Estimating the seismotelluric current required for observable electromagnetic ground signals

Directory of Open Access Journals (Sweden)

J. Bortnik

2010-08-01

Full Text Available We use a relatively simple model of an underground current source co-located with the earthquake hypocenter to estimate the magnitude of the seismotelluric current required to produce observable ground signatures. The Alum Rock earthquake of 31 October 2007, is used as an archetype of a typical California earthquake, and the effects of varying the ground conductivity and length of the current element are examined. Results show that for an observed 30 nT pulse at 1 Hz, the expected seismotelluric current magnitudes fall in the range ~10–100 kA. By setting the detectability threshold to 1 pT, we show that even when large values of ground conductivity are assumed, magnetic signals are readily detectable within a range of 30 km from the epicenter. When typical values of ground conductivity are assumed, the minimum current required to produce an observable signal within a 30 km range was found to be ~1 kA, which is a surprisingly low value. Furthermore, we show that deep nulls in the signal power develop in the non-cardinal directions relative to the orientation of the source current, indicating that a magnetometer station located in those regions may not observe a signal even though it is well within the detectable range. This result underscores the importance of using a network of magnetometers when searching for preseismic electromagnetic signals.

IEDA [Intelligent Eddy Current Data Analysis] helps make sense of eddy current data [steam generators

International Nuclear Information System (INIS)

Clark, R.

1989-01-01

The increasing sophistication of eddy current signal interpretation in steam generator tubing has improved capabilities, but has also made the process of analysis more complex and time consuming. Westinghouse has developed an intelligent computerised tool - the IEDA (Intelligent Eddy Current Data Analysis) system, to lighten the load on analysts. Since 1985, 44 plants have been inspected with IEDA, representing over 400,000 tubes. The system has provided a repeatability and a consistency not achieved by human operators. (U.K.)

Wavelet analysis for nonstationary signals

International Nuclear Information System (INIS)

Penha, Rosani Maria Libardi da

1999-01-01

Mechanical vibration signals play an important role in anomalies identification resulting of equipment malfunctioning. Traditionally, Fourier spectral analysis is used where the signals are assumed to be stationary. However, occasional transient impulses and start-up process are examples of nonstationary signals that can be found in mechanical vibrations. These signals can provide important information about the equipment condition, as early fault detection. The Fourier analysis can not adequately be applied to nonstationary signals because the results provide data about the frequency composition averaged over the duration of the signal. In this work, two methods for nonstationary signal analysis are used: Short Time Fourier Transform (STFT) and wavelet transform. The STFT is a method of adapting Fourier spectral analysis for nonstationary application to time-frequency domain. To have a unique resolution throughout the entire time-frequency domain is its main limitation. The wavelet transform is a new analysis technique suitable to nonstationary signals, which handles the STFT drawbacks, providing multi-resolution frequency analysis and time localization in a unique time-scale graphic. The multiple frequency resolutions are obtained by scaling (dilatation/compression) the wavelet function. A comparison of the conventional Fourier transform, STFT and wavelet transform is made applying these techniques to: simulated signals, arrangement rotor rig vibration signal and rotate machine vibration signal Hanning window was used to STFT analysis. Daubechies and harmonic wavelets were used to continuos, discrete and multi-resolution wavelet analysis. The results show the Fourier analysis was not able to detect changes in the signal frequencies or discontinuities. The STFT analysis detected the changes in the signal frequencies, but with time-frequency resolution problems. The wavelet continuos and discrete transform demonstrated to be a high efficient tool to detect

Electronic constant current and current pulse signal generator for nuclear instrumentation testing

International Nuclear Information System (INIS)

Brown, R.A.

1994-01-01

Circuitry is described for testing the ability of an intermediate range nuclear instrument to detect and measure a constant current and a periodic current pulse. The invention simulates the resistance and capacitance of the signal connection of a nuclear instrument ion chamber detector and interconnecting cable. An LED flasher/oscillator illuminates an LED at a periodic rate established by a timing capacitor and circuitry internal to the flasher/oscillator. When the LED is on, a periodic current pulse is applied to the instrument. When the LED is off, a constant current is applied. An inductor opposes battery current flow when the LED is on. 1 figures

Signal flow analysis

CERN Document Server

Abrahams, J R; Hiller, N

1965-01-01

Signal Flow Analysis provides information pertinent to the fundamental aspects of signal flow analysis. This book discusses the basic theory of signal flow graphs and shows their relation to the usual algebraic equations.Organized into seven chapters, this book begins with an overview of properties of a flow graph. This text then demonstrates how flow graphs can be applied to a wide range of electrical circuits that do not involve amplification. Other chapters deal with the parameters as well as circuit applications of transistors. This book discusses as well the variety of circuits using ther

F-actin-based Ca signaling-a critical comparison with the current concept of Ca signaling.

Science.gov (United States)

Lange, Klaus; Gartzke, Joachim

2006-11-01

A short comparative survey on the current idea of Ca signaling and the alternative concept of F-actin-based Ca signaling is given. The two hypotheses differ in one central aspect, the mechanism of Ca storage. The current theory rests on the assumption of Ca-accumulating endoplasmic/sarcoplasmic reticulum-derived vesicles equipped with an ATP-dependent Ca pump and IP3- or ryanodine-sensitive channel-receptors for Ca-release. The alternative hypothesis proceeds from the idea of Ca storage at the high-affinity binding sites of actin filaments. Cellular sites of F-actin-based Ca storage are microvilli and the submembrane cytoskeleton. Several specific features of Ca signaling such as store-channel coupling, quantal Ca release, spiking and oscillations, biphasic and "phasic" uptake kinetics, and Ca-induced Ca release (CICR), which are not adequately described by the current concept, are inherent properties of the F-actin system and its dynamic state of treadmilling. Copyright 2006 Wiley-Liss, Inc.

Semi-classical signal analysis

KAUST Repository

Laleg-Kirati, Taous-Meriem

2012-09-30

This study introduces a new signal analysis method, based on a semi-classical approach. The main idea in this method is to interpret a pulse-shaped signal as a potential of a Schrödinger operator and then to use the discrete spectrum of this operator for the analysis of the signal. We present some numerical examples and the first results obtained with this method on the analysis of arterial blood pressure waveforms. © 2012 Springer-Verlag London Limited.

Two-dimensional signal analysis

CERN Document Server

Garello, René

2010-01-01

This title sets out to show that 2-D signal analysis has its own role to play alongside signal processing and image processing.Concentrating its coverage on those 2-D signals coming from physical sensors (such as radars and sonars), the discussion explores a 2-D spectral approach but develops the modeling of 2-D signals and proposes several data-oriented analysis techniques for dealing with them. Coverage is also given to potential future developments in this area.

A review of intelligent systems for heart sound signal analysis.

Science.gov (United States)

Nabih-Ali, Mohammed; El-Dahshan, El-Sayed A; Yahia, Ashraf S

2017-10-01

Intelligent computer-aided diagnosis (CAD) systems can enhance the diagnostic capabilities of physicians and reduce the time required for accurate diagnosis. CAD systems could provide physicians with a suggestion about the diagnostic of heart diseases. The objective of this paper is to review the recent published preprocessing, feature extraction and classification techniques and their state of the art of phonocardiogram (PCG) signal analysis. Published literature reviewed in this paper shows the potential of machine learning techniques as a design tool in PCG CAD systems and reveals that the CAD systems for PCG signal analysis are still an open problem. Related studies are compared to their datasets, feature extraction techniques and the classifiers they used. Current achievements and limitations in developing CAD systems for PCG signal analysis using machine learning techniques are presented and discussed. In the light of this review, a number of future research directions for PCG signal analysis are provided.

Isotopic identification using Pulse Shape Analysis of current signals from silicon detectors: Recent results from the FAZIA collaboration

Energy Technology Data Exchange (ETDEWEB)

Pastore, G., E-mail: pastore@fi.infn.it [Dipartimento di Fisica, Università di Firenze, via G.Sansone 1, 50019 Sesto Fiorentino (Italy); INFN Sezione di Firenze, via G.Sansone 1, 50019 Sesto Fiorentino (Italy); Gruyer, D. [INFN Sezione di Firenze, via G.Sansone 1, 50019 Sesto Fiorentino (Italy); Ottanelli, P. [Dipartimento di Fisica, Università di Firenze, via G.Sansone 1, 50019 Sesto Fiorentino (Italy); INFN Sezione di Firenze, via G.Sansone 1, 50019 Sesto Fiorentino (Italy); Le Neindre, N. [LPC Caen, Normandie Univ, ENSICAEN, UNICAEN, CNRS/IN2P3, LPC Caen, 14000 Caen (France); Pasquali, G. [Dipartimento di Fisica, Università di Firenze, via G.Sansone 1, 50019 Sesto Fiorentino (Italy); INFN Sezione di Firenze, via G.Sansone 1, 50019 Sesto Fiorentino (Italy); Alba, R. [INFN LNS, Via S.Sofia 62, 95123 Catania (Italy); Barlini, S.; Bini, M. [Dipartimento di Fisica, Università di Firenze, via G.Sansone 1, 50019 Sesto Fiorentino (Italy); INFN Sezione di Firenze, via G.Sansone 1, 50019 Sesto Fiorentino (Italy); Bonnet, E. [SUBATECH, EMN-IN2P3/CNRS-Université de Nantes, Nantes (France); GANIL, CEA/DSM-CNRS/IN2P3, B.P. 5027, F-14076 Caen Cedex (France); Borderie, B. [Institut de Physique Nucléaire, CNRS-IN2P3, Univ. Paris-Sud, Université Paris-Saclay, F-91406 Orsay Cedex (France); Bougault, R. [LPC Caen, Normandie Univ, ENSICAEN, UNICAEN, CNRS/IN2P3, LPC Caen, 14000 Caen (France); Bruno, M. [INFN, Sezione di Bologna, Viale Berti Pichat 6/2, 40127 Bologna (Italy); Casini, G. [INFN Sezione di Firenze, via G.Sansone 1, 50019 Sesto Fiorentino (Italy); Chbihi, A. [GANIL, CEA/DSM-CNRS/IN2P3, B.P. 5027, F-14076 Caen Cedex (France); and others

2017-07-11

The FAZIA apparatus exploits Pulse Shape Analysis (PSA) to identify nuclear fragments stopped in the first layer of a Silicon-Silicon-CsI(Tl) detector telescope. In this work, for the first time, we show that the isotopes of fragments having atomic number as high as Z∼20 can be identified. Such a remarkable result has been obtained thanks to a careful construction of the Si detectors and to the use of low noise and high performance digitizing electronics. Moreover, optimized PSA algorithms are needed. This work deals with the choice of the best algorithm for PSA of current signals. A smoothing spline algorithm is demonstrated to give optimal results without requiring too much computational resources.

Petroleum Pumps’ Current and Vibration Signatures Analysis Using Wavelet Coherence Technique

Directory of Open Access Journals (Sweden)

Rmdan Shnibha

2013-01-01

Full Text Available Vibration analysis is widely used for rotating machinery diagnostics; however measuring vibration of operational oil well pumps is not possible. The pump’s driver’s current signatures may provide condition-related information without the need for an access to the pump itself. This paper investigates the degree of relationship between the pump’s driver’s current signatures and its induced vibration. This relationship between the driver’s current signatures (DCS and its vibration signatures (DVS is studied by calculating magnitude-squared coherence and phase coherence parameters at a certain frequency band using continuous wavelet transform (CWT. The CWT coherence-based technique allows better analysis of temporal evolution of the frequency content of dynamic signals and areas in the time-frequency plane where the two signals exhibit common power or consistent phase behaviour indicating a relationship between the signals. This novel approach is validated by experimental data acquired from 3 kW petroleum pump’s driver. Both vibration and current signatures were acquired under different speed and load conditions. The outcomes of this research suggest the use of DCS analysis as reliable and inexpensive condition monitoring tool, which could be implemented for oil pumps, real-time monitoring associated with condition-based maintenance (CBM program.

Multiscale Signal Analysis and Modeling

CERN Document Server

Zayed, Ahmed

2013-01-01

Multiscale Signal Analysis and Modeling presents recent advances in multiscale analysis and modeling using wavelets and other systems. This book also presents applications in digital signal processing using sampling theory and techniques from various function spaces, filter design, feature extraction and classification, signal and image representation/transmission, coding, nonparametric statistical signal processing, and statistical learning theory. This book also: Discusses recently developed signal modeling techniques, such as the multiscale method for complex time series modeling, multiscale positive density estimations, Bayesian Shrinkage Strategies, and algorithms for data adaptive statistics Introduces new sampling algorithms for multidimensional signal processing Provides comprehensive coverage of wavelets with presentations on waveform design and modeling, wavelet analysis of ECG signals and wavelet filters Reviews features extraction and classification algorithms for multiscale signal and image proce...

Investigating the computer analysis of eddy current NDT data

International Nuclear Information System (INIS)

Brown, R.L.

1979-01-01

The objective of this activity was to investigate and develop techniques for computer analysis of eddy current nondestructive testing (NDT) data. A single frequency commercial eddy current tester and a precision mechanical scanner were interfaced with a PDP-11/34 computer to obtain and analyze eddy current data from samples of 316 stainless steel tubing containing known discontinuities. Among the data analysis techniques investigated were: correlation, Fast Fourier Transforms (FFT), clustering, and Adaptive Learning Networks (ALN). The results were considered encouraging. ALN, for example, correctly identified 88% of the defects and non-defects from a group of 153 signal indications

Gas stream analysis using voltage-current time differential operation of electrochemical sensors

Science.gov (United States)

Woo, Leta Yar-Li; Glass, Robert Scott; Fitzpatrick, Joseph Jay; Wang, Gangqiang; Henderson, Brett Tamatea; Lourdhusamy, Anthoniraj; Steppan, James John; Allmendinger, Klaus Karl

2018-01-02

A method for analysis of a gas stream. The method includes identifying an affected region of an affected waveform signal corresponding to at least one characteristic of the gas stream. The method also includes calculating a voltage-current time differential between the affected region of the affected waveform signal and a corresponding region of an original waveform signal. The affected region and the corresponding region of the waveform signals have a sensitivity specific to the at least one characteristic of the gas stream. The method also includes generating a value for the at least one characteristic of the gas stream based on the calculated voltage-current time differential.

Electrical signal analysis to assess the physical condition of a human or animal

Science.gov (United States)

Cox, Daryl F.; Hochanadel, Charles D.; Haynes, Howard D.

2010-06-15

The invention is a human and animal performance data acquisition, analysis, and diagnostic system for fitness and therapy devices having an interface box removably disposed on incoming power wiring to a fitness and therapy device, at least one current transducer removably disposed on said interface box for sensing current signals to said fitness and therapy device, and a means for analyzing, displaying, and reporting said current signals to determine human and animal performance on said device using measurable parameters.

A signal processing analysis of Purkinje cells in vitro

Directory of Open Access Journals (Sweden)

Ze'ev R Abrams

2010-05-01

Full Text Available Cerebellar Purkinje cells in vitro fire recurrent sequences of Sodium and Calcium spikes. Here, we analyze the Purkinje cell using harmonic analysis, and our experiments reveal that its output signal is comprised of three distinct frequency bands, which are combined using Amplitude and Frequency Modulation (AM/FM. We find that the three characteristic frequencies - Sodium, Calcium and Switching – occur in various combinations in all waveforms observed using whole-cell current clamp recordings. We found that the Calcium frequency can display a frequency doubling of its frequency mode, and the Switching frequency can act as a possible generator of pauses that are typically seen in Purkinje output recordings. Using a reversibly photo-switchable kainate receptor agonist, we demonstrate the external modulation of the Calcium and Switching frequencies. These experiments and Fourier analysis suggest that the Purkinje cell can be understood as a harmonic signal oscillator, enabling a higher level of interpretation of Purkinje signaling based on modern signal processing techniques.

Postprocessing algorithm for automated analysis of pelvic intraoperative neuromonitoring signals

Directory of Open Access Journals (Sweden)

Wegner Celine

2016-09-01

Full Text Available Two dimensional pelvic intraoperative neuromonitoring (pIONM® is based on electric stimulation of autonomic nerves under observation of electromyography of internal anal sphincter (IAS and manometry of urinary bladder. The method provides nerve identification and verification of its’ functional integrity. Currently pIONM® is gaining increased attention in times where preservation of function is becoming more and more important. Ongoing technical and methodological developments in experimental and clinical settings require further analysis of the obtained signals. This work describes a postprocessing algorithm for pIONM® signals, developed for automated analysis of huge amount of recorded data. The analysis routine includes a graphical representation of the recorded signals in the time and frequency domain, as well as a quantitative evaluation by means of features calculated from the time and frequency domain. The produced plots are summarized automatically in a PowerPoint presentation. The calculated features are filled into a standardized Excel-sheet, ready for statistical analysis.

New signal processing methods for the evaluation of eddy current NDT data

International Nuclear Information System (INIS)

Anon.

1987-01-01

Signal processing and pattern recognition methods play a crucial role in a number of areas associated with nondestructive evaluation. Defect characterization schemes often involve mapping the signal onto an appropriate feature domain and using pattern recognition techniques for classification. In addition, signal processing methods are also used to acquire, enhance, restore, and compress data. EPRI Project RP 2673-4 is concerned with developing new signal processing and pattern recognition techniques for evaluating eddy current signals. Efforts under this project have focused on three closely related areas. The thrust has been to: (1) develop a scheme to compress eddy current signals for the purposes of storing them in a compact form, (2) develop a robust clustering algorithm capable of discarding feature vectors that fall in the gray areas between clusters, and (3) investigate the feasibility of designing and developing a digital eddyscope

Alleviating Border Effects in Wavelet Transforms for Nonlinear Time-varying Signal Analysis

Directory of Open Access Journals (Sweden)

SU, H.

2011-08-01

Full Text Available Border effects are very common in many finite signals analysis and processing approaches using convolution operation. Alleviating the border effects that can occur in the processing of finite-length signals using wavelet transform is considered in this paper. Traditional methods for alleviating the border effects are suitable to compression or coding applications. We propose an algorithm based on Fourier series which is proved to be appropriate to the application of time-frequency analysis of nonlinear signals. Fourier series extension method preserves the time-varying characteristics of the signals. A modified signal duration expression for measuring the extent of border effects region is presented. The proposed algorithm is confirmed to be efficient to alleviate the border effects in comparison to the current methods through the numerical examples.

Current signal of silicon detectors facing charged particles and heavy ions

International Nuclear Information System (INIS)

Hamrita, H.

2005-07-01

This work consisted in collecting and studying for the first time the shapes of current signals obtained from charged particles or heavy ions produced by silicon detectors. The document is divided into two main parts. The first consisted in reducing the experimental data obtained with charged particles as well as with heavy ions. These experiments were performed at the Orsay Tandem and at GANIL using LISE. These two experiments enabled us to create a data base formed of current signals with various shapes and various times of collection. The second part consisted in carrying out a simulation of the current signals obtained from the various ions. To obtain this simulation we propose a new model describing the formation of the signal. We used the data base of the signals obtained in experiments in order to constrain the three parameters of our model. In this model, the charge carriers created are regarded as dipoles and their density is related to the dielectric polarization in the silicon detector. This phenomenon induces an increase in permittivity throughout the range of the incident ion and consequently the electric field between the electrodes of the detector is decreased inside the trace. We coupled with this phenomenon a dissociation and extraction mode of the charge carriers so that they can be moved in the electric field. (author)

Characterisation of eddy current signals using different types of artificial neural networks

International Nuclear Information System (INIS)

Shyamsunder, M.T.; Rajagopalan, C.; Jayakumar, T.; Kalyanasundaram, P.; Baldev Raj; Ray, K.K.

1996-01-01

Eddy current testing is one of the important techniques in nondestructive testing. Automated characterisation of eddy current signals (ECS), either in the form of lissajous patterns (figure-of-eight) or individual voltage vs. time signals is an area of growing interest. This is particularly relevant in environments where the signal-to-noise ratio (SNR) of ECS are very poor. Intelligent, timely and precise interpretation of resulting data, is the key for improving the efficiency of NDT and E. A comprehensive study has been undertaken by the authors for the characterisation of ECS having poor SNR, using three types of artificial neural networks (ANNs). The types of ANNs used in this study are [a] the error-back propagation model, [b] the binary Hopfield model and [c] the Kohonen's self-organising maps model. Eddy current signals, acquired from different types of defects such as holes and notches on stainless steel type 316 sheets were used in this study. (author)

Large-signal analysis of DC motor drive system using state-space averaging technique

International Nuclear Information System (INIS)

Bekir Yildiz, Ali

2008-01-01

The analysis of a separately excited DC motor driven by DC-DC converter is realized by using state-space averaging technique. Firstly, a general and unified large-signal averaged circuit model for DC-DC converters is given. The method converts power electronic systems, which are periodic time-variant because of their switching operation, to unified and time independent systems. Using the averaged circuit model enables us to combine the different topologies of converters. Thus, all analysis and design processes about DC motor can be easily realized by using the unified averaged model which is valid during whole period. Some large-signal variations such as speed and current relating to DC motor, steady-state analysis, large-signal and small-signal transfer functions are easily obtained by using the averaged circuit model

Semi-classical signal analysis

KAUST Repository

Laleg-Kirati, Taous-Meriem; Cré peau, Emmanuelle; Sorine, Michel

2012-01-01

This study introduces a new signal analysis method, based on a semi-classical approach. The main idea in this method is to interpret a pulse-shaped signal as a potential of a Schrödinger operator and then to use the discrete spectrum

Differences between signal currents for both polarities of applied voltages on cavity ionization chambers

International Nuclear Information System (INIS)

Takata, N.

2000-01-01

It is necessary to obtain precise values of signal currents for the measurement of exposure rates for gamma rays with cavity ionization chambers. Signal currents are usually expected to have the same absolute values for both polarities of applied voltages. In the case of cylindrical cavity ionization chambers, volume recombination loss of ion pairs depends on the polarity of the applied voltage. This is because the values of mobility are different for positive and negative ions. It was found, however, that values of signal currents from a cylindrical ionization chamber change slightly more with a negative than with a positive applied voltage, even after being corrected for volume recombination loss. Moreover, absolute values of saturation currents, which are obtained by extrapolation of correction of initial recombination and diffusion loss, were larger for the negative than for the positive applied voltage. It is known from an experiment with parallel plate ionization chambers that when negative voltage is applied to the repeller electrode, the saturated signal current decreases with an increase in the applied voltage. This is because secondary electrons are accelerated and the stopping power of air for these electrons decreases. When positive voltage is applied, the reverse is true. The effects of acceleration and deceleration of secondary electrons by the electric field thus seem to cause a tendency opposite to the experimental results on the signal currents from cylindrical ionization chambers. The experimental results for the cylindrical ionization chamber can be explained as follows. When negative voltage is applied, secondary electrons are attracted to the central (collecting) electrode. Consequently, the path length of the trajectories of these secondary electrons in the ionization volume increases and signal current increases. The energy gain from the electric field by secondary electrons which stop in the ionization chamber also contributes to the

Process for treating signals returning by an eddy current absolute punctual probe

International Nuclear Information System (INIS)

Attaqui, P.; Benoist, B.; Besnard, R.; David, B.

1994-01-01

The method of signal treatment involves returning signals to eddy currents moving along an internal surface of a tube. A signal representing the state of the surface is delivered and the surface is swept based on a given order of elementary measurement zones. Values of samples of a signal are registered for each zone giving a three dimensional image of the surface. A background noise surface is constructed and substracted from the image. 7 figs

Signal to noise ratio enhancement for Eddy Current testing of steam generator tubes in PWR's

International Nuclear Information System (INIS)

Georgel, B.

1985-01-01

Noise reduction is a compulsory task when we try to recognize and characterize flaws. The signals we deal with come from Eddy Current testings of steam generator steel tubes. We point out the need for a spectral invariant in digital spectral analysis of 2 components signals. We make clear the pros and cons of classical passband filtering and suggest the use of a new noise cancellation method first discussed by Moriwaki and Tlusty. We generalize this tricky technique and prove it is a very special case of the well-known Wiener filter. In that sense the M-T method is shown to be optimal. 6 refs

An overview of data acquisition, signal coding and data analysis techniques for MST radars

Science.gov (United States)

Rastogi, P. K.

1986-01-01

An overview is given of the data acquisition, signal processing, and data analysis techniques that are currently in use with high power MST/ST (mesosphere stratosphere troposphere/stratosphere troposphere) radars. This review supplements the works of Rastogi (1983) and Farley (1984) presented at previous MAP workshops. A general description is given of data acquisition and signal processing operations and they are characterized on the basis of their disparate time scales. Then signal coding, a brief description of frequently used codes, and their limitations are discussed, and finally, several aspects of statistical data processing such as signal statistics, power spectrum and autocovariance analysis, outlier removal techniques are discussed.

Stability analysis of direct current control in current source rectifier

DEFF Research Database (Denmark)

Lu, Dapeng; Wang, Xiongfei; Blaabjerg, Frede

2017-01-01

Current source rectifier with high switching frequency has a great potential for improving the power efficiency and power density in ac-dc power conversion. This paper analyzes the stability of direct current control based on the time delay effect. Small signal model including dynamic behaviors...

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

KAUST Repository

Liu, Dayan

2012-08-01

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

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

KAUST Repository

Liu, Dayan; Laleg-Kirati, Taous-Meriem

2012-01-01

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

ANN-based wavelet analysis for predicting electrical signal from photovoltaic power supply system

Energy Technology Data Exchange (ETDEWEB)

Mellit, A. [Medea Univ., Medea (Algeria). Inst. of Science Engineering, Dept. of Electronics

2007-07-01

This study was conducted to predict different electrical signals from a photovoltaic power supply system (PVPS) using an artificial neural networks (ANN) with wavelet analysis. It involved the creation of a database of electrical signals (PV-generator current, voltage, battery current voltage, regulator current and voltage) obtained from an experimental PVPS system installed in the south of Algeria. The potential applications were for sizing and analyzing the performance of PVPS systems; control of maximum power point tracker (MPPT) in order to deliver the maximum energy from the PV-array; prediction of the optimal configuration (PV-array and battery sizing) of PVPS systems; expert configuration of PV-systems; faults diagnosis; supervision; and, control and monitoring. First, based on the wavelet analysis each electrical signal was mapped in several time frequency domains. The PV-system was then divided into 3-subsystems corresponding to ANN-PV generator model, ANN-battery model, and ANN-regulator model. An example of day-by-day prediction for each electrical signal was presented. The results of the proposed approach were in good agreement with experimental results. In addition, the accuracy of the proposed approach was more satisfactory when only ANN was used. It was concluded that this methodology offers the possibility of developing a new expert configuration of PVPS by implementing the soft computing ANN-wavelet program with a digital signal processing (DSP) circuit. 26 refs., 1 tab., 5 figs.

Cellular signaling identifiability analysis: a case study.

Science.gov (United States)

Roper, Ryan T; Pia Saccomani, Maria; Vicini, Paolo

2010-05-21

Two primary purposes for mathematical modeling in cell biology are (1) simulation for making predictions of experimental outcomes and (2) parameter estimation for drawing inferences from experimental data about unobserved aspects of biological systems. While the former purpose has become common in the biological sciences, the latter is less common, particularly when studying cellular and subcellular phenomena such as signaling-the focus of the current study. Data are difficult to obtain at this level. Therefore, even models of only modest complexity can contain parameters for which the available data are insufficient for estimation. In the present study, we use a set of published cellular signaling models to address issues related to global parameter identifiability. That is, we address the following question: assuming known time courses for some model variables, which parameters is it theoretically impossible to estimate, even with continuous, noise-free data? Following an introduction to this problem and its relevance, we perform a full identifiability analysis on a set of cellular signaling models using DAISY (Differential Algebra for the Identifiability of SYstems). We use our analysis to bring to light important issues related to parameter identifiability in ordinary differential equation (ODE) models. We contend that this is, as of yet, an under-appreciated issue in biological modeling and, more particularly, cell biology. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Acoustic signal analysis in the creeping discharge

International Nuclear Information System (INIS)

Nakamiya, T; Sonoda, Y; Tsuda, R; Ebihara, K; Ikegami, T

2008-01-01

We have previously succeeded in measuring the acoustic signal due to the dielectric barrier discharge and discriminating the dominant frequency components of the acoustic signal. The dominant frequency components appear over 20kHz of acoustic signal by the dielectric barrier discharge. Recently surface discharge control technology has been focused from practical applications such as ozonizer, NO X reactors, light source or display. The fundamental experiments are carried to examine the creeping discharge using the acoustic signal. When the high voltage (6kV, f = 10kHz) is applied to the electrode, the discharge current flows and the acoustic sound is generated. The current, voltage waveforms of creeping discharge and the sound signal detected by the condenser microphone are stored in the digital memory scope. In this scheme, Continuous Wavelet Transform (CWT) is applied to discriminate the acoustic sound of the micro discharge and the dominant frequency components are studied. CWT results of sound signal show the frequency spectrum of wideband up to 100kHz. In addition, the energy distributions of acoustic signal are examined by CWT

Digital Signal Processing and Generation for a DC Current Transformer for Particle Accelerators

Energy Technology Data Exchange (ETDEWEB)

Zorzetti, Silvia [Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)

2013-01-01

The thesis topic, digital signal processing and generation for a DC current transformer, focuses on the most fundamental beam diagnostics in the field of particle accelerators, the measurement of the beam intensity, or beam current. The technology of a DC current transformer (DCCT) is well known, and used in many areas, including particle accelerator beam instrumentation, as non-invasive (shunt-free) method to monitor the DC current in a conducting wire, or in our case, the current of charged particles travelling inside an evacuated metal pipe. So far, custom and commercial DCCTs are entirely based on analog technologies and signal processing, which makes them inflexible, sensitive to component aging, and difficult to maintain and calibrate.

Design and array signal suggestion of array type pulsed eddy current probe for health monitoring of metal tubes

Energy Technology Data Exchange (ETDEWEB)

Shin, Young Kil [Dept. of Electrical Engineering, Kunsan National University, Kunsan (Korea, Republic of)

2015-10-15

An array type probe for monitoring metal tubes is proposed in this paper which utilizes peak value and peak time of a pulsed eddy current(PEC) signal. The probe consists of an array of encircling coils along a tube and the outside of coils is shielded by ferrite to prevent source magnetic fields from directly affecting sensor signals since it is the magnetic fields produced by eddy currents that reflect the condition of metal tubes. The positions of both exciter and sensor coils are consecutively moved automatically so that manual scanning is not necessary. At one position of send-receive coils, peak value and peak time are extracted from a sensor PEC signal and these data are accumulated for all positions to form an array type peak value signal and an array type peak time signal. Numerical simulation was performed using the backward difference method in time and the finite element method for spatial analysis. Simulation results showed that peak value increases and the peak appears earlier as the defect depth or length increases. The proposed array signals are shown to be excellent in reflecting the defect location as well as variations of defect depth and length within the array probe.

Stem cell maintenance by manipulating signaling pathways: past, current and future

Science.gov (United States)

Chen, Xi; Ye, Shoudong; Ying, Qi-Long

2015-01-01

Pluripotent stem cells only exist in a narrow window during early embryonic development, whereas multipotent stem cells are abundant throughout embryonic development and are retainedin various adult tissues and organs. While pluripotent stem cell lines have been established from several species, including mouse, rat, and human, it is still challenging to establish stable multipotent stem cell lines from embryonic or adult tissues. Based on current knowledge, we anticipate that by manipulating extrinsic and intrinsic signaling pathways, most if not all types of stem cells can be maintained in a long-term culture. In this article, we summarize current culture conditions established for the long-term maintenance of authentic pluripotent and multipotent stem cells and the signaling pathways involved. We also discuss the general principles of stem cell maintenance and propose several strategies on the establishment of novel stem cell lines through manipulation of signaling pathways. [BMB Reports 2015; 48(12): 668-676] PMID:26497581

Correlation analysis of motor current and chatter vibration in grinding using complex continuous wavelet coherence

International Nuclear Information System (INIS)

Liu, Yao; Wang, Xiufeng; Lin, Jing; Zhao, Wei

2016-01-01

Motor current is an emerging and popular signal which can be used to detect machining chatter with its multiple advantages. To achieve accurate and reliable chatter detection using motor current, it is important to make clear the quantitative relationship between motor current and chatter vibration, which has not yet been studied clearly. In this study, complex continuous wavelet coherence, including cross wavelet transform and wavelet coherence, is applied to the correlation analysis of motor current and chatter vibration in grinding. Experimental results show that complex continuous wavelet coherence performs very well in demonstrating and quantifying the intense correlation between these two signals in frequency, amplitude and phase. When chatter occurs, clear correlations in frequency and amplitude in the chatter frequency band appear and the phase difference of current signal to vibration signal turns from random to stable. The phase lead of the most correlated chatter frequency is the largest. With the further development of chatter, the correlation grows up in intensity and expands to higher order chatter frequency band. The analyzing results confirm that there is a consistent correlation between motor current and vibration signals in the grinding chatter process. However, to achieve accurate and reliable chatter detection using motor current, the frequency response bandwidth of current loop of the feed drive system must be wide enough to response chatter effectively. (paper)

Expert system for the automatic analysis of the Eddy current signals from the monitoring of vapor generators of a PWR, type reactor

International Nuclear Information System (INIS)

Lefevre, F.; Baumaire, A.; Comby, R.; Benas, J.C.

1990-01-01

The automatization of the monitoring of the steam generator tubes required some developments in the field of data processing. The monitoring is performed by means of Eddy current tests. Improvements in signal processing and in pattern recognition associated to the artificial intelligence techniques induced EDF (French Electricity Company) to develop an automatic signal processing system. The system, named EXTRACSION (French acronym for Expert System for the Processing and classification of Signals of Nuclear Nature), insures the coherence between the different fields of knowledge (metallurgy, measurement, signals) during data processing by applying an object oriented representation [fr

Current Technologies of Electrochemical Immunosensors: Perspective on Signal Amplification

Directory of Open Access Journals (Sweden)

Il-Hoon Cho

2018-01-01

Full Text Available An electrochemical immunosensor employs antibodies as capture and detection means to produce electrical charges for the quantitative analysis of target molecules. This sensor type can be utilized as a miniaturized device for the detection of point-of-care testing (POCT. Achieving high-performance analysis regarding sensitivity has been one of the key issues with developing this type of biosensor system. Many modern nanotechnology efforts allowed for the development of innovative electrochemical biosensors with high sensitivity by employing various nanomaterials that facilitate the electron transfer and carrying capacity of signal tracers in combination with surface modification and bioconjugation techniques. In this review, we introduce novel nanomaterials (e.g., carbon nanotube, graphene, indium tin oxide, nanowire and metallic nanoparticles in order to construct a high-performance electrode. Also, we describe how to increase the number of signal tracers by employing nanomaterials as carriers and making the polymeric enzyme complex associated with redox cycling for signal amplification. The pros and cons of each method are considered throughout this review. We expect that these reviewed strategies for signal enhancement will be applied to the next versions of lateral-flow paper chromatography and microfluidic immunosensor, which are considered the most practical POCT biosensor platforms.

Method of signal analysis

International Nuclear Information System (INIS)

Berthomier, Charles

1975-01-01

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

Multivariate Analysis for the Processing of Signals

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Beattie J.R.

2014-01-01

Full Text Available Real-world experiments are becoming increasingly more complex, needing techniques capable of tracking this complexity. Signal based measurements are often used to capture this complexity, where a signal is a record of a sample’s response to a parameter (e.g. time, displacement, voltage, wavelength that is varied over a range of values. In signals the responses at each value of the varied parameter are related to each other, depending on the composition or state sample being measured. Since signals contain multiple information points, they have rich information content but are generally complex to comprehend. Multivariate Analysis (MA has profoundly transformed their analysis by allowing gross simplification of the tangled web of variation. In addition MA has also provided the advantage of being much more robust to the influence of noise than univariate methods of analysis. In recent years, there has been a growing awareness that the nature of the multivariate methods allows exploitation of its benefits for purposes other than data analysis, such as pre-processing of signals with the aim of eliminating irrelevant variations prior to analysis of the signal of interest. It has been shown that exploiting multivariate data reduction in an appropriate way can allow high fidelity denoising (removal of irreproducible non-signals, consistent and reproducible noise-insensitive correction of baseline distortions (removal of reproducible non-signals, accurate elimination of interfering signals (removal of reproducible but unwanted signals and the standardisation of signal amplitude fluctuations. At present, the field is relatively small but the possibilities for much wider application are considerable. Where signal properties are suitable for MA (such as the signal being stationary along the x-axis, these signal based corrections have the potential to be highly reproducible, and highly adaptable and are applicable in situations where the data is noisy or

Current lead thermal analysis code 'CURRENT'

International Nuclear Information System (INIS)

Yamaguchi, Masahito; Tada, Eisuke; Shimamoto, Susumu; Hata, Kenichiro.

1985-08-01

Large gas-cooled current lead with the capacity more than 30 kA and 22 kV is required for superconducting toroidal and poloidal coils for fusion application. The current lead is used to carry electrical current from the power supply system at room temperature to the superconducting coil at 4 K. Accordingly, the thermal performance of the current lead is significantly important to determine the heat load requirements of the coil system at 4 K. Japan Atomic Energy Research Institute (JAERI) has being developed the large gas-cooled current leads with the optimum condition in which the heat load is around 1 W per 1 kA at 4 K. In order to design the current lead with the optimum thermal performances, JAERI developed thermal analysis code named as ''CURRENT'' which can theoretically calculate the optimum geometric shape and cooling conditions of the current lead. The basic equations and the instruction manual of the analysis code are described in this report. (author)

Owls may use faeces and prey feathers to signal current reproduction.

Directory of Open Access Journals (Sweden)

Vincenzo Penteriani

Full Text Available BACKGROUND: Many animals communicate by marking focal elements of their home range with different kinds of materials. Visual signaling has been demonstrated to play a previously unrecognized role in the intraspecific communication of eagle owls (Bubo bubo, in both territorial and parent-offspring contexts. Visual signals may play a role in a variety of circumstances in this crepuscular and nocturnal species. METHODOLOGY/PRINCIPAL FINDINGS: Here, we report that a large amount of extremely visible white faeces and prey feathers appear during the breeding season on posts and plucking sites in proximity to the nest, potentially representing a way for eagle owls to mark their territory. We present descriptive and experimental evidence showing that faeces and prey remains could act as previously unrecognized visual signals in a nocturnal avian predator. This novel signaling behavior could indicate the owls' current reproductive status to potential intruders, such as other territorial owls or non-breeding floaters. Faeces and prey feather markings may also advertise an owl's reproductive status or function in mate-mate communication. CONCLUSIONS/SIGNIFICANCE: We speculate that faeces marks and plucking may represent an overlooked but widespread method for communicating current reproduction to conspecifics. Such marking behavior may be common in birds, and we may now be exploring other questions and mechanisms in territoriality.

Owls may use faeces and prey feathers to signal current reproduction.

Science.gov (United States)

Penteriani, Vincenzo; Delgado, Maria del Mar

2008-08-20

Many animals communicate by marking focal elements of their home range with different kinds of materials. Visual signaling has been demonstrated to play a previously unrecognized role in the intraspecific communication of eagle owls (Bubo bubo), in both territorial and parent-offspring contexts. Visual signals may play a role in a variety of circumstances in this crepuscular and nocturnal species. Here, we report that a large amount of extremely visible white faeces and prey feathers appear during the breeding season on posts and plucking sites in proximity to the nest, potentially representing a way for eagle owls to mark their territory. We present descriptive and experimental evidence showing that faeces and prey remains could act as previously unrecognized visual signals in a nocturnal avian predator. This novel signaling behavior could indicate the owls' current reproductive status to potential intruders, such as other territorial owls or non-breeding floaters. Faeces and prey feather markings may also advertise an owl's reproductive status or function in mate-mate communication. We speculate that faeces marks and plucking may represent an overlooked but widespread method for communicating current reproduction to conspecifics. Such marking behavior may be common in birds, and we may now be exploring other questions and mechanisms in territoriality.

Effect of injection current and temperature on signal strength in a laser diode optical feedback interferometer.

Science.gov (United States)

Al Roumy, Jalal; Perchoux, Julien; Lim, Yah Leng; Taimre, Thomas; Rakić, Aleksandar D; Bosch, Thierry

2015-01-10

We present a simple analytical model that describes the injection current and temperature dependence of optical feedback interferometry signal strength for a single-mode laser diode. The model is derived from the Lang and Kobayashi rate equations, and is developed both for signals acquired from the monitoring photodiode (proportional to the variations in optical power) and for those obtained by amplification of the corresponding variations in laser voltage. The model shows that both the photodiode and the voltage signal strengths are dependent on the laser slope efficiency, which itself is a function of the injection current and the temperature. Moreover, the model predicts that the photodiode and voltage signal strengths depend differently on injection current and temperature. This important model prediction was proven experimentally for a near-infrared distributed feedback laser by measuring both types of signals over a wide range of injection currents and temperatures. Therefore, this simple model provides important insight into the radically different biasing strategies required to achieve optimal sensor sensitivity for both interferometric signal acquisition schemes.

Signal analysis of ventricular fibrillation

NARCIS (Netherlands)

Herbschleb, J.N.; Heethaar, R.M.; Tweel, L.H. van der; Zimmerman, A.N.E.; Meijler, F.L.

Signal analysis of electro(cardio)grams during ventricular fibrillation (VF) in dogs and human patients indicates more organization and regularity than the official WHO definition suggests. The majority of the signal is characterized by a power spectrum with narrow, equidistant peaks. In a further

Biological signals classification and analysis

CERN Document Server

Kiasaleh, Kamran

2015-01-01

This authored monograph presents key aspects of signal processing analysis in the biomedical arena. Unlike wireless communication systems, biological entities produce signals with underlying nonlinear, chaotic nature that elude classification using the standard signal processing techniques, which have been developed over the past several decades for dealing primarily with standard communication systems. This book separates what is random from that which appears to be random, and yet is truly deterministic with random appearance. At its core, this work gives the reader a perspective on biomedical signals and the means to classify and process such signals. In particular, a review of random processes along with means to assess the behavior of random signals is also provided. The book also includes a general discussion of biological signals in order to demonstrate the inefficacy of the well-known techniques to correctly extract meaningful information from such signals. Finally, a thorough discussion of recently ...

Simultaneously measured signals in scanning probe microscopy with a needle sensor: frequency shift and tunneling current.

Science.gov (United States)

Morawski, Ireneusz; Voigtländer, Bert

2010-03-01

We present combined noncontact scanning force microscopy and tunneling current images of a platinum(111) surface obtained by means of a 1 MHz quartz needle sensor. The low-frequency circuit of the tunneling current was combined with a high-frequency signal of the quartz resonator enabling full electrical operation of the sensor. The frequency shift and the tunneling current were detected simultaneously, while the feedback control loop of the topography signal was fed using one of them. In both cases, the free signal that was not connected to the feedback loop reveals proportional-integral controller errorlike behavior, which is governed by the time derivative of the topography signal. A procedure is proposed for determining the mechanical oscillation amplitude by utilizing the tunneling current also including the average tip-sample work function.

A CMOS power-efficient low-noise current-mode front-end amplifier for neural signal recording.

Science.gov (United States)

Wu, Chung-Yu; Chen, Wei-Ming; Kuo, Liang-Ting

2013-04-01

In this paper, a new current-mode front-end amplifier (CMFEA) for neural signal recording systems is proposed. In the proposed CMFEA, a current-mode preamplifier with an active feedback loop operated at very low frequency is designed as the first gain stage to bypass any dc offset current generated by the electrode-tissue interface and to achieve a low high-pass cutoff frequency below 0.5 Hz. No reset signal or ultra-large pseudo resistor is required. The current-mode preamplifier has low dc operation current to enhance low-noise performance and decrease power consumption. A programmable current gain stage is adopted to provide adjustable gain for adaptive signal scaling. A following current-mode filter is designed to adjust the low-pass cutoff frequency for different neural signals. The proposed CMFEA is designed and fabricated in 0.18-μm CMOS technology and the area of the core circuit is 0.076 mm(2). The measured high-pass cutoff frequency is as low as 0.3 Hz and the low-pass cutoff frequency is adjustable from 1 kHz to 10 kHz. The measured maximum current gain is 55.9 dB. The measured input-referred current noise density is 153 fA /√Hz , and the power consumption is 13 μW at 1-V power supply. The fabricated CMFEA has been successfully applied to the animal test for recording the seizure ECoG of Long-Evan rats.

Detailed Analysis of Torque Ripple in High Frequency Signal Injection based Sensor less PMSM Drives

Directory of Open Access Journals (Sweden)

Ravikumar Setty A.

2017-01-01

Full Text Available High Frequency Signal Injection based techniques are robust and well proven to estimate the rotor position from stand still to low speed. However, Injected high frequency signal introduces, high frequency harmonics in the motor phase currents and results in significant Output Torque ripple. There is no detailed analysis exist in the literature, to study the effect of injected signal frequency on Torque ripple. Objective of this work is to study the Torque Ripple resulting from High Frequency signal injection in PMSM motor drives. Detailed MATLAB/Simulink simulations are carried to quantify the Torque ripple at different Signal frequencies.

A critical comparison of the current view of Ca signaling with the novel concept of F-actin-based Ca signaling.

Science.gov (United States)

Lange, Klaus; Gartzke, Joachim

2006-01-01

A detailed comparative survey on the current idea of Ca signaling and the alternative concept of F-actin-based Ca signaling is given. The two hypotheses differ in one central aspect - the mechanism of Ca storage. The current theory rests on the assumption of Ca-accumulating vesicles derived from the endoplasmic/ sarcoplasmic reticulum, which are equipped with an ATP-dependent Ca pump and IP3- or ryanodine-sensitive Ca-release channels/receptors. The alternative hypothesis proceeds from the idea of Ca storage at the high-affinity binding sites of F-actin subunits. Several prominent features of Ca signaling, which are not adequately described by the current concept, are inherent properties of the F-actin system and its dynamic state of treadmilling. F-actin is the only known biological Ca-binding system that has been proven by in vitro experiments to work within the physiological range of Ca concentrations and the only system that meets all necessary conditions to function as receptor-operated Ca store and as a coupling device between the Ca store and the store-operated Ca influx pathway. The most important properties of Ca signaling, such as store-channel coupling, quantal Ca release, spiking and oscillations, biphasic and "phasic" uptake kinetics, and Ca-induced Ca release, turn out to be systematic features of the new concept but remain unexplained by the classical vesicle storage hypothesis. A number of novel findings, specifically recent reports about direct effects of actin-specific toxins on Ca stores, have strengthened the new concept. The concept of F-actin-based Ca signaling combined with the notion of microvillar regulation of ion and substrate fluxes opens new aspects and far-reaching consequences, not only for cellular Ca signaling but also for various other cell functions, and represents an opportunity to connect several fields of cell physiology on the basis of a common mechanism.

Current Views of Toll-Like Receptor Signaling Pathways

Directory of Open Access Journals (Sweden)

Masahiro Yamamoto

2010-01-01

Full Text Available On microbial invasion, the host immediately evokes innate immune responses. Recent studies have demonstrated that Toll-like receptors (TLRs play crucial roles in innate responses that lead not only to the clearance of pathogens but also to the efficient establishment of acquired immunity by directly detecting molecules from microbes. In terms of intracellular TLR-mediated signaling pathways, cytoplasmic adaptor molecules containing Toll/IL-1R (TIR domains play important roles in inflammatory immune responses through the production of proinflammatory cytokines, nitric oxide, and type I interferon, and upregulation of costimulatory molecules. In this paper, we will describe our current understanding of the relationship between TLRs and their ligands derived from pathogens such as viruses, bacteria, fungi, and parasites. Moreover, we will review the historical and current literature to describe the mechanisms behind TLR-mediated activation of innate immune responses.

Steam generator automated eddy current data analysis: A benchmarking study. Final report

International Nuclear Information System (INIS)

Brown, S.D.

