breakthrough, due to the widespread range of accessible strategic applications and the availability of stable, high-power and widely tunable sources such as quantum cascade lasers. Here we demonstrate phase-locking of a 2.5 THz quantum cascade laser to a free-space comb, generated in a LiNbO(3) waveguide and covering the 0.1-6 THz frequency range. We show that even a small fraction (<100 nW) of the radiation emitted from the quantum cascade laser is sufficient to generate a beat note suitable for phase-locking to the comb, paving the way to novel metrological-grade terahertz applications, including high-resolution spectroscopy, manipulation of cold molecules, astronomy and telecommunications.

Calculating rhythmicity of infant breathing using wavelets

NASA Astrophysics Data System (ADS)

Macey, Katherine E.; Page, Wyatt H.; Harper, Ronald M.; Macey, Paul M.; Ford, Rodney P. K.

2000-12-01

Breathing signals are one set of physiological data that may provide information regarding the mechanisms that cause SIDS. Isolated breathing pauses have been implicated in fatal events. Other features of interest include slow amplitude modulation of the breathing signal, a phenomenon whose origin is unclear, and periodic breathing. The latter describes a repetitive series of apnea, and may be considered an extreme manifestation of amplitude modulation with successive cessations of breathing. Rhythmicity is defined to assess the impact of amplitude modulation on breathing signals and describes the extent to which frequency components remain constant for the duration of the signal. The wavelet transform was used to identify sections of constant frequency components within signals. Rhythmicity can be evaluated for all the frequency components in a signal, for individual frequencies. The rhythmicity of eight breathing epochs from sleeping infants at high and low risk for SIDS was calculated. Initial results show breathing from infants at high risk for SIDS exhibits greater rhythmicity of modulating frequencies than breathing from low risk infants.

Wavelet Packet Feature Assessment for High-Density Myoelectric Pattern Recognition and Channel Selection toward Stroke Rehabilitation.

PubMed

Wang, Dongqing; Zhang, Xu; Gao, Xiaoping; Chen, Xiang; Zhou, Ping

2016-01-01

This study presents wavelet packet feature assessment of neural control information in paretic upper limb muscles of stroke survivors for myoelectric pattern recognition, taking advantage of high-resolution time-frequency representations of surface electromyogram (EMG) signals. On this basis, a novel channel selection method was developed by combining the Fisher's class separability index and the sequential feedforward selection analyses, in order to determine a small number of appropriate EMG channels from original high-density EMG electrode array. The advantages of the wavelet packet features and the channel selection analyses were further illustrated by comparing with previous conventional approaches, in terms of classification performance when identifying 20 functional arm/hand movements implemented by 12 stroke survivors. This study offers a practical approach including paretic EMG feature extraction and channel selection that enables active myoelectric control of multiple degrees of freedom with paretic muscles. All these efforts will facilitate upper limb dexterity restoration and improved stroke rehabilitation.

Admissible Diffusion Wavelets and Their Applications in Space-Frequency Processing.

PubMed

Hou, Tingbo; Qin, Hong

2013-01-01

As signal processing tools, diffusion wavelets and biorthogonal diffusion wavelets have been propelled by recent research in mathematics. They employ diffusion as a smoothing and scaling process to empower multiscale analysis. However, their applications in graphics and visualization are overshadowed by nonadmissible wavelets and their expensive computation. In this paper, our motivation is to broaden the application scope to space-frequency processing of shape geometry and scalar fields. We propose the admissible diffusion wavelets (ADW) on meshed surfaces and point clouds. The ADW are constructed in a bottom-up manner that starts from a local operator in a high frequency, and dilates by its dyadic powers to low frequencies. By relieving the orthogonality and enforcing normalization, the wavelets are locally supported and admissible, hence facilitating data analysis and geometry processing. We define the novel rapid reconstruction, which recovers the signal from multiple bands of high frequencies and a low-frequency base in full resolution. It enables operations localized in both space and frequency by manipulating wavelet coefficients through space-frequency filters. This paper aims to build a common theoretic foundation for a host of applications, including saliency visualization, multiscale feature extraction, spectral geometry processing, etc.

Astrosat/LAXPC Reveals the High-energy Variability of GRS 1915+105 in the X Class

NASA Astrophysics Data System (ADS)

Yadav, J. S.; Misra, Ranjeev; Verdhan Chauhan, Jai; Agrawal, P. C.; Antia, H. M.; Pahari, Mayukh; Dedhia, Dhiraj; Katoch, Tilak; Madhwani, P.; Manchanda, R. K.; Paul, B.; Shah, Parag; Ishwara-Chandra, C. H.

2016-12-01

We present the first quick look analysis of data from nine AstroSat's Large Area X-ray Proportional Counter (LAXPC) observations of GRS 1915+105 during 2016 March when the source had the characteristics of being in the Radio-quiet χ class. We find that a simple empirical model of a disk blackbody emission, with Comptonization and a broad Gaussian Iron line can fit the time-averaged 3-80 keV spectrum with a systematic uncertainty of 1.5% and a background flux uncertainty of 4%. A simple dead time corrected Poisson noise level spectrum matches well with the observed high-frequency power spectra till 50 kHz and as expected the data show no significant high-frequency (\\gt 20 {Hz}) features. Energy dependent power spectra reveal a strong low-frequency (2-8 Hz) quasi-periodic oscillation and its harmonic along with broadband noise. The QPO frequency changes rapidly with flux (nearly 4 Hz in ˜5 hr). With increasing QPO frequency, an excess noise component appears significantly in the high-energy regime (\\gt 8 keV). At the QPO frequencies, the time-lag as a function of energy has a non-monotonic behavior such that the lags decrease with energy till about 15-20 keV and then increase for higher energies. These first-look results benchmark the performance of LAXPC at high energies and confirms that its data can be used for more sophisticated analysis such as flux or frequency-resolved spectro-timing studies.

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

NASA Astrophysics Data System (ADS)

Grasing, David; Desai, Sachi; Morcos, Amir

2008-04-01

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

Artillery/mortar type classification based on detected acoustic transients

NASA Astrophysics Data System (ADS)

Morcos, Amir; Grasing, David; Desai, Sachi

2008-04-01

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

Artillery/mortar round type classification to increase system situational awareness

NASA Astrophysics Data System (ADS)

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

2008-04-01

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

The Origin of High-Frequency Hearing in Whales.

PubMed

Churchill, Morgan; Martinez-Caceres, Manuel; de Muizon, Christian; Mnieckowski, Jessica; Geisler, Jonathan H

2016-08-22

Odontocetes (toothed whales) rely upon echoes of their own vocalizations to navigate and find prey underwater [1]. This sensory adaptation, known as echolocation, operates most effectively when using high frequencies, and odontocetes are rivaled only by bats in their ability to perceive ultrasonic sound greater than 100 kHz [2]. Although features indicative of ultrasonic hearing are present in the oldest known odontocetes [3], the significance of this finding is limited by the methods employed and taxa sampled. In this report, we describe a new xenorophid whale (Echovenator sandersi, gen. et sp. nov.) from the Oligocene of South Carolina that, as a member of the most basal clade of odontocetes, sheds considerable light on the evolution of ultrasonic hearing. By placing high-resolution CT data from Echovenator sandersi, 2 hippos, and 23 fossil and extant whales in a phylogenetic context, we conclude that ultrasonic hearing, albeit in a less specialized form, evolved at the base of the odontocete radiation. Contrary to the hypothesis that odontocetes evolved from low-frequency specialists [4], we find evidence that stem cetaceans, the archaeocetes, were more sensitive to high-frequency sound than their terrestrial ancestors. This indicates that selection for high-frequency hearing predates the emergence of Odontoceti and the evolution of echolocation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Investigating the high-frequency spectral features of SNRs Tycho, W44 and IC443 with the Sardinia Radio Telescope

NASA Astrophysics Data System (ADS)

Loru, S.; Pellizzoni, A.; Egron, E.; Righini, S.; Iacolina, M. N.; Mulas, S.; Cardillo, M.; Marongiu, M.; Ricci, R.; Bachetti, M.; Pilia, M.; Trois, A.; Ingallinera, A.; Petruk, O.; Murtas, G.; Serra, G.; Concu, F. Buffa R.; Gaudiomonte, F.; Melis, A.; Navarrini, A.; Perrodin, D.; Valente, G.

2018-05-01

The main characteristics in the radio continuum spectra of Supernova Remnants (SNRs) result from simple synchrotron emission. In addition, electron acceleration mechanisms can shape the spectra in specific ways, especially at high radio frequencies. These features are connected to the age and the peculiar conditions of the local interstellar medium interacting with the SNR. Whereas the bulk radio emission is expected at up to 20 - 50 GHz, sensitive high-resolution images of SNRs above 10 GHz are lacking and are not easily achievable, especially in the confused regions of the Galactic Plane. In the framework of the early science observations with the Sardinia Radio Telescope in February-March 2016, we obtained high-resolution images of SNRs Tycho, W44 and IC443 that provided accurate integrated flux density measurements at 21.4 GHz: 8.8 ± 0.9 Jy for Tycho, 25 ± 3 Jy for W44 and 66 ± 7 Jy for IC443. We coupled the SRT measurements with radio data available in the literature in order to characterise the integrated and spatially-resolved spectra of these SNRs, and to find significant frequency- and region-dependent spectral slope variations. For the first time, we provide direct evidence of a spectral break in the radio spectral energy distribution of W44 at an exponential cutoff frequency of 15 ± 2 GHz. This result constrains the maximum energy of the accelerated electrons in the range 6 - 13 GeV, in agreement with predictions indirectly derived from AGILE and Fermi-LAT gamma-ray observations. With regard to IC443, our results confirm the noticeable presence of a bump in the integrated spectrum around 20 - 70 GHz that could result from a spinning dust emission mechanism.

High-frequency tone-pip-evoked otoacoustic emissions in chinchillas

NASA Astrophysics Data System (ADS)

Siegel, Jonathan H.; Charaziak, Karolina K.

2015-12-01

We measured otoacoustic emissions in anesthetized chinchillas evoked by short (1 ms) high-frequency (4 kHz) tone-pips (TEOAE) using either a compression or suppression method to separate the stimulus from the emission. Both methods revealed consistent features of the TEOAEs. The main spectral band of the emission generally corresponded to the spectrum of the stimulus, exhibiting a group delay similar to that of SFOAEs [9]. However, a second spectral band below 1.5 kHz, clearly separated from the low-frequency cut-off frequency of the stimulus spectrum, corresponded to an amplitude modulation of the waveform of the TEOAE. The group delay of this low-frequency band was similar to that of the main band near the probe frequency. The average level and group delay of the main band declined monotonically when revealed as the suppressor frequency was raised above the probe. The low-frequency band was more sensitive than the main band to shifts in compound action potential thresholds near the probe frequency induced by acute exposure to intense tones. Taken together, the experiments indicate that both the main and low-frequency bands of the TEOAE are generated primarily near the cochlear region maximally stimulated by the probe, but that significant contributions arise over a large region even more basal.

Radial evolution of power spectra of interplanetary Alfvenic turbulence

NASA Technical Reports Server (NTRS)

Bavassano, B.; Dobrowolny, M.; Mariani, F.; Ness, N. F.

1981-01-01

The radial evolution of the power spectra of the MHD turbulence within the trailing edge of high speed streams in the solar wind was investigated with the magnetic field data of Helios 1 and 2 for heliocentric distance between 0.3 and 0.9 AU. In the analyzed frequency range (.00028 Hz to .0083 Hz) the computed spectra have, near the Earth, values of the spectral index close to that predicted for an incompressible hydromagnetic turbulence in a stationary state. Approaching the Sun the spectral slope remains unchanged for frequencies f or approximately .00 Hz, whereas at lower frequencies, a clear evolution toward a less steep fall off with frequency is found. The radial gradient of the power in Alfvenic fluctuations depends on frequency and it increases upon increasing frequency. For frequencies f or approximately .00 Hz, however, the radial gradient remains approximately the same. Possible theoretical implications of the observational features are discussed.

Automatic sleep staging using empirical mode decomposition, discrete wavelet transform, time-domain, and nonlinear dynamics features of heart rate variability signals.

PubMed

Ebrahimi, Farideh; Setarehdan, Seyed-Kamaledin; Ayala-Moyeda, Jose; Nazeran, Homer

2013-10-01

The conventional method for sleep staging is to analyze polysomnograms (PSGs) recorded in a sleep lab. The electroencephalogram (EEG) is one of the most important signals in PSGs but recording and analysis of this signal presents a number of technical challenges, especially at home. Instead, electrocardiograms (ECGs) are much easier to record and may offer an attractive alternative for home sleep monitoring. The heart rate variability (HRV) signal proves suitable for automatic sleep staging. Thirty PSGs from the Sleep Heart Health Study (SHHS) database were used. Three feature sets were extracted from 5- and 0.5-min HRV segments: time-domain features, nonlinear-dynamics features and time-frequency features. The latter was achieved by using empirical mode decomposition (EMD) and discrete wavelet transform (DWT) methods. Normalized energies in important frequency bands of HRV signals were computed using time-frequency methods. ANOVA and t-test were used for statistical evaluations. Automatic sleep staging was based on HRV signal features. The ANOVA followed by a post hoc Bonferroni was used for individual feature assessment. Most features were beneficial for sleep staging. A t-test was used to compare the means of extracted features in 5- and 0.5-min HRV segments. The results showed that the extracted features means were statistically similar for a small number of features. A separability measure showed that time-frequency features, especially EMD features, had larger separation than others. There was not a sizable difference in separability of linear features between 5- and 0.5-min HRV segments but separability of nonlinear features, especially EMD features, decreased in 0.5-min HRV segments. HRV signal features were classified by linear discriminant (LD) and quadratic discriminant (QD) methods. Classification results based on features from 5-min segments surpassed those obtained from 0.5-min segments. The best result was obtained from features using 5-min HRV segments classified by the LD classifier. A combination of linear/nonlinear features from HRV signals is effective in automatic sleep staging. Moreover, time-frequency features are more informative than others. In addition, a separability measure and classification results showed that HRV signal features, especially nonlinear features, extracted from 5-min segments are more discriminative than those from 0.5-min segments in automatic sleep staging. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Cuticular features as indicators of environmental pollution

Treesearch

G. K. Sharma

1976-01-01

Several leaf cuticular features such as stomatal frequency, stomatal size, trichome length, type, and frequency, and subsidiary cell complex respond to environmental pollution in different ways and hence can be used as indicators of environmental pollution in an area. Several modifications in cuticular features under polluted environments seem to indicate ecotypic or...

Frequency and Wavevector Dependence of the Atomic Level Stress-Stress Correlation Function in a Model Supercooled Liquid

NASA Astrophysics Data System (ADS)

Levashov, Valentin A.; Morris, James R.; Egami, Takeshi

2012-02-01

Temporal and spatial correlations among the local atomic level shear stresses were studied for a model liquid iron by molecular dynamics simulation [PRL 106,115703]. Integration over time and space of the shear stress correlation function F(r,t) yields viscosity via Green-Kubo relation. The stress correlation function in time and space F(r,t) was Fourier transformed to study the dependence on frequency, E, and wave vector, Q. The results, F(Q,E), showed damped shear stress waves propagating in the liquid for small Q at high and low temperatures. We also observed additional diffuse feature that appears as temperature is reduced below crossover temperature of potential energy landscape at relatively low frequencies at small Q. We suggest that this additional feature might be related to dynamic heterogeneity and boson peaks. We also discuss a relation between the time-scale of the stress-stress correlation function and the alpha-relaxation time of the intermediate self-scattering function S(Q,E).

Detection of broken rotor bar faults in induction motor at low load using neural network.

PubMed

Bessam, B; Menacer, A; Boumehraz, M; Cherif, H

2016-09-01

The knowledge of the broken rotor bars characteristic frequencies and amplitudes has a great importance for all related diagnostic methods. The monitoring of motor faults requires a high resolution spectrum to separate different frequency components. The Discrete Fourier Transform (DFT) has been widely used to achieve these requirements. However, at low slip this technique cannot give good results. As a solution for these problems, this paper proposes an efficient technique based on a neural network approach and Hilbert transform (HT) for broken rotor bar diagnosis in induction machines at low load. The Hilbert transform is used to extract the stator current envelope (SCE). Two features are selected from the (SCE) spectrum (the amplitude and frequency of the harmonic). These features will be used as input for neural network. The results obtained are astonishing and it is capable to detect the correct number of broken rotor bars under different load conditions. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

How much is enough? Examining frequency criteria for NSSI disorder in adolescent inpatients.

PubMed

Muehlenkamp, Jennifer J; Brausch, Amy M; Washburn, Jason J

2017-06-01

To empirically evaluate the diagnostic relevance of the proposed Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5 ; APA, 2013) Criterion-A frequency threshold for nonsuicidal self-injury (NSSI) disorder. Archival, de-identified, self-reported clinical assessment data from 746 adolescent psychiatric patients (Mage = 14.97; 88% female; 76% White) were used. The sample was randomly split into 2 unique samples for data analyses. Measures included assessments of NSSI, proposed DSM-5 NSSI-disorder criteria, psychopathology, dysfunction, distress, functional impairment, and suicidality. Discriminant-function analyses run with Sample A identified a significant differentiation of groups based on a frequency of NSSI at 25 or more days in the past year, Λ = .814, χ2(54) = 72.59, p < .05, canonical R2 = .36. This cutoff was replicated in the second sample. All patients were coded into 1 of 3 empirically derived NSSI-frequency cutoff groups: high (>25 days), moderate (5-24 days), and low (1-4 days) and compared. The high-NSSI group scored higher on most NSSI features, including DSM-5 -proposed Criterion-B and -C symptoms, depression, psychotic symptoms, substance abuse, borderline personality-disorder features, suicidal ideation, and suicide plans, than the moderate- and low-NSSI groups, who did not differ from each other on many of the variables. The currently proposed DSM-5 Criterion-A frequency threshold for NSSI disorder lacks validity and clinical utility. The field needs to consider raising the frequency threshold to ensure that a meaningful and valid set of diagnostic criteria are established, and to avoid overpathologizing individuals who infrequently engage in NSSI. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

High frequency power distribution system

NASA Technical Reports Server (NTRS)

Patel, Mikund R.

1986-01-01

The objective of this project was to provide the technology of high frequency, high power transmission lines to the 100 kW power range at 20 kHz frequency. In addition to the necessary design studies, a 150 m long, 600 V, 60 A transmission line was built, tested and delivered for full vacuum tests. The configuration analysis on five alternative configurations resulted in the final selection of the three parallel Litz straps configuration, which gave a virtually concentric design in the electromagnetic sense. Low inductance, low EMI and flexibility in handling are the key features of this configuration. The final design was made after a parametric study to minimize the losses, weight and inductance. The construction of the cable was completed with no major difficulties. The R,L,C parameters measured on the cable agreed well with the calculated values. The corona tests on insulation samples showed a safety factor of 3.

Temperature-dependent THz vibrational spectra of clenbuterol hydrochloride

NASA Astrophysics Data System (ADS)

Yang, YuPing; Lei, XiangYun; Yue, Ai; Zhang, Zhenwei

2013-04-01

Using the high-resolution Terahertz Time-domain spectroscopy (THz-TDS) and the standard sample pellet technique, the far-infrared vibrational spectra of clenbuterol hydrochloride (CH), a β 2-adrenergic agonist for decreasing fat deposition and enhancing protein accretion, were measured in temperature range of 77-295 K. Between 0.2 and 3.6 THz (6.6-120.0 cm-1), seven highly resolved spectral features, strong line-narrowing and a frequency blue-shift were observed with cooling. However, ractopamine hydrochloride, with some structural and pharmacological similarities to clenbuterol hydrochloride, showed no spectral features, indicating high sensitivity and strong specificity of THz-TDS. These results could be used for the rapid and nondestructive CH residual detection in food safety control.

A crowdful of letters: disentangling the role of similarity, eccentricity and spatial frequencies in letter crowding.

PubMed

Zahabi, Sacha; Arguin, Martin

2014-04-01

The present study investigated the joint impact of target-flanker similarity and of spatial frequency content on the crowding effect in letter identification. We presented spatial frequency filtered letters to neurologically intact non-dyslexic readers while manipulating target-flanker distance, target eccentricity and target-flanker confusability (letter similarity metric based on published letter confusion matrices). The results show that high target-flanker confusability magnifies crowding. They also reveal an intricate pattern of interactions of the spatial frequency content of the stimuli with target eccentricity, flanker distance and similarity. The findings are congruent with the notion that crowding results from the inappropriate pooling of target and flanker features and that this integration is more likely to match a response template at a subsequent decision stage with similar than dissimilar flankers. In addition, the evidence suggests that crowding from similar flankers is biased towards relatively high spatial frequencies and that crowding shifts towards lower spatial frequencies as target eccentricity is increased. Copyright © 2014 Elsevier B.V. All rights reserved.

Inductive phenomena at low frequencies in impedance spectra of proton exchange membrane fuel cells - A review

NASA Astrophysics Data System (ADS)

Pivac, Ivan; Barbir, Frano

2016-09-01

The results of electrochemical impedance spectroscopy of proton exchange membrane (PEM) fuel cells may exhibit inductive phenomena at low frequencies. The occurrence of inductive features at high frequencies is explained by the cables and wires of the test system. However, explanation of inductive loop at low frequencies requires a more detailed study. This review paper discusses several possible causes of such inductive behavior in PEM fuel cells, such as side reactions with intermediate species, carbon monoxide poisoning, and water transport, also as their equivalent circuit representations. It may be concluded that interpretation of impedance spectra at low frequencies is still ambiguous, and that better equivalent circuit models are needed with clearly defined physical meaning of each of the circuit elements.

Bottomside Ionospheric Electron Density Specification using Passive High Frequency Signals

NASA Astrophysics Data System (ADS)

Kaeppler, S. R.; Cosgrove, R. B.; Mackay, C.; Varney, R. H.; Kendall, E. A.; Nicolls, M. J.

2016-12-01

The vertical bottomside electron density profile is influenced by a variety of natural sources, most especially traveling ionospheric disturbances (TIDs). These disturbances cause plasma to be moved up or down along the local geomagnetic field and can strongly impact the propagation of high frequency radio waves. While the basic physics of these perturbations has been well studied, practical bottomside models are not well developed. We present initial results from an assimilative bottomside ionosphere model. This model uses empirical orthogonal functions based on the International Reference Ionosphere (IRI) to develop a vertical electron density profile, and features a builtin HF ray tracing function. This parameterized model is then perturbed to model electron density perturbations associated with TIDs or ionospheric gradients. Using the ray tracing feature, the model assimilates angle of arrival measurements from passive HF transmitters. We demonstrate the effectiveness of the model using angle of arrival data. Modeling results of bottomside electron density specification are compared against suitable ancillary observations to quantify accuracy of our model.

Robust k-mer frequency estimation using gapped k-mers

PubMed Central

Ghandi, Mahmoud; Mohammad-Noori, Morteza

2013-01-01

Oligomers of fixed length, k, commonly known as k-mers, are often used as fundamental elements in the description of DNA sequence features of diverse biological function, or as intermediate elements in the constuction of more complex descriptors of sequence features such as position weight matrices. k-mers are very useful as general sequence features because they constitute a complete and unbiased feature set, and do not require parameterization based on incomplete knowledge of biological mechanisms. However, a fundamental limitation in the use of k-mers as sequence features is that as k is increased, larger spatial correlations in DNA sequence elements can be described, but the frequency of observing any specific k-mer becomes very small, and rapidly approaches a sparse matrix of binary counts. Thus any statistical learning approach using k-mers will be susceptible to noisy estimation of k-mer frequencies once k becomes large. Because all molecular DNA interactions have limited spatial extent, gapped k-mers often carry the relevant biological signal. Here we use gapped k-mer counts to more robustly estimate the ungapped k-mer frequencies, by deriving an equation for the minimum norm estimate of k-mer frequencies given an observed set of gapped k-mer frequencies. We demonstrate that this approach provides a more accurate estimate of the k-mer frequencies in real biological sequences using a sample of CTCF binding sites in the human genome. PMID:23861010

Robust k-mer frequency estimation using gapped k-mers.

PubMed

Ghandi, Mahmoud; Mohammad-Noori, Morteza; Beer, Michael A

2014-08-01

Oligomers of fixed length, k, commonly known as k-mers, are often used as fundamental elements in the description of DNA sequence features of diverse biological function, or as intermediate elements in the constuction of more complex descriptors of sequence features such as position weight matrices. k-mers are very useful as general sequence features because they constitute a complete and unbiased feature set, and do not require parameterization based on incomplete knowledge of biological mechanisms. However, a fundamental limitation in the use of k-mers as sequence features is that as k is increased, larger spatial correlations in DNA sequence elements can be described, but the frequency of observing any specific k-mer becomes very small, and rapidly approaches a sparse matrix of binary counts. Thus any statistical learning approach using k-mers will be susceptible to noisy estimation of k-mer frequencies once k becomes large. Because all molecular DNA interactions have limited spatial extent, gapped k-mers often carry the relevant biological signal. Here we use gapped k-mer counts to more robustly estimate the ungapped k-mer frequencies, by deriving an equation for the minimum norm estimate of k-mer frequencies given an observed set of gapped k-mer frequencies. We demonstrate that this approach provides a more accurate estimate of the k-mer frequencies in real biological sequences using a sample of CTCF binding sites in the human genome.

Analysis of the seismic signals generated by controlled single-block rockfalls on soft clay shales sediments: the Rioux Bourdoux slope experiment (French Alps).

NASA Astrophysics Data System (ADS)

Hibert, Clément; Provost, Floriane; Malet, Jean-Philippe; Bourrier, Franck; Berger, Frédéric; Bornemann, Pierrick; Borgniet, Laurent; Tardif, Pascal; Mermin, Eric

2016-04-01

Understanding the dynamics of rockfalls is critical to mitigate the associated hazards but is made very difficult by the nature of these natural disasters that makes them hard to observe directly. Recent advances in seismology allow to determine the dynamics of the largest landslides on Earth from the very low-frequency seismic waves they generate. However, the vast majority of rockfalls that occur worldwide are too small to generate such low-frequency seismic waves and thus these methods cannot be used to reconstruct their dynamics. However, if seismic sensors are close enough, these events will generate high-frequency seismic signals. Unfortunately we cannot yet use these high-frequency seismic records to infer parameters synthetizing the rockfall dynamics as the source of these waves is not well understood. One of the first steps towards understanding the physical processes involved in the generation of high-frequency seismic waves by rockfalls is to study the link between the dynamics of a single block propagating along a well-known path and the features of the seismic signal generated. We conducted controlled releases of single blocks of limestones in a gully of clay-shales (e.g. black marls) in the Rioux Bourdoux torrent (French Alps). 28 blocks, with masses ranging from 76 kg to 472 kg, were released. A monitoring network combining high-velocity cameras, a broadband seismometer and an array of 4 high-frequency seismometers was deployed near the release area and along the travel path. The high-velocity cameras allow to reconstruct the 3D trajectories of the blocks, to estimate their velocities and the position of the different impacts with the slope surface. These data are compared to the seismic signals recorded. As the distance between the block and the seismic sensors at the time of each impact is known, we can determine the associated seismic signal amplitude corrected from propagation and attenuation effects. We can further compare the velocity, the energy and the momentum of the block at each impact to the true amplitude and the energy of the corresponding part of the seismic signal. Finding potential correlations and scaling laws between the dynamics of the source and the high-frequency seismic signal features constitutes an important breakthrough to understand more complex slope movements that involve multiple blocks or granular flows. This approach may lead to future developments of methods able to determine the dynamics of a large variety of slope movements directly from the seismic signals they generate.

Downscaling hydrodynamics features to depict causes of major productivity of Sicilian-Maltese area and implications for resource management.

PubMed

Capodici, Fulvio; Ciraolo, Giuseppe; Cosoli, Simone; Maltese, Antonino; Mangano, M Cristina; Sarà, Gianluca

2018-07-01

Chlorophyll-a (CHL-a) and sea surface temperature (SST) are generally accepted as proxies for water quality. They can be easily retrieved in a quasi-near real time mode through satellite remote sensing and, as such, they provide an overview of the water quality on a synoptic scale in open waters. Their distributions evolve in space and time in response to local and remote forcing, such as winds and currents, which however have much finer temporal and spatial scales than those resolvable by satellites in spite of recent advances in satellite remote-sensing techniques. Satellite data are often characterized by a moderate temporal resolution to adequately catch the actual sub-grid physical processes. Conventional pointwise measurements can resolve high-frequency motions such as tides or high-frequency wind-driven currents, however they are inadequate to resolve their spatial variability over wide areas. We show in this paper that a combined use of near-surface currents, available through High-Frequency (HF) radars, and satellite data (e.g., TERRA and AQUA/MODIS), can properly resolve the main oceanographic features in both coastal and open-sea regions, particularly at the coastal boundaries where satellite imageries fail, and are complementary tools to interpret ocean productivity and resource management in the Sicily Channel. Copyright © 2018. Published by Elsevier B.V.

Hierarchical Decentralized Control Strategy for Demand-Side Primary Frequency Response

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

Lian, Jianming; Hansen, Jacob; Marinovici, Laurentiu D.

The Grid Friendlymore » $$^\\textrm{TM}$$ Appliance~(GFA) controller, developed at Pacific Northwest National Laboratory, was designed for the purpose of autonomously switching off appliances by detecting under-frequency events. In this paper, a new frequency responsive load~(FRL) controller is first proposed by extending the functionality of the original GFA controller. The proposed FRL controller can autonomously switch on (or off) end-use loads by detecting over-frequency (or under-frequency) events through local frequency measurement. Then, a hierarchical decentralized control framework is developed for engaging the end-use loads to provide primary frequency response with the proposed FRL controller. The developed framework has several important features that are desirable in terms of providing primary frequency control. It not only exclusively maintains the autonomous operation of the end-use loads, but also effectively overcomes the stability issue associated with high penetration of FRLs. The simulation results illustrate the effectiveness of the developed hierarchical control framework for providing primary frequency response with the proposed FRL controller.« less

Petrosal anatomy and inner ear structures of the Late Jurassic Henkelotherium (Mammalia, Cladotheria, Dryolestoidea): insight into the early evolution of the ear region in cladotherian mammals

PubMed Central

Ruf, Irina; Luo, Zhe-Xi; Wible, John R; Martin, Thomas

2009-01-01

The petrosal anatomy and inner ear structure of Jurassic cladotherian mammals represent the ancestral morphological conditions (groundplan) from which modern therian mammals (marsupials and placentals) have evolved. We present the reconstruction of the petrosal and inner ear features of the Late Jurassic dryolestoid mammal Henkelotherium guimarotae from high-resolution computed tomography and three-dimensional imaging analysis. This study of Henkelotherium revealed a combination of derived and primitive features, including: cladotherian apomorphies, such as the promontorial sulcus for the internal carotid artery and reduced lateral trough; trechnotherian characters, such as an enclosed cochlear canaliculus for the perilymphatic duct, post-promontorial tympanic sinus and caudal tympanic process; in addition to plesiomorphic mammalian features, such as the cavum supracochleare and prootic canal. The inner ear of Henkelotherium shows a division between the utricle and saccule, a cochlear canal coiled through at least 270°, a distinctive primary bony lamina for the basilar membrane, and a secondary bony lamina. The development of the primary and secondary bony laminae in the cochlear canal is suggested here to be correlated with the concurrent coiling of the bony canal and membranous duct of the inner ear cochlea, apomorphies of the more inclusive cladotherian clade that also represent the ancestral morphotype of modern therian mammals. Because these features are crucial for high-frequency hearing in extant therian mammals, their early appearance in Late Jurassic cladotherians suggests a more ancient origination for high-frequency hearing in mammalian history than previously thought. PMID:19438763

A cascaded Schwarz converter for high frequency power distribution

NASA Technical Reports Server (NTRS)

Ray, Biswajit; Stuart, Thomas A.

1988-01-01

It is shown that two Schwarz converters in cascade provide a very reliable 20-kHz source that features zero current commutation, constant frequency, and fault-tolerant operation, meeting requirements for spacecraft applications. A steady-state analysis of the converter is presented, and equations for the steady-state performance are derived. Fault-current limiting is discussed. Experimental results are presented for a 900-W version, which has been successfully tested under no-load, full-load, and short-circut conditions.

Can the relativistic light-bending model explain X-ray spectral variations of Seyfert galaxies?

NASA Astrophysics Data System (ADS)

Mizumoto, Misaki; Moriyama, Kotaro; Ebisawa, Ken; Mineshige, Shin; Kawanaka, Norita; Tsujimoto, Masahiro

2018-04-01

Many Seyfert galaxies are known to exhibit Fe-K broad emission line features in their X-ray energy spectra. The observed lines have three distinct features: (1) the line profiles are skewed and show significant low-energy tails, (2) the Fe-K band has low variability, which produces a broad and deep dip in the root-mean-square (rms) spectra, and (3) photons in this band have time lags behind those in the adjacent energy bands with amplitudes of several Rg/c, where Rg is the gravitational radius. The "relativistic light-bending model" is proposed to explain these observed features, where a compact X-ray source ("lamp post") above an extreme Kerr black hole illuminates the innermost area of the accretion disc. In this paper, we critically examine the relativistic light-bending model by computing the rms spectra and the lag features using a ray-tracing technique, when a lamp post moves vertically on the black hole spin axis. As a result, we found that the observed deep rms dip requires that the iron is extremely overabundant (≳10 solar), whereas the observed lag amplitude is consistent with the normal iron abundance. Furthermore, disappearance of the lag in the high-flux state requires a source height as high as ˜40 Rg, which contradicts the relativistically broad emission line feature. Our simulations agree with the data that the reverberation feature moves to lower frequencies with larger source height; however, if this scenario is correct, the simulations predict the detection of a clear Fe-K lag at low frequencies, which is not constrained in the data. Therefore, we conclude that the relativistic light-bending model may not explain the characteristic Fe-K spectral variations in Seyfert galaxies.

Can the relativistic light-bending model explain X-ray spectral variations of Seyfert galaxies?

NASA Astrophysics Data System (ADS)

Mizumoto, Misaki; Moriyama, Kotaro; Ebisawa, Ken; Mineshige, Shin; Kawanaka, Norita; Tsujimoto, Masahiro

2018-06-01

Many Seyfert galaxies are known to exhibit Fe-K broad emission line features in their X-ray energy spectra. The observed lines have three distinct features: (1) the line profiles are skewed and show significant low-energy tails, (2) the Fe-K band has low variability, which produces a broad and deep dip in the root-mean-square (rms) spectra, and (3) photons in this band have time lags behind those in the adjacent energy bands with amplitudes of several Rg/c, where Rg is the gravitational radius. The "relativistic light-bending model" is proposed to explain these observed features, where a compact X-ray source ("lamp post") above an extreme Kerr black hole illuminates the innermost area of the accretion disc. In this paper, we critically examine the relativistic light-bending model by computing the rms spectra and the lag features using a ray-tracing technique, when a lamp post moves vertically on the black hole spin axis. As a result, we found that the observed deep rms dip requires that the iron is extremely overabundant (≳10 solar), whereas the observed lag amplitude is consistent with the normal iron abundance. Furthermore, disappearance of the lag in the high-flux state requires a source height as high as ˜40 Rg, which contradicts the relativistically broad emission line feature. Our simulations agree with the data that the reverberation feature moves to lower frequencies with larger source height; however, if this scenario is correct, the simulations predict the detection of a clear Fe-K lag at low frequencies, which is not constrained in the data. Therefore, we conclude that the relativistic light-bending model may not explain the characteristic Fe-K spectral variations in Seyfert galaxies.

Discriminating features of echolocation clicks of melon-headed whales (Peponocephala electra), bottlenose dolphins (Tursiops truncatus), and Gray's spinner dolphins (Stenella longirostris longirostris).

PubMed

Baumann-Pickering, Simone; Wiggins, Sean M; Hildebrand, John A; Roch, Marie A; Schnitzler, Hans-Ulrich

2010-10-01

Spectral parameters were used to discriminate between echolocation clicks produced by three dolphin species at Palmyra Atoll: melon-headed whales (Peponocephala electra), bottlenose dolphins (Tursiops truncatus) and Gray's spinner dolphins (Stenella longirostris longirostris). Single species acoustic behavior during daytime observations was recorded with a towed hydrophone array sampling at 192 and 480 kHz. Additionally, an autonomous, bottom moored High-frequency Acoustic Recording Package (HARP) collected acoustic data with a sampling rate of 200 kHz. Melon-headed whale echolocation clicks had the lowest peak and center frequencies, spinner dolphins had the highest frequencies and bottlenose dolphins were nested in between these two species. Frequency differences were significant. Temporal parameters were not well suited for classification. Feature differences were enhanced by reducing variability within a set of single clicks by calculating mean spectra for groups of clicks. Median peak frequencies of averaged clicks (group size 50) of melon-headed whales ranged between 24.4 and 29.7 kHz, of bottlenose dolphins between 26.7 and 36.7 kHz, and of spinner dolphins between 33.8 and 36.0 kHz. Discriminant function analysis showed the ability to correctly discriminate between 93% of melon-headed whales, 75% of spinner dolphins and 54% of bottlenose dolphins.

Decoding stimulus features in primate somatosensory cortex during perceptual categorization

PubMed Central

Alvarez, Manuel; Zainos, Antonio; Romo, Ranulfo

2015-01-01

Neurons of the primary somatosensory cortex (S1) respond as functions of frequency or amplitude of a vibrotactile stimulus. However, whether S1 neurons encode both frequency and amplitude of the vibrotactile stimulus or whether each sensory feature is encoded by separate populations of S1 neurons is not known, To further address these questions, we recorded S1 neurons while trained monkeys categorized only one sensory feature of the vibrotactile stimulus: frequency, amplitude, or duration. The results suggest a hierarchical encoding scheme in S1: from neurons that encode all sensory features of the vibrotactile stimulus to neurons that encode only one sensory feature. We hypothesize that the dynamic representation of each sensory feature in S1 might serve for further downstream processing that leads to the monkey’s psychophysical behavior observed in these tasks. PMID:25825711

Disproportionate emission of bubble streams with killer whale biphonic calls: perspectives on production and function.

PubMed

Bowles, Ann E; Grebner, Dawn M; Musser, Whitney B; Nash, Juliette S; Crance, Jessica L

2015-02-01

Stereotyped pulsed calls were attributed to 11 killer whales (Orcinus orca) with and without synchronous bubble streams in three datasets collected from two facilities from 1993 to 2012. Calls with and without synchronous bubble streams and divergent overlapping high frequency components ("biphonic" vs "monophonic") were compared. Subjects produced bubbles significantly more often when calls had divergent high frequency components. However, acoustic features in one biphonic call shared by five subjects provided little evidence for an acoustic effect of synchronous bubble flow. Disproportionate bubbling supported other evidence that biphonic calls form a distinct category, but suggested a function in short-range communication.

Three-dimensional propagation and absorption of high frequency Gaussian beams in magnetoactive plasmas

NASA Astrophysics Data System (ADS)

Nowak, S.; Orefice, A.

1994-05-01

In today's high frequency systems employed for plasma diagnostics, power heating, and current drive the behavior of the wave beams is appreciably affected by the self-diffraction phenomena due to their narrow collimation. In the present article the three-dimensional propagation of Gaussian beams in inhomogeneous and anisotropic media is analyzed, starting from a properly formulated dispersion relation. Particular attention is paid, in the case of electromagnetic electron cyclotron (EC) waves, to the toroidal geometry characterizing tokamak plasmas, to the power density evolution on the advancing wave fronts, and to the absorption features occurring when a beam crosses an EC resonant layer.

