Basic digital signal processing

CERN Document Server

Lockhart, Gordon B

1985-01-01

Basic Digital Signal Processing describes the principles of digital signal processing and experiments with BASIC programs involving the fast Fourier theorem (FFT). The book reviews the fundamentals of the BASIC program, continuous and discrete time signals including analog signals, Fourier analysis, discrete Fourier transform, signal energy, power. The text also explains digital signal processing involving digital filters, linear time-variant systems, discrete time unit impulse, discrete-time convolution, and the alternative structure for second order infinite impulse response (IIR) sections.

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

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

Ca analysis: an Excel based program for the analysis of intracellular calcium transients including multiple, simultaneous regression analysis.

Science.gov (United States)

Greensmith, David J

2014-01-01

Here I present an Excel based program for the analysis of intracellular Ca transients recorded using fluorescent indicators. The program can perform all the necessary steps which convert recorded raw voltage changes into meaningful physiological information. The program performs two fundamental processes. (1) It can prepare the raw signal by several methods. (2) It can then be used to analyze the prepared data to provide information such as absolute intracellular Ca levels. Also, the rates of change of Ca can be measured using multiple, simultaneous regression analysis. I demonstrate that this program performs equally well as commercially available software, but has numerous advantages, namely creating a simplified, self-contained analysis workflow. Copyright © 2013 The Author. Published by Elsevier Ireland Ltd.. All rights reserved.

Application of Photoshop and Scion Image analysis to quantification of signals in histochemistry, immunocytochemistry and hybridocytochemistry.

Science.gov (United States)

Tolivia, Jorge; Navarro, Ana; del Valle, Eva; Perez, Cristina; Ordoñez, Cristina; Martínez, Eva

2006-02-01

To describe a simple method to achieve the differential selection and subsequent quantification of the strength signal using only one section. Several methods for performing quantitative histochemistry, immunocytochemistry or hybridocytochemistry, without use of specific commercial image analysis systems, rely on pixel-counting algorithms, which do not provide information on the amount of chromogen present in the section. Other techniques use complex algorithms to calculate the cumulative signal strength using two consecutive sections. To separate the chromogen signal we used the "Color range" option of the Adobe Photoshop program, which provides a specific file for a particular chromogen selection that could be applied on similar sections. The measurement of the chromogen signal strength of the specific staining is achieved with the Scion Image software program. The method described in this paper can also be applied to simultaneous detection of different signals on the same section or different parameters (area of particles, number of particles, etc.) when the "Analyze particles" tool of the Scion program is used.

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.

Validation of the dynamics of SDS and RRS flux, flow, pressure and temperature signals using noise analysis technique

International Nuclear Information System (INIS)

Glockler, O.; Cooke, D.F.; Tulett, M.V.

1995-01-01

In 1992, a program was initiated to establish reactor noise analysis as a practical tool for plant performance monitoring and system diagnostics in Ontario Hydro's CANDU reactors. Since then, various CANDU-specific noise analysis applications have been developed and validated. The noise-based statistical techniques are being successfully applied as powerful troubleshooting and diagnostic tools to a wide variety of actual operational I and C problems. Critical plant components, instrumentation and processes are monitored on a regular basis, and their dynamic characteristics are verified on-power. Recent applications of noise analysis include (1) validating the dynamics of in-core flux detectors (ICFDS) and ion chambers, (2) estimating the prompt fraction ICFDs in noise measurements at full power and in power rundown tests, (3) identifying the cause of excessive signal fluctuations in certain flux detectors, (4) validating the dynamic coupling between liquid zone control signals, (5) detecting and monitoring mechanical vibrations of detector tubes, reactivity devices and fuel channels induced by moderator/coolant flow, (6) estimating the dynamics and response time of RTD temperature signals, (7) isolating the cause of RTD signal anomalies, (8) investigating the source of abnormal flow signal behaviour, (9) estimating the overall response time of flow and pressure signals, (1 0) detecting coolant boiling in fully instrumented fuel channels, (1 1) monitoring moderator circulation via temperature noise, and (12) predicting the performance of shut-off rods. Some of these applications are performed on an as needed basis. The noise analysis program, in the Pickering-B station alone, has saved Ontario Hydro millions of dollars during its first three years. The results of the noise analysis program have been also reviewed by the regulator (Atomic Energy Control Board of Canada) with favorable results. The AECB have expressed interest in Ontario Hydro further exploiting the

Electromagnetic modeling method for eddy current signal analysis

International Nuclear Information System (INIS)

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

2004-10-01

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

Analysis and software development for controlling RF signal generator proton cyclotron Decy-13 using DDS Technique