1998-12-01

The eddy current examination of steam generator tubes is a very demanding process. Challenges include: complex signal analysis, massive amount of data to be reviewed quickly with extreme precision and accuracy, shortages of data analysts during peak periods, and the desire to reduce examination costs. One method to address these challenges is by incorporating automation into the data analysis process. Specific advantages, which automated data analysis has the potential to provide, include the ability to analyze data more quickly, consistently and accurately than can be performed manually. Also, automated data analysis can potentially perform the data analysis function with significantly smaller levels of analyst staffing. Despite the clear advantages that an automated data analysis system has the potential to provide, no automated system has been produced and qualified that can perform all of the functions that utility engineers demand. This report investigates the current status of automated data analysis, both at the commercial and developmental level. A summary of the various commercial and developmental data analysis systems is provided which includes the signal processing methodologies used and, where available, the performance data obtained for each system. Also, included in this report is input from seventeen research organizations regarding the actions required and obstacles to be overcome in order to bring automatic data analysis from the laboratory into the field environment. In order to provide assistance with ongoing and future research efforts in the automated data analysis arena, the most promising approaches to signal processing are described in this report. These approaches include: wavelet applications, pattern recognition, template matching, expert systems, artificial neural networks, fuzzy logic, case based reasoning and genetic algorithms. Utility engineers and NDE researchers can use this information to assist in developing automated data

Eddy current testing

Energy Technology Data Exchange (ETDEWEB)

Song, Sung Jin; Lee, Hyang Beom; Kim, Young Hwan [Soongsil Univ., Seoul (Korea, Republic of); Shin, Young Kil [Kunsan Univ., Gunsan (Korea, Republic of)

2004-02-15

Eddy current testing has been widely used for non destructive testing of steam generator tubes. In order to retain reliability in ECT, the following subjects were carried out in this study: numerical modeling and analysis of defects by using BC and RPC probes in SG tube, preparation of absolute coil impedance plane diagram by FEM. Signal interpretation of the eddy current signals obtained from nuclear power plants.

Eddy current testing

International Nuclear Information System (INIS)

Song, Sung Jin; Lee, Hyang Beom; Kim, Young Hwan; Shin, Young Kil

2004-02-01

Eddy current testing has been widely used for non destructive testing of steam generator tubes. In order to retain reliability in ECT, the following subjects were carried out in this study: numerical modeling and analysis of defects by using BC and RPC probes in SG tube, preparation of absolute coil impedance plane diagram by FEM. Signal interpretation of the eddy current signals obtained from nuclear power plants

Matrix effect on emission/current correlated analysis in laser-induced breakdown spectroscopy of liquid droplets

International Nuclear Information System (INIS)

Huang, J.-S.; Ke, C.-B.; Lin, K.-C.

2004-01-01

We have investigated influence of matrix salts on the liquid droplets by laser-induced breakdown spectroscopy (LIBS). An electrospray ionization technique coupled with LIBS is employed to generate the microdroplets of the Na sample solution with various matrix salts added. A sequence of single-shot time-resolved LIB emission signals is detected. The LIB signal intensity integrated within a gate linearly correlates with the plasma-induced current response obtained simultaneously on a single-shot basis. The slopes thus obtained increase with the sample concentration, but appear to be irrespective of different matrix salts, added up to a 2000 mg/l concentration. The matrix salts involved have the same K + cation but different anions. Given a laser radiation emitting at 355 nm with the energy fixed at 23±1 mJ, a limit of detection (LOD) of 1.0 mg/l may be achieved for the Na analysis. The current normalization might have probably taken into account the ablated amount of the sample and the plasma temperature. Accordingly, the LIB/current correlated analysis becomes efficient to suppress the signal fluctuation, improve the LOD determination, and concurrently correct the matrix effect

Signal-dependent independent component analysis by tunable mother wavelets

International Nuclear Information System (INIS)

Seo, Kyung Ho

2006-02-01

The objective of this study is to improve the standard independent component analysis when applied to real-world signals. Independent component analysis starts from the assumption that signals from different physical sources are statistically independent. But real-world signals such as EEG, ECG, MEG, and fMRI signals are not statistically independent perfectly. By definition, standard independent component analysis algorithms are not able to estimate statistically dependent sources, that is, when the assumption of independence does not hold. Therefore before independent component analysis, some preprocessing stage is needed. This paper started from simple intuition that wavelet transformed source signals by 'well-tuned' mother wavelet will be simplified sufficiently, and then the source separation will show better results. By the correlation coefficient method, the tuning process between source signal and tunable mother wavelet was executed. Gamma component of raw EEG signal was set to target signal, and wavelet transform was executed by tuned mother wavelet and standard mother wavelets. Simulation results by these wavelets was shown

A method of multi-crack shape identification from eddy current testing signals of steam generator tubes including support plates as noise sources

International Nuclear Information System (INIS)

Nagaya, Yoshiaki; Endo, Hisashi; Takagi, Toshiyuki; Uchimoto, Tetsuya

2005-01-01

This paper deals with identifying multiple cracks from eddy current testing (ECT) signals obtained in a steam generator tube with a support plate and deposits. Assume two-dimensionally scanned ECT signals to be a picture image, then the signal processing by a multi-frequency technique eliminates noise caused by the support plate and deposits. A template matching with help of genetic algorithms detects number and positions of cracks from the image after the signal processing. Inverse analysis estimates the crack profile based on the predicted position of cracks. The number and positions of the cracks are sufficiently well predicted. Crack shape reconstructions are achieved with a satisfactory degree of accuracy. (author)

Low noise signal-to-noise ratio enhancing readout circuit for current-mediated active pixel sensors

International Nuclear Information System (INIS)

Ottaviani, Tony; Karim, Karim S.; Nathan, Arokia; Rowlands, John A.

2006-01-01

Diagnostic digital fluoroscopic applications continuously expose patients to low doses of x-ray radiation, posing a challenge to both the digital imaging pixel and readout electronics when amplifying small signal x-ray inputs. Traditional switch-based amorphous silicon imaging solutions, for instance, have produced poor signal-to-noise ratios (SNRs) at low exposure levels owing to noise sources from the pixel readout circuitry. Current-mediated amorphous silicon pixels are an improvement over conventional pixel amplifiers with an enhanced SNR across the same low-exposure range, but whose output also becomes nonlinear with increasing dosage. A low-noise SNR enhancing readout circuit has been developed that enhances the charge gain of the current-mediated active pixel sensor (C-APS). The solution takes advantage of the current-mediated approach, primarily integrating the signal input at the desired frequency necessary for large-area imaging, while adding minimal noise to the signal readout. Experimental data indicates that the readout circuit can detect pixel outputs over a large bandwidth suitable for real-time digital diagnostic x-ray fluoroscopy. Results from hardware testing indicate that the minimum achievable C-APS output current that can be discerned at the digital fluoroscopic output from the enhanced SNR readout circuit is 0.341 nA. The results serve to highlight the applicability of amorphous silicon current-mediated pixel amplifiers for large-area flat panel x-ray imagers

Analog and digital signal analysis from basics to applications

CERN Document Server

Cohen Tenoudji, Frédéric

2016-01-01

This book provides comprehensive, graduate-level treatment of analog and digital signal analysis suitable for course use and self-guided learning. This expert text guides the reader from the basics of signal theory through a range of application tools for use in acoustic analysis, geophysics, and data compression. Each concept is introduced and explained step by step, and the necessary mathematical formulae are integrated in an accessible and intuitive way. The first part of the book explores how analog systems and signals form the basics of signal analysis. This section covers Fourier series and integral transforms of analog signals, Laplace and Hilbert transforms, the main analog filter classes, and signal modulations. Part II covers digital signals, demonstrating their key advantages. It presents z and Fourier transforms, digital filtering, inverse filters, deconvolution, and parametric modeling for deterministic signals. Wavelet decomposition and reconstruction of non-stationary signals are also discussed...

Wavelet analysis of nonstationary fluctuations of Monte Carlo-simulated excitatory postsynaptic currents.

Science.gov (United States)

Aristizabal, F; Glavinovic, M I

2003-10-01

Tracking spectral changes of rapidly varying signals is a demanding task. In this study, we explore on Monte Carlo-simulated glutamate-activated AMPA patch and synaptic currents whether a wavelet analysis offers such a possibility. Unlike Fourier methods that determine only the frequency content of a signal, the wavelet analysis determines both the frequency and the time. This is owing to the nature of the basis functions, which are infinite for Fourier transforms (sines and cosines are infinite), but are finite for wavelet analysis (wavelets are localized waves). In agreement with previous reports, the frequency of the stationary patch current fluctuations is higher for larger currents, whereas the mean-variance plots are parabolic. The spectra of the current fluctuations and mean-variance plots are close to the theoretically predicted values. The median frequency of the synaptic and nonstationary patch currents is, however, time dependent, though at the peak of synaptic currents, the median frequency is insensitive to the number of glutamate molecules released. Such time dependence demonstrates that the "composite spectra" of the current fluctuations gathered over the whole duration of synaptic currents cannot be used to assess the mean open time or effective mean open time of AMPA channels. The current (patch or synaptic) versus median frequency plots show hysteresis. The median frequency is thus not a simple reflection of the overall receptor saturation levels and is greater during the rise phase for the same saturation level. The hysteresis is due to the higher occupancy of the doubly bound state during the rise phase and not due to the spatial spread of the saturation disk, which remains remarkably constant. Albeit time dependent, the variance of the synaptic and nonstationary patch currents can be accurately determined. Nevertheless the evaluation of the number of AMPA channels and their single current from the mean-variance plots of patch or synaptic

Regression analysis of pulsed eddy current signals for inspection of steam generator tube support structures

International Nuclear Information System (INIS)

Buck, J.; Underhill, P.R.; Mokros, S.G.; Morelli, J.; Krause, T.W.; Babbar, V.K.; Lepine, B.

2015-01-01

Nuclear steam generator (SG) support structure degradation and fouling can result in damage to SG tubes and loss of SG efficiency. Conventional eddy current technology is extensively used to detect cracks, frets at supports and other flaws, but has limited capabilities in the presence of multiple degradation modes or fouling. Pulsed eddy current (PEC) combined with principal components analysis (PCA) and multiple linear regression models was examined for the inspection of support structure degradation and SG tube off-centering with the goal of extending results to include additional degradation modes. (author)

Compressive Sensing: Analysis of Signals in Radio Astronomy

Directory of Open Access Journals (Sweden)

Gaigals G.

2013-12-01

Full Text Available The compressive sensing (CS theory says that for some kind of signals there is no need to keep or transfer all the data acquired accordingly to the Nyquist criterion. In this work we investigate if the CS approach is applicable for recording and analysis of radio astronomy (RA signals. Since CS methods are applicable for the signals with sparse (and compressible representations, the compressibility of RA signals is verified. As a result, we identify which RA signals can be processed using CS, find the parameters which can improve or degrade CS application to RA results, describe the optimum way how to perform signal filtering in CS applications. Also, a range of virtual LabVIEW instruments are created for the signal analysis with the CS theory.

Biomedical signal analysis

CERN Document Server

Rangayyan, Rangaraj M

2015-01-01

The book will help assist a reader in the development of techniques for analysis of biomedical signals and computer aided diagnoses with a pedagogical examination of basic and advanced topics accompanied by over 350 figures and illustrations. Wide range of filtering techniques presented to address various applications. 800 mathematical expressions and equations. Practical questions, problems and laboratory exercises. Includes fractals and chaos theory with biomedical applications.

Analysis of acoustic sound signal for ONB measurement

International Nuclear Information System (INIS)

Park, S. J.; Kim, H. I.; Han, K. Y.; Chai, H. T.; Park, C.

2003-01-01

The onset of nucleate boiling (ONB) was measured in a test fuel bundle composed of several fuel element simulators (FES) by analysing the aquatic sound signals. In order measure ONBs, a hydrophone, a pre-amplifier, and a data acquisition system to acquire/process the aquatic signal was prepared. The acoustic signal generated in the coolant is converted to the current signal through the microphone. When the signal is analyzed in the frequency domain, each sound signal can be identified according to its origin of sound source. As the power is increased to a certain degree, a nucleate boiling is started. The frequent formation and collapse of the void bubbles produce sound signal. By measuring this sound signal one can pinpoint the ONB. Since the signal characteristics is identical for different mass flow rates, this method can be applicable for ascertaining ONB

Study on signal processing in Eddy current testing for defects in spline gear

International Nuclear Information System (INIS)

Lee, Jae Ho; Park, Tae Sug; Park, Ik Keun

2016-01-01

Eddy current testing (ECT) is commonly applied for the inspection of automated production lines of metallic products, because it has a high inspection speed and a reasonable price. When ECT is applied for the inspection of a metallic object having an uneven target surface, such as the spline gear of a spline shaft, it is difficult to distinguish between the original signal obtained from the sensor and the signal generated by a defect because of the relatively large surface signals having similar frequency distributions. To facilitate the detection of defect signals from the spline gear, implementation of high-order filters is essential, so that the fault signals can be distinguished from the surrounding noise signals, and simultaneously, the pass-band of the filter can be adjusted according to the status of each production line and the object to be inspected. We will examine the infinite impulse filters (IIR filters) available for implementing an advanced filter for ECT, and attempt to detect the flaw signals through optimization of system design parameters for detecting the signals at the system level

Signal analysis for failure detection

International Nuclear Information System (INIS)

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

1994-01-01

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

Observation of dark-current signals from the S-band structures of the SLAC linac

International Nuclear Information System (INIS)

Assmann, R.; Decker, F.J.; Seidel, M.; Siemann, R.H.; Whittum, D.

1997-07-01

It is well known that the electro-magnetic fields in high-gradient RF structures can cause electron emission from the metallic structure walls. If the emitted electrons are captured and accelerated by the accelerating fields so-called dark-current is induced. Dark-currents have been measured and studied for various RF-structures. In this paper the authors present measurements of RF induced signals for the SLC S-band structures. For nominal gradients of 17 MV/m it is shown that the dark-current can be strong enough to significantly reduce the signal-to-noise ratio of the SLC beam wire scanners. They also show results from RF measurements in the dipole band. The measurements are compared to more direct observations of dark-current and it is tried to connect the results to possible effects on the accelerated particle beam

Empirical Analysis and Characterization of Indoor GPS Signal Fading and Multipath Conditions

DEFF Research Database (Denmark)

Blunck, Henrik; Kjærgaard, Mikkel Baun; Godsk, Torben

2009-01-01

of earlier measurement campaigns to characterize GNSS signal conditions in indoor environments have been published prominently in the GNSS research literature, see, e.g. [1,2,3]. To allow for in-depth signal analysis, these campaigns use a variety of measuring machinery such as channel sounders, mobile...... signal generators and spectrum analyzers. Furthermore, the use-case-specific usability of GPS as an indoor positioning technology as been evaluated empirically on a higher level, see, e.g. [4]. In this paper we present results of a measurement campaign, designed to characterize indoor GNSS signal...... conditions. The work presented can therefore be seen as an effort to the campaigns mentioned above. As the focus of our work lies on the real-world usability of current GNSS technology for indoor use, we employ in our measurement campaign foremost commercial receivers with features, typical for the use cases...

Photoacoustic signal and noise analysis for Si thin plate: signal correction in frequency domain.

Science.gov (United States)

Markushev, D D; Rabasović, M D; Todorović, D M; Galović, S; Bialkowski, S E

2015-03-01

Methods for photoacoustic signal measurement, rectification, and analysis for 85 μm thin Si samples in the 20-20 000 Hz modulation frequency range are presented. Methods for frequency-dependent amplitude and phase signal rectification in the presence of coherent and incoherent noise as well as distortion due to microphone characteristics are presented. Signal correction is accomplished using inverse system response functions deduced by comparing real to ideal signals for a sample with well-known bulk parameters and dimensions. The system response is a piece-wise construction, each component being due to a particular effect of the measurement system. Heat transfer and elastic effects are modeled using standard Rosencweig-Gersho and elastic-bending theories. Thermal diffusion, thermoelastic, and plasmaelastic signal components are calculated and compared to measurements. The differences between theory and experiment are used to detect and correct signal distortion and to determine detector and sound-card characteristics. Corrected signal analysis is found to faithfully reflect known sample parameters.

Eddy current manual: v.1

International Nuclear Information System (INIS)

Cecco, V.S.; Van Drunen, G.; Sharp, F.L.

1983-09-01

This training and reference manual was assembled to provide those involved in eddy current testing with both the fundamental principles of the technique as well as the knowledge to deal with often complicated test results. A non-rigorous approach is used to simplify complex physical phenomena. Emphasis is placed on proper choice of test frequency and signal interpretation. Defect detection and diagnosis receive particular attention. Design and construction of probes are covered extensively since probes play a key role in eddy current testing. The advantages and limitations of various probe types are discussed. Electromagnetic theory, instrumentation, test methods and signal analysis are covered. Simplified derivations of probe response to test parameters are presented to develop a basic understanding of eddy current behaviour. Eddy current signals are presented on impedance plane diagrams throughout the manual since this is the most common display on modern, general purpose instruments. The use of Σphase lagΣ in signal analysis is covered in detail. To supplement theory, practical examples are presented to develop proficiency in performing inspections, and to illustrate how basic principles are applied to diagnose real signals

Theory of diamagnetic signal in current-free stellarators

International Nuclear Information System (INIS)

Pustovitov, Vladimir D.

2010-01-01

The toroidal magnetic flux through the plasma column is calculated analytically for current-free stellarators of arbitrary geometry without assumptions on the plasma shape, aspect ratio, etc. This is done with accuracy sufficient for extracting the contribution due to the finite plasma pressure from this flux. The final result is a formula relating the measured diamagnetic signal with β, the ratio of the plasma pressure to the magnetic pressure. This formula is obtained assuming small β and the relative depth of the magnetic well. These are natural conditions for stellarators, therefore the final result can be recommended for magnetic diagnostics without practical limitations. (author)

Wavelet analysis to decompose a vibration simulation signal to improve pre-distribution testing of packaging

Science.gov (United States)

Griffiths, K. R.; Hicks, B. J.; Keogh, P. S.; Shires, D.

2016-08-01

In general, vehicle vibration is non-stationary and has a non-Gaussian probability distribution; yet existing testing methods for packaging design employ Gaussian distributions to represent vibration induced by road profiles. This frequently results in over-testing and/or over-design of the packaging to meet a specification and correspondingly leads to wasteful packaging and product waste, which represent 15bn per year in the USA and €3bn per year in the EU. The purpose of the paper is to enable a measured non-stationary acceleration signal to be replaced by a constructed signal that includes as far as possible any non-stationary characteristics from the original signal. The constructed signal consists of a concatenation of decomposed shorter duration signals, each having its own kurtosis level. Wavelet analysis is used for the decomposition process into inner and outlier signal components. The constructed signal has a similar PSD to the original signal, without incurring excessive acceleration levels. This allows an improved and more representative simulated input signal to be generated that can be used on the current generation of shaker tables. The wavelet decomposition method is also demonstrated experimentally through two correlation studies. It is shown that significant improvements over current international standards for packaging testing are achievable; hence the potential for more efficient packaging system design is possible.

Numerical Investigation of the Microscopic Heat Current Inside a Nanofluid System Based on Molecular Dynamics Simulation and Wavelet Analysis.

Science.gov (United States)

Jia, Tao; Gao, Di

2018-04-03

Molecular dynamics simulation is employed to investigate the microscopic heat current inside an argon-copper nanofluid. Wavelet analysis of the microscopic heat current inside the nanofluid system is conducted. The signal of the microscopic heat current is decomposed into two parts: one is the approximation part; the other is the detail part. The approximation part is associated with the low-frequency part of the signal, and the detail part is associated with the high-frequency part of the signal. Both the probability distributions of the high-frequency and the low-frequency parts of the signals demonstrate Gaussian-like characteristics. The curves fit to data of the probability distribution of the microscopic heat current are established, and the parameters including the mean value and the standard deviation in the mathematical formulas of the curves show dramatic changes for the cases before and after adding copper nanoparticles into the argon base fluid.

Knee joint vibroarthrographic signal processing and analysis

CERN Document Server

Wu, Yunfeng

2015-01-01

This book presents the cutting-edge technologies of knee joint vibroarthrographic signal analysis for the screening and detection of knee joint injuries. It describes a number of effective computer-aided methods for analysis of the nonlinear and nonstationary biomedical signals generated by complex physiological mechanics. This book also introduces several popular machine learning and pattern recognition algorithms for biomedical signal classifications. The book is well-suited for all researchers looking to better understand knee joint biomechanics and the advanced technology for vibration arthrometry. Dr. Yunfeng Wu is an Associate Professor at the School of Information Science and Technology, Xiamen University, Xiamen, Fujian, China.

Multitaper spectral analysis of atmospheric radar signals

Directory of Open Access Journals (Sweden)

V. K. Anandan

2004-11-01

Full Text Available Multitaper spectral analysis using sinusoidal taper has been carried out on the backscattered signals received from the troposphere and lower stratosphere by the Gadanki Mesosphere-Stratosphere-Troposphere (MST radar under various conditions of the signal-to-noise ratio. Comparison of study is made with sinusoidal taper of the order of three and single tapers of Hanning and rectangular tapers, to understand the relative merits of processing under the scheme. Power spectra plots show that echoes are better identified in the case of multitaper estimation, especially in the region of a weak signal-to-noise ratio. Further analysis is carried out to obtain three lower order moments from three estimation techniques. The results show that multitaper analysis gives a better signal-to-noise ratio or higher detectability. The spectral analysis through multitaper and single tapers is subjected to study of consistency in measurements. Results show that the multitaper estimate is better consistent in Doppler measurements compared to single taper estimates. Doppler width measurements with different approaches were studied and the results show that the estimation was better in the multitaper technique in terms of temporal resolution and estimation accuracy.

Design Considerations for CMOS Current Mode Operational Amplifiers and Current Conveyors

DEFF Research Database (Denmark)

Bruun, Erik

implementations of current mode opamps in CMOS technology are described. Also, current conveyor configurations with multiple outputs and flexible feedback connections from outputs to inputs are introduced. The dissertation includes several examples of circuit configurations ranging from simple class A and class......This dissertation is about CMOS current conveyors and current mode operational amplifiers (opamps). They are generic devices for continuous time signal processing in circuits and systems where signals are represented by currents.Substantial advancements are reported in the dissertation, both...... related to circuit implementations and system configurations and to an analysis of the fundamental limitations of the current mode technique.In the field of system configurations and circuit implementations different configurations of high gain current opamps are introduced and some of the first...

Preliminary code development for seismic signal analysis related to test ban treaty questions

International Nuclear Information System (INIS)

Brolley, J.E.

1977-01-01

Forensic seismology, from a present day viewpoint, appears to be divided into several areas. Overwhelmingly important, in view of current Complete Test Ban (CTB) discussions, is the seismological study of waves generated in the earth by underground nuclear explosions. Over the last two decades intensive effort has been devoted to developing improved observational apparatus and to the interpretation of the data produced by this equipment. It is clearly desirable to extract the maximum amount of information from seismic signals. It is, therefore, necessary to quantitatively compare various modes of analysis to establish which mode or combination of modes provides the most useful information. Preliminary code development for application of some modern developments in signal processing to seismic signals is described. Applications of noncircular functions are considered and compared with circular function results. The second portion of the discussion concerns maximum entropy analysis. Lastly, the multivariate aspects of the general problem are considered

Eddy current testing, volume 1

International Nuclear Information System (INIS)

Cecco, V.S.; Van Drunen, G.; Sharp, F.L.

1981-11-01

This training and reference manual was assembled to provide those involved in eddy current testing with both the fundamental principles of the technique as well as the knowledge to deal with often complicated test results. A non-rigorous approach is used to simplify complex physical phenomena. Emphasis is placed on proper choice of test frequency and interpretation. Defect detection and diagnosis receive particular attention. Design and construction of probes are covered extensively since probes play a key role in eddy current testing. The advantages and limitations of various probe types are discussed. Electromagnetic theory, instrumentation, test methods and signal analysis are covered. Simplified derivations of probe response to test parameters are presented to develop a basic understanding of eddy current behaviour. Eddy current signals are presented on impedance plane diagrams throughout the manual since this is the most common display on modern, general purpose instruments. The use of 'phase leg' in signal analysis is covered in detail. To supplement theory, practical examples are presented to develop proficiency in performing inspections, and to illustrate how basic principles are applied to diagnose real signals

Analysis of photogenerated random telegraph signal in single electron detector (photo-SET).

Science.gov (United States)

Troudi, M; Sghaier, Na; Kalboussi, A; Souifi, A

2010-01-04

In this paper, we analyzed slow single traps, situated inside the tunnel oxide of small area single electron photo-detector (photo-SET or nanopixel). The relationship between excitation signal (photons) and random-telegraph-signal (RTS) was evidenced. We demonstrated that photoinduced RTS observed on a photo-detector is due to the interaction between single photogenerated charges that tunnel from dot to dot and current path. Based on RTS analysis for various temperatures, gate bias and optical power we determined the characteristics of these single photogenerated traps: the energy position within the silicon bandgap, capture cross section and the position within the Si/SiO(x = 1.5) interfaces.

Detection of motion artifact patterns in photoplethysmographic signals based on time and period domain analysis

International Nuclear Information System (INIS)

Couceiro, R; Carvalho, P; Paiva, R P; Henriques, J; Muehlsteff, J

2014-01-01

The presence of motion artifacts in photoplethysmographic (PPG) signals is one of the major obstacles in the extraction of reliable cardiovascular parameters in continuous monitoring applications. In the current paper we present an algorithm for motion artifact detection based on the analysis of the variations in the time and the period domain characteristics of the PPG signal. The extracted features are ranked using a normalized mutual information feature selection algorithm and the best features are used in a support vector machine classification model to distinguish between clean and corrupted sections of the PPG signal. The proposed method has been tested in healthy and cardiovascular diseased volunteers, considering 11 different motion artifact sources. The results achieved by the current algorithm (sensitivity—SE: 84.3%, specificity—SP: 91.5% and accuracy—ACC: 88.5%) show that the current methodology is able to identify both corrupted and clean PPG sections with high accuracy in both healthy (ACC: 87.5%) and cardiovascular diseases (ACC: 89.5%) context. (paper)

Radar signal analysis and processing using Matlab

CERN Document Server

Mahafza, Bassem R

2008-01-01

Offering radar-related software for the analysis and design of radar waveform and signal processing, this book provides comprehensive coverage of radar signals and signal processing techniques and algorithms. It contains numerous graphical plots, common radar-related functions, table format outputs, and end-of-chapter problems. The complete set of MATLAB[registered] functions and routines are available for download online.

On semi-classical questions related to signal analysis

KAUST Repository

Helffer, Bernard

2011-12-01

This study explores the reconstruction of a signal using spectral quantities associated with some self-adjoint realization of an h-dependent Schrödinger operator -h2(d2/dx2)-y(x), h>0, when the parameter h tends to 0. Theoretical results in semi-classical analysis are proved. Some numerical results are also presented. We first consider as a toy model the sech2 function. Then we study a real signal given by arterial blood pressure measurements. This approach seems to be very promising in signal analysis. Indeed it provides new spectral quantities that can give relevant information on some signals as it is the case for arterial blood pressure signal. © 2011 - IOS Press and the authors. All rights reserved.

Signals from flavor changing scalar neutral currents at μ+μ- colliders

International Nuclear Information System (INIS)

Reina, L.

1996-01-01

We illustrate the possibility of observing signals from Flavor Changing Neutral Currents, originating from the scalar sector of a Two Higgs Doublet Model. In particular, we focus on the tree level process μ + μ - → bar tc + bar ct, via scalar exchange in the s-channel, as a distinctive process for μ + μ - colliders. 12 refs., 1 fig

IQM: an extensible and portable open source application for image and signal analysis in Java.

Science.gov (United States)

Kainz, Philipp; Mayrhofer-Reinhartshuber, Michael; Ahammer, Helmut

2015-01-01

Image and signal analysis applications are substantial in scientific research. Both open source and commercial packages provide a wide range of functions for image and signal analysis, which are sometimes supported very well by the communities in the corresponding fields. Commercial software packages have the major drawback of being expensive and having undisclosed source code, which hampers extending the functionality if there is no plugin interface or similar option available. However, both variants cannot cover all possible use cases and sometimes custom developments are unavoidable, requiring open source applications. In this paper we describe IQM, a completely free, portable and open source (GNU GPLv3) image and signal analysis application written in pure Java. IQM does not depend on any natively installed libraries and is therefore runnable out-of-the-box. Currently, a continuously growing repertoire of 50 image and 16 signal analysis algorithms is provided. The modular functional architecture based on the three-tier model is described along the most important functionality. Extensibility is achieved using operator plugins, and the development of more complex workflows is provided by a Groovy script interface to the JVM. We demonstrate IQM's image and signal processing capabilities in a proof-of-principle analysis and provide example implementations to illustrate the plugin framework and the scripting interface. IQM integrates with the popular ImageJ image processing software and is aiming at complementing functionality rather than competing with existing open source software. Machine learning can be integrated into more complex algorithms via the WEKA software package as well, enabling the development of transparent and robust methods for image and signal analysis.

Orbiter CCTV video signal noise analysis

Science.gov (United States)

Lawton, R. M.; Blanke, L. R.; Pannett, R. F.

1977-01-01

The amount of steady state and transient noise which will couple to orbiter CCTV video signal wiring is predicted. The primary emphasis is on the interim system, however, some predictions are made concerning the operational system wiring in the cabin area. Noise sources considered are RF fields from on board transmitters, precipitation static, induced lightning currents, and induced noise from adjacent wiring. The most significant source is noise coupled to video circuits from associated circuits in common connectors. Video signal crosstalk is the primary cause of steady state interference, and mechanically switched control functions cause the largest induced transients.

Improved signal analysis for motional Stark effect data

International Nuclear Information System (INIS)

Makowski, M.A.; Allen, S.L.; Ellis, R.; Geer, R.; Jayakumar, R.J.; Moller, J.M.; Rice, B.W.

2005-01-01

Nonideal effects in the optical train of the motional Stark effect diagnostic have been modeled using the Mueller matrix formalism. The effects examined are birefringence in the vacuum windows, an imperfect reflective mirror, and signal pollution due to the presence of a circularly polarized light component. Relations for the measured intensity ratio are developed for each case. These relations suggest fitting functions to more accurately model the calibration data. One particular function, termed the tangent offset model, is found to fit the data for all channels better than the currently used tangent slope function. Careful analysis of the calibration data with the fitting functions reveals that a nonideal effect is present in the edge array and is attributed to nonideal performance of a mirror in that system. The result of applying the fitting function to the analysis of our data has been to improve the equilibrium reconstruction

Influence of sodium deposits in steam generator tubes on remote field eddy current signals

Energy Technology Data Exchange (ETDEWEB)

Thirunavukkarasu, S. [EMSI Section, NDE Division, Metallurgy and Materials Group, Indira Gandhi Centre for Atomic Research, Kalpakkam 603 102, Tamil Nadu (India); Rao, B.P.C. [EMSI Section, NDE Division, Metallurgy and Materials Group, Indira Gandhi Centre for Atomic Research, Kalpakkam 603 102, Tamil Nadu (India)], E-mail: bpcrao@igcar.gov.in; Vaidyanathan, S.; Jayakumar, T.; Raj, Baldev [EMSI Section, NDE Division, Metallurgy and Materials Group, Indira Gandhi Centre for Atomic Research, Kalpakkam 603 102, Tamil Nadu (India)

2008-04-15

The presence of sodium deposits in defective regions of steam generator (SG) tubes of fast-breeder reactors is expected to influence the remote field eddy current (RFEC) signals. By exposing five SG tubes having uniform wall loss grooves to a sodium environment in a specially designed test vessel, changes in the shape of RFEC signals were observed and it was possible to approximate the volume of sodium deposited in defects. An invariant signal parameter was determined for quantitative characterization of defects despite the presence of sodium in the defects.

Motor current signature analysis for gearbox condition monitoring under transient speeds using wavelet analysis and dual-level time synchronous averaging

Science.gov (United States)

Bravo-Imaz, Inaki; Davari Ardakani, Hossein; Liu, Zongchang; García-Arribas, Alfredo; Arnaiz, Aitor; Lee, Jay

2017-09-01

This paper focuses on analyzing motor current signature for fault diagnosis of gearboxes operating under transient speed regimes. Two different strategies are evaluated, extensively tested and compared to analyze the motor current signature in order to implement a condition monitoring system for gearboxes in industrial machinery. A specially designed test bench is used, thoroughly monitored to fully characterize the experiments, in which gears in different health status are tested. The measured signals are analyzed using discrete wavelet decomposition, in different decomposition levels using a range of mother wavelets. Moreover, a dual-level time synchronous averaging analysis is performed on the same signal to compare the performance of the two methods. From both analyses, the relevant features of the signals are extracted and cataloged using a self-organizing map, which allows for an easy detection and classification of the diverse health states of the gears. The results demonstrate the effectiveness of both methods for diagnosing gearbox faults. A slightly better performance was observed for dual-level time synchronous averaging method. Based on the obtained results, the proposed methods can used as effective and reliable condition monitoring procedures for gearbox condition monitoring using only motor current signature.

Pattern theory the stochastic analysis of real-world signals

CERN Document Server

Mumford, David

2010-01-01

Pattern theory is a distinctive approach to the analysis of all forms of real-world signals. At its core is the design of a large variety of probabilistic models whose samples reproduce the look and feel of the real signals, their patterns, and their variability. Bayesian statistical inference then allows you to apply these models in the analysis of new signals. This book treats the mathematical tools, the models themselves, and the computational algorithms for applying statistics to analyze six representative classes of signals of increasing complexity. The book covers patterns in text, sound

Analysis and prediction of leucine-rich nuclear export signals

DEFF Research Database (Denmark)

La Cour, T.; Kiemer, Lars; Mølgaard, Anne

2004-01-01

We present a thorough analysis of nuclear export signals and a prediction server, which we have made publicly available. The machine learning prediction method is a significant improvement over the generally used consensus patterns. Nuclear export signals (NESs) are extremely important regulators...... this analysis is that the most important properties of NESs are accessibility and flexibility allowing relevant proteins to interact with the signal. Furthermore, we show that not only the known hydrophobic residues are important in defining a nuclear export signals. We employ both neural networks and hidden...

Determination of outdoor signal propagation via visibility analysis in outdoor wireless networks

Directory of Open Access Journals (Sweden)

Mustafa Coşar

2017-02-01

Full Text Available Wireless networks on university campuses has gained importance in recent years. These networks in major areas such as university campuses, are faced with many problems during the planning, design and establishment. These problems are among the first that comes to mind, the physical properties of the campus and is selected according to the characteristics of network equipment. There is no doubt at all points of a wireless network set up in order to provide uninterrupted service and quality of the signal is expected to be good. However, it should be understood literally cannot meet these expectations. Therefore, to solve many problems to campus planning and design can be made to have acceptable signal distribution will have the appropriate use of and satisfaction with increasing effect. In this study, due to the start of construction on the North Campus of Hitit University, wireless signal spread using the current spread has been determined with the help of geographic information systems visibility analysis. An area of 56 hectares, with the total of 9 AP the acceptable signal distribution was obtained.

Filling gaps in PPAR-alpha signaling through comparative nutrigenomics analysis

Directory of Open Access Journals (Sweden)

Radonjic Marijana

2009-12-01

Full Text Available Abstract Background The application of high-throughput genomic tools in nutrition research is a widespread practice. However, it is becoming increasingly clear that the outcome of individual expression studies is insufficient for the comprehensive understanding of such a complex field. Currently, the availability of the large amounts of expression data in public repositories has opened up new challenges on microarray data analyses. We have focused on PPARα, a ligand-activated transcription factor functioning as fatty acid sensor controlling the gene expression regulation of a large set of genes in various metabolic organs such as liver, small intestine or heart. The function of PPARα is strictly connected to the function of its target genes and, although many of these have already been identified, major elements of its physiological function remain to be uncovered. To further investigate the function of PPARα, we have applied a cross-species meta-analysis approach to integrate sixteen microarray datasets studying high fat diet and PPARα signal perturbations in different organisms. Results We identified 164 genes (MDEGs that were differentially expressed in a constant way in response to a high fat diet or to perturbations in PPARs signalling. In particular, we found five genes in yeast which were highly conserved and homologous of PPARα targets in mammals, potential candidates to be used as models for the equivalent mammalian genes. Moreover, a screening of the MDEGs for all known transcription factor binding sites and the comparison with a human genome-wide screening of Peroxisome Proliferating Response Elements (PPRE, enabled us to identify, 20 new potential candidate genes that show, both binding site, both change in expression in the condition studied. Lastly, we found a non random localization of the differentially expressed genes in the genome. Conclusion The results presented are potentially of great interest to resume the currently

Fluorescence In Situ Hybridization (FISH Signal Analysis Using Automated Generated Projection Images

Directory of Open Access Journals (Sweden)

Xingwei Wang

2012-01-01

Full Text Available Fluorescence in situ hybridization (FISH tests provide promising molecular imaging biomarkers to more accurately and reliably detect and diagnose cancers and genetic disorders. Since current manual FISH signal analysis is low-efficient and inconsistent, which limits its clinical utility, developing automated FISH image scanning systems and computer-aided detection (CAD schemes has been attracting research interests. To acquire high-resolution FISH images in a multi-spectral scanning mode, a huge amount of image data with the stack of the multiple three-dimensional (3-D image slices is generated from a single specimen. Automated preprocessing these scanned images to eliminate the non-useful and redundant data is important to make the automated FISH tests acceptable in clinical applications. In this study, a dual-detector fluorescence image scanning system was applied to scan four specimen slides with FISH-probed chromosome X. A CAD scheme was developed to detect analyzable interphase cells and map the multiple imaging slices recorded FISH-probed signals into the 2-D projection images. CAD scheme was then applied to each projection image to detect analyzable interphase cells using an adaptive multiple-threshold algorithm, identify FISH-probed signals using a top-hat transform, and compute the ratios between the normal and abnormal cells. To assess CAD performance, the FISH-probed signals were also independently visually detected by an observer. The Kappa coefficients for agreement between CAD and observer ranged from 0.69 to 1.0 in detecting/counting FISH signal spots in four testing samples. The study demonstrated the feasibility of automated FISH signal analysis that applying a CAD scheme to the automated generated 2-D projection images.

Reliability analysis for Atucha II reactor protection system signals

International Nuclear Information System (INIS)

Roca, Jose Luis

1996-01-01

Atucha II is a 745 MW Argentine Power Nuclear Reactor constructed by ENACE SA, Nuclear Argentine Company for Electrical Power Generation and SIEMENS AG KWU, Erlangen, Germany. A preliminary modular logic analysis of RPS (Reactor Protection System) signals was performed by means of the well known Swedish professional risk and reliability software named Risk-Spectrum taking as a basis a reference signal coded as JR17ER003 which command the two moderator loops valves. From the reliability and behavior knowledge for this reference signal follows an estimation of the reliability for the other 97 RPS signals. Because the preliminary character of this analysis Main Important Measures are not performed at this stage. Reliability is by the statistic value named unavailability predicted. The scope of this analysis is restricted from the measurement elements to the RPS buffer outputs. In the present context only one redundancy is analyzed so in the Instrumentation and Control area there no CCF (Common Cause Failures) present for signals. Finally those unavailability values could be introduced in the failure domain for the posterior complete Atucha II reliability analysis which includes all mechanical and electromechanical features. Also an estimation of the spurious frequency of RPS signals defined as faulty by no trip is performed

Reliability analysis for Atucha II reactor protection system signals

International Nuclear Information System (INIS)

Roca, Jose L.

2000-01-01

Atucha II is a 745 MW Argentine power nuclear reactor constructed by Nuclear Argentine Company for Electric Power Generation S.A. (ENACE S.A.) and SIEMENS AG KWU, Erlangen, Germany. A preliminary modular logic analysis of RPS (Reactor Protection System) signals was performed by means of the well known Swedish professional risk and reliability software named Risk-Spectrum taking as a basis a reference signal coded as JR17ER003 which command the two moderator loops valves. From the reliability and behavior knowledge for this reference signal follows an estimation of the reliability for the other 97 RPS signals. Because the preliminary character of this analysis Main Important Measures are not performed at this stage. Reliability is by the statistic value named unavailability predicted. The scope of this analysis is restricted from the measurement elements to the RPS buffer outputs. In the present context only one redundancy is analyzed so in the Instrumentation and Control area there no CCF (Common Cause Failures) present for signals. Finally those unavailability values could be introduced in the failure domain for the posterior complete Atucha II reliability analysis which includes all mechanical and electromechanical features. Also an estimation of the spurious frequency of RPS signals defined as faulty by no trip is performed. (author)

Mathematical principles of signal processing Fourier and wavelet analysis

CERN Document Server

Brémaud, Pierre

2002-01-01

Fourier analysis is one of the most useful tools in many applied sciences. The recent developments of wavelet analysis indicates that in spite of its long history and well-established applications, the field is still one of active research. This text bridges the gap between engineering and mathematics, providing a rigorously mathematical introduction of Fourier analysis, wavelet analysis and related mathematical methods, while emphasizing their uses in signal processing and other applications in communications engineering. The interplay between Fourier series and Fourier transforms is at the heart of signal processing, which is couched most naturally in terms of the Dirac delta function and Lebesgue integrals. The exposition is organized into four parts. The first is a discussion of one-dimensional Fourier theory, including the classical results on convergence and the Poisson sum formula. The second part is devoted to the mathematical foundations of signal processing - sampling, filtering, digital signal proc...

Performance Analysis of Control Signal Transmission Technique for Cognitive Radios in Dynamic Spectrum Access Networks

Science.gov (United States)

Sakata, Ren; Tomioka, Tazuko; Kobayashi, Takahiro

When cognitive radio (CR) systems dynamically use the frequency band, a control signal is necessary to indicate which carrier frequencies are currently available in the network. In order to keep efficient spectrum utilization, this control signal also should be transmitted based on the channel conditions. If transmitters dynamically select carrier frequencies, receivers have to receive control signals without knowledge of their carrier frequencies. To enable such transmission and reception, this paper proposes a novel scheme called DCPT (Differential Code Parallel Transmission). With DCPT, receivers can receive low-rate information with no knowledge of the carrier frequencies. The transmitter transmits two signals whose carrier frequencies are spaced by a predefined value. The absolute values of the carrier frequencies can be varied. When the receiver acquires the DCPT signal, it multiplies the signal by a frequency-shifted version of the signal; this yields a DC component that represents the data signal which is then demodulated. The performance was evaluated by means of numerical analysis and computer simulation. We confirmed that DCPT operates successfully even under severe interference if its parameters are appropriately configured.

Phosphoproteomics-based systems analysis of signal transduction networks

Directory of Open Access Journals (Sweden)

Hiroko eKozuka-Hata

2012-01-01

Full Text Available Signal transduction systems coordinate complex cellular information to regulate biological events such as cell proliferation and differentiation. Although the accumulating evidence on widespread association of signaling molecules has revealed essential contribution of phosphorylation-dependent interaction networks to cellular regulation, their dynamic behavior is mostly yet to be analyzed. Recent technological advances regarding mass spectrometry-based quantitative proteomics have enabled us to describe the comprehensive status of phosphorylated molecules in a time-resolved manner. Computational analyses based on the phosphoproteome dynamics accelerate generation of novel methodologies for mathematical analysis of cellular signaling. Phosphoproteomics-based numerical modeling can be used to evaluate regulatory network elements from a statistical point of view. Integration with transcriptome dynamics also uncovers regulatory hubs at the transcriptional level. These omics-based computational methodologies, which have firstly been applied to representative signaling systems such as the epidermal growth factor receptor pathway, have now opened up a gate for systems analysis of signaling networks involved in immune response and cancer.

Melatonin potentiates glycine currents through a PLC/PKC signalling pathway in rat retinal ganglion cells.

Science.gov (United States)

Zhao, Wen-Jie; Zhang, Min; Miao, Yanying; Yang, Xiong-Li; Wang, Zhongfeng

2010-07-15

In vertebrate retina, melatonin regulates various physiological functions. In this work we investigated the mechanisms underlying melatonin-induced potentiation of glycine currents in rat retinal ganglion cells (RGCs). Immunofluorescence double labelling showed that rat RGCs were solely immunoreactive to melatonin MT(2) receptors. Melatonin potentiated glycine currents of RGCs, which was reversed by the MT(2) receptor antagonist 4-P-PDOT. The melatonin effect was blocked by intracellular dialysis of GDP-beta-S. Either preincubation with pertussis toxin or application of the phosphatidylcholine (PC)-specific phospholipase C (PLC) inhibitor D609, but not the phosphatidylinositol (PI)-PLC inhibitor U73122, blocked the melatonin effect. The protein kinase C (PKC) activator PMA potentiated the glycine currents and in the presence of PMA melatonin failed to cause further potentiation of the currents, whereas application of the PKC inhibitor bisindolylmaleimide IV abolished the melatonin-induced potentiation. The melatonin effect persisted when [Ca(2+)](i) was chelated by BAPTA, and melatonin induced no increase in [Ca(2+)](i). Neither cAMP-PKA nor cGMP-PKG signalling pathways seemed to be involved because 8-Br-cAMP or 8-Br-cGMP failed to cause potentiation of the glycine currents and both the PKA inhibitor H-89 and the PKG inhibitor KT5823 did not block the melatonin-induced potentiation. In consequence, a distinct PC-PLC/PKC signalling pathway, following the activation of G(i/o)-coupled MT(2) receptors, is most likely responsible for the melatonin-induced potentiation of glycine currents of rat RGCs. Furthermore, in rat retinal slices melatonin potentiated light-evoked glycine receptor-mediated inhibitory postsynaptic currents in RGCs. These results suggest that melatonin, being at higher levels at night, may help animals to detect positive or negative contrast in night vision by modulating inhibitory signals largely mediated by glycinergic amacrine cells in the inner

Processing and Analysis of Multichannel Extracellular Neuronal Signals: State-of-the-art and Challenges

Directory of Open Access Journals (Sweden)

Mufti eMahmud

2016-06-01

Full Text Available In recent years multichannel neuronal signal acquisition systems have allowed scientists to focus on research questions which were otherwise impossible. They act as a powerful means to study brain (dysfunctions in in-vivo and in in-vitro animal models. Typically, each session of electrophysiological experiments with multichannel data acquisition systems generate large amount of raw data. For example, a 128 channel signal acquisition system with 16 bits A/D conversion and 20 kHz sampling rate will generate approximately 17 GB data per hour (uncompressed. This poses an important and challenging problem of inferring conclusions from the large amounts of acquired data. Thus, automated signal processing and analysis tools are becoming a key component in neuroscience research, facilitating extraction of relevant information from neuronal recordings in a reasonable time. The purpose of this review is to introduce the reader to the current state-of-the-art of open-source packages for (semiautomated processing and analysis of multichannel extracellular neuronal signals (i.e., neuronal spikes, local field potentials, electroencephalogram, etc., and the existing Neuroinformatics infrastructure for tool and data sharing. The review is concluded by pinpointing some major challenges that are to be faced, which include the development of novel benchmarking techniques, cloud-based distributed processing and analysis tools, as well as defining novel means to share and standardize data.

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

Directory of Open Access Journals (Sweden)

Chaman Verma

2018-03-01

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

Signal and image multiresolution analysis

CERN Document Server

Ouahabi, Abdelialil

2012-01-01

Multiresolution analysis using the wavelet transform has received considerable attention in recent years by researchers in various fields. It is a powerful tool for efficiently representing signals and images at multiple levels of detail with many inherent advantages, including compression, level-of-detail display, progressive transmission, level-of-detail editing, filtering, modeling, fractals and multifractals, etc.This book aims to provide a simple formalization and new clarity on multiresolution analysis, rendering accessible obscure techniques, and merging, unifying or completing

High-dimensional analysis of the aging immune system: verification of age-associated differences in immune signaling responses in healthy donors.