Improved parallel image reconstruction using feature refinement.

PubMed

Cheng, Jing; Jia, Sen; Ying, Leslie; Liu, Yuanyuan; Wang, Shanshan; Zhu, Yanjie; Li, Ye; Zou, Chao; Liu, Xin; Liang, Dong

2018-07-01

The aim of this study was to develop a novel feature refinement MR reconstruction method from highly undersampled multichannel acquisitions for improving the image quality and preserve more detail information. The feature refinement technique, which uses a feature descriptor to pick up useful features from residual image discarded by sparsity constrains, is applied to preserve the details of the image in compressed sensing and parallel imaging in MRI (CS-pMRI). The texture descriptor and structure descriptor recognizing different types of features are required for forming the feature descriptor. Feasibility of the feature refinement was validated using three different multicoil reconstruction methods on in vivo data. Experimental results show that reconstruction methods with feature refinement improve the quality of reconstructed image and restore the image details more accurately than the original methods, which is also verified by the lower values of the root mean square error and high frequency error norm. A simple and effective way to preserve more useful detailed information in CS-pMRI is proposed. This technique can effectively improve the reconstruction quality and has superior performance in terms of detail preservation compared with the original version without feature refinement. Magn Reson Med 80:211-223, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Multitasking: Effects of processing multiple auditory feature patterns

PubMed Central

Miller, Tova; Chen, Sufen; Lee, Wei Wei; Sussman, Elyse S.

2016-01-01

ERPs and behavioral responses were measured to assess how task-irrelevant sounds interact with task processing demands and affect the ability to monitor and track multiple sound events. Participants listened to four-tone sequential frequency patterns, and responded to frequency pattern deviants (reversals of the pattern). Irrelevant tone feature patterns (duration and intensity) and respective pattern deviants were presented together with frequency patterns and frequency pattern deviants in separate conditions. Responses to task-relevant and task-irrelevant feature pattern deviants were used to test processing demands for irrelevant sound input. Behavioral performance was significantly better when there were no distracting feature patterns. Errors primarily occurred in response to the to-be-ignored feature pattern deviants. Task-irrelevant elicitation of ERP components was consistent with the error analysis, indicating a level of processing for the irrelevant features. Task-relevant elicitation of ERP components was consistent with behavioral performance, demonstrating a “cost” of performance when there were two feature patterns presented simultaneously. These results provide evidence that the brain tracked the irrelevant duration and intensity feature patterns, affecting behavioral performance. Overall, our results demonstrate that irrelevant informational streams are processed at a cost, which may be considered a type of multitasking that is an ongoing, automatic processing of taskirrelevant sensory events. PMID:25939456

The medial pterygoid tubercle in the Atapuerca Early and Middle Pleistocene mandibles: evolutionary implications.

PubMed

Bermúdez de Castro, José-María; Quam, Rolf; Martinón-Torres, María; Martínez, Ignacio; Gracia-Téllez, Ana; Arsuaga, Juan Luís; Carbonell, Eudald

2015-01-01

Numerous studies have attempted to identify the presence of uniquely derived (autoapomorphic) Neandertal features. Here, we deal with the medial pterygoid tubercle (MTP), which is usually present on the internal face of the ascending ramus of Neandertal specimens. Our study stems from the identification of a hypertrophied tubercle in ATD6-96, an Early Pleistocene mandible recovered from the TD6 level of the Atapuerca-Gran Dolina site and attributed to Homo antecessor. Our review of the literature and study of numerous original fossil specimens and high quality replicas confirm that the MTP occurs at a high frequency in Neandertals (ca. 89%) and is also present in over half (ca. 55%) of the Middle Pleistocene Sima de los Huesos (SH) hominins. In contrast, it is generally absent or minimally developed in other extinct hominins, but can be found in variable frequencies (

Fault diagnosis for diesel valve trains based on time frequency images

NASA Astrophysics Data System (ADS)

Wang, Chengdong; Zhang, Youyun; Zhong, Zhenyuan

2008-11-01

In this paper, the Wigner-Ville distributions (WVD) of vibration acceleration signals which were acquired from the cylinder head in eight different states of valve train were calculated and displayed in grey images; and the probabilistic neural networks (PNN) were directly used to classify the time-frequency images after the images were normalized. By this way, the fault diagnosis of valve train was transferred to the classification of time-frequency images. As there is no need to extract further fault features (such as eigenvalues or symptom parameters) from time-frequency distributions before classification, the fault diagnosis process is highly simplified. The experimental results show that the faults of diesel valve trains can be classified accurately by the proposed methods.

Control system high-precision laser to obtain the ensemble of ultracold ions Th3+

NASA Astrophysics Data System (ADS)

Florentsev, V. V.; Zhdamirov, V. Yu; Rodko, I. I.; Borodulya, N. A.; Biryukov, A. P.

2018-01-01

One of key problems of nuclear standard frequency development is preparation assembly of ultracold thorium ions in Pauli trap. In this case semiconductive frequency-stabilized lasers with external resonator on frequencies 690 nm, 984 nm, and 1088 nm are used for excitation of corresponding electronic dipole and quadrupole cooling transitions for Th3+ ions. In the paper the results of development and creation of unified laser module, which is able to be used as base for full-featured system designed for laser cooling of Th3+ ions, are presented. The module is able to fine-tune necessary wavelength with accuracy ±5 nm.

Artificial neural networks for acoustic target recognition

NASA Astrophysics Data System (ADS)

Robertson, James A.; Mossing, John C.; Weber, Bruce A.

1995-04-01

Acoustic sensors can be used to detect, track and identify non-line-of-sight targets passively. Attempts to alter acoustic emissions often result in an undesirable performance degradation. This research project investigates the use of neural networks for differentiating between features extracted from the acoustic signatures of sources. Acoustic data were filtered and digitized using a commercially available analog-digital convertor. The digital data was transformed to the frequency domain for additional processing using the FFT. Narrowband peak detection algorithms were incorporated to select peaks above a user defined SNR. These peaks were then used to generate a set of robust features which relate specifically to target components in varying background conditions. The features were then used as input into a backpropagation neural network. A K-means unsupervised clustering algorithm was used to determine the natural clustering of the observations. Comparisons between a feature set consisting of the normalized amplitudes of the first 250 frequency bins of the power spectrum and a set of 11 harmonically related features were made. Initial results indicate that even though some different target types had a tendency to group in the same clusters, the neural network was able to differentiate the targets. Successful identification of acoustic sources under varying operational conditions with high confidence levels was achieved.

Modified DCTNet for audio signals classification

NASA Astrophysics Data System (ADS)

Xian, Yin; Pu, Yunchen; Gan, Zhe; Lu, Liang; Thompson, Andrew

2016-10-01

In this paper, we investigate DCTNet for audio signal classification. Its output feature is related to Cohen's class of time-frequency distributions. We introduce the use of adaptive DCTNet (A-DCTNet) for audio signals feature extraction. The A-DCTNet applies the idea of constant-Q transform, with its center frequencies of filterbanks geometrically spaced. The A-DCTNet is adaptive to different acoustic scales, and it can better capture low frequency acoustic information that is sensitive to human audio perception than features such as Mel-frequency spectral coefficients (MFSC). We use features extracted by the A-DCTNet as input for classifiers. Experimental results show that the A-DCTNet and Recurrent Neural Networks (RNN) achieve state-of-the-art performance in bird song classification rate, and improve artist identification accuracy in music data. They demonstrate A-DCTNet's applicability to signal processing problems.

Wavelet Based Characterization of Low Radio Frequency Solar Emissions

NASA Astrophysics Data System (ADS)

Suresh, A.; Sharma, R.; Das, S. B.; Oberoi, D.; Pankratius, V.; Lonsdale, C.

2016-12-01

Low-frequency solar radio observations with the Murchison Widefield Array (MWA) have revealed the presence of numerous short-lived, narrow-band weak radio features, even during quiet solar conditions. In their appearance in in the frequency-time plane, they come closest to the solar type III bursts, but with much shorter spectral spans and flux densities, so much so that they are not detectable with the usual swept frequency radio spectrographs. These features occur at rates of many thousand features per hour in the 30.72 MHz MWA bandwidth, and hence necessarily require an automated approach to determine robust statistical estimates of their properties, e.g., distributions of spectral widths, temporal spans, flux densities, slopes in the time-frequency plane and distribution over frequency. To achieve this, a wavelet decomposition approach has been developed for feature recognition and subsequent parameter extraction from the MWA dynamic spectrum. This work builds on earlier work by the members of this team to achieve a reliable flux calibration in a computationally efficient manner. Preliminary results show that the distribution of spectral span of these features peaks around 3 MHz, most of them last for less than two seconds and are characterized by flux densities of about 60% of the background solar emission. In analogy with the solar type III bursts, this non-thermal emission is envisaged to arise via coherent emission processes. There is also an exciting possibility that these features might correspond to radio signatures of nanoflares, hypothesized (Gold, 1964; Parker, 1972) to explain coronal heating.

Features of anti-inflammatory effects of modulated extremely high-frequency electromagnetic radiation.

PubMed

Gapeyev, Andrew B; Mikhailik, Elena N; Chemeris, Nikolay K

2009-09-01

Using a model of acute zymosan-induced paw edema in NMRI mice, we test the hypothesis that anti-inflammatory effects of extremely high-frequency electromagnetic radiation (EHF EMR) can be essentially modified by application of pulse modulation with certain frequencies. It has been revealed that a single exposure of animals to continuous EHF EMR for 20 min reduced the exudative edema of inflamed paw on average by 19% at intensities of 0.1-0.7 mW/cm(2) and frequencies from the range of 42.2-42.6 GHz. At fixed effective carrier frequency of 42.2 GHz, the anti-inflammatory effect of EHF EMR did not depend on modulation frequencies, that is, application of different modulation frequencies from the range of 0.03-100 Hz did not lead to considerable changes in the effect level. On the contrary, at "ineffective" carrier frequencies of 43.0 and 61.22 GHz, the use of modulation frequencies of 0.07-0.1 and 20-30 Hz has allowed us to restore the effect up to a maximal level. The results obtained show the critical dependence of anti-inflammatory action of low-intensity EHF EMR on carrier and modulation frequencies. Within the framework of this study, the possibility of changing the level of expected biological effect of modulated EMR by a special selection of combination of carrier and modulation frequencies is confirmed.

A Study on Regional Frequency Analysis using Artificial Neural Network - the Sumjin River Basin

NASA Astrophysics Data System (ADS)

Jeong, C.; Ahn, J.; Ahn, H.; Heo, J. H.

2017-12-01

Regional frequency analysis means to make up for shortcomings in the at-site frequency analysis which is about a lack of sample size through the regional concept. Regional rainfall quantile depends on the identification of hydrologically homogeneous regions, hence the regional classification based on hydrological homogeneous assumption is very important. For regional clustering about rainfall, multidimensional variables and factors related geographical features and meteorological figure are considered such as mean annual precipitation, number of days with precipitation in a year and average maximum daily precipitation in a month. Self-Organizing Feature Map method which is one of the artificial neural network algorithm in the unsupervised learning techniques solves N-dimensional and nonlinear problems and be shown results simply as a data visualization technique. In this study, for the Sumjin river basin in South Korea, cluster analysis was performed based on SOM method using high-dimensional geographical features and meteorological factor as input data. then, for the results, in order to evaluate the homogeneity of regions, the L-moment based discordancy and heterogeneity measures were used. Rainfall quantiles were estimated as the index flood method which is one of regional rainfall frequency analysis. Clustering analysis using SOM method and the consequential variation in rainfall quantile were analyzed. This research was supported by a grant(2017-MPSS31-001) from Supporting Technology Development Program for Disaster Management funded by Ministry of Public Safety and Security(MPSS) of the Korean government.

High frequency inductive lamp and power oscillator

DOEpatents

MacLennan, Donald A.; Turner, Brian P.; Dolan, James T.; Kirkpatrick, Douglas A.; Leng, Yongzhang

2000-01-01

A high frequency inductively coupled electrodeless lamp includes an excitation coil with an effective electrical length which is less than one half wavelength of a driving frequency applied thereto, preferably much less. The driving frequency may be greater than 100 MHz and is preferably as high as 915 MHz. Preferably, the excitation coil is configured as a non-helical, semi-cylindrical conductive surface having less than one turn, in the general shape of a wedding ring. At high frequencies, the current in the coil forms two loops which are spaced apart and parallel to each other. Configured appropriately, the coil approximates a Helmholtz configuration. The lamp preferably utilizes an bulb encased in a reflective ceramic cup with a pre-formed aperture defined therethrough. The ceramic cup may include structural features to aid in alignment and/or a flanged face to aid in thermal management. The lamp head is preferably an integrated lamp head comprising a metal matrix composite surrounding an insulating ceramic with the excitation integrally formed on the ceramic. A novel solid-state oscillator preferably provides RF power to the lamp. The oscillator is a single active element device capable of providing over 70 watts of power at over 70% efficiency. Various control circuits may be employed to match the driving frequency of the oscillator to a plurality of tuning states of the lamp.

Arrhythmia Mechanism and Scaling Effect on the Spectral Properties of Electroanatomical Maps With Manifold Harmonics.

PubMed

Sanroman-Junquera, Margarita; Mora-Jimenez, Inmaculada; Garcia-Alberola, Arcadio; Caamano, Antonio J; Trenor, Beatriz; Rojo-Alvarez, Jose L

2018-04-01

Spatial and temporal processing of intracardiac electrograms provides relevant information to support the arrhythmia ablation during electrophysiological studies. Current cardiac navigation systems (CNS) and electrocardiographic imaging (ECGI) build detailed 3-D electroanatomical maps (EAM), which represent the spatial anatomical distribution of bioelectrical features, such as activation time or voltage. We present a principled methodology for spectral analysis of both EAM geometry and bioelectrical feature in CNS or ECGI, including their spectral representation, cutoff frequency, or spatial sampling rate (SSR). Existing manifold harmonic techniques for spectral mesh analysis are adapted to account for a fourth dimension, corresponding to the EAM bioelectrical feature. Appropriate scaling is required to address different magnitudes and units. With our approach, simulated and real EAM showed strong SSR dependence on both the arrhythmia mechanism and the cardiac anatomical shape. For instance, high frequencies increased significantly the SSR because of the "early-meets-late" in flutter EAM, compared with the sinus rhythm. Besides, higher frequency components were obtained for the left atrium (more complex anatomy) than for the right atrium in sinus rhythm. The proposed manifold harmonics methodology opens the field toward new signal processing tools for principled EAM spatiofeature analysis in CNS and ECGI, and to an improved knowledge on arrhythmia mechanisms.

Physical activity classification using time-frequency signatures of motion artifacts in multi-channel electrical impedance plethysmographs.

PubMed

Khan, Hassan Aqeel; Gore, Amit; Ashe, Jeff; Chakrabartty, Shantanu

2017-07-01

Physical activities are known to introduce motion artifacts in electrical impedance plethysmographic (EIP) sensors. Existing literature considers motion artifacts as a nuisance and generally discards the artifact containing portion of the sensor output. This paper examines the notion of exploiting motion artifacts for detecting the underlying physical activities which give rise to the artifacts in question. In particular, we investigate whether the artifact pattern associated with a physical activity is unique; and does it vary from one human-subject to another? Data was recorded from 19 adult human-subjects while conducting 5 distinct, artifact inducing, activities. A set of novel features based on the time-frequency signatures of the sensor outputs are then constructed. Our analysis demonstrates that these features enable high accuracy detection of the underlying physical activity. Using an SVM classifier we are able to differentiate between 5 distinct physical activities (coughing, reaching, walking, eating and rolling-on-bed) with an average accuracy of 85.46%. Classification is performed solely using features designed specifically to capture the time-frequency signatures of different physical activities. This enables us to measure both respiratory and motion information using only one type of sensor. This is in contrast to conventional approaches to physical activity monitoring; which rely on additional hardware such as accelerometers to capture activity information.

Automated classification of mouse pup isolation syllables: from cluster analysis to an Excel-based "mouse pup syllable classification calculator".

PubMed

Grimsley, Jasmine M S; Gadziola, Marie A; Wenstrup, Jeffrey J

2012-01-01

Mouse pups vocalize at high rates when they are cold or isolated from the nest. The proportions of each syllable type produced carry information about disease state and are being used as behavioral markers for the internal state of animals. Manual classifications of these vocalizations identified 10 syllable types based on their spectro-temporal features. However, manual classification of mouse syllables is time consuming and vulnerable to experimenter bias. This study uses an automated cluster analysis to identify acoustically distinct syllable types produced by CBA/CaJ mouse pups, and then compares the results to prior manual classification methods. The cluster analysis identified two syllable types, based on their frequency bands, that have continuous frequency-time structure, and two syllable types featuring abrupt frequency transitions. Although cluster analysis computed fewer syllable types than manual classification, the clusters represented well the probability distributions of the acoustic features within syllables. These probability distributions indicate that some of the manually classified syllable types are not statistically distinct. The characteristics of the four classified clusters were used to generate a Microsoft Excel-based mouse syllable classifier that rapidly categorizes syllables, with over a 90% match, into the syllable types determined by cluster analysis.

Automated video-based assessment of surgical skills for training and evaluation in medical schools.

PubMed

Zia, Aneeq; Sharma, Yachna; Bettadapura, Vinay; Sarin, Eric L; Ploetz, Thomas; Clements, Mark A; Essa, Irfan

2016-09-01

Routine evaluation of basic surgical skills in medical schools requires considerable time and effort from supervising faculty. For each surgical trainee, a supervisor has to observe the trainees in person. Alternatively, supervisors may use training videos, which reduces some of the logistical overhead. All these approaches however are still incredibly time consuming and involve human bias. In this paper, we present an automated system for surgical skills assessment by analyzing video data of surgical activities. We compare different techniques for video-based surgical skill evaluation. We use techniques that capture the motion information at a coarser granularity using symbols or words, extract motion dynamics using textural patterns in a frame kernel matrix, and analyze fine-grained motion information using frequency analysis. We were successfully able to classify surgeons into different skill levels with high accuracy. Our results indicate that fine-grained analysis of motion dynamics via frequency analysis is most effective in capturing the skill relevant information in surgical videos. Our evaluations show that frequency features perform better than motion texture features, which in-turn perform better than symbol-/word-based features. Put succinctly, skill classification accuracy is positively correlated with motion granularity as demonstrated by our results on two challenging video datasets.

Effects of metric hierarchy and rhyme predictability on word duration in The Cat in the Hat.

PubMed

Breen, Mara

2018-05-01

Word durations convey many types of linguistic information, including intrinsic lexical features like length and frequency and contextual features like syntactic and semantic structure. The current study was designed to investigate whether hierarchical metric structure and rhyme predictability account for durational variation over and above other features in productions of a rhyming, metrically-regular children's book: The Cat in the Hat (Dr. Seuss, 1957). One-syllable word durations and inter-onset intervals were modeled as functions of segment number, lexical frequency, word class, syntactic structure, repetition, and font emphasis. Consistent with prior work, factors predicting longer word durations and inter-onset intervals included more phonemes, lower frequency, first mention, alignment with a syntactic boundary, and capitalization. A model parameter corresponding to metric grid height improved model fit of word durations and inter-onset intervals. Specifically, speakers realized five levels of metric hierarchy with inter-onset intervals such that interval duration increased linearly with increased height in the metric hierarchy. Conversely, speakers realized only three levels of metric hierarchy with word duration, demonstrating that they shortened the highly predictable rhyme resolutions. These results further understanding of the factors that affect spoken word duration, and demonstrate the myriad cues that children receive about linguistic structure from nursery rhymes. Copyright © 2018 Elsevier B.V. All rights reserved.

Non-stationary signal analysis based on general parameterized time-frequency transform and its application in the feature extraction of a rotary machine

NASA Astrophysics Data System (ADS)

Zhou, Peng; Peng, Zhike; Chen, Shiqian; Yang, Yang; Zhang, Wenming

2018-06-01

With the development of large rotary machines for faster and more integrated performance, the condition monitoring and fault diagnosis for them are becoming more challenging. Since the time-frequency (TF) pattern of the vibration signal from the rotary machine often contains condition information and fault feature, the methods based on TF analysis have been widely-used to solve these two problems in the industrial community. This article introduces an effective non-stationary signal analysis method based on the general parameterized time-frequency transform (GPTFT). The GPTFT is achieved by inserting a rotation operator and a shift operator in the short-time Fourier transform. This method can produce a high-concentrated TF pattern with a general kernel. A multi-component instantaneous frequency (IF) extraction method is proposed based on it. The estimation for the IF of every component is accomplished by defining a spectrum concentration index (SCI). Moreover, such an IF estimation process is iteratively operated until all the components are extracted. The tests on three simulation examples and a real vibration signal demonstrate the effectiveness and superiority of our method.

The dielectric properties of soil-water mixtures at microwave frequencies

NASA Technical Reports Server (NTRS)

Wang, J. R.

1979-01-01

Recent measurements on the dielectric constants of soil-water mixtures show the existence of two frequency regions in which the dielectric behavior of these mixtures was quite different. At the frequencies of 1.4 GHz to 5 GHz, there were strong evidences that the variations of the dielectric (epsilon) with water content (W) depended on soil type. While the real part of epsilon for sandy soils rose rapidly with the increase in W, epsilon for the high-clay content soils rose only slowly with W. As a consequence, epsilon was generally higher for the sandy soils than for the high-clay content soils at a given W. On the other hand, most of the measurements at frequencies 1 GHz indicated the increase of epsilon with W independent of soil types. At a given W, epsilon' (sandy soil) approximately equals epsilon (high-clay content soil) within the precision of the measurements. These observational features can be satisfactorily interpreted in terms of a simple dielectric relaxation model, with an appropriate choice of the mean relaxation frequency f(m) and the range of the activation energy (beta). It was found that smaller f(m) and larger beta were required for the high-clay content soils than the sandy soils in order to be consistent with the measured data.

Effects of Sound Frequency on Audiovisual Integration: An Event-Related Potential Study

PubMed Central

Yang, Weiping; Yang, Jingjing; Gao, Yulin; Tang, Xiaoyu; Ren, Yanna; Takahashi, Satoshi; Wu, Jinglong

2015-01-01

A combination of signals across modalities can facilitate sensory perception. The audiovisual facilitative effect strongly depends on the features of the stimulus. Here, we investigated how sound frequency, which is one of basic features of an auditory signal, modulates audiovisual integration. In this study, the task of the participant was to respond to a visual target stimulus by pressing a key while ignoring auditory stimuli, comprising of tones of different frequencies (0.5, 1, 2.5 and 5 kHz). A significant facilitation of reaction times was obtained following audiovisual stimulation, irrespective of whether the task-irrelevant sounds were low or high frequency. Using event-related potential (ERP), audiovisual integration was found over the occipital area for 0.5 kHz auditory stimuli from 190–210 ms, for 1 kHz stimuli from 170–200 ms, for 2.5 kHz stimuli from 140–200 ms, 5 kHz stimuli from 100–200 ms. These findings suggest that a higher frequency sound signal paired with visual stimuli might be early processed or integrated despite the auditory stimuli being task-irrelevant information. Furthermore, audiovisual integration in late latency (300–340 ms) ERPs with fronto-central topography was found for auditory stimuli of lower frequencies (0.5, 1 and 2.5 kHz). Our results confirmed that audiovisual integration is affected by the frequency of an auditory stimulus. Taken together, the neurophysiological results provide unique insight into how the brain processes a multisensory visual signal and auditory stimuli of different frequencies. PMID:26384256

Wavelet-based Characterization of Small-scale Solar Emission Features at Low Radio Frequencies

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

Suresh, A.; Sharma, R.; Oberoi, D.

Low radio frequency solar observations using the Murchison Widefield Array have recently revealed the presence of numerous weak short-lived narrowband emission features, even during moderately quiet solar conditions. These nonthermal features occur at rates of many thousands per hour in the 30.72 MHz observing bandwidth, and hence necessarily require an automated approach for their detection and characterization. Here, we employ continuous wavelet transform using a mother Ricker wavelet for feature detection from the dynamic spectrum. We establish the efficacy of this approach and present the first statistically robust characterization of the properties of these features. In particular, we examine distributionsmore » of their peak flux densities, spectral spans, temporal spans, and peak frequencies. We can reliably detect features weaker than 1 SFU, making them, to the best of our knowledge, the weakest bursts reported in literature. The distribution of their peak flux densities follows a power law with an index of −2.23 in the 12–155 SFU range, implying that they can provide an energetically significant contribution to coronal and chromospheric heating. These features typically last for 1–2 s and possess bandwidths of about 4–5 MHz. Their occurrence rate remains fairly flat in the 140–210 MHz frequency range. At the time resolution of the data, they appear as stationary bursts, exhibiting no perceptible frequency drift. These features also appear to ride on a broadband background continuum, hinting at the likelihood of them being weak type-I bursts.« less

Bearing performance degradation assessment based on time-frequency code features and SOM network

NASA Astrophysics Data System (ADS)

Zhang, Yan; Tang, Baoping; Han, Yan; Deng, Lei

2017-04-01

Bearing performance degradation assessment and prognostics are extremely important in supporting maintenance decision and guaranteeing the system’s reliability. To achieve this goal, this paper proposes a novel feature extraction method for the degradation assessment and prognostics of bearings. Features of time-frequency codes (TFCs) are extracted from the time-frequency distribution using a hybrid procedure based on short-time Fourier transform (STFT) and non-negative matrix factorization (NMF) theory. An alternative way to design the health indicator is investigated by quantifying the similarity between feature vectors using a self-organizing map (SOM) network. On the basis of this idea, a new health indicator called time-frequency code quantification error (TFCQE) is proposed to assess the performance degradation of the bearing. This indicator is constructed based on the bearing real-time behavior and the SOM model that is previously trained with only the TFC vectors under the normal condition. Vibration signals collected from the bearing run-to-failure tests are used to validate the developed method. The comparison results demonstrate the superiority of the proposed TFCQE indicator over many other traditional features in terms of feature quality metrics, incipient degradation identification and achieving accurate prediction. Highlights • Time-frequency codes are extracted to reflect the signals’ characteristics. • SOM network served as a tool to quantify the similarity between feature vectors. • A new health indicator is proposed to demonstrate the whole stage of degradation development. • The method is useful for extracting the degradation features and detecting the incipient degradation. • The superiority of the proposed method is verified using experimental data.

Micro-Doppler analysis of multiple frequency continuous wave radar signatures

NASA Astrophysics Data System (ADS)

Anderson, Michael G.; Rogers, Robert L.

2007-04-01

Micro-Doppler refers to Doppler scattering returns produced by non rigid-body motion. Micro-Doppler gives rise to many detailed radar image features in addition to those associated with bulk target motion. Targets of different classes (for example, humans, animals, and vehicles) produce micro-Doppler images that are often distinguishable even by nonexpert observers. Micro-Doppler features have great potential for use in automatic target classification algorithms. Although the potential benefit of using micro-Doppler in classification algorithms is high, relatively little experimental (non-synthetic) micro-Doppler data exists. Much of the existing experimental data comes from highly cooperative targets (human or vehicle targets directly approaching the radar). This research involved field data collection and analysis of micro-Doppler radar signatures from non-cooperative targets. The data was collected using a low cost Xband multiple frequency continuous wave (MFCW) radar with three transmit frequencies. The collected MFCW radar signatures contain data from humans, vehicles, and animals. The presented data includes micro-Doppler signatures previously unavailable in the literature such as crawling humans and various animal species. The animal micro-Doppler signatures include deer, dog, and goat datasets. This research focuses on the analysis of micro-Doppler from noncooperative targets approaching the radar at various angles, maneuvers, and postures.

Survey of Current Practice in the Fitting and Fine-Tuning of Common Signal-Processing Features in Hearing Aids for Adults.

PubMed

Anderson, Melinda C; Arehart, Kathryn H; Souza, Pamela E

2018-02-01

Current guidelines for adult hearing aid fittings recommend the use of a prescriptive fitting rationale with real-ear verification that considers the audiogram for the determination of frequency-specific gain and ratios for wide dynamic range compression. However, the guidelines lack recommendations for how other common signal-processing features (e.g., noise reduction, frequency lowering, directional microphones) should be considered during the provision of hearing aid fittings and fine-tunings for adult patients. The purpose of this survey was to identify how audiologists make clinical decisions regarding common signal-processing features for hearing aid provision in adults. An online survey was sent to audiologists across the United States. The 22 survey questions addressed four primary topics including demographics of the responding audiologists, factors affecting selection of hearing aid devices, the approaches used in the fitting of signal-processing features, and the strategies used in the fine-tuning of these features. A total of 251 audiologists who provide hearing aid fittings to adults completed the electronically distributed survey. The respondents worked in a variety of settings including private practice, physician offices, university clinics, and hospitals/medical centers. Data analysis was based on a qualitative analysis of the question responses. The survey results for each of the four topic areas (demographics, device selection, hearing aid fitting, and hearing aid fine-tuning) are summarized descriptively. Survey responses indicate that audiologists vary in the procedures they use in fitting and fine-tuning based on the specific feature, such that the approaches used for the fitting of frequency-specific gain differ from other types of features (i.e., compression time constants, frequency lowering parameters, noise reduction strength, directional microphones, feedback management). Audiologists commonly rely on prescriptive fitting formulas and probe microphone measures for the fitting of frequency-specific gain and rely on manufacturers' default settings and recommendations for both the initial fitting and the fine-tuning of signal-processing features other than frequency-specific gain. The survey results are consistent with a lack of published protocols and guidelines for fitting and adjusting signal-processing features beyond frequency-specific gain. To streamline current practice, a transparent evidence-based tool that enables clinicians to prescribe the setting of other features from individual patient characteristics would be desirable. American Academy of Audiology

Operation of the CAPRICE electron cyclotron resonance ion source applying frequency tuning and double frequency heating.

PubMed

Maimone, F; Tinschert, K; Celona, L; Lang, R; Mäder, J; Rossbach, J; Spädtke, P

2012-02-01

The properties of the electromagnetic waves heating the electrons of the ECR ion sources (ECRIS) plasma affect the features of the extracted ion beams such as the emittance, the shape, and the current, in particular for higher charge states. The electron heating methods such as the frequency tuning effect and the double frequency heating are widely used for enhancing the performances of ECRIS or even for the routine operation during the beam production. In order to better investigate these effects the CAPRICE ECRIS has been operated using these techniques. The ion beam properties for highly charged ions have been measured with beam diagnostic tools. The reason of the observed variations of this performance can be related to the different electromagnetic field patterns, which are changing inside the plasma chamber when the frequency is varying.

Investigating High Frequency Magnetic Activity During Local Helicity Injection on the Pegasus Toroidal Experiment

NASA Astrophysics Data System (ADS)

Richner, N. J.; Bongard, M. W.; Fonck, R. J.; Pachicano, J. L.; Perry, J. M.; Reusch, J. A.

2017-10-01

Understanding the current drive mechanism(s) of Local Helicity Injection (LHI) is needed for confident scaling to next-step devices. 3D resistive MHD NIMROD simulations ascribe large-scale reconnection events of helical injector current streams as a current drive mechanism. The events generate n = 1 B fluctuations on outboard Mirnov coils, consistent with experiment. New results suggest additional mechanisms are also active during LHI. Reconnection-driven ion heating is better correlated with high frequency activity than the n = 1 bursts. Experiments with inboard injectors can exhibit an abrupt ( 250 μs) transition to a reduced MHD state on outboard Mirnovs where the n = 1 feature vanishes, while still maintaining current growth and/or sustainment. A new insertable magnetics probe was developed to investigate these phenomena. It measures TeXBz up to 3.5 MHz at 15 points over a 14 cm radial extent (ΔR 1 cm). Measurements with this probe are consistent with the outboard Mirnovs when positioned far from the plasma boundary. However, measurements near the plasma edge lack the reduction in broadband power (up to 2 MHz) following the transition. The probe shows power is concentrated at higher frequencies during LHI, with mostly flat B spectra up to 600-800 kHz ( fci) at which there is a resonance-like feature; at higher frequencies, the power decreases. These measurements suggest short-wavelength activity may play a significant role in LHI current drive. Work supported by US DOE Grant DE-FG02-96ER54375.

[Comparative evaluation of the efficiency of the effect of very high frequency electromagnetic waves on platelet functional activity].

PubMed

Kirichuk, V F; Maĭborodin, A V; Volin, M V; Krenitskiĭ, A P; Tupikin, V D

2001-01-01

A comparative analysis was made of the effect of two kinds of EMI MMD-radiation: EMI MMD-waves, generated by a vehicle "Jav-1 M" (42.2 and 53.5 HHz), and EMI MMD-waves exerting influence with frequencies of molecular spectrum of radiation and nitric oxide absorption (150.176-150.644 HHz), obtained with a specially created generator, with respect to their influence on the functional ability of platelets of unstable angina pectoris patients. It was shown that in vitro EMI MMD-fluctuations with frequencies of molecular spectrum of radiation and nitric oxide absorption exert a stronger inhibiting influence on the functional activity of platelets of unstable angina pectoris patients. Features of the action of various kinds of EMI MMD-effect on the activative-high-speed characteristics of platelet aggregation are shown.

High speed micromachining with high power UV laser

NASA Astrophysics Data System (ADS)

Patel, Rajesh S.; Bovatsek, James M.

2013-03-01

Increasing demand for creating fine features with high accuracy in manufacturing of electronic mobile devices has fueled growth for lasers in manufacturing. High power, high repetition rate ultraviolet (UV) lasers provide an opportunity to implement a cost effective high quality, high throughput micromachining process in a 24/7 manufacturing environment. The energy available per pulse and the pulse repetition frequency (PRF) of diode pumped solid state (DPSS) nanosecond UV lasers have increased steadily over the years. Efficient use of the available energy from a laser is important to generate accurate fine features at a high speed with high quality. To achieve maximum material removal and minimal thermal damage for any laser micromachining application, use of the optimal process parameters including energy density or fluence (J/cm2), pulse width, and repetition rate is important. In this study we present a new high power, high PRF QuasarR 355-40 laser from Spectra-Physics with TimeShiftTM technology for unique software adjustable pulse width, pulse splitting, and pulse shaping capabilities. The benefits of these features for micromachining include improved throughput and quality. Specific example and results of silicon scribing are described to demonstrate the processing benefits of the Quasar's available power, PRF, and TimeShift technology.

Attention to Orthographic and Phonological Word Forms in Vocabulary Instruction for Kindergarten English Learners

ERIC Educational Resources Information Center

Vadasy, Patricia F.; Sanders, Elizabeth A.

2016-01-01

This study examined benefits of connecting meaning, speech, and print in vocabulary learning for kindergarten English learners. Students screened eligible with limited English proficiency were randomly assigned to two instruction conditions. Both groups received direct instruction in high frequency root words. One condition featured added…

Cross-Sensory Correspondences and Symbolism in Spoken and Written Language

ERIC Educational Resources Information Center

Walker, Peter

2016-01-01

Lexical sound symbolism in language appears to exploit the feature associations embedded in cross-sensory correspondences. For example, words incorporating relatively high acoustic frequencies (i.e., front/close rather than back/open vowels) are deemed more appropriate as names for concepts associated with brightness, lightness in weight,…

Bearing Fault Diagnosis Based on Statistical Locally Linear Embedding

PubMed Central

Wang, Xiang; Zheng, Yuan; Zhao, Zhenzhou; Wang, Jinping

2015-01-01

Fault diagnosis is essentially a kind of pattern recognition. The measured signal samples usually distribute on nonlinear low-dimensional manifolds embedded in the high-dimensional signal space, so how to implement feature extraction, dimensionality reduction and improve recognition performance is a crucial task. In this paper a novel machinery fault diagnosis approach based on a statistical locally linear embedding (S-LLE) algorithm which is an extension of LLE by exploiting the fault class label information is proposed. The fault diagnosis approach first extracts the intrinsic manifold features from the high-dimensional feature vectors which are obtained from vibration signals that feature extraction by time-domain, frequency-domain and empirical mode decomposition (EMD), and then translates the complex mode space into a salient low-dimensional feature space by the manifold learning algorithm S-LLE, which outperforms other feature reduction methods such as PCA, LDA and LLE. Finally in the feature reduction space pattern classification and fault diagnosis by classifier are carried out easily and rapidly. Rolling bearing fault signals are used to validate the proposed fault diagnosis approach. The results indicate that the proposed approach obviously improves the classification performance of fault pattern recognition and outperforms the other traditional approaches. PMID:26153771

High-frequency electroencephalographic activity in left temporal area is associated with pleasant emotion induced by video clips.

PubMed

Kortelainen, Jukka; Väyrynen, Eero; Seppänen, Tapio

2015-01-01

Recent findings suggest that specific neural correlates for the key elements of basic emotions do exist and can be identified by neuroimaging techniques. In this paper, electroencephalogram (EEG) is used to explore the markers for video-induced emotions. The problem is approached from a classifier perspective: the features that perform best in classifying person's valence and arousal while watching video clips with audiovisual emotional content are searched from a large feature set constructed from the EEG spectral powers of single channels as well as power differences between specific channel pairs. The feature selection is carried out using a sequential forward floating search method and is done separately for the classification of valence and arousal, both derived from the emotional keyword that the subject had chosen after seeing the clips. The proposed classifier-based approach reveals a clear association between the increased high-frequency (15-32 Hz) activity in the left temporal area and the clips described as "pleasant" in the valence and "medium arousal" in the arousal scale. These clips represent the emotional keywords amusement and joy/happiness. The finding suggests the occurrence of a specific neural activation during video-induced pleasant emotion and the possibility to detect this from the left temporal area using EEG.

Aeroacoustic Measurements of a Wing-Flap Configuration

NASA Technical Reports Server (NTRS)

Meadows, Kristine R.; Brooks, Thomas F.; Humphreys, William M.; Hunter, William H.; Gerhold, Carl H.

1997-01-01

Aeroacoustic measurements are being conducted to investigate the mechanisms of sound generation in high-lift wing configurations, and initial results are presented. The model is approximately 6 percent of a full scale configuration, and consists of a main element NACA 63(sub 2) - 215 wing section and a 30 percent chord half-span flap. Flow speeds up to Mach 0.17 are tested at Reynolds number up to approximately 1.7 million. Results are presented for a main element at a 16 degree angle of attack, and flap deflection angles of 29 and 39 degrees. The measurement systems developed for this test include two directional arrays used to localize and characterize the noise sources, and an array of unsteady surface pressure transducers used to characterize wave number spectra and correlate with acoustic measurements. Sound source localization maps show that locally dominant noise sources exist on the flap-side edge. The spectral distribution of the noise sources along the flap-side edge shows a decrease in frequency of the locally dominant noise source with increasing distance downstream of the flap leading edge. Spectra are presented which show general spectral characteristics of Strouhal dependent flow-surface interaction noise. However, the appearance of multiple broadband tonal features at high frequency indicates the presence of aeroacoustic phenomenon following different scaling characteristics. The scaling of the high frequency aeroacoustic phenomenon is found to be different for the two flap deflection angles tested. Unsteady surface pressure measurements in the vicinity of the flap edge show high coherence levels between adjacent sensors on the flap-side edge and on the flap edge upper surface in a region which corresponds closely to where the flap-side edge vortex begins to spill over to the flap upper surface. The frequency ranges where these high levels of coherence occur on the flap surface are consistent with the frequency ranges in which dominant features appear in far field acoustic spectra. The consistency of strongly correlated unsteady surface pressures and far field pressure fluctuations suggests the importance of regions on the flap edge in generating sound.