International Nuclear Information System (INIS)

Prajitno

2012-01-01

Analysis and manufacture of computer programs for controlling the signal generator Radio Frequency (RF) proton cyclotron Decy-13 have been done. Signal generator uses a technique Direct Digital Synthesiser (DDS) which settings must be done with software. Signal generator consists of electronic modules which are: DDS, micro controller ATmega16, amplifier RF.dan ± 12 Vdc power supply. Function of the programs that have been made is to set the DDS module, namely: output frequency, step frequency and phase settings and displays the operating parameters of the DDS and the RF amplifier on the monitor screen. Computer programs created with Visual Basic and has been tested to control the RF signal generator to send data serially to the module ATmega16 and receives data to be displayed on the monitor screen. Testing sending and receiving data is done with a baudrate of 1200 bps to 19200 bps with perfect results. Computer programs that have been made equipped with a Human Machine Interface to provide values parameter input on the DDS operations. (author)

Interference Reduction Selected Measurement Signals of Ships

Directory of Open Access Journals (Sweden)

Jan Monieta

2014-08-01

Full Text Available The paper presents problems encountered at the signal processing of mechanical values with electric methods. Depending on the measured quantity, the location of the sensors and the analysis frequency band, they are differently interferences. The article presents the results of applying the analysis of parameters of working and accompanying process marine medium speed reciprocating engines in the time, amplitude, frequency domain and wavelet analysis to select a reasonable method. The applied signal acquisition program allows you to perform some analysis of signals in different areas and the transformation of the data to other programs. The ways of interference reducing at various stages of their occurrence and analysis are presented. [b]Keywords[/b]: electrical signals, domain analysis, measurement interference

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

Directory of Open Access Journals (Sweden)

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

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 ...

Ca analysis: An Excel based program for the analysis of intracellular calcium transients including multiple, simultaneous regression analysis☆

Science.gov (United States)

Greensmith, David J.

2014-01-01

Here I present an Excel based program for the analysis of intracellular Ca transients recorded using fluorescent indicators. The program can perform all the necessary steps which convert recorded raw voltage changes into meaningful physiological information. The program performs two fundamental processes. (1) It can prepare the raw signal by several methods. (2) It can then be used to analyze the prepared data to provide information such as absolute intracellular Ca levels. Also, the rates of change of Ca can be measured using multiple, simultaneous regression analysis. I demonstrate that this program performs equally well as commercially available software, but has numerous advantages, namely creating a simplified, self-contained analysis workflow. PMID:24125908

Programming signal processing applications on heterogeneous wireless sensor platforms

NARCIS (Netherlands)

Buondonno, L.; Fortino, G.; Galzarano, S.; Giannantonio, R.; Giordano, A.; Gravina, R.; Guerrieri, A.

2009-01-01

This paper proposes the SPINE frameworks (SPINE1.x and SPINE2) for the programming of signal processing applications on heterogeneous wireless sensor platforms. In particular, two integrable approaches based on the proposed frameworks are described that allow to develop applications for wireless

No-signaling quantum key distribution: solution by linear programming

Science.gov (United States)

Hwang, Won-Young; Bae, Joonwoo; Killoran, Nathan

2015-02-01

We outline a straightforward approach for obtaining a secret key rate using only no-signaling constraints and linear programming. Assuming an individual attack, we consider all possible joint probabilities. Initially, we study only the case where Eve has binary outcomes, and we impose constraints due to the no-signaling principle and given measurement outcomes. Within the remaining space of joint probabilities, by using linear programming, we get bound on the probability of Eve correctly guessing Bob's bit. We then make use of an inequality that relates this guessing probability to the mutual information between Bob and a more general Eve, who is not binary-restricted. Putting our computed bound together with the Csiszár-Körner formula, we obtain a positive key generation rate. The optimal value of this rate agrees with known results, but was calculated in a more straightforward way, offering the potential of generalization to different scenarios.

NET-2 Network Analysis Program

International Nuclear Information System (INIS)

Malmberg, A.F.

1974-01-01

The NET-2 Network Analysis Program is a general purpose digital computer program which solves the nonlinear time domain response and the linearized small signal frequency domain response of an arbitrary network of interconnected components. NET-2 is capable of handling a variety of components and has been applied to problems in several engineering fields, including electronic circuit design and analysis, missile flight simulation, control systems, heat flow, fluid flow, mechanical systems, structural dynamics, digital logic, communications network design, solid state device physics, fluidic systems, and nuclear vulnerability due to blast, thermal, gamma radiation, neutron damage, and EMP effects. Network components may be selected from a repertoire of built-in models or they may be constructed by the user through appropriate combinations of mathematical, empirical, and topological functions. Higher-level components may be defined by subnetworks composed of any combination of user-defined components and built-in models. The program provides a modeling capability to represent and intermix system components on many levels, e.g., from hole and electron spatial charge distributions in solid state devices through discrete and integrated electronic components to functional system blocks. NET-2 is capable of simultaneous computation in both the time and frequency domain, and has statistical and optimization capability. Network topology may be controlled as a function of the network solution. (U.S.)