Science.gov (United States)

Longo, Diane M; Louie, Brent; Ptacek, Jason; Friedland, Greg; Evensen, Erik; Putta, Santosh; Atallah, Michelle; Spellmeyer, David; Wang, Ena; Pos, Zoltan; Marincola, Francesco M; Schaeffer, Andrea; Lukac, Suzanne; Railkar, Radha; Beals, Chan R; Cesano, Alessandra; Carayannopoulos, Leonidas N; Hawtin, Rachael E

2014-06-21

Single-cell network profiling (SCNP) is a multiparametric flow cytometry-based approach that simultaneously measures evoked signaling in multiple cell subsets. Previously, using the SCNP approach, age-associated immune signaling responses were identified in a cohort of 60 healthy donors. In the current study, a high-dimensional analysis of intracellular signaling was performed by measuring 24 signaling nodes in 7 distinct immune cell subsets within PBMCs in an independent cohort of 174 healthy donors [144 elderly (>65 yrs); 30 young (25-40 yrs)]. Associations between age and 9 immune signaling responses identified in the previously published 60 donor cohort were confirmed in the current study. Furthermore, within the current study cohort, 48 additional immune signaling responses differed significantly between young and elderly donors. These associations spanned all profiled modulators and immune cell subsets. These results demonstrate that SCNP, a systems-based approach, can capture the complexity of the cellular mechanisms underlying immunological aging. Further, the confirmation of age associations in an independent donor cohort supports the use of SCNP as a tool for identifying reproducible predictive biomarkers in areas such as vaccine response and response to cancer immunotherapies.

Current and sea-level signals in periplatform ooze (Neogene, Maldives, Indian Ocean)

Science.gov (United States)

Betzler, Christian; Lüdmann, Thomas; Hübscher, Christian; Fürstenau, Jörn

2013-05-01

Periplatform ooze is an admixture of pelagic carbonate and sediment derived from neritic carbonate platforms. Compositional variations of periplatform ooze allow the reconstruction of past sea-level changes. Periplatform ooze formed during sea-level highstands is finer grained and richer in aragonite through the elevated input of material from the flooded platform compared to periplatform ooze formed during the episodes of lowered sea level. In many cases, however, the sea floor around carbonate platforms is subjected to bottom currents which are expected to affect sediment composition, i.e. through winnowing of the fine fraction. The interaction of sea-level driven highstand shedding and current impact on the formation of periplatform ooze has hitherto not been analyzed. To test if a sea-level driven input signal in periplatform ooze is influenced or even distorted by changing current activity, an integrated study using seismic, hydroacoustic and sedimentological data has been performed on periplatform ooze deposited in the Inner Sea of the Maldives. The Miocene to Pleistocene succession of drift deposits is subdivided into nine units; limits of seismostratigraphic units correspond to changes or turnarounds in grain size trends in cores recovered at ODP Site 716 and NEOMA Site 1143. For the Pleistocene it can be shown how changes in grain size occur in concert with sea-level changes and changes of the monsoonal system, which is thought to be a major driver of bottom currents in the Maldives. A clear highstand shedding pattern only appears in the data at a time of relaxation of monsoonal strength during the last 315 ky. Results imply (1) that drift sediments provide a potential target for analyzing past changes in oceanic currents and (2) that the ooze composition bears a mixed signal of input and physical winnowing at the sea floor.

Signal Adaptive System for Space/Spatial-Frequency Analysis

Directory of Open Access Journals (Sweden)

Veselin N. Ivanović

2009-01-01

Full Text Available This paper outlines the development of a multiple-clock-cycle implementation (MCI of a signal adaptive two-dimensional (2D system for space/spatial-frequency (S/SF signal analysis. The design is based on a method for improved S/SF representation of the analyzed 2D signals, also proposed here. The proposed MCI design optimizes critical design performances related to hardware complexity, making it a suitable system for real time implementation on an integrated chip. Additionally, the design allows the implemented system to take a variable number of clock cycles (CLKs (the only necessary ones regarding desirable—2D Wigner distribution-presentation of autoterms in different frequency-frequency points during the execution. This ability represents a major advantage of the proposed design which helps to optimize the time required for execution and produce an improved, cross-terms-free S/SF signal representation. The design has been verified by a field-programmable gate array (FPGA circuit design, capable of performing S/SF analysis of 2D signals in real time.

Quantitative Analysis of Signaling Networks across Differentially Embedded Tumors Highlights Interpatient Heterogeneity in Human Glioblastoma

Science.gov (United States)

2015-01-01

Glioblastoma multiforme (GBM) is the most aggressive malignant primary brain tumor, with a dismal mean survival even with the current standard of care. Although in vitro cell systems can provide mechanistic insight into the regulatory networks governing GBM cell proliferation and migration, clinical samples provide a more physiologically relevant view of oncogenic signaling networks. However, clinical samples are not widely available and may be embedded for histopathologic analysis. With the goal of accurately identifying activated signaling networks in GBM tumor samples, we investigated the impact of embedding in optimal cutting temperature (OCT) compound followed by flash freezing in LN2 vs immediate flash freezing (iFF) in LN2 on protein expression and phosphorylation-mediated signaling networks. Quantitative proteomic and phosphoproteomic analysis of 8 pairs of tumor specimens revealed minimal impact of the different sample processing strategies and highlighted the large interpatient heterogeneity present in these tumors. Correlation analyses of the differentially processed tumor sections identified activated signaling networks present in selected tumors and revealed the differential expression of transcription, translation, and degradation associated proteins. This study demonstrates the capability of quantitative mass spectrometry for identification of in vivo oncogenic signaling networks from human tumor specimens that were either OCT-embedded or immediately flash-frozen. PMID:24927040

Photoacoustic signal attenuation analysis for the assessment of thin layers thickness in paintings

Science.gov (United States)

Tserevelakis, George J.; Dal Fovo, Alice; Melessanaki, Krystalia; Fontana, Raffaella; Zacharakis, Giannis

2018-03-01

This study introduces a novel method for the thickness estimation of thin paint layers in works of art, based on photoacoustic signal attenuation analysis (PAcSAA). Ad hoc designed samples with acrylic paint layers (Primary Red Magenta, Cadmium Yellow, Ultramarine Blue) of various thicknesses on glass substrates were realized for the specific application. After characterization by Optical Coherence Tomography imaging, samples were irradiated at the back side using low energy nanosecond laser pulses of 532 nm wavelength. Photoacoustic waves undergo a frequency-dependent exponential attenuation through the paint layer, before being detected by a broadband ultrasonic transducer. Frequency analysis of the recorded time-domain signals allows for the estimation of the average transmitted frequency function, which shows an exponential decay with the layer thickness. Ultrasonic attenuation models were obtained for each pigment and used to fit the data acquired on an inhomogeneous painted mock-up simulating a real canvas painting. Thickness evaluation through PAcSAA resulted in excellent agreement with cross-section analysis with a conventional brightfield microscope. The results of the current study demonstrate the potential of the proposed PAcSAA method for the non-destructive stratigraphic analysis of painted artworks.

Source Signals Separation and Reconstruction Following Principal Component Analysis

Directory of Open Access Journals (Sweden)

WANG Cheng

2014-02-01

Full Text Available For separation and reconstruction of source signals from observed signals problem, the physical significance of blind source separation modal and independent component analysis is not very clear, and its solution is not unique. Aiming at these disadvantages, a new linear and instantaneous mixing model and a novel source signals separation reconstruction solving method from observed signals based on principal component analysis (PCA are put forward. Assumption of this new model is statistically unrelated rather than independent of source signals, which is different from the traditional blind source separation model. A one-to-one relationship between linear and instantaneous mixing matrix of new model and linear compound matrix of PCA, and a one-to-one relationship between unrelated source signals and principal components are demonstrated using the concept of linear separation matrix and unrelated of source signals. Based on this theoretical link, source signals separation and reconstruction problem is changed into PCA of observed signals then. The theoretical derivation and numerical simulation results show that, in despite of Gauss measurement noise, wave form and amplitude information of unrelated source signal can be separated and reconstructed by PCA when linear mixing matrix is column orthogonal and normalized; only wave form information of unrelated source signal can be separated and reconstructed by PCA when linear mixing matrix is column orthogonal but not normalized, unrelated source signal cannot be separated and reconstructed by PCA when mixing matrix is not column orthogonal or linear.

Applications of wavelet transforms for nuclear power plant signal analysis

International Nuclear Information System (INIS)

Seker, S.; Turkcan, E.; Upadhyaya, B.R.; Erbay, A.S.

1998-01-01

The safety of Nuclear Power Plants (NPPs) may be enhanced by the timely processing of information derived from multiple process signals from NPPs. The most widely used technique in signal analysis applications is the Fourier transform in the frequency domain to generate power spectral densities (PSD). However, the Fourier transform is global in nature and will obscure any non-stationary signal feature. Lately, a powerful technique called the Wavelet Transform, has been developed. This transform uses certain basis functions for representing the data in an effective manner, with capability for sub-band analysis and providing time-frequency localization as needed. This paper presents a brief overview of wavelets applied to the nuclear industry for signal processing and plant monitoring. The basic theory of Wavelets is also summarized. In order to illustrate the application of wavelet transforms data were acquired from the operating nuclear power plant Borssele in the Netherlands. The experimental data consist of various signals in the power plant and are selected from a stationary power operation. Their frequency characteristics and the mutual relations were investigated using MATLAB signal processing and wavelet toolbox for computing their PSDs and coherence functions by multi-resolution analysis. The results indicate that the sub-band PSD matches with the original signal PSD and enhances the estimation of coherence functions. The Wavelet analysis demonstrates the feasibility of application to stationary signals to provide better estimates in the frequency band of interest as compared to the classical FFT approach. (author)

Note for the Mirnov signal analysis in tokamaks

International Nuclear Information System (INIS)

Kikuchi, M.

1985-05-01

The relation between Mirnov coil signals and the current perturbation on the rational surface is examined analytically by using the approximate Green's function for the case of large aspect ratio circular tokamaks. Satellite island formation, phase modulation effect due to the poloidal variation of the field line pitch, and the shift effect of the plasma column with respect to the center of the vacuum chamber are examined. The detectability of these effects from Mirnov coil signals is discussed for TFTR

Analysis of signal acquisition in GPS receiver software

Directory of Open Access Journals (Sweden)

Vlada S. Sokolović

2011-01-01

Full Text Available This paper presents a critical analysis of the flow signal processing carried out in GPS receiver software, which served as a basis for a critical comparison of different signal processing architectures within the GPS receiver. It is possible to achieve Increased flexibility and reduction of GPS device commercial costs, including those of mobile devices, by using radio technology software (SDR, Software Defined Radio. The SDR application can be realized when certain hardware components in a GPS receiver are replaced. Signal processing in the SDR is implemented using a programmable DSP (Digital Signal Processing or FPGA (Field Programmable Gate Array circuit, which allows a simple change of digital signal processing algorithms and a simple change of the receiver parameters. The starting point of the research is the signal generated on the satellite the structure of which is shown in the paper. Based on the GPS signal structure, a receiver is realized with a task to extract an appropriate signal from the spectrum and detect it. Based on collected navigation data, the receiver calculates the position of the end user. The signal coming from the satellite may be at the carrier frequencies of L1 and L2. Since the SPS is used in the civil service, all the tests shown in the work were performed on the L1 signal. The signal coming to the receiver is generated in the spread spectrum technology and is situated below the level of noise. Such signals often interfere with signals from the environment which presents a difficulty for a receiver to perform proper detection and signal processing. Therefore, signal processing technology is continually being improved, aiming at more accurate and faster signal processing. All tests were carried out on a signal acquired from the satellite using the SE4110 input circuit used for filtering, amplification and signal selection. The samples of the received signal were forwarded to a computer for data post processing, i. e

Acceleration Signal Characteristics for Intuitional Mass Analysis of Metallic Loose Parts

International Nuclear Information System (INIS)

Lee, Kwang-Hyun; Jung, Chang-Gyu

2016-01-01

Nuclear power plants (NPPs) have operated LPMS (Loose Parts Monitoring System) for early detection of the possible presence of metallic parts in the reactor coolant system (RCS); however, analysis of the metallic impact wave characteristics in the LPMS is an important issue because information, such as the mass of the metallic part and the impact location, is not provided. Most studies have concentrated on fieldwork using the frequency characteristics for the analysis of the metallic part mass. Thus, the field engineers cannot analyze signals without special software and access to the system. This paper is intended to introduce a process of intuitional mass analysis using the attenuation rate of the acceleration signal and the intervals between peak signals. Most studies related to mass analysis of a metallic part impact signal in LPMS have used the frequency spectrum. This paper presents a method of using the acceleration signal characteristics for intuitional mass analysis of loose metallic parts. With the method proposed in this paper, because the mass of a metallic part can be understood intuitionally without any special analysis program, intuitional analysis used in parallel with frequency spectrum analysis will be in effect

Acceleration Signal Characteristics for Intuitional Mass Analysis of Metallic Loose Parts

Energy Technology Data Exchange (ETDEWEB)

Lee, Kwang-Hyun; Jung, Chang-Gyu [KHNP CRI, Daejeon (Korea, Republic of)

2016-10-15

Nuclear power plants (NPPs) have operated LPMS (Loose Parts Monitoring System) for early detection of the possible presence of metallic parts in the reactor coolant system (RCS); however, analysis of the metallic impact wave characteristics in the LPMS is an important issue because information, such as the mass of the metallic part and the impact location, is not provided. Most studies have concentrated on fieldwork using the frequency characteristics for the analysis of the metallic part mass. Thus, the field engineers cannot analyze signals without special software and access to the system. This paper is intended to introduce a process of intuitional mass analysis using the attenuation rate of the acceleration signal and the intervals between peak signals. Most studies related to mass analysis of a metallic part impact signal in LPMS have used the frequency spectrum. This paper presents a method of using the acceleration signal characteristics for intuitional mass analysis of loose metallic parts. With the method proposed in this paper, because the mass of a metallic part can be understood intuitionally without any special analysis program, intuitional analysis used in parallel with frequency spectrum analysis will be in effect.

Tunable Signal-Off and Signal-On Electrochemical Cisplatin Sensor.

Science.gov (United States)

Wu, Yao; Lai, Rebecca Y

2017-09-19

We report the first electrochemical cisplatin sensor fabricated with a thiolated and methylene blue (MB)-modified oligo-adenine (A)-guanine (G) DNA probe. Depending on the probe coverage, the sensor can behave as a signal-off or signal-on sensor. For the high-coverage sensor, formation of intrastrand Pt(II)-AG adducts rigidifies the oligo-AG probe, resulting in a concentration-dependent decrease in the MB signal. For the low-coverage sensor, the increase in probe-to-probe spacing enables binding of cisplatin via the intrastrand GNG motif (N = A), generating a bend in the probe which results in an increase in the MB current. Although both high-coverage signal-off and low-coverage signal-on sensors are capable of detecting cisplatin, the signal-on sensing mechanism is better suited for real time analysis of cisplatin. The low-coverage sensor has a lower limit of detection, wider optimal AC frequency range, and faster response time. It has high specificity for cisplatin and potentially other Pt(II) drugs and does not cross-react with satraplatin, a Pt(IV) prodrug. It is also selective enough to be employed directly in 50% saliva and 50% urine. This detection strategy may offer a new approach for sensitive and real time analysis of cisplatin in clinical samples.

Signals and transforms in linear systems analysis

CERN Document Server

Wasylkiwskyj, Wasyl

2013-01-01

Signals and Transforms in Linear Systems Analysis covers the subject of signals and transforms, particularly in the context of linear systems theory. Chapter 2 provides the theoretical background for the remainder of the text. Chapter 3 treats Fourier series and integrals. Particular attention is paid to convergence properties at step discontinuities. This includes the Gibbs phenomenon and its amelioration via the Fejer summation techniques. Special topics include modulation and analytic signal representation, Fourier transforms and analytic function theory, time-frequency analysis and frequency dispersion. Fundamentals of linear system theory for LTI analogue systems, with a brief account of time-varying systems, are covered in Chapter 4 . Discrete systems are covered in Chapters 6 and 7.  The Laplace transform treatment in Chapter 5 relies heavily on analytic function theory as does Chapter 8 on Z -transforms. The necessary background on complex variables is provided in Appendix A. This book is intended to...

[Computers in biomedical research: I. Analysis of bioelectrical signals].

Science.gov (United States)

Vivaldi, E A; Maldonado, P

2001-08-01

A personal computer equipped with an analog-to-digital conversion card is able to input, store and display signals of biomedical interest. These signals can additionally be submitted to ad-hoc software for analysis and diagnosis. Data acquisition is based on the sampling of a signal at a given rate and amplitude resolution. The automation of signal processing conveys syntactic aspects (data transduction, conditioning and reduction); and semantic aspects (feature extraction to describe and characterize the signal and diagnostic classification). The analytical approach that is at the basis of computer programming allows for the successful resolution of apparently complex tasks. Two basic principles involved are the definition of simple fundamental functions that are then iterated and the modular subdivision of tasks. These two principles are illustrated, respectively, by presenting the algorithm that detects relevant elements for the analysis of a polysomnogram, and the task flow in systems that automate electrocardiographic reports.

Signal intensity analysis and optimization for in vivo imaging of Cherenkov and excited luminescence

Science.gov (United States)

LaRochelle, Ethan P. M.; Shell, Jennifer R.; Gunn, Jason R.; Davis, Scott C.; Pogue, Brian W.

2018-04-01

During external beam radiotherapy (EBRT), in vivo Cherenkov optical emissions can be used as a dosimetry tool or to excite luminescence, termed Cherenkov-excited luminescence (CEL) with microsecond-level time-gated cameras. The goal of this work was to develop a complete theoretical foundation for the detectable signal strength, in order to provide guidance on optimization of the limits of detection and how to optimize near real time imaging. The key parameters affecting photon production, propagation and detection were considered and experimental validation with both tissue phantoms and a murine model are shown. Both the theoretical analysis and experimental data indicate that the detection level is near a single photon-per-pixel for the detection geometry and frame rates commonly used, with the strongest factor being the signal decrease with the square of distance from tissue to camera. Experimental data demonstrates how the SNR improves with increasing integration time, but only up to the point where the dominance of camera read noise is overcome by stray photon noise that cannot be suppressed. For the current camera in a fixed geometry, the signal to background ratio limits the detection of light signals, and the observed in vivo Cherenkov emission is on the order of 100×  stronger than CEL signals. As a result, imaging signals from depths  <15 mm is reasonable for Cherenkov light, and depths  <3 mm is reasonable for CEL imaging. The current investigation modeled Cherenkov and CEL imaging of two oxygen sensing phosphorescent compounds, but the modularity of the code allows for easy comparison of different agents or alternative cameras, geometries or tissues.

Signal Characteristics of Eddy Current Test for Intergranular Attack of Steam Generator Tubes

International Nuclear Information System (INIS)

Choi, Myung Sik; Lee, Deok Hyun; Han, Jung Ho; Hur, Do Haeng; Cho, Se Gon; Yim, Chang Jae

2002-01-01

Because intergranular attack (IGA), one of the localized corrosion forms occurring on steam generator tubes, can not be fabricated by an electric discharge machining method, there are few data for the eddy current test (ECT) characteristics of IGA. In this paper, the characteristics of eddy current signals are evaluated using nonexpanded tubes with IGA defects formed in 0.1 M sodium tetrathionate solution at 40 .deg. C. The detectability and sizing accuracy of IGA were discussed in terms of the coil type and frequency of the ECT probes

A Comparison of Alternating Current and Direct Current Electrospray Ionization for Mass Spectrometry

Science.gov (United States)

Sarver, Scott A.; Chetwani, Nishant; Dovichi, Norman J.; Go, David B.; Gartner, Carlos A.

2014-04-01

A series of studies comparing the performance of alternating current electrospray ionization (AC ESI) mass spectrometry (MS) and direct current electrospray ionization (DC ESI) MS have been conducted, exploring the absolute signal intensity and signal-to-background ratios produced by both methods using caffeine and a model peptide as targets. Because the high-voltage AC signal was more susceptible to generating gas discharges, the operating voltage range of AC ESI was significantly smaller than that for DC ESI, such that the absolute signal intensities produced by DC ESI at peak voltages were one to two orders of magnitude greater than those for AC ESI. Using an electronegative nebulizing gas, sulfur hexafluoride (SF6), instead of nitrogen (N2) increased the operating range of AC ESI by ~50 %, but did not appreciably improve signal intensities. While DC ESI generated far greater signal intensities, both ionization methods produced comparable signal-to-background noise, with AC ESI spectra appearing qualitatively cleaner. A quantitative calibration analysis was performed for two analytes, caffeine and the peptide MRFA. AC ESI utilizing SF6 outperforms all other techniques for the detection of MRFA, producing chromatographic limits of detection nearly one order of magnitude lower than that of DC ESI utilizing N2, and one-half that of DC ESI utilizing SF6. However, DC ESI outperforms AC ESI for the analysis of caffeine, indicating that improvements in spectral quality may benefit certain compounds or classes of compounds, on an individual basis.

An oject oriented environment for multi-channel signal analysis and understanding

Energy Technology Data Exchange (ETDEWEB)

Maurer, W.J.; Dowla, F.U. [Lawrence Livermore National Lab., CA (United States)

1994-11-15

We describe an interactive signal analysis an understanding tool for multichannel signals. The system, written entirely in the C++ language, takes full advantage of the modern workstation GUI tools and integrates traditional signal-processing methods with intelligent domain-specific tools for the exploration and analysis of semistructured problems. By semistructured problems, we mean problems that require a high degree of interactive analysis, and further, the analysis steps are highly adaptive. In other words, a finite number of rules cannot be used to obtain a good solution to the problem.

Digital signal processing the Tevatron BPM signals

International Nuclear Information System (INIS)

Cancelo, G.; James, E.; Wolbers, S.

2005-01-01

The Beam Position Monitor (TeV BPM) readout system at Fermilab's Tevatron has been updated and is currently being commissioned. The new BPMs use new analog and digital hardware to achieve better beam position measurement resolution. The new system reads signals from both ends of the existing directional stripline pickups to provide simultaneous proton and antiproton measurements. The signals provided by the two ends of the BPM pickups are processed by analog band-pass filters and sampled by 14-bit ADCs at 74.3MHz. A crucial part of this work has been the design of digital filters that process the signal. This paper describes the digital processing and estimation techniques used to optimize the beam position measurement. The BPM electronics must operate in narrow-band and wide-band modes to enable measurements of closed-orbit and turn-by-turn positions. The filtering and timing conditions of the signals are tuned accordingly for the operational modes. The analysis and the optimized result for each mode are presented

Book: Marine Bioacoustic Signal Processing and Analysis

Science.gov (United States)

2011-09-30

physicists , and mathematicians . However, more and more biologists and psychologists are starting to use advanced signal processing techniques and...Book: Marine Bioacoustic Signal Processing and Analysis 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT ...chapters than it should be, since the project must be finished by Dec. 31. I have started setting aside 2 hours of uninterrupted per workday to work

Power system small signal stability analysis and control

CERN Document Server

Mondal, Debasish; Sengupta, Aparajita

2014-01-01

Power System Small Signal Stability Analysis and Control presents a detailed analysis of the problem of severe outages due to the sustained growth of small signal oscillations in modern interconnected power systems. The ever-expanding nature of power systems and the rapid upgrade to smart grid technologies call for the implementation of robust and optimal controls. Power systems that are forced to operate close to their stability limit have resulted in the use of control devices by utility companies to improve the performance of the transmission system against commonly occurring power system

The Cause of an Eddy Current Signal Noise from a Steam Generator Tube and its Effect on the Detectability of a Crack

International Nuclear Information System (INIS)

Lee, Deok Hyun; Choi, Myung Sik; Hur, Do Haeng; Kim, Kyung Mo; Han, Jung Ho

2008-01-01

An eddy current inspection has been applied for a pre-service and in-service examination of a steam generator in nuclear power plants. The experience from the inspection of steam generators showed that many plants had an excessive number of tubes with eddy current noise signals over several hundreds, which originated from manufacturing anomalies. The plants in U.S suffered significant downstream inspection costs, history reviews, and diagnostic testing because some signals resembled flaws and others masked a flaw. These lessens learned resulted in issuing the guidelines for steam generator tubing specifications and repair, in order to reduce the number of anomalous signals in the tubes and also to provide the requirement of a signal to noise ratio by applying a field type examination with bobbin coil eddy current probes at a manufacturing process. Besides the noise signals of a bobbin coil eddy current probe from manufacturing anomalies, the excessive background noise of the rotating coil eddy current probe signal is frequently observed from a tube and it negatively affects the detection and sizing estimate of a defect. Since the inspection intervals are being extended up to 60 months for the more recent steam generator of corrosion resistant alloy 690TT tubing, the detection of an earlier crack and an accurate sizing are becoming more important in the activity of a non-destructive examination. In this study, the cause of an eddy current signal noise of a rotating coil probe from a steam generator tube was examined and its influence on the detectability of a crack was analyzed

Multistep Current Signal in Protein Translocation through Graphene Nanopores

KAUST Repository

Bonome, Emma Letizia

2015-05-07

© 2015 American Chemical Society. In nanopore sensing experiments, the properties of molecules are probed by the variation of ionic currents flowing through the nanopore. In this context, the electronic properties and the single-layer thickness of graphene constitute a major advantage for molecule characterization. Here we analyze the translocation pathway of the thioredoxin protein across a graphene nanopore, and the related ionic currents, by integrating two nonequilibrium molecular dynamics methods with a bioinformatic structural analysis. To obtain a qualitative picture of the translocation process and to identify salient features we performed unsupervised structural clustering on translocation conformations. This allowed us to identify some specific and robust translocation intermediates, characterized by significantly different ionic current flows. We found that the ion current strictly anticorrelates with the amount of pore occupancy by thioredoxin residues, providing a putative explanation of the multilevel current scenario observed in recently published translocation experiments.

Pulsed Direct Current Electrospray: Enabling Systematic Analysis of Small Volume Sample by Boosting Sample Economy.

Science.gov (United States)

Wei, Zhenwei; Xiong, Xingchuang; Guo, Chengan; Si, Xingyu; Zhao, Yaoyao; He, Muyi; Yang, Chengdui; Xu, Wei; Tang, Fei; Fang, Xiang; Zhang, Sichun; Zhang, Xinrong

2015-11-17

We had developed pulsed direct current electrospray ionization mass spectrometry (pulsed-dc-ESI-MS) for systematically profiling and determining components in small volume sample. Pulsed-dc-ESI utilized constant high voltage to induce the generation of single polarity pulsed electrospray remotely. This method had significantly boosted the sample economy, so as to obtain several minutes MS signal duration from merely picoliter volume sample. The elongated MS signal duration enable us to collect abundant MS(2) information on interested components in a small volume sample for systematical analysis. This method had been successfully applied for single cell metabolomics analysis. We had obtained 2-D profile of metabolites (including exact mass and MS(2) data) from single plant and mammalian cell, concerning 1034 components and 656 components for Allium cepa and HeLa cells, respectively. Further identification had found 162 compounds and 28 different modification groups of 141 saccharides in a single Allium cepa cell, indicating pulsed-dc-ESI a powerful tool for small volume sample systematical analysis.

Develop advanced nonlinear signal analysis topographical mapping system

Science.gov (United States)

1994-01-01

The Space Shuttle Main Engine (SSME) has been undergoing extensive flight certification and developmental testing, which involves some 250 health monitoring measurements. Under the severe temperature, pressure, and dynamic environments sustained during operation, numerous major component failures have occurred, resulting in extensive engine hardware damage and scheduling losses. To enhance SSME safety and reliability, detailed analysis and evaluation of the measurements signal are mandatory to assess its dynamic characteristics and operational condition. Efficient and reliable signal detection techniques will reduce catastrophic system failure risks and expedite the evaluation of both flight and ground test data, and thereby reduce launch turn-around time. The basic objective of this contract are threefold: (1) develop and validate a hierarchy of innovative signal analysis techniques for nonlinear and nonstationary time-frequency analysis. Performance evaluation will be carried out through detailed analysis of extensive SSME static firing and flight data. These techniques will be incorporated into a fully automated system; (2) develop an advanced nonlinear signal analysis topographical mapping system (ATMS) to generate a Compressed SSME TOPO Data Base (CSTDB). This ATMS system will convert tremendous amount of complex vibration signals from the entire SSME test history into a bank of succinct image-like patterns while retaining all respective phase information. High compression ratio can be achieved to allow minimal storage requirement, while providing fast signature retrieval, pattern comparison, and identification capabilities; and (3) integrate the nonlinear correlation techniques into the CSTDB data base with compatible TOPO input data format. Such integrated ATMS system will provide the large test archives necessary for quick signature comparison. This study will provide timely assessment of SSME component operational status, identify probable causes of

Performance Improvement of Power Analysis Attacks on AES with Encryption-Related Signals

Science.gov (United States)

Lee, You-Seok; Lee, Young-Jun; Han, Dong-Guk; Kim, Ho-Won; Kim, Hyoung-Nam

A power analysis attack is a well-known side-channel attack but the efficiency of the attack is frequently degraded by the existence of power components, irrelative to the encryption included in signals used for the attack. To enhance the performance of the power analysis attack, we propose a preprocessing method based on extracting encryption-related parts from the measured power signals. Experimental results show that the attacks with the preprocessed signals detect correct keys with much fewer signals, compared to the conventional power analysis attacks.

Social Signals, their function, and automatic analysis: A survey

NARCIS (Netherlands)

Vinciarelli, Alessandro; Pantic, Maja; Bourlard, Hervé; Pentland, Alex

2008-01-01

Social Signal Processing (SSP) aims at the analysis of social behaviour in both Human-Human and Human-Computer interactions. SSP revolves around automatic sensing and interpretation of social signals, complex aggregates of nonverbal behaviours through which individuals express their attitudes

Development of capacitive beam position, beam current and Schottky-signal monitors for the Cryogenic Storage Ring (CSR)

International Nuclear Information System (INIS)

Laux, Felix

2011-01-01

In this thesis novel techniques based on capacitive pickups for the determination of the beam current, the beam position and the Schottky-signal in storage rings have been developed. Beam current measurements at the heavy ion storage ring TSR with a capacitive pickup have been found in very good agreement with the theory. Using this device the accurate measurement of beam currents at the TSR far below 1 μA is now possible. This method will also be used at the Cryogenic Storage Ring (CSR) at which beam currents in the range of 1 nA-1 μA are expected. For the first time, position measurements with a resonant amplifier system for capacitive pickups have been examined at the TSR for later use of this technique in the CSR. With this method an increased signal-to-noise ratio can be achieved using a parallel inductance. A comparison with measurements using the rest gas beam profile monitor has shown very good agreement even at very low intensities. Experiments with the cryo-capable electronics for the CSR beam position monitors have shown an achievable quality factor of Q=500, resulting in the prospect of precise position measurements at the CSR even at very low beam currents. The CSR Schottky-Pickup will also be equipped with a resonant amplifier system with a comparable quality factor. An estimation of the signal-to-noise ratio suggests a detection limit of a few protons. (orig.)

A Quantitative Analysis of Pulsed Signals Emitted by Wild Bottlenose Dolphins.

Directory of Open Access Journals (Sweden)

Ana Rita Luís

Full Text Available Common bottlenose dolphins (Tursiops truncatus, produce a wide variety of vocal emissions for communication and echolocation, of which the pulsed repertoire has been the most difficult to categorize. Packets of high repetition, broadband pulses are still largely reported under a general designation of burst-pulses, and traditional attempts to classify these emissions rely mainly in their aural characteristics and in graphical aspects of spectrograms. Here, we present a quantitative analysis of pulsed signals emitted by wild bottlenose dolphins, in the Sado estuary, Portugal (2011-2014, and test the reliability of a traditional classification approach. Acoustic parameters (minimum frequency, maximum frequency, peak frequency, duration, repetition rate and inter-click-interval were extracted from 930 pulsed signals, previously categorized using a traditional approach. Discriminant function analysis revealed a high reliability of the traditional classification approach (93.5% of pulsed signals were consistently assigned to their aurally based categories. According to the discriminant function analysis (Wilk's Λ = 0.11, F3, 2.41 = 282.75, P < 0.001, repetition rate is the feature that best enables the discrimination of different pulsed signals (structure coefficient = 0.98. Classification using hierarchical cluster analysis led to a similar categorization pattern: two main signal types with distinct magnitudes of repetition rate were clustered into five groups. The pulsed signals, here described, present significant differences in their time-frequency features, especially repetition rate (P < 0.001, inter-click-interval (P < 0.001 and duration (P < 0.001. We document the occurrence of a distinct signal type-short burst-pulses, and highlight the existence of a diverse repertoire of pulsed vocalizations emitted in graded sequences. The use of quantitative analysis of pulsed signals is essential to improve classifications and to better assess the

The Photoplethismographic Signal Processed with Nonlinear Time Series Analysis Tools

International Nuclear Information System (INIS)

Hernandez Caceres, Jose Luis; Hong, Rolando; Garcia Lanz, Abel; Garcia Dominguez, Luis; Cabannas, Karelia

2001-01-01

Finger photoplethismography (PPG) signals were submitted to nonlinear time series analysis. The applied analytical techniques were: (i) High degree polynomial fitting for baseline estimation; (ii) FFT analysis for estimating power spectra; (iii) fractal dimension estimation via the Higuchi's time-domain method, and (iv) kernel nonparametric estimation for reconstructing noise free-attractors and also for estimating signal's stochastic components

Monte-Carlo Analysis of the Flavour Changing Neutral Current B \\to Gamma at Babar

Energy Technology Data Exchange (ETDEWEB)

Smith, D. [Imperial College, London (United Kingdom)

2001-09-01

The main theme of this thesis is a Monte-Carlo analysis of the rare Flavour Changing Neutral Current (FCNC) decay b→sγ. The analysis develops techniques that could be applied to real data, to discriminate between signal and background events in order to make a measurement of the branching ratio of this rare decay using the BaBar detector. Also included in this thesis is a description of the BaBar detector and the work I have undertaken in the development of the electronic data acquisition system for the Electromagnetic calorimeter (EMC), a subsystem of the BaBar detector.

Frames and operator theory in analysis and signal processing

CERN Document Server

Larson, David R; Nashed, Zuhair; Nguyen, Minh Chuong; Papadakis, Manos

2008-01-01

This volume contains articles based on talks presented at the Special Session Frames and Operator Theory in Analysis and Signal Processing, held in San Antonio, Texas, in January of 2006. Recently, the field of frames has undergone tremendous advancement. Most of the work in this field is focused on the design and construction of more versatile frames and frames tailored towards specific applications, e.g., finite dimensional uniform frames for cellular communication. In addition, frames are now becoming a hot topic in mathematical research as a part of many engineering applications, e.g., matching pursuits and greedy algorithms for image and signal processing. Topics covered in this book include: Application of several branches of analysis (e.g., PDEs; Fourier, wavelet, and harmonic analysis; transform techniques; data representations) to industrial and engineering problems, specifically image and signal processing. Theoretical and applied aspects of frames and wavelets. Pure aspects of operator theory empha...

Novel Signal Noise Reduction Method through Cluster Analysis, Applied to Photoplethysmography.

Science.gov (United States)

Waugh, William; Allen, John; Wightman, James; Sims, Andrew J; Beale, Thomas A W

2018-01-01

Physiological signals can often become contaminated by noise from a variety of origins. In this paper, an algorithm is described for the reduction of sporadic noise from a continuous periodic signal. The design can be used where a sample of a periodic signal is required, for example, when an average pulse is needed for pulse wave analysis and characterization. The algorithm is based on cluster analysis for selecting similar repetitions or pulses from a periodic single. This method selects individual pulses without noise, returns a clean pulse signal, and terminates when a sufficiently clean and representative signal is received. The algorithm is designed to be sufficiently compact to be implemented on a microcontroller embedded within a medical device. It has been validated through the removal of noise from an exemplar photoplethysmography (PPG) signal, showing increasing benefit as the noise contamination of the signal increases. The algorithm design is generalised to be applicable for a wide range of physiological (physical) signals.

Persistence and storage of activity patterns in spiking recurrent cortical networks: modulation of sigmoid signals by after-hyperpolarization currents and acetylcholine.

Science.gov (United States)

Palma, Jesse; Grossberg, Stephen; Versace, Massimiliano

2012-01-01

Many cortical networks contain recurrent architectures that transform input patterns before storing them in short-term memory (STM). Theorems in the 1970's showed how feedback signal functions in rate-based recurrent on-center off-surround networks control this process. A sigmoid signal function induces a quenching threshold below which inputs are suppressed as noise and above which they are contrast-enhanced before pattern storage. This article describes how changes in feedback signaling, neuromodulation, and recurrent connectivity may alter pattern processing in recurrent on-center off-surround networks of spiking neurons. In spiking neurons, fast, medium, and slow after-hyperpolarization (AHP) currents control sigmoid signal threshold and slope. Modulation of AHP currents by acetylcholine (ACh) can change sigmoid shape and, with it, network dynamics. For example, decreasing signal function threshold and increasing slope can lengthen the persistence of a partially contrast-enhanced pattern, increase the number of active cells stored in STM, or, if connectivity is distance-dependent, cause cell activities to cluster. These results clarify how cholinergic modulation by the basal forebrain may alter the vigilance of category learning circuits, and thus their sensitivity to predictive mismatches, thereby controlling whether learned categories code concrete or abstract features, as predicted by Adaptive Resonance Theory. The analysis includes global, distance-dependent, and interneuron-mediated circuits. With an appropriate degree of recurrent excitation and inhibition, spiking networks maintain a partially contrast-enhanced pattern for 800 ms or longer after stimuli offset, then resolve to no stored pattern, or to winner-take-all (WTA) stored patterns with one or multiple winners. Strengthening inhibition prolongs a partially contrast-enhanced pattern by slowing the transition to stability, while strengthening excitation causes more winners when the network

Persistence and storage of activity patterns in spiking recurrent cortical networks:Modulation of sigmoid signals by after-hyperpolarization currents and acetylcholine

Directory of Open Access Journals (Sweden)

Jesse ePalma

2012-06-01

Full Text Available Many cortical networks contain recurrent architectures that transform input patterns before storing them in short-term memory (STM. Theorems in the 1970’s showed how feedback signal functions in rate-based recurrent on-center off-surround networks control this process. A sigmoid signal function induces a quenching threshold below which inputs are suppressed as noise and above which they are contrast-enhanced before pattern storage. This article describes how changes in feedback signaling, neuromodulation, and recurrent connectivity may alter pattern processing in recurrent on-center off-surround networks of spiking neurons. In spiking neurons, fast, medium, and slow after-hyperpolarization (AHP currents control sigmoid signal threshold and slope. Modulation of AHP currents by acetylcholine (ACh can change sigmoid shape and, with it, network dynamics. For example, decreasing signal function threshold and increasing slope can lengthen the persistence of a partially contrast-enhanced pattern, increase the number of active cells stored in STM, or, if connectivity is distance-dependent, cause cell activities to cluster. These results clarify how cholinergic modulation by the basal forebrain may alter the vigilance of category learning circuits, and thus their sensitivity to predictive mismatches, thereby controlling whether learned categories code concrete or abstract features, as predicted by Adaptive Resonance Theory. The analysis includes global, distance-dependent, and interneuron-mediated circuits. With an appropriate degree of recurrent excitation and inhibition, spiking networks maintain a partially contrast-enhanced pattern for 800 milliseconds or longer after stimuli offset, then resolve to no stored pattern, or to winner-take-all stored patterns with one or multiple winners. Strengthening inhibition prolongs a partially contrast-enhanced pattern by slowing the transition to stability, while strengthening excitation causes more winners

Sensor signal analysis by neural networks for surveillance in nuclear reactors

International Nuclear Information System (INIS)

Keyvan, S.; Rabelo, L.C.

1992-01-01

The application of neural networks as a tool for reactor diagnostics is examined here. Reactor pump signals utilized in a wear-out monitoring system developed for early detection of the degradation of a pump shaft are analyzed as a semi-benchmark test to study the feasibility of neural networks for monitoring and surveillance in nuclear reactors. The Adaptive Resonance Theory (ART 2 and ART 2-A) paradigm of neural networks is applied in this study. The signals are collected signals as well as generated signals simulating the wear progress. The wear-out monitoring system applies noise analysis techniques, and is capable of distinguishing these signals apart and providing a measure of the progress of the degradation. This paper presents the results of the analysis of these data, and provides an evaluation on the performance of ART 2-A and ART 2 for reactor signal analysis. The selection of ART 2 is due to its desired design principles such as unsupervised learning, stability-plasticity, search-direct access, and the match-reset tradeoffs

An in-vacuum wall current monitor and low cost signal sampling system

International Nuclear Information System (INIS)

Yin, Y.; Rawnsley, W.R.; Mackenzie, G.H.

1993-11-01

The beam bunches extracted from the TRIUMF cyclotron are usually about 4 ns long, contain ∼ 4 x 10 7 protons, and are spaced at 43 ns. A wall current monitor capable of giving the charge distribution within a bunch, on a bunch by bunch basis, has recently been installed together with a sampling system for routine display in the control room. The wall current monitor is enclosed in a vacuum vessel and no ceramic spacer is required. This enhances the response to high frequencies, ferrite rings extend the low frequency response. Bench measurements show a flat response between a few hundred kilohertz and 4.6 GHz. For a permanent display in the control room the oscilloscope will be replaced by a Stanford Research Systems fast sampler module, a scanner module, and an interface module made at TRIUMF. The time to acquire one 10 ns distribution encompassing the beam bunch is 30 ms with a sample width of 100 ps and an average sample spacing of 13 ps. The scan, sample, and retrace signals are buffered carried on 70 m differential lines to the control room. An analog scope in XYZ mode provides a real time display. Signal averaging can be performed by using a digital oscilloscope in YT mode. (author). 6 refs., 2 tabs., 7 figs

Data analysis algorithms for flaw sizing based on eddy current rotating probe examination of steam generator tubes

International Nuclear Information System (INIS)

Bakhtiari, S.; Elmer, T.W.

2009-01-01

Computer-aided data analysis tools can help improve the efficiency and reliability of flaw sizing based on nondestructive examination data. They can further help produce more consistent results, which is important for both in-service inspection applications and for engineering assessments associated with steam generator tube integrity. Results of recent investigations at Argonne on the development of various algorithms for sizing of flaws in steam generator tubes based on eddy current rotating probe data are presented. The research was carried out as part of the activities under the International Steam Generator Tube Integrity Program (ISG-TIP) sponsored by the U.S. Nuclear Regulatory Commission. A computer-aided data analysis tool has been developed for off-line processing of eddy current inspection data. The main objectives of the work have been to a) allow all data processing stages to be performed under the same user interface, b) simplify modification and testing of signal processing and data analysis scripts, and c) allow independent evaluation of viable flaw sizing algorithms. The focus of most recent studies at Argonne has been on the processing of data acquired with the +Point probe, which is one of the more widely used eddy current rotating probes for steam generator tube examinations in the U.S. The probe employs a directional surface riding differential coil, which helps reduce the influence of tubing artifacts and in turn helps improve the signal-to-noise ratio. Various algorithms developed under the MATLAB environment for the conversion, segmentation, calibration, and analysis of data have been consolidated within a single user interface. Data acquired with a number of standard eddy current test equipment are automatically recognized and converted to a standard format for further processing. Because of its modular structure, the graphical user interface allows user-developed routines to be easily incorporated, modified, and tested independent of the

Safety analysis - current and future regulatory challenges

Energy Technology Data Exchange (ETDEWEB)

Jamieson, T., E-mail: Terry.Jamieson@cnsc-ccsn.gc.ca [Canadian Nuclear Safety Commission, Ottawa, ON (Canada)

2015-07-01

'Full text:' The current and future regulatory challenges associated with deterministic safety analysis are reviewed, including: 1. The CNSC's and safety control areas. 2. Traditional safety analysis approach. 3. Experience gained and impact. 4. Current analysis and regulatory approaches. 5. Current status. 6. Complexity and challenges In particular, the technical, regulatory and strategic aspects of these challenges are discussed. (author)

Safety analysis - current and future regulatory challenges

International Nuclear Information System (INIS)

Jamieson, T.

2015-01-01

'Full text:' The current and future regulatory challenges associated with deterministic safety analysis are reviewed, including: 1. The CNSC's and safety control areas. 2. Traditional safety analysis approach. 3. Experience gained and impact. 4. Current analysis and regulatory approaches. 5. Current status. 6. Complexity and challenges In particular, the technical, regulatory and strategic aspects of these challenges are discussed. (author)

Evaluation of the effect of probe design parameters on ECT signal and development of eddy current probe for irradiated fuel rods

International Nuclear Information System (INIS)

Kwank, S. W.; Han, Y. K.; Woo, S. K.; Kim, T. W.; Park, J. Y.; Kim, B. J.; Park, J. Y.

1999-01-01

Eddy current test(ECT) is used to inspect not only the failed fuel rods but also peripheral rods during repairing of the failed fuel rods, to detect internal defects in irradiated fuel rods which could not be detected by ultrasonic test and visual test, and to obtain the data for determining the root cause of fuel rod failure. This study evaluates the effect of properties of test article, irradiated fuel rods, on the impedance diagram in order to reduce the difficulty of ECT signal analysis. The optimum eddy current probe design conditions for inspecting the irradiated fuel rods, is estimate by using experimental equations and the probe is manufactured based on the estimated conditions. The performance of developed eddy current probe and the optimum conditions is proved through characteristic comparison experiment with the probe purchased from the foreign vendor

Numerical Analysis of Through Transmission Pulsed Eddy Current Testing and Effects of Pulse Width Variation

International Nuclear Information System (INIS)

Shin, Young Kil; Choi, Dong Myung

2007-01-01

By using numerical analysis methods, through transmission type pulsed eddy current (PEC) testing is modeled and PEC signal responses due to varying material conductivity, permeability, thickness, lift-off and pulse width are investigated. Results show that the peak amplitude of PEC signal gets reduced and the time to reach the peak amplitude is increased as the material conductivity, permeability, and specimen thickness increase. Also, they indicate that the pulse width needs to be shorter when evaluating the material conductivity and the plate thickness using the peak amplitude, and when the pulse width is long, the peak time is found to be more useful. Other results related to lift-off variation are reported as well

Pre-earthquake signals – Part I: Deviatoric stresses turn rocks into a source of electric currents

Directory of Open Access Journals (Sweden)

F. T. Freund

2007-09-01

Full Text Available Earthquakes are feared because they often strike so suddenly. Yet, there are innumerable reports of pre-earthquake signals. Widespread disagreement exists in the geoscience community how these signals can be generated in the Earth's crust and whether they are early warning signs, related to the build-up of tectonic stresses before major seismic events. Progress in understanding and eventually using these signals has been slow because the underlying physical process or processes are basically not understood. This has changed with the discovery that, when igneous or high-grade metamorphic rocks are subjected to deviatoric stress, dormant electronic charge carriers are activated: electrons and defect electrons. The activation increases the number density of mobile charge carriers in the rocks and, hence, their electric conductivity. The defect electrons are associated with the oxygen anion sublattice and are known as positive holes or pholes for short. The boundary between stressed and unstressed rock acts a potential barrier that lets pholes pass but blocks electrons. Therefore, like electrons and ions in an electrochemical battery, the stress-activated electrons and pholes in the "rock battery" have to flow out in different directions. When the circuit is closed, the battery currents can flow. The discovery of such stress-activated currents in crustal rocks has far-reaching implications for understanding pre-earthquake signals.

Electrical measurement, signal processing, and displays

CERN Document Server

Webster, John G

2003-01-01

ELECTROMAGNETIC VARIABLES MEASUREMENTVoltage MeasurementCurrent Measurement Power Measurement Power Factor Measurement Phase Measurement Energy Measurement Electrical Conductivity and Resistivity Charge Measurement Capacitance and Capacitance Measurements Permittivity Measurement Electric Field Strength Magnetic Field Measurement Permeability and Hysteresis MeasurementInductance Measurement Immittance MeasurementQ Factor Measurement Distortion Measurement Noise Measurement.Microwave Measurement SIGNAL PROCESSINGAmplifiers and Signal ConditionersModulation Filters Spectrum Analysis and Correlat

Data analysis of gravitational-wave signals from spinning neutron stars. IV. An all-sky search

International Nuclear Information System (INIS)

Astone, Pia; Borkowski, Kazimierz M.; Jaranowski, Piotr; Krolak, Andrzej

2002-01-01

We develop a set of data analysis tools for a realistic all-sky search for continuous gravitational-wave signals and we test our tools against simulated data. The aim of the paper is to prepare for an analysis of the real data from the EXPLORER bar detector; however, the methods that we present apply both to data from the resonant bar detectors that are currently in operation and the laser interferometric detectors that are in the final stages of construction and commissioning. With our techniques we shall be able to perform an all-sky coherent search of 2 days of data from the EXPLORER detector for a frequency bandwidth of 0.76 Hz in one month with 250 Mflops computing power. This search will detect all the continuous gravitational-wave signals with the dimensionless amplitude larger than 2.8x10 -23 with 99% confidence, assuming that the noise in the detector is Gaussian

Time-Frequency Analysis of Signals Generated by Rotating Machines

Directory of Open Access Journals (Sweden)

R. Zetik

1999-06-01

Full Text Available This contribution is devoted to the higher order time-frequency analyses of signals. Firstly, time-frequency representations of higher order (TFRHO are defined. Then L-Wigner distribution (LWD is given as a special case of TFRHO. Basic properties of LWD are illustrated based on the analysis of mono-component and multi-component synthetic signals and acoustical signals generated by rotating machine. The obtained results confirm usefulness of LWD application for the purpose of rotating machine condition monitoring.