A hybrid method combining the surface integral equation method and ray tracing for the numerical simulation of high frequency diffraction involved in ultrasonic NDT

NASA Astrophysics Data System (ADS)

Bonnet, M.; Collino, F.; Demaldent, E.; Imperiale, A.; Pesudo, L.

2018-05-01

Ultrasonic Non-Destructive Testing (US NDT) has become widely used in various fields of applications to probe media. Exploiting the surface measurements of the ultrasonic incident waves echoes after their propagation through the medium, it allows to detect potential defects (cracks and inhomogeneities) and characterize the medium. The understanding and interpretation of those experimental measurements is performed with the help of numerical modeling and simulations. However, classical numerical methods can become computationally very expensive for the simulation of wave propagation in the high frequency regime. On the other hand, asymptotic techniques are better suited to model high frequency scattering over large distances but nevertheless do not allow accurate simulation of complex diffraction phenomena. Thus, neither numerical nor asymptotic methods can individually solve high frequency diffraction problems in large media, as those involved in UNDT controls, both quickly and accurately, but their advantages and limitations are complementary. Here we propose a hybrid strategy coupling the surface integral equation method and the ray tracing method to simulate high frequency diffraction under speed and accuracy constraints. This strategy is general and applicable to simulate diffraction phenomena in acoustic or elastodynamic media. We provide its implementation and investigate its performances for the 2D acoustic diffraction problem. The main features of this hybrid method are described and results of 2D computational experiments discussed.

Estimating cognitive workload using wavelet entropy-based features during an arithmetic task.

PubMed

Zarjam, Pega; Epps, Julien; Chen, Fang; Lovell, Nigel H

2013-12-01

Electroencephalography (EEG) has shown promise as an indicator of cognitive workload; however, precise workload estimation is an ongoing research challenge. In this investigation, seven levels of workload were induced using an arithmetic task, and the entropy of wavelet coefficients extracted from EEG signals is shown to distinguish all seven levels. For a subject-independent multi-channel classification scheme, the entropy features achieved high accuracy, up to 98% for channels from the frontal lobes, in the delta frequency band. This suggests that a smaller number of EEG channels in only one frequency band can be deployed for an effective EEG-based workload classification system. Together with analysis based on phase locking between channels, these results consistently suggest increased synchronization of neural responses for higher load levels. Copyright © 2013 Elsevier Ltd. All rights reserved.

Wafer-scalable high-performance CVD graphene devices and analog circuits

NASA Astrophysics Data System (ADS)

Tao, Li; Lee, Jongho; Li, Huifeng; Piner, Richard; Ruoff, Rodney; Akinwande, Deji

2013-03-01

Graphene field effect transistors (GFETs) will serve as an essential component for functional modules like amplifier and frequency doublers in analog circuits. The performance of these modules is directly related to the mobility of charge carriers in GFETs, which per this study has been greatly improved. Low-field electrostatic measurements show field mobility values up to 12k cm2/Vs at ambient conditions with our newly developed scalable CVD graphene. For both hole and electron transport, fabricated GFETs offer substantial amplification for small and large signals at quasi-static frequencies limited only by external capacitances at high-frequencies. GFETs biased at the peak transconductance point featured high small-signal gain with eventual output power compression similar to conventional transistor amplifiers. GFETs operating around the Dirac voltage afforded positive conversion gain for the first time, to our knowledge, in experimental graphene frequency doublers. This work suggests a realistic prospect for high performance linear and non-linear analog circuits based on the unique electron-hole symmetry and fast transport now accessible in wafer-scalable CVD graphene. *Support from NSF CAREER award (ECCS-1150034) and the W. M. Keck Foundation are appreicated.

The technique of entropy optimization in motor current signature analysis and its application in the fault diagnosis of gear transmission

NASA Astrophysics Data System (ADS)

Chen, Xiaoguang; Liang, Lin; Liu, Fei; Xu, Guanghua; Luo, Ailing; Zhang, Sicong

2012-05-01

Nowadays, Motor Current Signature Analysis (MCSA) is widely used in the fault diagnosis and condition monitoring of machine tools. However, although the current signal has lower SNR (Signal Noise Ratio), it is difficult to identify the feature frequencies of machine tools from complex current spectrum that the feature frequencies are often dense and overlapping by traditional signal processing method such as FFT transformation. With the study in the Motor Current Signature Analysis (MCSA), it is found that the entropy is of importance for frequency identification, which is associated with the probability distribution of any random variable. Therefore, it plays an important role in the signal processing. In order to solve the problem that the feature frequencies are difficult to be identified, an entropy optimization technique based on motor current signal is presented in this paper for extracting the typical feature frequencies of machine tools which can effectively suppress the disturbances. Some simulated current signals were made by MATLAB, and a current signal was obtained from a complex gearbox of an iron works made in Luxembourg. In diagnosis the MCSA is combined with entropy optimization. Both simulated and experimental results show that this technique is efficient, accurate and reliable enough to extract the feature frequencies of current signal, which provides a new strategy for the fault diagnosis and the condition monitoring of machine tools.

Systemic connective tissue features in women with fibromuscular dysplasia.

PubMed

O'Connor, Sarah; Kim, Esther Sh; Brinza, Ellen; Moran, Rocio; Fendrikova-Mahlay, Natalia; Wolski, Kathy; Gornik, Heather L

2015-10-01

Fibromuscular dysplasia (FMD) is a non-atherosclerotic disease associated with hypertension, headache, dissection, stroke, and aneurysm. The etiology is unknown but hypothesized to involve genetic and environmental components. Previous studies suggest a possible overlap of FMD with other connective tissue diseases that present with dissections and aneurysms. The aim of this study was to investigate the prevalence of connective tissue physical features in FMD. A total of 142 FMD patients were consecutively enrolled at a single referral center (97.9% female, 92.1% of whom had multifocal FMD). Data are reported for 139 female patients. Moderately severe myopia (29.1%), high palate (33.1%), dental crowding (29.7%), and early-onset arthritis (15.6%) were prevalent features. Classic connective features such as hypertelorism, cleft palate, and hypermobility were uncommon. The frequency of systemic connective tissue features was compared between FMD patients with a high vascular risk profile (having had ⩾1 dissection and/or ⩾2 aneurysms) and those with a standard vascular risk profile. A history of spontaneous pneumothorax (5.9% high risk vs 0% standard risk) and atrophic scarring (17.6% high risk vs 6.8% standard risk) were significantly more prevalent in the high risk group, p<0.05. High palate was observed in 43.1% of the high risk group versus 27.3% in the standard risk group, p=0.055. In conclusion, in a cohort of women with FMD, there was a prevalence of moderately severe myopia, high palate, dental crowding, and early-onset osteoarthritis. However, a characteristic phenotype was not discovered. Several connective tissue features such as high palate and pneumothorax were more prominent among FMD patients with a high vascular risk profile. © The Author(s) 2015.

Systemic Connective Tissue Features in Women with Fibromuscular Dysplasia

PubMed Central

O’Connor, Sarah; Kim, Esther S. H.; Brinza, Ellen; Moran, Rocio; Fendrikova-Mahlay, Natalia; Wolski, Kathy; Gornik, Heather L.

2016-01-01

Background Fibromuscular Dysplasia (FMD) is an non-atherosclerotic disease associated with hypertension, headache, dissection, stroke, and aneurysm. The etiology is unknown but hypothesized to involve genetic and environmental components. Previous studies suggest a possible overlap of FMD with other connective tissue diseases that present with dissections and aneurysms. The aim of this study was to investigate the prevalence of connective tissue physical features in FMD. Methods and Results 142 FMD patients were consecutively enrolled at a single referral center (97.9% female, 92.3% had multifocal FMD). Data are reported for 139 female patients. Moderately severe myopia (29.1%), high palate (33.1%), dental crowding (29.7%), and early onset arthritis (15.6%) were prevalent features. Classic connective features such as hypertelorism, cleft palate, and hypermobility were uncommon. Frequency of systemic connective tissue features was compared between FMD patients with a high vascular risk profile (having had ≥1 dissection and/or ≥2 aneurysms) and those with a standard vascular risk profile. History of spontaneous pneumothorax (5.9% high risk vs. 0% standard risk) and atrophic scarring (17.3% high risk vs. 6.8% standard risk) were significantly more prevalent in the high risk group, p<0.05. High palate was observed in 43.1% of the high risk group vs. 27.3% in the standard risk group, p=0.055. Conclusions In a cohort of women with FMD, there was a prevalence of moderately severe myopia, high palate, dental crowding, and early onset osteoarthritis. However, a characteristic phenotype was not discovered. Several connective tissue features such as high palate and pneumothorax were more prominent among FMD patients with a high vascular risk profile. PMID:26156071

[An improved medical image fusion algorithm and quality evaluation].

PubMed

Chen, Meiling; Tao, Ling; Qian, Zhiyu

2009-08-01

Medical image fusion is of very important value for application in medical image analysis and diagnosis. In this paper, the conventional method of wavelet fusion is improved,so a new algorithm of medical image fusion is presented and the high frequency and low frequency coefficients are studied respectively. When high frequency coefficients are chosen, the regional edge intensities of each sub-image are calculated to realize adaptive fusion. The choice of low frequency coefficient is based on the edges of images, so that the fused image preserves all useful information and appears more distinctly. We apply the conventional and the improved fusion algorithms based on wavelet transform to fuse two images of human body and also evaluate the fusion results through a quality evaluation method. Experimental results show that this algorithm can effectively retain the details of information on original images and enhance their edge and texture features. This new algorithm is better than the conventional fusion algorithm based on wavelet transform.

Mid-infrared optical frequency combs at 2.5 μm based on crystalline microresonators

PubMed Central

Wang, C. Y.; Herr, T.; Del’Haye, P.; Schliesser, A.; Hofer, J.; Holzwarth, R.; Hänsch, T. W.; Picqué, N.; Kippenberg, T. J.

2013-01-01

The mid-infrared spectral range (λ~2–20 μm) is of particular importance as many molecules exhibit strong vibrational fingerprints in this region. Optical frequency combs—broadband optical sources consisting of equally spaced and mutually coherent sharp lines—are creating new opportunities for advanced spectroscopy. Here we demonstrate a novel approach to create mid-infrared optical frequency combs via four-wave mixing in a continuous-wave pumped ultra-high Q crystalline microresonator made of magnesium fluoride. Careful choice of the resonator material and design made it possible to generate a broadband, low-phase noise Kerr comb at λ=2.5 μm spanning 200 nm (≈10 THz) with a line spacing of 100 GHz. With its distinguishing features of compactness, efficient conversion, large mode spacing and high power per comb line, this novel frequency comb source holds promise for new approaches to molecular spectroscopy and is suitable to be extended further into the mid-infrared. PMID:23299895

Learning high-level features for chord recognition using Autoencoder

NASA Astrophysics Data System (ADS)

Phongthongloa, Vilailukkana; Kamonsantiroj, Suwatchai; Pipanmaekaporn, Luepol

2016-07-01

Chord transcription is valuable to do by itself. It is known that the manual transcription of chords is very tiresome, time-consuming. It requires, moreover, musical knowledge. Automatic chord recognition has recently attracted a number of researches in the Music Information Retrieval field. It has known that a pitch class profile (PCP) is the commonly signal representation of musical harmonic analysis. However, the PCP may contain additional non-harmonic noise such as harmonic overtones and transient noise. The problem of non-harmonic might be generating the sound energy in term of frequency more than the actual notes of the respective chord. Autoencoder neural network may be trained to learn a mapping from low level feature to one or more higher-level representation. These high-level representations can explain dependencies of the inputs and reduce the effect of non-harmonic noise. Then these improve features are fed into neural network classifier. The proposed high-level musical features show 80.90% of accuracy. The experimental results have shown that the proposed approach can achieve better performance in comparison with other based method.

Discriminating Induced-Microearthquakes Using New Seismic Features

NASA Astrophysics Data System (ADS)

Mousavi, S. M.; Horton, S.

2016-12-01

We studied characteristics of induced-microearthquakes on the basis of the waveforms recorded on a limited number of surface receivers using machine-learning techniques. Forty features in the time, frequency, and time-frequency domains were measured on each waveform, and several techniques such as correlation-based feature selection, Artificial Neural Networks (ANNs), Logistic Regression (LR) and X-mean were used as research tools to explore the relationship between these seismic features and source parameters. The results show that spectral features have the highest correlation to source depth. Two new measurements developed as seismic features for this study, spectral centroids and 2D cross-correlations in the time-frequency domain, performed better than the common seismic measurements. These features can be used by machine learning techniques for efficient automatic classification of low energy signals recorded at one or more seismic stations. We applied the technique to 440 microearthquakes-1.7Reference: Mousavi, S.M., S.P. Horton, C. A. Langston, B. Samei, (2016) Seismic features and automatic discrimination of deep and shallow induced-microearthquakes using neural network and logistic regression, Geophys. J. Int. doi: 10.1093/gji/ggw258.

A fast, robust algorithm for power line interference cancellation in neural recording.

PubMed

Keshtkaran, Mohammad Reza; Yang, Zhi

2014-04-01

Power line interference may severely corrupt neural recordings at 50/60 Hz and harmonic frequencies. The interference is usually non-stationary and can vary in frequency, amplitude and phase. To retrieve the gamma-band oscillations at the contaminated frequencies, it is desired to remove the interference without compromising the actual neural signals at the interference frequency bands. In this paper, we present a robust and computationally efficient algorithm for removing power line interference from neural recordings. The algorithm includes four steps. First, an adaptive notch filter is used to estimate the fundamental frequency of the interference. Subsequently, based on the estimated frequency, harmonics are generated by using discrete-time oscillators, and then the amplitude and phase of each harmonic are estimated by using a modified recursive least squares algorithm. Finally, the estimated interference is subtracted from the recorded data. The algorithm does not require any reference signal, and can track the frequency, phase and amplitude of each harmonic. When benchmarked with other popular approaches, our algorithm performs better in terms of noise immunity, convergence speed and output signal-to-noise ratio (SNR). While minimally affecting the signal bands of interest, the algorithm consistently yields fast convergence (<100 ms) and substantial interference rejection (output SNR >30 dB) in different conditions of interference strengths (input SNR from -30 to 30 dB), power line frequencies (45-65 Hz) and phase and amplitude drifts. In addition, the algorithm features a straightforward parameter adjustment since the parameters are independent of the input SNR, input signal power and the sampling rate. A hardware prototype was fabricated in a 65 nm CMOS process and tested. Software implementation of the algorithm has been made available for open access at https://github.com/mrezak/removePLI. The proposed algorithm features a highly robust operation, fast adaptation to interference variations, significant SNR improvement, low computational complexity and memory requirement and straightforward parameter adjustment. These features render the algorithm suitable for wearable and implantable sensor applications, where reliable and real-time cancellation of the interference is desired.

A fast, robust algorithm for power line interference cancellation in neural recording

NASA Astrophysics Data System (ADS)

Keshtkaran, Mohammad Reza; Yang, Zhi

2014-04-01

Objective. Power line interference may severely corrupt neural recordings at 50/60 Hz and harmonic frequencies. The interference is usually non-stationary and can vary in frequency, amplitude and phase. To retrieve the gamma-band oscillations at the contaminated frequencies, it is desired to remove the interference without compromising the actual neural signals at the interference frequency bands. In this paper, we present a robust and computationally efficient algorithm for removing power line interference from neural recordings. Approach. The algorithm includes four steps. First, an adaptive notch filter is used to estimate the fundamental frequency of the interference. Subsequently, based on the estimated frequency, harmonics are generated by using discrete-time oscillators, and then the amplitude and phase of each harmonic are estimated by using a modified recursive least squares algorithm. Finally, the estimated interference is subtracted from the recorded data. Main results. The algorithm does not require any reference signal, and can track the frequency, phase and amplitude of each harmonic. When benchmarked with other popular approaches, our algorithm performs better in terms of noise immunity, convergence speed and output signal-to-noise ratio (SNR). While minimally affecting the signal bands of interest, the algorithm consistently yields fast convergence (<100 ms) and substantial interference rejection (output SNR >30 dB) in different conditions of interference strengths (input SNR from -30 to 30 dB), power line frequencies (45-65 Hz) and phase and amplitude drifts. In addition, the algorithm features a straightforward parameter adjustment since the parameters are independent of the input SNR, input signal power and the sampling rate. A hardware prototype was fabricated in a 65 nm CMOS process and tested. Software implementation of the algorithm has been made available for open access at https://github.com/mrezak/removePLI. Significance. The proposed algorithm features a highly robust operation, fast adaptation to interference variations, significant SNR improvement, low computational complexity and memory requirement and straightforward parameter adjustment. These features render the algorithm suitable for wearable and implantable sensor applications, where reliable and real-time cancellation of the interference is desired.

The effect of time-variant acoustical properties on orchestral instrument timbres

NASA Astrophysics Data System (ADS)

Hajda, John Michael

1999-06-01

The goal of this study was to investigate the timbre of orchestral instrument tones. Kendall (1986) showed that time-variant features are important to instrument categorization. But the relative salience of specific time-variant features to each other and to other acoustical parameters is not known. As part of a convergence strategy, a battery of experiments was conducted to assess the importance of global amplitude envelope, spectral frequencies, and spectral amplitudes. An omnibus identification experiment investigated the salience of global envelope partitions (attack, steady state, and decay). Valid partitioning models should identify important boundary conditions in the evolution of a signal; therefore, these models should be based on signal characteristics. With the use of such a model for sustained continuant tones, the steady-state segment was more salient than the attack. These findings contradicted previous research, which used questionable operational definitions for signal partitioning. For the next set of experiments, instrument tones were analyzed by phase vocoder, and stimuli were created by additive synthesis. Edits and combinations of edits controlled global amplitude envelope, spectral frequencies, and relative spectral amplitudes. Perceptual measurements were made with distance estimation, Verbal Attribute Magnitude Estimation, and similarity scaling. Results indicated that the primary acoustical attribute was the long-time-average spectral centroid. Spectral centroid is a measure of the center of energy distribution for spectral frequency components. Instruments with high values of spectral centroid (bowed strings) sound nasal while instruments with low spectral centroid (flute, clarinet) sound not nasal. The secondary acoustical attribute was spectral amplitude time variance. Predictably, time variance correlated highly with subject ratings of vibrato. The control of relative spectral amplitudes was more salient than the control of global envelope and spectral frequencies. Both amplitude phase relationships and time- variant spectral centroid were affected by the control of relative spectral amplitudes. Further experimentation is required to determine the salience of these features. The finding that instrumental vibrato is a manifestation of spectral amplitude time variance contradicts the common belief that vibrato is due to frequency (pitch) and intensity (loudness) modulation. This study suggests that vibrato is due to a periodic modulation in timbre. Future research should employ musical contexts.

Mechanical design and fabrication of the VHF-gun, the Berkeley normal-conducting continuous-wave high-brightness electron source

NASA Astrophysics Data System (ADS)

Wells, R. P.; Ghiorso, W.; Staples, J.; Huang, T. M.; Sannibale, F.; Kramasz, T. D.

2016-02-01

A high repetition rate, MHz-class, high-brightness electron source is a key element in future high-repetition-rate x-ray free electron laser-based light sources. The VHF-gun, a novel low frequency radio-frequency gun, is the Lawrence Berkeley National Laboratory (LBNL) response to that need. The gun design is based on a normal conducting, single cell cavity resonating at 186 MHz in the VHF band and capable of continuous wave operation while still delivering the high accelerating fields at the cathode required for the high brightness performance. The VHF-gun was fabricated and successfully commissioned in the framework of the Advanced Photo-injector EXperiment, an injector built at LBNL to demonstrate the capability of the gun to deliver the required beam quality. The basis for the selection of the VHF-gun technology, novel design features, and fabrication techniques are described.

Mechanical design and fabrication of the VHF-gun, the Berkeley normal-conducting continuous-wave high-brightness electron source.

PubMed

Wells, R P; Ghiorso, W; Staples, J; Huang, T M; Sannibale, F; Kramasz, T D

2016-02-01

A high repetition rate, MHz-class, high-brightness electron source is a key element in future high-repetition-rate x-ray free electron laser-based light sources. The VHF-gun, a novel low frequency radio-frequency gun, is the Lawrence Berkeley National Laboratory (LBNL) response to that need. The gun design is based on a normal conducting, single cell cavity resonating at 186 MHz in the VHF band and capable of continuous wave operation while still delivering the high accelerating fields at the cathode required for the high brightness performance. The VHF-gun was fabricated and successfully commissioned in the framework of the Advanced Photo-injector EXperiment, an injector built at LBNL to demonstrate the capability of the gun to deliver the required beam quality. The basis for the selection of the VHF-gun technology, novel design features, and fabrication techniques are described.

On the upper part load vortex rope in Francis turbine: Experimental investigation

NASA Astrophysics Data System (ADS)

Nicolet, C.; Zobeiri, A.; Maruzewski, P.; Avellan, F.

2010-08-01

The swirling flow developing in Francis turbine draft tube under part load operation leads to pressure fluctuations usually in the range of 0.2 to 0.4 times the runner rotational frequency resulting from the so-called vortex breakdown. For low cavitation number, the flow features a cavitation vortex rope animated with precession motion. Under given conditions, these pressure fluctuations may lead to undesirable pressure fluctuations in the entire hydraulic system and also produce active power oscillations. For the upper part load range, between 0.7 and 0.85 times the best efficiency discharge, pressure fluctuations may appear in a higher frequency range of 2 to 4 times the runner rotational speed and feature modulations with vortex rope precession. It has been pointed out that for this particular operating point, the vortex rope features elliptical cross section and is animated of a self-rotation. This paper presents an experimental investigation focusing on this peculiar phenomenon, defined as the upper part load vortex rope. The experimental investigation is carried out on a high specific speed Francis turbine scale model installed on a test rig of the EPFL Laboratory for Hydraulic Machines. The selected operating point corresponds to a discharge of 0.83 times the best efficiency discharge. Observations of the cavitation vortex carried out with high speed camera have been recorded and synchronized with pressure fluctuations measurements at the draft tube cone. First, the vortex rope self rotation frequency is evidenced and the related frequency is deduced. Then, the influence of the sigma cavitation number on vortex rope shape and pressure fluctuations is presented. The waterfall diagram of the pressure fluctuations evidences resonance effects with the hydraulic circuit. The time evolution of the vortex rope volume is compared with pressure fluctuations time evolution using image processing. Finally, the influence of the Froude number on the vortex rope shape and the associated pressure fluctuations is analyzed by varying the rotational speed.

Non-stationary discharge patterns in motor cortex under subthalamic nucleus deep brain stimulation.

PubMed

Santaniello, Sabato; Montgomery, Erwin B; Gale, John T; Sarma, Sridevi V

2012-01-01

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) directly modulates the basal ganglia (BG), but how such stimulation impacts the cortex upstream is largely unknown. There is evidence of cortical activation in 6-hydroxydopamine (OHDA)-lesioned rodents and facilitation of motor evoked potentials in Parkinson's disease (PD) patients, but the impact of the DBS settings on the cortical activity in normal vs. Parkinsonian conditions is still debated. We use point process models to analyze non-stationary activation patterns and inter-neuronal dependencies in the motor and sensory cortices of two non-human primates during STN DBS. These features are enhanced after treatment with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), which causes a consistent PD-like motor impairment, while high-frequency (HF) DBS (i.e., ≥100 Hz) strongly reduces the short-term patterns (period: 3-7 ms) both before and after MPTP treatment, and elicits a short-latency post-stimulus activation. Low-frequency DBS (i.e., ≤50 Hz), instead, has negligible effects on the non-stationary features. Finally, by using tools from the information theory [i.e., receiver operating characteristic (ROC) curve and information rate (IR)], we show that the predictive power of these models is dependent on the DBS settings, i.e., the probability of spiking of the cortical neurons (which is captured by the point process models) is significantly conditioned on the timely delivery of the DBS input. This dependency increases with the DBS frequency and is significantly larger for high- vs. low-frequency DBS. Overall, the selective suppression of non-stationary features and the increased modulation of the spike probability suggest that HF STN DBS enhances the neuronal activation in motor and sensory cortices, presumably because of reinforcement mechanisms, which perhaps involve the overlap between feedback antidromic and feed-forward orthodromic responses along the BG-thalamo-cortical loop.

Accurate step-FMCW ultrasound ranging and comparison with pulse-echo signaling methods

NASA Astrophysics Data System (ADS)

Natarajan, Shyam; Singh, Rahul S.; Lee, Michael; Cox, Brian P.; Culjat, Martin O.; Grundfest, Warren S.; Lee, Hua

2010-03-01

This paper presents a method setup for high-frequency ultrasound ranging based on stepped frequency-modulated continuous waves (FMCW), potentially capable of producing a higher signal-to-noise ratio (SNR) compared to traditional pulse-echo signaling. In current ultrasound systems, the use of higher frequencies (10-20 MHz) to enhance resolution lowers signal quality due to frequency-dependent attenuation. The proposed ultrasound signaling format, step-FMCW, is well-known in the radar community, and features lower peak power, wider dynamic range, lower noise figure and simpler electronics in comparison to pulse-echo systems. In pulse-echo ultrasound ranging, distances are calculated using the transmit times between a pulse and its subsequent echoes. In step-FMCW ultrasonic ranging, the phase and magnitude differences at stepped frequencies are used to sample the frequency domain. Thus, by taking the inverse Fourier transform, a comprehensive range profile is recovered that has increased immunity to noise over conventional ranging methods. Step-FMCW and pulse-echo waveforms were created using custom-built hardware consisting of an arbitrary waveform generator and dual-channel super heterodyne receiver, providing high SNR and in turn, accuracy in detection.

The nature of pulsar radio emission

NASA Astrophysics Data System (ADS)

Dyks, J.; Rudak, B.; Demorest, P.

2010-01-01

High-quality averaged radio profiles of some pulsars exhibit double, highly symmetric features both in emission and in absorption. It is shown that both types of feature are produced by a split fan beam of extraordinary-mode curvature radiation that is emitted/absorbed by radially extended streams of magnetospheric plasma. With no emissivity in the plane of the stream, such a beam produces bifurcated emission components (BFCs) when our line of sight passes through the plane. An example of a double component created in this way is present in the averaged profile of the 5-ms pulsar J1012+5307. We show that the component can indeed be very well fitted by the textbook formula for the non-coherent beam of curvature radiation in the polarization state that is orthogonal to the plane of electron trajectory. The observed width of the BFC decreases with increasing frequency at a rate that confirms the curvature origin. Likewise, the double absorption features (double notches) are produced by the same beam of the extraordinary-mode curvature radiation, when it is eclipsed by thin plasma streams. The intrinsic property of curvature radiation to create bifurcated fan beams explains the double features in terms of a very natural geometry and implies the curvature origin of pulsar radio emission. Similarly, the `double conal' profiles of class D result from a cut through a wider stream with finite extent in magnetic azimuth. Therefore, their width reacts very slowly to changes of viewing geometry resulting from geodetic precession. The stream-cut interpretation implies a highly non-orthodox origin of both the famous S-swing of polarization angle and the low-frequency pulse broadening in D profiles. The azimuthal structure of polarization modes in the curvature radiation beam provides an explanation for the polarized `multiple imaging' and the edge depolarization of pulsar profiles.

A Novel Characteristic Frequency Bands Extraction Method for Automatic Bearing Fault Diagnosis Based on Hilbert Huang Transform

PubMed Central

Yu, Xiao; Ding, Enjie; Chen, Chunxu; Liu, Xiaoming; Li, Li

2015-01-01

Because roller element bearings (REBs) failures cause unexpected machinery breakdowns, their fault diagnosis has attracted considerable research attention. Established fault feature extraction methods focus on statistical characteristics of the vibration signal, which is an approach that loses sight of the continuous waveform features. Considering this weakness, this article proposes a novel feature extraction method for frequency bands, named Window Marginal Spectrum Clustering (WMSC) to select salient features from the marginal spectrum of vibration signals by Hilbert–Huang Transform (HHT). In WMSC, a sliding window is used to divide an entire HHT marginal spectrum (HMS) into window spectrums, following which Rand Index (RI) criterion of clustering method is used to evaluate each window. The windows returning higher RI values are selected to construct characteristic frequency bands (CFBs). Next, a hybrid REBs fault diagnosis is constructed, termed by its elements, HHT-WMSC-SVM (support vector machines). The effectiveness of HHT-WMSC-SVM is validated by running series of experiments on REBs defect datasets from the Bearing Data Center of Case Western Reserve University (CWRU). The said test results evidence three major advantages of the novel method. First, the fault classification accuracy of the HHT-WMSC-SVM model is higher than that of HHT-SVM and ST-SVM, which is a method that combines statistical characteristics with SVM. Second, with Gauss white noise added to the original REBs defect dataset, the HHT-WMSC-SVM model maintains high classification accuracy, while the classification accuracy of ST-SVM and HHT-SVM models are significantly reduced. Third, fault classification accuracy by HHT-WMSC-SVM can exceed 95% under a Pmin range of 500–800 and a m range of 50–300 for REBs defect dataset, adding Gauss white noise at Signal Noise Ratio (SNR) = 5. Experimental results indicate that the proposed WMSC method yields a high REBs fault classification accuracy and a good performance in Gauss white noise reduction. PMID:26540059

A Novel Characteristic Frequency Bands Extraction Method for Automatic Bearing Fault Diagnosis Based on Hilbert Huang Transform.

PubMed

Yu, Xiao; Ding, Enjie; Chen, Chunxu; Liu, Xiaoming; Li, Li

2015-11-03

Because roller element bearings (REBs) failures cause unexpected machinery breakdowns, their fault diagnosis has attracted considerable research attention. Established fault feature extraction methods focus on statistical characteristics of the vibration signal, which is an approach that loses sight of the continuous waveform features. Considering this weakness, this article proposes a novel feature extraction method for frequency bands, named Window Marginal Spectrum Clustering (WMSC) to select salient features from the marginal spectrum of vibration signals by Hilbert-Huang Transform (HHT). In WMSC, a sliding window is used to divide an entire HHT marginal spectrum (HMS) into window spectrums, following which Rand Index (RI) criterion of clustering method is used to evaluate each window. The windows returning higher RI values are selected to construct characteristic frequency bands (CFBs). Next, a hybrid REBs fault diagnosis is constructed, termed by its elements, HHT-WMSC-SVM (support vector machines). The effectiveness of HHT-WMSC-SVM is validated by running series of experiments on REBs defect datasets from the Bearing Data Center of Case Western Reserve University (CWRU). The said test results evidence three major advantages of the novel method. First, the fault classification accuracy of the HHT-WMSC-SVM model is higher than that of HHT-SVM and ST-SVM, which is a method that combines statistical characteristics with SVM. Second, with Gauss white noise added to the original REBs defect dataset, the HHT-WMSC-SVM model maintains high classification accuracy, while the classification accuracy of ST-SVM and HHT-SVM models are significantly reduced. Third, fault classification accuracy by HHT-WMSC-SVM can exceed 95% under a Pmin range of 500-800 and a m range of 50-300 for REBs defect dataset, adding Gauss white noise at Signal Noise Ratio (SNR) = 5. Experimental results indicate that the proposed WMSC method yields a high REBs fault classification accuracy and a good performance in Gauss white noise reduction.

Ecological prediction with nonlinear multivariate time-frequency functional data models

USGS Publications Warehouse

Yang, Wen-Hsi; Wikle, Christopher K.; Holan, Scott H.; Wildhaber, Mark L.

2013-01-01

Time-frequency analysis has become a fundamental component of many scientific inquiries. Due to improvements in technology, the amount of high-frequency signals that are collected for ecological and other scientific processes is increasing at a dramatic rate. In order to facilitate the use of these data in ecological prediction, we introduce a class of nonlinear multivariate time-frequency functional models that can identify important features of each signal as well as the interaction of signals corresponding to the response variable of interest. Our methodology is of independent interest and utilizes stochastic search variable selection to improve model selection and performs model averaging to enhance prediction. We illustrate the effectiveness of our approach through simulation and by application to predicting spawning success of shovelnose sturgeon in the Lower Missouri River.

Communication: Vibrational sum-frequency spectrum of the air-water interface, revisited

NASA Astrophysics Data System (ADS)

Ni, Yicun; Skinner, J. L.

2016-07-01

Before 2015, heterodyne-detected sum-frequency-generation experiments on the air-water interface showed the presence of a positive feature at low frequency in the imaginary part of the susceptibility. However, three very recent experiments indicate that this positive feature is in fact absent. Armed with a better understanding, developed by others, of how to calculate sum-frequency spectra, we recalculate the spectrum and find good agreement with these new experiments. In addition, we provide a revised interpretation of the spectrum.

Temporal resolution of orientation-defined texture segregation: a VEP study.

PubMed

Lachapelle, Julie; McKerral, Michelle; Jauffret, Colin; Bach, Michael

2008-09-01

Orientation is one of the visual dimensions that subserve figure-ground discrimination. A spatial gradient in orientation leads to "texture segregation", which is thought to be concurrent parallel processing across the visual field, without scanning. In the visual-evoked potential (VEP) a component can be isolated which is related to texture segregation ("tsVEP"). Our objective was to evaluate the temporal frequency dependence of the tsVEP to compare processing speed of low-level features (e.g., orientation, using the VEP, here denoted llVEP) with texture segregation because of a recent literature controversy in that regard. Visual-evoked potentials (VEPs) were recorded in seven normal adults. Oriented line segments of 0.1 degrees x 0.8 degrees at 100% contrast were presented in four different arrangements: either oriented in parallel for two homogeneous stimuli (from which were obtained the low-level VEP (llVEP)) or with a 90 degrees orientation gradient for two textured ones (from which were obtained the texture VEP). The orientation texture condition was presented at eight different temporal frequencies ranging from 7.5 to 45 Hz. Fourier analysis was used to isolate low-level components at the pattern-change frequency and texture-segregation components at half that frequency. For all subjects, there was lower high-cutoff frequency for tsVEP than for llVEPs, on average 12 Hz vs. 17 Hz (P = 0.017). The results suggest that the processing of feature gradients to extract texture segregation requires additional processing time, resulting in a lower fusion frequency.

Clinical skin imaging using color spatial frequency domain imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Yang, Bin; Lesicko, John; Moy, Austin J.; Reichenberg, Jason; Tunnell, James W.

2016-02-01

Skin diseases are typically associated with underlying biochemical and structural changes compared with normal tissues, which alter the optical properties of the skin lesions, such as tissue absorption and scattering. Although widely used in dermatology clinics, conventional dermatoscopes don't have the ability to selectively image tissue absorption and scattering, which may limit its diagnostic power. Here we report a novel clinical skin imaging technique called color spatial frequency domain imaging (cSFDI) which enhances contrast by rendering color spatial frequency domain (SFD) image at high spatial frequency. Moreover, by tuning spatial frequency, we can obtain both absorption weighted and scattering weighted images. We developed a handheld imaging system specifically for clinical skin imaging. The flexible configuration of the system allows for better access to skin lesions in hard-to-reach regions. A total of 48 lesions from 31 patients were imaged under 470nm, 530nm and 655nm illumination at a spatial frequency of 0.6mm^(-1). The SFD reflectance images at 470nm, 530nm and 655nm were assigned to blue (B), green (G) and red (R) channels to render a color SFD image. Our results indicated that color SFD images at f=0.6mm-1 revealed properties that were not seen in standard color images. Structural features were enhanced and absorption features were reduced, which helped to identify the sources of the contrast. This imaging technique provides additional insights into skin lesions and may better assist clinical diagnosis.

A new time-frequency method for identification and classification of ball bearing faults

NASA Astrophysics Data System (ADS)

Attoui, Issam; Fergani, Nadir; Boutasseta, Nadir; Oudjani, Brahim; Deliou, Adel

2017-06-01

In order to fault diagnosis of ball bearing that is one of the most critical components of rotating machinery, this paper presents a time-frequency procedure incorporating a new feature extraction step that combines the classical wavelet packet decomposition energy distribution technique and a new feature extraction technique based on the selection of the most impulsive frequency bands. In the proposed procedure, firstly, as a pre-processing step, the most impulsive frequency bands are selected at different bearing conditions using a combination between Fast-Fourier-Transform FFT and Short-Frequency Energy SFE algorithms. Secondly, once the most impulsive frequency bands are selected, the measured machinery vibration signals are decomposed into different frequency sub-bands by using discrete Wavelet Packet Decomposition WPD technique to maximize the detection of their frequency contents and subsequently the most useful sub-bands are represented in the time-frequency domain by using Short Time Fourier transform STFT algorithm for knowing exactly what the frequency components presented in those frequency sub-bands are. Once the proposed feature vector is obtained, three feature dimensionality reduction techniques are employed using Linear Discriminant Analysis LDA, a feedback wrapper method and Locality Sensitive Discriminant Analysis LSDA. Lastly, the Adaptive Neuro-Fuzzy Inference System ANFIS algorithm is used for instantaneous identification and classification of bearing faults. In order to evaluate the performances of the proposed method, different testing data set to the trained ANFIS model by using different conditions of healthy and faulty bearings under various load levels, fault severities and rotating speed. The conclusion resulting from this paper is highlighted by experimental results which prove that the proposed method can serve as an intelligent bearing fault diagnosis system.

Detection of epileptiform activity in EEG signals based on time-frequency and non-linear analysis

PubMed Central

Gajic, Dragoljub; Djurovic, Zeljko; Gligorijevic, Jovan; Di Gennaro, Stefano; Savic-Gajic, Ivana

2015-01-01

We present a new technique for detection of epileptiform activity in EEG signals. After preprocessing of EEG signals we extract representative features in time, frequency and time-frequency domain as well as using non-linear analysis. The features are extracted in a few frequency sub-bands of clinical interest since these sub-bands showed much better discriminatory characteristics compared with the whole frequency band. Then we optimally reduce the dimension of feature space to two using scatter matrices. A decision about the presence of epileptiform activity in EEG signals is made by quadratic classifiers designed in the reduced two-dimensional feature space. The accuracy of the technique was tested on three sets of electroencephalographic (EEG) signals recorded at the University Hospital Bonn: surface EEG signals from healthy volunteers, intracranial EEG signals from the epilepsy patients during the seizure free interval from within the seizure focus and intracranial EEG signals of epileptic seizures also from within the seizure focus. An overall detection accuracy of 98.7% was achieved. PMID:25852534

Gravitational Waves and Time Domain Astronomy

NASA Technical Reports Server (NTRS)

Centrella, Joan; Nissanke, Samaya; Williams, Roy

2012-01-01

The gravitational wave window onto the universe will open in roughly five years, when Advanced LIGO and Virgo achieve the first detections of high frequency gravitational waves, most likely coming from compact binary mergers. Electromagnetic follow-up of these triggers, using radio, optical, and high energy telescopes, promises exciting opportunities in multi-messenger time domain astronomy. In the decade, space-based observations of low frequency gravitational waves from massive black hole mergers, and their electromagnetic counterparts, will open up further vistas for discovery. This two-part workshop featured brief presentations and stimulating discussions on the challenges and opportunities presented by gravitational wave astronomy. Highlights from the workshop, with the emphasis on strategies for electromagnetic follow-up, are presented in this report.

Alcohol Marketing during the UEFA EURO 2016 Football Tournament: A Frequency Analysis

PubMed Central

Critchlow, Nathan; Stead, Martine; Adams, Jean; Brown, Katherine

2017-01-01

This study examined the frequency and nature of alcohol marketing references in broadcasts of the 2016 UEFA (Union of European Football Associations) European Championships football tournament in the United Kingdom (UK). Eighteen matches from across the tournament were recorded in full as broadcast in the UK, including all four matches featuring the English national team and all seven featuring the French national team. All visual and verbal references to alcohol marketing were recorded using a tool with high inter-rater reliability. A total of 2213 alcohol marketing references were recorded, an average of 122.94 per broadcast and 0.65 per broadcast minute (0.52 per minute in-play and 0.80 per minute out-of-play). Almost all references were visual (97.5%), with 77.9% occurring around the pitch border. Almost all (90.6%) were indirect references to alcohol brands (e.g., references to well-known slogans), compared to only 9.4% direct references to brands (e.g., brand names). The frequency of references to alcohol marketing was high. Although the overall proportion of direct brand references was low, the high proportion of indirect references demonstrates that alcohol producers were able to circumvent the French national law governing alcohol marketing (the Loi Évin) using indirect “alibi marketing”. To ensure the spirit of the Loi Évin regulations are achieved, stricter enforcement may be required to limit exposure to alcohol marketing, particularly for young people. PMID:28661462

Monitoring El Hierro submarine volcanic eruption events with a submarine seismic array

NASA Astrophysics Data System (ADS)

Jurado, Maria Jose; Molino, Erik; Lopez, Carmen

2013-04-01

A submarine volcanic eruption took place near the southernmost emerged land of the El Hierro Island (Canary Islands, Spain), from October 2011 to February 2012. The Instituto Geografico Nacional (IGN) seismic stations network evidenced seismic unrest since July 2012 and was a reference also to follow the evolution of the seismic activity associated with the volcanic eruption. From the beginning of the eruption a geophone string was installed less than 2 km away from the new volcano, next to La Restinga village shore, to record seismic activity related to the volcanic activity, continuously and with special interest on high frequency events. The seismic array was endowed with 8, high frequency, 3 component, 250 Hz, geophone cable string with a separation of 6 m between them. The analysis of the dataset using spectral techniques allows the characterization of the different phases of the eruption and the study of its dynamics. The correlation of the data analysis results with the observed sea surface activity (ash and lava emission and degassing) and also with the seismic activity recorded by the IGN field seismic monitoring system, allows the identification of different stages suggesting the existence of different signal sources during the volcanic eruption and also the posteruptive record of the degassing activity. The study shows that the high frequency capability of the geophone array allow the study of important features that cannot be registered by the standard seismic stations. The accumulative spectral amplitude show features related to eruptive changes.

Alcohol Marketing during the UEFA EURO 2016 Football Tournament: A Frequency Analysis.

PubMed

Purves, Richard I; Critchlow, Nathan; Stead, Martine; Adams, Jean; Brown, Katherine

2017-06-29

This study examined the frequency and nature of alcohol marketing references in broadcasts of the 2016 UEFA (Union of European Football Associations) European Championships football tournament in the United Kingdom (UK). Eighteen matches from across the tournament were recorded in full as broadcast in the UK, including all four matches featuring the English national team and all seven featuring the French national team. All visual and verbal references to alcohol marketing were recorded using a tool with high inter-rater reliability. A total of 2213 alcohol marketing references were recorded, an average of 122.94 per broadcast and 0.65 per broadcast minute (0.52 per minute in-play and 0.80 per minute out-of-play). Almost all references were visual (97.5%), with 77.9% occurring around the pitch border. Almost all (90.6%) were indirect references to alcohol brands (e.g., references to well-known slogans), compared to only 9.4% direct references to brands (e.g., brand names). The frequency of references to alcohol marketing was high. Although the overall proportion of direct brand references was low, the high proportion of indirect references demonstrates that alcohol producers were able to circumvent the French national law governing alcohol marketing (the Loi Évin) using indirect "alibi marketing". To ensure the spirit of the Loi Évin regulations are achieved, stricter enforcement may be required to limit exposure to alcohol marketing, particularly for young people.

A Model Describing Stable Coherent Synchrotron Radiation in Storage Rings

NASA Astrophysics Data System (ADS)

Sannibale, F.; Byrd, J. M.; Loftsdóttir, Á.; Venturini, M.; Abo-Bakr, M.; Feikes, J.; Holldack, K.; Kuske, P.; Wüstefeld, G.; Hübers, H.-W.; Warnock, R.

2004-08-01

We present a model describing high power stable broadband coherent synchrotron radiation (CSR) in the terahertz frequency region in an electron storage ring. The model includes distortion of bunch shape from the synchrotron radiation (SR), which enhances higher frequency coherent emission, and limits to stable emission due to an instability excited by the SR wakefield. It gives a quantitative explanation of several features of the recent observations of CSR at the BESSYII storage ring. We also use this model to optimize the performance of a source for stable CSR emission.

Very high-frequency gravitational waves from magnetars and gamma-ray bursts

NASA Astrophysics Data System (ADS)

Wen, Hao; Li, Fang-Yu; Li, Jin; Fang, Zhen-Yun; Beckwith, Andrew

2017-12-01

Extremely powerful astrophysical electromagnetic (EM) systems could be possible sources of high-frequency gravitational waves (HFGWs). Here, based on properties of magnetars and gamma-ray bursts (GRBs), we address “Gamma-HFGWs” (with very high-frequency around 1020 Hz) caused by ultra-strong EM radiation (in the radiation-dominated phase of GRB fireballs) interacting with super-high magnetar surface magnetic fields (˜1011 T). By certain parameters of distance and power, the Gamma-HFGWs would have far field energy density Ω gw around 10-6, and they would cause perturbed signal EM waves of ˜10-20 W/m2 in a proposed HFGW detection system based on the EM response to GWs. Specially, Gamma-HFGWs would possess distinctive envelopes with characteristic shapes depending on the particular structures of surface magnetic fields of magnetars, which could be exclusive features helpful to distinguish them from background noise. Results obtained suggest that magnetars could be involved in possible astrophysical EM sources of GWs in the very high-frequency band, and Gamma-HFGWs could be potential targets for observations in the future. Supported by National Natural Science Foundation of China (11605015, 11375279, 11205254, 11647307) and the Fundamental Research Funds for the Central Universities (106112017CDJXY300003, 106112017CDJXFLX0014)

Spike train generation and current-to-frequency conversion in silicon diodes

NASA Technical Reports Server (NTRS)

Coon, D. D.; Perera, A. G. U.

1989-01-01

A device physics model is developed to analyze spontaneous neuron-like spike train generation in current driven silicon p(+)-n-n(+) devices in cryogenic environments. The model is shown to explain the very high dynamic range (0 to the 7th) current-to-frequency conversion and experimental features of the spike train frequency as a function of input current. The devices are interesting components for implementation of parallel asynchronous processing adjacent to cryogenically cooled focal planes because of their extremely low current and power requirements, their electronic simplicity, and their pulse coding capability, and could be used to form the hardware basis for neural networks which employ biologically plausible means of information coding.

Research of infrared laser based pavement imaging and crack detection

NASA Astrophysics Data System (ADS)

Hong, Hanyu; Wang, Shu; Zhang, Xiuhua; Jing, Genqiang

2013-08-01

Road crack detection is seriously affected by many factors in actual applications, such as some shadows, road signs, oil stains, high frequency noise and so on. Due to these factors, the current crack detection methods can not distinguish the cracks in complex scenes. In order to solve this problem, a novel method based on infrared laser pavement imaging is proposed. Firstly, single sensor laser pavement imaging system is adopted to obtain pavement images, high power laser line projector is well used to resist various shadows. Secondly, the crack extraction algorithm which has merged multiple features intelligently is proposed to extract crack information. In this step, the non-negative feature and contrast feature are used to extract the basic crack information, and circular projection based on linearity feature is applied to enhance the crack area and eliminate noise. A series of experiments have been performed to test the proposed method, which shows that the proposed automatic extraction method is effective and advanced.

Single Trial EEG Patterns for the Prediction of Individual Differences in Fluid Intelligence.

PubMed

Qazi, Emad-Ul-Haq; Hussain, Muhammad; Aboalsamh, Hatim; Malik, Aamir Saeed; Amin, Hafeez Ullah; Bamatraf, Saeed

2016-01-01

Assessing a person's intelligence level is required in many situations, such as career counseling and clinical applications. EEG evoked potentials in oddball task and fluid intelligence score are correlated because both reflect the cognitive processing and attention. A system for prediction of an individual's fluid intelligence level using single trial Electroencephalography (EEG) signals has been proposed. For this purpose, we employed 2D and 3D contents and 34 subjects each for 2D and 3D, which were divided into low-ability (LA) and high-ability (HA) groups using Raven's Advanced Progressive Matrices (RAPM) test. Using visual oddball cognitive task, neural activity of each group was measured and analyzed over three midline electrodes (Fz, Cz, and Pz). To predict whether an individual belongs to LA or HA group, features were extracted using wavelet decomposition of EEG signals recorded in visual oddball task and support vector machine (SVM) was used as a classifier. Two different types of Haar wavelet transform based features have been extracted from the band (0.3 to 30 Hz) of EEG signals. Statistical wavelet features and wavelet coefficient features from the frequency bands 0.0-1.875 Hz (delta low) and 1.875-3.75 Hz (delta high), resulted in the 100 and 98% prediction accuracies, respectively, both for 2D and 3D contents. The analysis of these frequency bands showed clear difference between LA and HA groups. Further, discriminative values of the features have been validated using statistical significance tests and inter-class and intra-class variation analysis. Also, statistical test showed that there was no effect of 2D and 3D content on the assessment of fluid intelligence level. Comparisons with state-of-the-art techniques showed the superiority of the proposed system.

The morphologic and immunohistochemical spectrum of papillary renal cell carcinoma: study including 132 cases with pure type 1 and type 2 morphology as well as tumors with overlapping features.

PubMed

Chevarie-Davis, Myriam; Riazalhosseini, Yasser; Arseneault, Madeleine; Aprikian, Armen; Kassouf, Wassim; Tanguay, Simon; Latour, Mathieu; Brimo, Fadi

2014-07-01

Papillary renal cell carcinomas (pRCC) are classically divided into type 1 and 2 tumors. However, many cases do not fulfill all the criteria for either type. We describe the clinical, morphologic, and immunohistochemical (IHC) features of 132 pRCCs to better characterize the frequency and nature of tumors with overlapping features. Cases were reviewed and classified; IHC evaluation of CK7, EMA, TopoIIα, napsin A, and AMACR was performed on 95 cases. The frequencies of type 1, type 2, and "overlapping" pRCC were 25%, 28%, and 47%, respectively. The 2 categories of "overlapping" tumors were: (1) cases with bland cuboidal cells but no basophilic cytoplasm (type A); and (2) cases with predominantly type 1 histology admixed with areas showing prominent nucleoli (type B). The pathologic stage of "overlapping" cases showed concordance with type 1 tumors. Using the 2 discriminatory markers (CK7, EMA), "type A" cases were similar to type 1. Although the high-nuclear grade areas of "type B" tumors showed some staining differences from their low-nuclear grade counterpart, their IHC profile was closer to type 1. Single nucleotide polymorphism array results, although preliminary and restricted to only 9 cases (3 with overlapping features), also seemed to confirm those findings. In conclusion, we demonstrate that variations in cytoplasmic quality and/or presence of high-grade nuclei in tumors otherwise displaying features of type 1 pRCCs are similar in stage and IHC profile those with classic type 1 histology, suggesting that their spectrum might be wider than originally described.

Anomalous Complex Electrical Conductivity of a Graphitic Black Schist From the Himalayas of Central Nepal

NASA Astrophysics Data System (ADS)

Börner, Jana H.; Girault, Frédéric; Bhattarai, Mukunda; Adhikari, Lok Bijaya; Deldicque, Damien; Perrier, Frédéric; Spitzer, Klaus

2018-05-01

We analyzed in the laboratory the frequency-dependent, complex-valued, electrical conductivity of a graphitic black schist and an augen gneiss, both collected in the Main Central Thrust shear zone in the Himalayas of central Nepal, which was heavily affected by the deadly Mw7.8 Gorkha earthquake in 2015. We focused on anisotropy and salinity dependence of both cores and crushed material as well as the impact of CO2 on conductivity. This black schist possesses an extraordinarily high polarizability and a highly frequency-dependent conductivity. Its anisotropy is very pronounced. The investigations can relate the main polarization feature to disseminated, aligned plates of graphite. By contrast, the augen gneiss shows low polarizability and a moderately anisotropic conductivity dominated by the pore-filling brine. We further demonstrate that neglecting the complex and frequency-dependent nature of conductivity can lead to serious misinterpretation of magnetotelluric data during inversion if highly polarizable rocks are present.

Theory of low-power ultra-broadband terahertz sideband generation in bi-layer graphene.

PubMed

Crosse, J A; Xu, Xiaodong; Sherwin, Mark S; Liu, R B

2014-09-24

In a semiconductor illuminated by a strong terahertz (THz) field, optically excited electron-hole pairs can recombine to emit light in a broad frequency comb evenly spaced by twice the THz frequency. Such high-order THz sideband generation is of interest both as an example of extreme nonlinear optics and also as a method for ultrafast electro-optical modulation. So far, this phenomenon has only been observed with large field strengths (~10 kV cm(-1)), an obstacle for technological applications. Here we predict that bi-layer graphene generates high-order sidebands at much weaker THz fields. We find that a THz field of strength 1 kV cm(-1) can produce a high-sideband spectrum of about 30 THz, 100 times broader than in GaAs. The sidebands are generated despite the absence of classical collisions, with the quantum coherence of the electron-hole pairs enabling recombination. These remarkable features lower the barrier to desktop electro-optical modulation at THz frequencies, facilitating ultrafast optical communications.

Active Control of Separation From the Flap of a Supercritical Airfoil

NASA Technical Reports Server (NTRS)

Melton, LaTunia Pack; Yao, Chung-Sheng; Seifert, Avi

2006-01-01

Zero-mass-flux periodic excitation was applied at several regions on a simplified high-lift system to delay the occurrence of flow separation. The NASA Energy Efficient Transport (EET) supercritical airfoil was equipped with a 15% chord simply hinged leading edge flap and a 25% chord simply hinged trailing edge flap. Detailed flow features were measured in an attempt to identify optimal actuator placement. The measurements included steady and unsteady model and tunnel wall pressures, wake surveys, arrays of surface hot-films, flow visualization, and particle image velocimetry (PIV). The current paper describes the application of active separation control at several locations on the deflected trailing edge flap. High frequency (F(+) approximately equal to 10) and low frequency amplitude modulation (F(+) sub AM approximately equal to 1) of the high frequency excitation were used for control. It was noted that the same performance gains were obtained with amplitude modulation and required only 30% of the momentum input required by pure sine excitation.

Active Control of Separation From the Flap of a Supercritical Airfoil

NASA Technical Reports Server (NTRS)

Melton, La Tunia Pack; Yao, Chung-Sheng; Seifert, Avi

2003-01-01

Active flow control in the form of periodic zero-mass-flux excitation was applied at several regions on the leading edge and trailing edge flaps of a simplified high-lift system t o delay flow separation. The NASA Energy Efficient Transport (EET) supercritical airfoil was equipped with a 15% chord simply hinged leading edge flap and a 25% chord simply hinged trailing edge flap. Detailed flow features were measured in an attempt to identify optimal actuator placement. The measurements included steady and unsteady model and tunnel wall pressures, wake surveys, arrays of surface hot-films, flow visualization, and particle image velocimetry (PIV). The current paper describes the application of active separation control at several locations on the deflected trailing edge flap. High frequency (F(+) approx.= 10) and low frequency amplitude modulation (F(+)AM approx.= 1) of the high frequency excitation were used for control. Preliminary efforts to combine leading and trailing edge flap excitations are also reported.

Radiological Features of Brain Metastases from Non-small Cell Lung Cancer Harboring EGFR Mutation.

PubMed

Takamori, Shinkichi; Toyokawa, Gouji; Shimokawa, Mototsugu; Kinoshita, Fumihiko; Kozuma, Yuka; Matsubara, Taichi; Haratake, Naoki; Akamine, Takaki; Mukae, Nobutaka; Hirai, Fumihiko; Tagawa, Tetsuzo; Oda, Yoshinao; Iwaki, Toru; Iihara, Koji; Honda, Hiroshi; Maehara, Yoshihiko

2018-06-01

To investigate the radiological features on computed tomography (CT) of brain metastasis (BM) from epidermal growth factor receptor (EGFR)-mutated non-small cell lung cancer (NSCLC). Thirty-four patients with NSCLC with BMs who underwent surgical resection of the BMs at the Department of Neurosurgery, Kyushu University from 2005 to 2016 were enrolled in the study. The EGFR statuses of the 34 BMs were investigated. Radiological features, including the number, size, and location of the tumor, were delineated by CT. Patients with EGFR-mutated BMs had significantly higher frequencies of multiple metastases than those with the non-EGFR-mutated type (p=0.042). BMs harboring mutations in EGFR were more frequently observed in the central area of the brain compared to those without mutations in EGFR (p=0.037). Careful follow-up of patients with EGFR-mutated NSCLC may be necessary given the high frequencies of multiple BMs and their location in the central area of the brain. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Image alignment

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

Dowell, Larry Jonathan

Disclosed is a method and device for aligning at least two digital images. An embodiment may use frequency-domain transforms of small tiles created from each image to identify substantially similar, "distinguishing" features within each of the images, and then align the images together based on the location of the distinguishing features. To accomplish this, an embodiment may create equal sized tile sub-images for each image. A "key" for each tile may be created by performing a frequency-domain transform calculation on each tile. A information-distance difference between each possible pair of tiles on each image may be calculated to identify distinguishingmore » features. From analysis of the information-distance differences of the pairs of tiles, a subset of tiles with high discrimination metrics in relation to other tiles may be located for each image. The subset of distinguishing tiles for each image may then be compared to locate tiles with substantially similar keys and/or information-distance metrics to other tiles of other images. Once similar tiles are located for each image, the images may be aligned in relation to the identified similar tiles.« less

Multiscale Thermo-Mechanical Design and Analysis of High Frequency and High Power Vacuum Electron Devices

NASA Astrophysics Data System (ADS)

Gamzina, Diana

Diana Gamzina March 2016 Mechanical and Aerospace Engineering Multiscale Thermo-Mechanical Design and Analysis of High Frequency and High Power Vacuum Electron Devices Abstract A methodology for performing thermo-mechanical design and analysis of high frequency and high average power vacuum electron devices is presented. This methodology results in a "first-pass" engineering design directly ready for manufacturing. The methodology includes establishment of thermal and mechanical boundary conditions, evaluation of convective film heat transfer coefficients, identification of material options, evaluation of temperature and stress field distributions, assessment of microscale effects on the stress state of the material, and fatigue analysis. The feature size of vacuum electron devices operating in the high frequency regime of 100 GHz to 1 THz is comparable to the microstructure of the materials employed for their fabrication. As a result, the thermo-mechanical performance of a device is affected by the local material microstructure. Such multiscale effects on the stress state are considered in the range of scales from about 10 microns up to a few millimeters. The design and analysis methodology is demonstrated on three separate microwave devices: a 95 GHz 10 kW cw sheet beam klystron, a 263 GHz 50 W long pulse wide-bandwidth sheet beam travelling wave tube, and a 346 GHz 1 W cw backward wave oscillator.

Sources of sound in fluid flows

NASA Technical Reports Server (NTRS)

Williams, J. E. F.

1974-01-01

Some features of a flow that produce acoustic radiation, particularly when the flow is turbulent and interacting with solid surfaces such as turbine or compressor blades are discussed. Early theoretical ideas on the subject are reviewed and are shown to be inadequate at high Mach number. Some recent theoretical developments that form the basis of a description of sound generation by supersonic flows interacting with surfaces are described. At high frequencies the problem is treated as one of describing the surface-induced diffraction field of adjacent aerodynamic quadrupole sources. This approach has given rise to distinctly new features of the problem that seem to have bearing on the radiating properties of relatively large aerodynamic surfaces.

The new 34-meter antenna

NASA Technical Reports Server (NTRS)

Pompa, M. F.

1986-01-01

The new 34-m high efficiency Azimuth - Elevation antenna configuration, including its features, dynamic characteristics and performance at 8.4-GHz frequencies is described. The current-technology features of this antenna produce a highly reliable configuration by incorporation of a main wheel and track azimuth support, central pintle pivot bearing, close tolerance surface panels and all-welded construction. Also described are basic drive controls that, as slaved to three automatic microprocessors, provide accurate and safe control of the antenna's steering tasks. At this time antenna installations are completed at Goldstone and Canberra and have operationally supported the Voyager - Uranus encounter. A third installation is being constructed currently in Madrid and is scheduled for completion in late 1986.

Design and performance of the LCLS cavity BPM system.

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

Lill, R.; Norum, E.; Morrison, L.

2008-01-01

In this paper we present the design of the beam position monitor (BPM) system for the LCLS undulator, which features a high-resolution X-band cavity BPM. Each BPM has a TM{sub 010} monopole reference cavity and a TM{sub 110} dipole cavity designed to operate at a center frequency of 11.384 GHz. The signal processing electronics features a low- noise single-stage three-channel heterodyne receiver that has selectable gain and a phase locking local oscillator. We will discuss the system specifications, design, and prototype test results.

Design and Performance of the LCLS Cavity BPM System

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

Lill, R.M.; Morrison, L.H.; Norum, W.E.

2008-01-23

In this paper we present the design of the beam position monitor (BPM) system for the LCLS undulator, which features a high-resolution X-band cavity BPM. Each BPM has a TM{sub 010} monopole reference cavity and a TM{sub 110} dipole cavity designed to operate at a center frequency of 11.384 GHz. The signal processing electronics features a low noise single-stage three-channel heterodyne receiver that has selectable gain and a phase locking local oscillator. We will discuss the system specifications, design, and prototype test results.

Minimal Power Latch for Single-Slope ADCs

NASA Technical Reports Server (NTRS)

Hancock, Bruce R. (Inventor)

2015-01-01

A latch circuit that uses two interoperating latches. The latch circuit has the beneficial feature that it switches only a single time during a measurement that uses a stair step or ramp function as an input signal in an analog to digital converter. This feature minimizes the amount of power that is consumed in the latch and also minimizes the amount of high frequency noise that is generated by the latch. An application using a plurality of such latch circuits in a parallel decoding ADC for use in an image sensor is given as an example.

Aeroelastic characteristics of composite bearingless rotor blades

NASA Technical Reports Server (NTRS)

Bielawa, R. L.

1976-01-01

Owing to the inherent unique structural features of composite bearingless rotors, various assumptions upon which conventional rotor aeroelastic analyses are formulated, are violated. Three such features identified are highly nonlinear and time-varying structural twist, structural redundancy in bending and torsion, and for certain configurations a strongly coupled low frequency bending-torsion mode. An examination of these aeroelastic considerations and appropriate formulations required for accurate analyses of such rotor systems is presented. Also presented are test results from a dynamically scaled model rotor and complementary analytic results obtained with the appropriately reformulated aeroelastic analysis.

Low-frequency 1/f noise in graphene devices

NASA Astrophysics Data System (ADS)

Balandin, Alexander A.

2013-08-01

Low-frequency noise with a spectral density that depends inversely on frequency has been observed in a wide variety of systems including current fluctuations in resistors, intensity fluctuations in music and signals in human cognition. In electronics, the phenomenon, which is known as 1/f noise, flicker noise or excess noise, hampers the operation of numerous devices and circuits, and can be a significant impediment to the development of practical applications from new materials. Graphene offers unique opportunities for studying 1/f noise because of its two-dimensional structure and widely tunable two-dimensional carrier concentration. The creation of practical graphene-based devices will also depend on our ability to understand and control the low-frequency noise in this material system. Here, the characteristic features of 1/f noise in graphene and few-layer graphene are reviewed, and the implications of such noise for the development of graphene-based electronics including high-frequency devices and sensors are examined.

Low-frequency 1/f noise in graphene devices.

PubMed

Balandin, Alexander A

2013-08-01

Low-frequency noise with a spectral density that depends inversely on frequency has been observed in a wide variety of systems including current fluctuations in resistors, intensity fluctuations in music and signals in human cognition. In electronics, the phenomenon, which is known as 1/f noise, flicker noise or excess noise, hampers the operation of numerous devices and circuits, and can be a significant impediment to the development of practical applications from new materials. Graphene offers unique opportunities for studying 1/f noise because of its two-dimensional structure and widely tunable two-dimensional carrier concentration. The creation of practical graphene-based devices will also depend on our ability to understand and control the low-frequency noise in this material system. Here, the characteristic features of 1/f noise in graphene and few-layer graphene are reviewed, and the implications of such noise for the development of graphene-based electronics including high-frequency devices and sensors are examined.

Modulation of microsaccades by spatial frequency during object categorization.

PubMed

Craddock, Matt; Oppermann, Frank; Müller, Matthias M; Martinovic, Jasna

2017-01-01

The organization of visual processing into a coarse-to-fine information processing based on the spatial frequency properties of the input forms an important facet of the object recognition process. During visual object categorization tasks, microsaccades occur frequently. One potential functional role of these eye movements is to resolve high spatial frequency information. To assess this hypothesis, we examined the rate, amplitude and speed of microsaccades in an object categorization task in which participants viewed object and non-object images and classified them as showing either natural objects, man-made objects or non-objects. Images were presented unfiltered (broadband; BB) or filtered to contain only low (LSF) or high spatial frequency (HSF) information. This allowed us to examine whether microsaccades were modulated independently by the presence of a high-level feature - the presence of an object - and by low-level stimulus characteristics - spatial frequency. We found a bimodal distribution of saccades based on their amplitude, with a split between smaller and larger microsaccades at 0.4° of visual angle. The rate of larger saccades (⩾0.4°) was higher for objects than non-objects, and higher for objects with high spatial frequency content (HSF and BB objects) than for LSF objects. No effects were observed for smaller microsaccades (<0.4°). This is consistent with a role for larger microsaccades in resolving HSF information for object identification, and previous evidence that more microsaccades are directed towards informative image regions. Copyright © 2016 Elsevier Ltd. All rights reserved.

An Attempt to Simulate Letter-by-Letter Dyslexia in Normal Readers

ERIC Educational Resources Information Center

Fiset, Stephanie; Arguin, Martin; Fiset, Daniel

2006-01-01

We attempted to simulate the main features of letter-by-letter (LBL) dyslexia in normal readers through stimulus degradation (i.e. contrast reduction and removal of high spatial frequencies). The results showed the word length and the letter confusability effects characteristic of LBL dyslexia. However, the interaction of letter confusability and…

Mood and Anxiety Symptoms in Psychiatric Inpatients with Autism Spectrum Disorder and Depression

ERIC Educational Resources Information Center

Charlot, Lauren; Deutsch, Curtis K.; Albert, Aranya; Hunt, Anne; Connor, Daniel F.; McIlvane, William J., Jr.

2008-01-01

Recent reports suggest that individuals with autism spectrum disorders (ASD) may experience depression at a high frequency, yet few published studies address this issue, especially among adults. In the current investigation, we reviewed features of depression and comorbid traits among depressed inpatients with intellectual disabilities (ID) as a…

Reduced Reliance on Optimal Facial Information for Identity Recognition in Autism Spectrum Disorder

ERIC Educational Resources Information Center

Leonard, Hayley C.; Annaz, Dagmara; Karmiloff-Smith, Annette; Johnson, Mark H.

2013-01-01

Previous research into face processing in autism spectrum disorder (ASD) has revealed atypical biases toward particular facial information during identity recognition. Specifically, a focus on features (or high spatial frequencies [HSFs]) has been reported for both face and nonface processing in ASD. The current study investigated the development…

Exploring the parahippocampal cortex response to high and low spatial frequency spaces.

PubMed

Zeidman, Peter; Mullally, Sinéad L; Schwarzkopf, Dietrich Samuel; Maguire, Eleanor A

2012-05-30

The posterior parahippocampal cortex (PHC) supports a range of cognitive functions, in particular scene processing. However, it has recently been suggested that PHC engagement during functional MRI simply reflects the representation of three-dimensional local space. If so, PHC should respond to space in the absence of scenes, geometric layout, objects or contextual associations. It has also been reported that PHC activation may be influenced by low-level visual properties of stimuli such as spatial frequency. Here, we tested whether PHC was responsive to the mere sense of space in highly simplified stimuli, and whether this was affected by their spatial frequency distribution. Participants were scanned using functional MRI while viewing depictions of simple three-dimensional space, and matched control stimuli that did not depict a space. Half the stimuli were low-pass filtered to ascertain the impact of spatial frequency. We observed a significant interaction between space and spatial frequency in bilateral PHC. Specifically, stimuli depicting space (more than nonspatial stimuli) engaged the right PHC when they featured high spatial frequencies. In contrast, the interaction in the left PHC did not show a preferential response to space. We conclude that a simple depiction of three-dimensional space that is devoid of objects, scene layouts or contextual associations is sufficient to robustly engage the right PHC, at least when high spatial frequencies are present. We suggest that coding for the presence of space may be a core function of PHC, and could explain its engagement in a range of tasks, including scene processing, where space is always present.

Asymmetry of bifurcated features in radio pulsar profiles

NASA Astrophysics Data System (ADS)

Dyks, J.; Rudak, B.

2012-03-01

High-quality integrated radio profiles of some pulsars contain bifurcated, highly symmetric emission components (BECs). They are observed when our line of sight traverses through a split-fan shaped emission beam. It is shown that for oblique cuts through such a beam, the features appear asymmetric at nearly all frequencies, except for a single 'frequency of symmetry'νsym, at which both peaks in the BEC have the same height. Around νsym, the ratio of flux in the two peaks of a BEC evolves in a way resembling the multifrequency behaviour of J1012+5307. Because of the inherent asymmetry resulting from the oblique traverse of the sightline, each minimum in double notches can be modelled independently. Such a composed model reproduces the double notches of B1929+10 if the fitted function is the microscopic beam of curvature radiation in the orthogonal polarization mode. These results confirm our view that some of the double components in radio pulsar profiles directly reveal the microscopic nature of the emitted radiation beam as the microbeam of the curvature radiation polarized orthogonally to the trajectory of electrons.

A New Deep Learning Model for Fault Diagnosis with Good Anti-Noise and Domain Adaptation Ability on Raw Vibration Signals

PubMed Central

Zhang, Wei; Peng, Gaoliang; Li, Chuanhao; Chen, Yuanhang; Zhang, Zhujun

2017-01-01

Intelligent fault diagnosis techniques have replaced time-consuming and unreliable human analysis, increasing the efficiency of fault diagnosis. Deep learning models can improve the accuracy of intelligent fault diagnosis with the help of their multilayer nonlinear mapping ability. This paper proposes a novel method named Deep Convolutional Neural Networks with Wide First-layer Kernels (WDCNN). The proposed method uses raw vibration signals as input (data augmentation is used to generate more inputs), and uses the wide kernels in the first convolutional layer for extracting features and suppressing high frequency noise. Small convolutional kernels in the preceding layers are used for multilayer nonlinear mapping. AdaBN is implemented to improve the domain adaptation ability of the model. The proposed model addresses the problem that currently, the accuracy of CNN applied to fault diagnosis is not very high. WDCNN can not only achieve 100% classification accuracy on normal signals, but also outperform the state-of-the-art DNN model which is based on frequency features under different working load and noisy environment conditions. PMID:28241451

An Application of Rotation- and Translation-Invariant Overcomplete Wavelets to the registration of Remotely Sensed Imagery

NASA Technical Reports Server (NTRS)

LeMoigne, Jacqueline; Zavorine, Ilya

1999-01-01

A wavelet-based image registration approach has previously been proposed by the authors. In this work, wavelet coefficient maxima obtained from an orthogonal wavelet decomposition using Daubechies filters were utilized to register images in a multi-resolution fashion. Tested on several remote sensing datasets, this method gave very encouraging results. Despite the lack of translation-invariance of these filters, we showed that when using cross-correlation as a feature matching technique, features of size larger than twice the size of the filters are correctly registered by using the low-frequency subbands of the Daubechies wavelet decomposition. Nevertheless, high-frequency subbands are still sensitive to translation effects. In this work, we are considering a rotation- and translation-invariant representation developed by E. Simoncelli and integrate it in our image registration scheme. The two types of filters, Daubechies and Simoncelli filters, are then being compared from a registration point of view, utilizing synthetic data as well as data from the Landsat/ Thematic Mapper (TM) and from the NOAA Advanced Very High Resolution Radiometer (AVHRR).

An Application of Rotation- and Translation-Invariant Overcomplete Wavelets to the Registration of Remotely Sensed Imagery

NASA Technical Reports Server (NTRS)

LeMoigne, Jacqueline; Zavorine, Ilya

1999-01-01

A wavelet-based image registration approach has previously been proposed by the authors. In this work, wavelet coefficient maxima obtained from an orthogonal wavelet decomposition using Daubechies filters were utilized to register images in a multi-resolution fashion. Tested on several remote sensing datasets, this method gave very encouraging results. Despite the lack of translation-invariance of these filters, we showed that when using cross-correlation as a feature matching technique, features of size larger than twice the size of the filters are correctly registered by using the low-frequency subbands of the Daubechies wavelet decomposition. Nevertheless, high-frequency subbands are still sensitive to translation effects. In this work, we are considering a rotation- and translation-invariant representation developed by E. Simoncelli and integrate it in our image registration scheme. The two types of filters, Daubechies and Simoncelli filters, are then being compared from a registration point of view, utilizing synthetic data as well as data from the Landsat/ Thematic Mapper (TM) and from the NOAA Advanced Very High Resolution Radiometer (AVHRR).

High-frequency health data and spline functions.

PubMed

Martín-Rodríguez, Gloria; Murillo-Fort, Carlos

2005-03-30

Seasonal variations are highly relevant for health service organization. In general, short run movements of medical magnitudes are important features for managers in this field to make adequate decisions. Thus, the analysis of the seasonal pattern in high-frequency health data is an appealing task. The aim of this paper is to propose procedures that allow the analysis of the seasonal component in this kind of data by means of spline functions embedded into a structural model. In the proposed method, useful adaptions of the traditional spline formulation are developed, and the resulting procedures are capable of capturing periodic variations, whether deterministic or stochastic, in a parsimonious way. Finally, these methodological tools are applied to a series of daily emergency service demand in order to capture simultaneous seasonal variations in which periods are different.

EEG-based workload estimation across affective contexts

PubMed Central

Mühl, Christian; Jeunet, Camille; Lotte, Fabien

2014-01-01

Workload estimation from electroencephalographic signals (EEG) offers a highly sensitive tool to adapt the human–computer interaction to the user state. To create systems that reliably work in the complexity of the real world, a robustness against contextual changes (e.g., mood), has to be achieved. To study the resilience of state-of-the-art EEG-based workload classification against stress we devise a novel experimental protocol, in which we manipulated the affective context (stressful/non-stressful) while the participant solved a task with two workload levels. We recorded self-ratings, behavior, and physiology from 24 participants to validate the protocol. We test the capability of different, subject-specific workload classifiers using either frequency-domain, time-domain, or both feature varieties to generalize across contexts. We show that the classifiers are able to transfer between affective contexts, though performance suffers independent of the used feature domain. However, cross-context training is a simple and powerful remedy allowing the extraction of features in all studied feature varieties that are more resilient to task-unrelated variations in signal characteristics. Especially for frequency-domain features, across-context training is leading to a performance comparable to within-context training and testing. We discuss the significance of the result for neurophysiology-based workload detection in particular and for the construction of reliable passive brain–computer interfaces in general. PMID:24971046

Bilateral preictal signature of phase-amplitude coupling in canine epilepsy.

PubMed

Gagliano, Laura; Bou Assi, Elie; Nguyen, Dang K; Rihana, Sandy; Sawan, Mohamad

2018-01-01

Seizure forecasting would improve the quality of life of patients with refractory epilepsy. Although early findings were optimistic, no single feature has been found capable of individually characterizing brain dynamics during transition to seizure. Cross-frequency phase amplitude coupling has been recently proposed as a precursor of seizure activity. This work evaluates the existence of a statistically significant difference in mean phase amplitude coupling distribution between the preictal and interictal states of seizures in dogs with bilaterally implanted intracranial electrodes. Results show a statistically significant change (p<0.05) of phase amplitude coupling during the preictal phase. This change is correlated with the position of implanted electrodes and is more significant within high-gamma frequency bands. These findings highlight the potential benefit of bilateral iEEG analysis and the feasibility of seizure forecasting based on slow modulation of high frequency amplitude. Copyright © 2017 Elsevier B.V. All rights reserved.

ECG denoising with adaptive bionic wavelet transform.

PubMed

Sayadi, Omid; Shamsollahi, Mohammad Bagher

2006-01-01

In this paper a new ECG denoising scheme is proposed using a novel adaptive wavelet transform, named bionic wavelet transform (BWT), which had been first developed based on a model of the active auditory system. There has been some outstanding features with the BWT such as nonlinearity, high sensitivity and frequency selectivity, concentrated energy distribution and its ability to reconstruct signal via inverse transform but the most distinguishing characteristic of BWT is that its resolution in the time-frequency domain can be adaptively adjusted not only by the signal frequency but also by the signal instantaneous amplitude and its first-order differential. Besides by optimizing the BWT parameters parallel to modifying a new threshold value, one can handle ECG denoising with results comparing to those of wavelet transform (WT). Preliminary tests of BWT application to ECG denoising were constructed on the signals of MIT-BIH database which showed high performance of noise reduction.

Amplification of a high-frequency electromagnetic wave by a relativistic plasma

NASA Technical Reports Server (NTRS)

Yoon, Peter H.

1990-01-01

The amplification of a high-frequency transverse electromagnetic wave by a relativistic plasma component, via the synchrotron maser process, is studied. The background plasma that supports the transverse wave is considered to be cold, and the energetic component whose density is much smaller than that of the background component has a loss-cone feature in the perpendicular momentum space and a finite field-aligned drift speed. The ratio of the background plasma frequency squared to the electron gyrofrequency squared is taken to be sufficiently larger than unity. Such a parameter regime is relevant to many space and astrophysical situations. A detailed study of the amplification process is carried out over a wide range of physical parameters including the loss-cone index, the ratio of the electron mass energy to the temperature of the energetic component, the field-aligned drift speed, the normalized density, and the wave propagation angle.

A wavelet-based technique to predict treatment outcome for Major Depressive Disorder.