Signal correlations in biomass combustion. An information theoretic analysis

Energy Technology Data Exchange (ETDEWEB)

Ruusunen, M.

2013-09-01

Increasing environmental and economic awareness are driving the development of combustion technologies to efficient biomass use and clean burning. To accomplish these goals, quantitative information about combustion variables is needed. However, for small-scale combustion units the existing monitoring methods are often expensive or complex. This study aimed to quantify correlations between flue gas temperatures and combustion variables, namely typical emission components, heat output, and efficiency. For this, data acquired from four small-scale combustion units and a large circulating fluidised bed boiler was studied. The fuel range varied from wood logs, wood chips, and wood pellets to biomass residue. Original signals and a defined set of their mathematical transformations were applied to data analysis. In order to evaluate the strength of the correlations, a multivariate distance measure based on information theory was derived. The analysis further assessed time-varying signal correlations and relative time delays. Ranking of the analysis results was based on the distance measure. The uniformity of the correlations in the different data sets was studied by comparing the 10-quantiles of the measured signal. The method was validated with two benchmark data sets. The flue gas temperatures and the combustion variables measured carried similar information. The strongest correlations were mainly linear with the transformed signal combinations and explicable by the combustion theory. Remarkably, the results showed uniformity of the correlations across the data sets with several signal transformations. This was also indicated by simulations using a linear model with constant structure to monitor carbon dioxide in flue gas. Acceptable performance was observed according to three validation criteria used to quantify modelling error in each data set. In general, the findings demonstrate that the presented signal transformations enable real-time approximation of the studied

The speech signal segmentation algorithm using pitch synchronous analysis

Directory of Open Access Journals (Sweden)

Amirgaliyev Yedilkhan

2017-03-01

Full Text Available Parameterization of the speech signal using the algorithms of analysis synchronized with the pitch frequency is discussed. Speech parameterization is performed by the average number of zero transitions function and the signal energy function. Parameterization results are used to segment the speech signal and to isolate the segments with stable spectral characteristics. Segmentation results can be used to generate a digital voice pattern of a person or be applied in the automatic speech recognition. Stages needed for continuous speech segmentation are described.

A method of signal transmission path analysis for multivariate random processes

International Nuclear Information System (INIS)

Oguma, Ritsuo

1984-04-01

A method for noise analysis called ''STP (signal transmission path) analysis'' is presentd as a tool to identify noise sources and their propagation paths in multivariate random proceses. Basic idea of the analysis is to identify, via time series analysis, effective network for the signal power transmission among variables in the system and to make use of its information to the noise analysis. In the present paper, we accomplish this through two steps of signal processings; first, we estimate, using noise power contribution analysis, variables which have large contribution to the power spectrum of interest, and then evaluate the STPs for each pair of variables to identify STPs which play significant role for the generated noise to transmit to the variable under evaluation. The latter part of the analysis is executed through comparison of partial coherence function and newly introduced partial noise power contribution function. This paper presents the procedure of the STP analysis and demonstrates, using simulation data as well as Borssele PWR noise data, its effectiveness for investigation of noise generation and propagation mechanisms. (author)

DC feedback for wide band frequency fixed current source

Directory of Open Access Journals (Sweden)

Aoday Hashim Mohamad Al-Rawi

2013-03-01

Full Text Available Alternating current sources are mainly used in bioelectrical impedance devices. Nowadays 50 – 100 kHz bioelectrical impedance devices are commonly used for body composition analysis. High frequency bioelectrical impedance analysis devices are mostly used in bioimpedance tomography and blood analysis. High speed op-amps and voltage comparators are used in this circuit. Direct current feedback is used to prevent delay. An N-Channel J-FET transistor was used to establish the voltage controlled gain amplifier (VCG. A sine wave signal has been applied as input voltage. The value of this signal should be constant in 170 mV rms to keep the output current in about 1 mA rms. Four frequencies; 100 kHz, 1 MHz, 2 MHz and 3.2 MHz were applied to the circuit and the current was measured for different load resistances. The results showed that the current was stable for changes in the resistor load, bouncing around an average point as a result of bouncing DC feedback.

siGnum: graphical user interface for EMG signal analysis.

Science.gov (United States)

Kaur, Manvinder; Mathur, Shilpi; Bhatia, Dinesh; Verma, Suresh

2015-01-01

Electromyography (EMG) signals that represent the electrical activity of muscles can be used for various clinical and biomedical applications. These are complicated and highly varying signals that are dependent on anatomical location and physiological properties of the muscles. EMG signals acquired from the muscles require advanced methods for detection, decomposition and processing. This paper proposes a novel Graphical User Interface (GUI) siGnum developed in MATLAB that will apply efficient and effective techniques on processing of the raw EMG signals and decompose it in a simpler manner. It could be used independent of MATLAB software by employing a deploy tool. This would enable researcher's to gain good understanding of EMG signal and its analysis procedures that can be utilized for more powerful, flexible and efficient applications in near future.

Response Analysis on Electrical Pulses under Severe Nuclear Accident Temperature Conditions Using an Abnormal Signal Simulation Analysis Module

Directory of Open Access Journals (Sweden)

Kil-Mo Koo

2012-01-01

Full Text Available Unlike design basis accidents, some inherent uncertainties of the reliability of instrumentations are expected while subjected to harsh environments (e.g., high temperature and pressure, high humidity, and high radioactivity occurring in severe nuclear accident conditions. Even under such conditions, an electrical signal should be within its expected range so that some mitigating actions can be taken based on the signal in the control room. For example, an industrial process control standard requires that the normal signal level for pressure, flow, and resistance temperature detector sensors be in the range of 4~20 mA for most instruments. Whereas, in the case that an abnormal signal is expected from an instrument, such a signal should be refined through a signal validation process so that the refined signal could be available in the control room. For some abnormal signals expected under severe accident conditions, to date, diagnostics and response analysis have been evaluated with an equivalent circuit model of real instruments, which is regarded as the best method. The main objective of this paper is to introduce a program designed to implement a diagnostic and response analysis for equivalent circuit modeling. The program links signal analysis tool code to abnormal signal simulation engine code not only as a one body order system, but also as a part of functions of a PC-based ASSA (abnormal signal simulation analysis module developed to obtain a varying range of the R-C circuit elements in high temperature conditions. As a result, a special function for abnormal pulse signal patterns can be obtained through the program, which in turn makes it possible to analyze the abnormal output pulse signals through a response characteristic of a 4~20 mA circuit model and a range of the elements changing with temperature under an accident condition.

Integrated Circuits for Analog Signal Processing

CERN Document Server

2013-01-01

  This book presents theory, design methods and novel applications for integrated circuits for analog signal processing.  The discussion covers a wide variety of active devices, active elements and amplifiers, working in voltage mode, current mode and mixed mode.  This includes voltage operational amplifiers, current operational amplifiers, operational transconductance amplifiers, operational transresistance amplifiers, current conveyors, current differencing transconductance amplifiers, etc.  Design methods and challenges posed by nanometer technology are discussed and applications described, including signal amplification, filtering, data acquisition systems such as neural recording, sensor conditioning such as biomedical implants, actuator conditioning, noise generators, oscillators, mixers, etc.   Presents analysis and synthesis methods to generate all circuit topologies from which the designer can select the best one for the desired application; Includes design guidelines for active devices/elements...

Does a trade-off between current reproductive success and survival affect the honesty of male signalling in species with male parental care?

Science.gov (United States)

Kelly, N B; Alonzo, S H

2010-11-01

Recent theory predicted that male advertisement will reliably signal investment in paternal care in species where offspring survival requires paternal care and males allocate resources between advertisement and care. However, the predicted relationship between care and advertisement depended on the marginal gains from investment in current reproductive traits. Life history theory suggests that these fitness gains are also subject to a trade-off between current and future reproduction. Here, we investigate whether male signalling remains a reliable indicator of parental care when males allocate resources between current advertisement, paternal care and survival to future reproduction. We find that advertisement is predicted to remain a reliable signal of male care but that advertisement may cease to reliably indicate male quality because low-quality males are predicted to invest in current reproduction, whereas higher-quality males are able to invest in both current reproduction and survival to future reproduction. © 2010 The Authors. Journal Compilation © 2010 European Society For Evolutionary Biology.

Numerical simulations of eddy current testing signals of steam generator tubes by 3-D finite element method

International Nuclear Information System (INIS)

Sakai, Takayuki; Soneda, Naoki

1996-01-01

In every inspection of Japanese PWR plants, all of steam generator tubes are inspected using Eddy Current Testing (ECT) method. However, the relationships between the ECT signals and the defect shapes are known only for the representative shapes of defects. In order to improve the reliability of inspections and the capability of ECT probes, development of numerical simulation technique of the ECT signals for arbitrarily shaped defects is essential. In this study, three-dimensional finite element code is developed to simulate the ECT signals for any kinds of defects in the SG tubes. The code is fully vectorized so that it runs on the supercomputers very efficiently. The simulation results agree very well with the experimental results. Sensitivity analyses are performed to investigate the relationships between the defect shapes and the ECT signals. (author)

SURFACE ELECTROMYOGRAPHY IN BIOMECHANICS: APPLICATIONS AND SIGNAL ANALYSIS ASPECTS

Directory of Open Access Journals (Sweden)

DEAK GRAłIELA-FLAVIA

2009-12-01

Full Text Available Surface electromyography (SEMG is a technique for detecting and recording the electrical activity of the muscles using surface electrodes. The EMG signal is used in biomechanics mainly as an indicator of the initiation of muscle activation, as an indicator of the force produced by a contracting muscle, and as an index ofthe fatigue occurring within a muscle. EMG, used as a method of investigation, can tell us if the muscle is active or not, if the muscle is more or less active, when it is on or off, how much active is it, and finally, if it fatigues.The purpose of this article is to discuss some specific EMG signal analysis aspects with emphasis on comparison type analysis and frequency fatigue analysis.

Small-Signal Analysis of the Microgrid Secondary Control Considering a Communication Time Delay

DEFF Research Database (Denmark)

Coelho, Ernane Antônio Alves; Wu, Dan; Guerrero, Josep M.

2016-01-01

This paper presents a small-signal analysis of an islanded microgrid composed of two or more voltage-source inverters connected in parallel. The primary control of each inverter is integrated through an internal current and voltage loops using proportional resonant compensators, a virtual impedance......, and an external power controller based on frequency and voltage droops. The frequency restoration function is implemented at the secondary control level, which executes a consensus algorithm that consists of a load-frequency control and a single time delay communication network. The consensus network consists...... the behavior of the system considering control parameters and time delay variation....

The Signal and Noise Analysis of Direct Conversion EHM Transceivers

Directory of Open Access Journals (Sweden)

Shayegh

2006-01-01

Full Text Available A direct conversion modulator-demodulator with even harmonic mixers with emphasis on noise analysis is presented. The circuits consist of even harmonic mixers (EHMs realized with antiparallel diode pairs (APDPs. We evaluate the different levels of I/Q imbalances and DC offsets and use signal space concepts to analyze the bit error rate (BER of the proposed transceiver using M-ary QAM schemes. Moreover, the simultaneous analysis of the signal and noise has been presented.

Resonance detection of EEG signals using two-layer wavelet analysis

International Nuclear Information System (INIS)

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

2000-01-01

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

Verification of the Viability of Equipotential Switching Direct Current Potential Drop Method for Piping Wall Loss Monitoring with Signal Sensitivity Analysis

International Nuclear Information System (INIS)

Ryu, Kyung Ha; Hwang, Il Soon; Kim, Ji Hyun

2008-01-01

Flow accelerated corrosion (FAC) phenomenon of low alloy carbon steels in nuclear power plant has been known as one of major degradation mechanisms. It has a potential to cause nuclear pipe rupture accident which may directly impact on the plant reliability and safety. Recently, the equipotential switching direct current potential drop (ES-DCPD) method has been developed, by the present authors, as a method to monitor wall loss in a piping. This method can rapidly monitor the thinning of piping, utilizing either the wide range monitoring (WiRM) or the narrow range monitoring (NaRM) technique. WiRM is a method to monitor wide range of straight piping, whereas NaRM focuses significantly on a narrow range such as an elbow. WiRM and NaRM can improve the reliability of the current FAC screening method that is based on computer modeling on fluid flow conditions. In this paper, the measurements by ES-DCPD are performed with signal sensitivity analyses in the laboratory environment for extended period and showed the viability of ES-DCPD for real plant applications.

Numeric signal analysis process, with particular application to eddy current testing

International Nuclear Information System (INIS)

Combes, J.Y.; Ledinghen, E. de; Lionti, F.

1996-01-01

Eddy current testing uses analogic demodulation process, and then analog or digital phase shift measurement. These techniques are efficient, but not always versatile enough to apply to different configurations, in particular when a change of operating frequency is requested. This method performs an entirely digital conditioning. Excitation is simultaneously performed at N different frequencies (typically N=4). By sampling at a much higher frequency, 2N equation are obtained, allowing the resolution of the linear equations system. (D.L.)

Eddy currents signal processing for steam generator inspection in PWR nuclear power plants

International Nuclear Information System (INIS)

Georgel, B.

1992-01-01

Steam generator tubes in nuclear power plants are periodically checked by means of eddy current probes. The output of a probe is composed of three types of signals: known events (rolling zone, support plates, U-bend part), noise (mainly metallurgical noise) and possible flaws. The latter are random transients, both in arrival time and in shape: they have to be detected and then estimated, before to be fed to the high level stages of a diagnostic system. The objective of the study presented is to develop a semi-automatic system, which could manage and process more than 1 M-bytes of data per tube and provide an operator with reliable diagnostics proposals within a few minutes. This can be achieved only by cooperation of several digital signal processing techniques: detection, segmentation, estimation, noise subtraction, adaptive filtering, modelization, pattern recognition. The paper describes some of these items

The quantitative evaluation of complex defect signals from eddy current testings with multi-frequency methods

International Nuclear Information System (INIS)

Naegele, W.

1982-01-01

The usual formulation of multi-frequency eddy current signals of large defects by linearized impedance diagrams may lead to misinterpretations. Here a developement of the linear superposition principle is proposed, which takes into account also the curvature of the impedance diagrams thus allowing to identify even large defects in an unambiguous way. (orig.) [de

Introduction to applied statistical signal analysis guide to biomedical and electrical engineering applications

CERN Document Server

Shiavi, Richard

2007-01-01

Introduction to Applied Statistical Signal Analysis is designed for the experienced individual with a basic background in mathematics, science, and computer. With this predisposed knowledge, the reader will coast through the practical introduction and move on to signal analysis techniques, commonly used in a broad range of engineering areas such as biomedical engineering, communications, geophysics, and speech.Introduction to Applied Statistical Signal Analysis intertwines theory and implementation with practical examples and exercises. Topics presented in detail include: mathematical

The Real-time Frequency Spectrum Analysis of Neutron Pulse Signal Series

International Nuclear Information System (INIS)

Tang Yuelin; Ren Yong; Wei Biao; Feng Peng; Mi Deling; Pan Yingjun; Li Jiansheng; Ye Cenming

2009-01-01

The frequency spectrum analysis of neutron pulse signal is a very important method in nuclear stochastic signal processing Focused on the special '0' and '1' of neutron pulse signal series, this paper proposes new rotation-table and realizes a real-time frequency spectrum algorithm under 1G Hz sample rate based on PC with add, address and SSE. The numerical experimental results show that under the count rate of 3X10 6 s -1 , this algorithm is superior to FFTW in time-consumption and can meet the real-time requirement of frequency spectrum analysis. (authors)

Classification of DNA nucleotides with transverse tunneling currents

DEFF Research Database (Denmark)

Pedersen, Jonas Nyvold; Boynton, Paul; Ventra, Massimiliano Di

2017-01-01

, however. In realistic liquid environments, typical currents in tunneling devices are of the order of picoamps. This corresponds to only six electrons per microsecond, and this number affects the integration time required to do current measurements in real experiments. This limits the speed of sequencing......, though current fluctuations due to Brownian motion of the molecule average out during the required integration time. Moreover, data acquisition equipment introduces noise, and electronic filters create correlations in time-series data. We discuss how these effects must be included in the analysis of, e.......g., the assignment of specific nucleobases to current signals. As the signals from different molecules overlap, unambiguous classification is impossible with a single measurement. We argue that the assignment of molecules to a signal is a standard pattern classification problem and calculation of the error rates...

Hybrid soft computing systems for electromyographic signals analysis: a review.

Science.gov (United States)

Xie, Hong-Bo; Guo, Tianruo; Bai, Siwei; Dokos, Socrates

2014-02-03

Electromyographic (EMG) is a bio-signal collected on human skeletal muscle. Analysis of EMG signals has been widely used to detect human movement intent, control various human-machine interfaces, diagnose neuromuscular diseases, and model neuromusculoskeletal system. With the advances of artificial intelligence and soft computing, many sophisticated techniques have been proposed for such purpose. Hybrid soft computing system (HSCS), the integration of these different techniques, aims to further improve the effectiveness, efficiency, and accuracy of EMG analysis. This paper reviews and compares key combinations of neural network, support vector machine, fuzzy logic, evolutionary computing, and swarm intelligence for EMG analysis. Our suggestions on the possible future development of HSCS in EMG analysis are also given in terms of basic soft computing techniques, further combination of these techniques, and their other applications in EMG analysis.

Correlation analysis of respiratory signals by using parallel coordinate plots.

Science.gov (United States)

Saatci, Esra

2018-01-01

The understanding of the bonds and the relationships between the respiratory signals, i.e. the airflow, the mouth pressure, the relative temperature and the relative humidity during breathing may provide the improvement on the measurement methods of respiratory mechanics and sensor designs or the exploration of the several possible applications in the analysis of respiratory disorders. Therefore, the main objective of this study was to propose a new combination of methods in order to determine the relationship between respiratory signals as a multidimensional data. In order to reveal the coupling between the processes two very different methods were used: the well-known statistical correlation analysis (i.e. Pearson's correlation and cross-correlation coefficient) and parallel coordinate plots (PCPs). Curve bundling with the number intersections for the correlation analysis, Least Mean Square Time Delay Estimator (LMS-TDE) for the point delay detection and visual metrics for the recognition of the visual structures were proposed and utilized in PCP. The number of intersections was increased when the correlation coefficient changed from high positive to high negative correlation between the respiratory signals, especially if whole breath was processed. LMS-TDE coefficients plotted in PCP indicated well-matched point delay results to the findings in the correlation analysis. Visual inspection of PCB by visual metrics showed range, dispersions, entropy comparisons and linear and sinusoidal-like relationships between the respiratory signals. It is demonstrated that the basic correlation analysis together with the parallel coordinate plots perceptually motivates the visual metrics in the display and thus can be considered as an aid to the user analysis by providing meaningful views of the data. Copyright © 2017 Elsevier B.V. All rights reserved.

Analysis and modelization of short-duration windows of seismic signals

International Nuclear Information System (INIS)

Berriani, B.; Lacoume, J.L.; Martin, N.; Cliet, C.; Dubesset, M.

1987-01-01

The spectral analysis of a seismic arrival is of a great interest, but unfortunately the common Fourier analysis is unserviceable on short-time windows. So, in order to obtain the spectral characteristics of the dominant components of a seismic signal on a short-time interval, the authors study parametric methods. At first, the autoregressive methods are able to localize a small number of non-stationary pure frequencies. But the amplitude determination is impossible with these methods. So, they develop a combination of AR and Capon's methods. In the Capon's method, the amplitude is conserved for a given frequency, at the very time when the contribution of the other frequencies is minimized. Finally, to characterize completely the different pure-frequency dominant components of the signal and to be able to reconstruct the signal and to be able to reconstruct the signal with these elements, the authors need also the phase and the attenuation; for that, they use the Prony's method where the signal is represented by a sum of damped sinusoids. This last method is used to modelize an offset VSP. It is shown that, using four frequencies and their attributes (amplitude, phase, attenuation), it is possible to modelize quasi-exactly the section. When reconstructing the signal, if one (or more) frequency is eliminated, an efficient filtering can be applied. The AR methods, and Prony's in particular, are efficient tools for signal component decomposition and information compression

Study on non-linear bistable dynamics model based EEG signal discrimination analysis method.

Science.gov (United States)

Ying, Xiaoguo; Lin, Han; Hui, Guohua

2015-01-01

Electroencephalogram (EEG) is the recording of electrical activity along the scalp. EEG measures voltage fluctuations generating from ionic current flows within the neurons of the brain. EEG signal is looked as one of the most important factors that will be focused in the next 20 years. In this paper, EEG signal discrimination based on non-linear bistable dynamical model was proposed. EEG signals were processed by non-linear bistable dynamical model, and features of EEG signals were characterized by coherence index. Experimental results showed that the proposed method could properly extract the features of different EEG signals.

Turning Noise into Signal: Utilizing Impressed Pipeline Currents for EM Exploration

Science.gov (United States)

Lindau, Tobias; Becken, Michael

2017-04-01

Impressed Current Cathodic Protection (ICCP) systems are extensively used for the protection of central Europe's dense network of oil-, gas- and water pipelines against destruction by electrochemical corrosion. While ICCP systems usually provide protection by injecting a DC current into the pipeline, mandatory pipeline integrity surveys demand a periodical switching of the current. Consequently, the resulting time varying pipe currents induce secondary electric- and magnetic fields in the surrounding earth. While these fields are usually considered to be unwanted cultural noise in electromagnetic exploration, this work aims at utilizing the fields generated by the ICCP system for determining the electrical resistivity of the subsurface. The fundamental period of the switching cycles typically amounts to 15 seconds in Germany and thereby roughly corresponds to periods used in controlled source EM applications (CSEM). For detailed studies we chose an approximately 30km long pipeline segment near Herford, Germany as a test site. The segment is located close to the southern margin of the Lower Saxony Basin (LSB) and part of a larger gas pipeline composed of multiple segments. The current injected into the pipeline segment originates in a rectified 50Hz AC signal which is periodically switched on and off. In contrast to the usual dipole sources used in CSEM surveys, the current distribution along the pipeline is unknown and expected to be non-uniform due to coating defects that cause current to leak into the surrounding soil. However, an accurate current distribution is needed to model the fields generated by the pipeline source. We measured the magnetic fields at several locations above the pipeline and used Biot-Savarts-Law to estimate the currents decay function. The resulting frequency dependent current distribution shows a current decay away from the injection point as well as a frequency dependent phase shift which is increasing with distance from the injection

A new similarity index for nonlinear signal analysis based on local extrema patterns

Science.gov (United States)

Niknazar, Hamid; Motie Nasrabadi, Ali; Shamsollahi, Mohammad Bagher

2018-02-01

Common similarity measures of time domain signals such as cross-correlation and Symbolic Aggregate approximation (SAX) are not appropriate for nonlinear signal analysis. This is because of the high sensitivity of nonlinear systems to initial points. Therefore, a similarity measure for nonlinear signal analysis must be invariant to initial points and quantify the similarity by considering the main dynamics of signals. The statistical behavior of local extrema (SBLE) method was previously proposed to address this problem. The SBLE similarity index uses quantized amplitudes of local extrema to quantify the dynamical similarity of signals by considering patterns of sequential local extrema. By adding time information of local extrema as well as fuzzifying quantized values, this work proposes a new similarity index for nonlinear and long-term signal analysis, which extends the SBLE method. These new features provide more information about signals and reduce noise sensitivity by fuzzifying them. A number of practical tests were performed to demonstrate the ability of the method in nonlinear signal clustering and classification on synthetic data. In addition, epileptic seizure detection based on electroencephalography (EEG) signal processing was done by the proposed similarity to feature the potentials of the method as a real-world application tool.

Time-Frequency Analysis and Hermite Projection Method Applied to Swallowing Accelerometry Signals

Directory of Open Access Journals (Sweden)

Ervin Sejdić

2010-01-01

Full Text Available Fast Hermite projections have been often used in image-processing procedures such as image database retrieval, projection filtering, and texture analysis. In this paper, we propose an innovative approach for the analysis of one-dimensional biomedical signals that combines the Hermite projection method with time-frequency analysis. In particular, we propose a two-step approach to characterize vibrations of various origins in swallowing accelerometry signals. First, by using time-frequency analysis we obtain the energy distribution of signal frequency content in time. Second, by using fast Hermite projections we characterize whether the analyzed time-frequency regions are associated with swallowing or other phenomena (vocalization, noise, bursts, etc.. The numerical analysis of the proposed scheme clearly shows that by using a few Hermite functions, vibrations of various origins are distinguishable. These results will be the basis for further analysis of swallowing accelerometry to detect swallowing difficulties.

Analysis of tidal currents in the North Sea from shipboard acoustic Doppler current profiler data

Science.gov (United States)

Vindenes, Håvard; Orvik, Kjell Arild; Søiland, Henrik; Wehde, Henning

2018-06-01

North Sea tidal currents are determined by applying harmonic analysis to ship-borne acoustic Doppler current profiler data recorded from 1999 to 2016, covering large areas of the northern North Sea. Direct current measurement data sets of this magnitude are rare in the otherwise well investigated North Sea, and thus it is a valuable asset in studying and expanding our understanding of its tidal currents and circulation in general. The harmonic analysis is applied to a least squares fit of the current observations at a set of knot points. Results from the harmonic analysis compare favorably to tidal parameters estimated from observations from moored instruments. The analysis shows that the tides are characterized by strong semi-diurnal component, with amplitudes of the principal Lunar constituent ranging from 1.6 cm/s in the Skagerrak to 67 cm/s in the Fair Isle Channel. Diurnal tides are found to be approximately one fifth the strength of the predominant semi-diurnal constituent. Output from a regional barotropic tide model compares well to tidal current determined from the harmonic analysis of the Acoustic Doppler Current Profiler data.

Quantitative Evaluation of Remote Field Eddy Current Defect Signals

International Nuclear Information System (INIS)

Jeong, Jin Oh; Yi, Jae Kyung; Kim, Hyoung Jean

2000-01-01

The remote field eddy current (RFEC) inspection was performed on the ductile cast iron pipes with nominal outer diameter of 100mm, which were machined with various shapes and sizes of defects. Ductile cast iron pipes which are used as water supply pipe have the non-uniform thickness and asymmetric cross section due to relatively high degree of allowable errors during the manufacturing processes. These characteristics of ductile cast in pipes cause the long range background noises in RFEC signals along the pipe. In this study, tile machined defects in pipes were effectively classified by the moving window average (MWA) method which eliminated the long-range noise. The voltage plane polar plots (VPPP) method was used to quantitatively evaluate the depth and circumferential degree of defects. The VPPP signatures showed that the angle between defect signature and the normalized in-phase component on the VPPP is linear to the depth of defects. The nondestructive RFEC technique proved to be capable of quantitatively evaluating the machined defects of underground water supply pipe

Tyrosine Phosphorylation in Toll-Like Receptor Signaling

Science.gov (United States)

Chattopadhyay, Saurabh; Sen, Ganes C.

2014-01-01

There is a wealth of knowledge about how different Ser/Thr protein kinases participate in Toll-like receptor (TLR) signaling. In many cases, we know the identities of the Ser/Thr residues of various components of the TLR-signaling pathways that are phosphorylated, the functional consequences of the phosphorylation and the responsible protein kinases. In contrast, the analysis of Tyr-phosphorylation of TLRs and their signaling proteins is currently incomplete, because several existing analyses are not systematic or they do not rely on robust experimental data. Nevertheless, it is clear that many TLRs require, for signaling, ligand-dependent phosphorylation of specific Tyr residues in their cytoplasmic domains; the list includes TLR2, TLR3, TLR4, TLR5, TLR8 and TLR9. In this article, we discuss the current status of knowledge on the effect of Tyr-phosphorylation of TLRs and their signaling proteins on their biochemical and biological functions, the possible identities of the relevant protein tyrosine kinases (PTKs) and the nature of regulations of PTK-mediated activation of TLR signaling pathways. PMID:25022196

Hybrid soft computing systems for electromyographic signals analysis: a review

Science.gov (United States)

2014-01-01

Electromyographic (EMG) is a bio-signal collected on human skeletal muscle. Analysis of EMG signals has been widely used to detect human movement intent, control various human-machine interfaces, diagnose neuromuscular diseases, and model neuromusculoskeletal system. With the advances of artificial intelligence and soft computing, many sophisticated techniques have been proposed for such purpose. Hybrid soft computing system (HSCS), the integration of these different techniques, aims to further improve the effectiveness, efficiency, and accuracy of EMG analysis. This paper reviews and compares key combinations of neural network, support vector machine, fuzzy logic, evolutionary computing, and swarm intelligence for EMG analysis. Our suggestions on the possible future development of HSCS in EMG analysis are also given in terms of basic soft computing techniques, further combination of these techniques, and their other applications in EMG analysis. PMID:24490979

The properties of ULF/VLF signals generated by the SURA facility without ionospheric currents modulation

Science.gov (United States)

Kotik, D. S.; Raybov, A. V.; Ermakova, E. N.

2012-12-01

traditional mechanism of ionospheric current modulation. Also this signals displayed unusual behavior during the magnetic storm deceasing in the amplitude. The work was supported by RFBR grants 11-02-00419, 11-02-97104 and RF Ministry of education and science by state contract 16.518.11.7066.;

Analysis of room transfer function and reverberant signal statistics

DEFF Research Database (Denmark)

Georganti, Eleftheria; Mourjopoulos, John; Jacobsen, Finn

2008-01-01

For some time now, statistical analysis has been a valuable tool in analyzing room transfer functions (RTFs). This work examines existing statistical time-frequency models and techniques for RTF analysis (e.g., Schroeder's stochastic model and the standard deviation over frequency bands for the RTF...... magnitude and phase). RTF fractional octave smoothing, as with 1-slash 3 octave analysis, may lead to RTF simplifications that can be useful for several audio applications, like room compensation, room modeling, auralisation purposes. The aim of this work is to identify the relationship of optimal response...... and the corresponding ratio of the direct and reverberant signal. In addition, this work examines the statistical quantities for speech and audio signals prior to their reproduction within rooms and when recorded in rooms. Histograms and other statistical distributions are used to compare RTF minima of typical...

Signal discrimination of ULF electromagnetic data with using singular spectrum analysis – an attempt to detect train noise

Directory of Open Access Journals (Sweden)

S. Saito

2011-07-01

Full Text Available Electromagnetic phenomena associated with crustal activities have been reported in a wide frequency range (DC-HF. In particular, ULF electromagnetic phenomena are the most promising among them because of the deeper skin depth. However, ULF geoelctromagnetic data are a superposition of signals of different origins. They originated from interactions between the geomagnetic field and the solar wind, leak current by a DC-driven train (train noise, precipitation, and so on. In general, the intensity of electromagnetic signals associated with crustal activity is smaller than the above variations. Therefore, in order to detect a smaller signal, signal discrimination such as noise reduction or identification of noises is very important. In this paper, the singular spectrum analysis (SSA has been performed to detect the DC-driven train noise in geoelectric potential difference data. The aim of this paper is to develop an effective algorithm for the DC-driven train noise detection.

Mental-disorder detection using chaos and nonlinear dynamical analysis of photoplethysmographic signals

International Nuclear Information System (INIS)

Pham, Tuan D.; Thang, Truong Cong; Oyama-Higa, Mayumi; Sugiyama, Masahide

2013-01-01

Highlights: • Chaos and nonlinear dynamical analysis are applied for mental-disorder detection. • Experimental results show significant detection improvement with feature synergy. • Proposed approach is effective for analysis of photoplethysmographic signals. • Proposed approach is promising for developing automated mental-health systems. -- Abstract: Mental disorder can be defined as a psychological disturbance of thought or emotion. In particular, depression is a mental disease which can ultimately lead to death from suicide. If depression is identified, it can be treated with medication and psychotherapy. However, the diagnosis of depression is difficult and there are currently no any quick and reliable medical tests to detect if someone is depressed. This is because the exact cause of depression is still unknown given the belief that depression results in chemical brain changes, genetic disorder, stress, or the combination of these problems. Photoplethysmography has recently been realized as a non-invasive optical technique that can give new insights into the physiology and pathophysiology of the central and peripheral nervous systems. We present in this paper an automated mental-disorder detection approach in a general sense based on a novel synergy of chaos and nonlinear dynamical methods for the analysis of photoplethysmographic finger pulse waves of mental and control subjects. Such an approach can be applied for automated detection of depression as a special case. Because of the computational effectiveness of the studied methods and low cost of generation of the physiological signals, the proposed automated detection of mental illness is feasible for real-life applications including self-assessment, self-monitoring, and computerized health care

Time-frequency analysis of phonocardiogram signals using wavelet transform: a comparative study.

Science.gov (United States)

Ergen, Burhan; Tatar, Yetkin; Gulcur, Halil Ozcan

2012-01-01

Analysis of phonocardiogram (PCG) signals provides a non-invasive means to determine the abnormalities caused by cardiovascular system pathology. In general, time-frequency representation (TFR) methods are used to study the PCG signal because it is one of the non-stationary bio-signals. The continuous wavelet transform (CWT) is especially suitable for the analysis of non-stationary signals and to obtain the TFR, due to its high resolution, both in time and in frequency and has recently become a favourite tool. It decomposes a signal in terms of elementary contributions called wavelets, which are shifted and dilated copies of a fixed mother wavelet function, and yields a joint TFR. Although the basic characteristics of the wavelets are similar, each type of the wavelets produces a different TFR. In this study, eight real types of the most known wavelets are examined on typical PCG signals indicating heart abnormalities in order to determine the best wavelet to obtain a reliable TFR. For this purpose, the wavelet energy and frequency spectrum estimations based on the CWT and the spectra of the chosen wavelets were compared with the energy distribution and the autoregressive frequency spectra in order to determine the most suitable wavelet. The results show that Morlet wavelet is the most reliable wavelet for the time-frequency analysis of PCG signals.

Multiplicity counting from fission chamber signals in the current mode

Energy Technology Data Exchange (ETDEWEB)

Pázsit, I. [Chalmers University of Technology, Department of Physics, Division of Subatomic and Plasma Physics, SE-412 96 Göteborg (Sweden); Pál, L. [Centre for Energy Research, Hungarian Academy of Sciences, 114, POB 49, H-1525 Budapest (Hungary); Nagy, L. [Chalmers University of Technology, Department of Physics, Division of Subatomic and Plasma Physics, SE-412 96 Göteborg (Sweden); Budapest University of Technology and Economics, Institute of Nuclear Techniques, H-1111 Budapest (Hungary)

2016-12-11

In nuclear safeguards, estimation of sample parameters using neutron-based non-destructive assay methods is traditionally based on multiplicity counting with thermal neutron detectors in the pulse mode. These methods in general require multi-channel analysers and various dead time correction methods. This paper proposes and elaborates on an alternative method, which is based on fast neutron measurements with fission chambers in the current mode. A theory of “multiplicity counting” with fission chambers is developed by incorporating Böhnel's concept of superfission [1] into a master equation formalism, developed recently by the present authors for the statistical theory of fission chamber signals [2,3]. Explicit expressions are derived for the first three central auto- and cross moments (cumulants) of the signals of up to three detectors. These constitute the generalisation of the traditional Campbell relationships for the case when the incoming events represent a compound Poisson distribution. Because now the expressions contain the factorial moments of the compound source, they contain the same information as the singles, doubles and triples rates of traditional multiplicity counting. The results show that in addition to the detector efficiency, the detector pulse shape also enters the formulas; hence, the method requires a more involved calibration than the traditional method of multiplicity counting. However, the method has some advantages by not needing dead time corrections, as well as having a simpler and more efficient data processing procedure, in particular for cross-correlations between different detectors, than the traditional multiplicity counting methods.

Temperature analysis with voltage-current time differential operation of electrochemical sensors

Energy Technology Data Exchange (ETDEWEB)

Woo, Leta Yar-Li; Glass, Robert Scott; Fitzpatrick, Joseph Jay; Wang, Gangqiang; Henderson, Brett Tamatea; Lourdhusamy, Anthoniraj; Steppan, James John; Allmendinger, Klaus Karl

2018-01-02

A method for temperature analysis of a gas stream. The method includes identifying a temperature parameter of an affected waveform signal. The method also includes calculating a change in the temperature parameter by comparing the affected waveform signal with an original waveform signal. The method also includes generating a value from the calculated change which corresponds to the temperature of the gas stream.

An electromagnetic signals monitoring and analysis wireless platform employing personal digital assistants and pattern analysis techniques

Science.gov (United States)

Ninos, K.; Georgiadis, P.; Cavouras, D.; Nomicos, C.

2010-05-01

This study presents the design and development of a mobile wireless platform to be used for monitoring and analysis of seismic events and related electromagnetic (EM) signals, employing Personal Digital Assistants (PDAs). A prototype custom-developed application was deployed on a 3G enabled PDA that could connect to the FTP server of the Institute of Geodynamics of the National Observatory of Athens and receive and display EM signals at 4 receiver frequencies (3 KHz (E-W, N-S), 10 KHz (E-W, N-S), 41 MHz and 46 MHz). Signals may originate from any one of the 16 field-stations located around the Greek territory. Employing continuous recordings of EM signals gathered from January 2003 till December 2007, a Support Vector Machines (SVM)-based classification system was designed to distinguish EM precursor signals within noisy background. EM-signals corresponding to recordings preceding major seismic events (Ms≥5R) were segmented, by an experienced scientist, and five features (mean, variance, skewness, kurtosis, and a wavelet based feature), derived from the EM-signals were calculated. These features were used to train the SVM-based classification scheme. The performance of the system was evaluated by the exhaustive search and leave-one-out methods giving 87.2% overall classification accuracy, in correctly identifying EM precursor signals within noisy background employing all calculated features. Due to the insufficient processing power of the PDAs, this task was performed on a typical desktop computer. This optimal trained context of the SVM classifier was then integrated in the PDA based application rendering the platform capable to discriminate between EM precursor signals and noise. System's efficiency was evaluated by an expert who reviewed 1/ multiple EM-signals, up to 18 days prior to corresponding past seismic events, and 2/ the possible EM-activity of a specific region employing the trained SVM classifier. Additionally, the proposed architecture can form a

Evaluation of Eddy Current Signals from the Inner Wall Axial Cracks of Steam Generator Tubes

International Nuclear Information System (INIS)

Choi, Myung Sik; Hur, Do Haeng; Lee, Doek Hyun; Han, Jung Ho; Park, Jung Am

2001-01-01

For the enhancement of ECT reliability on the primary water stress corrosion cracks of nuclear steam generator tubes, of which the occurrence is on the increase, it is important to comprehend the signal characteristics on crack morphology and to select an appropriate probe type. In this paper, the sizing accuracy and the detectability for the inner wall axial cracks of tubes were quantitatively evaluated using the following specimens: the electric discharge machined notches and the corrosion cracks which were developed on the operating steam generator tubes. The difference of eddy current signal characteristics between pancake and axial coil were also Investigated. The results obtained from this study provide a useful information for more precise evaluation on the inner wall axial tracks oi steam generator tubes

A noise reconfigurable current-reuse resistive feedback amplifier with signal-dependent power consumption for fetal ECG monitoring

NARCIS (Netherlands)

Song, Shuang; Rooijakkers, M.J.; Harpe, P.; Rabotti, C.; Mischi, M.; Van Roermund, A.H.M.; Cantatore, E.

2016-01-01

This paper presents a noise-reconfigurable resistive feedback amplifier with current-reuse technique for fetal ECG monitoring. The proposed amplifier allows for both tuning of the noise level and changing the power consumption according to the signal properties, minimizing the total power

CMS Data Analysis: Current Status and Future Strategy

CERN Document Server

Innocente, V

2003-01-01

We present the current status of CMS data analysis architecture and describe work on future Grid-based distributed analysis prototypes. CMS has two main software frameworks related to data analysis: COBRA, the main framework, and IGUANA, the interactive visualisation framework. Software using these frameworks is used today in the world-wide production and analysis of CMS data. We describe their overall design and present examples of their current use with emphasis on interactive analysis. CMS is currently developing remote analysis prototypes, including one based on Clarens, a Grid-enabled client-server tool. Use of the prototypes by CMS physicists will guide us in forming a Grid-enriched analysis strategy. The status of this work is presented, as is an outline of how we plan to leverage the power of our existing frameworks in the migration of CMS software to the Grid.

Eddy current analysis in fusion devices

International Nuclear Information System (INIS)

Turner, L.R.

1988-06-01

In magnetic fusion devices, particularly tokamaks and reversed field pinch (RFP) experiments, time-varying magnetic fields are in intimate contact with electrically conducting components of the device. Induced currents, fields, forces, and torques result. This note reviews the analysis of eddy current effects in the following systems: Interaction of a tokamak plasma with the eddy currents in the first wall, blanket, and shield (FWBS) systems; Eddy currents in a complex but two-dimensional vacuum vessel, as in TFTR, JET, and JT-60; Eddy currents in the FWBS system of a tokamak reactor, such as NET, FER, or ITER; and Eddy currents in a RFP shell. The cited studies are chosen to be illustrative, rather than exhaustive. 42 refs

Improving the spatial resolution in CZT detectors using charge sharing effect and transient signal analysis: Simulation study

Energy Technology Data Exchange (ETDEWEB)

Zheng, Xiaoqing; Cheng, Zeng [Department of Electrical and Computer Engineering, McMaster University (Canada); Deen, M. Jamal, E-mail: jamal@mcmaster.ca [Department of Electrical and Computer Engineering, McMaster University (Canada); School of Biomedical Engineering, McMaster University (Canada); Peng, Hao, E-mail: penghao@mcmaster.ca [Department of Electrical and Computer Engineering, McMaster University (Canada); School of Biomedical Engineering, McMaster University (Canada); Department of Medical Physics, McMaster University, Ontario L8S 4K1, Hamilton (Canada)

2016-02-01

Cadmium Zinc Telluride (CZT) semiconductor detectors are capable of providing superior energy resolution and three-dimensional position information of gamma ray interactions in a large variety of fields, including nuclear physics, gamma-ray imaging and nuclear medicine. Some dedicated Positron Emission Tomography (PET) systems, for example, for breast cancer detection, require higher contrast recovery and more accurate event location compared with a whole-body PET system. The spatial resolution is currently limited by electrode pitch in CZT detectors. A straightforward approach to increase the spatial resolution is by decreasing the detector electrode pitch, but this leads to higher fabrication cost and a larger number of readout channels. In addition, inter-electrode charge spreading can negate any improvement in spatial resolution. In this work, we studied the feasibility of achieving sub-pitch spatial resolution in CZT detectors using two methods: charge sharing effect and transient signal analysis. We noted that their valid ranges of usage were complementary. The dependences of their corresponding valid ranges on electrode design, depth-of-interaction (DOI), voltage bias and signal triggering threshold were investigated. The implementation of these two methods in both pixelated and cross-strip configuration of CZT detectors were discussed. Our results show that the valid range of charge sharing effect increases as a function of DOI, but decreases with increasing gap width and bias voltage. For a CZT detector of 5 mm thickness, 100 µm gap and biased at 400 V, the valid range of charge sharing effect was found to be about 112.3 µm around the gap center. This result complements the valid range of the transient signal analysis within one electrode pitch. For a signal-to-noise ratio (SNR) of ~17 and preliminary measurements, the sub-pitch spatial resolution is expected to be ~30 µm and ~250 µm for the charge sharing and transient signal analysis methods

The analysis of transesophageal oxygen saturation photoplethysmography from different signal sources.

Science.gov (United States)

Mou, Ling; Gong, Quan; Wei, Wei; Gao, Bo

2013-06-01

The photoplethysmography (PPG) signals detected by transesophageal oximetry sensor toward aorta arch (AA), descending aorta (DA), and left ventricle (LV) under the guidance of transesophageal echocardiography (TEE) were investigated, and the effects of filter application on PPG signals were evaluated. Eleven cardiac surgical patients were involved. After anesthesia was induced, the TEE probe with a modified pulse oximetry sensor was inserted. Under the guidance of TEE, the AA PPG, DA PPG and LV PPG were detected respectively when ventilator was on and off. The mean alternating current (AC) amplitudes and direct current (DC) values of original and filtered PPG signals were measured. The ratio of AC and DC value (AC/DC) and ventilation-induced AC variations were calculated. Satisfactory PPG waveforms were obtained in all patients under the guidance of TEE. The AC amplitude in LV PPG was significant larger than in AA and DA PPG, and both AC/DC and ventilation-induced AC variation in LV PPG were significantly higher than in AA PPG or DA PPG either. There were no significant differences of AC amplitude between filtered and ventilation off PPG signals. The AC amplitudes and AC/DC toward LV are significantly higher than transesophageal oximeter toward AA or DA, and the effect of mechanical ventilation on transesophageal PPG can be obviously reduced by filtering techniques.

Current level detector

International Nuclear Information System (INIS)

Kerns, C.R.

1977-01-01

A device is provided for detecting the current level of a dc signal. It includes an even harmonic modulator to which a reference ac signal is applied. The unknown dc signal acts on the reference ac signal so that the output of the modulator includes an even harmonic whose amplitude is proportional to the unknown dc current. The device may be used to provide overcurrent protection for proportional wire chambers

Analysis of Satellite-Based Navigation Signal Reflectometry: Simulations and Observations

DEFF Research Database (Denmark)

von Benzon, Hans-Henrik; Høeg, Per; Durgonics, Tibor

2016-01-01

on different ocean characteristics. The spectra of the simulated surface reflections are analyzed, and the results from the simulations are compared to measured GPS surface reflections. The measurements were performed using a space-qualified GPS receiver placed on a mountain at the Haleakala observatory...... on the Hawaiian island of Maui. The GPS receiver was during the experiments running in an open-loop configuration. The analysis of both the simulated surface-reflection signals and the measured reflection signals will in general reveal spectral structures of the reflected signals that can lead to extraction...

Signal transforms in dynamic measurements

CERN Document Server

Layer, Edward

2015-01-01

This book is devoted to the analysis of measurement signals which requires specific mathematical operations like Convolution, Deconvolution, Laplace, Fourier, Hilbert, Wavelet or Z transform which are all presented in the present book. The different problems refer to the modulation of signals, filtration of disturbance as well as to the orthogonal signals and their use in digital form for the measurement of current, voltage, power and frequency are also widely discussed. All the topics covered in this book are presented in detail and illustrated by means of examples in MathCad and LabVIEW. This book provides a useful source for researchers, scientists and engineers who in their daily work are required to deal with problems of measurement and signal processing and can also be helpful to undergraduate students of electrical engineering.    

Speed Control Analysis of Brushless DC Motor Based on Maximum Amplitude DC Current Feedback

Directory of Open Access Journals (Sweden)

Hassan M.A.A.

2014-07-01

Full Text Available This paper describes an approach to develop accurate and simple current controlled modulation technique for brushless DC (BLDC motor drive. The approach is applied to control phase current based on generation of quasi-square wave current by using only one current controller for the three phases. Unlike the vector control method which is complicated to be implemented, this simple current modulation technique presents advantages such as phase currents are kept in balance and the current is controlled through only one dc signal which represent maximum amplitude value of trapezoidal current (Imax. This technique is performed with Proportional Integral (PI control algorithm and triangular carrier comparison method to generate Pulse Width Modulation (PWM signal. In addition, the PI speed controller is incorporated with the current controller to perform desirable speed operation of non-overshoot response. The performance and functionality of the BLDC motor driver are verified via simulation by using MATLAB/SIMULINK. The simulation results show the developed control system performs desirable speed operation of non-overshoot and good current waveforms.