PubMed

Mumtaz, Wajid; Xia, Likun; Mohd Yasin, Mohd Azhar; Azhar Ali, Syed Saad; Malik, Aamir Saeed

2017-01-01

Treatment management for Major Depressive Disorder (MDD) has been challenging. However, electroencephalogram (EEG)-based predictions of antidepressant's treatment outcome may help during antidepressant's selection and ultimately improve the quality of life for MDD patients. In this study, a machine learning (ML) method involving pretreatment EEG data was proposed to perform such predictions for Selective Serotonin Reuptake Inhibitor (SSRIs). For this purpose, the acquisition of experimental data involved 34 MDD patients and 30 healthy controls. Consequently, a feature matrix was constructed involving time-frequency decomposition of EEG data based on wavelet transform (WT) analysis, termed as EEG data matrix. However, the resultant EEG data matrix had high dimensionality. Therefore, dimension reduction was performed based on a rank-based feature selection method according to a criterion, i.e., receiver operating characteristic (ROC). As a result, the most significant features were identified and further be utilized during the training and testing of a classification model, i.e., the logistic regression (LR) classifier. Finally, the LR model was validated with 100 iterations of 10-fold cross-validation (10-CV). The classification results were compared with short-time Fourier transform (STFT) analysis, and empirical mode decompositions (EMD). The wavelet features extracted from frontal and temporal EEG data were found statistically significant. In comparison with other time-frequency approaches such as the STFT and EMD, the WT analysis has shown highest classification accuracy, i.e., accuracy = 87.5%, sensitivity = 95%, and specificity = 80%. In conclusion, significant wavelet coefficients extracted from frontal and temporal pre-treatment EEG data involving delta and theta frequency bands may predict antidepressant's treatment outcome for the MDD patients.

Spike Timing Matters in Novel Neuronal Code Involved in Vibrotactile Frequency Perception.

PubMed

Birznieks, Ingvars; Vickery, Richard M

2017-05-22

Skin vibrations sensed by tactile receptors contribute significantly to the perception of object properties during tactile exploration [1-4] and to sensorimotor control during object manipulation [5]. Sustained low-frequency skin vibration (<60 Hz) evokes a distinct tactile sensation referred to as flutter whose frequency can be clearly perceived [6]. How afferent spiking activity translates into the perception of frequency is still unknown. Measures based on mean spike rates of neurons in the primary somatosensory cortex are sufficient to explain performance in some frequency discrimination tasks [7-11]; however, there is emerging evidence that stimuli can be distinguished based also on temporal features of neural activity [12, 13]. Our study's advance is to demonstrate that temporal features are fundamental for vibrotactile frequency perception. Pulsatile mechanical stimuli were used to elicit specified temporal spike train patterns in tactile afferents, and subsequently psychophysical methods were employed to characterize human frequency perception. Remarkably, the most salient temporal feature determining vibrotactile frequency was not the underlying periodicity but, rather, the duration of the silent gap between successive bursts of neural activity. This burst gap code for frequency represents a previously unknown form of neural coding in the tactile sensory system, which parallels auditory pitch perception mechanisms based on purely temporal information where longer inter-pulse intervals receive higher perceptual weights than short intervals [14]. Our study also demonstrates that human perception of stimuli can be determined exclusively by temporal features of spike trains independent of the mean spike rate and without contribution from population response factors. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

SCINTILLATION ARCS IN LOW-FREQUENCY OBSERVATIONS OF THE TIMING-ARRAY MILLISECOND PULSAR PSR J0437–4715

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

Bhat, N. D. R.; Ord, S. M.; Tremblay, S. E.

2016-02-10

Low-frequency observations of pulsars provide a powerful means for probing the microstructure in the turbulent interstellar medium (ISM). Here we report on high-resolution dynamic spectral analysis of our observations of the timing-array millisecond pulsar PSR J0437–4715 with the Murchison Widefield Array (MWA), enabled by our recently commissioned tied-array beam processing pipeline for voltage data recorded from the high time resolution mode of the MWA. A secondary spectral analysis reveals faint parabolic arcs akin to those seen in high-frequency observations of pulsars with the Green Bank and Arecibo telescopes. Data from Parkes observations at a higher frequency of 732 MHz revealmore » a similar parabolic feature with a curvature that scales approximately as the square of the observing wavelength (λ{sup 2}) to the MWA's frequency of 192 MHz. Our analysis suggests that scattering toward PSR J0437–4715 predominantly arises from a compact region about 115 pc from the Earth, which matches well with the expected location of the edge of the Local Bubble that envelopes the local Solar neighborhood. As well as demonstrating new and improved pulsar science capabilities of the MWA, our analysis underscores the potential of low-frequency pulsar observations for gaining valuable insights into the local ISM and for characterizing the ISM toward timing-array pulsars.« less

[Analysis on occupational noise-induced hearing loss of different type workers in underground mining].

PubMed

Liu, Q C; Duo, C H; Wang, Z; Yan, K; Zhang, J; Xiong, W; Zhu, M

2017-11-20

Objective: To investigate hearing loss status of blasters, drillers mechanics and so on in underground mining, and put forward suggestion diagnosis of occupational explosive deafness and occupational deafness. Methods: Underground excavation workers in a metal mine were recruited in this study, those with a history of ear disease and non-occupational deafness were all excluded. Finally, the features of pure tone audiometry of 459 noise-exposed workers were analyzed. Results: High-frequency hearing loss occurred on 351workers and the positive detection rate was 74.29%, workers who had both high-frequency and linguistic frequency hearing loss were 51 and the positive detection rate was 11.11%. The positive detection of high-frequency hearing loss in right ear (χ(2)=9.427 and P = 0.024) and in left ear (χ(2)=14.375, P =0.002) was significantly different between different exposure age groups. The positive detection of high-frequency hearing loss of driving group was the highest, followed by blasting group, mining group and machine repair group. The characteristics of the hearing loss caused by drilling noise of the blasting workers with no accident occurred were in line with that of noise-induced hearing loss. Conclusion: The diagnosis grading should be carried out according to the diagnostic criteria of occupational noise-induced deafness for the employees who engaged in the blasting operation with no record of blast accident.

Electromagnetic Ion Cyclotron Waves in the High Altitude Cusp: Polar Observations

NASA Technical Reports Server (NTRS)

Le, Guan; Blanco-Cano, X.; Russell, C. T.; Zhou, X.-W.; Mozer, F.; Trattner, K. J.; Fuselier, S. A.; Anderson, B. J.; Vondrak, Richard R. (Technical Monitor)

2001-01-01

High-resolution magnetic field data from the Polar Magnetic Field Experiment (MFE) show that narrow band waves at frequencies approximately 0.2 to 3 Hz are a permanent feature in the vicinity of the polar cusp. The waves have been found in the magnetosphere adjacent to the cusp (both poleward and equatorward of the cusp) and in the cusp itself. The occurrence of waves is coincident with depression of magnetic field strength associated with enhanced plasma density, indicating the entry of magnetosheath plasma into the cusp region. The wave frequencies are generally scaled by the local proton cyclotron frequency, and vary between 0.2 and 1.7 times local proton cyclotron frequency. This suggests that the waves are generated in the cusp region by the precipitating magnetosheath plasma. The properties of the waves are highly variable. The waves exhibit both lefthanded and right-handed polarization in the spacecraft frame. The propagation angles vary from nearly parallel to nearly perpendicular to the magnetic field. We find no correlation among wave frequency, propagation angle and polarization. Combined magnetic field and electric field data for the waves indicate that the energy flux of the waves is guided by the background magnetic field and points downward toward the ionosphere.

Electromagnetic Ion Cyclotron Waves in the High-Altitude Cusp: Polar Observations

NASA Technical Reports Server (NTRS)

Le, G.; Blanco-Cano, X.; Russell, C. T.; Zhou, X.-W.; Mozer, F.; Trattner, K. J.; Fuselier, S. A.; Anderson, B. J.

2005-01-01

High-resolution magnetic field data from the Polar Magnetic Field Experiment (MFE) show that narrow-band waves at frequencies approx. 0.2-3 Hz are a permanent feature in the vicinity of the polar cusp. The waves have been found in the magnetosphere adjacent to the cusp (both poleward and equatorward of the cusp) and in the cusp itself. The occurrence of waves is coincident with depression of magnetic field strength associated with enhanced plasma density, indicating the entry of magnetosheath plasma into the cusp region. The wave frequencies are generally scaled by the local proton cyclotron frequency and vary between 0.2 and 1.7 times local proton cyclotron frequency. This suggests that the waves are generated in the cusp region by the precipitating magnetosheath plasma. The properties of the waves are highly variable. The waves exhibit both left-handed and right-handed polarization in the spacecraft frame. The propagation angles vary from nearly parallel to nearly perpendicular to the magnetic field. We find no correlation among wave frequency, propagation angle, and polarization. Combined magnetic field and electric field data for the waves indicate that the energy flux of the waves is guided by the background magnetic field and points downward toward the ionosphere.

The Vestibular System Implements a Linear–Nonlinear Transformation In Order to Encode Self-Motion

PubMed Central

Massot, Corentin; Schneider, Adam D.; Chacron, Maurice J.; Cullen, Kathleen E.

2012-01-01

Although it is well established that the neural code representing the world changes at each stage of a sensory pathway, the transformations that mediate these changes are not well understood. Here we show that self-motion (i.e. vestibular) sensory information encoded by VIIIth nerve afferents is integrated nonlinearly by post-synaptic central vestibular neurons. This response nonlinearity was characterized by a strong (∼50%) attenuation in neuronal sensitivity to low frequency stimuli when presented concurrently with high frequency stimuli. Using computational methods, we further demonstrate that a static boosting nonlinearity in the input-output relationship of central vestibular neurons accounts for this unexpected result. Specifically, when low and high frequency stimuli are presented concurrently, this boosting nonlinearity causes an intensity-dependent bias in the output firing rate, thereby attenuating neuronal sensitivities. We suggest that nonlinear integration of afferent input extends the coding range of central vestibular neurons and enables them to better extract the high frequency features of self-motion when embedded with low frequency motion during natural movements. These findings challenge the traditional notion that the vestibular system uses a linear rate code to transmit information and have important consequences for understanding how the representation of sensory information changes across sensory pathways. PMID:22911113

Infrared and visible fusion face recognition based on NSCT domain

NASA Astrophysics Data System (ADS)

Xie, Zhihua; Zhang, Shuai; Liu, Guodong; Xiong, Jinquan

2018-01-01

Visible face recognition systems, being vulnerable to illumination, expression, and pose, can not achieve robust performance in unconstrained situations. Meanwhile, near infrared face images, being light- independent, can avoid or limit the drawbacks of face recognition in visible light, but its main challenges are low resolution and signal noise ratio (SNR). Therefore, near infrared and visible fusion face recognition has become an important direction in the field of unconstrained face recognition research. In this paper, a novel fusion algorithm in non-subsampled contourlet transform (NSCT) domain is proposed for Infrared and visible face fusion recognition. Firstly, NSCT is used respectively to process the infrared and visible face images, which exploits the image information at multiple scales, orientations, and frequency bands. Then, to exploit the effective discriminant feature and balance the power of high-low frequency band of NSCT coefficients, the local Gabor binary pattern (LGBP) and Local Binary Pattern (LBP) are applied respectively in different frequency parts to obtain the robust representation of infrared and visible face images. Finally, the score-level fusion is used to fuse the all the features for final classification. The visible and near infrared face recognition is tested on HITSZ Lab2 visible and near infrared face database. Experiments results show that the proposed method extracts the complementary features of near-infrared and visible-light images and improves the robustness of unconstrained face recognition.

Time-frequency Features for Impedance Cardiography Signals During Anesthesia Using Different Distribution Kernels.

PubMed

Muñoz, Jesús Escrivá; Gambús, Pedro; Jensen, Erik W; Vallverdú, Montserrat

2018-01-01

This works investigates the time-frequency content of impedance cardiography signals during a propofol-remifentanil anesthesia. In the last years, impedance cardiography (ICG) is a technique which has gained much attention. However, ICG signals need further investigation. Time-Frequency Distributions (TFDs) with 5 different kernels are used in order to analyze impedance cardiography signals (ICG) before the start of the anesthesia and after the loss of consciousness. In total, ICG signals from one hundred and thirty-one consecutive patients undergoing major surgery under general anesthesia were analyzed. Several features were extracted from the calculated TFDs in order to characterize the time-frequency content of the ICG signals. Differences between those features before and after the loss of consciousness were studied. The Extended Modified Beta Distribution (EMBD) was the kernel for which most features shows statistically significant changes between before and after the loss of consciousness. Among all analyzed features, those based on entropy showed a sensibility, specificity and area under the curve of the receiver operating characteristic above 60%. The anesthetic state of the patient is reflected on linear and non-linear features extracted from the TFDs of the ICG signals. Especially, the EMBD is a suitable kernel for the analysis of ICG signals and offers a great range of features which change according to the patient's anesthesia state in a statistically significant way. Schattauer GmbH.

Application of lifting wavelet and random forest in compound fault diagnosis of gearbox

NASA Astrophysics Data System (ADS)

Chen, Tang; Cui, Yulian; Feng, Fuzhou; Wu, Chunzhi

2018-03-01

Aiming at the weakness of compound fault characteristic signals of a gearbox of an armored vehicle and difficult to identify fault types, a fault diagnosis method based on lifting wavelet and random forest is proposed. First of all, this method uses the lifting wavelet transform to decompose the original vibration signal in multi-layers, reconstructs the multi-layer low-frequency and high-frequency components obtained by the decomposition to get multiple component signals. Then the time-domain feature parameters are obtained for each component signal to form multiple feature vectors, which is input into the random forest pattern recognition classifier to determine the compound fault type. Finally, a variety of compound fault data of the gearbox fault analog test platform are verified, the results show that the recognition accuracy of the fault diagnosis method combined with the lifting wavelet and the random forest is up to 99.99%.

High-frequency shear Alfven instability driven by circulating energetic ions in NSTX

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

Kolesnichenko, Ya. I.; White, R. B.; Yakovenko, Yu. V.

2006-12-15

It is shown that a number of features of an instability with the frequency comparable to the ion gyrofrequency observed in the National Spherical Torus Experiment [E. D. Fredrickson et al., 'Observation of hole-clump pair generation by global or compressional Alfven eigenmodes', Contributed Papers, 33rd European Physical Society Conference on Plasma Physics, Rome, 2006, Europhysics Conference Abstracts (European Physical Society, Petit-Lancy, 2006), Report P5.058 (unpublished)] is consistent with the features of the Alfven instability with large, about the inverse, Larmor radius of the energetic ions ({rho}{sub b}{sup -1}) longitudinal wavenumbers. The conclusions drawn are based on an analysis of themore » resonant interaction of the energetic circulating ions and the waves, as well as on the calculation of the instability growth rate taking into account effects of the finite Larmor radius, {rho}{sub b}.« less

Fermi arc plasmons in Weyl semimetals

NASA Astrophysics Data System (ADS)

Song, Justin C. W.; Rudner, Mark S.

2017-11-01

In the recently discovered Weyl semimetals, the Fermi surface may feature disjoint, open segments—the so-called Fermi arcs—associated with topological states bound to exposed crystal surfaces. Here we show that the collective dynamics of electrons near such surfaces sharply departs from that of a conventional three-dimensional metal. In magnetic systems with broken time reversal symmetry, the resulting Fermi arc plasmons (FAPs) are chiral, with dispersion relations featuring open, hyperbolic constant frequency contours. As a result, a large range of surface plasmon wave vectors can be supported at a given frequency, with corresponding group velocity vectors directed along a few specific collimated directions. Fermi arc plasmons can be probed using near-field photonics techniques, which may be used to launch highly directional, focused surface plasmon beams. The unusual characteristics of FAPs arise from the interplay of bulk and surface Fermi arc carrier dynamics and give a window into the unusual fermiology of Weyl semimetals.

Electron Scattering by High-Frequency Whistler Waves at Earth's Bow Shock

NASA Technical Reports Server (NTRS)

Oka, M.; Wilson, L. B., III; Phan, T. D.; Hull, A. J.; Amano, T.; Hoshino, M.; Argall, M. R.; Le Contel, O.; Agapitov, O.; Gersham, D. J.;

Electron Scattering by High-frequency Whistler Waves at Earth’s Bow Shock

NASA Astrophysics Data System (ADS)

Oka, M.; Wilson, L. B., III; Phan, T. D.; Hull, A. J.; Amano, T.; Hoshino, M.; Argall, M. R.; Le Contel, O.; Agapitov, O.; Gershman, D. J.; Khotyaintsev, Y. V.; Burch, J. L.; Torbert, R. B.; Pollock, C.; Dorelli, J. C.; Giles, B. L.; Moore, T. E.; Saito, Y.; Avanov, L. A.; Paterson, W.; Ergun, R. E.; Strangeway, R. J.; Russell, C. T.; Lindqvist, P. A.

2017-06-01

Electrons are accelerated to non-thermal energies at shocks in space and astrophysical environments. While different mechanisms of electron acceleration have been proposed, it remains unclear how non-thermal electrons are produced out of the thermal plasma pool. Here, we report in situ evidence of pitch-angle scattering of non-thermal electrons by whistler waves at Earth’s bow shock. On 2015 November 4, the Magnetospheric Multiscale (MMS) mission crossed the bow shock with an Alfvén Mach number ˜11 and a shock angle ˜84°. In the ramp and overshoot regions, MMS revealed bursty enhancements of non-thermal (0.5-2 keV) electron flux, correlated with high-frequency (0.2-0.4 {{{Ω }}}{ce}, where {{{Ω }}}{ce} is the cyclotron frequency) parallel-propagating whistler waves. The electron velocity distribution (measured at 30 ms cadence) showed an enhanced gradient of phase-space density at and around the region where the electron velocity component parallel to the magnetic field matched the resonant energy inferred from the wave frequency range. The flux of 0.5 keV electrons (measured at 1 ms cadence) showed fluctuations with the same frequency. These features indicate that non-thermal electrons were pitch-angle scattered by cyclotron resonance with the high-frequency whistler waves. However, the precise role of the pitch-angle scattering by the higher-frequency whistler waves and possible nonlinear effects in the electron acceleration process remains unclear.

SHORT-TERM SOLAR FLARE PREDICTION USING MULTIRESOLUTION PREDICTORS

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

Yu Daren; Huang Xin; Hu Qinghua

2010-01-20

Multiresolution predictors of solar flares are constructed by a wavelet transform and sequential feature extraction method. Three predictors-the maximum horizontal gradient, the length of neutral line, and the number of singular points-are extracted from Solar and Heliospheric Observatory/Michelson Doppler Imager longitudinal magnetograms. A maximal overlap discrete wavelet transform is used to decompose the sequence of predictors into four frequency bands. In each band, four sequential features-the maximum, the mean, the standard deviation, and the root mean square-are extracted. The multiresolution predictors in the low-frequency band reflect trends in the evolution of newly emerging fluxes. The multiresolution predictors in the high-frequencymore » band reflect the changing rates in emerging flux regions. The variation of emerging fluxes is decoupled by wavelet transform in different frequency bands. The information amount of these multiresolution predictors is evaluated by the information gain ratio. It is found that the multiresolution predictors in the lowest and highest frequency bands contain the most information. Based on these predictors, a C4.5 decision tree algorithm is used to build the short-term solar flare prediction model. It is found that the performance of the short-term solar flare prediction model based on the multiresolution predictors is greatly improved.« less

Bearing fault diagnosis using a whale optimization algorithm-optimized orthogonal matching pursuit with a combined time-frequency atom dictionary

NASA Astrophysics Data System (ADS)

Zhang, Xin; Liu, Zhiwen; Miao, Qiang; Wang, Lei

2018-07-01

Condition monitoring and fault diagnosis of rolling element bearings are significant to guarantee the reliability and functionality of a mechanical system, production efficiency, and plant safety. However, this is almost invariably a formidable challenge because the fault features are often buried by strong background noises and other unstable interference components. To satisfactorily extract the bearing fault features, a whale optimization algorithm (WOA)-optimized orthogonal matching pursuit (OMP) with a combined time-frequency atom dictionary is proposed in this paper. Firstly, a combined time-frequency atom dictionary whose atom is a combination of Fourier dictionary atom and impact time-frequency dictionary atom is designed according to the properties of bearing fault vibration signal. Furthermore, to improve the efficiency and accuracy of signal sparse representation, the WOA is introduced into the OMP algorithm to optimize the atom parameters for best approximating the original signal with the dictionary atoms. The proposed method is validated through analyzing the bearing fault simulation signal and the real vibration signals collected from an experimental bearing and a wheelset bearing of high-speed trains. The comparisons with the respect to the state of the art in the field are illustrated in detail, which highlight the advantages of the proposed method.

Oriented modulation for watermarking in direct binary search halftone images.

PubMed

Guo, Jing-Ming; Su, Chang-Cheng; Liu, Yun-Fu; Lee, Hua; Lee, Jiann-Der

2012-09-01

In this paper, a halftoning-based watermarking method is presented. This method enables high pixel-depth watermark embedding, while maintaining high image quality. This technique is capable of embedding watermarks with pixel depths up to 3 bits without causing prominent degradation to the image quality. To achieve high image quality, the parallel oriented high-efficient direct binary search (DBS) halftoning is selected to be integrated with the proposed orientation modulation (OM) method. The OM method utilizes different halftone texture orientations to carry different watermark data. In the decoder, the least-mean-square-trained filters are applied for feature extraction from watermarked images in the frequency domain, and the naïve Bayes classifier is used to analyze the extracted features and ultimately to decode the watermark data. Experimental results show that the DBS-based OM encoding method maintains a high degree of image quality and realizes the processing efficiency and robustness to be adapted in printing applications.

Topside enhancements of the ionline in response to high-power HF-radio wave pumping at high latitudes

NASA Astrophysics Data System (ADS)

Rexer, Theresa; Gustavsson, Björn; Grydeland, Tom; Rietveld, Mike; Leyser, Thomas; Brändström, Urban; Sergienko, Tima

2017-04-01

A high power, high frequency heating experiment of the polar ionosphere was conducted in Tromsø, Norway in March 2016. The wave-plasma interactions were observed with the European Incoherent SCATer UHF radar co-located with the heating facility. HF pulses in a 3 minute ON 3 minute OFF cycles were transmitted, sweeping frequencies in 10 and 20 kHz steps from just below to just above the 3rd and 4th multiples of the F-region gyro-frequency. Several interesting features have been found in the radar measurements of the backscatter from the heated plasma. In agreement with current theory we observed an enhanced ionline near the HF reflection height on the bottom-side of the F layer. Simultaneously, a less intense, but clearly visible, ionline enhancement was observed approximately 100 km above this bottom-side enhancement for several 3 minute sweep pulses. We present the observations and discuss the top-side enhanced ion-line in relation to Z and L-mode propagation through the F-region peak.

High-resolution, anthropomorphic, computational breast phantom: fusion of rule-based structures with patient-based anatomy

NASA Astrophysics Data System (ADS)

Chen, Xinyuan; Gong, Xiaolin; Graff, Christian G.; Santana, Maira; Sturgeon, Gregory M.; Sauer, Thomas J.; Zeng, Rongping; Glick, Stephen J.; Lo, Joseph Y.

2017-03-01

While patient-based breast phantoms are realistic, they are limited by low resolution due to the image acquisition and segmentation process. The purpose of this study is to restore the high frequency components for the patient-based phantoms by adding power law noise (PLN) and breast structures generated based on mathematical models. First, 3D radial symmetric PLN with β=3 was added at the boundary between adipose and glandular tissue to connect broken tissue and create a high frequency contour of the glandular tissue. Next, selected high-frequency features from the FDA rule-based computational phantom (Cooper's ligaments, ductal network, and blood vessels) were fused into the phantom. The effects of enhancement in this study were demonstrated by 2D mammography projections and digital breast tomosynthesis (DBT) reconstruction volumes. The addition of PLN and rule-based models leads to a continuous decrease in β. The new β is 2.76, which is similar to what typically found for reconstructed DBT volumes. The new combined breast phantoms retain the realism from segmentation and gain higher resolution after restoration.

Characteristics of cloud occurrence using ceilometer measurements and its relationship to precipitation over Seoul

NASA Astrophysics Data System (ADS)

Lee, Sanghee; Hwang, Seung-On; Kim, Jhoon; Ahn, Myoung-Hwan

2018-03-01

Clouds are an important component of the atmosphere that affects both climate and weather, however, their contributions can be very difficult to determine. Ceilometer measurements can provide high resolution information on atmospheric conditions such as cloud base height (CBH) and vertical frequency of cloud occurrence (CVF). This study presents the first comprehensive analysis of CBH and CVF derived using Vaisala CL51 ceilometers at two urban stations in Seoul, Korea, during a three-year period from January 2014 to December 2016. The average frequency of cloud occurrence detected by the ceilometers is 54.3%. It is found that the CL51 is better able to capture CBH as compared to another ceilometer CL31 at a nearby meteorological station because it could detect high clouds more accurately. Frequency distributions for CBH up to 13,000 m providing detailed vertical features with 500-m interval show 55% of CBHs below 2 km for aggregated CBHs. A bimodal frequency distribution was observed for three-layers CBHs. A monthly variation of CVF reveals that frequency concentration of lower clouds is found in summer and winter, and higher clouds more often detected in spring and autumn. Monthly distribution features of cloud occurrence and precipitation are depending on seasons and it might be easy to define their relationship due to higher degree of variability of precipitation than cloud occurrence. However, a fluctuation of cloud occurrence frequency in summer is similar to precipitation in trend, whereas clouds in winter are relatively frequent but precipitation is not accompanied. In addition, recent decrease of summer precipitation could be mostly explained by a decrease of cloud occurrence. Anomalous precipitation recorded sometimes is considerably related to corresponding cloud occurrence. The diurnal and daily variations of CBH and CVF from ceilometer observations and the analysis of microwave radiometer measurements for two typical cloudiness cases are also reviewed in parallel. This analysis in finer temporal scale exhibits that utilization of ground-based observations together could help to analyze the cloud behaviors.

Experimental test of contemporary mathematical models of visual letter recognition.

PubMed

Townsend, J T; Ashby, F G

1982-12-01

A letter confusion experiment that used brief durations manipulated payoffs across the four stimulus letters, which were composed of line segments equal in length. The observers were required to report the features they perceived as well as to give a letter response. The early feature-sampling process is separated from the later letter-decision process in the substantive feature models, and predictions are thus obtained for the frequencies of feature report as well as letter report. Four substantive visual feature-processing models are developed and tested against one another and against three models of a more descriptive nature. The substantive models predict the decisional letter report phase much better than they do the feature-sampling phase, but the best overall 4 X 4 letter confusion matrix fits are obtained with one of the descriptive models, the similarity choice model. The present and other recent results suggest that the assumption that features are sampled in a stochastically independent manner may not be generally valid. The traditional high-threshold conceptualization of feature sampling is also falsified by the frequent reporting by observers of features not contained in the stimulus letter.

Synthesis of laughter by modifying excitation characteristics.

PubMed

Thati, Sathya Adithya; Kumar K, Sudheer; Yegnanarayana, B

2013-05-01

In this paper, a method to synthesize laughter by modifying the excitation source information is presented. The excitation source information is derived by extracting epoch locations and instantaneous fundamental frequency using zero frequency filtering approach. The zero frequency filtering approach is modified to capture the rapidly varying instantaneous fundamental frequency in natural laugh signals. The nature of variation of excitation features in natural laughter is examined to determine the features to be incorporated in the synthesis of a laugh signal. Features such as pitch period and strength of excitation are modified in the utterance of vowel /a/ or /i/ to generate the laughter signal. Frication is also incorporated wherever appropriate. Laugh signal is generated by varying parameters at both call level and bout level. Experiments are conducted to determine the significance of different features in the perception of laughter. Subjective evaluation is performed to determine the level of acceptance and quality of synthesis of the synthesized laughter signal for different choices of parameter values and for different input types.

Advanced GPR imaging of sedimentary features: integrated attribute analysis applied to sand dunes

NASA Astrophysics Data System (ADS)

Zhao, Wenke; Forte, Emanuele; Fontolan, Giorgio; Pipan, Michele

2018-04-01

We evaluate the applicability and the effectiveness of integrated GPR attribute analysis to image the internal sedimentary features of the Piscinas Dunes, SW Sardinia, Italy. The main objective is to explore the limits of GPR techniques to study sediment-bodies geometry and to provide a non-invasive high-resolution characterization of the different subsurface domains of dune architecture. On such purpose, we exploit the high-quality Piscinas data-set to extract and test different attributes of the GPR trace. Composite displays of multi-attributes related to amplitude, frequency, similarity and textural features are displayed with overlays and RGB mixed models. A multi-attribute comparative analysis is used to characterize different radar facies to better understand the characteristics of internal reflection patterns. The results demonstrate that the proposed integrated GPR attribute analysis can provide enhanced information about the spatial distribution of sediment bodies, allowing an enhanced and more constrained data interpretation.

20-nm enhancement-mode metamorphic GaAs HEMT with highly doped InGaAs source/drain regions for high-frequency applications

NASA Astrophysics Data System (ADS)

Ajayan, J.; Nirmal, D.

2017-03-01

In this article, the DC and RF performance of a SiN passivated 20-nm gate length metamorphic high electron mobility transistor (MHEMT) on GaAs substrate with highly doped InGaAs source/drain (S/D) regions have investigated using the Synopsys TCAD tool. The 20-nm enhancement-mode (E-mode) MHEMT device also features δ-doped sheets on either side of the In0.53Ga0.47As/InAs/In0.53Ga0.47As channel which exhibits a transconductance of 3100 mS/mm, cut-off frequency (fT) of 740 GHz and a maximum oscillation frequency (fmax) of 1040 GHz. The threshold voltage of the device is found to be 0.07 V. The room temperature Hall mobilities of the 2-dimensional sheet charge density are measured to be over 12,600 cm2/Vs with a sheet charge density larger than 3.6 × 1012 cm-2. These high-performance E-mode MHEMTs are attractive candidates for sub-millimetre wave applications such as high-resolution radars for space research, remote atmospheric sensing, imaging systems and also for low noise wide bandwidth amplifier for future communication systems.

a Comparative Analysis of Fluent and Cerebral Palsied Speech.

NASA Astrophysics Data System (ADS)

van Doorn, Janis Lee

Several features of the acoustic waveforms of fluent and cerebral palsied speech were compared, using six fluent and seven cerebral palsied subjects, with a major emphasis being placed on an investigation of the trajectories of the first three formants (vocal tract resonances). To provide an overall picture which included other acoustic features, fundamental frequency, intensity, speech timing (speech rate and syllable duration), and prevocalization (vocalization prior to initial stop consonants found in cerebral palsied speech) were also investigated. Measurements were made using repetitions of a test sentence which was chosen because it required large excursions of the speech articulators (lips, tongue and jaw), so that differences in the formant trajectories for the fluent and cerebral palsied speakers would be emphasized. The acoustic features were all extracted from the digitized speech waveform (10 kHz sampling rate): the fundamental frequency contours were derived manually, the intensity contours were measured using the signal covariance, speech rate and syllable durations were measured manually, as were the prevocalization durations, while the formant trajectories were derived from short time spectra which were calculated for each 10 ms of speech using linear prediction analysis. Differences which were found in the acoustic features can be summarized as follows. For cerebral palsied speakers, the fundamental frequency contours generally showed inappropriate exaggerated fluctuations, as did some of the intensity contours; the mean fundamental frequencies were either higher or the same as for the fluent subjects; speech rates were reduced, and syllable durations were longer; prevocalization was consistently present at the beginning of the test sentence; formant trajectories were found to have overall reduced frequency ranges, and to contain anomalous transitional features, but it is noteworthy that for any one cerebral palsied subject, the inappropriate trajectory pattern was generally reproducible. The anomalous transitional features took the form of (a) inappropriate transition patterns, (b) reduced frequency excursions, (c) increased transition durations, and (d) decreased maximum rates of frequency change.

A support vector machine approach for classification of welding defects from ultrasonic signals

NASA Astrophysics Data System (ADS)

Chen, Yuan; Ma, Hong-Wei; Zhang, Guang-Ming

2014-07-01

Defect classification is an important issue in ultrasonic non-destructive evaluation. A layered multi-class support vector machine (LMSVM) classification system, which combines multiple SVM classifiers through a layered architecture, is proposed in this paper. The proposed LMSVM classification system is applied to the classification of welding defects from ultrasonic test signals. The measured ultrasonic defect echo signals are first decomposed into wavelet coefficients by the wavelet packet transform. The energy of the wavelet coefficients at different frequency channels are used to construct the feature vectors. The bees algorithm (BA) is then used for feature selection and SVM parameter optimisation for the LMSVM classification system. The BA-based feature selection optimises the energy feature vectors. The optimised feature vectors are input to the LMSVM classification system for training and testing. Experimental results of classifying welding defects demonstrate that the proposed technique is highly robust, precise and reliable for ultrasonic defect classification.

Book reviews in medical journals.

PubMed Central

Kroenke, K

1986-01-01

In a study of book reviews published in four general medical journals over a six-month period, 480 reviews were analyzed. Twenty-five features that reviewers address when evaluating a text were identified, and the frequency of commentary for each feature was determined. The mean number of features addressed per review was 9.0. Reviews averaged 389 words, but review length did not correlate with the length or scope of the book, with the number of features addressed, nor with the reviewer's assessment of the text. Extraneous commentary by the reviewer occurred in 16% of the reviews. This editorializing appeared in lengthier reviews that addressed fewer features. Favorable reviews were far more common than unfavorable ones (88.5% vs. 11.5%). Consequently, for the fifty-five books reviewed in more than one journal, agreement regarding rating of the text was high (86%). Results of this study may provide useful guidelines for reviewers of medical texts. PMID:3947772

A hybrid feature selection approach for the early diagnosis of Alzheimer’s disease

NASA Astrophysics Data System (ADS)

Gallego-Jutglà, Esteve; Solé-Casals, Jordi; Vialatte, François-Benoît; Elgendi, Mohamed; Cichocki, Andrzej; Dauwels, Justin

2015-02-01

Objective. Recently, significant advances have been made in the early diagnosis of Alzheimer’s disease (AD) from electroencephalography (EEG). However, choosing suitable measures is a challenging task. Among other measures, frequency relative power (RP) and loss of complexity have been used with promising results. In the present study we investigate the early diagnosis of AD using synchrony measures and frequency RP on EEG signals, examining the changes found in different frequency ranges. Approach. We first explore the use of a single feature for computing the classification rate (CR), looking for the best frequency range. Then, we present a multiple feature classification system that outperforms all previous results using a feature selection strategy. These two approaches are tested in two different databases, one containing mild cognitive impairment (MCI) and healthy subjects (patients age: 71.9 ± 10.2, healthy subjects age: 71.7 ± 8.3), and the other containing Mild AD and healthy subjects (patients age: 77.6 ± 10.0 healthy subjects age: 69.4 ± 11.5). Main results. Using a single feature to compute CRs we achieve a performance of 78.33% for the MCI data set and of 97.56% for Mild AD. Results are clearly improved using the multiple feature classification, where a CR of 95% is found for the MCI data set using 11 features, and 100% for the Mild AD data set using four features. Significance. The new features selection method described in this work may be a reliable tool that could help to design a realistic system that does not require prior knowledge of a patient's status. With that aim, we explore the standardization of features for MCI and Mild AD data sets with promising results.

Basic data features and results from a spatially dense seismic array on the San Jacinto fault zone

NASA Astrophysics Data System (ADS)

Ben-Zion, Yehuda; Vernon, Frank L.; Ozakin, Yaman; Zigone, Dimitri; Ross, Zachary E.; Meng, Haoran; White, Malcolm; Reyes, Juan; Hollis, Dan; Barklage, Mitchell

2015-07-01

We discuss several outstanding aspects of seismograms recorded during >4 weeks by a spatially dense Nodal array, straddling the damage zone of the San Jacinto fault in southern California, and some example results. The waveforms contain numerous spikes and bursts of high-frequency waves (up to the recorded 200 Hz) produced in part by minute failure events in the shallow crust. The high spatial density of the array facilitates the detection of 120 small local earthquakes in a single day, most of which not detected by the surrounding ANZA and regional southern California networks. Beamforming results identify likely ongoing cultural noise sources dominant in the frequency range 1-10 Hz and likely ongoing earthquake sources dominant in the frequency range 20-40 Hz. Matched-field processing and back-projection of seismograms provide alternate event location. The median noise levels during the experiment at different stations, waves generated by Betsy gunshots, and wavefields from nearby earthquakes point consistently to several structural units across the fault. Seismic trapping structure and local sedimentary basin produce localized motion amplification and stronger attenuation than adjacent regions. Cross correlations of high-frequency noise recorded at closely spaced stations provide a structural image of the subsurface material across the fault zone. The high spatial density and broad frequency range of the data can be used for additional high resolution studies of structure and source properties in the shallow crust.

Temporal Characteristics of High-Frequency Lower-Limb Oscillation during Freezing of Gait in Parkinson's Disease

PubMed Central

Yungher, Don A.; Morris, Tiffany R.; Dilda, Valentina; Shine, James M.; Naismith, Sharon L.; Lewis, Simon J. G.; Moore, Steven T.

2014-01-01

A cardinal feature of freezing of gait (FOG) is high frequency (3–8 Hz) oscillation of the legs, and this study aimed to quantify the temporal pattern of lower-body motion prior to and during FOG. Acceleration data was obtained from sensors attached to the back, thighs, shanks, and feet in 14 Parkinson's disease patients performing timed-up-and-go tasks, and clinical assessment of FOG was performed by two experienced raters from video. A total of 23 isolated FOG events, defined as occurring at least 5 s after gait initiation and with no preceding FOG, were identified from the clinical ratings. The corresponding accelerometer records were analyzed within a 4 s window centered at the clinical onset of freezing. FOG-related high-frequency oscillation (an increase in power in the 3–8 Hz band >3 SD from baseline) followed a distal to proximal onset pattern, appearing at the feet, shanks, thighs, and then back over a period of 250 ms. Peak power tended to decrease as the focus of oscillation moved from feet to back. There was a consistent delay (mean 872 ms) between the onset of high frequency oscillation at the feet and clinical onset of FOG. We infer that FOG is characterized by high frequency oscillation at the feet, which progresses proximally and is mechanically damped at the torso. PMID:25101189

Differences in clinical characteristics and frequency of accompanying migraine features in episodic and chronic cluster headache.

PubMed

Gaul, C; Christmann, N; Schröder, D; Weber, R; Shanib, H; Diener, H C; Holle, D

2012-05-01

Data on clinical differences between episodic (eCH) and chronic cluster headache (cCH) and accompanying migraine features are limited. History and clinical features of 209 consecutive cluster headache patients (144 eCH, 65 cCH; male:female ratio 3.4 : 1) were obtained in a tertiary headache centre by face-to-face interviews. Relationship between occurrence of accompanying symptoms, pain intensity, comorbid migraine, and circannual and circadian rhythmicity was analysed. 99.5% of patients reported a minimum of one ipsilateral cranial autonomic symptom (CAS); 80% showed at least three CAS. A seasonal rhythmicity was observed in both eCH and cCH. A comorbid headache disorder occurred in 25%. No significant difference was detected between patients with comorbid migraine and without regarding occurrence of phonophobia, photophobia or nausea during cluster attacks. Patients with comorbid migraine reported allodynia significantly (p = 0.022) more often during cluster attacks than patients without comorbid migraine. Occurrence of CAS and attack frequency, as well as periodic patterns of attacks, are relatively uniform in eCH and cCH. Multiple CAS are not related to pain intensity. Allodynia during cluster attacks is a frequent symptom. The unexpectedly high rate of accompanying migrainous features during cluster attacks cannot be explained by comorbid migraine.