Modelling and Analysis of Biochemical Signalling Pathway Cross-talk

Directory of Open Access Journals (Sweden)

Robin Donaldson

2010-02-01

Full Text Available Signalling pathways are abstractions that help life scientists structure the coordination of cellular activity. Cross-talk between pathways accounts for many of the complex behaviours exhibited by signalling pathways and is often critical in producing the correct signal-response relationship. Formal models of signalling pathways and cross-talk in particular can aid understanding and drive experimentation. We define an approach to modelling based on the concept that a pathway is the (synchronising parallel composition of instances of generic modules (with internal and external labels. Pathways are then composed by (synchronising parallel composition and renaming; different types of cross-talk result from different combinations of synchronisation and renaming. We define a number of generic modules in PRISM and five types of cross-talk: signal flow, substrate availability, receptor function, gene expression and intracellular communication. We show that Continuous Stochastic Logic properties can both detect and distinguish the types of cross-talk. The approach is illustrated with small examples and an analysis of the cross-talk between the TGF-b/BMP, WNT and MAPK pathways.

Analysis of impulse signals with Hylaty ELF station

Science.gov (United States)

Kulak, A.; Mlynarczyk, J.; Ostrowski, M.; Kubisz, J.; Michalec, A.

2012-04-01

Lighting discharges generate electromagnetic field pulses that propagate in the Earth-ionosphere waveguide. The attenuation in the ELF range is so small that the pulses originating from strong atmospheric discharges can be observed even several thousand kilometers away from the individual discharge. The recorded waveform depends on the discharge process, the Earth-ionosphere waveguide properties on the source-receiver path, and the transfer function of the receiver. If the distance from the source is known, an inverse method can be used for reconstructing the current moment waveform and the charge moment of the discharge. In order to reconstruct the source parameters from the recorded signal a reliable model of the radio wave propagation in the Earth-ionosphere waveguide as well as practical signal processing techniques are necessary. We present two methods, both based on analytical formulas. The first method allows for fast calculation of the charge moment of relatively short atmospheric discharges. It is based on peak amplitude measurement of the recorded magnetic component of the ELF EM field and it takes into account the receiver characteristics. The second method, called "inverse channel method" allows reconstructing the complete current moment waveform of strong atmospheric discharges that exhibit the continuing current phase, such as Gigantic Jets and Sprites. The method makes it possible to fully remove from the observed waveform the distortions related to the receiver's impulse response as well as the influence of the Earth-ionosphere propagation channel. Our ELF station is equipped with two magnetic antennas for Bx and By components measurement in the 0.03 to 55 Hz frequency range. ELF Data recording is carried out since 1993, with continuous data acquisition since 2005. The station features low noise level and precise timing. It is battery powered and located in the sparsely populated area, far from major electric power lines, which results in high

The time course of individual face recognition: A pattern analysis of ERP signals.

Science.gov (United States)

Nemrodov, Dan; Niemeier, Matthias; Mok, Jenkin Ngo Yin; Nestor, Adrian

2016-05-15

An extensive body of work documents the time course of neural face processing in the human visual cortex. However, the majority of this work has focused on specific temporal landmarks, such as N170 and N250 components, derived through univariate analyses of EEG data. Here, we take on a broader evaluation of ERP signals related to individual face recognition as we attempt to move beyond the leading theoretical and methodological framework through the application of pattern analysis to ERP data. Specifically, we investigate the spatiotemporal profile of identity recognition across variation in emotional expression. To this end, we apply pattern classification to ERP signals both in time, for any single electrode, and in space, across multiple electrodes. Our results confirm the significance of traditional ERP components in face processing. At the same time though, they support the idea that the temporal profile of face recognition is incompletely described by such components. First, we show that signals associated with different facial identities can be discriminated from each other outside the scope of these components, as early as 70ms following stimulus presentation. Next, electrodes associated with traditional ERP components as well as, critically, those not associated with such components are shown to contribute information to stimulus discriminability. And last, the levels of ERP-based pattern discrimination are found to correlate with recognition accuracy across subjects confirming the relevance of these methods for bridging brain and behavior data. Altogether, the current results shed new light on the fine-grained time course of neural face processing and showcase the value of novel methods for pattern analysis to investigating fundamental aspects of visual recognition. Copyright © 2016 Elsevier Inc. All rights reserved.

Removing Eddy-current probe wobble noise from steam generator tubes testing using wavelet transform

International Nuclear Information System (INIS)

Lopez, Luiz Antonio Negro Martin; Ting, Daniel Kao Sun; Upadhyaya, Belle R.

2005-01-01

One of the most import nondestructive evaluation (NDE) applied to steam generator tubes inspection is the electromagnetic Eddy-Current testing (ECT). The signals generated in this NDE, in general, contain many noises which make difficult the interpretation and analysis of ECT signals. One of the noises present in the signals is the probe wobble noise, which is caused by the existing slack between the probe and the tube. In this work, Wavelet Transform (WT) is used in the probe wobble de-noising. WT is a relatively recent mathematical tool, which allows local analysis of non stationary signals such as ECT signals. This is a great advantage of WT when compared with other analysis tools such as Fourier Transform. However, using WT involves wavelets and coefficients selection as well as choosing the number of decomposition level needed. This work presents a probe wobble de-noising method when used in conjunction with the traditional ECT evaluation. Comparative results using several WT applied do Eddy-Current signals are presented in a reliable way, in other words, without loss of inherent defect information. A stainless steel tube, with 2 artificial defects generated by electro-erosion, was inspected by a ZETEC MIZ-17ET ECT equipment. The signals were de-noised through several different WT and the results are presented. The method offer good results and is a promising method because allows for the removal of Eddy-Current signals probe wobble effect without loss of essential signal information. (author)

Wnt signaling in cancer

Science.gov (United States)

Zhan, T; Rindtorff, N; Boutros, M

2017-01-01

Wnt signaling is one of the key cascades regulating development and stemness, and has also been tightly associated with cancer. The role of Wnt signaling in carcinogenesis has most prominently been described for colorectal cancer, but aberrant Wnt signaling is observed in many more cancer entities. Here, we review current insights into novel components of Wnt pathways and describe their impact on cancer development. Furthermore, we highlight expanding functions of Wnt signaling for both solid and liquid tumors. We also describe current findings how Wnt signaling affects maintenance of cancer stem cells, metastasis and immune control. Finally, we provide an overview of current strategies to antagonize Wnt signaling in cancer and challenges that are associated with such approaches. PMID:27617575

Transistor Small Signal Analysis under Radiation Effects

International Nuclear Information System (INIS)

Sharshar, K.A.A.

2004-01-01

A Small signal transistor parameters dedicate the operation of bipolar transistor before and after exposed to gamma radiation (1 Mrad up to 5 Mrads) and electron beam(1 MeV, 25 mA) with the same doses as a radiation sources, the electrical parameters of the device are changed. The circuit Model has been discussed.Parameters, such as internal emitter resistance (re), internal base resistance, internal collector resistance (re), emitter base photocurrent (Ippe) and base collector photocurrent (Ippe). These parameters affect on the operation of the device in its applications, which work as an effective element, such as current gain (hFE≡β)degradation it's and effective parameter in the device operation. Also the leakage currents (IcBO) and (IEBO) are most important parameters, Which increased with radiation doses. Theoretical representation of the change in the equivalent circuit for NPN and PNP bipolar transistor were discussed, the input and output parameters of the two types were discussed due to the change in small signal input resistance of the two types. The emitter resistance(re) were changed by the effect of gamma and electron beam irradiation, which makes a change in the role of matching impedances between transistor stages. Also the transistor stability factors S(Ico), S(VBE) and S(β are detected to indicate the transistor operations after exposed to radiation fields. In low doses the gain stability is modified due to recombination of induced charge generated during device fabrication. Also the load resistance values are connected to compensate the effect

Study of interhemispheric asymmetries in electroencephalographic signals by frequency analysis

International Nuclear Information System (INIS)

Zapata, J F; Garzon, J

2011-01-01

This study provides a new method for the detection of interhemispheric asymmetries in patients with continuous video-electroencephalography (EEG) monitoring at Intensive Care Unit (ICU), using wavelet energy. We obtained the registration of EEG signals in 42 patients with different pathologies, and then we proceeded to perform signal processing using the Matlab program, we compared the abnormalities recorded in the report by the neurophysiologist, the images of each patient and the result of signals analysis with the Discrete Wavelet Transform (DWT). Conclusions: there exists correspondence between the abnormalities found in the processing of the signal with the clinical reports of findings in patients; according to previous conclusion, the methodology used can be a useful tool for diagnosis and early quantitative detection of interhemispheric asymmetries.

Development of a methodology for analysis of delayed-neutron signals

International Nuclear Information System (INIS)

Gross, K.C.; Strain, R.V.; Fryer, R.M.

1980-02-01

Experimental and analytical techniques have been developed for analysis and characterization of delayed-neutron (DN) signals that can provide diagnostic information to augment data from cover-gas analyses in the detection and identification of breached elements in an LMFBR. Eleven flow-reduction tests have been run in EBR-II to provide base data support for predicting DN signal characteristics during exposed-fuel operation. Results from the tests demonstrate the feasibility and practicability of response-analysis techniques for determining (a) the transit time, T/sub tr/, for DN emitters traveling from the core to the detector and (b) the isotropic holdup time, T/sub h/, of DN precursors in the fuel element

Stationary analysis of signals and ratio decay determination in BWR type reactors by neuronal network

International Nuclear Information System (INIS)

Sanchis, R.; Palomo, M. J.; Munoz-Cobo, J. L.

1998-01-01

The signals registered in the nuclear plants have non stationary characteristics, in numerous times. This made difficult the application of the methods of analysis. There are determinate temporal intervals in that the signal is stationary with determinate mean, value together of zones with corrupt registers, and other zones with mean value distinct, but stationary during a temporal interval. The methodology consist in a stationary analysis to the signal received of the nuclear plant. With the Gabor Transformation are determined the temporal intervals of the stationary signals, synthesised it, as previous phase to the application of the methods of the analysis of stability parameters with methods ARMA, SVD, Neural Net,... to the reconstructed signal. 4 refs. (Author)

Application of «Sensor signal analysis network» complex for distributed, time synchronized analysis of electromagnetic radiation

Science.gov (United States)

Mochalov, Vladimir; Mochalova, Anastasia

2017-10-01

The paper considers a developing software-hardware complex «Sensor signal analysis network» for distributed and time synchronized analysis of electromagnetic radiations. The areas of application and the main features of the complex are described. An example of application of the complex to monitor natural electromagnetic radiation sources is considered based on the data recorded in VLF range. A generalized functional scheme of stream analysis of signals by a complex functional node is suggested and its application for stream detection of atmospherics, whistlers and tweaks is considered.

Automatic modulation recognition of communication signals

CERN Document Server

Azzouz, Elsayed Elsayed

1996-01-01

Automatic modulation recognition is a rapidly evolving area of signal analysis. In recent years, interest from the academic and military research institutes has focused around the research and development of modulation recognition algorithms. Any communication intelligence (COMINT) system comprises three main blocks: receiver front-end, modulation recogniser and output stage. Considerable work has been done in the area of receiver front-ends. The work at the output stage is concerned with information extraction, recording and exploitation and begins with signal demodulation, that requires accurate knowledge about the signal modulation type. There are, however, two main reasons for knowing the current modulation type of a signal; to preserve the signal information content and to decide upon the suitable counter action, such as jamming. Automatic Modulation Recognition of Communications Signals describes in depth this modulation recognition process. Drawing on several years of research, the authors provide a cr...

Distributed sensing signal analysis of deformable plate/membrane mirrors

Science.gov (United States)

Lu, Yifan; Yue, Honghao; Deng, Zongquan; Tzou, Hornsen

2017-11-01

Deformable optical mirrors usually play key roles in aerospace and optical structural systems applied to space telescopes, radars, solar collectors, communication antennas, etc. Limited by the payload capacity of current launch vehicles, the deformable mirrors should be lightweight and are generally made of ultra-thin plates or even membranes. These plate/membrane mirrors are susceptible to external excitations and this may lead to surface inaccuracy and jeopardize relevant working performance. In order to investigate the modal vibration characteristics of the mirror, a piezoelectric layer is fully laminated on its non-reflective side to serve as sensors. The piezoelectric layer is segmented into infinitesimal elements so that microscopic distributed sensing signals can be explored. In this paper, the deformable mirror is modeled as a pre-tensioned plate and membrane respectively and sensing signal distributions of the two models are compared. Different pre-tensioning forces are also applied to reveal the tension effects on the mode shape and sensing signals of the mirror. Analytical results in this study could be used as guideline of optimal sensor/actuator placement for deformable space mirrors.

Intramolecular 13C analysis of tree rings provides multiple plant ecophysiology signals covering decades.

Science.gov (United States)

Wieloch, Thomas; Ehlers, Ina; Yu, Jun; Frank, David; Grabner, Michael; Gessler, Arthur; Schleucher, Jürgen

2018-03-22

Measurements of carbon isotope contents of plant organic matter provide important information in diverse fields such as plant breeding, ecophysiology, biogeochemistry and paleoclimatology. They are currently based on 13 C/ 12 C ratios of specific, whole metabolites, but we show here that intramolecular ratios provide higher resolution information. In the glucose units of tree-ring cellulose of 12 tree species, we detected large differences in 13 C/ 12 C ratios (>10‰) among carbon atoms, which provide isotopically distinct inputs to major global C pools, including wood and soil organic matter. Thus, considering position-specific differences can improve characterisation of soil-to-atmosphere carbon fluxes and soil metabolism. In a Pinus nigra tree-ring archive formed from 1961 to 1995, we found novel 13 C signals, and show that intramolecular analysis enables more comprehensive and precise signal extraction from tree rings, and thus higher resolution reconstruction of plants' responses to climate change. Moreover, we propose an ecophysiological mechanism for the introduction of a 13 C signal, which links an environmental shift to the triggered metabolic shift and its intramolecular 13 C signature. In conclusion, intramolecular 13 C analyses can provide valuable new information about long-term metabolic dynamics for numerous applications.

The ultimate intrinsic signal-to-noise ratio of loop- and dipole-like current patterns in a realistic human head model.

Science.gov (United States)

Pfrommer, Andreas; Henning, Anke

2018-03-13

The ultimate intrinsic signal-to-noise ratio (UISNR) represents an upper bound for the achievable SNR of any receive coil. To reach this threshold a complete basis set of equivalent surface currents is required. This study systematically investigated to what extent either loop- or dipole-like current patterns are able to reach the UISNR threshold in a realistic human head model between 1.5 T and 11.7 T. Based on this analysis, we derived guidelines for coil designers to choose the best array element at a given field strength. Moreover, we present ideal current patterns yielding the UISNR in a realistic body model. We distributed generic current patterns on a cylindrical and helmet-shaped surface around a realistic human head model. We excited electromagnetic fields in the human head by using eigenfunctions of the spherical and cylindrical Helmholtz operator. The electromagnetic field problem was solved by a fast volume integral equation solver. At 7 T and above, adding curl-free current patterns to divergence-free current patterns substantially increased the SNR in the human head (locally >20%). This was true for the helmet-shaped and the cylindrical surface. On the cylindrical surface, dipole-like current patterns had high SNR performance in central regions at ultra-high field strength. The UISNR increased superlinearly with B0 in most parts of the cerebrum but only sublinearly in the periphery of the human head. The combination of loop and dipole elements could enhance the SNR performance in the human head at ultra-high field strength. © 2018 International Society for Magnetic Resonance in Medicine.

Electrochemical Random Signal Analysis during Localized Corrosion of Anodized 1100 Aluminum Alloy in Chloride Environments

International Nuclear Information System (INIS)

Sakairi, M.; Shimoyama, Y.; Nagasawa, D.

2008-01-01

A new type of electrochemical random signal (electrochemical noise) analysis technique was applied to localized corrosion of anodic oxide film formed 1100 aluminum alloy in 0.5 kmol/m 3 H 3 BO 4 /0.05 kmol/m 3 Na 2 B 4 O 7 with 0.01 kmol/m 3 NaCl. The effect of anodic oxide film structure, barrier type, porous type, and composite type on galvanic corrosion resistance was also examined. Before localized corrosion started, incubation period for pitting corrosion, both current and potential slightly change as initial value with time. The incubation period of porous type anodic oxide specimens are longer than that of barrier type anodic oxide specimens. While pitting corrosion, the current and potential were changed with fluctuations and the potential and the current fluctuations show a good correlation. The records of the current and potential were processed by calculating the power spectrum density (PSD) by the Fast Fourier Transform (FFT) method. The potential and current PSD decrease with increasing frequency, and the slopes are steeper than or equal to minus one (-1). This technique allows observation of electrochemical impedance changes during localized corrosion

Joint time frequency analysis in digital signal processing

DEFF Research Database (Denmark)

Pedersen, Flemming

with this technique is that the resolution is limited because of distortion. To overcome the resolution limitations of the Fourier Spectogram, many new distributions have been developed. In spite of this the Fourier Spectogram is by far the prime method for the analysis of signals whose spectral content is varying...

Analysis Sparse Representation for Nonnegative Signals Based on Determinant Measure by DC Programming

Directory of Open Access Journals (Sweden)

Yujie Li

2018-01-01

Full Text Available Analysis sparse representation has recently emerged as an alternative approach to the synthesis sparse model. Most existing algorithms typically employ the l0-norm, which is generally NP-hard. Other existing algorithms employ the l1-norm to relax the l0-norm, which sometimes cannot promote adequate sparsity. Most of these existing algorithms focus on general signals and are not suitable for nonnegative signals. However, many signals are necessarily nonnegative such as spectral data. In this paper, we present a novel and efficient analysis dictionary learning algorithm for nonnegative signals with the determinant-type sparsity measure which is convex and differentiable. The analysis sparse representation can be cast in three subproblems, sparse coding, dictionary update, and signal update, because the determinant-type sparsity measure would result in a complex nonconvex optimization problem, which cannot be easily solved by standard convex optimization methods. Therefore, in the proposed algorithms, we use a difference of convex (DC programming scheme for solving the nonconvex problem. According to our theoretical analysis and simulation study, the main advantage of the proposed algorithm is its greater dictionary learning efficiency, particularly compared with state-of-the-art algorithms. In addition, our proposed algorithm performs well in image denoising.

Bearing defect signature analysis using advanced nonlinear signal analysis in a controlled environment

Science.gov (United States)

Zoladz, T.; Earhart, E.; Fiorucci, T.

1995-01-01

Utilizing high-frequency data from a highly instrumented rotor assembly, seeded bearing defect signatures are characterized using both conventional linear approaches, such as power spectral density analysis, and recently developed nonlinear techniques such as bicoherence analysis. Traditional low-frequency (less than 20 kHz) analysis and high-frequency envelope analysis of both accelerometer and acoustic emission data are used to recover characteristic bearing distress information buried deeply in acquired data. The successful coupling of newly developed nonlinear signal analysis with recovered wideband envelope data from accelerometers and acoustic emission sensors is the innovative focus of this research.

Analysis of a dynamic model of guard cell signaling reveals the stability of signal propagation

Science.gov (United States)

Gan, Xiao; Albert, RéKa

Analyzing the long-term behaviors (attractors) of dynamic models of biological systems can provide valuable insight into biological phenotypes and their stability. We identified the long-term behaviors of a multi-level, 70-node discrete dynamic model of the stomatal opening process in plants. We reduce the model's huge state space by reducing unregulated nodes and simple mediator nodes, and by simplifying the regulatory functions of selected nodes while keeping the model consistent with experimental observations. We perform attractor analysis on the resulting 32-node reduced model by two methods: 1. converting it into a Boolean model, then applying two attractor-finding algorithms; 2. theoretical analysis of the regulatory functions. We conclude that all nodes except two in the reduced model have a single attractor; and only two nodes can admit oscillations. The multistability or oscillations do not affect the stomatal opening level in any situation. This conclusion applies to the original model as well in all the biologically meaningful cases. We further demonstrate the robustness of signal propagation by showing that a large percentage of single-node knockouts does not affect the stomatal opening level. Thus, we conclude that the complex structure of this signal transduction network provides multiple information propagation pathways while not allowing extensive multistability or oscillations, resulting in robust signal propagation. Our innovative combination of methods offers a promising way to analyze multi-level models.

Analysis of monochromatic signals by using data from the detector of Allegro gravitational waves

International Nuclear Information System (INIS)

Oliveira, Fernanda Gomes de

2010-01-01

The present work is developed in the searching for monochromatic gravitational waves signals in ALLEGRO's data. We have two procedures for data analysis based on the periodogram of Welch, which a method for the detection of monochromatic signals in the middle of noise which basically makes power spectrum estimates using averaged modified periodograms. By using this method it was possible to obtain a power spectrum for the data which reinforce peaks due to monochromatic signals. The two procedures of analysis for the years 1997 and 1999, were focused on monitoring a peak that appears in the spectral density of ALLEGRO's detector, so called 'mystery mode' (near 887 Hz). We look for variations in the frequency of the mystery mode that agree with the variation of the Doppler effect. In the rst analysis we have used by the variation of daily and annual Doppler shift. For the second one, we have only searched annual Doppler shift. We have applied the periodogram of Welch in both tests in the raw data of the detector in the search for a real signal and we found some peaks that can be candidates of gravitational radiation only the second analysis. In order to test the method we used in both analysis a simulated gravitational wave signal modulated by the Doppler effect injected in the data. We detected in both methods the artificial signal of GW simulated. Therefore we have reason to conclude that both methods are efficient in the search for monochromatic signals. (author)

An introduction to audio content analysis applications in signal processing and music informatics

CERN Document Server

Lerch, Alexander

2012-01-01

"With the proliferation of digital audio distribution over digital media, audio content analysis is fast becoming a requirement for designers of intelligent signal-adaptive audio processing systems. Written by a well-known expert in the field, this book provides quick access to different analysis algorithms and allows comparison between different approaches to the same task, making it useful for newcomers to audio signal processing and industry experts alike. A review of relevant fundamentals in audio signal processing, psychoacoustics, and music theory, as well as downloadable MATLAB files are also included"--

Essential parameters in eddy current inspection

International Nuclear Information System (INIS)

Stepinski, T.

2000-05-01

Our aim was to qualitatively analyze a number of variables that may affect the result of eddy current (EC) inspection but because of various reasons are not considered as essential in common practice. In the report we concentrate on such variables that can vary during or between inspections but their influence is not determined during routine calibrations. We present a qualitative analysis of the influence of the above-mentioned variables on the ability to detect and size flaws using mechanized eddy current testing (ET). ET employs some type of coil or probe, sensing magnetic flux generated by eddy currents induced in the tested specimen. An amplitude-phase modulated signal (with test frequency f0 ) from the probe is sensed by the EC instrument. The amplitude-phase modulated signal is amplified and demodulated in phase-sensitive detectors removing carrier frequency f0 from the signal. The detectors produce an in-phase and a quadrature component of the signal defining it as a point in the impedance plane. Modern instruments are provided with a screen presenting the demodulated and filtered signal in complex plane. We focus on such issues, related to the EC equipment as, probe matching, distortion introduced by phase discriminators and signal filters, and the influence of probe resolution and lift-off on sizing. The influence of different variables is investigated by means of physical reasoning employing theoretical models and demonstrated using simulated and real EC signals. In conclusion, we discuss the way in which the investigated variables may affect the result of ET. We also present a number of practical recommendations for the users of ET and indicate the areas that are to be further analyzed

Signal analysis and processing for SmartPET

International Nuclear Information System (INIS)

Scraggs, David; Boston, Andrew; Boston, Helen; Cooper, Reynold; Hall, Chris; Mather, Andy; Nolan, Paul; Turk, Gerard

2007-01-01

Measurement of induced transient charges on spectator electrodes is a critical requirement of the SmartPET project. Such a task requires the precise measurement of small amplitude pulses. Induced charge magnitudes on the SmartPET detectors were therefore studied and the suitability of wavelet analysis applied to de-noising signals was investigated. It was found that the absolute net maximum induced charge magnitudes from the two adjacent electrodes to the collecting electrode is 17% of the real charge magnitude for the AC side and 20% for the DC side. It was also found that wavelet analysis could identify induced charges of comparable magnitude to system noise

Application on technique of joint time-frequency analysis of seismic signal's first arrival estimation

International Nuclear Information System (INIS)

Xu Chaoyang; Liu Junmin; Fan Yanfang; Ji Guohua

2008-01-01

Joint time-frequency analysis is conducted to construct one joint density function of time and frequency. It can open out one signal's frequency components and their evolvements. It is the new evolvement of Fourier analysis. In this paper, according to the characteristic of seismic signal's noise, one estimation method of seismic signal's first arrival based on triple correlation of joint time-frequency spectrum is introduced, and the results of experiment and conclusion are presented. (authors)

Cascaded analysis of signal and noise propagation through a heterogeneous breast model

International Nuclear Information System (INIS)

Mainprize, James G.; Yaffe, Martin J.

2010-01-01

Purpose: The detectability of lesions in radiographic images can be impaired by patterns caused by the surrounding anatomic structures. The presence of such patterns is often referred to as anatomic noise. Others have previously extended signal and noise propagation theory to include variable background structure as an additional noise term and used in simulations for analysis by human and ideal observers. Here, the analytic forms of the signal and noise transfer are derived to obtain an exact expression for any input random distribution and the ''power law'' filter used to generate the texture of the tissue distribution. Methods: A cascaded analysis of propagation through a heterogeneous model is derived for x-ray projection through simulated heterogeneous backgrounds. This is achieved by considering transmission through the breast as a correlated amplification point process. The analytic forms of the cascaded analysis were compared to monoenergetic Monte Carlo simulations of x-ray propagation through power law structured backgrounds. Results: As expected, it was found that although the quantum noise power component scales linearly with the x-ray signal, the anatomic noise will scale with the square of the x-ray signal. There was a good agreement between results obtained using analytic expressions for the noise power and those from Monte Carlo simulations for different background textures, random input functions, and x-ray fluence. Conclusions: Analytic equations for the signal and noise properties of heterogeneous backgrounds were derived. These may be used in direct analysis or as a tool to validate simulations in evaluating detectability.

Random signal tomographical analysis of two-phase flow

International Nuclear Information System (INIS)

Han, P.; Wesser, U.

1990-01-01

This paper reports on radiation tomography which is a useful tool for studying the internal structures of two-phase flow. However, general tomography analysis gives only time-averaged results, hence much information is lost. As a result, it is sometimes difficult to identify the flow regime; for example, the time-averaged picture does not significantly change as an annual flow develops from a slug flow. A two-phase flow diagnostic technique based on random signal tomographical analysis is developed. It extracts more information by studying the statistical variation of the measured signal with time. Local statistical parameters, including mean value, variance, skewness and flatness etc., are reconstructed from the information obtained by a general tomography technique. More important information are provided by the results. Not only the void fraction can be easily calculated, but also the flow pattern can be identified more objectively and more accurately. The experimental setup is introduced. It consisted of a two-phase flow loop, an X-ray system, a fan-like five-beam detector system and a signal acquisition and processing system. In the experiment, for both horizontal and vertical test sections (aluminum and steel tube with Di/Do = 40/45 mm), different flow situations are realized by independently adjusting air and water mass flow. Through a glass tube connected with the test section, some typical flow patterns are visualized and used for comparing with the reconstruction results

Advanced Time-Frequency Representation in Voice Signal Analysis

Directory of Open Access Journals (Sweden)

Dariusz Mika

2018-03-01

Full Text Available The most commonly used time-frequency representation of the analysis in voice signal is spectrogram. This representation belongs in general to Cohen's class, the class of time-frequency energy distributions. From the standpoint of properties of the resolution spectrogram representation is not optimal. In Cohen class representations are known which have a better resolution properties. All of them are created by smoothing the Wigner-Ville'a (WVD distribution characterized by the best resolution, however, the biggest harmful interference. Used smoothing functions decide about a compromise between the properties of resolution and eliminating harmful interference term. Another class of time-frequency energy distributions is the affine class of distributions. From the point of view of readability of analysis the best properties are known so called Redistribution of energy caused by the use of a general methodology referred to as reassignment to any time-frequency representation. Reassigned distributions efficiently combine a reduction of the interference terms provided by a well adapted smoothing kernel and an increased concentration of the signal components.

The differential Howland current source with high signal to noise ratio for bioimpedance measurement system

Energy Technology Data Exchange (ETDEWEB)

Liu, Jinzhen; Li, Gang; Lin, Ling, E-mail: linling@tju.edu.cn [State Key Laboratory of Precision Measurement Technology and Instruments, Tianjin University, Tianjin, People' s Republic of China, and Tianjin Key Laboratory of Biomedical Detecting Techniques and Instruments, Tianjin University, Tianjin (China); Qiao, Xiaoyan [College of Physics and Electronic Engineering, Shanxi University, Shanxi (China); Wang, Mengjun [School of Information Engineering, Hebei University of Technology, Tianjin (China); Zhang, Weibo [Institute of Acupuncture and Moxibustion China Academy of Chinese Medical Sciences, Beijing (China)

2014-05-15

The stability and signal to noise ratio (SNR) of the current source circuit are the important factors contributing to enhance the accuracy and sensitivity in bioimpedance measurement system. In this paper we propose a new differential Howland topology current source and evaluate its output characters by simulation and actual measurement. The results include (1) the output current and impedance in high frequencies are stabilized after compensation methods. And the stability of output current in the differential current source circuit (DCSC) is 0.2%. (2) The output impedance of two current circuits below the frequency of 200 KHz is above 1 MΩ, and below 1 MHz the output impedance can arrive to 200 KΩ. Then in total the output impedance of the DCSC is higher than that of the Howland current source circuit (HCSC). (3) The SNR of the DCSC are 85.64 dB and 65 dB in the simulation and actual measurement with 10 KHz, which illustrates that the DCSC effectively eliminates the common mode interference. (4) The maximum load in the DCSC is twice as much as that of the HCSC. Lastly a two-dimensional phantom electrical impedance tomography is well reconstructed with the proposed HCSC. Therefore, the measured performance shows that the DCSC can significantly improve the output impedance, the stability, the maximum load, and the SNR of the measurement system.

Signal Based Mixing Analysis for the magnetohydrodynamic mode reconstruction from homodyne microwave reflectometry

International Nuclear Information System (INIS)

Ejiri, Akira; Sakakibara, Satoru; Kawahata, Kazuo.

1995-03-01

A new method 'Signal Based Mixing Analysis', to extract the components which are coherent to a certain reference signal from a noisy signal, has been developed. The method is applied to homodyne microwave reflectometry to reconstruct the radial structure of a magnetohydrodynamic (MHD) mode in heliotron/torsatron Compact Helical System (CHS) [K. Matsuoka et al. Plasma Phys. Control. Nuclear Fusion Research 1988 Vol. 2, IAEA, Vienna 411 (1989)]. In CHS plasmas, MHD fluctuations measured with magnetic probes show bursts, in which the amplitude and frequency quasi-periodically vary. The signal based mixing analysis uses a set of functions which have the same amplitude and the harmonic frequency as those of the magnetic fluctuations. The product (mixing) of the signal of reflectometer and the functions yields the amplitude and phase of the coherent components. When the plasma density gradually increases, the measuring position moves radially outward. Thus, the radial structure of MHD modes can be obtained by this method. The analysis indicates several peaks and nodes inside the resonance surface of the MHD mode. In addition, the structure does not propagate radially during a burst. (author)

Can Technical Analysis Signals Detect Price Reactions Around Earnings Announcement?: Evidence from Indonesia

OpenAIRE

Dedhy Sulistiawan; Jogiyanto Hartono

2014-01-01

This study examines whether technical analysis signals can detect price reactions before and after earnings announcement dates in Indonesian stock market. Earnings announcements produce reactions, both before and after the announcements. Informed investors may use private information before earnings announcements (Christophe, Ferri and Angel, 2004; Porter, 1992). Using technical analysis signals, this study expects that retail investors (uninformed investors) can detect preannouncements react...

Increasing reliability of defect characterization on sg tubings using a combination of signal processing and expert system

International Nuclear Information System (INIS)

Benoist, B.; David, B.; Pigeon, M.

1989-01-01

An expert system is developed for automatic analysis of eddy current signals provided by the multifrequency control of steam generators tubing. This article describes on one hand the aim and the results of the elimination of pilgrim noise, on the other hand the expert system which uses signal analysis and signal processing in unison

Statistical 21-cm Signal Separation via Gaussian Process Regression Analysis

Science.gov (United States)

Mertens, F. G.; Ghosh, A.; Koopmans, L. V. E.

2018-05-01

Detecting and characterizing the Epoch of Reionization and Cosmic Dawn via the redshifted 21-cm hyperfine line of neutral hydrogen will revolutionize the study of the formation of the first stars, galaxies, black holes and intergalactic gas in the infant Universe. The wealth of information encoded in this signal is, however, buried under foregrounds that are many orders of magnitude brighter. These must be removed accurately and precisely in order to reveal the feeble 21-cm signal. This requires not only the modeling of the Galactic and extra-galactic emission, but also of the often stochastic residuals due to imperfect calibration of the data caused by ionospheric and instrumental distortions. To stochastically model these effects, we introduce a new method based on `Gaussian Process Regression' (GPR) which is able to statistically separate the 21-cm signal from most of the foregrounds and other contaminants. Using simulated LOFAR-EoR data that include strong instrumental mode-mixing, we show that this method is capable of recovering the 21-cm signal power spectrum across the entire range k = 0.07 - 0.3 {h cMpc^{-1}}. The GPR method is most optimal, having minimal and controllable impact on the 21-cm signal, when the foregrounds are correlated on frequency scales ≳ 3 MHz and the rms of the signal has σ21cm ≳ 0.1 σnoise. This signal separation improves the 21-cm power-spectrum sensitivity by a factor ≳ 3 compared to foreground avoidance strategies and enables the sensitivity of current and future 21-cm instruments such as the Square Kilometre Array to be fully exploited.

Analysis of radiometric signal in sedimentating suspension flow in open channel

Directory of Open Access Journals (Sweden)

Zych Marcin

2015-01-01

Full Text Available The article discusses issues related to the estimation of the sedimentating solid particles average flow velocity in an open channel using radiometric methods. Due to the composition of the compound, which formed water and diatomite, received data have a very weak signal to noise ratio. In the process analysis the known determining of the solid phase transportation time delay the classical cross-correlation function is the most reliable method. The use of advanced frequency analysis based on mutual spectral density function and wavelet transform of recorded signals allows a reduction of the noise contribution.

Classification of DNA nucleotides with transverse tunneling currents

Science.gov (United States)

Pedersen, Jonas Nyvold; Boynton, Paul; Ventra, Massimiliano Di; Jauho, Antti-Pekka; Flyvbjerg, Henrik

2016-01-01

It has been theoretically suggested and experimentally demonstrated that fast and low-cost sequencing of DNA, RNA, and peptide molecules might be achieved by passing such molecules between electrodes embedded in a nanochannel. The experimental realization of this scheme faces major challenges, however. In realistic liquid environments, typical currents in tunnelling devices are of the order of picoamps. This corresponds to only six electrons per microsecond, and this number affects the integration time required to do current measurements in real experiments. This limits the speed of sequencing, though current fluctuations due to Brownian motion of the molecule average out during the required integration time. Moreover, data acquisition equipment introduces noise, and electronic filters create correlations in time-series data. We discuss how these effects must be included in the analysis of, e.g., the assignment of specific nucleobases to current signals. As the signals from different molecules overlap, unambiguous classification is impossible with a single measurement. We argue that the assignment of molecules to a signal is a standard pattern classification problem and calculation of the error rates is straightforward. The ideas presented here can be extended to other sequencing approaches of current interest. PMID:27897144

Classification of DNA nucleotides with transverse tunneling currents

Science.gov (United States)

Nyvold Pedersen, Jonas; Boynton, Paul; Di Ventra, Massimiliano; Jauho, Antti-Pekka; Flyvbjerg, Henrik

2017-01-01

It has been theoretically suggested and experimentally demonstrated that fast and low-cost sequencing of DNA, RNA, and peptide molecules might be achieved by passing such molecules between electrodes embedded in a nanochannel. The experimental realization of this scheme faces major challenges, however. In realistic liquid environments, typical currents in tunneling devices are of the order of picoamps. This corresponds to only six electrons per microsecond, and this number affects the integration time required to do current measurements in real experiments. This limits the speed of sequencing, though current fluctuations due to Brownian motion of the molecule average out during the required integration time. Moreover, data acquisition equipment introduces noise, and electronic filters create correlations in time-series data. We discuss how these effects must be included in the analysis of, e.g., the assignment of specific nucleobases to current signals. As the signals from different molecules overlap, unambiguous classification is impossible with a single measurement. We argue that the assignment of molecules to a signal is a standard pattern classification problem and calculation of the error rates is straightforward. The ideas presented here can be extended to other sequencing approaches of current interest.

Fault Diagnosis of Three Phase Induction Motor Using Current Signal, MSAF-Ratio15 and Selected Classifiers

Directory of Open Access Journals (Sweden)

Glowacz A.

2017-12-01

Full Text Available A degradation of metallurgical equipment is normal process depended on time. Some factors such as: operation process, friction, high temperature can accelerate the degradation process of metallurgical equipment. In this paper the authors analyzed three phase induction motors. These motors are common used in the metallurgy industry, for example in conveyor belt. The diagnostics of such motors is essential. An early detection of faults prevents financial loss and downtimes. The authors proposed a technique of fault diagnosis based on recognition of currents. The authors analyzed 4 states of three phase induction motor: healthy three phase induction motor, three phase induction motor with 1 faulty rotor bar, three phase induction motor with 2 faulty rotor bars, three phase induction motor with faulty ring of squirrel-cage. An analysis was carried out for original method of feature extraction called MSAF-RATIO15 (Method of Selection of Amplitudes of Frequencies – Ratio 15% of maximum of amplitude. A classification of feature vectors was performed by Bayes classifier, Linear Discriminant Analysis (LDA and Nearest Neighbour classifier. The proposed technique of fault diagnosis can be used for protection of three phase induction motors and other rotating electrical machines. In the near future the authors will analyze other motors and faults. There is also idea to use thermal, acoustic, electrical, vibration signal together.

Analysis of Muscle Fatigue Progression using Cyclostationary Property of Surface Electromyography Signals.

Science.gov (United States)

Karthick, P A; Venugopal, G; Ramakrishnan, S

2016-01-01

Analysis of neuromuscular fatigue finds various applications ranging from clinical studies to biomechanics. Surface electromyography (sEMG) signals are widely used for these studies due to its non-invasiveness. During cyclic dynamic contractions, these signals are nonstationary and cyclostationary. In recent years, several nonstationary methods have been employed for the muscle fatigue analysis. However, cyclostationary based approach is not well established for the assessment of muscle fatigue. In this work, cyclostationarity associated with the biceps brachii muscle fatigue progression is analyzed using sEMG signals and Spectral Correlation Density (SCD) functions. Signals are recorded from fifty healthy adult volunteers during dynamic contractions under a prescribed protocol. These signals are preprocessed and are divided into three segments, namely, non-fatigue, first muscle discomfort and fatigue zones. Then SCD is estimated using fast Fourier transform accumulation method. Further, Cyclic Frequency Spectral Density (CFSD) is calculated from the SCD spectrum. Two features, namely, cyclic frequency spectral area (CFSA) and cyclic frequency spectral entropy (CFSE) are proposed to study the progression of muscle fatigue. Additionally, degree of cyclostationarity (DCS) is computed to quantify the amount of cyclostationarity present in the signals. Results show that there is a progressive increase in cyclostationary during the progression of muscle fatigue. CFSA shows an increasing trend in muscle fatiguing contraction. However, CFSE shows a decreasing trend. It is observed that when the muscle progresses from non-fatigue to fatigue condition, the mean DCS of fifty subjects increases from 0.016 to 0.99. All the extracted features found to be distinct and statistically significant in the three zones of muscle contraction (p < 0.05). It appears that these SCD features could be useful in the automated analysis of sEMG signals for different neuromuscular conditions.

Design and Analysis of a New Hair Sensor for Multi-Physical Signal Measurement

Directory of Open Access Journals (Sweden)

Bo Yang

2016-07-01

Full Text Available A new hair sensor for multi-physical signal measurements, including acceleration, angular velocity and air flow, is presented in this paper. The entire structure consists of a hair post, a torsional frame and a resonant signal transducer. The hair post is utilized to sense and deliver the physical signals of the acceleration and the air flow rate. The physical signals are converted into frequency signals by the resonant transducer. The structure is optimized through finite element analysis. The simulation results demonstrate that the hair sensor has a frequency of 240 Hz in the first mode for the acceleration or the air flow sense, 3115 Hz in the third and fourth modes for the resonant conversion, and 3467 Hz in the fifth and sixth modes for the angular velocity transformation, respectively. All the above frequencies present in a reasonable modal distribution and are separated from interference modes. The input-output analysis of the new hair sensor demonstrates that the scale factor of the acceleration is 12.35 Hz/g, the scale factor of the angular velocity is 0.404 nm/deg/s and the sensitivity of the air flow is 1.075 Hz/(m/s2, which verifies the multifunction sensitive characteristics of the hair sensor. Besides, the structural optimization of the hair post is used to improve the sensitivity of the air flow rate and the acceleration. The analysis results illustrate that the hollow circular hair post can increase the sensitivity of the air flow and the II-shape hair post can increase the sensitivity of the acceleration. Moreover, the thermal analysis confirms the scheme of the frequency difference for the resonant transducer can prominently eliminate the temperature influences on the measurement accuracy. The air flow analysis indicates that the surface area increase of hair post is significantly beneficial for the efficiency improvement of the signal transmission. In summary, the structure of the new hair sensor is proved to be feasible by

DEAP: A Database for Emotion Analysis Using Physiological Signals

NARCIS (Netherlands)

Koelstra, Sander; Mühl, C.; Soleymani, Mohammad; Lee, Jung Seok; Yazdani, Ashkan; Ebrahimi, Touradj; Pun, Thierry; Nijholt, Antinus; Patras, Ioannis

2012-01-01

We present a multimodal dataset for the analysis of human affective states. The electroencephalogram (EEG) and peripheral physiological signals of 32 participants were recorded as each watched 40 one-minute long excerpts of music videos. Participants rated each video in terms of the levels of

Advancement of the Eddy Current Testing using neural network technique. Development of 3-D finite element analysis sytem of elctro-magnetic field

International Nuclear Information System (INIS)

Sakai, Takayuki; Soneda, Naoki

1994-01-01

In PWR plants, an automatic recognition system of Eddy Current Testing (ECT) signals of steam generator tubes are strongly required to reduce inspectors' labor and to improve the reliability of the testing. Although the neural-network technique is very promising for this kind of system, it is necessary to evaluate its applicability to ECT signals throughly, where a database of the relationship of the defects and ECT signals plays a very important role. In this paper, a three dimensional finite element analysis system of electromagnetic field, which consists of an FEM code and pre/post processor, is developed to generate a database of ECT signals. T-Ω method and the edge element are employed in the FEM code to reduce the required computer memory. The code is verified through some comparisons with experiments and other calculations. (author)

Analysis and Simulation of Multi-target Echo Signals from a Phased Array Radar

OpenAIRE

Jia Zhen; Zhou Rui

2017-01-01

The construction of digital radar simulation systems has been a research hotspot of the radar field. This paper focuses on theoretical analysis and simulation of multi-target echo signals produced in a phased array radar system, and constructs an array antenna element and a signal generation environment. The antenna element is able to simulate planar arrays and optimizes these arrays by adding window functions. And the signal environment can model and simulate radar transmission signals, rada...

Diagnostic of corrosion defects in steam generator tubes using advanced signal processing from Eddy current testing

International Nuclear Information System (INIS)

Formigoni, Andre L.; Lopez, Luiz A.N.M.; Ting, Daniel K.S.

2009-01-01

Recently, the Brazilian Angra I PWR nuclear power plant went into a programmed shutdown for substitution of its Steam Generator (SG) which life was shortened due to stress corrosion in its tubes. The total cost of investment were around R$724 million. The signals generated during an Eddy-current Testing (ECT) inspection in SG tubes of nuclear plant allows for the localization and dimensioning of defects in the tubes. The defects related with corrosion generate complex signals that are difficult to analyze and are the most common cause in SG replacement in nuclear power plants around the world. The objective of this paper is the development of a methodology that allows for the characterization of corrosion signals by ECT inspections applied in the heat exchangers tubes of SG of a nuclear power plant. In this present work, the aim is to investigate distributed type defects by inducing controlled corrosion in sample tubes of different materials The ECT signals obtained from these samples tubes with corrosion implanted, will be analyzed using Zetec ECT equipment, the MIZ-17ET and its probes. The data acquisition will use a NI PC A/D CARD 700 card and the LabVIEW program. Subsequently, we will apply mathematical tools for signal processing like time windowed Fast Fourier transforms and Wavelets transforms, in MATLAB platform, which will allow effectiveness to remove the noises and to extract representative characteristics for the defect being analyzed. Previously obtained results as well as the proposal for the future work will be presented. (author)

Robust Parameter and Signal Estimation in Induction Motors

DEFF Research Database (Denmark)

Børsting, H.

This thesis deals with theories and methods for robust parameter and signal estimation in induction motors. The project originates in industrial interests concerning sensor-less control of electrical drives. During the work, some general problems concerning estimation of signals and parameters...... in nonlinear systems, have been exposed. The main objectives of this project are: - analysis and application of theories and methods for robust estimation of parameters in a model structure, obtained from knowledge of the physics of the induction motor. - analysis and application of theories and methods...... for robust estimation of the rotor speed and driving torque of the induction motor based only on measurements of stator voltages and currents. Only contimuous-time models have been used, which means that physical related signals and parameters are estimated directly and not indirectly by some discrete...

SVM-Based Spectral Analysis for Heart Rate from Multi-Channel WPPG Sensor Signals.

Science.gov (United States)

Xiong, Jiping; Cai, Lisang; Wang, Fei; He, Xiaowei

2017-03-03

Although wrist-type photoplethysmographic (hereafter referred to as WPPG) sensor signals can measure heart rate quite conveniently, the subjects' hand movements can cause strong motion artifacts, and then the motion artifacts will heavily contaminate WPPG signals. Hence, it is challenging for us to accurately estimate heart rate from WPPG signals during intense physical activities. The WWPG method has attracted more attention thanks to the popularity of wrist-worn wearable devices. In this paper, a mixed approach called Mix-SVM is proposed, it can use multi-channel WPPG sensor signals and simultaneous acceleration signals to measurement heart rate. Firstly, we combine the principle component analysis and adaptive filter to remove a part of the motion artifacts. Due to the strong relativity between motion artifacts and acceleration signals, the further denoising problem is regarded as a sparse signals reconstruction problem. Then, we use a spectrum subtraction method to eliminate motion artifacts effectively. Finally, the spectral peak corresponding to heart rate is sought by an SVM-based spectral analysis method. Through the public PPG database in the 2015 IEEE Signal Processing Cup, we acquire the experimental results, i.e., the average absolute error was 1.01 beat per minute, and the Pearson correlation was 0.9972. These results also confirm that the proposed Mix-SVM approach has potential for multi-channel WPPG-based heart rate estimation in the presence of intense physical exercise.

Unveiling Hidden Dynamics of Hippo Signalling: A Systems Analysis

Directory of Open Access Journals (Sweden)

Sung-Young Shin

2016-08-01

Full Text Available The Hippo signalling pathway has recently emerged as an important regulator of cell apoptosis and proliferation with significant implications in human diseases. In mammals, the pathway contains the core kinases MST1/2, which phosphorylate and activate LATS1/2 kinases. The pro-apoptotic function of the MST/LATS signalling axis was previously linked to the Akt and ERK MAPK pathways, demonstrating that the Hippo pathway does not act alone but crosstalks with other signalling pathways to coordinate network dynamics and cellular outcomes. These crosstalks were characterised by a multitude of complex regulatory mechanisms involving competitive protein-protein interactions and phosphorylation mediated feedback loops. However, how these different mechanisms interplay in different cellular contexts to drive the context-specific network dynamics of Hippo-ERK signalling remains elusive. Using mathematical modelling and computational analysis, we uncovered that the Hippo-ERK network can generate highly diverse dynamical profiles that can be clustered into distinct dose-response patterns. For each pattern, we offered mechanistic explanation that defines when and how the observed phenomenon can arise. We demonstrated that Akt displays opposing, dose-dependent functions towards ERK, which are mediated by the balance between the Raf-1/MST2 protein interaction module and the LATS1 mediated feedback regulation. Moreover, Ras displays a multi-functional role and drives biphasic responses of both MST2 and ERK activities; which are critically governed by the competitive protein interaction between MST2 and Raf-1. Our study represents the first in-depth and systematic analysis of the Hippo-ERK network dynamics and provides a concrete foundation for future studies.

Sensitivity analysis of intracellular signaling pathway kinetics predicts targets for stem cell fate control.

Directory of Open Access Journals (Sweden)

Alborz Mahdavi

2007-07-01

Full Text Available Directing stem cell fate requires knowledge of how signaling networks integrate temporally and spatially segregated stimuli. We developed and validated a computational model of signal transducer and activator of transcription-3 (Stat3 pathway kinetics, a signaling network involved in embryonic stem cell (ESC self-renewal. Our analysis identified novel pathway responses; for example, overexpression of the receptor glycoprotein-130 results in reduced pathway activation and increased ESC differentiation. We used a systematic in silico screen to identify novel targets and protein interactions involved in Stat3 activation. Our analysis demonstrates that signaling activation and desensitization (the inability to respond to ligand restimulation is regulated by balancing the activation state of a distributed set of parameters including nuclear export of Stat3, nuclear phosphatase activity, inhibition by suppressor of cytokine signaling, and receptor trafficking. This knowledge was used to devise a temporally modulated ligand delivery strategy that maximizes signaling activation and leads to enhanced ESC self-renewal.

Generalized sample entropy analysis for traffic signals based on similarity measure

Science.gov (United States)

Shang, Du; Xu, Mengjia; Shang, Pengjian

2017-05-01

Sample entropy is a prevailing method used to quantify the complexity of a time series. In this paper a modified method of generalized sample entropy and surrogate data analysis is proposed as a new measure to assess the complexity of a complex dynamical system such as traffic signals. The method based on similarity distance presents a different way of signals patterns match showing distinct behaviors of complexity. Simulations are conducted over synthetic data and traffic signals for providing the comparative study, which is provided to show the power of the new method. Compared with previous sample entropy and surrogate data analysis, the new method has two main advantages. The first one is that it overcomes the limitation about the relationship between the dimension parameter and the length of series. The second one is that the modified sample entropy functions can be used to quantitatively distinguish time series from different complex systems by the similar measure.

Non-destructive testing of full-length bonded rock bolts based on HHT signal analysis

Science.gov (United States)

Shi, Z. M.; Liu, L.; Peng, M.; Liu, C. C.; Tao, F. J.; Liu, C. S.

2018-04-01

Full-length bonded rock bolts are commonly used in mining, tunneling and slope engineering because of their simple design and resistance to corrosion. However, the length of a rock bolt and grouting quality do not often meet the required design standards in practice because of the concealment and complexity of bolt construction. Non-destructive testing is preferred when testing a rock bolt's quality because of the convenience, low cost and wide detection range. In this paper, a signal analysis method for the non-destructive sound wave testing of full-length bonded rock bolts is presented, which is based on the Hilbert-Huang transform (HHT). First, we introduce the HHT analysis method to calculate the bolt length and identify defect locations based on sound wave reflection test signals, which includes decomposing the test signal via empirical mode decomposition (EMD), selecting the intrinsic mode functions (IMF) using the Pearson Correlation Index (PCI) and calculating the instantaneous phase and frequency via the Hilbert transform (HT). Second, six model tests are conducted using different grouting defects and bolt protruding lengths to verify the effectiveness of the HHT analysis method. Lastly, the influence of the bolt protruding length on the test signal, identification of multiple reflections from defects, bolt end and protruding end, and mode mixing from EMD are discussed. The HHT analysis method can identify the bolt length and grouting defect locations from signals that contain noise at multiple reflected interfaces. The reflection from the long protruding end creates an irregular test signal with many frequency peaks on the spectrum. The reflections from defects barely change the original signal because they are low energy, which cannot be adequately resolved using existing methods. The HHT analysis method can identify reflections from the long protruding end of the bolt and multiple reflections from grouting defects based on mutations in the instantaneous

Continuous EEG signal analysis for asynchronous BCI application.

Science.gov (United States)

Hsu, Wei-Yen

2011-08-01

In this study, we propose a two-stage recognition system for continuous analysis of electroencephalogram (EEG) signals. An independent component analysis (ICA) and correlation coefficient are used to automatically eliminate the electrooculography (EOG) artifacts. Based on the continuous wavelet transform (CWT) and Student's two-sample t-statistics, active segment selection then detects the location of active segment in the time-frequency domain. Next, multiresolution fractal feature vectors (MFFVs) are extracted with the proposed modified fractal dimension from wavelet data. Finally, the support vector machine (SVM) is adopted for the robust classification of MFFVs. The EEG signals are continuously analyzed in 1-s segments, and every 0.5 second moves forward to simulate asynchronous BCI works in the two-stage recognition architecture. The segment is first recognized as lifted or not in the first stage, and then is classified as left or right finger lifting at stage two if the segment is recognized as lifting in the first stage. Several statistical analyses are used to evaluate the performance of the proposed system. The results indicate that it is a promising system in the applications of asynchronous BCI work.

Comparison of HF radar measurements with Eulerian and Lagrangian surface currents

Science.gov (United States)

Röhrs, Johannes; Sperrevik, Ann Kristin; Christensen, Kai Håkon; Broström, Göran; Breivik, Øyvind

2015-05-01

High-frequency (HF) radar-derived ocean currents are compared with in situ measurements to conclude if the radar observations include effects of surface waves that are of second order in the wave amplitude. Eulerian current measurements from a high-resolution acoustic Doppler current profiler and Lagrangian measurements from surface drifters are used as references. Directional wave spectra are obtained from a combination of pressure sensor data and a wave model. Our analysis shows that the wave-induced Stokes drift is not included in the HF radar-derived currents, that is, HF radars measure the Eulerian current. A disputed nonlinear correction to the phase velocity of surface gravity waves, which may affect HF radar signals, has a magnitude of about half the Stokes drift at the surface. In our case, this contribution by nonlinear dispersion would be smaller than the accuracy of the HF radar currents, hence no conclusion can be made. Finally, the analysis confirms that the HF radar data represent an exponentially weighted vertical average where the decay scale is proportional to the wavelength of the transmitted signal.

Current signal of silicon detectors facing charged particles and heavy ions; Reponse en courant des detecteurs silicium aux particules chargees et aux ions lourds

Energy Technology Data Exchange (ETDEWEB)

Hamrita, H

2005-07-01

This work consisted in collecting and studying for the first time the shapes of current signals obtained from charged particles or heavy ions produced by silicon detectors. The document is divided into two main parts. The first consisted in reducing the experimental data obtained with charged particles as well as with heavy ions. These experiments were performed at the Orsay Tandem and at GANIL using LISE. These two experiments enabled us to create a data base formed of current signals with various shapes and various times of collection. The second part consisted in carrying out a simulation of the current signals obtained from the various ions. To obtain this simulation we propose a new model describing the formation of the signal. We used the data base of the signals obtained in experiments in order to constrain the three parameters of our model. In this model, the charge carriers created are regarded as dipoles and their density is related to the dielectric polarization in the silicon detector. This phenomenon induces an increase in permittivity throughout the range of the incident ion and consequently the electric field between the electrodes of the detector is decreased inside the trace. We coupled with this phenomenon a dissociation and extraction mode of the charge carriers so that they can be moved in the electric field. (author)

Analysis Spectrum of ECG Signal and QRS Detection during Running on Treadmill

Science.gov (United States)

Agung Suhendra, M.; Ilham R., M.; Simbolon, Artha I.; Faizal A., M.; Munandar, A.

2018-03-01

The heart is an important organ in our metabolism in which it controls circulatory and oxygen. The heart exercise is needed one of them using the treadmill to prevent health. To analysis, it using electrocardiograph (ECG) to investigating and diagnosing anomalies of the heart. In this paper, we would like to analysis ECG signals during running on the treadmill with kinds of speeds. There are two analysis ECG signals i.e. QRS detection and power spectrum density (PSD). The result of PSD showed that subject 3 has highly for all subject and the result of QRS detection using pan Tomkins algorithm that a percentage of failed detection is an approaching to 0 % for all subject.

Methods for the Analysis of Protein Phosphorylation-Mediated Cellular Signaling Networks

Science.gov (United States)

White, Forest M.; Wolf-Yadlin, Alejandro

2016-06-01

Protein phosphorylation-mediated cellular signaling networks regulate almost all aspects of cell biology, including the responses to cellular stimulation and environmental alterations. These networks are highly complex and comprise hundreds of proteins and potentially thousands of phosphorylation sites. Multiple analytical methods have been developed over the past several decades to identify proteins and protein phosphorylation sites regulating cellular signaling, and to quantify the dynamic response of these sites to different cellular stimulation. Here we provide an overview of these methods, including the fundamental principles governing each method, their relative strengths and weaknesses, and some examples of how each method has been applied to the analysis of complex signaling networks. When applied correctly, each of these techniques can provide insight into the topology, dynamics, and regulation of protein phosphorylation signaling networks.

Hall Sensor Output Signal Fault-Detection & Safety Implementation Logic

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Lee SangHun

2016-01-01

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

Dynamic strain analysis of structures employing digital signal processing, storage and display

Energy Technology Data Exchange (ETDEWEB)

Patwardhan, P K; Misra, V M; Kumar, Surendra

1975-01-01

A multi-channel digital technique has been adopted for analysing wave patterns of stresses and strains in structures, particularly under dynamic conditions. This technique provides adequate signal to noise discrimination and high sensitivity for very small (few milli-volts) and slow varying signals (few Hz to 100 Hz.), and A-D conversion accompined by live display during the course of data gathering and computer compatible output. This system also provides fast response because of inherent 50 MHz digitising speed and a large dynamic range of 1024 discrete signal steps. The signals can be suitably fed to the A-D converter (50 MHz) or can be analysed employing frequency modulation techniques and time mode operation of the analyser. The data can be gathered in the field on cassette tapes and replayed in the laboratory for detailed analysis. This technique would provide a versatile system for dynamic analysis of structures under varying conditions. e.g. structures in nuclear power systems, such as testing of end fittings, calandria, vibration testing and measurements exploying pressure transducers.

Dynamic strain analysis of structures employing digital signal processing, storage and display

International Nuclear Information System (INIS)

Patwardhan, P.K.; Misra, V.M.; Kumar, Surendra

1975-01-01

A multi-channel digital technique has been adopted for analysing wave patterns of stresses and strains in structures, particularly under dynamic conditions. This technique provides adequate signal to noise discrimination and high sensitivity for very small (few milli-volts) and slow varying signals (few Hz to 100 Hz.), A-D conversion accompined by live display during the course of data gathering and computer compatible output. This system also provides fast response because of inherent 50 MHz digitising speed and a large dynamic range of 1024 discrete signal steps. The signals can be suitably fed to the A-D converter (50 MHz) or can be analysed employing frequency modulation techniques and time mode operation of the analyser. The data can be gathered in the field on cassette tapes and replayed in the laboratory for detailed analysis. This technique would provide a versatile system for dynamic analysis of structures under varying conditions. e.g. structures in nuclear power systems, such as testing of end fittings, calandria, vibration testing and measurements exploying pressure transducers. (author)

PROTECTION OF HOUSEHOLD APPLIANCES INDUCTION MOTORS AGAINST OVERCURRENT TAKING INTO ACCOUNT NONLINEAR DISTORTION OF PHASE CURRENT

Directory of Open Access Journals (Sweden)

A.G. Sereda

2015-06-01

Full Text Available Purpose. Theoretical justification and engineering of induction motors heat protection method from overload currents taking into account nonlinear distortion of the phase current and implementation as a microprocessor device functioning algorithm. Methodology. To solve the problem used the theory of the representing complex harmonic oscillations analog signals expansion into the oscillation spectrum forming elementary harmonic components in order to compare their properties by applying the theory of discrete signals and systems, as well as methods of spectral analysis and discrete signals filtering. The harmonic analysis versatility is that any periodic signal may be synthesized from harmonic oscillation of certain amplitude, frequency and initial phase. A mathematical model for determining the phase current harmonic content of power supply networks with isolated neutral and non-linear loads types and, as a consequence, the distortion of sinusoidal phase current change is developed by multiplying the analog current in time dependency on the grate delta-function with different sampling intervals, in which the use of simple and widely used in relay protection units, in particular electronic overcurrent relays, mathematical operations of integration squares instantaneous current allows the most in harmony with the mathematical tools to build other network protection types. Findings. The necessity to increase the sensitivity of the induction motors heat protection from overload currents taking into account nonlinear distortion of the phase currents is proved. By nonlinear distortion harmonic analysis of the phase currents the motor protection reliability increasing provided by taking into account the higher harmonic components of the phase currents, which causes to additional losses and heating of the stator winding. It uses the simplest and widely used in protective relaying mathematical apparatus determining of most significant higher harmonics

Design and prototyping of a wristband-type wireless photoplethysmographic device for heart rate variability signal analysis.

Science.gov (United States)

Ghamari, M; Soltanpur, C; Cabrera, S; Romero, R; Martinek, R; Nazeran, H

2016-08-01

Heart Rate Variability (HRV) signal analysis provides a quantitative marker of the Autonomic Nervous System (ANS) function. A wristband-type wireless photoplethysmographic (PPG) device was custom-designed to collect and analyze the arterial pulse in the wrist. The proposed device is comprised of an optical sensor to monitor arterial pulse, a signal conditioning unit to filter and amplify the analog PPG signal, a microcontroller to digitize the analog PPG signal, and a Bluetooth module to transfer the data to a smart device. This paper proposes a novel model to represent the PPG signal as the summation of two Gaussian functions. The paper concludes with a verification procedure for HRV signal analysis during sedentary activities.

SVM-Based Spectral Analysis for Heart Rate from Multi-Channel WPPG Sensor Signals

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Jiping Xiong

2017-03-01

Full Text Available Although wrist-type photoplethysmographic (hereafter referred to as WPPG sensor signals can measure heart rate quite conveniently, the subjects’ hand movements can cause strong motion artifacts, and then the motion artifacts will heavily contaminate WPPG signals. Hence, it is challenging for us to accurately estimate heart rate from WPPG signals during intense physical activities. The WWPG method has attracted more attention thanks to the popularity of wrist-worn wearable devices. In this paper, a mixed approach called Mix-SVM is proposed, it can use multi-channel WPPG sensor signals and simultaneous acceleration signals to measurement heart rate. Firstly, we combine the principle component analysis and adaptive filter to remove a part of the motion artifacts. Due to the strong relativity between motion artifacts and acceleration signals, the further denoising problem is regarded as a sparse signals reconstruction problem. Then, we use a spectrum subtraction method to eliminate motion artifacts effectively. Finally, the spectral peak corresponding to heart rate is sought by an SVM-based spectral analysis method. Through the public PPG database in the 2015 IEEE Signal Processing Cup, we acquire the experimental results, i.e., the average absolute error was 1.01 beat per minute, and the Pearson correlation was 0.9972. These results also confirm that the proposed Mix-SVM approach has potential for multi-channel WPPG-based heart rate estimation in the presence of intense physical exercise.

Multiple-Fault Detection Methodology Based on Vibration and Current Analysis Applied to Bearings in Induction Motors and Gearboxes on the Kinematic Chain

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Juan Jose Saucedo-Dorantes

2016-01-01

Full Text Available Gearboxes and induction motors are important components in industrial applications and their monitoring condition is critical in the industrial sector so as to reduce costs and maintenance downtimes. There are several techniques associated with the fault diagnosis in rotating machinery; however, vibration and stator currents analysis are commonly used due to their proven reliability. Indeed, vibration and current analysis provide fault condition information by means of the fault-related spectral component identification. This work presents a methodology based on vibration and current analysis for the diagnosis of wear in a gearbox and the detection of bearing defect in an induction motor both linked to the same kinematic chain; besides, the location of the fault-related components for analysis is supported by the corresponding theoretical models. The theoretical models are based on calculation of characteristic gearbox and bearings fault frequencies, in order to locate the spectral components of the faults. In this work, the influence of vibrations over the system is observed by performing motor current signal analysis to detect the presence of faults. The obtained results show the feasibility of detecting multiple faults in a kinematic chain, making the proposed methodology suitable to be used in the application of industrial machinery diagnosis.

EMD-Based Symbolic Dynamic Analysis for the Recognition of Human and Nonhuman Pyroelectric Infrared Signals

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Jiaduo Zhao

2016-01-01

Full Text Available In this paper, we propose an effective human and nonhuman pyroelectric infrared (PIR signal recognition method to reduce PIR detector false alarms. First, using the mathematical model of the PIR detector, we analyze the physical characteristics of the human and nonhuman PIR signals; second, based on the analysis results, we propose an empirical mode decomposition (EMD-based symbolic dynamic analysis method for the recognition of human and nonhuman PIR signals. In the proposed method, first, we extract the detailed features of a PIR signal into five symbol sequences using an EMD-based symbolization method, then, we generate five feature descriptors for each PIR signal through constructing five probabilistic finite state automata with the symbol sequences. Finally, we use a weighted voting classification strategy to classify the PIR signals with their feature descriptors. Comparative experiments show that the proposed method can effectively classify the human and nonhuman PIR signals and reduce PIR detector’s false alarms.

EMD-Based Symbolic Dynamic Analysis for the Recognition of Human and Nonhuman Pyroelectric Infrared Signals.

Science.gov (United States)

Zhao, Jiaduo; Gong, Weiguo; Tang, Yuzhen; Li, Weihong

2016-01-20

In this paper, we propose an effective human and nonhuman pyroelectric infrared (PIR) signal recognition method to reduce PIR detector false alarms. First, using the mathematical model of the PIR detector, we analyze the physical characteristics of the human and nonhuman PIR signals; second, based on the analysis results, we propose an empirical mode decomposition (EMD)-based symbolic dynamic analysis method for the recognition of human and nonhuman PIR signals. In the proposed method, first, we extract the detailed features of a PIR signal into five symbol sequences using an EMD-based symbolization method, then, we generate five feature descriptors for each PIR signal through constructing five probabilistic finite state automata with the symbol sequences. Finally, we use a weighted voting classification strategy to classify the PIR signals with their feature descriptors. Comparative experiments show that the proposed method can effectively classify the human and nonhuman PIR signals and reduce PIR detector's false alarms.

Purinergic signalling: from discovery to current developments.

Science.gov (United States)

Burnstock, Geoffrey

2014-01-01

This lecture is about the history of the purinergic signalling concept. It begins with reference to the paper by Paton & Vane published in 1963, which identified non-cholinergic relaxation in response to vagal nerve stimulation in several species, although they suggested that it might be due to sympathetic adrenergic nerves in the vagal nerve trunk. Using the sucrose gap technique for simultaneous mechanical and electrical recordings in smooth muscle (developed while in Feldberg's department in the National Institute for Medical Research) of the guinea-pig taenia coli preparation (learned when working in Edith Bülbring's smooth muscle laboratory in Oxford Pharmacology), we showed that the hyperpolarizations recorded in the presence of antagonists to the classical autonomic neurotransmitters, acetylcholine and noradrenaline, were inhibitory junction potentials in response to non-adrenergic, non-cholinergic neurotransmission, mediated by intrinsic enteric nerves controlled by vagal and sacral parasympathetic nerves. We then showed that ATP satisfied the criteria needed to identify a neurotransmitter released by these nerves. Subsequently, it was shown that ATP is a cotransmitter in all nerves in the peripheral and central nervous systems. The receptors for purines and pyrimidines were cloned and characterized in the early 1990 s, and immunostaining showed that most non-neuronal cells as well as nerve cells expressed these receptors. The physiology and pathophysiology of purinergic signalling is discussed.

Orexin/Hypocretin Signaling.

Science.gov (United States)

Kukkonen, Jyrki P

Orexin/hypocretin peptide (orexin-A and orexin-B) signaling is believed to take place via the two G-protein-coupled receptors (GPCRs), named OX 1 and OX 2 orexin receptors, as described in the previous chapters. Signaling of orexin peptides has been investigated in diverse endogenously orexin receptor-expressing cells - mainly neurons but also other types of cells - and in recombinant cells expressing the receptors in a heterologous manner. Findings in the different systems are partially convergent but also indicate cellular background-specific signaling. The general picture suggests an inherently high degree of diversity in orexin receptor signaling.In the current chapter, I present orexin signaling on the cellular and molecular levels. Discussion of the connection to (potential) physiological orexin responses is only brief since these are in focus of other chapters in this book. The same goes for the post-synaptic signaling mechanisms, which are dealt with in Burdakov: Postsynaptic actions of orexin. The current chapter is organized according to the tissue type, starting from the central nervous system. Finally, receptor signaling pathways are discussed across tissues, cell types, and even species.

Investigation of mental fatigue through EEG signal processing based on nonlinear analysis: Symbolic dynamics

International Nuclear Information System (INIS)

Azarnoosh, Mahdi; Motie Nasrabadi, Ali; Mohammadi, Mohammad Reza; Firoozabadi, Mohammad

2011-01-01

Highlights: Mental fatigue indices’ variation discussed during simple long-term attentive task. Symbolic dynamics of reaction time and EEG signal determine mental state variation. Nonlinear quantifiers such as entropy can display chaotic behaviors of the brain. Frontal and central lobes of the brain are effective in attention investigations. Mental fatigue causes a reduction in the complexity of the brain’s activity. Abstract: To investigate nonlinear analysis of attention physiological indices this study used a simple repetitive attentive task in four consecutive trials that resulted in mental fatigue. Traditional performance indices, such as reaction time, error responses, and EEG signals, were simultaneously recorded to evaluate differences between the trials. Performance indices analysis demonstrated that a selected task leads to mental fatigue. In addition, the study aimed to find a method to determine mental fatigue based on nonlinear analysis of EEG signals. Symbolic dynamics was selected as a qualitative method used to extract some quantitative qualifiers such as entropy. This method was executed on the reaction time of responses, and EEG signals to distinguish mental states. The results revealed that nonlinear analysis of reaction time, and EEG signals of the frontal and central lobes of the brain could differentiate between attention, and occurrence of mental fatigue in trials. In addition, the trend of entropy variation displayed a reduction in the complexity of mental activity as fatigue occurred.

Meta-analysis of melanin-concentrating hormone signaling-deficient mice on behavioral and metabolic phenotypes.

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Kenkichi Takase

Full Text Available The demand for meta-analyses in basic biomedical research has been increasing because the phenotyping of genetically modified mice does not always produce consistent results. Melanin-concentrating hormone (MCH has been reported to be involved in a variety of behaviors that include feeding, body-weight regulation, anxiety, sleep, and reward behavior. However, the reported behavioral and metabolic characteristics of MCH signaling-deficient mice, such as MCH-deficient mice and MCH receptor 1 (MCHR1-deficient mice, are not consistent with each other. In the present study, we performed a meta-analysis of the published data related to MCH-deficient and MCHR1-deficient mice to obtain robust conclusions about the role of MCH signaling. Overall, the meta-analysis revealed that the deletion of MCH signaling enhanced wakefulness, locomotor activity, aggression, and male sexual behavior and that MCH signaling deficiency suppressed non-REM sleep, anxiety, responses to novelty, startle responses, and conditioned place preferences. In contrast to the acute orexigenic effect of MCH, MCH signaling deficiency significantly increased food intake. Overall, the meta-analysis also revealed that the deletion of MCH signaling suppressed the body weight, fat mass, and plasma leptin, while MCH signaling deficiency increased the body temperature, oxygen consumption, heart rate, and mean arterial pressure. The lean phenotype of the MCH signaling-deficient mice was also confirmed in separate meta-analyses that were specific to sex and background strain (i.e., C57BL/6 and 129Sv. MCH signaling deficiency caused a weak anxiolytic effect as assessed with the elevated plus maze and the open field test but also caused a weak anxiogenic effect as assessed with the emergence test. MCH signaling-deficient mice also exhibited increased plasma corticosterone under non-stressed conditions, which suggests enhanced activity of the hypothalamic-pituitary-adrenal axis. To the best of our

Characterizing volumetric discontinuities present in NPP heat exchangers with EASY: an eddy current data analysis system

Energy Technology Data Exchange (ETDEWEB)

Alencar, Donizete A.; Silva Junior, Silverio F., E-mail: daa@cdtn.b, E-mail: silvasf@cdtn.b [Centro de Desenvolvimento da Tecnologia Nuclear (CDTN/CNEN-MG), Belo Horizonte, MG (Brazil)

2011-07-01

Eddy current is a very important NDT inspection method widely used to perform integrity evaluation of tubes installed in heat exchangers. For nuclear power plants, a classical example is the remote inspection of steam generators and condensers, as well as other ordinary auxiliary equipment. Data evaluation can be performed by means of precise phase and amplitude measurements of complex impedance signals, represented as Lissajous figures plotted on the screen of the inspection systems. This paper presents the software EASY, a computer assisted analysis system developed at CDTN to help the characterization of volumetric discontinuities present in heat exchangers tubes. Data to be analyzed are obtained from commercial eddy current equipment data file, such as ECT MAD8D. Main advantage of that system is its portability and easy use, since it can be executed in ordinary PC, under Microsoft Windows operating system. (author)

Characterizing volumetric discontinuities present in NPP heat exchangers with EASY: an eddy current data analysis system

International Nuclear Information System (INIS)

Alencar, Donizete A.; Silva Junior, Silverio F.

2011-01-01

Eddy current is a very important NDT inspection method widely used to perform integrity evaluation of tubes installed in heat exchangers. For nuclear power plants, a classical example is the remote inspection of steam generators and condensers, as well as other ordinary auxiliary equipment. Data evaluation can be performed by means of precise phase and amplitude measurements of complex impedance signals, represented as Lissajous figures plotted on the screen of the inspection systems. This paper presents the software EASY, a computer assisted analysis system developed at CDTN to help the characterization of volumetric discontinuities present in heat exchangers tubes. Data to be analyzed are obtained from commercial eddy current equipment data file, such as ECT MAD8D. Main advantage of that system is its portability and easy use, since it can be executed in ordinary PC, under Microsoft Windows operating system. (author)

High-Selectivity Filter Banks for Spectral Analysis of Music Signals

Directory of Open Access Journals (Sweden)

Luiz W. P. Biscainho

2007-01-01

Full Text Available This paper approaches, under a unified framework, several algorithms for the spectral analysis of musical signals. Such algorithms include the fast Fourier transform (FFT, the fast filter bank (FFB, the constant-Q transform (CQT, and the bounded-Q transform (BQT, previously known from the associated literature. Two new methods are then introduced, namely, the constant-Q fast filter bank (CQFFB and the bounded-Q fast filter bank (BQFFB, combining the positive characteristics of the previously mentioned algorithms. The provided analyses indicate that the proposed BQFFB achieves an excellent compromise between the reduced computational effort of the FFT, the high selectivity of each output channel of the FFB, and the efficient distribution of frequency channels associated to the CQT and BQT methods. Examples are included to illustrate the performances of these methods in the spectral analysis of music signals.

Eddy current analysis by BEM utilizing loop electric and surface magnetic currents as unknowns

International Nuclear Information System (INIS)

Ishibashi, Kazuhisa

2002-01-01

The surface integral equations whose unknowns are the surface electric and magnetic currents are widely used in eddy current analysis. However, when the skin depth is thick, computational error is increased especially in obtaining electromagnetic fields near the edge of the conductor. In order to obtain the electromagnetic field accurately, we propose an approach to solve surface integral equations utilizing loop electric and surface magnetic currents as unknowns. (Author)

Reactive oxygen species signaling and stomatal movement: Current updates and future perspectives

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Rachana Singh

2017-04-01

Full Text Available Reactive oxygen species (ROS, a by-product of aerobic metabolism were initially studied in context to their damaging effect but recent decades witnessed significant advancements in understanding the role of ROS as signaling molecules. Contrary to earlier views, it is becoming evident that ROS production is not necessarily a symptom of cellular dysfunction but it might represent a necessary signal in adjusting the cellular machinery according to the altered conditions. Stomatal movement is controlled by multifaceted signaling network in response to endogenous and environmental signals. Furthermore, the stomatal aperture is regulated by a coordinated action of signaling proteins, ROS-generating enzymes, and downstream executors like transporters, ion pumps, plasma membrane channels, which control the turgor pressure of the guard cell. The earliest hallmarks of stomatal closure are ROS accumulation in the apoplast and chloroplasts and thereafter, there is a successive increase in cytoplasmic Ca2+ level which rules the multiple kinases activity that in turn regulates the activity of ROS-generating enzymes and various ion channels. In addition, ROS also regulate the action of multiple proteins directly by oxidative post translational modifications to adjust guard cell signaling. Notwithstanding, an active progress has been made with ROS signaling mechanism but the regulatory action for ROS signaling processes in stomatal movement is still fragmentary. Therefore, keeping in view the above facts, in this mini review the basic concepts and role of ROS signaling in the stomatal movement have been presented comprehensively along with recent highlights.

Combined analysis of cortical (EEG) and nerve stump signals improves robotic hand control.

Science.gov (United States)

Tombini, Mario; Rigosa, Jacopo; Zappasodi, Filippo; Porcaro, Camillo; Citi, Luca; Carpaneto, Jacopo; Rossini, Paolo Maria; Micera, Silvestro

2012-01-01

Interfacing an amputee's upper-extremity stump nerves to control a robotic hand requires training of the individual and algorithms to process interactions between cortical and peripheral signals. To evaluate for the first time whether EEG-driven analysis of peripheral neural signals as an amputee practices could improve the classification of motor commands. Four thin-film longitudinal intrafascicular electrodes (tf-LIFEs-4) were implanted in the median and ulnar nerves of the stump in the distal upper arm for 4 weeks. Artificial intelligence classifiers were implemented to analyze LIFE signals recorded while the participant tried to perform 3 different hand and finger movements as pictures representing these tasks were randomly presented on a screen. In the final week, the participant was trained to perform the same movements with a robotic hand prosthesis through modulation of tf-LIFE-4 signals. To improve the classification performance, an event-related desynchronization/synchronization (ERD/ERS) procedure was applied to EEG data to identify the exact timing of each motor command. Real-time control of neural (motor) output was achieved by the participant. By focusing electroneurographic (ENG) signal analysis in an EEG-driven time window, movement classification performance improved. After training, the participant regained normal modulation of background rhythms for movement preparation (α/β band desynchronization) in the sensorimotor area contralateral to the missing limb. Moreover, coherence analysis found a restored α band synchronization of Rolandic area with frontal and parietal ipsilateral regions, similar to that observed in the opposite hemisphere for movement of the intact hand. Of note, phantom limb pain (PLP) resolved for several months. Combining information from both cortical (EEG) and stump nerve (ENG) signals improved the classification performance compared with tf-LIFE signals processing alone; training led to cortical reorganization and

ALIF: A New Promising Technique for the Decomposition and Analysis of Nonlinear and Nonstationary Signals

Science.gov (United States)

Cicone, A.; Zhou, H.; Piersanti, M.; Materassi, M.; Spogli, L.

2017-12-01

Nonlinear and nonstationary signals are ubiquitous in real life. Their decomposition and analysis is of crucial importance in many research fields. Traditional techniques, like Fourier and wavelet Transform have been proved to be limited in this context. In the last two decades new kind of nonlinear methods have been developed which are able to unravel hidden features of these kinds of signals. In this poster we present a new method, called Adaptive Local Iterative Filtering (ALIF). This technique, originally developed to study mono-dimensional signals, unlike any other algorithm proposed so far, can be easily generalized to study two or higher dimensional signals. Furthermore, unlike most of the similar methods, it does not require any a priori assumption on the signal itself, so that the technique can be applied as it is to any kind of signals. Applications of ALIF algorithm to real life signals analysis will be presented. Like, for instance, the behavior of the water level near the coastline in presence of a Tsunami, length of the day signal, pressure measured at ground level on a global grid, radio power scintillation from GNSS signals,

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

Directory of Open Access Journals (Sweden)

Chin-Teng Lin

2018-01-01

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

Quantitative pulsed eddy current analysis

International Nuclear Information System (INIS)

Morris, R.A.

1975-01-01

The potential of pulsed eddy current testing for furnishing more information than conventional single-frequency eddy current methods has been known for some time. However, a fundamental problem has been analyzing the pulse shape with sufficient precision to produce accurate quantitative results. Accordingly, the primary goal of this investigation was to: demonstrate ways of digitizing the short pulses encountered in PEC testing, and to develop empirical analysis techniques that would predict some of the parameters (e.g., depth) of simple types of defect. This report describes a digitizing technique using a computer and either a conventional nuclear ADC or a fast transient analyzer; the computer software used to collect and analyze pulses; and some of the results obtained. (U.S.)

TSLP signaling pathway map: a platform for analysis of TSLP-mediated signaling.

Science.gov (United States)

Zhong, Jun; Sharma, Jyoti; Raju, Rajesh; Palapetta, Shyam Mohan; Prasad, T S Keshava; Huang, Tai-Chung; Yoda, Akinori; Tyner, Jeffrey W; van Bodegom, Diederik; Weinstock, David M; Ziegler, Steven F; Pandey, Akhilesh

2014-01-01

Thymic stromal lymphopoietin (TSLP) is a four-helix bundle cytokine that plays a critical role in the regulation of immune responses and in the differentiation of hematopoietic cells. TSLP signals through a heterodimeric receptor complex consisting of an interleukin-7 receptor α chain and a unique TSLP receptor (TSLPR) [also known as cytokine receptor-like factor 2 (CRLF2)]. Cellular targets of TSLP include dendritic cells, B cells, mast cells, regulatory T (Treg) cells and CD4+ and CD8+ T cells. The TSLP/TSLPR axis can activate multiple signaling transduction pathways including the JAK/STAT pathway and the PI-3 kinase pathway. Aberrant TSLP/TSLPR signaling has been associated with a variety of human diseases including asthma, atopic dermatitis, nasal polyposis, inflammatory bowel disease, eosinophilic eosophagitis and, most recently, acute lymphoblastic leukemia. A centralized resource of the TSLP signaling pathway cataloging signaling events is not yet available. In this study, we present a literature-annotated resource of reactions in the TSLP signaling pathway. This pathway map is publicly available through NetPath (http://www.netpath.org/), an open access signal transduction pathway resource developed previously by our group. This map includes 236 molecules and 252 reactions that are involved in TSLP/TSLPR signaling pathway. We expect that the TSLP signaling pathway map will provide a rich resource to study the biology of this important cytokine as well as to identify novel therapeutic targets for diseases associated with dysregulated TSLP/TSLPR signaling. Database URL: http://www.netpath.org/pathways?path_id=NetPath_24.

Multi-Scale Factor Analysis of High-Dimensional Brain Signals

KAUST Repository

Ting, Chee-Ming

2017-05-18

In this paper, we develop an approach to modeling high-dimensional networks with a large number of nodes arranged in a hierarchical and modular structure. We propose a novel multi-scale factor analysis (MSFA) model which partitions the massive spatio-temporal data defined over the complex networks into a finite set of regional clusters. To achieve further dimension reduction, we represent the signals in each cluster by a small number of latent factors. The correlation matrix for all nodes in the network are approximated by lower-dimensional sub-structures derived from the cluster-specific factors. To estimate regional connectivity between numerous nodes (within each cluster), we apply principal components analysis (PCA) to produce factors which are derived as the optimal reconstruction of the observed signals under the squared loss. Then, we estimate global connectivity (between clusters or sub-networks) based on the factors across regions using the RV-coefficient as the cross-dependence measure. This gives a reliable and computationally efficient multi-scale analysis of both regional and global dependencies of the large networks. The proposed novel approach is applied to estimate brain connectivity networks using functional magnetic resonance imaging (fMRI) data. Results on resting-state fMRI reveal interesting modular and hierarchical organization of human brain networks during rest.

Denoising of chaotic signal using independent component analysis and empirical mode decomposition with circulate translating

International Nuclear Information System (INIS)

Wang Wen-Bo; Zhang Xiao-Dong; Chang Yuchan; Wang Xiang-Li; Wang Zhao; Chen Xi; Zheng Lei

2016-01-01

In this paper, a new method to reduce noises within chaotic signals based on ICA (independent component analysis) and EMD (empirical mode decomposition) is proposed. The basic idea is decomposing chaotic signals and constructing multidimensional input vectors, firstly, on the base of EMD and its translation invariance. Secondly, it makes the independent component analysis on the input vectors, which means that a self adapting denoising is carried out for the intrinsic mode functions (IMFs) of chaotic signals. Finally, all IMFs compose the new denoised chaotic signal. Experiments on the Lorenz chaotic signal composed of different Gaussian noises and the monthly observed chaotic sequence on sunspots were put into practice. The results proved that the method proposed in this paper is effective in denoising of chaotic signals. Moreover, it can correct the center point in the phase space effectively, which makes it approach the real track of the chaotic attractor. (paper)

Polyspectral signal analysis techniques for condition based maintenance of helicopter drive-train system

Science.gov (United States)

Hassan Mohammed, Mohammed Ahmed

For an efficient maintenance of a diverse fleet of air- and rotorcraft, effective condition based maintenance (CBM) must be established based on rotating components monitored vibration signals. In this dissertation, we present theory and applications of polyspectral signal processing techniques for condition monitoring of critical components in the AH-64D helicopter tail rotor drive train system. Currently available vibration-monitoring tools are mostly built around auto- and cross-power spectral analysis which have limited performance in detecting frequency correlations higher than second order. Studying higher order correlations and their Fourier transforms, higher order spectra, provides more information about the vibration signals which helps in building more accurate diagnostic models of the mechanical system. Based on higher order spectral analysis, different signal processing techniques are developed to assess health conditions of different critical rotating-components in the AH-64D helicopter drive-train. Based on cross-bispectrum, quadratic nonlinear transfer function is presented to model second order nonlinearity in a drive-shaft running between the two hanger bearings. Then, quadratic-nonlinearity coupling coefficient between frequency harmonics of the rotating shaft is used as condition metric to study different seeded shaft faults compared to baseline case, namely: shaft misalignment, shaft imbalance, and combination of shaft misalignment and imbalance. The proposed quadratic-nonlinearity metric shows better capabilities in distinguishing the four studied shaft settings than the conventional linear coupling based on cross-power spectrum. We also develop a new concept of Quadratic-Nonlinearity Power-Index spectrum, QNLPI(f), that can be used in signal detection and classification, based on bicoherence spectrum. The proposed QNLPI(f) is derived as a projection of the three-dimensional bicoherence spectrum into two-dimensional spectrum that

Analysis and logical modeling of biological signaling transduction networks

Science.gov (United States)

Sun, Zhongyao

The study of network theory and its application span across a multitude of seemingly disparate fields of science and technology: computer science, biology, social science, linguistics, etc. It is the intrinsic similarities embedded in the entities and the way they interact with one another in these systems that link them together. In this dissertation, I present from both the aspect of theoretical analysis and the aspect of application three projects, which primarily focus on signal transduction networks in biology. In these projects, I assembled a network model through extensively perusing literature, performed model-based simulations and validation, analyzed network topology, and proposed a novel network measure. The application of network modeling to the system of stomatal opening in plants revealed a fundamental question about the process that has been left unanswered in decades. The novel measure of the redundancy of signal transduction networks with Boolean dynamics by calculating its maximum node-independent elementary signaling mode set accurately predicts the effect of single node knockout in such signaling processes. The three projects as an organic whole advance the understanding of a real system as well as the behavior of such network models, giving me an opportunity to take a glimpse at the dazzling facets of the immense world of network science.

The signal-to-noise analysis of the Little-Hopfield model revisited

International Nuclear Information System (INIS)

Bolle, D; Blanco, J Busquets; Verbeiren, T

2004-01-01

Using the generating functional analysis an exact recursion relation is derived for the time evolution of the effective local field of the fully connected Little-Hopfield model. It is shown that, by leaving out the feedback correlations arising from earlier times in this effective dynamics, one precisely finds the recursion relations usually employed in the signal-to-noise approach. The consequences of this approximation as well as the physics behind it are discussed. In particular, it is pointed out why it is hard to notice the effects, especially for model parameters corresponding to retrieval. Numerical simulations confirm these findings. The signal-to-noise analysis is then extended to include all correlations, making it a full theory for dynamics at the level of the generating functional analysis. The results are applied to the frequently employed extremely diluted (a)symmetric architectures and to sequence processing networks

Improved prediction of signal peptides: SignalP 3.0

DEFF Research Database (Denmark)

Bendtsen, Jannick Dyrløv; Nielsen, Henrik; von Heijne, G.

2004-01-01

We describe improvements of the currently most popular method for prediction of classically secreted proteins, SignalP. SignalP consists of two different predictors based on neural network and hidden Markov model algorithms, where both components have been updated. Motivated by the idea that the ...

Time-frequency analysis of non-stationary fusion plasma signals using an improved Hilbert-Huang transform

International Nuclear Information System (INIS)

Liu, Yangqing; Tan, Yi; Xie, Huiqiao; Wang, Wenhao; Gao, Zhe

2014-01-01

An improved Hilbert-Huang transform method is developed to the time-frequency analysis of non-stationary signals in tokamak plasmas. Maximal overlap discrete wavelet packet transform rather than wavelet packet transform is proposed as a preprocessor to decompose a signal into various narrow-band components. Then, a correlation coefficient based selection method is utilized to eliminate the irrelevant intrinsic mode functions obtained from empirical mode decomposition of those narrow-band components. Subsequently, a time varying vector autoregressive moving average model instead of Hilbert spectral analysis is performed to compute the Hilbert spectrum, i.e., a three-dimensional time-frequency distribution of the signal. The feasibility and effectiveness of the improved Hilbert-Huang transform method is demonstrated by analyzing a non-stationary simulated signal and actual experimental signals in fusion plasmas

Advances in Photopletysmography Signal Analysis for Biomedical Applications

Directory of Open Access Journals (Sweden)

Jermana L. Moraes

2018-06-01

Full Text Available Heart Rate Variability (HRV is an important tool for the analysis of a patient’s physiological conditions, as well a method aiding the diagnosis of cardiopathies. Photoplethysmography (PPG is an optical technique applied in the monitoring of the HRV and its adoption has been growing significantly, compared to the most commonly used method in medicine, Electrocardiography (ECG. In this survey, definitions of these technique are presented, the different types of sensors used are explained, and the methods for the study and analysis of the PPG signal (linear and nonlinear methods are described. Moreover, the progress, and the clinical and practical applicability of the PPG technique in the diagnosis of cardiovascular diseases are evaluated. In addition, the latest technologies utilized in the development of new tools for medical diagnosis are presented, such as Internet of Things, Internet of Health Things, genetic algorithms, artificial intelligence and biosensors which result in personalized advances in e-health and health care. After the study of these technologies, it can be noted that PPG associated with them is an important tool for the diagnosis of some diseases, due to its simplicity, its cost–benefit ratio, the easiness of signals acquisition, and especially because it is a non-invasive technique.

Pan-cancer analysis of TCGA data reveals notable signaling pathways

International Nuclear Information System (INIS)

Neapolitan, Richard; Horvath, Curt M.; Jiang, Xia

2015-01-01

A signal transduction pathway (STP) is a network of intercellular information flow initiated when extracellular signaling molecules bind to cell-surface receptors. Many aberrant STPs have been associated with various cancers. To develop optimal treatments for cancer patients, it is important to discover which STPs are implicated in a cancer or cancer-subtype. The Cancer Genome Atlas (TCGA) makes available gene expression level data on cases and controls in ten different types of cancer including breast cancer, colon adenocarcinoma, glioblastoma, kidney renal papillary cell carcinoma, low grade glioma, lung adenocarcinoma, lung squamous cell carcinoma, ovarian carcinoma, rectum adenocarcinoma, and uterine corpus endometriod carcinoma. Signaling Pathway Impact Analysis (SPIA) is a software package that analyzes gene expression data to identify whether a pathway is relevant in a given condition. We present the results of a study that uses SPIA to investigate all 157 signaling pathways in the KEGG PATHWAY database. We analyzed each of the ten cancer types mentioned above separately, and we perform a pan-cancer analysis by grouping the data for all the cancer types. In each analysis several pathways were found to be markedly more significant than all the other pathways. We call them notable. Research has already established a connection between many of these pathways and the corresponding cancer type. However, some of our discovered pathways appear to be new findings. Altogether there were 37 notable findings in the separate analyses, 26 of them occurred in 7 pathways. These 7 pathways included the 4 notable pathways discovered in the pan-cancer analysis. So, our results suggest that these 7 pathways account for much of the mechanisms of cancer. Furthermore, by looking at the overlap among pathways, we identified possible regions on the pathways where the aberrant activity is occurring. We obtained 37 notable findings concerning 18 pathways. Some of them appear to be

Current collapse modeling in AlGaN/GaN HEMT using small signal equivalent circuit for high power application

Science.gov (United States)

Nirmal, D.; Arivazhagan, L.; Fletcher, A. S. Augustine; Ajayan, J.; Prajoon, P.

2018-01-01

In this paper, the drain current collapse in AlGaN/GaN High Electron Mobility Transistor (HEMT) with field plate engineering is investigated. A small signal equivalent circuit of AlGaN/GaN HEMT is developed and a new drain current model is derived. This model is useful to correlate the impact of intrinsic capacitance and conductance on drain current collapse. The proposed device suppressed the current collapse phenomena by 10% compared with the conventional AlGaN/GaN HEMT. Moreover, the DC characteristics of the simulated device shows a drain current of 900 mA/mm, breakdown voltage of 291 V and transconductance of 175 mS/mm. Besides, the intrinsic capacitance and conductance parameters are extracted and its impact on drain current is analysed. Finally, the simulation results obtained were in compliance with the derived mathematical model of AlGaN/GaN HEMT.

Small-Signal Stability Analysis of Full-Load Converter Interfaced Wind Turbines

DEFF Research Database (Denmark)

Knüppel, Thyge; Akhmatov, Vladislav; Nielsen, Jørgen Nygård

2009-01-01

focus since the share of wind power increases substituting power generation from conventional power plants. Here, a study based on modal analysis is presented which investigate the effect of large scale integration of full-load converter interfaced wind turbines on inter-area oscillations in a three...... generator network. A detailed aggregated wind turbine model is employed which includes all necessary control functions. It is shown that the wind urbines have very low participation in the inter-area power oscillation.......Power system stability investigations of wind farms often cover the tasks of low-voltage-fault-ride-through, voltage and reactive power control, and power balancing, but not much attention has yet been paid to the task of small-signal stability. Small-signal stability analysis needs increasing...