Real-time machine vision system using FPGA and soft-core processor

NASA Astrophysics Data System (ADS)

Malik, Abdul Waheed; Thörnberg, Benny; Meng, Xiaozhou; Imran, Muhammad

2012-06-01

This paper presents a machine vision system for real-time computation of distance and angle of a camera from reference points in the environment. Image pre-processing, component labeling and feature extraction modules were modeled at Register Transfer (RT) level and synthesized for implementation on field programmable gate arrays (FPGA). The extracted image component features were sent from the hardware modules to a soft-core processor, MicroBlaze, for computation of distance and angle. A CMOS imaging sensor operating at a clock frequency of 27MHz was used in our experiments to produce a video stream at the rate of 75 frames per second. Image component labeling and feature extraction modules were running in parallel having a total latency of 13ms. The MicroBlaze was interfaced with the component labeling and feature extraction modules through Fast Simplex Link (FSL). The latency for computing distance and angle of camera from the reference points was measured to be 2ms on the MicroBlaze, running at 100 MHz clock frequency. In this paper, we present the performance analysis, device utilization and power consumption for the designed system. The FPGA based machine vision system that we propose has high frame speed, low latency and a power consumption that is much lower compared to commercially available smart camera solutions.

Reflectance spectrum of plasmon waveguide interband cascade lasers and observation of the Berreman effect

NASA Astrophysics Data System (ADS)

Hinkey, Robert T.; Tian, Zhaobing; Yang, Rui Q.; Mishima, Tetsuya D.; Santos, Michael B.

2011-08-01

Noninvasive infrared reflectance measurements have been explored as a method for studying the optical properties of Si-doped cladding layers of plasmon waveguide interband cascade lasers. Measurements and theoretical simulations of the reflectance spectra were carried out on both the laser structures themselves, as well as highly doped InAs films grown on GaAs substrates. We have found that there is a sharp drop in the signal of the reflectance spectrum for p-polarized light oscillating near the plasma frequency. This is a manifestation of the so-called Berreman effect, which occurs at frequencies where the dielectric function approaches zero. This is distinct from the plasma edge feature seen in the reflectance spectrum of thick samples. The plasma frequencies of the highly doped layers were obtained by identifying the Berreman feature in the measured spectrum and fitting the spectrum to a modeled curve. Using a model for the effective mass, we were able to obtain measurements of the conduction electron concentration (in a range from 1018 to 1019 cm-3) in the waveguide cladding layers with values that were in good agreement with those found using Hall effect and SIMS measurements. The reflectance data was effectively used to achieve better calibration of the Si-doping during the growth of the n++-type InAs layers in the plasmon waveguide laser structures.

Separation of Intercepted Multi-Radar Signals Based on Parameterized Time-Frequency Analysis

NASA Astrophysics Data System (ADS)

Lu, W. L.; Xie, J. W.; Wang, H. M.; Sheng, C.

2016-09-01

Modern radars use complex waveforms to obtain high detection performance and low probabilities of interception and identification. Signals intercepted from multiple radars overlap considerably in both the time and frequency domains and are difficult to separate with primary time parameters. Time-frequency analysis (TFA), as a key signal-processing tool, can provide better insight into the signal than conventional methods. In particular, among the various types of TFA, parameterized time-frequency analysis (PTFA) has shown great potential to investigate the time-frequency features of such non-stationary signals. In this paper, we propose a procedure for PTFA to separate overlapped radar signals; it includes five steps: initiation, parameterized time-frequency analysis, demodulating the signal of interest, adaptive filtering and recovering the signal. The effectiveness of the method was verified with simulated data and an intercepted radar signal received in a microwave laboratory. The results show that the proposed method has good performance and has potential in electronic reconnaissance applications, such as electronic intelligence, electronic warfare support measures, and radar warning.

Reconfigurable radio-frequency arbitrary waveforms synthesized in a silicon photonic chip.

PubMed

Wang, Jian; Shen, Hao; Fan, Li; Wu, Rui; Niu, Ben; Varghese, Leo T; Xuan, Yi; Leaird, Daniel E; Wang, Xi; Gan, Fuwan; Weiner, Andrew M; Qi, Minghao

2015-01-12

Photonic methods of radio-frequency waveform generation and processing can provide performance advantages and flexibility over electronic methods due to the ultrawide bandwidth offered by the optical carriers. However, bulk optics implementations suffer from the lack of integration and slow reconfiguration speed. Here we propose an architecture of integrated photonic radio-frequency generation and processing and implement it on a silicon chip fabricated in a semiconductor manufacturing foundry. Our device can generate programmable radio-frequency bursts or continuous waveforms with only the light source, electrical drives/controls and detectors being off-chip. It modulates an individual pulse in a radio-frequency burst within 4 ns, achieving a reconfiguration speed three orders of magnitude faster than thermal tuning. The on-chip optical delay elements offer an integrated approach to accurately manipulating individual radio-frequency waveform features without constraints set by the speed and timing jitter of electronics, and should find applications ranging from high-speed wireless to defence electronics.

Reconfigurable radio-frequency arbitrary waveforms synthesized in a silicon photonic chip

PubMed Central

Wang, Jian; Shen, Hao; Fan, Li; Wu, Rui; Niu, Ben; Varghese, Leo T.; Xuan, Yi; Leaird, Daniel E.; Wang, Xi; Gan, Fuwan; Weiner, Andrew M.; Qi, Minghao

2015-01-01

Photonic methods of radio-frequency waveform generation and processing can provide performance advantages and flexibility over electronic methods due to the ultrawide bandwidth offered by the optical carriers. However, bulk optics implementations suffer from the lack of integration and slow reconfiguration speed. Here we propose an architecture of integrated photonic radio-frequency generation and processing and implement it on a silicon chip fabricated in a semiconductor manufacturing foundry. Our device can generate programmable radio-frequency bursts or continuous waveforms with only the light source, electrical drives/controls and detectors being off-chip. It modulates an individual pulse in a radio-frequency burst within 4 ns, achieving a reconfiguration speed three orders of magnitude faster than thermal tuning. The on-chip optical delay elements offer an integrated approach to accurately manipulating individual radio-frequency waveform features without constraints set by the speed and timing jitter of electronics, and should find applications ranging from high-speed wireless to defence electronics. PMID:25581847

Evaluation of Feature Extraction and Recognition for Activity Monitoring and Fall Detection Based on Wearable sEMG Sensors.

PubMed

Xi, Xugang; Tang, Minyan; Miran, Seyed M; Luo, Zhizeng

2017-05-27

As an essential subfield of context awareness, activity awareness, especially daily activity monitoring and fall detection, plays a significant role for elderly or frail people who need assistance in their daily activities. This study investigates the feature extraction and pattern recognition of surface electromyography (sEMG), with the purpose of determining the best features and classifiers of sEMG for daily living activities monitoring and fall detection. This is done by a serial of experiments. In the experiments, four channels of sEMG signal from wireless, wearable sensors located on lower limbs are recorded from three subjects while they perform seven activities of daily living (ADL). A simulated trip fall scenario is also considered with a custom-made device attached to the ankle. With this experimental setting, 15 feature extraction methods of sEMG, including time, frequency, time/frequency domain and entropy, are analyzed based on class separability and calculation complexity, and five classification methods, each with 15 features, are estimated with respect to the accuracy rate of recognition and calculation complexity for activity monitoring and fall detection. It is shown that a high accuracy rate of recognition and a minimal calculation time for daily activity monitoring and fall detection can be achieved in the current experimental setting. Specifically, the Wilson Amplitude (WAMP) feature performs the best, and the classifier Gaussian Kernel Support Vector Machine (GK-SVM) with Permutation Entropy (PE) or WAMP results in the highest accuracy for activity monitoring with recognition rates of 97.35% and 96.43%. For fall detection, the classifier Fuzzy Min-Max Neural Network (FMMNN) has the best sensitivity and specificity at the cost of the longest calculation time, while the classifier Gaussian Kernel Fisher Linear Discriminant Analysis (GK-FDA) with the feature WAMP guarantees a high sensitivity (98.70%) and specificity (98.59%) with a short calculation time (65.586 ms), making it a possible choice for pre-impact fall detection. The thorough quantitative comparison of the features and classifiers in this study supports the feasibility of a wireless, wearable sEMG sensor system for automatic activity monitoring and fall detection.

Evaluation of Feature Extraction and Recognition for Activity Monitoring and Fall Detection Based on Wearable sEMG Sensors

PubMed Central

Xi, Xugang; Tang, Minyan; Miran, Seyed M.; Luo, Zhizeng

2017-01-01

As an essential subfield of context awareness, activity awareness, especially daily activity monitoring and fall detection, plays a significant role for elderly or frail people who need assistance in their daily activities. This study investigates the feature extraction and pattern recognition of surface electromyography (sEMG), with the purpose of determining the best features and classifiers of sEMG for daily living activities monitoring and fall detection. This is done by a serial of experiments. In the experiments, four channels of sEMG signal from wireless, wearable sensors located on lower limbs are recorded from three subjects while they perform seven activities of daily living (ADL). A simulated trip fall scenario is also considered with a custom-made device attached to the ankle. With this experimental setting, 15 feature extraction methods of sEMG, including time, frequency, time/frequency domain and entropy, are analyzed based on class separability and calculation complexity, and five classification methods, each with 15 features, are estimated with respect to the accuracy rate of recognition and calculation complexity for activity monitoring and fall detection. It is shown that a high accuracy rate of recognition and a minimal calculation time for daily activity monitoring and fall detection can be achieved in the current experimental setting. Specifically, the Wilson Amplitude (WAMP) feature performs the best, and the classifier Gaussian Kernel Support Vector Machine (GK-SVM) with Permutation Entropy (PE) or WAMP results in the highest accuracy for activity monitoring with recognition rates of 97.35% and 96.43%. For fall detection, the classifier Fuzzy Min-Max Neural Network (FMMNN) has the best sensitivity and specificity at the cost of the longest calculation time, while the classifier Gaussian Kernel Fisher Linear Discriminant Analysis (GK-FDA) with the feature WAMP guarantees a high sensitivity (98.70%) and specificity (98.59%) with a short calculation time (65.586 ms), making it a possible choice for pre-impact fall detection. The thorough quantitative comparison of the features and classifiers in this study supports the feasibility of a wireless, wearable sEMG sensor system for automatic activity monitoring and fall detection. PMID:28555016

Contextual Interactions in Grating Plaid Configurations Are Explained by Natural Image Statistics and Neural Modeling

PubMed Central

Ernst, Udo A.; Schiffer, Alina; Persike, Malte; Meinhardt, Günter

2016-01-01

Processing natural scenes requires the visual system to integrate local features into global object descriptions. To achieve coherent representations, the human brain uses statistical dependencies to guide weighting of local feature conjunctions. Pairwise interactions among feature detectors in early visual areas may form the early substrate of these local feature bindings. To investigate local interaction structures in visual cortex, we combined psychophysical experiments with computational modeling and natural scene analysis. We first measured contrast thresholds for 2 × 2 grating patch arrangements (plaids), which differed in spatial frequency composition (low, high, or mixed), number of grating patch co-alignments (0, 1, or 2), and inter-patch distances (1° and 2° of visual angle). Contrast thresholds for the different configurations were compared to the prediction of probability summation (PS) among detector families tuned to the four retinal positions. For 1° distance the thresholds for all configurations were larger than predicted by PS, indicating inhibitory interactions. For 2° distance, thresholds were significantly lower compared to PS when the plaids were homogeneous in spatial frequency and orientation, but not when spatial frequencies were mixed or there was at least one misalignment. Next, we constructed a neural population model with horizontal laminar structure, which reproduced the detection thresholds after adaptation of connection weights. Consistent with prior work, contextual interactions were medium-range inhibition and long-range, orientation-specific excitation. However, inclusion of orientation-specific, inhibitory interactions between populations with different spatial frequency preferences were crucial for explaining detection thresholds. Finally, for all plaid configurations we computed their likelihood of occurrence in natural images. The likelihoods turned out to be inversely related to the detection thresholds obtained at larger inter-patch distances. However, likelihoods were almost independent of inter-patch distance, implying that natural image statistics could not explain the crowding-like results at short distances. This failure of natural image statistics to resolve the patch distance modulation of plaid visibility remains a challenge to the approach. PMID:27757076

Preattentive extraction of abstract feature conjunctions from auditory stimulation as reflected by the mismatch negativity (MMN).

PubMed

Paavilainen, P; Simola, J; Jaramillo, M; Näätänen, R; Winkler, I

2001-03-01

Brain mechanisms extracting invariant information from varying auditory inputs were studied using the mismatch-negativity (MMN) brain response. We wished to determine whether the preattentive sound-analysis mechanisms, reflected by MMN, are capable of extracting invariant relationships based on abstract conjunctions between two sound features. The standard stimuli varied over a large range in frequency and intensity dimensions following the rule that the higher the frequency, the louder the intensity. The occasional deviant stimuli violated this frequency-intensity relationship and elicited an MMN. The results demonstrate that preattentive processing of auditory stimuli extends to unexpectedly complex relationships between the stimulus features.

Ballistic missile precession frequency extraction by spectrogram's texture

NASA Astrophysics Data System (ADS)

Wu, Longlong; Xu, Shiyou; Li, Gang; Chen, Zengping

2013-10-01

In order to extract precession frequency, an crucial parameter in ballistic target recognition, which reflected the kinematical characteristics as well as structural and mass distribution features, we developed a dynamic RCS signal model for a conical ballistic missile warhead, with a log-norm multiplicative noise, substituting the familiar additive noise, derived formulas of micro-Doppler induced by precession motion, and analyzed time-varying micro-Doppler features utilizing time-frequency transforms, extracted precession frequency by measuring the spectrogram's texture, verified them by computer simulation studies. Simulation demonstrates the excellent performance of the method proposed in extracting the precession frequency, especially in the case of low SNR.

Stimulated Brillouin scattering during electron gyro-harmonic heating at EISCAT

NASA Astrophysics Data System (ADS)

Fu, H. Y.; Scales, W. A.; Bernhardt, P. A.; Briczinski, S. J.; Kosch, M. J.; Senior, A.; Rietveld, M. T.; Yeoman, T. K.; Ruohoniemi, J. M.

2015-08-01

Observations of secondary radiation, stimulated electromagnetic emission (SEE), produced during ionospheric modification experiments using ground-based, high-power, high-frequency (HF) radio waves are considered. The High Frequency Active Auroral Research Program (HAARP) facility is capable of generating narrowband SEE in the form of stimulated Brillouin scatter (SBS) and stimulated ion Bernstein scatter (SIBS) in the SEE spectrum. Such narrowband SEE spectral lines have not been reported using the European Incoherent Scatter (EISCAT) heater facility before. This work reports the first EISCAT results of narrowband SEE spectra and compares them to SEE previously observed at HAARP during electron gyro-harmonic heating. An analysis of experimental SEE data shows observations of emission lines within 100 Hz of the pump frequency, interpreted as SBS, during the 2012 July EISCAT campaign. Experimental results indicate that SBS strengthens as the pump frequency approaches the third electron gyro-harmonic. Also, for different heater antenna beam angles, the CUTLASS radar backscatter induced by HF radio pumping is suppressed near electron gyro-harmonics, whereas electron temperature enhancement weakens as measured by EISCAT/UHF radar. The main features of these new narrowband EISCAT observations are generally consistent with previous SBS measurements at HAARP.

Wedding ring shaped excitation coil

DOEpatents

MacLennan, Donald A.; Tsai, Peter

2001-01-01

A high frequency inductively coupled electrodeless lamp includes an excitation coil with an effective electrical length which is less than one half wavelength of a driving frequency applied thereto, preferably much less. The driving frequency may be greater than 100 MHz and is preferably as high as 915 MHz. Preferably, the excitation coil is configured as a non-helical, semi-cylindrical conductive surface having less than one turn, in the general shape of a wedding ring. At high frequencies, the current in the coil forms two loops which are spaced apart and parallel to each other. Configured appropriately, the coil approximates a Helmholtz configuration. The lamp preferably utilizes an bulb encased in a reflective ceramic cup with a pre-formed aperture defined therethrough. The ceramic cup may include structural features to aid in alignment and/or a flanged face to aid in thermal management. The lamp head is preferably an integrated lamp head comprising a metal matrix composite surrounding an insulating ceramic with the excitation integrally formed on the ceramic. A novel solid-state oscillator preferably provides RF power to the lamp. The oscillator is a single active element device capable of providing over 70 watts of power at over 70% efficiency.

CD5-expressing B-cell lymphomas/leukemias: relatively high frequency of CD5+ B-cell lymphomas with an overall poor prognosis in Nagasaki Japan.

PubMed

Kamihira, S; Hirakata, Y; Atogami, S; Sohda, H; Tsuruda, K; Yamada, Y; Tomonaga, M

1996-06-01

To characterize CD5+ B-cell neoplasms in Japan, where chronic lymphocytic leukemia (CLL) is rare and of different subtypes in comparison with Western countries, we collected 58 cases of CD5+ B-cell lymphomas/leukemias and analyzed their clinicopathologic features. According to the French-American-British (FAB) and standard histologic classification, the cases corresponded to small lymphocytic lymphoma (SLL, group I; n = 22, consisting of CLL, n = 10, CLL/PL, n = 3, and CLLmixed, n = 7); intermediate differentiated lymphoma/mantle cell lymphoma (IDL/MCL, group II, n = 18); and others with CD5-positive lymphomas (group III, n = 18). The CD5+ B-cell lymphomas showed morphologic and prognostic variability among the three groups. The clinical and immunophenotypic features were remarkably consistent in leukemic disease being seen in 73% of all cases, splenomegaly in 63%, and intense CD19, CD20, surface membrane immunogobulin M (SmIgM) or SmIgM and SmIgD, light-chain expression, and no CD10 expression. The median survival time of groups I, II, and III was 7.8, 3.3, and 0.8 years, respectively. These findings suggest that CD5 antigens may serve as valid markers for the prognosis and clinical features of B-cell lymphomas and that CD5+ B-cell lymphomas with an overall poor prognosis occurs at a relatively high frequency in Japan. This also suggests that a combination of immunophenotypic and morphologic features is of value for characterizing CD5+ B-cell neoplasms.

A statistical analysis of cervical auscultation signals from adults with unsafe airway protection.

PubMed

Dudik, Joshua M; Kurosu, Atsuko; Coyle, James L; Sejdić, Ervin

2016-01-22

Aspiration, where food or liquid is allowed to enter the larynx during a swallow, is recognized as the most clinically salient feature of oropharyngeal dysphagia. This event can lead to short-term harm via airway obstruction or more long-term effects such as pneumonia. In order to non-invasively identify this event using high resolution cervical auscultation there is a need to characterize cervical auscultation signals from subjects with dysphagia who aspirate. In this study, we collected swallowing sound and vibration data from 76 adults (50 men, 26 women, mean age 62) who underwent a routine videofluoroscopy swallowing examination. The analysis was limited to swallows of liquid with either thin (<5 cps) or viscous (≈300 cps) consistency and was divided into those with deep laryngeal penetration or aspiration (unsafe airway protection), and those with either shallow or no laryngeal penetration (safe airway protection), using a standardized scale. After calculating a selection of time, frequency, and time-frequency features for each swallow, the safe and unsafe categories were compared using Wilcoxon rank-sum statistical tests. Our analysis found that few of our chosen features varied in magnitude between safe and unsafe swallows with thin swallows demonstrating no statistical variation. We also supported our past findings with regard to the effects of sex and the presence or absence of stroke on cervical ausculation signals, but noticed certain discrepancies with regards to bolus viscosity. Overall, our results support the necessity of using multiple statistical features concurrently to identify laryngeal penetration of swallowed boluses in future work with high resolution cervical auscultation.

Transient features in nanosecond pulsed electric fields differentially modulate mitochondria and viability.

PubMed

Beebe, Stephen J; Chen, Yeong-Jer; Sain, Nova M; Schoenbach, Karl H; Xiao, Shu

2012-01-01

It is hypothesized that high frequency components of nanosecond pulsed electric fields (nsPEFs), determined by transient pulse features, are important for maximizing electric field interactions with intracellular structures. For monopolar square wave pulses, these transient features are determined by the rapid rise and fall of the pulsed electric fields. To determine effects on mitochondria membranes and plasma membranes, N1-S1 hepatocellular carcinoma cells were exposed to single 600 ns pulses with varying electric fields (0-80 kV/cm) and short (15 ns) or long (150 ns) rise and fall times. Plasma membrane effects were evaluated using Fluo-4 to determine calcium influx, the only measurable source of increases in intracellular calcium. Mitochondria membrane effects were evaluated using tetramethylrhodamine ethyl ester (TMRE) to determine mitochondria membrane potentials (ΔΨm). Single pulses with short rise and fall times caused electric field-dependent increases in calcium influx, dissipation of ΔΨm and cell death. Pulses with long rise and fall times exhibited electric field-dependent increases in calcium influx, but diminished effects on dissipation of ΔΨm and viability. Results indicate that high frequency components have significant differential impact on mitochondria membranes, which determines cell death, but lesser variances on plasma membranes, which allows calcium influxes, a primary determinant for dissipation of ΔΨm and cell death.

Project CONVERGE: Initial Results From the Mapping of Surface Currents in Palmer Deep

NASA Astrophysics Data System (ADS)

Statscewich, H.; Kohut, J. T.; Winsor, P.; Oliver, M. J.; Bernard, K. S.; Cimino, M. A.; Fraser, W.

2016-02-01

The Palmer Deep submarine canyon on the Western Antarctic Peninsula provides a conduit for upwelling of relatively warm, nutrient rich waters which enhance local primary production and support a food web productive enough to sustain a large top predator biomass. In an analysis of ten years of satellite-tagged penguins, Oliver et al. (2013) showed that circulation features associated with tidal flows may be a key driver of nearshore predator distributions. During diurnal tides, the penguins feed close to their breeding colonies and during semi-diurnal tides, the penguins make foraging trips to the more distant regions of Palmer Deep. It is hypothesized that convergent features act to concentrate primary producers and aggregate schools of krill that influence the behavior of predator species. The initial results from a six month deployment of a High Frequency Radar network in Palmer Deep are presented in an attempt to characterize and quantify convergent features. During a three month period from January through March 2015, we conducted in situ sampling consisting of multiple underwater glider deployments, small boat acoustic surveys of Antarctic krill, and penguin ARGOS-linked satellite telemetry and time-depth recorders (TDRs). The combination of real-time surface current maps with adaptive in situ sampling introduces High Frequency Radar to the Antarctic in a way that allows us to rigorously and efficiently test the influence of local tidal processes on top predator foraging ecology.

Prediction of Peptide and Protein Propensity for Amyloid Formation

PubMed Central

Família, Carlos; Dennison, Sarah R.; Quintas, Alexandre; Phoenix, David A.

2015-01-01

Understanding which peptides and proteins have the potential to undergo amyloid formation and what driving forces are responsible for amyloid-like fiber formation and stabilization remains limited. This is mainly because proteins that can undergo structural changes, which lead to amyloid formation, are quite diverse and share no obvious sequence or structural homology, despite the structural similarity found in the fibrils. To address these issues, a novel approach based on recursive feature selection and feed-forward neural networks was undertaken to identify key features highly correlated with the self-assembly problem. This approach allowed the identification of seven physicochemical and biochemical properties of the amino acids highly associated with the self-assembly of peptides and proteins into amyloid-like fibrils (normalized frequency of β-sheet, normalized frequency of β-sheet from LG, weights for β-sheet at the window position of 1, isoelectric point, atom-based hydrophobic moment, helix termination parameter at position j+1 and ΔG° values for peptides extrapolated in 0 M urea). Moreover, these features enabled the development of a new predictor (available at http://cran.r-project.org/web/packages/appnn/index.html) capable of accurately and reliably predicting the amyloidogenic propensity from the polypeptide sequence alone with a prediction accuracy of 84.9 % against an external validation dataset of sequences with experimental in vitro, evidence of amyloid formation. PMID:26241652

Spectral negentropy based sidebands and demodulation analysis for planet bearing fault diagnosis

NASA Astrophysics Data System (ADS)

Feng, Zhipeng; Ma, Haoqun; Zuo, Ming J.

2017-12-01

Planet bearing vibration signals are highly complex due to intricate kinematics (involving both revolution and spinning) and strong multiple modulations (including not only the fault induced amplitude modulation and frequency modulation, but also additional amplitude modulations due to load zone passing, time-varying vibration transfer path, and time-varying angle between the gear pair mesh lines of action and fault impact force vector), leading to difficulty in fault feature extraction. Rolling element bearing fault diagnosis essentially relies on detection of fault induced repetitive impulses carried by resonance vibration, but they are usually contaminated by noise and therefor are hard to be detected. This further adds complexity to planet bearing diagnostics. Spectral negentropy is able to reveal the frequency distribution of repetitive transients, thus providing an approach to identify the optimal frequency band of a filter for separating repetitive impulses. In this paper, we find the informative frequency band (including the center frequency and bandwidth) of bearing fault induced repetitive impulses using the spectral negentropy based infogram. In Fourier spectrum, we identify planet bearing faults according to sideband characteristics around the center frequency. For demodulation analysis, we filter out the sensitive component based on the informative frequency band revealed by the infogram. In amplitude demodulated spectrum (squared envelope spectrum) of the sensitive component, we diagnose planet bearing faults by matching the present peaks with the theoretical fault characteristic frequencies. We further decompose the sensitive component into mono-component intrinsic mode functions (IMFs) to estimate their instantaneous frequencies, and select a sensitive IMF with an instantaneous frequency fluctuating around the center frequency for frequency demodulation analysis. In the frequency demodulated spectrum (Fourier spectrum of instantaneous frequency) of selected IMF, we discern planet bearing fault reasons according to the present peaks. The proposed spectral negentropy infogram based spectrum and demodulation analysis method is illustrated via a numerical simulated signal analysis. Considering the unique load bearing feature of planet bearings, experimental validations under both no-load and loading conditions are done to verify the derived fault symptoms and the proposed method. The localized faults on outer race, rolling element and inner race are successfully diagnosed.

Can acoustic emission detect the initiation of fatigue cracks: Application to high-strength light alloys used in aeronautics

NASA Technical Reports Server (NTRS)

Bathias, C.; Brinet, B.; Sertour, G.

1978-01-01

Acoustic emission was used for the detection of fatigue cracking in a number of high-strength light alloys used in aeronautical structures. Among the features studied were: the influence of emission frequency, the effect of surface oxidation, and the influence of grains. It was concluded that acoustic emission is an effective nondestructive technique for evaluating the initiation of fatigue cracking in such materials.

Microfocus computed tomography in medicine

NASA Astrophysics Data System (ADS)

Obodovskiy, A. V.

2018-02-01

Recent advances in the field of high-frequency power schemes for X-ray devices allow the creation of high-resolution instruments. At the department of electronic devices and Equipment of the St. Petersburg State Electrotechnical University, a model of a microfocus computer tomograph was developed. Used equipment allows to receive projection data with an increase up to 100 times. A distinctive feature of the device is the possibility of implementing various schemes for obtaining projection data.

Holographic radar imaging privacy techniques utilizing dual-frequency implementation

NASA Astrophysics Data System (ADS)

McMakin, Douglas L.; Hall, Thomas E.; Sheen, David M.

2008-04-01

Over the last 15 years, the Pacific Northwest National Laboratory has performed significant research and development activities to enhance the state of the art of holographic radar imaging systems to be used at security checkpoints for screening people for concealed threats hidden under their garments. These enhancement activities included improvements to privacy techniques to remove human features and providing automatic detection of body-worn concealed threats. The enhanced privacy and detection methods used both physical and software imaging techniques. The physical imaging techniques included polarization-diversity illumination and reception, dual-frequency implementation, and high-frequency imaging at 60 GHz. Software imaging techniques to enhance the privacy of the person under surveillance included extracting concealed threat artifacts from the imagery to automatically detect the threat. This paper will focus on physical privacy techniques using dual-frequency implementation.

Holographic Radar Imaging Privacy Techniques Utilizing Dual-Frequency Implementation

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

McMakin, Douglas L.; Hall, Thomas E.; Sheen, David M.

2008-04-18

Over the last 15 years, the Pacific Northwest National Laboratory has performed significant research and development activities to enhance the state of the art of holographic radar imaging systems to be used at security checkpoints for screening people for concealed threats hidden under their garments. These enhancement activities included improvements to privacy techniques to remove human features and providing automatic detection of body-worn concealed threats. The enhanced privacy and detection methods used both physical and software imaging techniques. The physical imaging techniques included polarization-diversity illumination and reception, dual-frequency implementation, and high-frequency imaging at 60 GHz. Software imaging techniques to enhancemore » the privacy of the person under surveillance included extracting concealed threat artifacts from the imagery to automatically detect the threat. This paper will focus on physical privacy techniques using dual-frequency implementation.« less

Detection Performance Evaluation of the ASDE-3 Using Fixed Frequency and Frequency-Agile Operation

DOT National Transportation Integrated Search

1981-03-01

The ASDE-3 (Airport Surface Detection Equipment) Radar design has many features to enhance operational usefulness. The purpose of all these features is to provide a better airport surface surveillance display for the control power tower cab. One of t...

Determination of sound types and source levels of airborne vocalizations by California sea lions, Zalophus californianus, in rehabilitation at the Marine Mammal Center in Sausalito, California

NASA Astrophysics Data System (ADS)

Schwalm, Afton Leigh

California sea lions (Zalophus californianus) are a highly popular and easily recognized marine mammal in zoos, aquariums, circuses, and often seen by ocean visitors. They are highly vocal and gregarious on land. Surprisingly, little research has been performed on the vocalization types, source levels, acoustic properties, and functions of airborne sounds used by California sea lions. This research on airborne vocalizations of California sea lions will advance the understanding of this aspect of California sea lions communication, as well as examine the relationship between health condition and acoustic behavior. Using a PhillipsRTM digital recorder with attached microphone and a calibrated RadioShackRTM sound pressure level meter, acoustical data were recorded opportunistically on California sea lions during rehabilitation at The Marine Mammal Center in Sausalito, CA. Vocalizations were analyzed using frequency, time, and amplitude variables with Raven Pro: Interactive Sound Analysis Software Version 1.4 (The Cornell Lab of Ornithology, Ithaca, NY). Five frequency, three time, and four amplitude variables were analyzed for each vocalization. Differences in frequency, time, and amplitude variables were not significant by sex. The older California sea lion group produced vocalizations that were significantly lower in four frequency variables, significantly longer in two time variables, significantly higher in calibrated maximum and minimum amplitude variables, and significantly lower in frequency at maximum and minimum amplitude compared with pups. Six call types were identified: bark, goat, growl/grumble, bark/grumble, bark/growl, and grumble/moan. The growl/grumble call was higher in dominant beginning, ending, and minimum frequency, as well as in the frequency at maximum amplitude compared with the bark, goat, bark/grumble calls in the first versus last vocalization sample. The goat call was significantly higher in first harmonic interval than any other call type in the all vocalizations sample. The "fate" of a sea lion was categorized as: released, placed at another facility, remained at TMMC, euthanized, or died. To determine if acoustic features could be used to assess the recovery of a pup, the acoustic features of a pup's first recorded vocalization were compared with the frequency, time, and amplitude of the last vocalization recorded (i.e., before it was released or placed at another facility). In addition, all first vocalizations were pooled and all last vocalizations were pooled for acoustic analysis, regardless of their fate. Released pups had shorter duration calls, a greater first harmonic interval, and a higher dominant maximum frequency than either pups that died or pups remaining at TMMC. Released pups had a higher frequency at maximum and minimum amplitude compared to dead and remaining pups. Pups that died had significantly lower dominant ending frequency and a lower dominant minimum frequency than released or remaining pups. These results were supported by other studies on different species of otariids, phocids, and cetaceans. The preliminary analyses presented in this thesis holds promise that with additional data acoustic features of California sea lion airborne vocalizations could indicate sex, age, and possibly health condition or the potential for release.

The spread of attention across features of a surface

PubMed Central

Ernst, Zachary Raymond; Jazayeri, Mehrdad

2013-01-01

Contrasting theories of visual attention have emphasized selection by spatial location, individual features, and whole objects. We used functional magnetic resonance imaging to ask whether and how attention to one feature of an object spreads to other features of the same object. Subjects viewed two spatially superimposed surfaces of random dots that were segregated by distinct color-motion conjunctions. The color and direction of motion of each surface changed smoothly and in a cyclical fashion. Subjects were required to track one feature (e.g., color) of one of the two surfaces and detect brief moments when the attended feature diverged from its smooth trajectory. To tease apart the effect of attention to individual features on the hemodynamic response, we used a frequency-tagging scheme. In this scheme, the stimulus features (color and direction of motion) are modulated periodically at distinct frequencies so that the contribution of each feature to the hemodynamics can be inferred from the harmonic response at the corresponding frequency. We found that attention to one feature (e.g., color) of one surface increased the response modulation not only to the attended feature but also to the other feature (e.g., motion) of the same surface. This attentional modulation was evident in multiple visual areas and was present as early as V1. The spread of attention to the behaviorally irrelevant features of a surface suggests that attention may automatically select all features of a single object. Thus object-based attention may be supported by an enhancement of feature-specific sensory signals in the visual cortex. PMID:23883860

Gain-Compensating Circuit For NDE and Ultrasonics

NASA Technical Reports Server (NTRS)

Kushnick, Peter W.

1987-01-01

High-frequency gain-compensating circuit designed for general use in nondestructive evaluation and ultrasonic measurements. Controls gain of ultrasonic receiver as function of time to aid in measuring attenuation of samples with high losses; for example, human skin and graphite/epoxy composites. Features high signal-to-noise ratio, large signal bandwidth and large dynamic range. Control bandwidth of 5 MHz ensures accuracy of control signal. Currently being used for retrieval of more information from ultrasonic signals sent through composite materials that have high losses, and to measure skin-burn depth in humans.

Microfabricated high-bandpass foucault aperture for electron microscopy

DOEpatents

Glaeser, Robert; Cambie, Rossana; Jin, Jian

2014-08-26

A variant of the Foucault (knife-edge) aperture is disclosed that is designed to provide single-sideband (SSB) contrast at low spatial frequencies but retain conventional double-sideband (DSB) contrast at high spatial frequencies in transmission electron microscopy. The aperture includes a plate with an inner open area, a support extending from the plate at an edge of the open area, a half-circle feature mounted on the support and located at the center of the aperture open area. The radius of the half-circle portion of reciprocal space that is blocked by the aperture can be varied to suit the needs of electron microscopy investigation. The aperture is fabricated from conductive material which is preferably non-oxidizing, such as gold, for example.

Quantum correlation of high dimensional system in a dephasing environment

NASA Astrophysics Data System (ADS)

Ji, Yinghua; Ke, Qiang; Hu, Juju

2018-05-01

For a high dimensional spin-S system embedded in a dephasing environment, we theoretically analyze the time evolutions of quantum correlation and entanglement via Frobenius norm and negativity. The quantum correlation dynamics can be considered as a function of the decoherence parameters, including the ratio between the system oscillator frequency ω0 and the reservoir cutoff frequency ωc , and the different environment temperature. It is shown that the quantum correlation can not only measure nonclassical correlation of the considered system, but also perform a better robustness against the dissipation. In addition, the decoherence presents the non-Markovian features and the quantum correlation freeze phenomenon. The former is much weaker than that in the sub-Ohmic or Ohmic thermal reservoir environment.

A tomographic technique for the simultaneous imaging of temperature, chemical species, and pressure in reactive flows using absorption spectroscopy with frequency-agile lasers

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

Cai, Weiwei; Kaminski, Clemens F., E-mail: cfk23@cam.ac.uk

2014-01-20

This paper proposes a technique that can simultaneously retrieve distributions of temperature, concentration of chemical species, and pressure based on broad bandwidth, frequency-agile tomographic absorption spectroscopy. The technique holds particular promise for the study of dynamic combusting flows. A proof-of-concept numerical demonstration is presented, using representative phantoms to model conditions typically prevailing in near-atmospheric or high pressure flames. The simulations reveal both the feasibility of the proposed technique and its robustness. Our calculations indicate precisions of ∼70 K at flame temperatures and ∼0.05 bars at high pressure from reconstructions featuring as much as 5% Gaussian noise in the projections.

Atomic force microscopy characterization of Zerodur mirror substrates for the extreme ultraviolet telescopes aboard NASA's Solar Dynamics Observatory.

PubMed

Soufli, Regina; Baker, Sherry L; Windt, David L; Gullikson, Eric M; Robinson, Jeff C; Podgorski, William A; Golub, Leon

2007-06-01

The high-spatial frequency roughness of a mirror operating at extreme ultraviolet (EUV) wavelengths is crucial for the reflective performance and is subject to very stringent specifications. To understand and predict mirror performance, precision metrology is required for measuring the surface roughness. Zerodur mirror substrates made by two different polishing vendors for a suite of EUV telescopes for solar physics were characterized by atomic force microscopy (AFM). The AFM measurements revealed features in the topography of each substrate that are associated with specific polishing techniques. Theoretical predictions of the mirror performance based on the AFM-measured high-spatial-frequency roughness are in good agreement with EUV reflectance measurements of the mirrors after multilayer coating.

[Experience of the development special medical technical laboratory for studies of effects caused by potent electromagnetic radiation in biologic objects].

PubMed

Gorodetsky, B N; Kalyada, T V; Petrov, S V

2015-01-01

This article covers topics of creating special medical technical laboratory for medial and biologic studies concerning influence of potent high-frequency elecromagnetic radiation on various biologic objects. The authors gave example of such laboratory, described its construction features, purpose and main characteristics of the included devices.

Construction and Characterization of a Compact, Portable, Low-Cost Colorimeter for the Chemistry Lab

ERIC Educational Resources Information Center

Clippard, Carrie M.; Hughes, William; Chohan, Balwant S.; Sykes, Danny G.

2016-01-01

A low-cost and portable colorimeter was constructed featuring a low-voltage programmable color light sensor-to-frequency converter, a CMOS 8-bit microcontroller, and an LCD display. The instrument has successfully facilitated the introduction and application of spectroscopy to groups of middle school, high school, and undergraduate students. A…

Characterization of Early Partial Seizure Onset: Frequency, Complexity and Entropy

PubMed Central

Jouny, Christophe C.; Bergey, Gregory K.

2011-01-01

Objective A clear classification of partial seizures onset features is not yet established. Complexity and entropy have been very widely used to describe dynamical systems, but a systematic evaluation of these measures to characterize partial seizures has never been performed. Methods Eighteen different measures including power in frequency bands up to 300Hz, Gabor atom density (GAD), Higuchi fractal dimension (HFD), Lempel-Ziv complexity, Shannon entropy, sample entropy, and permutation entropy, were selected to test sensitivity to partial seizure onset. Intracranial recordings from forty-five patients with mesial temporal, neocortical temporal and neocortical extratemporal seizure foci were included (331 partial seizures). Results GAD, Lempel-Ziv complexity, HFD, high frequency activity, and sample entropy were the most reliable measures to assess early seizure onset. Conclusions Increases in complexity and occurrence of high-frequency components appear to be commonly associated with early stages of partial seizure evolution from all regions. The type of measure (frequency-based, complexity or entropy) does not predict the efficiency of the method to detect seizure onset. Significance Differences between measures such as GAD and HFD highlight the multimodal nature of partial seizure onsets. Improved methods for early seizure detection may be achieved from a better understanding of these underlying dynamics. PMID:21872526

Dynamics of mode-coupling-induced microresonator frequency combs in normal dispersion

NASA Astrophysics Data System (ADS)

Jang, Jae K.; Okawachi, Yoshitomo; Yu, Mengjie; Luke, Kevin; Ji, Xingchen; Lipson, Michal; Gaeta, Alexander L.