Variability of signal-to-noise ratio and the network analysis of gravitational wave burst signals

International Nuclear Information System (INIS)

Mohanty, S D; Rakhmanov, M; Klimenko, S; Mitselmakher, G

2006-01-01

The detection and estimation of gravitational wave burst signals, with a priori unknown polarization waveforms, requires the use of data from a network of detectors. Maximizing the network likelihood functional over all waveforms and sky positions yields point estimates for them as well as a detection statistic. However, the transformation from the data to estimates can become ill-conditioned over parts of the sky, resulting in significant errors in estimation. We modify the likelihood procedure by introducing a penalty functional which suppresses candidate solutions that display large signal-to-noise ratio (SNR) variability as the source is displaced on the sky. Simulations show that the resulting network analysis method performs significantly better in estimating the sky position of a source. Further, this method can be applied to any network, irrespective of the number or mutual alignment of detectors

Nitric oxide/cGMP/PKG signaling pathway activated by M1-type muscarinic acetylcholine receptor cascade inhibits Na+-activated K+ currents in Kenyon cells

Science.gov (United States)

Hasebe, Masaharu

2016-01-01

The interneurons of the mushroom body, known as Kenyon cells, are essential for the long-term memory of olfactory associative learning in some insects. Some studies have reported that nitric oxide (NO) is strongly related to this long-term memory in Kenyon cells. However, the target molecules and upstream and downstream NO signaling cascades are not completely understood. Here we analyzed the effect of the NO signaling cascade on Na+-activated K+ (KNa) channel activity in Kenyon cells of crickets (Gryllus bimaculatus). We found that two different NO donors, S-nitrosoglutathione (GSNO) and S-nitroso-N-acetyl-dl-penicillamine (SNAP), strongly suppressed KNa channel currents. Additionally, this inhibitory effect of GSNO on KNa channel activity was diminished by 1H-[1,2,4]oxadiazolo[4,3-a]quinoxalin-1-one (ODQ), an inhibitor of soluble guanylate cyclase (sGC), and KT5823, an inhibitor of protein kinase G (PKG). Next, we analyzed the role of ACh in the NO signaling cascade. ACh strongly suppressed KNa channel currents, similar to NO donors. Furthermore, this inhibitory effect of ACh was blocked by pirenzepine, an M1 muscarinic ACh receptor antagonist, but not by 1,1-dimethyl-4-diphenylacetoxypiperidinium iodide (4-DAMP) and mecamylamine, an M3 muscarinic ACh receptor antagonist and a nicotinic ACh receptor antagonist, respectively. The ACh-induced inhibition of KNa channel currents was also diminished by the PLC inhibitor U73122 and the calmodulin antagonist W-7. Finally, we found that ACh inhibition was blocked by the nitric oxide synthase (NOS) inhibitor NG-nitro-l-arginine methyl ester (l-NAME). These results suggested that the ACh signaling cascade promotes NO production by activating NOS and NO inhibits KNa channel currents via the sGC/cGMP/PKG signaling cascade in Kenyon cells. PMID:26984419

A low-power current-reuse dual-band analog front-end for multi-channel neural signal recording.

Science.gov (United States)

Sepehrian, H; Gosselin, B

2014-01-01

Thoroughly studying the brain activity of freely moving subjects requires miniature data acquisition systems to measure and wirelessly transmit neural signals in real time. In this application, it is mandatory to simultaneously record the bioelectrical activity of a large number of neurons to gain a better knowledge of brain functions. However, due to limitations in transferring the entire raw data to a remote base station, employing dedicated data reduction techniques to extract the relevant part of neural signals is critical to decrease the amount of data to transfer. In this work, we present a new dual-band neural amplifier to separate the neuronal spike signals (SPK) and the local field potential (LFP) simultaneously in the analog domain, immediately after the pre-amplification stage. By separating these two bands right after the pre-amplification stage, it is possible to process LFP and SPK separately. As a result, the required dynamic range of the entire channel, which is determined by the signal-to-noise ratio of the SPK signal of larger bandwidth, can be relaxed. In this design, a new current-reuse low-power low-noise amplifier and a new dual-band filter that separates SPK and LFP while saving capacitors and pseudo resistors. A four-channel dual-band (SPK, LFP) analog front-end capable of simultaneously separating SPK and LFP is implemented in a TSMC 0.18 μm technology. Simulation results present a total power consumption per channel of 3.1 μw for an input referred noise of 3.28 μV and a NEF for 2.07. The cutoff frequency of the LFP band is fc=280 Hz, and fL=725 Hz and fL=11.2 KHz for SPK, with 36 dB gain for LFP band 46 dB gain for SPK band.

Automatic adjustment of bias current for direct current superconducting quantum interference device

International Nuclear Information System (INIS)

Makie-Fukuda, K.; Hotta, M.; Okajima, K.; Kado, H.

1993-01-01

A new method of adjusting the bias current of dc superconducting quantum interference device (SQUID) is described. It is shown that the signal-to-noise ratio of a SQUID magnetometer connected in a flux-locked loop configuration is proportional to the second harmonic of the output signal from the SQUID. A circuit configuration that can automatically optimize a SQUID's bias current by measuring this second harmonic and adjusting the bias current accordingly is proposed

Constraint-based modeling and kinetic analysis of the Smad dependent TGF-beta signaling pathway.

Directory of Open Access Journals (Sweden)

Zhike Zi

Full Text Available BACKGROUND: Investigation of dynamics and regulation of the TGF-beta signaling pathway is central to the understanding of complex cellular processes such as growth, apoptosis, and differentiation. In this study, we aim at using systems biology approach to provide dynamic analysis on this pathway. METHODOLOGY/PRINCIPAL FINDINGS: We proposed a constraint-based modeling method to build a comprehensive mathematical model for the Smad dependent TGF-beta signaling pathway by fitting the experimental data and incorporating the qualitative constraints from the experimental analysis. The performance of the model generated by constraint-based modeling method is significantly improved compared to the model obtained by only fitting the quantitative data. The model agrees well with the experimental analysis of TGF-beta pathway, such as the time course of nuclear phosphorylated Smad, the subcellular location of Smad and signal response of Smad phosphorylation to different doses of TGF-beta. CONCLUSIONS/SIGNIFICANCE: The simulation results indicate that the signal response to TGF-beta is regulated by the balance between clathrin dependent endocytosis and non-clathrin mediated endocytosis. This model is useful to be built upon as new precise experimental data are emerging. The constraint-based modeling method can also be applied to quantitative modeling of other signaling pathways.

Embedding Dimension Selection for Adaptive Singular Spectrum Analysis of EEG Signal.

Science.gov (United States)

Xu, Shanzhi; Hu, Hai; Ji, Linhong; Wang, Peng

2018-02-26

The recorded electroencephalography (EEG) signal is often contaminated with different kinds of artifacts and noise. Singular spectrum analysis (SSA) is a powerful tool for extracting the brain rhythm from a noisy EEG signal. By analyzing the frequency characteristics of the reconstructed component (RC) and the change rate in the trace of the Toeplitz matrix, it is demonstrated that the embedding dimension is related to the frequency bandwidth of each reconstructed component, in consistence with the component mixing in the singular value decomposition step. A method for selecting the embedding dimension is thereby proposed and verified by simulated EEG signal based on the Markov Process Amplitude (MPA) EEG Model. Real EEG signal is also collected from the experimental subjects under both eyes-open and eyes-closed conditions. The experimental results show that based on the embedding dimension selection method, the alpha rhythm can be extracted from the real EEG signal by the adaptive SSA, which can be effectively utilized to distinguish between the eyes-open and eyes-closed states.

Embedding Dimension Selection for Adaptive Singular Spectrum Analysis of EEG Signal

Directory of Open Access Journals (Sweden)

Shanzhi Xu

2018-02-01

Full Text Available The recorded electroencephalography (EEG signal is often contaminated with different kinds of artifacts and noise. Singular spectrum analysis (SSA is a powerful tool for extracting the brain rhythm from a noisy EEG signal. By analyzing the frequency characteristics of the reconstructed component (RC and the change rate in the trace of the Toeplitz matrix, it is demonstrated that the embedding dimension is related to the frequency bandwidth of each reconstructed component, in consistence with the component mixing in the singular value decomposition step. A method for selecting the embedding dimension is thereby proposed and verified by simulated EEG signal based on the Markov Process Amplitude (MPA EEG Model. Real EEG signal is also collected from the experimental subjects under both eyes-open and eyes-closed conditions. The experimental results show that based on the embedding dimension selection method, the alpha rhythm can be extracted from the real EEG signal by the adaptive SSA, which can be effectively utilized to distinguish between the eyes-open and eyes-closed states.

LC-MS/MS signal suppression effects in the analysis of pesticides in complex environmental matrices.

Science.gov (United States)

Choi, B K; Hercules, D M; Gusev, A I

2001-02-01

The application of LC separation and mobile phase additives in addressing LC-MS/MS matrix signal suppression effects for the analysis of pesticides in a complex environmental matrix was investigated. It was shown that signal suppression is most significant for analytes eluting early in the LC-MS analysis. Introduction of different buffers (e.g. ammonium formate, ammonium hydroxide, formic acid) into the LC mobile phase was effective in improving signal correlation between the matrix and standard samples. The signal improvement is dependent on buffer concentration as well as LC separation of the matrix components. The application of LC separation alone was not effective in addressing suppression effects when characterizing complex matrix samples. Overloading of the LC column by matrix components was found to significantly contribute to analyte-matrix co-elution and suppression of signal. This signal suppression effect can be efficiently compensated by 2D LC (LC-LC) separation techniques. The effectiveness of buffers and LC separation in improving signal correlation between standard and matrix samples is discussed.

Large-Signal Lyapunov-Based Stability Analysis of DC/AC Inverters and Inverter-Based Microgrids

Science.gov (United States)

Kabalan, Mahmoud

study. This will enable future studies to save computational effort and produce the most accurate results according to the needs of the study being performed. Moreover, the effect of grid (line) impedance on the accuracy of droop control is explored using the 5th order model. Simulation results show that traditional droop control is valid up to R/X line impedance value of 2. Furthermore, the 3rd order nonlinear model improves the currently available inverter-infinite bus models by accounting for grid impedance, active power-frequency droop and reactive power-voltage droop. Results show the 3rd order model's ability to account for voltage and reactive power changes during a transient event. Finally, the large-signal Lyapunov-based stability analysis is completed for a 3 bus microgrid system (made up of 2 inverters and 1 linear load). The thesis provides a systematic state space large-signal nonlinear mathematical modeling method of inverter-based microgrids. The inverters include the dc-side dynamics associated with dc sources. The mathematical model is then used to estimate the domain of asymptotic stability of the 3 bus microgrid. The three bus microgrid system was used as a case study to highlight the design and optimization capability of a large-signal-based approach. The study explores the effect of system component sizing, load transient and generation variations on the asymptotic stability of the microgrid. Essentially, this advancement gives microgrid designers and engineers the ability to manipulate the domain of asymptotic stability depending on performance requirements. Especially important, this research was able to couple the domain of asymptotic stability of the ac microgrid with that of the dc side voltage source. Time domain simulations were used to demonstrate the mathematical nonlinear analysis results.

Speckle noise reduction technique for Lidar echo signal based on self-adaptive pulse-matching independent component analysis

Science.gov (United States)

Xu, Fan; Wang, Jiaxing; Zhu, Daiyin; Tu, Qi

2018-04-01

Speckle noise has always been a particularly tricky problem in improving the ranging capability and accuracy of Lidar system especially in harsh environment. Currently, effective speckle de-noising techniques are extremely scarce and should be further developed. In this study, a speckle noise reduction technique has been proposed based on independent component analysis (ICA). Since normally few changes happen in the shape of laser pulse itself, the authors employed the laser source as a reference pulse and executed the ICA decomposition to find the optimal matching position. In order to achieve the self-adaptability of algorithm, local Mean Square Error (MSE) has been defined as an appropriate criterion for investigating the iteration results. The obtained experimental results demonstrated that the self-adaptive pulse-matching ICA (PM-ICA) method could effectively decrease the speckle noise and recover the useful Lidar echo signal component with high quality. Especially, the proposed method achieves 4 dB more improvement of signal-to-noise ratio (SNR) than a traditional homomorphic wavelet method.

A Sparse Modulation Signal Bispectrum Analysis Method for Rolling Element Bearing Diagnosis

Directory of Open Access Journals (Sweden)

Guangbin Wang

2018-01-01

Full Text Available Modulation signal bispectrum (MSB analysis is an effective method to obtain the fault frequency for rolling bearing, but harmonics make fault frequency dense and even frequency aliasing. Carrier frequency of bearing is generally determined by its structure and inherent characteristics and changes with the increase of the damage degree, so it is hard to be accurately found. To solve these problems, this paper proposes a sparse modulation signal bispectrum analysis method. Firstly the vibration signal is demodulated by MSB analysis and its bispectrum is obtained. After the frequency domain filtering, the carrier frequency is computed based on the characteristics of energy concentration at the carrier frequency on MSB. By shift-frequency MSB (SF-MSB, the carrier frequency is moved to the coordinate origin, the entire MSB is shifted for the same distance, and SF-MSB is obtained. At last, the bispectrum is shifted to the frequency zero point and diagonal slices are performed to obtain a sparse representation of MSB. Experimental results show that sparse MSB (S-MSB method can not only eliminate the interference of harmonic frequency, but also make the extracted characteristic frequency of fault more obvious.

Frequency Analysis of Acoustic Emission Signal to Monitor Damage Evolution in Masonry Structures

International Nuclear Information System (INIS)

Masera, D; Bocca, P; Grazzini, A

2011-01-01

A crucial aspect in damage evaluation of masonry structures is the analysis of long-term behaviour and for this reason fatigue analysis has a great influence on safety assessment of this structures. Acoustic Emission (AE) are very effective non-destructive techniques applied to identify micro and macro-defects and their temporal evolution in several materials. This technique permits to estimate the velocity of ultrasound waves propagation and the amount of energy released during fracture propagation to obtain information on the criticality of the ongoing process. By means of AE monitoring, an experimental analysis on a set of reinforced and unreinforced masonry walls under variable amplitude and static loading has been carried out. During these tests, the AE signals were recorded. The AE signals were analysed using Fast Fourier Transform (FFT) to examine the frequency distribution of the micro and macro cracking. It possible to evaluate the evolution of the wavelength of the AE signal through the two characteristic peak in the AE spectrum signals and the wave speed of the P or S waves. This wavelength evolution can be represent the microcrak and macrocrack evolution in masonry walls. This procedure permits to estimate the fracture dimension characteristic in several loading condition and for several masonry reinforced condition.

Repeatability study of replicate crash tests: A signal analysis approach.

Science.gov (United States)

Seppi, Jeremy; Toczyski, Jacek; Crandall, Jeff R; Kerrigan, Jason

2017-10-03

To provide an objective basis on which to evaluate the repeatability of vehicle crash test methods, a recently developed signal analysis method was used to evaluate correlation of sensor time history data between replicate vehicle crash tests. The goal of this study was to evaluate the repeatability of rollover crash tests performed with the Dynamic Rollover Test System (DRoTS) relative to other vehicle crash test methods. Test data from DRoTS tests, deceleration rollover sled (DRS) tests, frontal crash tests, frontal offset crash tests, small overlap crash tests, small overlap impact (SOI) crash tests, and oblique crash tests were obtained from the literature and publicly available databases (the NHTSA vehicle database and the Insurance Institute for Highway Safety TechData) to examine crash test repeatability. Signal analysis of the DRoTS tests showed that force and deformation time histories had good to excellent repeatability, whereas vehicle kinematics showed only fair repeatability due to the vehicle mounting method for one pair of tests and slightly dissimilar mass properties (2.2%) in a second pair of tests. Relative to the DRS, the DRoTS tests showed very similar or higher levels of repeatability in nearly all vehicle kinematic data signals with the exception of global X' (road direction of travel) velocity and displacement due to the functionality of the DRoTS fixture. Based on the average overall scoring metric of the dominant acceleration, DRoTS was found to be as repeatable as all other crash tests analyzed. Vertical force measures showed good repeatability and were on par with frontal crash barrier forces. Dynamic deformation measures showed good to excellent repeatability as opposed to poor repeatability seen in SOI and oblique deformation measures. Using the signal analysis method as outlined in this article, the DRoTS was shown to have the same or better repeatability of crash test methods used in government regulatory and consumer evaluation test

Signal Integrity Analysis in Single and Bundled Carbon Nanotube Interconnects

International Nuclear Information System (INIS)

Majumder, M.K.; Pandya, N.D.; Kaushik, B.K.; Manhas, S.K.

2013-01-01

Carbon nanotube (CN T) can be considered as an emerging interconnect material in current nano scale regime. They are more promising than other interconnect materials such as Al or Cu because of their robustness to electromigration. This research paper aims to address the crosstalk-related issues (signal integrity) in interconnect lines. Different analytical models of single- (SWCNT), double- (DWCNT), and multiwalled CNTs (MWCNT) are studied to analyze the crosstalk delay at global interconnect lengths. A capacitively coupled three-line bus architecture employing CMOS driver is used for accurate estimation of crosstalk delay. Each line in bus architecture is represented with the equivalent RLC models of single and bundled SWCNT, DWCNT, and MWCNT interconnects. Crosstalk delay is observed at middle line (victim) when it switches in opposite direction with respect to the other two lines (aggressors). Using the data predicted by ITRS 2012, a comparative analysis on the basis of crosstalk delay is performed for bundled SWCNT/DWCNT and single MWCNT interconnects. It is observed that the overall crosstalk delay is improved by 40.92% and 21.37% for single MWCNT in comparison to bundled SWCNT and bundled DWCNT interconnects, respectively.

Advanced electrical current measurements of microdischarges: evidence of sub-critical pulses and ion currents in barrier discharge in air

Science.gov (United States)

Synek, Petr; Zemánek, Miroslav; Kudrle, Vít; Hoder, Tomáš

2018-04-01

Electrical current measurements in corona or barrier microdischarges are a challenge as they require both high temporal resolution and a large dynamic range of the current probe used. In this article, we apply a simple self-assembled current probe and compare it to commercial ones. An analysis in the time and frequency domain is carried out. Moreover, an improved methodology is presented, enabling both temporal resolution in sub-nanosecond times and current sensitivity in the order of tens of micro-amperes. Combining this methodology with a high-tech oscilloscope and self-developed software, a unique statistical analysis of currents in volume barrier discharge driven in atmospheric-pressure air is made for over 80 consecutive periods of a 15 kHz applied voltage. We reveal the presence of repetitive sub-critical current pulses and conclude that these can be identified with the discharging of surface charge microdomains. Moreover, extremely low, long-lasting microsecond currents were detected which are caused by ion flow, and are analysed in detail. The statistical behaviour presented gives deeper insight into the discharge physics of these usually undetectable current signals.

pyAudioAnalysis: An Open-Source Python Library for Audio Signal Analysis.

Science.gov (United States)

Giannakopoulos, Theodoros

2015-01-01

Audio information plays a rather important role in the increasing digital content that is available today, resulting in a need for methodologies that automatically analyze such content: audio event recognition for home automations and surveillance systems, speech recognition, music information retrieval, multimodal analysis (e.g. audio-visual analysis of online videos for content-based recommendation), etc. This paper presents pyAudioAnalysis, an open-source Python library that provides a wide range of audio analysis procedures including: feature extraction, classification of audio signals, supervised and unsupervised segmentation and content visualization. pyAudioAnalysis is licensed under the Apache License and is available at GitHub (https://github.com/tyiannak/pyAudioAnalysis/). Here we present the theoretical background behind the wide range of the implemented methodologies, along with evaluation metrics for some of the methods. pyAudioAnalysis has been already used in several audio analysis research applications: smart-home functionalities through audio event detection, speech emotion recognition, depression classification based on audio-visual features, music segmentation, multimodal content-based movie recommendation and health applications (e.g. monitoring eating habits). The feedback provided from all these particular audio applications has led to practical enhancement of the library.

Comparative analysis of chosen transforms in the context of de-noising harmonic signals

Directory of Open Access Journals (Sweden)

Artur Zacniewski

2015-09-01

Full Text Available In the article, comparison of popular transforms used i.a. in denoising harmonical signals was presented. The division of signals submitted to mathematical analysis was shown and chosen transforms such as Short Time Fourier Transform, Wigner-Ville Distribution, Wavelet Transform and Discrete Cosine Transform were presented. Harmonic signal with white noise added was submitted for research. During research, the parameters of noise were changed to analyze the effects of using particular transform on noised signal. The importance of right choice for transform and its parameters (different for particular kind of transform was shown. Small changes in parameters or different functions used in transform can lead to considerably different results.[b]Keywords[/b]: denoising of harmonical signals, wavelet transform, discrete cosine transform, DCT

Carbon price signal. Impact Analysis on the European Electricity System

International Nuclear Information System (INIS)

2016-03-01

The Paris Agreement signed by 195 countries late in December 2015, after COP 21, created a new basis for efficient cooperation between countries in the fight against climate change. The technologies being rolled out by the electricity sector will have very different impacts on climate change and, for the time being, investments other than public aid for renewable energies are being guided primarily by prices. To shed more slight on the issue of greenhouse gas emissions, which is closely related to the challenges addressed at COP21, RTE initiated a study in 2015 based on the models used in its Generation Adequacy Report. ADEME wanted to contribute to this effort and offer its support. The present document outlines the approach taken to assessing the impact of the carbon price signal on emissions from the European electric power system, its production costs and its structural evolution over the medium term. This approach was discussed with members of the 'Network Outlook Committee' of the Transmission System Users' Committee which includes environmental NGOs as well as the main economic actors from the power sector. Key findings resulting from the analysis developed in this report include: Simulations conducted with the current generation fleet show that the carbon price would have to be close to euro 30/tonne at the European level to drive a significant reduction in emissions (about 100 million tonnes a year, or 15 %) from the European power sector. A higher price of about euro 100/tonne would help drive an emissions reduction of close to 30%. Over the medium and long terms, beyond an impact on the number of hours fossil fuel power plants would be run, having a high carbon price would send a signal encouraging investment in renewable energies and could incentivise the development of flexible and storage capacity. It would notably guarantee the profitability of gas-fired plants and renewable power development. The following assumptions are factored into the study

An Optimization-Driven Analysis Pipeline to Uncover Biomarkers and Signaling Paths: Cervix Cancer

Directory of Open Access Journals (Sweden)

Enery Lorenzo

2015-05-01

Full Text Available Establishing how a series of potentially important genes might relate to each other is relevant to understand the origin and evolution of illnesses, such as cancer. High‑throughput biological experiments have played a critical role in providing information in this regard. A special challenge, however, is that of trying to conciliate information from separate microarray experiments to build a potential genetic signaling path. This work proposes a two-step analysis pipeline, based on optimization, to approach meta-analysis aiming to build a proxy for a genetic signaling path.

An approach to reconstruction of a natural crack using signals of eddy current testing. 1. Reconstruction of an idealized natural crack

International Nuclear Information System (INIS)

Chen, Zhenmao

1998-12-01

In this paper, an approach to the reconstruction of an idealized natural crack of non-vanishing conductivity is proposed with use of signals of eddy current testing. Two numerical models are introduced at first for modeling a Stress Corrosion Crack (SCC) in order it possibly to be represented by a set of crack parameters. A method for rapid prediction of the eddy current testing signals arisen from these idealized cracks is given then by extending a knowledge based fast forward solver developed by authors to the case of a non-vanishing conductivity. On the other hand, the inverse algorithm of conjugate gradient method is improved to reconstruct the crack parameters and is implemented with the pick-up signals and gradients calculated by using the rapid forward solver. Several examples are presented finally for validating the proposed strategy. The results verified that both of the models can give reasonable reconstruction results in case of a low noise level. The model concerning the touch of crack surfaces with a conducting band region surrounded by the crack edge, however, is proved more efficient that the model using a conductivity distribution from the point of view of both reconstruction speed and accuracy. (author)

TERMA Framework for Biomedical Signal Analysis: An Economic-Inspired Approach

Directory of Open Access Journals (Sweden)

Mohamed Elgendi

2016-11-01

Full Text Available Biomedical signals contain features that represent physiological events, and each of these events has peaks. The analysis of biomedical signals for monitoring or diagnosing diseases requires the detection of these peaks, making event detection a crucial step in biomedical signal processing. Many researchers have difficulty detecting these peaks to investigate, interpret and analyze their corresponding events. To date, there is no generic framework that captures these events in a robust, efficient and consistent manner. A new method referred to for the first time as two event-related moving averages (“TERMA” involves event-related moving averages and detects events in biomedical signals. The TERMA framework is flexible and universal and consists of six independent LEGO building bricks to achieve high accuracy detection of biomedical events. Results recommend that the window sizes for the two moving averages ( W 1 and W 2 have to follow the inequality ( 8 × W 1 ≥ W 2 ≥ ( 2 × W 1 . Moreover, TERMA is a simple yet efficient event detector that is suitable for wearable devices, point-of-care devices, fitness trackers and smart watches, compared to more complex machine learning solutions.

Development of a central PC-based system for reactor signal monitoring and analysis

International Nuclear Information System (INIS)

Karim, A.; Ansari, S.A.; Baig, A.R.

1996-05-01

A personal computer based system was developed for on-line monitoring, signal processing and display of important parameters of the Pakistan Reactor-1. The system was designed for assistance to both reactor operator and users. It performs three main functions. The first is the centralized radiation monitoring in and around the reactor building. The computer acquires signals from radiation monitoring channels and continuously displays them on distributed monitors. Trend monitoring and alarm generation is also done. In case of any abnormal condition the radiation level data is automatically stored in computer memory for detailed off-line analysis. In the second part the computer does the performance testing of nuclear instrumentation channels by signal statistical analysis and generates alarm in case the channel standard deviation error exceeds the permissible error. Mean values of important nuclear signals are also displayed on distributed monitors as a part of reactor safety parameters display system. The third function is on-line computation of reactor physics parameters of the core which are important from operational and safety point-of-view. The signals from radiation protection system and nuclear instrumentation channels in the reactor were interfaced with the computer for this purpose. The development work was done under an IAEA research contract as a part of coordinated research programme. (author) 12 figs

Development of a central PC-based system for reactor signal monitoring and analysis

International Nuclear Information System (INIS)

Karim, A.; Ansari, S.A.; Rauf Baig, A.

1998-01-01

A personal computer based system was developed for on-line monitoring, signal processing and display of important reactor parameters of the Pakistan Research Reactor-1. The system was designed for assistance to both reactor operator and users. It performs three main functions. The first is the centralized radiation monitoring in and around the reactor building. The computer acquires signals from radiation monitoring channels and continuously displays them on distributed monitors. Trend monitoring and alarm generation is also done. In case of any abnormal condition the radiation level data is automatically stored in computer memory for detailed off-line analysis. In the second part the computer does the performance testing of nuclear instrumentation channels by signal statistical analysis, and generates alarm in case the channel standard deviation error exceeds the permissible error. Mean values of important nuclear signals are also displayed on distributed monitors as a part of reactor safety parameters display system. The third function is on-line computation of reactor physics parameters of the core which are important from operational and safety points-of-view. The signals from radiation protection system and nuclear instrumentation channels in the reactor were interfaced with the computer for this purpose. The development work was done under an IAEA research contract as a part of coordinated research programme. (author)

Fractional Modeling of the AC Large-Signal Frequency Response in Magnetoresistive Current Sensors

Directory of Open Access Journals (Sweden)

Sergio Iván Ravelo Arias

2013-12-01

Full Text Available Fractional calculus is considered when derivatives and integrals of non-integer order are applied over a specific function. In the electrical and electronic domain, the transfer function dependence of a fractional filter not only by the filter order n, but additionally, of the fractional order α is an example of a great number of systems where its input-output behavior could be more exactly modeled by a fractional behavior. Following this aim, the present work shows the experimental ac large-signal frequency response of a family of electrical current sensors based in different spintronic conduction mechanisms. Using an ac characterization set-up the sensor transimpedance function  is obtained considering it as the relationship between sensor output voltage and input sensing current,[PLEASE CHECK FORMULA IN THE PDF]. The study has been extended to various magnetoresistance sensors based in different technologies like anisotropic magnetoresistance (AMR, giant magnetoresistance (GMR, spin-valve (GMR-SV and tunnel magnetoresistance (TMR. The resulting modeling shows two predominant behaviors, the low-pass and the inverse low-pass with fractional index different from the classical integer response. The TMR technology with internal magnetization offers the best dynamic and sensitivity properties opening the way to develop actual industrial applications.

Updating signal typing in voice: addition of type 4 signals.

Science.gov (United States)

Sprecher, Alicia; Olszewski, Aleksandra; Jiang, Jack J; Zhang, Yu

2010-06-01

The addition of a fourth type of voice to Titze's voice classification scheme is proposed. This fourth voice type is characterized by primarily stochastic noise behavior and is therefore unsuitable for both perturbation and correlation dimension analysis. Forty voice samples were classified into the proposed four types using narrowband spectrograms. Acoustic, perceptual, and correlation dimension analyses were completed for all voice samples. Perturbation measures tended to increase with voice type. Based on reliability cutoffs, the type 1 and type 2 voices were considered suitable for perturbation analysis. Measures of unreliability were higher for type 3 and 4 voices. Correlation dimension analyses increased significantly with signal type as indicated by a one-way analysis of variance. Notably, correlation dimension analysis could not quantify the type 4 voices. The proposed fourth voice type represents a subset of voices dominated by noise behavior. Current measures capable of evaluating type 4 voices provide only qualitative data (spectrograms, perceptual analysis, and an infinite correlation dimension). Type 4 voices are highly complex and the development of objective measures capable of analyzing these voices remains a topic of future investigation.

Optical coherence tomography signal analysis: LIDAR like equation and inverse methods

International Nuclear Information System (INIS)

Amaral, Marcello Magri

2012-01-01

Optical Coherence Tomography (OCT) is based on the media backscattering properties in order to obtain tomographic images. In a similar way, LIDAR (Light Detection and Range) technique uses these properties to determine atmospheric characteristics, specially the signal extinction coefficient. Exploring this similarity allowed the application of signal inversion methods to the OCT images, allowing to construct images based in the extinction coefficient, original result until now. The goal of this work was to study, propose, develop and implement algorithms based on OCT signal inversion methodologies with the aim of determine the extinction coefficient as a function of depth. Three inversion methods were used and implemented in LABView R : slope, boundary point and optical depth. Associated errors were studied and real samples (homogeneous and stratified) were used for two and three dimension analysis. The extinction coefficient images obtained from the optical depth method were capable to differentiate air from the sample. The images were studied applying PCA and cluster analysis that established the methodology strength in determining the sample's extinction coefficient value. Moreover, the optical depth methodology was applied to study the hypothesis that there is some correlation between signal extinction coefficient and the enamel teeth demineralization during a cariogenic process. By applying this methodology, it was possible to observe the variation of the extinction coefficient as depth function and its correlation with microhardness variation, showing that in deeper layers its values tends to a healthy tooth values, behaving as the same way that the microhardness. (author)

A Review of Sleep Disorder Diagnosis by Electromyogram Signal Analysis.

Science.gov (United States)

Shokrollahi, Mehrnaz; Krishnan, Sridhar

2015-01-01

Sleep and sleep-related problems play a role in a large number of human disorders and affect every field of medicine. It is estimated that 50 to 70 million Americans suffer from a chronic sleep disorder, which hinders their daily life, affects their health, and confers a significant economic burden to society. The negative public health consequences of sleep disorders are enormous and could have long-term effects, including increased risk of hypertension, diabetes, obesity, heart attack, stroke and in some cases death. Polysomnographic modalities can monitor sleep cycles to identify disrupted sleep patterns, adjust the treatments, increase therapeutic options and enhance the quality of life of recording the electroencephalogram (EEG), electromyogram (EMG) and electrocardiogram (ECG). Although the skills acquired by medical facilitators are quite extensive, it is just as important for them to have access to an assortment of technologies and to further improve their monitoring and treatment capabilities. Computer-aided analysis is one advantageous technique that could provide quantitative indices for sleep disorder screening. Evolving evidence suggests that Parkinson's disease may be associated with rapid eye movement sleep behavior disorder (RBD). With this article, we are reviewing studies that are related to EMG signal analysis for detection of neuromuscular diseases that result from sleep movement disorders. As well, the article describes the recent progress in analysis of EMG signals using temporal analysis, frequency-domain analysis, time-frequency, and sparse representations, followed by the comparison of the recent research.

Analysis of physiological signals for recognition of boredom, pain, and surprise emotions.

Science.gov (United States)

Jang, Eun-Hye; Park, Byoung-Jun; Park, Mi-Sook; Kim, Sang-Hyeob; Sohn, Jin-Hun

2015-06-18

The aim of the study was to examine the differences of boredom, pain, and surprise. In addition to that, it was conducted to propose approaches for emotion recognition based on physiological signals. Three emotions, boredom, pain, and surprise, are induced through the presentation of emotional stimuli and electrocardiography (ECG), electrodermal activity (EDA), skin temperature (SKT), and photoplethysmography (PPG) as physiological signals are measured to collect a dataset from 217 participants when experiencing the emotions. Twenty-seven physiological features are extracted from the signals to classify the three emotions. The discriminant function analysis (DFA) as a statistical method, and five machine learning algorithms (linear discriminant analysis (LDA), classification and regression trees (CART), self-organizing map (SOM), Naïve Bayes algorithm, and support vector machine (SVM)) are used for classifying the emotions. The result shows that the difference of physiological responses among emotions is significant in heart rate (HR), skin conductance level (SCL), skin conductance response (SCR), mean skin temperature (meanSKT), blood volume pulse (BVP), and pulse transit time (PTT), and the highest recognition accuracy of 84.7% is obtained by using DFA. This study demonstrates the differences of boredom, pain, and surprise and the best emotion recognizer for the classification of the three emotions by using physiological signals.

In situ visualization and data analysis for turbidity currents simulation

Science.gov (United States)

Camata, Jose J.; Silva, Vítor; Valduriez, Patrick; Mattoso, Marta; Coutinho, Alvaro L. G. A.

2018-01-01

Turbidity currents are underflows responsible for sediment deposits that generate geological formations of interest for the oil and gas industry. LibMesh-sedimentation is an application built upon the libMesh library to simulate turbidity currents. In this work, we present the integration of libMesh-sedimentation with in situ visualization and in transit data analysis tools. DfAnalyzer is a solution based on provenance data to extract and relate strategic simulation data in transit from multiple data for online queries. We integrate libMesh-sedimentation and ParaView Catalyst to perform in situ data analysis and visualization. We present a parallel performance analysis for two turbidity currents simulations showing that the overhead for both in situ visualization and in transit data analysis is negligible. We show that our tools enable monitoring the sediments appearance at runtime and steer the simulation based on the solver convergence and visual information on the sediment deposits, thus enhancing the analytical power of turbidity currents simulations.

Low Power Continuous-Time Delta-Sigma ADC with Current Output DAC

DEFF Research Database (Denmark)

Marker-Villumsen, Niels; Jørgensen, Ivan Harald Holger; Bruun, Erik

2015-01-01

The paper presents a continuous-time (CT) DeltaSigma (∆Σ) analog-to-digital converter (ADC) using a current output digital-to-analog converter (DAC) for the feedback. From circuit analysis it is shown that using a current output DAC makes it possible to relax the noise requirements of the 1st...... integrator of the loopfilter, and thereby reduce the current consumption. Furthermore, the noise of the current output DAC being dependent on the ADC input signal level, enabling a dynamic range that is larger than the peak signal-to-noise ratio (SNR). The current output DAC is used in a 3rd order multibit...... CT ∆Σ ADC for audio applications, designed in a 0.18 µm CMOS process, with active-RC integrators, a 7-level Flash ADC quantizer and current output DAC for the feedback. From simulations the ADC achieves a dynamic range of 95.0 dB in the audio band, with a current consumption of 284 µA for a 1.7 V...

Interleukin-2 signaling pathway analysis by quantitative phosphoproteomics

DEFF Research Database (Denmark)

Osinalde, Nerea; Moss, Helle; Arrizabalaga, Onetsine

2011-01-01

among which 79 were found with increased abundance in the tyrosine-phosphorylated complexes, including several previously not reported IL-2 downstream effectors. Combinatorial site-specific phosphoproteomic analysis resulted in identification of 99 phosphorylated sites mapping to the identified proteins...... with increased abundance in the tyrosine-phosphorylated complexes, of which 34 were not previously described. In addition, chemical inhibition of the identified IL-2-mediated JAK, PI3K and MAPK signaling pathways, resulted in distinct alteration on the IL-2 dependent proliferation....

Symbolic transfer entropy-based premature signal analysis

International Nuclear Information System (INIS)

Wang Jun; Yu Zheng-Feng

2012-01-01

In this paper, we use symbolic transfer entropy to study the coupling strength between premature signals. Numerical experiments show that three types of signal couplings are in the same direction. Among them, normal signal coupling is the strongest, followed by that of premature ventricular contractions, and that of atrial premature beats is the weakest. The T test shows that the entropies of the three signals are distinct. Symbolic transfer entropy requires less data, can distinguish the three types of signals and has very good computational efficiency. (interdisciplinary physics and related areas of science and technology)

Signal sensitivity of alternating current potential drop measurement for crack detection of conductive substrate with tunable coating materials through finite element modeling

International Nuclear Information System (INIS)

Rao, Simha Sandeep; Zhao, Huijuan; Liu, Ming; Peng, Fei; Zhang, Bo

2016-01-01

We adopt a finite element numerical modeling approach to investigate the electromagnetic coupling effect of two parallel electric conductors with tunable electric conductivity σ and magnetic permeability μ . For two parallel conductors C and S ( μ C   ⋅  σ C   ≤  μ S   ⋅  σ S ), we find that the shape of current density profile of conductor S is dependent on the product of μ C   ⋅  σ C , while the magnitude is determined by the AC current frequency f . On the other hand, the frequency f affects not only the shape but also the magnitude of the current density profile of conductor C. We further adopt a coplanar model to investigate the signal sensitivity of alternating current potential drop (ACPD) measurement for both surface crack and inner crack detection. We find that with modified coating materials (lower electric conductivity and higher magnetic permeability, compared with the substrate material properties), the crack detection signal sensitivity can be greatly enhanced for both the cracks within the coating and at the coating/substrate interface, where cracks are most commonly encountered in real situations. (paper)

Urban Traffic Signal System Control Structural Optimization Based on Network Analysis

Directory of Open Access Journals (Sweden)

Li Wang

2013-01-01

Full Text Available Advanced urban traffic signal control systems such as SCOOT and SCATS normally coordinate traffic network using multilevel hierarchical control mechanism. In this mechanism, several key intersections will be selected from traffic signal network and the network will be divided into different control subareas. Traditionally, key intersection selection and control subareas division are executed according to dynamic traffic counts and link length between intersections, which largely rely on traffic engineers’ experience. However, it omits important inherent characteristics of traffic network topology. In this paper, we will apply network analysis approach into these two aspects for traffic system control structure optimization. Firstly, the modified C-means clustering algorithm will be proposed to assess the importance of intersections in traffic network and furthermore determine the key intersections based on three indexes instead of merely on traffic counts in traditional methods. Secondly, the improved network community discovery method will be used to give more reasonable evidence in traffic control subarea division. Finally, to test the effectiveness of network analysis approach, a hardware-in-loop simulation environment composed of regional traffic control system, microsimulation software and signal controller hardware, will be built. Both traditional method and proposed approach will be implemented on simulation test bed to evaluate traffic operation performance indexes, for example, travel time, stop times, delay and average vehicle speed. Simulation results show that the proposed network analysis approach can improve the traffic control system operation performance effectively.

Time-frequency feature analysis and recognition of fission neutrons signal based on support vector machine

International Nuclear Information System (INIS)

Jin Jing; Wei Biao; Feng Peng; Tang Yuelin; Zhou Mi

2010-01-01

Based on the interdependent relationship between fission neutrons ( 252 Cf) and fission chain ( 235 U system), the paper presents the time-frequency feature analysis and recognition in fission neutron signal based on support vector machine (SVM) through the analysis on signal characteristics and the measuring principle of the 252 Cf fission neutron signal. The time-frequency characteristics and energy features of the fission neutron signal are extracted by using wavelet decomposition and de-noising wavelet packet decomposition, and then applied to training and classification by means of support vector machine based on statistical learning theory. The results show that, it is effective to obtain features of nuclear signal via wavelet decomposition and de-noising wavelet packet decomposition, and the latter can reflect the internal characteristics of the fission neutron system better. With the training accomplished, the SVM classifier achieves an accuracy rate above 70%, overcoming the lack of training samples, and verifying the effectiveness of the algorithm. (authors)

Large-Signal Code TESLA: Current Status and Recent Development

National Research Council Canada - National Science Library

Chernyavskiy, Igor A; Vlasov, Alexander N; Cooke, Simon J; Abe, David K; Levush, Baruch; Antonsen, Jr., Thomas M; Nguyen, Khanh T

2008-01-01

.... One such tool is the large-signal code TESLA, which was successfully applied for the modeling of single-beam and multiple-beam klystron devices at the Naval Research Laboratory and which is now used by number of U.S. companies...

Dancing with Hormones: A Current Perspective of Nitrate Signaling and Regulation in Arabidopsis

Directory of Open Access Journals (Sweden)

Peizhu Guan

2017-09-01

Full Text Available In nature and agriculture, nitrate availability is a main environmental cue for plant growth, development and stress responses. Nitrate signaling and regulation are hence at the center of communications between plant intrinsic programs and the environment. It is also well known that endogenous phytohormones play numerous critical roles in integrating extrinsic cues and intrinsic responses, regulating and refining almost all aspects of plant growth, development and stress responses. Therefore, interaction between nitrate and phytohormones, such as auxins, cytokinins, abscisic acid, gibberellins, and ethylene, is prevalent. The growing evidence indicates that biosynthesis, de-conjugation, transport, and signaling of hormones are partly controlled by nitrate signaling. Recent advances with nitrate signaling and transcriptional regulation in Arabidopsis give rise to new paradigms. Given the comprehensive nitrate transport, sensing, signaling and regulations at the level of the cell and organism, nitrate itself is a local and long-distance signal molecule, conveying N status at the whole-plant level. A direct molecular link between nitrate signaling and cell cycle progression was revealed with TEOSINTE BRANCHED1/CYCLOIDEA/PROLIFERATING CELL FACTOR1-20 (TCP20 – NIN-LIKE PROTEIN 6/7 (NLP6/7 regulatory nexus. NLPs are key regulators of nitrogen responses in plants. TCPs function as the main regulators of plant morphology and architecture, with the emerging role as integrators of plant developmental responses to the environment. By analogy with auxin being proposed as a plant morphogen, nitrate may be an environmental morphogen. The morphogen-gradient-dependent and cell-autonomous mechanisms of nitrate signaling and regulation are an integral part of cell growth and cell identification. This is especially true in root meristem growth that is regulated by intertwined nitrate, phytohormones, and glucose-TOR signaling pathways. Furthermore, the nitrate

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

Science.gov (United States)

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

2018-03-01

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

Analysis of pulse-shape discrimination techniques for BC501A using GHz digital signal processing

International Nuclear Information System (INIS)

Rooney, B.D.; Dinwiddie, D.R.; Nelson, M.A.; Rawool-Sullivan, Mohini W.

2001-01-01

A comparison study of pulse-shape analysis techniques was conducted for a BC501A scintillator using digital signal processing (DSP). In this study, output signals from a preamplifier were input directly into a 1 GHz analog-to-digital converter. The digitized data obtained with this method was post-processed for both pulse-height and pulse-shape information. Several different analysis techniques were evaluated for neutron and gamma-ray pulse-shape discrimination. It was surprising that one of the simplest and fastest techniques resulted in some of the best pulse-shape discrimination results. This technique, referred to here as the Integral Ratio technique, was able to effectively process several thousand detector pulses per second. This paper presents the results and findings of this study for various pulse-shape analysis techniques with digitized detector signals.

Sentiment analysis for PTSD signals

CERN Document Server

Kagan, Vadim; Sapounas, Demetrios

2013-01-01

This book describes a computational framework for real-time detection of psychological signals related to Post-Traumatic Stress Disorder (PTSD) in online text-based posts, including blogs and web forums. Further, it explores how emerging computational techniques such as sentiment mining can be used in real-time to identify posts that contain PTSD-related signals, flag those posts, and bring them to the attention of psychologists, thus providing an automated flag and referral capability.

Variable current speed controller for eddy current motors

Science.gov (United States)

Gerth, H.L.; Bailey, J.M.; Casstevens, J.M.; Dixon, J.H.; Griffith, B.O.; Igou, R.E.

1982-03-12

A speed control system for eddy current motors is provided in which the current to the motor from a constant frequency power source is varied by comparing the actual motor speed signal with a setpoint speed signal to control the motor speed according to the selected setpoint speed. A three-phase variable voltage autotransformer is provided for controlling the voltage from a three-phase power supply. A corresponding plurality of current control resistors is provided in series with each phase of the autotransformer output connected to inputs of a three-phase motor. Each resistor is connected in parallel with a set of normally closed contacts of plurality of relays which are operated by control logic. A logic circuit compares the selected speed with the actual motor speed obtained from a digital tachometer monitoring the motor spindle speed and operated the relays to add or substract resistance equally in each phase of the motor input to vary the motor current to control the motor at the selected speed.

LASSIE: the large analogue signal and scaling information environment for FAIR

International Nuclear Information System (INIS)

Hoffmann, T.; Braeuning, H.; Haseitl, R.

2012-01-01

At FAIR, the Facility for Antiproton and Ion Research, several new accelerators and storage rings such as the SIS-100, HESR, CR, the inter-connecting HEBT beam lines, S-FRS and experiments will be built. All of these installations are equipped with beam diagnostic devices and other components, which deliver time-resolved analogue signals to show status, quality and performance of the accelerators. These signals can originate from particle detectors such as ionization chambers and plastic scintillators, but also from adapted output signals of transformers, collimators, magnet functions, RF cavities and others. To visualize and precisely correlate the time axis of all input signals a dedicated FESA based data acquisition and analysis system named LASSIE, the Large Analogue Signal and Scaling Information Environment, is currently being developed. The main operation mode of LASSIE is currently pulse counting with latching VME scaler boards. Later enhancements for ADC, QDC, or TDC digitization in the future are foreseen. The concept, features and challenges of this large distributed data acquisition system are presented. (authors)

Analysis and Classification of Acoustic Emission Signals During Wood Drying Using the Principal Component Analysis

Energy Technology Data Exchange (ETDEWEB)

Kang, Ho Yang [Korea Research Institute of Standards and Science, Daejeon (Korea, Republic of); Kim, Ki Bok [Chungnam National University, Daejeon (Korea, Republic of)

2003-06-15

In this study, acoustic emission (AE) signals due to surface cracking and moisture movement in the flat-sawn boards of oak (Quercus Variablilis) during drying under the ambient conditions were analyzed and classified using the principal component analysis. The AE signals corresponding to surface cracking showed higher in peak amplitude and peak frequency, and shorter in rise time than those corresponding to moisture movement. To reduce the multicollinearity among AE features and to extract the significant AE parameters, correlation analysis was performed. Over 99% of the variance of AE parameters could be accounted for by the first to the fourth principal components. The classification feasibility and success rate were investigated in terms of two statistical classifiers having six independent variables (AE parameters) and six principal components. As a result, the statistical classifier having AE parameters showed the success rate of 70.0%. The statistical classifier having principal components showed the success rate of 87.5% which was considerably than that of the statistical classifier having AE parameters

Analysis and Classification of Acoustic Emission Signals During Wood Drying Using the Principal Component Analysis

International Nuclear Information System (INIS)

Kang, Ho Yang; Kim, Ki Bok

2003-01-01

In this study, acoustic emission (AE) signals due to surface cracking and moisture movement in the flat-sawn boards of oak (Quercus Variablilis) during drying under the ambient conditions were analyzed and classified using the principal component analysis. The AE signals corresponding to surface cracking showed higher in peak amplitude and peak frequency, and shorter in rise time than those corresponding to moisture movement. To reduce the multicollinearity among AE features and to extract the significant AE parameters, correlation analysis was performed. Over 99% of the variance of AE parameters could be accounted for by the first to the fourth principal components. The classification feasibility and success rate were investigated in terms of two statistical classifiers having six independent variables (AE parameters) and six principal components. As a result, the statistical classifier having AE parameters showed the success rate of 70.0%. The statistical classifier having principal components showed the success rate of 87.5% which was considerably than that of the statistical classifier having AE parameters

X-ray tube current control

International Nuclear Information System (INIS)

Dupuis, W.A.; Resnick, T.A.

1982-01-01

A closed loop feedback system for controlling the current output of an x-ray tube. The system has circuitry for improving the transient response and stability of the x-ray tube current over a substantial nonlinear portion of the tube current production characteristic. The system includes a reference generator for applying adjustable step function reference signals representing desired tube currents. The system also includes means for instantaneous sensing of actual tube current. An error detector compares the value of actual and reference tube current and produces an error signal as a function of their difference. The system feedback loop includes amplification circuitry for controlling x-ray tube filament dc voltage to regulate tube current as a function of the error signal value. The system also includes compensation circuitry, between the reference generator and the amplification circuitry, to vary the loop gain of the feedback control system as a function of the reference magnitude

Investigating discrimination model of the signals obtained by eddy current testing

International Nuclear Information System (INIS)

Wache, G.; Rivenez, J.

1986-01-01

A software using an eddy current system controlled by a desk computer has been developed in order to separate a characteristic physical value among several parts. The numerical process involved uses multiparameter measurements done previously on significant parts belonging to the same class. The analysis presented deals with hardness testing of steel bolts in relation with heat-treatment, but other applications dealing with either micro structure check or defect investigation, could be done in the future by using a similar method

Transient signal analysis in power reactors by means of the wavelet technique

International Nuclear Information System (INIS)

Wentzeis, Luis

1999-01-01

The application of the wavelet technique, had enabled to study the time evolution of the properties (amplitude and frequency content) of a signals set, measured in the Embalse nuclear power plant (CANDU 600 M we), in the low frequency range and for different operating conditions. Particularly, by means of this technique, we studied the time evolution of the signals in the non-stationary state of the reactor (during a raise in power), where the Fourier analysis results inadequate. (author)

Use of eddy current mixes to solve a weld examination application

International Nuclear Information System (INIS)

Ward, R.C.; LaBoissonniere, A.

1995-01-01

The augmentation of typical nondestructive (i.e., ultrasound) weld inspection techniques by the use of eddy current tools may significantly enhance the quality and reliability of weld inspections. One recent example is the development of an eddy current technique for use in the examination of BWR core shroud welds, where multi-frequency mixes are used to eliminate signals coming from the weld material so that the examination of the heat affected zone is enhanced. An analysis tool most commonly associated with ultrasound examinations, the C-Scan based on gated information, may be implemented with eddy current data to enhance analysis

Stochastic resonance is applied to quantitative analysis for weak chromatographic signal of glyburide in plasma

International Nuclear Information System (INIS)

Zhang Wei; Xiang Bingren; Wu Yanwei; Shang Erxin

2005-01-01

Based on the theory of stochastic resonance, a new method carried on the quantitive analysis to weak chromatographic signal of glyburide in plasma, which was embedded in the noise background and the signal-to-noise ratio (SNR) of HPLC-UV is enhanced remarkably. This method enhances the quantification limit to 1 ng ml -1 , which is the same as HPLC-MS, and makes it possible to detect the weak signal accurately by HPLC-UV, which was not suitable before. The results showed good recovery and linear range from 1 to 50 ng ml -1 of glyburide in plasma and the method can be used for quantitative analysis of glyburide

Analysis of Seasonal Signal in GPS Short-Baseline Time Series

Science.gov (United States)

Wang, Kaihua; Jiang, Weiping; Chen, Hua; An, Xiangdong; Zhou, Xiaohui; Yuan, Peng; Chen, Qusen

2018-04-01

Proper modeling of seasonal signals and their quantitative analysis are of interest in geoscience applications, which are based on position time series of permanent GPS stations. Seasonal signals in GPS short-baseline (paper, to better understand the seasonal signal in GPS short-baseline time series, we adopted and processed six different short-baselines with data span that varies from 2 to 14 years and baseline length that varies from 6 to 1100 m. To avoid seasonal signals that are overwhelmed by noise, each of the station pairs is chosen with significant differences in their height (> 5 m) or type of the monument. For comparison, we also processed an approximately zero baseline with a distance of pass-filtered (BP) noise is valid for approximately 40% of the baseline components, and another 20% of the components can be best modeled by a combination of the first-order Gauss-Markov (FOGM) process plus white noise (WN). The TEM displacements are then modeled by considering the monument height of the building structure beneath the GPS antenna. The median contributions of TEM to the annual amplitude in the vertical direction are 84% and 46% with and without additional parts of the monument, respectively. Obvious annual signals with amplitude > 0.4 mm in the horizontal direction are observed in five short-baselines, and the amplitudes exceed 1 mm in four of them. These horizontal seasonal signals are likely related to the propagation of daily/sub-daily TEM displacement or other signals related to the site environment. Mismodeling of the tropospheric delay may also introduce spurious seasonal signals with annual amplitudes of 5 and 2 mm, respectively, for two short-baselines with elevation differences greater than 100 m. The results suggest that the monument height of the additional part of a typical GPS station should be considered when estimating the TEM displacement and that the tropospheric delay should be modeled cautiously, especially with station pairs with

Stability analysis of offshore wind farm and marine current farm

Science.gov (United States)

Shawon, Mohammad Hasanuzzaman

-trend for large electric energy production using offshore wind generators and marine current generators, respectively. Thus DFIG based offshore wind farm can be an economic solution to stabilize squirrel cage induction generator based marine current farm without installing any addition FACTS devices. This thesis first focuses on the stabilization of fixed speed IG based marine current farm using SDBR. Also stabilization of DFIG based variable speed wind farm utilizing SDBR is studied in this work. Finally a co-operative control strategy is proposed where DFIG is controlled in such a way that it can even provide necessary reactive power demand of induction generator, so that additional cost of FACTS devices can be avoided. In that way, the DFIGs of the offshore wind farm (OWF) will actively compensate the reactive power demand of adjacent IGs of the marine current farm (MCF) during grid fault. Detailed modeling and control scheme for the proposed system are demonstrated considering some realistic scenarios. The power system small signal stability analysis is also carried out by eigenvalue analysis for marine current generator topology, wind turbine generator topology and integrated topology. The relation between the modes and state variables are discussed in light of modal and sensitivity analyses. The results of theoretical analyses are verified by MATLAB/SIMULINK and laboratory standard power system simulator PSCAD/EMTDC.

Programmable delay circuit for sparker signal analysis

Digital Repository Service at National Institute of Oceanography (India)

Pathak, D.

The sparker echo signal had been recorded along with the EPC recorder trigger on audio cassettes in a dual channel analog recorder. The sparker signal in the analog form had to be digitised for further signal processing techniques to be performed...

Advanced Signal Analysis for Forensic Applications of Ground Penetrating Radar

Energy Technology Data Exchange (ETDEWEB)

Steven Koppenjan; Matthew Streeton; Hua Lee; Michael Lee; Sashi Ono

2004-06-01

Ground penetrating radar (GPR) systems have traditionally been used to image subsurface objects. The main focus of this paper is to evaluate an advanced signal analysis technique. Instead of compiling spatial data for the analysis, this technique conducts object recognition procedures based on spectral statistics. The identification feature of an object type is formed from the training vectors by a singular-value decomposition procedure. To illustrate its capability, this procedure is applied to experimental data and compared to the performance of the neural-network approach.

Analysis of strain distribution and critical current of superconductors based on a strain-critical current measurement system

International Nuclear Information System (INIS)

Liu Fang; Wu Yu; Long Feng

2010-01-01

Based on Pacman device which is widely used to investigate the axial strain dependence of the critical current in superconductors, the finite element analysis method is employed to carry out the force analysis of the spring and the superconducting strand, thereby the axial and lateral strain distributions of the superconducting strand are obtained. According to the two extreme assumptions(low inter-filament resistance and high inter-filament resistance), the effects of the strain homogeneity at the cross section of the superconductor on the critical current is analyzed combined with the Nb 3 Sn deviatoric strain-critical current scaling law. (authors)

Pre-earthquake signals – Part II: Flow of battery currents in the crust

Directory of Open Access Journals (Sweden)

F. T. Freund

2007-09-01

Full Text Available When rocks are subjected to stress, dormant electronic charge carriers are activated. They turn the stressed rock volume into a battery, from where currents can flow out. The charge carriers are electrons and defect electrons, also known as positive holes or pholes for short. The boundary between stressed and unstressed rock acts as a potential barrier that lets pholes pass but blocks electrons. One can distinguish two situations in the Earth's crust: (i only pholes spread out of a stressed rock volume into the surrounding unstressed rocks. This is expected to lead to a positive surface charge over a wide area around the future epicenter, to perturbations in the ionosphere, to stimulated infrared emission from the ground, to ionization of the near-ground air, to cloud formation and to other phenomena that have been reported to precede major earthquakes. (ii both pholes and electrons flow out of the stressed rock volume along different paths, sideward into the relatively cool upper layers of the crust and downward into the hot lower crust. This situation, which is likely to be realized late in the earthquake preparation process, is necessary for the battery circuit to close and for transient electric currents to flow. If burst-like, these currents should lead to the emission of low frequency electromagnetic radiation. Understanding how electronic charge carriers are stress-activated in rocks, how they spread or flow probably holds the key to deciphering a wide range of pre-earthquake signals. It opens the door to a global earthquake early warning system, provided resources are pooled through a concerted and constructive community effort, including seismologists, with international participation.

Transient analysis for alternating over-current characteristics of HTSC power transmission cable

Science.gov (United States)

Lim, S. H.; Hwang, S. D.

2006-10-01

In this paper, the transient analysis for the alternating over-current distribution in case that the over-current was applied for a high-TC superconducting (HTSC) power transmission cable was performed. The transient analysis for the alternating over-current characteristics of HTSC power transmission cable with multi-layer is required to estimate the redistribution of the over-current between its conducting layers and to protect the cable system from the over-current in case that the quench in one or two layers of the HTSC power cable happens. For its transient analysis, the resistance generation of the conducting layers for the alternating over-current was reflected on its equivalent circuit, based on the resistance equation obtained by applying discrete Fourier transform (DFT) for the voltage and the current waveforms of the HTSC tape, which comprises each layer of the HTSC power transmission cable. It was confirmed through the numerical analysis on its equivalent circuit that after the current redistribution from the outermost layer into the inner layers first happened, the fast current redistribution between the inner layers developed as the amplitude of the alternating over-current increased.

Aggregation of Electric Current Consumption Features to Extract Maintenance KPIs

Science.gov (United States)

Simon, Victor; Johansson, Carl-Anders; Galar, Diego

2017-09-01

All electric powered machines offer the possibility of extracting information and calculating Key Performance Indicators (KPIs) from the electric current signal. Depending on the time window, sampling frequency and type of analysis, different indicators from the micro to macro level can be calculated for such aspects as maintenance, production, energy consumption etc. On the micro-level, the indicators are generally used for condition monitoring and diagnostics and are normally based on a short time window and a high sampling frequency. The macro indicators are normally based on a longer time window with a slower sampling frequency and are used as indicators for overall performance, cost or consumption. The indicators can be calculated directly from the current signal but can also be based on a combination of information from the current signal and operational data like rpm, position etc. One or several of those indicators can be used for prediction and prognostics of a machine's future behavior. This paper uses this technique to calculate indicators for maintenance and energy optimization in electric powered machines and fleets of machines, especially machine tools.

Study of time-domain digital pulse shaping algorithms for nuclear signals

International Nuclear Information System (INIS)

Zhou Jianbin; Tuo Xianguo; Zhu Xing; Liu Yi; Zhou Wei; Lei Jiarong

2012-01-01

With the development on high-speed integrated circuit, fast high resolution sampling ADC and digital signal processors are replacing analog shaping amplifier circuit. This paper firstly presents the numerical analysis and simulation on R-C shaping circuit model and C-R shaping circuit model. Mathematic models are established based on 1 st order digital differential method and Kirchhoff Current Law in time domain, and a simulation and error evaluation experiment on an ideal digital signal are carried out with Excel VBA. A digital shaping test for a semiconductor X-ray detector in real time is also presented. Then a numerical analysis for Sallen-Key(S-K) low-pass filter circuit model is implemented based on the analysis of digital R-C and digital C-R shaping methods. By applying the 2 nd order non-homogeneous differential equation,the authors implement a digital Gaussian filter model for a standard exponential-decaying signal and a nuclear pulse signal. Finally, computer simulations and experimental tests are carried out and the results show the possibility of the digital pulse processing algorithms. (authors)

Current-induced atomic dynamics, instabilities, and Raman signals

DEFF Research Database (Denmark)

Lu, Jing Tao; Brandbyge, Mads; Hedegard, Per

2012-01-01

We derive and employ a semiclassical Langevin equation obtained from path integrals to describe the ionic dynamics of a molecular junction in the presence of electrical current. The electronic environment serves as an effective nonequilibrium bath. The bath results in random forces describing Joule...... heating, current-induced forces including the nonconservative wind force, dissipative frictional forces, and an effective Lorentz-type force due to the Berry phase of the nonequilibrium electrons. Using a generic two-level molecular model, we highlight the importance of both current-induced forces...... and Joule heating for the stability of the system. We compare the impact of the different forces, and the wide-band approximation for the electronic structure on our result. We examine the current-induced instabilities (excitation of runaway "waterwheel" modes) and investigate the signature...

Current status of methods for shielding analysis

International Nuclear Information System (INIS)

Engle, W.W.

1980-01-01

Current methods used in shielding analysis and recent improvements in those methods are discussed. The status of methods development is discussed based on needs cited at the 1977 International Conference on Reactor Shielding. Additional areas where methods development is needed are discussed

Automated Bearing Fault Diagnosis Using 2D Analysis of Vibration Acceleration Signals under Variable Speed Conditions

Directory of Open Access Journals (Sweden)

Sheraz Ali Khan

2016-01-01

Full Text Available Traditional fault diagnosis methods of bearings detect characteristic defect frequencies in the envelope power spectrum of the vibration signal. These defect frequencies depend upon the inherently nonstationary shaft speed. Time-frequency and subband signal analysis of vibration signals has been used to deal with random variations in speed, whereas design variations require retraining a new instance of the classifier for each operating speed. This paper presents an automated approach for fault diagnosis in bearings based upon the 2D analysis of vibration acceleration signals under variable speed conditions. Images created from the vibration signals exhibit unique textures for each fault, which show minimal variation with shaft speed. Microtexture analysis of these images is used to generate distinctive fault signatures for each fault type, which can be used to detect those faults at different speeds. A k-nearest neighbor classifier trained using fault signatures generated for one operating speed is used to detect faults at all the other operating speeds. The proposed approach is tested on the bearing fault dataset of Case Western Reserve University, and the results are compared with those of a spectrum imaging-based approach.

Design of microcontroller-based EMG and the analysis of EMG signals.

Science.gov (United States)

Güler, Nihal Fatma; Hardalaç, Firat

2002-04-01

In this work, a microcontroller-based EMG designed and tested on 40 patients. When the patients are in rest, the fast Fourier transform (FFT) analysis was applied to EMG signals recorded from right leg peroneal region. The histograms are constructed from the results of the FFT analysis. The analysis results shows that the amplitude of fibrillation potential of the muscle fiber of 30 patients measured from peroneal region is low and the duration is short. This is the reason why the motor nerves degenerated and 10 patients were found to be healthy.

Signal-independent timescale analysis (SITA) and its application for neural coding during reaching and walking.

Science.gov (United States)

Zacksenhouse, Miriam; Lebedev, Mikhail A; Nicolelis, Miguel A L

2014-01-01

What are the relevant timescales of neural encoding in the brain? This question is commonly investigated with respect to well-defined stimuli or actions. However, neurons often encode multiple signals, including hidden or internal, which are not experimentally controlled, and thus excluded from such analysis. Here we consider all rate modulations as the signal, and define the rate-modulations signal-to-noise ratio (RM-SNR) as the ratio between the variance of the rate and the variance of the neuronal noise. As the bin-width increases, RM-SNR increases while the update rate decreases. This tradeoff is captured by the ratio of RM-SNR to bin-width, and its variations with the bin-width reveal the timescales of neural activity. Theoretical analysis and simulations elucidate how the interactions between the recovery properties of the unit and the spectral content of the encoded signals shape this ratio and determine the timescales of neural coding. The resulting signal-independent timescale analysis (SITA) is applied to investigate timescales of neural activity recorded from the motor cortex of monkeys during: (i) reaching experiments with Brain-Machine Interface (BMI), and (ii) locomotion experiments at different speeds. Interestingly, the timescales during BMI experiments did not change significantly with the control mode or training. During locomotion, the analysis identified units whose timescale varied consistently with the experimentally controlled speed of walking, though the specific timescale reflected also the recovery properties of the unit. Thus, the proposed method, SITA, characterizes the timescales of neural encoding and how they are affected by the motor task, while accounting for all rate modulations.

Optimal Signal Quality Index for Photoplethysmogram Signals

Directory of Open Access Journals (Sweden)

Mohamed Elgendi

2016-09-01

Full Text Available A photoplethysmogram (PPG is a noninvasive circulatory signal related to the pulsatile volume of blood in tissue and is typically collected by pulse oximeters. PPG signals collected via mobile devices are prone to artifacts that negatively impact measurement accuracy, which can lead to a significant number of misleading diagnoses. Given the rapidly increased use of mobile devices to collect PPG signals, developing an optimal signal quality index (SQI is essential to classify the signal quality from these devices. Eight SQIs were developed and tested based on: perfusion, kurtosis, skewness, relative power, non-stationarity, zero crossing, entropy, and the matching of systolic wave detectors. Two independent annotators annotated all PPG data (106 recordings, 60 s each and a third expert conducted the adjudication of differences. The independent annotators labeled each PPG signal with one of the following labels: excellent, acceptable or unfit for diagnosis. All indices were compared using Mahalanobis distance, linear discriminant analysis, quadratic discriminant analysis, and support vector machine with leave-one-out cross-validation. The skewness index outperformed the other seven indices in differentiating between excellent PPG and acceptable, acceptable combined with unfit, and unfit recordings, with overall F 1 scores of 86.0%, 87.2%, and 79.1%, respectively.

Optimal Signal Quality Index for Photoplethysmogram Signals.

Science.gov (United States)

Elgendi, Mohamed

2016-09-22

A photoplethysmogram (PPG) is a noninvasive circulatory signal related to the pulsatile volume of blood in tissue and is typically collected by pulse oximeters. PPG signals collected via mobile devices are prone to artifacts that negatively impact measurement accuracy, which can lead to a significant number of misleading diagnoses. Given the rapidly increased use of mobile devices to collect PPG signals, developing an optimal signal quality index (SQI) is essential to classify the signal quality from these devices. Eight SQIs were developed and tested based on: perfusion, kurtosis, skewness, relative power, non-stationarity, zero crossing, entropy, and the matching of systolic wave detectors. Two independent annotators annotated all PPG data (106 recordings, 60 s each) and a third expert conducted the adjudication of differences. The independent annotators labeled each PPG signal with one of the following labels: excellent, acceptable or unfit for diagnosis. All indices were compared using Mahalanobis distance, linear discriminant analysis, quadratic discriminant analysis, and support vector machine with leave-one-out cross-validation. The skewness index outperformed the other seven indices in differentiating between excellent PPG and acceptable, acceptable combined with unfit, and unfit recordings, with overall F 1 scores of 86.0%, 87.2%, and 79.1%, respectively.

Evaluation of the autoregression time-series model for analysis of a noisy signal

International Nuclear Information System (INIS)

Allen, J.W.

1977-01-01

The autoregression (AR) time-series model of a continuous noisy signal was statistically evaluated to determine quantitatively the uncertainties of the model order, the model parameters, and the model's power spectral density (PSD). The result of such a statistical evaluation enables an experimenter to decide whether an AR model can adequately represent a continuous noisy signal and be consistent with the signal's frequency spectrum, and whether it can be used for on-line monitoring. Although evaluations of other types of signals have been reported in the literature, no direct reference has been found to AR model's uncertainties for continuous noisy signals; yet the evaluation is necessary to decide the usefulness of AR models of typical reactor signals (e.g., neutron detector output or thermocouple output) and the potential of AR models for on-line monitoring applications. AR and other time-series models for noisy data representation are being investigated by others since such models require fewer parameters than the traditional PSD model. For this study, the AR model was selected for its simplicity and conduciveness to uncertainty analysis, and controlled laboratory bench signals were used for continuous noisy data. (author)

Assuring SS7 dependability: A robustness characterization of signaling network elements

Science.gov (United States)

Karmarkar, Vikram V.

1994-04-01

Current and evolving telecommunication services will rely on signaling network performance and reliability properties to build competitive call and connection control mechanisms under increasing demands on flexibility without compromising on quality. The dimensions of signaling dependability most often evaluated are the Rate of Call Loss and End-to-End Route Unavailability. A third dimension of dependability that captures the concern about large or catastrophic failures can be termed Network Robustness. This paper is concerned with the dependability aspects of the evolving Signaling System No. 7 (SS7) networks and attempts to strike a balance between the probabilistic and deterministic measures that must be evaluated to accomplish a risk-trend assessment to drive architecture decisions. Starting with high-level network dependability objectives and field experience with SS7 in the U.S., potential areas of growing stringency in network element (NE) dependability are identified to improve against current measures of SS7 network quality, as per-call signaling interactions increase. A sensitivity analysis is presented to highlight the impact due to imperfect coverage of duplex network component or element failures (i.e., correlated failures), to assist in the setting of requirements on NE robustness. A benefit analysis, covering several dimensions of dependability, is used to generate the domain of solutions available to the network architect in terms of network and network element fault tolerance that may be specified to meet the desired signaling quality goals.

Tutorial on beam current monitoring

International Nuclear Information System (INIS)

Webber, Robert C.

2000-01-01

This paper is a tutorial level review covering a wide range of aspects related to charged particle beam current measurement. The tutorial begins with a look at the characteristics of the beam as a signal source, the associated electromagnetic fields, the influence of the typical accelerator environment on those fields, and the usual means of modifying and controlling that environment to facilitate beam current measurement. Short descriptions of three quite different types of current monitors are presented and a quantitative review of the classical transformer circuit is given. Recognizing that environmental noise pick-up may present a large source of error in quantitative measurements, signal handling considerations are given considerable attention using real-life examples. An example of a successful transport line beam current monitor implementation is presented and the tutorial concludes with a few comments about signal processing and current monitor calibration issues

A Signal Based Triangular Structuring Element for Mathematical Morphological Analysis and Its Application in Rolling Element Bearing Fault Diagnosis

Directory of Open Access Journals (Sweden)

Zhaowen Chen

2014-01-01

Full Text Available Mathematical morphology (MM is an efficient nonlinear signal processing tool. It can be adopted to extract fault information from bearing signal according to a structuring element (SE. Since the bearing signal features differ for every unique cause of failure, the SEs should be well tailored to extract the fault feature from a particular signal. In the following, a signal based triangular SE according to the statistics of the magnitude of a vibration signal is proposed, together with associated methodology, which processes the bearing signal by MM analysis based on proposed SE to get the morphology spectrum of a signal. A correlation analysis on morphology spectrum is then employed to obtain the final classification of bearing faults. The classification performance of the proposed method is evaluated by a set of bearing vibration signals with inner race, ball, and outer race faults, respectively. Results show that all faults can be detected clearly and correctly. Compared with a commonly used flat SE, the correlation analysis on morphology spectrum with proposed SE gives better performance at fault diagnosis of bearing, especially the identification of the location of outer race fault and the level of fault severity.

Improving detector signal processing with pulse height analysis in Moessbauer spectrometers

International Nuclear Information System (INIS)

Pechousek, Jiri; Mashlan, Miroslav; Frydrych, Jiri; Jancik, Dalibor; Prochazka, Roman

2007-01-01

A plenty of different programming techniques and instrument solutions are used in the development of Moessbauer spectrometers. Each of them should provide a faster spectrum accumulation process, increased productivity of measurements, decreased nonlinearity of the velocity scale, etc. The well known virtual instrumentation programming method has been used to design a computer-based Moessbauer spectrometer. Hardware solution was based on two commercially-available PCI modules produced by National Instruments Co. Virtual Moessbauer spectrometer is implemented by the graphical programming language LabVIEW 7 Express. This design environment allows to emulate the multichannel analyzer on the digital oscilloscope platform. This is a novel method based on Waveform Peak Detection function which allows detailed analysis of the acquired signal. The optimal treatment of the detector signal from various detector types is achieved by mathematical processing only. As a result, the possibility of an increase of signal/noise ratio is presented.

Techniques for processing remote field eddy current signals from bend regions of steam generator tubes of prototype fast breeder reactor

Energy Technology Data Exchange (ETDEWEB)

Thirunavukkarasu, S. [Non Destructive Evaluation Division, Indira Gandhi Centre for Atomic Research, Kalpakkam, TN 603 102 (India); Rao, B.P.C., E-mail: bpcrao@igcar.gov.in [Non Destructive Evaluation Division, Indira Gandhi Centre for Atomic Research, Kalpakkam, TN 603 102 (India); Jayakumar, T.; Raj, Baldev [Non Destructive Evaluation Division, Indira Gandhi Centre for Atomic Research, Kalpakkam, TN 603 102 (India)

2011-04-15

Steam generator (SG) is one of the most critical components of sodium cooled fast breeder reactor. Remote field eddy current (RFEC) technique has been chosen for in-service inspection (ISI) of these ferromagnetic SG tubes made of modified 9Cr-1Mo steel (Grade 91). Expansion bends are provided in the SGs to accommodate differential thermal expansion. During ISI using RFEC technique, in expansion bend regions, exciter-receiver coil misalignment, bending stresses, probe wobble and magnetic permeability variations produce disturbing noise hindering detection of defects. Fourier filtering, cross-correlation and wavelet transform techniques have been studied for noise reduction as well as enhancement of RFEC signals of defects in bend regions, having machined grooves and localized defects. Performance of these three techniques has been compared using signal-to-noise ratio (SNR). Fourier filtering technique has shown better performance for noise reduction while cross-correlation technique has resulted in significant enhancement of signals. Wavelet transform technique has shown the combined capability of noise reduction and signal enhancement and resulted in unambiguous detection of 10% of wall loss grooves and localized defects in the bend regions with SNR better than 7 dB.

Single particle irradiation effect of digital signal processor

International Nuclear Information System (INIS)

Fan Si'an; Chen Kenan

2010-01-01

The single particle irradiation effect of high energy neutron on digital signal processor TMS320P25 in dynamic working condition has been studied. The influence of the single particle on the device has been explored through the acquired waveform and working current of TMS320P25. Analysis results, test data and test methods have also been presented. (authors)

Digital signal processing and spectral analysis for scientists concepts and applications

CERN Document Server

Alessio, Silvia Maria

2016-01-01

This book covers the basics of processing and spectral analysis of monovariate discrete-time signals. The approach is practical, the aim being to acquaint the reader with the indications for and drawbacks of the various methods and to highlight possible misuses. The book is rich in original ideas, visualized in new and illuminating ways, and is structured so that parts can be skipped without loss of continuity. Many examples are included, based on synthetic data and real measurements from the fields of physics, biology, medicine, macroeconomics etc., and a complete set of MATLAB exercises requiring no previous experience of programming is provided. Prior advanced mathematical skills are not needed in order to understand the contents: a good command of basic mathematical analysis is sufficient. Where more advanced mathematical tools are necessary, they are included in an Appendix and presented in an easy-to-follow way. With this book, digital signal processing leaves the domain of engineering to address the ne...

Phase-rectified signal averaging method to predict perinatal outcome in infants with very preterm fetal growth restriction- a secondary analysis of TRUFFLE-trial

NARCIS (Netherlands)

Lobmaier, Silvia M.; Mensing van Charante, Nico; Ferrazzi, Enrico; Giussani, Dino A.; Shaw, Caroline J.; Müller, Alexander; Ortiz, Javier U.; Ostermayer, Eva; Haller, Bernhard; Prefumo, Federico; Frusca, Tiziana; Hecher, Kurt; Arabin, Birgit; Thilaganathan, Baskaran; Papageorghiou, Aris T.; Bhide, Amarnath; Martinelli, Pasquale; Duvekot, Johannes J.; van Eyck, Jim; Visser, Gerard H A; Schmidt, Georg; Ganzevoort, Wessel; Lees, Christoph C.; Schneider, Karl T M; Bilardo, Caterina M.; Brezinka, Christoph; Diemert, Anke; Derks, Jan B.; Schlembach, Dietmar; Todros, Tullia; Valcamonico, Adriana; Marlow, Neil; van Wassenaer-Leemhuis, Aleid

2016-01-01

Background Phase-rectified signal averaging, an innovative signal processing technique, can be used to investigate quasi-periodic oscillations in noisy, nonstationary signals that are obtained from fetal heart rate. Phase-rectified signal averaging is currently the best method to predict survival

Phase-rectified signal averaging method to predict perinatal outcome in infants with very preterm fetal growth restriction- a secondary analysis of TRUFFLE-trial

NARCIS (Netherlands)

Lobmaier, Silvia M.; Mensing van Charante, Nico; Ferrazzi, Enrico; Giussani, Dino A.; Shaw, Caroline J.; Müller, Alexander; Ortiz, Javier U.; Ostermayer, Eva; Haller, Bernhard; Prefumo, Federico; Frusca, Tiziana; Hecher, Kurt; Arabin, Birgit; Thilaganathan, Baskaran; Papageorghiou, Aris T.; Bhide, Amarnath; Martinelli, Pasquale; Duvekot, Johannes J.; van Eyck, Jim; Visser, Gerard H. A.; Schmidt, Georg; Ganzevoort, Wessel; Lees, Christoph C.; Schneider, Karl T. M.; Bilardo, Caterina M.; Brezinka, Christoph; Diemert, Anke; Derks, Jan B.; Schlembach, Dietmar; Todros, Tullia; Valcamonico, Adriana; Marlow, Neil; van Wassenaer-Leemhuis, Aleid

2016-01-01

Phase-rectified signal averaging, an innovative signal processing technique, can be used to investigate quasi-periodic oscillations in noisy, nonstationary signals that are obtained from fetal heart rate. Phase-rectified signal averaging is currently the best method to predict survival after

Decoding a combined amplitude modulated and frequency modulated signal

DEFF Research Database (Denmark)

2015-01-01

The present disclosure relates to a method for decoding a combined AM/FM encoded signal, comprising the steps of: combining said encoded optical signal with light from a local oscillator configured with a local oscillator frequency; converting the combined local oscillator and encoded optical...... signal into one or more electrical signals by means of at least one opto-electrical converter having a predefined frequency bandwidth, thereby providing an amplified and encoded electrical signal having one or more encoded signal current(s), where one type of states have a higher oscillation frequency...... than other type of states; rectifying the encoded signal current(s), thereby obtaining an encoded power spectrum, wherein said power spectrum has different states, such as "0"-states and "1"-states, with different power levels such that they can be discriminated, said local oscillator frequency...

Complex Signal Kurtosis and Independent Component Analysis for Wideband Radio Frequency Interference Detection

Science.gov (United States)

Schoenwald, Adam; Mohammed, Priscilla; Bradley, Damon; Piepmeier, Jeffrey; Wong, Englin; Gholian, Armen

2016-01-01

Radio-frequency interference (RFI) has negatively implicated scientific measurements across a wide variation passive remote sensing satellites. This has been observed in the L-band radiometers SMOS, Aquarius and more recently, SMAP [1, 2]. RFI has also been observed at higher frequencies such as K band [3]. Improvements in technology have allowed wider bandwidth digital back ends for passive microwave radiometry. A complex signal kurtosis radio frequency interference detector was developed to help identify corrupted measurements [4]. This work explores the use of ICA (Independent Component Analysis) as a blind source separation technique to pre-process radiometric signals for use with the previously developed real and complex signal kurtosis detectors.

Joint Motion Quality in Chondromalacia Progression Assessed by Vibroacoustic Signal Analysis.

Science.gov (United States)

Bączkowicz, Dawid; Majorczyk, Edyta

2016-11-01

Because of the specific biomechanical environment of the patellofemoral joint, chondral disorders, including chondromalacia, often are observed in this articulation. Chondromalacia via pathologic changes in cartilage may lead to qualitative impairment of knee joint motion. To determine the patellofemoral joint motion quality in particular chondromalacia stages and to compare with controls. Retrospective, comparative study. Voivodship hospitals, university biomechanical laboratory. A total of 89 knees with chondromalacia (25 with stage I; 30 with stage II and 34 with stage III) from 50 patients and 64 control healthy knees (from 32 individuals). Vibroacoustic signal pattern analysis of joint motion quality. For all knees vibroacoustic signals were recorded. Each obtained signal was described by variation of mean square, mean range (R4), and power spectral density for frequency of 50-250 Hz (P1) and 250-450 Hz (P2) parameters. Differences between healthy controls and all chondromalacic knees as well as chondromalacia patellae groups were observed as an increase of analyzed parameters (P chondromalacia patellae was found. All chondromalacia groups were differentiated by the use of all analyzed parameters (P chondromalacia. Chondromalacia generates abnormal vibroacoustic signals, and there seems to be a relationship between the level of signal amplitude as well as frequency and cartilage destruction from the superficial layer to the subchondral bone. IV. Copyright © 2016 American Academy of Physical Medicine and Rehabilitation. Published by Elsevier Inc. All rights reserved.

Assessment of Homomorphic Analysis for Human Activity Recognition from Acceleration Signals.

Science.gov (United States)

Vanrell, Sebastian Rodrigo; Milone, Diego Humberto; Rufiner, Hugo Leonardo

2017-07-03

Unobtrusive activity monitoring can provide valuable information for medical and sports applications. In recent years, human activity recognition has moved to wearable sensors to deal with unconstrained scenarios. Accelerometers are the preferred sensors due to their simplicity and availability. Previous studies have examined several \\azul{classic} techniques for extracting features from acceleration signals, including time-domain, time-frequency, frequency-domain, and other heuristic features. Spectral and temporal features are the preferred ones and they are generally computed from acceleration components, leaving the acceleration magnitude potential unexplored. In this study, based on homomorphic analysis, a new type of feature extraction stage is proposed in order to exploit discriminative activity information present in acceleration signals. Homomorphic analysis can isolate the information about whole body dynamics and translate it into a compact representation, called cepstral coefficients. Experiments have explored several configurations of the proposed features, including size of representation, signals to be used, and fusion with other features. Cepstral features computed from acceleration magnitude obtained one of the highest recognition rates. In addition, a beneficial contribution was found when time-domain and moving pace information was included in the feature vector. Overall, the proposed system achieved a recognition rate of 91.21% on the publicly available SCUT-NAA dataset. To the best of our knowledge, this is the highest recognition rate on this dataset.

Signal processing of eddy current three-dimensional maps

International Nuclear Information System (INIS)

Birac, C.; David, D.; Lamant, D.

1987-01-01

Digital processing of eddy current three-dimensional maps improves accuracy of detection: flattening, filtering, computing deconvolution, mapping new variables,.., give new possibilities for difficult test problems. With simulation of defects, probes, probe travels, it is now possible to compute new eddy current processes, without machining defects or building probes

Improving the Molecular Ion Signal Intensity for In Situ Liquid SIMS Analysis.

Science.gov (United States)

Zhou, Yufan; Yao, Juan; Ding, Yuanzhao; Yu, Jiachao; Hua, Xin; Evans, James E; Yu, Xiaofei; Lao, David B; Heldebrant, David J; Nune, Satish K; Cao, Bin; Bowden, Mark E; Yu, Xiao-Ying; Wang, Xue-Lin; Zhu, Zihua

2016-12-01

In situ liquid secondary ion mass spectrometry (SIMS) enabled by system for analysis at the liquid vacuum interface (SALVI) has proven to be a promising new tool to provide molecular information at solid-liquid and liquid-vacuum interfaces. However, the initial data showed that useful signals in positive ion spectra are too weak to be meaningful in most cases. In addition, it is difficult to obtain strong negative molecular ion signals when m/z>200. These two drawbacks have been the biggest obstacle towards practical use of this new analytical approach. In this study, we report that strong and reliable positive and negative molecular signals are achievable after optimizing the SIMS experimental conditions. Four model systems, including a 1,8-diazabicycloundec-7-ene (DBU)-base switchable ionic liquid, a live Shewanella oneidensis biofilm, a hydrated mammalian epithelia cell, and an electrolyte popularly used in Li ion batteries were studied. A signal enhancement of about two orders of magnitude was obtained in comparison with non-optimized conditions. Therefore, molecular ion signal intensity has become very acceptable for use of in situ liquid SIMS to study solid-liquid and liquid-vacuum interfaces. Graphical Abstract ᅟ.

Charged Current Quasielastic Analysis from MINERνA

Energy Technology Data Exchange (ETDEWEB)

Ghosh, Anushree [Rio de Janeiro, CBPF

2015-08-01

The MINERνA detector situated in Fermilab, is designed to make precision cross-section measurements for scattering processes on various nuclei. In this proceeding, the results of the charged current quasi-elastic (CCQE) analysis using lepton kinematics and with proton kinematics have been presented. Comparison of these with theoretical models suggested that further studies are required to include the additional nuclear effects in the current simulations. The first direct measurement of electron-neutrino quasielastic-like scattering in the few-GeV region of incident neutrino energy has also been presented. All three analyses, discussed here, are carried out on hydrocarbon target.

Spectral analysis of highly aliased sea-level signals

Science.gov (United States)

Ray, Richard D.

1998-10-01

Observing high-wavenumber ocean phenomena with a satellite altimeter generally calls for "along-track" analyses of the data: measurements along a repeating satellite ground track are analyzed in a point-by-point fashion, as opposed to spatially averaging data over multiple tracks. The sea-level aliasing problems encountered in such analyses can be especially challenging. For TOPEX/POSEIDON, all signals with frequency greater than 18 cycles per year (cpy), including both tidal and subdiurnal signals, are folded into the 0-18 cpy band. Because the tidal bands are wider than 18 cpy, residual tidal cusp energy, plus any subdiurnal energy, is capable of corrupting any low-frequency signal of interest. The practical consequences of this are explored here by using real sea-level measurements from conventional tide gauges, for which the true oceanographic spectrum is known and to which a simulated "satellite-measured" spectrum, based on coarsely subsampled data, may be compared. At many locations the spectrum is sufficently red that interannual frequencies remain unaffected. Intra-annual frequencies, however, must be interpreted with greater caution, and even interannual frequencies can be corrupted if the spectrum is flat. The results also suggest that whenever tides must be estimated directly from the altimetry, response methods of analysis are preferable to harmonic methods, even in nonlinear regimes; this will remain so for the foreseeable future. We concentrate on three example tide gauges: two coastal stations on the Malay Peninsula where the closely aliased K1 and Ssa tides are strong and at Canton Island where trapped equatorial waves are aliased.

Performance analysis of signaling protocols on OBS switches

Science.gov (United States)

Kirci, Pinar; Zaim, A. Halim

2005-10-01

In this paper, Just-In-Time (JIT), Just-Enough-Time (JET) and Horizon signalling schemes for Optical Burst Switched Networks (OBS) are presented. These signaling schemes run over a core dWDM network and a network architecture based on Optical Burst Switches (OBS) is proposed to support IP, ATM and Burst traffic. In IP and ATM traffic several packets are assembled in a single packet called burst and the burst contention is handled by burst dropping. The burst length distribution in IP traffic is arbitrary between 0 and 1, and is fixed in ATM traffic at 0,5. Burst traffic on the other hand is arbitrary between 1 and 5. The Setup and Setup ack length distributions are arbitrary. We apply the Poisson model with rate λ and Self-Similar model with pareto distribution rate α to identify inter-arrival times in these protocols. We consider a communication between a source client node and a destination client node over an ingress and one or more multiple intermediate switches.We use buffering only in the ingress node. The communication is based on single burst connections in which, the connection is set up just before sending a burst and then closed as soon as the burst is sent. Our analysis accounts for several important parameters, including the burst setup, burst setup ack, keepalive messages and the optical switching protocol. We compare the performance of the three signalling schemes on the network under as burst dropping probability under a range of network scenarios.

Signal Detection Analysis of Factors Associated with Diabetes among Semirural Mexican American Adults

Science.gov (United States)

Hanni, K. D.; Ahn, D. A.; Winkleby, M. A.

2013-01-01

Signal detection analysis was used to evaluate a combination of sociodemographic, acculturation, mental health, health care, and chronic disease risk factors potentially associated with diabetes in a sample of 4,505 semirural Mexican American adults. Overall, 8.9% of adults had been diagnosed with diabetes. The analysis resulted in 12 mutually…

Analysis of harmonic current interaction in an industrial plant

NARCIS (Netherlands)

Cuk, V.; Cobben, J.F.G.; Kling, W.L.; Timens, R.B.

2011-01-01

An analysis of current transients caused by the operation of a nearby device in an industrial plant is presented in the paper. The source of current transients in the factory lighting system was traced to the operation of the nearby six-pulse AC/DC converter. To determine the nature of the

Signal-Independent Timescale Analysis (SITA and its Application for Neural Coding during Reaching and Walking

Directory of Open Access Journals (Sweden)

Miriam eZacksenhouse

2014-08-01

Full Text Available What are the relevant timescales of neural encoding in the brain? This question is commonly investigated with respect to well-defined stimuli or actions. However, neurons often encode multiple signals, including hidden or internal, which are not experimentally controlled, and thus excluded from such analysis. Here we consider all rate modulations as the signal, and define the rate-modulations signal-to-noise ratio (RM-SNR as the ratio between the variance of the rate and the variance of the neuronal noise. As the bin-width increases, RM-SNR increases while the update rate decreases. This tradeoff is captured by the ratio of RM-SNR to bin-width, and its variations with the bin-width reveal the timescales of neural activity. Theoretical analysis and simulations elucidate how the interactions between the recovery properties of the unit and the spectral content of the encoded signals shape this ratio and determine the timescales of neural coding. The resulting signal-independent timescale analysis (SITA is applied to investigate timescales of neural activity recorded from the motor cortex of monkeys during: (i reaching experiments with Brain-Machine Interface (BMI, and (ii locomotion experiments at different speeds. Interestingly, the timescales during BMI experiments did not change significantly with the control mode or training. During locomotion, the analysis identified units whose timescale varied consistently with the experimentally controlled speed of walking, though the specific timescale reflected also the recovery properties of the unit. Thus, the proposed method, SITA, characterizes the timescales of neural encoding and how they are affected by the motor task, while accounting for all rate modulations.

Nonlinear Analysis of Auscultation Signals in TCM Using the Combination of Wavelet Packet Transform and Sample Entropy

Directory of Open Access Journals (Sweden)

Jian-Jun Yan

2012-01-01

Full Text Available Auscultation signals are nonstationary in nature. Wavelet packet transform (WPT has currently become a very useful tool in analyzing nonstationary signals. Sample entropy (SampEn has recently been proposed to act as a measurement for quantifying regularity and complexity of time series data. WPT and SampEn were combined in this paper to analyze auscultation signals in traditional Chinese medicine (TCM. SampEns for WPT coefficients were computed to quantify the signals from qi- and yin-deficient, as well as healthy, subjects. The complexity of the signal can be evaluated with this scheme in different time-frequency resolutions. First, the voice signals were decomposed into approximated and detailed WPT coefficients. Then, SampEn values for approximated and detailed coefficients were calculated. Finally, SampEn values with significant differences in the three kinds of samples were chosen as the feature parameters for the support vector machine to identify the three types of auscultation signals. The recognition accuracy rates were higher than 90%.

Preliminary analysis of accident in SST-1 current feeder system

International Nuclear Information System (INIS)

Roy, Swati; Kanabar, Deven; Garg, Atul; Singh, Amit; Tanna, Vipul; Prasad, Upendra; Srinivasan, R.

2017-01-01

Steady-state Tokamak-1 (SST-1) has 16 superconducting Toroidal field (TF) and 9 superconducting poloidal field (PF) coils rated for 10kA DC. All the TF are connected in series and are operated in DC condition whereas PF coils are individually operated in pulse mode during SST-1 campaigns. SST-1 current feeder system (CFS) houses 9 pairs of PF current leads and 1 pair of TF current leads. During past SST-1 campaign, there were arcing incidents within SST-1 CFS chamber which caused significant damage to PF superconducting current leads as well as its Helium cooling lines of the current leads. This paper brings out the preliminary analysis of the mentioned arcing incident, possible reasons and its investigation thereby laying out the sequence of events. From this analysis and observations, various measures to avoid such arcing incidents have also been proposed. (author)

Si/SiC-based DD hetero-structure IMPATTs as MM-wave power-source: a generalized large-signal analysis

International Nuclear Information System (INIS)

Mukherjee, Moumita; Tripathy, P. R.; Pati, S. P.

2015-01-01

A full-scale, self-consistent, non-linear, large-signal model of double-drift hetero-structure IMPATT diode with general doping profile is derived. This newly developed model, for the first time, has been used to analyze the large-signal characteristics of hexagonal SiC-based double-drift IMPATT diode. Considering the fabrication feasibility, the authors have studied the large-signal characteristics of Si/SiC-based hetero-structure devices. Under small-voltage modulation (∼ 2%, i.e. small-signal conditions) results are in good agreement with calculations done using a linearised small-signal model. The large-signal values of the diode's negative conductance (5 × 10 6 S/m 2 ), susceptance (10.4 × 10 7 S/m 2 ), average breakdown voltage (207.6 V), and power generating efficiency (15%, RF power: 25.0 W at 94 GHz) are obtained as a function of oscillation amplitude (50% of DC breakdown voltage) for a fixed average current density. The large-signal calculations exhibit power and efficiency saturation for large-signal (> 50%) voltage modulation and thereafter decrease gradually with further increasing voltage-modulation. This generalized large-signal formulation is applicable for all types of IMPATT structures with distributed and narrow avalanche zones. The simulator is made more realistic by incorporating the space-charge effects, realistic field and temperature dependent material parameters in Si and SiC. The electric field snap-shots and the large-signal impedance and admittance of the diode with current excitation are expressed in closed loop form. This study will act as a guide for researchers to fabricate a high-power Si/SiC-based IMPATT for possible application in high-power MM-wave communication systems. (paper)

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

Science.gov (United States)

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

2012-06-01

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

Predicting Secretory Proteins with SignalP

DEFF Research Database (Denmark)

Nielsen, Henrik

2017-01-01

SignalP is the currently most widely used program for prediction of signal peptides from amino acid sequences. Proteins with signal peptides are targeted to the secretory pathway, but are not necessarily secreted. After a brief introduction to the biology of signal peptides and the history...

Dynamic Signal Strength Mapping and Analysis by Means of Mobile Geographic Information System

Directory of Open Access Journals (Sweden)

Kulawiak Marcin

2017-12-01

Full Text Available Bluetooth beacons are becoming increasingly popular for various applications such as marketing or indoor navigation. However, designing a proper beacon installation requires knowledge of the possible sources of interference in the target environment. While theoretically beacon signal strength should decay linearly with log distance, on-site measurements usually reveal that noise from objects such as Wi-Fi networks operating in the vicinity significantly alters the expected signal range. The paper presents a novel mobile Geographic Information System for measurement, mapping and local as well as online storage of Bluetooth beacon signal strength in semireal time. For the purpose of on-site geovisual analysis of the signal, the application integrates a dedicated interpolation algorithm optimized for low-power devices. The paper discusses the performance and quality of the mapping algorithms in several different test environments.

Extraction of fast neuronal changes from multichannel functional near-infrared spectroscopy signals using independent component analysis

Science.gov (United States)

Morren, Geert; Wolf, Martin; Lemmerling, Philippe; Wolf, Ursula; Choi, Jee H.; Gratton, Enrico; De Lathauwer, Lieven; Van Huffel, Sabine

2002-06-01

Fast changes in the range of milliseconds in the optical properties of cerebral tissue, which are associated with brain activity, can be detected using non-invasive near-infrared spectroscopy (NIRS). These changes in light scattering are due to an alteration in the refractive index at neuronal membranes. The aim of this study was to develop highly sensitive data analysis algorithms to detect this fast signal, which is small compared to other physiological signals. A frequency-domain tissue oximeter, whose laser diodes were modulated at 110MHz was used. The amplitude, mean intensity and phase of the modulated optical signal was measured at 96Hz sample rate. The probe consisting of 4 crossed source detector pairs was placed above the motor cortex, contralateral to the hand performing a tapping exercise consisting of alternating rest- and tapping periods of 20s each. The tapping frequency, which was set to 3.55Hz or 2.5 times the heart rate of the subject to avoid the influence of harmonics on the signal, could not be observed in any of the individual signals measured by the detectors. An adaptive filter was used to remove the arterial pulsatility from the optical signals. Independent Component Analysis allowed to separate signal components in which the tapping frequency was clearly visible.

Determination of over current protection thresholds for class D audio amplifiers

DEFF Research Database (Denmark)

Nyboe, Flemming; Risbo, L; Andreani, Pietro

2005-01-01

Monolithic class-D audio amplifiers typically feature built-in over current protection circuitry that shuts down the amplifier in case of a short circuit on the output speaker terminals. To minimize cost, the threshold at which the device shuts down must be set just above the maximum current...... that can flow in the loudspeaker during normal operation. The current required is determined by the complex loudspeaker impedance and properties of the music signals played. This work presents a statistical analysis of peak output currents when playing music on typical loudspeakers for home entertainment....