2016-12-01

We experimentally and theoretically investigate the dynamics of microresonator-based frequency comb generation assisted by mode coupling in the normal group-velocity dispersion (GVD) regime. We show that mode coupling can initiate intracavity modulation instability (MI) by directly perturbing the pump-resonance mode. We also observe the formation of a low-noise comb as the pump frequency is tuned further into resonance from the MI point. We determine the phase-matching conditions that accurately predict all the essential features of the MI and comb spectra, and extend the existing analogy between mode coupling and high-order dispersion to the normal GVD regime. We discuss the applicability of our analysis to the possibility of broadband comb generation in the normal GVD regime.

Computerized detection of breast cancer using resonance-frequency-based electrical impedance spectroscopy

NASA Astrophysics Data System (ADS)

Gao, Wei; Fan, Ming; Zhao, Weijie; Zheng, Bin; Li, Lihua

2017-03-01

This study developed and tested a multi-probe resonance-frequency-based electrical impedance spectroscopy (REIS) system aimed at detection of breast cancer. The REIS system consists of specially designed mechanical supporting device that can be easily lifted to fit women of different height, a seven probe sensor cup, and a computer providing software for system control and management. The sensor cup includes one central probe for direct contact with the nipple, and other six probes uniformly distributed at a distance of 35mm away from the center probe to enable contact with breast skin surface. It takes about 18 seconds for this system to complete a data acquisition process. We utilized this system for examination of breast cancer, collecting a dataset of 289 cases including biopsy verified 74 malignant and 215 benign tumors. After that, 23 REIS based features, including seven frequency, fifteen magnitude features were extracted, and an age feature. To reduce redundancy we selected 6 features using the evolutionary algorithm for classification. The area under a receiver operating characteristic curve (AUC) was computed to assess classifier performance. A multivariable logistic regression method was performed for detection of the tumors. The results of our study showed for the 23 REIS features AUC and ACC, Sensitivity and Specificity of 0.796, 0.727, 0.731 and 0.726, respectively. The AUC and ACC, Sensitivity and Specificity for the 6 REIS features of 0.840, 0.80, 0.703 and 0.833, respectively, and AUC of 0.662 and 0.619 for the frequency and magnitude based REIS features, respectively. The performance of the classifiers using all the 6 features was significantly better than solely using magnitude features (p=3.29e-08) and frequency features (5.61e-07). Smote algorithm was used to expand small samples to balance the dataset, the AUC after data balance of 0.846 increased than the original data classification performance. The results indicated that the REIS system is a promising tool for detection of breast cancer and may be acceptable for clinical implementation.

Intelligent Fault Diagnosis of HVCB with Feature Space Optimization-Based Random Forest

PubMed Central

Ma, Suliang; Wu, Jianwen; Wang, Yuhao; Jia, Bowen; Jiang, Yuan

2018-01-01

Mechanical faults of high-voltage circuit breakers (HVCBs) always happen over long-term operation, so extracting the fault features and identifying the fault type have become a key issue for ensuring the security and reliability of power supply. Based on wavelet packet decomposition technology and random forest algorithm, an effective identification system was developed in this paper. First, compared with the incomplete description of Shannon entropy, the wavelet packet time-frequency energy rate (WTFER) was adopted as the input vector for the classifier model in the feature selection procedure. Then, a random forest classifier was used to diagnose the HVCB fault, assess the importance of the feature variable and optimize the feature space. Finally, the approach was verified based on actual HVCB vibration signals by considering six typical fault classes. The comparative experiment results show that the classification accuracy of the proposed method with the origin feature space reached 93.33% and reached up to 95.56% with optimized input feature vector of classifier. This indicates that feature optimization procedure is successful, and the proposed diagnosis algorithm has higher efficiency and robustness than traditional methods. PMID:29659548

Ternary mixed crystal effects on interface optical phonon and electron-phonon coupling in zinc-blende GaN/AlxGa1-xN spherical quantum dots

NASA Astrophysics Data System (ADS)

Huang, Wen Deng; Chen, Guang De; Yuan, Zhao Lin; Yang, Chuang Hua; Ye, Hong Gang; Wu, Ye Long

2016-02-01

The theoretical investigations of the interface optical phonons, electron-phonon couplings and its ternary mixed effects in zinc-blende spherical quantum dots are obtained by using the dielectric continuum model and modified random-element isodisplacement model. The features of dispersion curves, electron-phonon coupling strengths, and its ternary mixed effects for interface optical phonons in a single zinc-blende GaN/AlxGa1-xN spherical quantum dot are calculated and discussed in detail. The numerical results show that there are three branches of interface optical phonons. One branch exists in low frequency region; another two branches exist in high frequency region. The interface optical phonons with small quantum number l have more important contributions to the electron-phonon interactions. It is also found that ternary mixed effects have important influences on the interface optical phonon properties in a single zinc-blende GaN/AlxGa1-xN quantum dot. With the increase of Al component, the interface optical phonon frequencies appear linear changes, and the electron-phonon coupling strengths appear non-linear changes in high frequency region. But in low frequency region, the frequencies appear non-linear changes, and the electron-phonon coupling strengths appear linear changes.

Multimodal 2D Brain Computer Interface.

PubMed

Almajidy, Rand K; Boudria, Yacine; Hofmann, Ulrich G; Besio, Walter; Mankodiya, Kunal

2015-08-01

In this work we used multimodal, non-invasive brain signal recording systems, namely Near Infrared Spectroscopy (NIRS), disc electrode electroencephalography (EEG) and tripolar concentric ring electrodes (TCRE) electroencephalography (tEEG). 7 healthy subjects participated in our experiments to control a 2-D Brain Computer Interface (BCI). Four motor imagery task were performed, imagery motion of the left hand, the right hand, both hands and both feet. The signal slope (SS) of the change in oxygenated hemoglobin concentration measured by NIRS was used for feature extraction while the power spectrum density (PSD) of both EEG and tEEG in the frequency band 8-30Hz was used for feature extraction. Linear Discriminant Analysis (LDA) was used to classify different combinations of the aforementioned features. The highest classification accuracy (85.2%) was achieved by using features from all the three brain signals recording modules. The improvement in classification accuracy was highly significant (p = 0.0033) when using the multimodal signals features as compared to pure EEG features.

Gesture recognition for smart home applications using portable radar sensors.

PubMed

Wan, Qian; Li, Yiran; Li, Changzhi; Pal, Ranadip

2014-01-01

In this article, we consider the design of a human gesture recognition system based on pattern recognition of signatures from a portable smart radar sensor. Powered by AAA batteries, the smart radar sensor operates in the 2.4 GHz industrial, scientific and medical (ISM) band. We analyzed the feature space using principle components and application-specific time and frequency domain features extracted from radar signals for two different sets of gestures. We illustrate that a nearest neighbor based classifier can achieve greater than 95% accuracy for multi class classification using 10 fold cross validation when features are extracted based on magnitude differences and Doppler shifts as compared to features extracted through orthogonal transformations. The reported results illustrate the potential of intelligent radars integrated with a pattern recognition system for high accuracy smart home and health monitoring purposes.

[The morphological features of skin wounds inflicted by joinery hand saws designed for different types of sawing].

PubMed

Sarkisian, B A; Azarov, P A

2014-01-01

The objective of the present work was to study the morphological features of skin wounds inflicted by joinery hand saws designed for longitudinal, transverse, and mixed sawing. A total of 60 injuries to the thigh skin inflicted by the recurring and reciprocating saw movements were simulated. The hand saws had 5 mm high "sharp" and "blunt"-tipped teeth. The analysis of the morphological features of the wounds revealed differences in their length and depth, shape of edge cuts and defects, and the relief of the walls depending on the sawtooth sharpness and the mode of sawing. It is concluded that morphological features of the wounds may be used to determine the type of the saw, the sharpness of its teeth, the direction and frequency of its movements.

A fast complex domain-matching pursuit algorithm and its application to deep-water gas reservoir detection

NASA Astrophysics Data System (ADS)

Zeng, Jing; Huang, Handong; Li, Huijie; Miao, Yuxin; Wen, Junxiang; Zhou, Fei

2017-12-01

The main emphasis of exploration and development is shifting from simple structural reservoirs to complex reservoirs, which all have the characteristics of complex structure, thin reservoir thickness and large buried depth. Faced with these complex geological features, hydrocarbon detection technology is a direct indication of changes in hydrocarbon reservoirs and a good approach for delimiting the distribution of underground reservoirs. It is common to utilize the time-frequency (TF) features of seismic data in detecting hydrocarbon reservoirs. Therefore, we research the complex domain-matching pursuit (CDMP) method and propose some improvements. First is the introduction of a scale parameter, which corrects the defect that atomic waveforms only change with the frequency parameter. Its introduction not only decomposes seismic signal with high accuracy and high efficiency but also reduces iterations. We also integrate jumping search with ergodic search to improve computational efficiency while maintaining the reasonable accuracy. Then we combine the improved CDMP with the Wigner-Ville distribution to obtain a high-resolution TF spectrum. A one-dimensional modeling experiment has proved the validity of our method. Basing on the low-frequency domain reflection coefficient in fluid-saturated porous media, we finally get an approximation formula for the mobility attributes of reservoir fluid. This approximation formula is used as a hydrocarbon identification factor to predict deep-water gas-bearing sand of the M oil field in the South China Sea. The results are consistent with the actual well test results and our method can help inform the future exploration of deep-water gas reservoirs.

Spallation-induced roughness promoting high spatial frequency nanostructure formation on Cr

NASA Astrophysics Data System (ADS)

Abou-Saleh, A.; Karim, E. T.; Maurice, C.; Reynaud, S.; Pigeon, F.; Garrelie, F.; Zhigilei, L. V.; Colombier, J. P.

2018-04-01

Interaction of ultrafast laser pulses with metal surfaces in the spallation regime can result in the formation of anisotropic nanoscale surface morphology commonly referred to as laser-induced periodic surface structures (LIPSS) or ripples. The surface structures generated by a single pulse irradiation of monocrystalline Cr samples are investigated experimentally and computationally for laser fluences that produce high spatial frequency nanostructures in the multi-pulse irradiation regime. Electron microscopy reveals distinct response of samples with different crystallographic surface orientations, with (100) surfaces exhibiting the formation of more refined nanostructure by a single pulse irradiation and a more pronounced LIPSS after two laser pulses as compared to (110) surfaces. A large-scale molecular dynamics simulation of laser interaction with a (100) Cr target provides detailed information on processes responsible for spallation of a liquid layer, redistribution of molten material, and rapid resolidification of the target. The nanoscale roughness of the resolidified surface predicted in the simulation features elongated frozen nanospikes, nanorims and nanocavities with dimensions and surface density similar to those in the surface morphology observed for (100) Cr target with atomic force microscopy. The results of the simulation suggest that the types, sizes and dimensions of the nanoscale surface features are defined by the competition between the evolution of transient liquid structures generated in the spallation process and the rapid resolidification of the surface region of the target. The spallation-induced roughness is likely to play a key role in triggering the generation of high-frequency LIPSS upon irradiation by multiple laser pulses.

Polymeric Mold For Providing A Microscale Part

DOEpatents

Boehme, Dale R.; Bankert, Michelle A.; Christenson, Todd R.

2005-01-11

The invention is a developer system for developing a PMMA photoresist having exposed patterns comprising features having both very small sizes, and very high aspect ratios. The developer system of the present invention comprises a developer tank, an intermediate rinse tank and a final rinse tank, each tank having a source of high frequency sonic agitation, temperature control, and continuous filtration. It has been found that by moving a patterned wafer, through a specific sequence of developer/rinse solutions, where an intermediate rinse solution completes development of those portions of the exposed resist left undeveloped after the development solution, by agitating the solutions with a source of high frequency sonic vibration, and by adjusting and closely controlling the temperatures and continuously filtering and recirculating these solutions, it is possible to maintain the kinetic dissolution of the exposed PMMA polymer as the rate limiting step.

Localized Spoof Surface Plasmons based on Closed Subwavelength High Contrast Gratings: Concept and Microwave-Regime Realizations

NASA Astrophysics Data System (ADS)

Li, Zhuo; Xu, Bingzheng; Liu, Liangliang; Xu, Jia; Chen, Chen; Gu, Changqing; Zhou, Yongjin

2016-06-01

In this work, we report the existence of spoof localized surface plasmons (spoof-LSPs) arising with closed high contrast gratings (HCGs) at deep subwavelength scales, another platform for field localization at microwave frequencies. The HCGs are in the form of a periodic array of radial dielectric blocks with high permittivity around a metal core supporting spoof-LSPs of transverse magnetic (TM) form. Simulation results validate the phenomenon and a metamaterial approach is also given to capture all the resonant features of this kind of spoof-LSPs. In addition, experimental verification of the existence of spoof-LSPs supported by a three dimensional (3D) HCGs resonance structure in the microwave regime is presented. This work expands the original spoof-LSPs theory and opens up a new avenue for obtaining resonance devices in the microwave frequencies.

Synthesis of Joint Volumes, Visualization of Paths, and Revision of Viewing Sequences in a Multi-dimensional Seismic Data Viewer

NASA Astrophysics Data System (ADS)

Chen, D. M.; Clapp, R. G.; Biondi, B.

2006-12-01

Ricksep is a freely-available interactive viewer for multi-dimensional data sets. The viewer is very useful for simultaneous display of multiple data sets from different viewing angles, animation of movement along a path through the data space, and selection of local regions for data processing and information extraction. Several new viewing features are added to enhance the program's functionality in the following three aspects. First, two new data synthesis algorithms are created to adaptively combine information from a data set with mostly high-frequency content, such as seismic data, and another data set with mainly low-frequency content, such as velocity data. Using the algorithms, these two data sets can be synthesized into a single data set which resembles the high-frequency data set on a local scale and at the same time resembles the low- frequency data set on a larger scale. As a result, the originally separated high and low-frequency details can now be more accurately and conveniently studied together. Second, a projection algorithm is developed to display paths through the data space. Paths are geophysically important because they represent wells into the ground. Two difficulties often associated with tracking paths are that they normally cannot be seen clearly inside multi-dimensional spaces and depth information is lost along the direction of projection when ordinary projection techniques are used. The new algorithm projects samples along the path in three orthogonal directions and effectively restores important depth information by using variable projection parameters which are functions of the distance away from the path. Multiple paths in the data space can be generated using different character symbols as positional markers, and users can easily create, modify, and view paths in real time. Third, a viewing history list is implemented which enables Ricksep's users to create, edit and save a recipe for the sequence of viewing states. Then, the recipe can be loaded into an active Ricksep session, after which the user can navigate to any state in the sequence and modify the sequence from that state. Typical uses of this feature are undoing and redoing viewing commands and animating a sequence of viewing states. The theoretical discussion are carried out and several examples using real seismic data are provided to show how these new Ricksep features provide more convenient, accurate ways to manipulate multi-dimensional data sets.

Short-term stability improvements of an optical frequency standard based on free Ca atoms

NASA Astrophysics Data System (ADS)

Sherman, Jeff; Oates, Chris

2010-03-01

Compared to optical frequency standards featuring trapped ions or atoms in optical lattices, the strength of a standard using freely expanding neutral calcium atoms is not ultimate accuracy but rather short-term stability and experimental simplicity. Recently, a fractional frequency instability of 4 x10-15 at 1 second was demonstrated for the Ca standard at 657 nm [1]. The short cycle time (˜2 ms) combined with only a moderate interrogation duty cycle (˜15 %) is thought to introduce excess, and potentially critically limiting technical noise due to the Dick effect---high-frequency noise on the laser oscillator is not averaged away but is instead down-sampled by aliasing. We will present results of two strategies employed to minimize this effect: the reduction of clock laser noise by filtering the master clock oscillator through a high-finesse optical cavity [2], and an optimization of the interrogation cycle to match our laser's noise spectrum.[4pt] [1] Oates et al., Optics Letters, 25(21), 1603--5 (2000)[0pt] [2] Nazarova et al., J. Opt. Soc. Am. B, 5(10), 1632--8 (2008)

Screening for the C9ORF72 repeat expansion in a greek frontotemporal dementia cohort.

PubMed

Kartanou, Chrisoula; Karadima, Georgia; Koutsis, Georgios; Breza, Marianthi; Papageorgiou, Sokratis G; Paraskevas, George P; Kapaki, Elisabeth; Panas, Marios

2018-02-01

The C9orf72 repeat expansion is a common genetic cause of frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) in European populations. A previous study has reported a high frequency of the expansion in Greek ALS. However, no data have been reported on the frequency of the expansion in Greek FTD. Currently, we investigated the frequency of the C9orfF72 expansion in a well-characterized cohort of 64 Greek FTD patients. We detected the C9orf72 repeat expansion in 9.3% of cases. Overall, 27.7% of familial and 2.2% of sporadic cases were expansion-positive. Five out of 6 cases had a diagnosis of behavioral variant FTD. All expansion-positive cases had fairly typical FTD presentations. Clinical features included motor neuron disease, Parkinsonism and hallucinations. We conclude that the overall frequency of C9orf72-positive cases in Greek FTD is high, comparable to Greek ALS, similar to some Western European, but significantly higher than some Mediterranean FTD populations.

Common mode noise rejection properties of amplitude and phase noise in a heterodyne interferometer.

PubMed

Hechenblaikner, Gerald

2013-05-01

High precision metrology systems based on heterodyne interferometry can measure the position and attitude of objects to accuracies of picometer and nanorad, respectively. A frequently found feature of the general system design is the subtraction of a reference phase from the phase of the position interferometer, which suppresses low frequency common mode amplitude and phase fluctuations occurring in volatile optical path sections shared by both the position and reference interferometer. Spectral components of the noise at frequencies around or higher than the heterodyne frequency, however, are generally transmitted into the measurement band and may limit the measurement accuracy. Detailed analytical calculations complemented with Monte Carlo simulations show that high frequency noise components may also be entirely suppressed, depending on the relative difference of measurement and reference phase, which may be exploited by corresponding design provisions. While these results are applicable to any heterodyne interferometer with certain design characteristics, specific calculations and related discussions are given for the example of the optical metrology system of the LISA Pathfinder mission to space.

Frequency accurate coherent electro-optic dual-comb spectroscopy in real-time.

PubMed

Martín-Mateos, Pedro; Jerez, Borja; Largo-Izquierdo, Pedro; Acedo, Pablo

2018-04-16

Electro-optic dual-comb spectrometers have proved to be a promising technology for sensitive, high-resolution and rapid spectral measurements. Electro-optic combs possess very attractive features like simplicity, reliability, bright optical teeth, and typically moderate but quickly tunable optical spans. Furthermore, in a dual-comb arrangement, narrowband electro-optic combs are generated with a level of mutual coherence that is sufficiently high to enable optical multiheterodyning without inter-comb stabilization or signal processing systems. However, this valuable tool still presents several limitations; for instance, on most systems, absolute frequency accuracy and long-term stability cannot be guaranteed; likewise, interferometer-induced phase noise restricts coherence time and limits the attainable signal-to-noise ratio. In this paper, we address these drawbacks and demonstrate a cost-efficient absolute electro-optic dual-comb instrument based on a frequency stabilization mechanism and a novel adaptive interferogram acquisition approach devised for electro-optic dual-combs capable of operating in real-time. The spectrometer, completely built from commercial components, provides sub-ppm frequency uncertainties and enables a signal-to-noise ratio of 10000 (intensity noise) in 30 seconds of integration time.

Transmitted spectral modulation of double-ring resonator using liquid crystals in terahertz range

NASA Astrophysics Data System (ADS)

Sun, Huijuan; Zhou, Qingli; Wang, Xiumin; Li, Chenyu; Wu, Ani; Zhang, Cunlin

2013-12-01

Metamaterials with subwavelength structural features show unique electromagnetic responses that are unattainable with natural materials. Recent research on these artificial materials has been pushed forward to the terahertz region because of potential applications in biological fingerprinting, security imaging, remote sensing, and high frequency magnetic and electric resonant devices. Active control of their properties could further facilitate and open up new applications in terms of modulation and switching. Liquid crystals, which have been the subject of research for more than a century, have the unique properties for the development of many other optical components such as light valves, tunable filters and tunable lenses. In this paper, we investigated the transmitted spectral modulation in terahertz range by using liquid crystals (5CB and TEB300) covering on the fabricated double-ring resonators to realize the shift of the resonance frequency. Our obtained results indicate the low frequency resonance shows the obvious blue-shift, while the location of high frequency resonance is nearly unchanged. We believe this phenomenon is related to not only the refractive index of the covering liquid crystals but also the resonant mechanism of both resonances.

Ranking of predictor variables based on effect size criterion provides an accurate means of automatically classifying opinion column articles

NASA Astrophysics Data System (ADS)

Legara, Erika Fille; Monterola, Christopher; Abundo, Cheryl

2011-01-01

We demonstrate an accurate procedure based on linear discriminant analysis that allows automatic authorship classification of opinion column articles. First, we extract the following stylometric features of 157 column articles from four authors: statistics on high frequency words, number of words per sentence, and number of sentences per paragraph. Then, by systematically ranking these features based on an effect size criterion, we show that we can achieve an average classification accuracy of 93% for the test set. In comparison, frequency size based ranking has an average accuracy of 80%. The highest possible average classification accuracy of our data merely relying on chance is ∼31%. By carrying out sensitivity analysis, we show that the effect size criterion is superior than frequency ranking because there exist low frequency words that significantly contribute to successful author discrimination. Consistent results are seen when the procedure is applied in classifying the undisputed Federalist papers of Alexander Hamilton and James Madison. To the best of our knowledge, the work is the first attempt in classifying opinion column articles, that by virtue of being shorter in length (as compared to novels or short stories), are more prone to over-fitting issues. The near perfect classification for the longer papers supports this claim. Our results provide an important insight on authorship attribution that has been overlooked in previous studies: that ranking discriminant variables based on word frequency counts is not necessarily an optimal procedure.

Energy-Based Tetrahedron Sensor for High-Temperature, High-Pressure Environments

NASA Technical Reports Server (NTRS)

Gee, Kent L.; Sommerfeldt, Scott D.; Blotter, Jonathan D.

2012-01-01

An acoustic energy-based probe has been developed that incorporates multiple acoustic sensing elements in order to obtain the acoustic pressure and three-dimensional acoustic particle velocity. With these quantities, the user can obtain various energy-based quantities, including acoustic energy density, acoustic intensity, and acoustic impedance. In this specific development, the probe has been designed to operate in an environment characterized by high temperatures and high pressures as is found in the close vicinity of rocket plumes. Given these capabilities, the probe is designed to be used to investigate the acoustic conditions within the plume of a rocket engine or jet engine to facilitate greater understanding of the noise generation mechanisms in those plumes. The probe features sensors mounted inside a solid sphere. The associated electronics for the probe are contained within the sphere and the associated handle for the probe. More importantly, the design of the probe has desirable properties that reduce the bias errors associated with determining the acoustic pressure and velocity using finite sum and difference techniques. The diameter of the probe dictates the lower and upper operating frequencies for the probe, where accurate measurements can be acquired. The current probe design implements a sphere diameter of 1 in. (2.5 cm), which limits the upper operating frequency to about 4.5 kHz. The sensors are operational up to much higher frequencies, and could be used to acquire pressure data at higher frequencies, but the energy-based measurements are limited to that upper frequency. Larger or smaller spherical probes could be designed to go to lower or higher frequency range

Launch vehicle payload adapter design with vibration isolation features

NASA Astrophysics Data System (ADS)

Thomas, Gareth R.; Fadick, Cynthia M.; Fram, Bryan J.

2005-05-01

Payloads, such as satellites or spacecraft, which are mounted on launch vehicles, are subject to severe vibrations during flight. These vibrations are induced by multiple sources that occur between liftoff and the instant of final separation from the launch vehicle. A direct result of the severe vibrations is that fatigue damage and failure can be incurred by sensitive payload components. For this reason a payload adapter has been designed with special emphasis on its vibration isolation characteristics. The design consists of an annular plate that has top and bottom face sheets separated by radial ribs and close-out rings. These components are manufactured from graphite epoxy composites to ensure a high stiffness to weight ratio. The design is tuned to keep the frequency of the axial mode of vibration of the payload on the flexibility of the adapter to a low value. This is the main strategy adopted for isolating the payload from damaging vibrations in the intermediate to higher frequency range (45Hz-200Hz). A design challenge for this type of adapter is to keep the pitch frequency of the payload above a critical value in order to avoid dynamic interactions with the launch vehicle control system. This high frequency requirement conflicts with the low axial mode frequency requirement and this problem is overcome by innovative tuning of the directional stiffnesses of the composite parts. A second design strategy that is utilized to achieve good isolation characteristics is the use of constrained layer damping. This feature is particularly effective at keeping the responses to a minimum for one of the most important dynamic loading mechanisms. This mechanism consists of the almost-tonal vibratory load associated with the resonant burn condition present in any stage powered by a solid rocket motor. The frequency of such a load typically falls in the 45-75Hz range and this phenomenon drives the low frequency design of the adapter. Detailed finite element analysis is used throughout to qualify the design for vibration isolation performance as well as confirm its static and dynamic strength.

A broadband chip-scale optical frequency synthesizer at 2.7 × 10−16 relative uncertainty

PubMed Central

Huang, Shu-Wei; Yang, Jinghui; Yu, Mingbin; McGuyer, Bart H.; Kwong, Dim-Lee; Zelevinsky, Tanya; Wong, Chee Wei

2016-01-01

Optical frequency combs—coherent light sources that connect optical frequencies with microwave oscillations—have become the enabling tool for precision spectroscopy, optical clockwork, and attosecond physics over the past decades. Current benchmark systems are self-referenced femtosecond mode-locked lasers, but Kerr nonlinear dynamics in high-Q solid-state microresonators has recently demonstrated promising features as alternative platforms. The advance not only fosters studies of chip-scale frequency metrology but also extends the realm of optical frequency combs. We report the full stabilization of chip-scale optical frequency combs. The microcomb’s two degrees of freedom, one of the comb lines and the native 18-GHz comb spacing, are simultaneously phase-locked to known optical and microwave references. Active comb spacing stabilization improves long-term stability by six orders of magnitude, reaching a record instrument-limited residual instability of 3.6mHz/τ. Comparing 46 nitride frequency comb lines with a fiber laser frequency comb, we demonstrate the unprecedented microcomb tooth-to-tooth relative frequency uncertainty down to 50 mHz and 2.7 × 10−16, heralding novel solid-state applications in precision spectroscopy, coherent communications, and astronomical spectrography. PMID:27152341

A Space Affine Matching Approach to fMRI Time Series Analysis.

PubMed

Chen, Liang; Zhang, Weishi; Liu, Hongbo; Feng, Shigang; Chen, C L Philip; Wang, Huili

2016-07-01

For fMRI time series analysis, an important challenge is to overcome the potential delay between hemodynamic response signal and cognitive stimuli signal, namely the same frequency but different phase (SFDP) problem. In this paper, a novel space affine matching feature is presented by introducing the time domain and frequency domain features. The time domain feature is used to discern different stimuli, while the frequency domain feature to eliminate the delay. And then we propose a space affine matching (SAM) algorithm to match fMRI time series by our affine feature, in which a normal vector is estimated using gradient descent to explore the time series matching optimally. The experimental results illustrate that the SAM algorithm is insensitive to the delay between the hemodynamic response signal and the cognitive stimuli signal. Our approach significantly outperforms GLM method while there exists the delay. The approach can help us solve the SFDP problem in fMRI time series matching and thus of great promise to reveal brain dynamics.

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

A satellite-based personal communication system for the 21st century

NASA Technical Reports Server (NTRS)

Sue, Miles K.; Dessouky, Khaled; Levitt, Barry; Rafferty, William

1990-01-01

Interest in personal communications (PCOMM) has been stimulated by recent developments in satellite and terrestrial mobile communications. A personal access satellite system (PASS) concept was developed at the Jet Propulsion Laboratory (JPL) which has many attractive user features, including service diversity and a handheld terminal. Significant technical challenges addressed in formulating the PASS space and ground segments are discussed. PASS system concept and basic design features, high risk enabling technologies, an optimized multiple access scheme, alternative antenna coverage concepts, the use of non-geostationary orbits, user terminal radiation constraints, and user terminal frequency reference are covered.

A hybrid fault diagnosis approach based on mixed-domain state features for rotating machinery.

PubMed

Xue, Xiaoming; Zhou, Jianzhong

2017-01-01

To make further improvement in the diagnosis accuracy and efficiency, a mixed-domain state features data based hybrid fault diagnosis approach, which systematically blends both the statistical analysis approach and the artificial intelligence technology, is proposed in this work for rolling element bearings. For simplifying the fault diagnosis problems, the execution of the proposed method is divided into three steps, i.e., fault preliminary detection, fault type recognition and fault degree identification. In the first step, a preliminary judgment about the health status of the equipment can be evaluated by the statistical analysis method based on the permutation entropy theory. If fault exists, the following two processes based on the artificial intelligence approach are performed to further recognize the fault type and then identify the fault degree. For the two subsequent steps, mixed-domain state features containing time-domain, frequency-domain and multi-scale features are extracted to represent the fault peculiarity under different working conditions. As a powerful time-frequency analysis method, the fast EEMD method was employed to obtain multi-scale features. Furthermore, due to the information redundancy and the submergence of original feature space, a novel manifold learning method (modified LGPCA) is introduced to realize the low-dimensional representations for high-dimensional feature space. Finally, two cases with 12 working conditions respectively have been employed to evaluate the performance of the proposed method, where vibration signals were measured from an experimental bench of rolling element bearing. The analysis results showed the effectiveness and the superiority of the proposed method of which the diagnosis thought is more suitable for practical application. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Morphologic features of basal cell carcinoma using the en-face mode in frequency domain optical coherence tomography.

PubMed

von Braunmühl, T; Hartmann, D; Tietze, J K; Cekovic, D; Kunte, C; Ruzicka, T; Berking, C; Sattler, E C

2016-11-01

Optical coherence tomography (OCT) has become a valuable non-invasive tool in the in vivo diagnosis of non-melanoma skin cancer, especially of basal cell carcinoma (BCC). Due to an updated software-supported algorithm, a new en-face mode - similar to the horizontal en-face mode in high-definition OCT and reflectance confocal microscopy - surface-parallel imaging is possible which, in combination with the established slice mode of frequency domain (FD-)OCT, may offer additional information in the diagnosis of BCC. To define characteristic morphologic features of BCC using the new en-face mode in addition to the conventional cross-sectional imaging mode for three-dimensional imaging of BCC in FD-OCT. A total of 33 BCC were examined preoperatively by imaging in en-face mode as well as cross-sectional mode in FD-OCT. Characteristic features were evaluated and correlated with histopathology findings. Features established in the cross-sectional imaging mode as well as additional features were present in the en-face mode of FD-OCT: lobulated structures (100%), dark peritumoral rim (75%), bright peritumoral stroma (96%), branching vessels (90%), compressed fibrous bundles between lobulated nests ('star shaped') (78%), and intranodular small bright dots (51%). These features were also evaluated according to the histopathological subtype. In the en-face mode, the lobulated structures with compressed fibrous bundles of the BCC were more distinct than in the slice mode. FD-OCT with a new depiction for horizontal and vertical imaging modes offers additional information in the diagnosis of BCC, especially in nodular BCC, and enhances the possibility of the evaluation of morphologic tumour features. © 2016 European Academy of Dermatology and Venereology.

Exploring spatial-temporal dynamics of fire regime features in mainland Spain

NASA Astrophysics Data System (ADS)

Jiménez-Ruano, Adrián; Rodrigues Mimbrero, Marcos; de la Riva Fernández, Juan

2017-10-01

This paper explores spatial-temporal dynamics in fire regime features, such as fire frequency, burnt area, large fires and natural- and human-caused fires, as an essential part of fire regime characterization. Changes in fire features are analysed at different spatial - regional and provincial/NUTS3 - levels, together with summer and winter temporal scales, using historical fire data from Spain for the period 1974-2013. Temporal shifts in fire features are investigated by means of change point detection procedures - Pettitt test, AMOC (at most one change), PELT (pruned exact linear time) and BinSeg (binary segmentation) - at a regional level to identify changes in the time series of the features. A trend analysis was conducted using the Mann-Kendall and Sen's slope tests at both the regional and NUTS3 level. Finally, we applied a principal component analysis (PCA) and varimax rotation to trend outputs - mainly Sen's slope values - to summarize overall temporal behaviour and to explore potential links in the evolution of fire features. Our results suggest that most fire features show remarkable shifts between the late 1980s and the first half of the 1990s. Mann-Kendall outputs revealed negative trends in the Mediterranean region. Results from Sen's slope suggest high spatial and intra-annual variability across the study area. Fire activity related to human sources seems to be experiencing an overall decrease in the northwestern provinces, particularly pronounced during summer. Similarly, the Hinterland and the Mediterranean coast are gradually becoming less fire affected. Finally, PCA enabled trends to be synthesized into four main components: winter fire frequency (PC1), summer burnt area (PC2), large fires (PC3) and natural fires (PC4).

A wavelet-based technique to predict treatment outcome for Major Depressive Disorder

PubMed Central

Xia, Likun; Mohd Yasin, Mohd Azhar; Azhar Ali, Syed Saad

2017-01-01

Treatment management for Major Depressive Disorder (MDD) has been challenging. However, electroencephalogram (EEG)-based predictions of antidepressant’s treatment outcome may help during antidepressant’s selection and ultimately improve the quality of life for MDD patients. In this study, a machine learning (ML) method involving pretreatment EEG data was proposed to perform such predictions for Selective Serotonin Reuptake Inhibitor (SSRIs). For this purpose, the acquisition of experimental data involved 34 MDD patients and 30 healthy controls. Consequently, a feature matrix was constructed involving time-frequency decomposition of EEG data based on wavelet transform (WT) analysis, termed as EEG data matrix. However, the resultant EEG data matrix had high dimensionality. Therefore, dimension reduction was performed based on a rank-based feature selection method according to a criterion, i.e., receiver operating characteristic (ROC). As a result, the most significant features were identified and further be utilized during the training and testing of a classification model, i.e., the logistic regression (LR) classifier. Finally, the LR model was validated with 100 iterations of 10-fold cross-validation (10-CV). The classification results were compared with short-time Fourier transform (STFT) analysis, and empirical mode decompositions (EMD). The wavelet features extracted from frontal and temporal EEG data were found statistically significant. In comparison with other time-frequency approaches such as the STFT and EMD, the WT analysis has shown highest classification accuracy, i.e., accuracy = 87.5%, sensitivity = 95%, and specificity = 80%. In conclusion, significant wavelet coefficients extracted from frontal and temporal pre-treatment EEG data involving delta and theta frequency bands may predict antidepressant’s treatment outcome for the MDD patients. PMID:28152063

Ultra high molecular weight polyethylene: Optical features at millimeter wavelengths

NASA Astrophysics Data System (ADS)

D'Alessandro, G.; Paiella, A.; Coppolecchia, A.; Castellano, M. G.; Colantoni, I.; de Bernardis, P.; Lamagna, L.; Masi, S.

2018-05-01

The next generation of experiments for the measurement of the Cosmic Microwave Background (CMB) requires more and more the use of advanced materials, with specific physical and structural properties. An example is the material used for receiver's cryostat windows and internal lenses. The large throughput of current CMB experiments requires a large diameter (of the order of 0.5 m) of these parts, resulting in heavy structural and optical requirements on the material to be used. Ultra High Molecular Weight (UHMW) polyethylene (PE) features high resistance to traction and good transmissivity in the frequency range of interest. In this paper, we discuss the possibility of using UHMW PE for windows and lenses in experiments working at millimeter wavelengths, by measuring its optical properties: emissivity, transmission and refraction index. Our measurements show that the material is well suited to this purpose.

Obstructive Sleep Apnea in Women: Study of Speech and Craniofacial Characteristics

PubMed Central

Tyan, Marina; Fernández Pozo, Rubén; Toledano, Doroteo; Lopez Gonzalo, Eduardo; Alcazar Ramirez, Jose Daniel; Hernandez Gomez, Luis Alfonso

2017-01-01

Background Obstructive sleep apnea (OSA) is a common sleep disorder characterized by frequent cessation of breathing lasting 10 seconds or longer. The diagnosis of OSA is performed through an expensive procedure, which requires an overnight stay at the hospital. This has led to several proposals based on the analysis of patients’ facial images and speech recordings as an attempt to develop simpler and cheaper methods to diagnose OSA. Objective The objective of this study was to analyze possible relationships between OSA and speech and facial features on a female population and whether these possible connections may be affected by the specific clinical characteristics in OSA population and, more specifically, to explore how the connection between OSA and speech and facial features can be affected by gender. Methods All the subjects are Spanish subjects suspected to suffer from OSA and referred to a sleep disorders unit. Voice recordings and photographs were collected in a supervised but not highly controlled way, trying to test a scenario close to a realistic clinical practice scenario where OSA is assessed using an app running on a mobile device. Furthermore, clinical variables such as weight, height, age, and cervical perimeter, which are usually reported as predictors of OSA, were also gathered. Acoustic analysis is centered in sustained vowels. Facial analysis consists of a set of local craniofacial features related to OSA, which were extracted from images after detecting facial landmarks by using the active appearance models. To study the probable OSA connection with speech and craniofacial features, correlations among apnea-hypopnea index (AHI), clinical variables, and acoustic and facial measurements were analyzed. Results The results obtained for female population indicate mainly weak correlations (r values between .20 and .39). Correlations between AHI, clinical variables, and speech features show the prevalence of formant frequencies over bandwidths, with F2/i/ being the most appropriate formant frequency for OSA prediction in women. Results obtained for male population indicate mainly very weak correlations (r values between .01 and .19). In this case, bandwidths prevail over formant frequencies. Correlations between AHI, clinical variables, and craniofacial measurements are very weak. Conclusions In accordance with previous studies, some clinical variables are found to be good predictors of OSA. Besides, strong correlations are found between AHI and some clinical variables with speech and facial features. Regarding speech feature, the results show the prevalence of formant frequency F2/i/ over the rest of features for the female population as OSA predictive feature. Although the correlation reported is weak, this study aims to find some traces that could explain the possible connection between OSA and speech in women. In the case of craniofacial measurements, results evidence that some features that can be used for predicting OSA in male patients are not suitable for testing female population. PMID:29109068

The effect of gamma-enhancing binaural beats on the control of feature bindings.

PubMed

Colzato, Lorenza S; Steenbergen, Laura; Sellaro, Roberta

2017-07-01

Binaural beats represent the auditory experience of an oscillating sound that occurs when two sounds with neighboring frequencies are presented to one's left and right ear separately. Binaural beats have been shown to impact information processing via their putative role in increasing neural synchronization. Recent studies of feature-repetition effects demonstrated interactions between perceptual features and action-related features: repeating only some, but not all features of a perception-action episode hinders performance. These partial-repetition (or binding) costs point to the existence of temporary episodic bindings (event files) that are automatically retrieved by repeating at least one of their features. Given that neural synchronization in the gamma band has been associated with visual feature bindings, we investigated whether the impact of binaural beats extends to the top-down control of feature bindings. Healthy adults listened to gamma-frequency (40 Hz) binaural beats or to a constant tone of 340 Hz (control condition) for ten minutes before and during a feature-repetition task. While the size of visuomotor binding costs (indicating the binding of visual and action features) was unaffected by the binaural beats, the size of visual feature binding costs (which refer to the binding between the two visual features) was considerably smaller during gamma-frequency binaural beats exposure than during the control condition. Our results suggest that binaural beats enhance selectivity in updating episodic memory traces and further strengthen the hypothesis that neural activity in the gamma band is critically associated with the control of feature binding.

High performance mode locking characteristics of single section quantum dash lasers.

PubMed

Rosales, Ricardo; Murdoch, S G; Watts, R T; Merghem, K; Martinez, Anthony; Lelarge, Francois; Accard, Alain; Barry, L P; Ramdane, Abderrahim

2012-04-09

Mode locking features of single section quantum dash based lasers are investigated. Particular interest is given to the static spectral phase profile determining the shape of the mode locked pulses. The phase profile dependence on cavity length and injection current is experimentally evaluated, demonstrating the possibility of efficiently using the wide spectral bandwidth exhibited by these quantum dash structures for the generation of high peak power sub-picosecond pulses with low radio frequency linewidths.

Death-associated protein kinase promoter methylation correlates with clinicopathological and prognostic features in nonsmall cell lung cancer patients: A cohort study.

PubMed

Yang, Xiao-Yu; Zhang, Jun; Yu, Xiao-Ling; Zheng, Guo-Feng; Zhao, Fei; Jia, Xiao-Jing

2018-01-01

The objective was to study the correlation between death-associated protein kinase (DAPK) promoter methylation and the clinicopathological and prognostic features in nonsmall cell lung cancer (NSCLC) patients. A total of 117 NSCLC patients were recruited into our study between December 2012 and December 2014. Methylation-specific polymerase chain reaction was employed to detect the methylation status of DAPK in cancer tissues, peficancerous tissues, and serum samples of 117 NSCLC patients. In addition, serum samples of 115 healthy subjects were analyzed as controls. A literature search of English and Chinese databases, based on predefined criteria, identified published studies closely related to this study. Data were extracted, and meta-analysis was performed using STATA 12.0 software (STATA Corporation, College Station, TX, USA). Our study results showed that DAPK promoter methylation frequency was significantly higher in NSCLC tissues compared to peficancerous normal tissues (58.1% vs. 12.8%, χ 2 = 52.45, P < 0.001). When serum samples were compared, DAPK methylation frequency in NSCLC patients was higher than the control group (27.4% vs. 0, χ 2 = 37.07, P < 0.001). Our meta-analysis results demonstrated that DAPK methylation frequency was lower in tumor node metastasis (TNM) stage I-II compared to TNM stage III-IV (relative risk [RR] =0.87, 95% confidence interval [CI] =0.76-0.99, P = 0.041). DAPK promoter methylation frequency in NSCLC patients with lymph node metastasis was significantly higher compared to the patients with no metastases (RR = 1.26, 95% CI = 1.04-1.52, P = 0.020). Finally, the 5-year survival rate was lower in NSCLC patient group with high frequency of DAPK methylation, compared to the patient group with unmethylated DAPK (RR = 0.71, 95% CI = 0.56-0.89, P = 0.004). Our results showed that DAPK promoter methylation is tightly correlated with clinicopathological features of NSCLC and is associated with poor prognosis in patients.

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.

Fast multi-scale feature fusion for ECG heartbeat classification

NASA Astrophysics Data System (ADS)

Ai, Danni; Yang, Jian; Wang, Zeyu; Fan, Jingfan; Ai, Changbin; Wang, Yongtian

2015-12-01

Electrocardiogram (ECG) is conducted to monitor the electrical activity of the heart by presenting small amplitude and duration signals; as a result, hidden information present in ECG data is difficult to determine. However, this concealed information can be used to detect abnormalities. In our study, a fast feature-fusion method of ECG heartbeat classification based on multi-linear subspace learning is proposed. The method consists of four stages. First, baseline and high frequencies are removed to segment heartbeat. Second, as an extension of wavelets, wavelet-packet decomposition is conducted to extract features. With wavelet-packet decomposition, good time and frequency resolutions can be provided simultaneously. Third, decomposed confidences are arranged as a two-way tensor, in which feature fusion is directly implemented with generalized N dimensional ICA (GND-ICA). In this method, co-relationship among different data information is considered, and disadvantages of dimensionality are prevented; this method can also be used to reduce computing compared with linear subspace-learning methods (PCA). Finally, support vector machine (SVM) is considered as a classifier in heartbeat classification. In this study, ECG records are obtained from the MIT-BIT arrhythmia database. Four main heartbeat classes are used to examine the proposed algorithm. Based on the results of five measurements, sensitivity, positive predictivity, accuracy, average accuracy, and t-test, our conclusion is that a GND-ICA-based strategy can be used to provide enhanced ECG heartbeat classification. Furthermore, large redundant features are eliminated, and classification time is reduced.

Interspecific variation of warning calls in piranhas: a comparative analysis.

PubMed

Mélotte, Geoffrey; Vigouroux, Régis; Michel, Christian; Parmentier, Eric

2016-10-26

Fish sounds are known to be species-specific, possessing unique temporal and spectral features. We have recorded and compared sounds in eight piranha species to evaluate the potential role of acoustic communication as a driving force in clade diversification. All piranha species showed the same kind of sound-producing mechanism: sonic muscles originate on vertebrae and attach to a tendon surrounding the bladder ventrally. Contractions of the sound-producing muscles force swimbladder vibration and dictate the fundamental frequency. It results the calling features of the eight piranha species logically share many common characteristics. In all the species, the calls are harmonic sounds composed of multiple continuous cycles. However, the sounds of Serrasalmus elongatus (higher number of cycles and high fundamental frequency) and S. manueli (long cycle periods and low fundamental frequency) are clearly distinguishable from the other species. The sonic mechanism being largely conserved throughout piranha evolution, acoustic communication can hardly be considered as the main driving force in the diversification process. However, sounds of some species are clearly distinguishable despite the short space for variations supporting the need for specific communication. Behavioural studies are needed to clearly understand the eventual role of the calls during spawning events.

Quantitative theory of driven nonlinear brain dynamics.

PubMed

Roberts, J A; Robinson, P A

2012-09-01

Strong periodic stimuli such as bright flashing lights evoke nonlinear responses in the brain and interact nonlinearly with ongoing cortical activity, but the underlying mechanisms for these phenomena are poorly understood at present. The dominant features of these experimentally observed dynamics are reproduced by the dynamics of a quantitative neural field model subject to periodic drive. Model power spectra over a range of drive frequencies show agreement with multiple features of experimental measurements, exhibiting nonlinear effects including entrainment over a range of frequencies around the natural alpha frequency f(α), subharmonic entrainment near 2f(α), and harmonic generation. Further analysis of the driven dynamics as a function of the drive parameters reveals rich nonlinear dynamics that is predicted to be observable in future experiments at high drive amplitude, including period doubling, bistable phase-locking, hysteresis, wave mixing, and chaos indicated by positive Lyapunov exponents. Moreover, photosensitive seizures are predicted for physiologically realistic model parameters yielding bistability between healthy and seizure dynamics. These results demonstrate the applicability of neural field models to the new regime of periodically driven nonlinear dynamics, enabling interpretation of experimental data in terms of specific generating mechanisms and providing new tests of the theory. Copyright © 2012 Elsevier Inc. All rights reserved.

High-spatial-resolution sub-surface imaging using a laser-based acoustic microscopy technique.

PubMed

Balogun, Oluwaseyi; Cole, Garrett D; Huber, Robert; Chinn, Diane; Murray, Todd W; Spicer, James B

2011-01-01

Scanning acoustic microscopy techniques operating at frequencies in the gigahertz range are suitable for the elastic characterization and interior imaging of solid media with micrometer-scale spatial resolution. Acoustic wave propagation at these frequencies is strongly limited by energy losses, particularly from attenuation in the coupling media used to transmit ultrasound to a specimen, leading to a decrease in the depth in a specimen that can be interrogated. In this work, a laser-based acoustic microscopy technique is presented that uses a pulsed laser source for the generation of broadband acoustic waves and an optical interferometer for detection. The use of a 900-ps microchip pulsed laser facilitates the generation of acoustic waves with frequencies extending up to 1 GHz which allows for the resolution of micrometer-scale features in a specimen. Furthermore, the combination of optical generation and detection approaches eliminates the use of an ultrasonic coupling medium, and allows for elastic characterization and interior imaging at penetration depths on the order of several hundred micrometers. Experimental results illustrating the use of the laser-based acoustic microscopy technique for imaging micrometer-scale subsurface geometrical features in a 70-μm-thick single-crystal silicon wafer with a (100) orientation are presented.

Interspecific variation of warning calls in piranhas: a comparative analysis

PubMed Central

Mélotte, Geoffrey; Vigouroux, Régis; Michel, Christian; Parmentier, Eric

2016-01-01

Fish sounds are known to be species-specific, possessing unique temporal and spectral features. We have recorded and compared sounds in eight piranha species to evaluate the potential role of acoustic communication as a driving force in clade diversification. All piranha species showed the same kind of sound-producing mechanism: sonic muscles originate on vertebrae and attach to a tendon surrounding the bladder ventrally. Contractions of the sound-producing muscles force swimbladder vibration and dictate the fundamental frequency. It results the calling features of the eight piranha species logically share many common characteristics. In all the species, the calls are harmonic sounds composed of multiple continuous cycles. However, the sounds of Serrasalmus elongatus (higher number of cycles and high fundamental frequency) and S. manueli (long cycle periods and low fundamental frequency) are clearly distinguishable from the other species. The sonic mechanism being largely conserved throughout piranha evolution, acoustic communication can hardly be considered as the main driving force in the diversification process. However, sounds of some species are clearly distinguishable despite the short space for variations supporting the need for specific communication. Behavioural studies are needed to clearly understand the eventual role of the calls during spawning events. PMID:27782184

Image fusion method based on regional feature and improved bidimensional empirical mode decomposition

NASA Astrophysics Data System (ADS)

Qin, Xinqiang; Hu, Gang; Hu, Kai

2018-01-01

The decomposition of multiple source images using bidimensional empirical mode decomposition (BEMD) often produces mismatched bidimensional intrinsic mode functions, either by their number or their frequency, making image fusion difficult. A solution to this problem is proposed using a fixed number of iterations and a union operation in the sifting process. By combining the local regional features of the images, an image fusion method has been developed. First, the source images are decomposed using the proposed BEMD to produce the first intrinsic mode function (IMF) and residue component. Second, for the IMF component, a selection and weighted average strategy based on local area energy is used to obtain a high-frequency fusion component. Third, for the residue component, a selection and weighted average strategy based on local average gray difference is used to obtain a low-frequency fusion component. Finally, the fused image is obtained by applying the inverse BEMD transform. Experimental results show that the proposed algorithm provides superior performance over methods based on wavelet transform, line and column-based EMD, and complex empirical mode decomposition, both in terms of visual quality and objective evaluation criteria.

Efferent innervation to the auditory basilar papilla of scincid lizards.

PubMed

Wibowo, Erik; Brockhausen, Jennifer; Köppl, Christine

2009-09-01

Hair cells of the inner ear of vertebrates are innervated by afferent neurons that transmit sensory information to the brain as well as efferent neurons that receive feedback from the brainstem. The function of the efferent feedback system is poorly understood and may have changed during evolution when different tetrapod groups acquired sensitivity to airborne sound and extended their hearing ranges to higher frequencies. Lizards show a unique subdivision of their basilar papilla (homologous to the mammalian organ of Corti) into a low-frequency (<1 kHz) and a high-frequency (approximately 1-5 kHz) region. The high-frequency region was reported to have lost its efferent innervation, suggesting it was insignificant or even functionally detrimental at higher frequencies. We re-examined the innervation to the basilar papilla of five species of Australian scincid lizards, by using immunohistochemistry. Anti-choline acetyltransferase (ChAT) was used as an efferent marker. Co-localization with anti-synaptic vesicle protein 2 confirmed the synaptic identity of label. Cholinergic terminals were observed along the whole length of the basilar papilla, including the regions that had previously been described as devoid of efferent innervation. However, there was a clear decrease in terminal density from apical, low-frequency to basal, high-frequency locations. Our findings suggest that efferent innervation is a general feature of the hair cells in the basilar papilla of lizards, irrespective of tonotopic location. This re-enforces the notion that efferent feedback control of hair cells is a fundamental and important property of all vertebrate hearing organs. (c) 2009 Wiley-Liss, Inc.

Detecting phase-amplitude coupling with high frequency resolution using adaptive decompositions

PubMed Central

Pittman-Polletta, Benjamin; Hsieh, Wan-Hsin; Kaur, Satvinder; Lo, Men-Tzung; Hu, Kun

2014-01-01

Background Phase-amplitude coupling (PAC) – the dependence of the amplitude of one rhythm on the phase of another, lower-frequency rhythm – has recently been used to illuminate cross-frequency coordination in neurophysiological activity. An essential step in measuring PAC is decomposing data to obtain rhythmic components of interest. Current methods of PAC assessment employ narrowband Fourier-based filters, which assume that biological rhythms are stationary, harmonic oscillations. However, biological signals frequently contain irregular and nonstationary features, which may contaminate rhythms of interest and complicate comodulogram interpretation, especially when frequency resolution is limited by short data segments. New method To better account for nonstationarities while maintaining sharp frequency resolution in PAC measurement, even for short data segments, we introduce a new method of PAC assessment which utilizes adaptive and more generally broadband decomposition techniques – such as the empirical mode decomposition (EMD). To obtain high frequency resolution PAC measurements, our method distributes the PAC associated with pairs of broadband oscillations over frequency space according to the time-local frequencies of these oscillations. Comparison with existing methods We compare our novel adaptive approach to a narrowband comodulogram approach on a variety of simulated signals of short duration, studying systematically how different types of nonstationarities affect these methods, as well as on EEG data. Conclusions Our results show: (1) narrowband filtering can lead to poor PAC frequency resolution, and inaccuracy and false negatives in PAC assessment; (2) our adaptive approach attains better PAC frequency resolution and is more resistant to nonstationarities and artifacts than traditional comodulograms. PMID:24452055

Bivariate empirical mode decomposition for ECG-based biometric identification with emotional data.

PubMed

Ferdinando, Hany; Seppanen, Tapio; Alasaarela, Esko

2017-07-01

Emotions modulate ECG signals such that they might affect ECG-based biometric identification in real life application. It motivated in finding good feature extraction methods where the emotional state of the subjects has minimum impacts. This paper evaluates feature extraction based on bivariate empirical mode decomposition (BEMD) for biometric identification when emotion is considered. Using the ECG signal from the Mahnob-HCI database for affect recognition, the features were statistical distributions of dominant frequency after applying BEMD analysis to ECG signals. The achieved accuracy was 99.5% with high consistency using kNN classifier in 10-fold cross validation to identify 26 subjects when the emotional states of the subjects were ignored. When the emotional states of the subject were considered, the proposed method also delivered high accuracy, around 99.4%. We concluded that the proposed method offers emotion-independent features for ECG-based biometric identification. The proposed method needs more evaluation related to testing with other classifier and variation in ECG signals, e.g. normal ECG vs. ECG with arrhythmias, ECG from various ages, and ECG from other affective databases.

Radar signal analysis of ballistic missile with micro-motion based on time-frequency distribution

NASA Astrophysics Data System (ADS)

Wang, Jianming; Liu, Lihua; Yu, Hua

2015-12-01

The micro-motion of ballistic missile targets induces micro-Doppler modulation on the radar return signal, which is a unique feature for the warhead discrimination during flight. In order to extract the micro-Doppler feature of ballistic missile targets, time-frequency analysis is employed to process the micro-Doppler modulated time-varying radar signal. The images of time-frequency distribution (TFD) reveal the micro-Doppler modulation characteristic very well. However, there are many existing time-frequency analysis methods to generate the time-frequency distribution images, including the short-time Fourier transform (STFT), Wigner distribution (WD) and Cohen class distribution, etc. Under the background of ballistic missile defence, the paper aims at working out an effective time-frequency analysis method for ballistic missile warhead discrimination from the decoys.

A Hybrid Approach to Detect Driver Drowsiness Utilizing Physiological Signals to Improve System Performance and Wearability.

PubMed

Awais, Muhammad; Badruddin, Nasreen; Drieberg, Micheal

2017-08-31

Driver drowsiness is a major cause of fatal accidents, injury, and property damage, and has become an area of substantial research attention in recent years. The present study proposes a method to detect drowsiness in drivers which integrates features of electrocardiography (ECG) and electroencephalography (EEG) to improve detection performance. The study measures differences between the alert and drowsy states from physiological data collected from 22 healthy subjects in a driving simulator-based study. A monotonous driving environment is used to induce drowsiness in the participants. Various time and frequency domain feature were extracted from EEG including time domain statistical descriptors, complexity measures and power spectral measures. Features extracted from the ECG signal included heart rate (HR) and heart rate variability (HRV), including low frequency (LF), high frequency (HF) and LF/HF ratio. Furthermore, subjective sleepiness scale is also assessed to study its relationship with drowsiness. We used paired t -tests to select only statistically significant features ( p < 0.05), that can differentiate between the alert and drowsy states effectively. Significant features of both modalities (EEG and ECG) are then combined to investigate the improvement in performance using support vector machine (SVM) classifier. The other main contribution of this paper is the study on channel reduction and its impact to the performance of detection. The proposed method demonstrated that combining EEG and ECG has improved the system's performance in discriminating between alert and drowsy states, instead of using them alone. Our channel reduction analysis revealed that an acceptable level of accuracy (80%) could be achieved by combining just two electrodes (one EEG and one ECG), indicating the feasibility of a system with improved wearability compared with existing systems involving many electrodes. Overall, our results demonstrate that the proposed method can be a viable solution for a practical driver drowsiness system that is both accurate and comfortable to wear.

A Hybrid Approach to Detect Driver Drowsiness Utilizing Physiological Signals to Improve System Performance and Wearability

PubMed Central

Badruddin, Nasreen

2017-01-01

Driver drowsiness is a major cause of fatal accidents, injury, and property damage, and has become an area of substantial research attention in recent years. The present study proposes a method to detect drowsiness in drivers which integrates features of electrocardiography (ECG) and electroencephalography (EEG) to improve detection performance. The study measures differences between the alert and drowsy states from physiological data collected from 22 healthy subjects in a driving simulator-based study. A monotonous driving environment is used to induce drowsiness in the participants. Various time and frequency domain feature were extracted from EEG including time domain statistical descriptors, complexity measures and power spectral measures. Features extracted from the ECG signal included heart rate (HR) and heart rate variability (HRV), including low frequency (LF), high frequency (HF) and LF/HF ratio. Furthermore, subjective sleepiness scale is also assessed to study its relationship with drowsiness. We used paired t-tests to select only statistically significant features (p < 0.05), that can differentiate between the alert and drowsy states effectively. Significant features of both modalities (EEG and ECG) are then combined to investigate the improvement in performance using support vector machine (SVM) classifier. The other main contribution of this paper is the study on channel reduction and its impact to the performance of detection. The proposed method demonstrated that combining EEG and ECG has improved the system’s performance in discriminating between alert and drowsy states, instead of using them alone. Our channel reduction analysis revealed that an acceptable level of accuracy (80%) could be achieved by combining just two electrodes (one EEG and one ECG), indicating the feasibility of a system with improved wearability compared with existing systems involving many electrodes. Overall, our results demonstrate that the proposed method can be a viable solution for a practical driver drowsiness system that is both accurate and comfortable to wear. PMID:28858220

How is depression experienced around the world? A systematic review of qualitative literature

PubMed Central

Haroz, E.E.; Ritchey, M.; Bass, J.K.; Kohrt, B.A.; Augustinavicius, J.; Michalopoulos, L.; Burkey, M.D.; Bolton, P.

2017-01-01

To date global research on depression has used assessment tools based on research and clinical experience drawn from Western populations (i.e., in North American, European and Australian). There may be features of depression in non-Western populations which are not captured in current diagnostic criteria or measurement tools, as well as criteria for depression that are not relevant in other regions. We investigated this possibility through a systematic review of qualitative studies of depression worldwide. Nine online databases were searched for records that used qualitative methods to study depression. Initial searches were conducted between August 2012 and December 2012; an updated search was repeated in June of 2015 to include relevant literature published between December 30, 2012 and May 30, 2015. No date limits were set for inclusion of articles. A total of 16,130 records were identified and 138 met full inclusion criteria. Included studies were published between 1976 and 2015. These 138 studies represented data on 170 different study populations (some reported on multiple samples) and 77 different nationalities/ethnicities. Variation in results by geographical region, gender, and study context were examined to determine the consistency of descriptions across populations. Fisher’s exact tests were used to compare frequencies of features across region, gender and context. Seven of the 15 features with the highest relative frequency form part of the DSM-5 diagnosis of Major Depressive Disorder (MDD). However, many of the other features with relatively high frequencies across the studies are associated features in the DSM, but are not prioritized as diagnostic criteria and therefore not included in standard instruments. The DSM-5 diagnostic criteria of problems with concentration and psychomotor agitation or slowing were infrequently mentioned. This research suggests that the DSM model and standard instruments currently based on the DSM may not adequately reflect the experience of depression at the worldwide or regional levels. PMID:28069271

How is depression experienced around the world? A systematic review of qualitative literature.

PubMed

Haroz, E E; Ritchey, M; Bass, J K; Kohrt, B A; Augustinavicius, J; Michalopoulos, L; Burkey, M D; Bolton, P

2017-06-01

To date global research on depression has used assessment tools based on research and clinical experience drawn from Western populations (i.e., in North American, European and Australian). There may be features of depression in non-Western populations which are not captured in current diagnostic criteria or measurement tools, as well as criteria for depression that are not relevant in other regions. We investigated this possibility through a systematic review of qualitative studies of depression worldwide. Nine online databases were searched for records that used qualitative methods to study depression. Initial searches were conducted between August 2012 and December 2012; an updated search was repeated in June of 2015 to include relevant literature published between December 30, 2012 and May 30, 2015. No date limits were set for inclusion of articles. A total of 16,130 records were identified and 138 met full inclusion criteria. Included studies were published between 1976 and 2015. These 138 studies represented data on 170 different study populations (some reported on multiple samples) and 77 different nationalities/ethnicities. Variation in results by geographical region, gender, and study context were examined to determine the consistency of descriptions across populations. Fisher's exact tests were used to compare frequencies of features across region, gender and context. Seven of the 15 features with the highest relative frequency form part of the DSM-5 diagnosis of Major Depressive Disorder (MDD). However, many of the other features with relatively high frequencies across the studies are associated features in the DSM, but are not prioritized as diagnostic criteria and therefore not included in standard instruments. The DSM-5 diagnostic criteria of problems with concentration and psychomotor agitation or slowing were infrequently mentioned. This research suggests that the DSM model and standard instruments currently based on the DSM may not adequately reflect the experience of depression at the worldwide or regional levels. Copyright © 2016 Elsevier Ltd. All rights reserved.

Anatomical evidence for low frequency sensitivity in an archaeocete whale: comparison of the inner ear of Zygorhiza kochii with that of crown Mysticeti.

PubMed

Ekdale, Eric G; Racicot, Rachel A

2015-01-01

The evolution of hearing in cetaceans is a matter of current interest given that odontocetes (toothed whales) are sensitive to high frequency sounds and mysticetes (baleen whales) are sensitive to low and potentially infrasonic noises. Earlier diverging stem cetaceans (archaeocetes) were hypothesized to have had either low or high frequency sensitivity. Through CT scanning, the morphology of the bony labyrinth of the basilosaurid archaeocete Zygorhiza kochii is described and compared to novel information from the inner ears of mysticetes, which are less known than the inner ears of odontocetes. Further comparisons are made with published information for other cetaceans. The anatomy of the cochlea of Zygorhiza is in line with mysticetes and supports the hypothesis that Zygorhiza was sensitive to low frequency noises. Morphological features that support the low frequency hypothesis and are shared by Zygorhiza and mysticetes include a long cochlear canal with a high number of turns, steeply graded curvature of the cochlear spiral in which the apical turn is coiled tighter than the basal turn, thin walls separating successive turns that overlap in vestibular view, and reduction of the secondary bony lamina. Additional morphology of the vestibular system indicates that Zygorhiza was more sensitive to head rotations than extant mysticetes are, which likely indicates higher agility in the ancestral taxon. © 2014 Anatomical Society.

Anatomical evidence for low frequency sensitivity in an archaeocete whale: comparison of the inner ear of Zygorhiza kochii with that of crown Mysticeti

PubMed Central

Ekdale, Eric G; Racicot, Rachel A

2015-01-01

The evolution of hearing in cetaceans is a matter of current interest given that odontocetes (toothed whales) are sensitive to high frequency sounds and mysticetes (baleen whales) are sensitive to low and potentially infrasonic noises. Earlier diverging stem cetaceans (archaeocetes) were hypothesized to have had either low or high frequency sensitivity. Through CT scanning, the morphology of the bony labyrinth of the basilosaurid archaeocete Zygorhiza kochii is described and compared to novel information from the inner ears of mysticetes, which are less known than the inner ears of odontocetes. Further comparisons are made with published information for other cetaceans. The anatomy of the cochlea of Zygorhiza is in line with mysticetes and supports the hypothesis that Zygorhiza was sensitive to low frequency noises. Morphological features that support the low frequency hypothesis and are shared by Zygorhiza and mysticetes include a long cochlear canal with a high number of turns, steeply graded curvature of the cochlear spiral in which the apical turn is coiled tighter than the basal turn, thin walls separating successive turns that overlap in vestibular view, and reduction of the secondary bony lamina. Additional morphology of the vestibular system indicates that Zygorhiza was more sensitive to head rotations than extant mysticetes are, which likely indicates higher agility in the ancestral taxon. PMID:25400023

All solid-state high power microwave source with high repetition frequency.

PubMed

Bragg, J-W B; Sullivan, W W; Mauch, D; Neuber, A A; Dickens, J C

2013-05-01

An all solid-state, megawatt-class high power microwave system featuring a silicon carbide (SiC) photoconductive semiconductor switch (PCSS) and a ferrimagnetic-based, coaxial nonlinear transmission line (NLTL) is presented. A 1.62 cm(2), 50 kV 4H-SiC PCSS is hard-switched to produce electrical pulses with 7 ns full width-half max (FWHM) pulse widths at 2 ns risetimes in single shot and burst-mode operation. The PCSS resistance drops to sub-ohm when illuminated with approximately 3 mJ of laser energy at 355 nm (tripled Nd:YAG) in a single pulse. Utilizing a fiber optic based optical delivery system, a laser pulse train of four 7 ns (FWHM) signals was generated at 65 MHz repetition frequency. The resulting electrical pulse train from the PCSS closely follows the optical input and is utilized to feed the NLTL generating microwave pulses with a base microwave-frequency of about 2.1 GHz at 65 MHz pulse repetition frequency (prf). Under typical experimental conditions, the NLTL produces sharpened output risetimes of 120 ps and microwave oscillations at 2-4 GHz that are generated due to damped gyromagnetic precession of the ferrimagnetic material's axially pre-biased magnetic moments. The complete system is discussed in detail with its output matched into 50 Ω, and results covering MHz-prf in burst-mode operation as well as frequency agility in single shot operation are discussed.

Reduced high-frequency motor neuron firing, EMG fractionation, and gait variability in awake walking ALS mice

PubMed Central

Hadzipasic, Muhamed; Ni, Weiming; Nagy, Maria; Steenrod, Natalie; McGinley, Matthew J.; Kaushal, Adi; Thomas, Eleanor; McCormick, David A.

2016-01-01

Amyotrophic lateral sclerosis (ALS) is a lethal neurodegenerative disease prominently featuring motor neuron (MN) loss and paralysis. A recent study using whole-cell patch clamp recording of MNs in acute spinal cord slices from symptomatic adult ALS mice showed that the fastest firing MNs are preferentially lost. To measure the in vivo effects of such loss, awake symptomatic-stage ALS mice performing self-initiated walking on a wheel were studied. Both single-unit extracellular recordings within spinal cord MN pools for lower leg flexor and extensor muscles and the electromyograms (EMGs) of the corresponding muscles were recorded. In the ALS mice, we observed absent or truncated high-frequency firing of MNs at the appropriate time in the step cycle and step-to-step variability of the EMG, as well as flexor-extensor coactivation. In turn, kinematic analysis of walking showed step-to-step variability of gait. At the MN level, the higher frequencies absent from recordings from mutant mice corresponded with the upper range of frequencies observed for fast-firing MNs in earlier slice measurements. These results suggest that, in SOD1-linked ALS mice, symptoms are a product of abnormal MN firing due at least in part to loss of neurons that fire at high frequency, associated with altered EMG patterns and hindlimb kinematics during gait. PMID:27821773

High Frequency SSVEP-BCI With Hardware Stimuli Control and Phase-Synchronized Comb Filter.

PubMed

Chabuda, Anna; Durka, Piotr; Zygierewicz, Jaroslaw

2018-02-01

We present an efficient implementation of brain-computer interface (BCI) based on high-frequency steady state visually evoked potentials (SSVEP). Individual shape of the SSVEP response is extracted by means of a feedforward comb filter, which adds delayed versions of the signal to itself. Rendering of the stimuli is controlled by specialized hardware (BCI Appliance). Out of 15 participants of the study, nine were able to produce stable response in at least eight out of ten frequencies from the 30-39 Hz range. They achieved on average 96±4% accuracy and 47±5 bit/min information transfer rate (ITR) for an optimized simple seven-letter speller, while generic full-alphabet speller allowed in this group for 89±9% accuracy and 36±9 bit/min ITR. These values exceed the performances of high-frequency SSVEP-BCI systems reported to date. Classical approach to SSVEP parameterization by relative spectral power in the frequencies of stimulation, implemented on the same data, resulted in significantly lower performance. This suggests that specific shape of the response is an important feature in classification. Finally, we discuss the differences in SSVEP responses of the participants who were able or unable to use the interface, as well as the statistically significant influence of the layout of the speller on the speed of BCI operation.

The communicative potential of bat echolocation pulses.

PubMed

Jones, Gareth; Siemers, Björn M

2011-05-01

Ecological constraints often shape the echolocation pulses emitted by bat species. Consequently some (but not all) bats emit species-specific echolocation pulses. Because echolocation pulses are often intense and emitted at high rates, they are potential targets for eavesdropping by other bats. Echolocation pulses can also vary within species according to sex, body size, age, social group and geographic location. Whether these features can be recognised by other bats can only be determined reliably by playback experiments, which have shown that echolocation pulses do provide sufficient information for the identification of sex and individual in one species. Playbacks also show that bats can locate conspecifics and heterospecifics at foraging and roost sites by eavesdropping on echolocation pulses. Guilds of echolocating bat species often partition their use of pulse frequencies. Ecology, allometric scaling and phylogeny play roles here, but are not sufficient to explain this partitioning. Evidence is accumulating to support the hypothesis that frequency partitioning evolved to facilitate intraspecific communication. Acoustic character displacement occurs in at least one instance. Future research can relate genetic population structure to regional variation in echolocation pulse features and elucidate those acoustic features that most contribute to discrimination of individuals.

Modeling and evaluation of a high-resolution CMOS detector for cone-beam CT of the extremities.

PubMed

Cao, Qian; Sisniega, Alejandro; Brehler, Michael; Stayman, J Webster; Yorkston, John; Siewerdsen, Jeffrey H; Zbijewski, Wojciech

2018-01-01

Quantitative assessment of trabecular bone microarchitecture in extremity cone-beam CT (CBCT) would benefit from the high spatial resolution, low electronic noise, and fast scan time provided by complementary metal-oxide semiconductor (CMOS) x-ray detectors. We investigate the performance of CMOS sensors in extremity CBCT, in particular with respect to potential advantages of thin (<0.7 mm) scintillators offering higher spatial resolution. A cascaded systems model of a CMOS x-ray detector incorporating the effects of CsI:Tl scintillator thickness was developed. Simulation studies were performed using nominal extremity CBCT acquisition protocols (90 kVp, 0.126 mAs/projection). A range of scintillator thickness (0.35-0.75 mm), pixel size (0.05-0.4 mm), focal spot size (0.05-0.7 mm), magnification (1.1-2.1), and dose (15-40 mGy) was considered. The detectability index was evaluated for both CMOS and a-Si:H flat-panel detector (FPD) configurations for a range of imaging tasks emphasizing spatial frequencies associated with feature size aobj. Experimental validation was performed on a CBCT test bench in the geometry of a compact orthopedic CBCT system (SAD = 43.1 cm, SDD = 56.0 cm, matching that of the Carestream OnSight 3D system). The test-bench studies involved a 0.3 mm focal spot x-ray source and two CMOS detectors (Dalsa Xineos-3030HR, 0.099 mm pixel pitch) - one with the standard CsI:Tl thickness of 0.7 mm (C700) and one with a custom 0.4 mm thick scintillator (C400). Measurements of modulation transfer function (MTF), detective quantum efficiency (DQE), and CBCT scans of a cadaveric knee (15 mGy) were obtained for each detector. Optimal detectability for high-frequency tasks (feature size of ~0.06 mm, consistent with the size of trabeculae) was ~4× for the C700 CMOS detector compared to the a-Si:H FPD at nominal system geometry of extremity CBCT. This is due to ~5× lower electronic noise of a CMOS sensor, which enables input quantum-limited imaging at smaller pixel size. Optimal pixel size for high-frequency tasks was <0.1 mm for a CMOS, compared to ~0.14 mm for an a-Si:H FPD. For this fine pixel pitch, detectability of fine features could be improved by using a thinner scintillator to reduce light spread blur. A 22% increase in detectability of 0.06 mm features was found for the C400 configuration compared to C700. An improvement in the frequency at 50% modulation (f 50 ) of MTF was measured, increasing from 1.8 lp/mm for C700 to 2.5 lp/mm for C400. The C400 configuration also achieved equivalent or better DQE as C700 for frequencies above ~2 mm -1 . Images of cadaver specimens confirmed improved visualization of trabeculae with the C400 sensor. The small pixel size of CMOS detectors yields improved performance in high-resolution extremity CBCT compared to a-Si:H FPDs, particularly when coupled with a custom 0.4 mm thick scintillator. The results indicate that adoption of a CMOS detector in extremity CBCT can benefit applications in quantitative imaging of trabecular microstructure in humans. © 2017 American Association of Physicists in Medicine.

Plasma wave observations during ion gun experiments

NASA Astrophysics Data System (ADS)

Olsen, R. C.; Weddle, L. E.; Roeder, J. L.

1990-06-01

Experiments in charge control on the AF/NASA P78-2 (SCATHA) satellite were conducted with a plasma/ion source in the inner magnetosphere. These experiments were monitored with plasma wave instruments capable of high temporal and frequency resolution in the 0-6 kHz frequency range. Ion gun experiments revealed two distinct classes of behavior. Nonneutralized ion beam operation at 1 mA, 1kV resulted in arcing signatures (spiky in time, broad frequency range), coincident with induced satellite potentials of -600 to -900 V. This signature disappeared when the accelerating voltage was switched off or the beam was neutralized. The signal is attributed to arcing between differentially charged surfaces. An additional feature was noted in the 100-kHz channel of the wave receiver. During emission of dense, low-energy plasma, a signal is generated which may be at the upper hybrid, or plasma frequency for the local plasma.

Theory of low-power ultra-broadband terahertz sideband generation in bi-layer graphene

PubMed Central

Crosse, J. A.; Xu, Xiaodong; Sherwin, Mark S.; Liu, R. B.

2014-01-01

In a semiconductor illuminated by a strong terahertz (THz) field, optically excited electron–hole pairs can recombine to emit light in a broad frequency comb evenly spaced by twice the THz frequency. Such high-order THz sideband generation is of interest both as an example of extreme nonlinear optics and also as a method for ultrafast electro-optical modulation. So far, this phenomenon has only been observed with large field strengths (~10 kV cm−1), an obstacle for technological applications. Here we predict that bi-layer graphene generates high-order sidebands at much weaker THz fields. We find that a THz field of strength 1 kV cm−1 can produce a high-sideband spectrum of about 30 THz, 100 times broader than in GaAs. The sidebands are generated despite the absence of classical collisions, with the quantum coherence of the electron–hole pairs enabling recombination. These remarkable features lower the barrier to desktop electro-optical modulation at THz frequencies, facilitating ultrafast optical communications. PMID:25249245

Recognition memory for low- and high-frequency-filtered emotional faces: Low spatial frequencies drive emotional memory enhancement, whereas high spatial frequencies drive the emotion-induced recognition bias.

PubMed

Rohr, Michaela; Tröger, Johannes; Michely, Nils; Uhde, Alarith; Wentura, Dirk

2017-07-01

This article deals with two well-documented phenomena regarding emotional stimuli: emotional memory enhancement-that is, better long-term memory for emotional than for neutral stimuli-and the emotion-induced recognition bias-that is, a more liberal response criterion for emotional than for neutral stimuli. Studies on visual emotion perception and attention suggest that emotion-related processes can be modulated by means of spatial-frequency filtering of the presented emotional stimuli. Specifically, low spatial frequencies are assumed to play a primary role for the influence of emotion on attention and judgment. Given this theoretical background, we investigated whether spatial-frequency filtering also impacts (1) the memory advantage for emotional faces and (2) the emotion-induced recognition bias, in a series of old/new recognition experiments. Participants completed incidental-learning tasks with high- (HSF) and low- (LSF) spatial-frequency-filtered emotional and neutral faces. The results of the surprise recognition tests showed a clear memory advantage for emotional stimuli. Most importantly, the emotional memory enhancement was significantly larger for face images containing only low-frequency information (LSF faces) than for HSF faces across all experiments, suggesting that LSF information plays a critical role in this effect, whereas the emotion-induced recognition bias was found only for HSF stimuli. We discuss our findings in terms of both the traditional account of different processing pathways for HSF and LSF information and a stimulus features account. The double dissociation in the results favors the latter account-that is, an explanation in terms of differences in the characteristics of HSF and LSF stimuli.

Attentional state modulates the effect of an irrelevant stimulus dimension on perception.

PubMed

Herrmann, Björn; Johnsrude, Ingrid S

2018-01-01

Covariations of acoustic features provide redundancy in rapidly changing soundscapes: Hearing one feature enables a listener to infer another if these 2 features normally covary. However, it is unknown whether situational demands affect the degree to which covariations influence perceptual inferences. We exploited a perceptual interdependency between modulation rate and frequency and examined, in 6 experiments, whether challenging situations would alter the degree to which people rely on frequency information to make decisions about modulation rate. Participants listened to amplitude-modulated (AM) sounds with modulation rates (∼5 Hz) either decreasing or increasing over time and identified the direction of the rate change. Participants were instructed to ignore carrier frequency, which either decreased or increased (∼1,300 Hz) over time. We observed that participants were more likely to perceive the modulation rate as slowing down when frequency decreased and as speeding up when frequency increased (AM-rate change illusion). The magnitude of the illusion increased when uninformative cues (compared with informative cues) prohibited regulation of attention to sounds, and under distraction introduced by a concurrent visual motion-tracking task. The evidence suggests that the attentional state affects how strongly people rely on featural covariations to make perceptual inferences. (PsycINFO Database Record (c) 2018 APA, all rights reserved).