Programming a DSP card for generating an ECG signal with possibility of anomalies

International Nuclear Information System (INIS)

Hamrouni, Sayma

2013-01-01

This project consists of programming a DSP designed to generate an ECG signal with a probability of anomaly. To begin with, we get to know the characteristics of a DSP card and its architecture. As a second step, we programmed the DSP32C using the compiler D3CC associated with Textpad in order to obtain an analog signal in the respective outputs. And then finally, we developed a graphical user interface using the programming software LabVIEW that aims controlling the good operation of DSP. The tests previously made have proved the good operation of the application.

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

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...

The Denver region traffic signal system improvement program : planning for management and operations

Science.gov (United States)

2009-04-01

The Denver Regional Council of Governments (DRCOG) works with over 30 local jurisdictions on the Traffic Signal System Improvement Program (TSSIP), a combination of management and operations strategies designed to time and coordinate traffic signals ...

Logic integer programming models for signaling networks.

Science.gov (United States)

Haus, Utz-Uwe; Niermann, Kathrin; Truemper, Klaus; Weismantel, Robert

2009-05-01

We propose a static and a dynamic approach to model biological signaling networks, and show how each can be used to answer relevant biological questions. For this, we use the two different mathematical tools of Propositional Logic and Integer Programming. The power of discrete mathematics for handling qualitative as well as quantitative data has so far not been exploited in molecular biology, which is mostly driven by experimental research, relying on first-order or statistical models. The arising logic statements and integer programs are analyzed and can be solved with standard software. For a restricted class of problems the logic models reduce to a polynomial-time solvable satisfiability algorithm. Additionally, a more dynamic model enables enumeration of possible time resolutions in poly-logarithmic time. Computational experiments are included.

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...

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.

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

Signal analysis of Hindustani classical music

CERN Document Server

Datta, Asoke Kumar; Sengupta, Ranjan; Chakraborty, Soubhik; Mahto, Kartik; Patranabis, Anirban

2017-01-01

This book presents a comprehensive overview of the basics of Hindustani music and the associated signal analysis and technological developments. It begins with an in-depth introduction to musical signal analysis and its current applications, and then moves on to a detailed discussion of the features involved in understanding the musical meaning of the signal in the context of Hindustani music. The components consist of tones, shruti, scales, pitch duration and stability, raga, gharana and musical instruments. The book covers the various technological developments in this field, supplemented with a number of case studies and their analysis. The book offers new music researchers essential insights into the use of the automatic concept for finding and testing the musical features for their applications. Intended primarily for postgraduate and PhD students working in the area of scientific research on Hindustani music, as well as other genres where the concepts are applicable, it is also a valuable resource for p...

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.

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.

Reverse engineering GTPase programming languages with reconstituted signaling networks.

Science.gov (United States)

Coyle, Scott M

2016-07-02

The Ras superfamily GTPases represent one of the most prolific signaling currencies used in Eukaryotes. With these remarkable molecules, evolution has built GTPase networks that control diverse cellular processes such as growth, morphology, motility and trafficking. (1-4) Our knowledge of the individual players that underlie the function of these networks is deep; decades of biochemical and structural data has provided a mechanistic understanding of the molecules that turn GTPases ON and OFF, as well as how those GTPase states signal by controlling the assembly of downstream effectors. However, we know less about how these different activities work together as a system to specify complex dynamic signaling outcomes. Decoding this molecular "programming language" would help us understand how different species and cell types have used the same GTPase machinery in different ways to accomplish different tasks, and would also provide new insights as to how mutations to these networks can cause disease. We recently developed a bead-based microscopy assay to watch reconstituted H-Ras signaling systems at work under arbitrary configurations of regulators and effectors. (5) Here we highlight key observations and insights from this study and propose extensions to our method to further study this and other GTPase signaling systems.

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.

Ecosystem Analysis Program

International Nuclear Information System (INIS)

Burgess, R.L.

1978-01-01

Progress is reported on the following research programs: analysis and modeling of ecosystems; EDFB/IBP data center; biome analysis studies; land/water interaction studies; and computer programs for development of models

General programmed system for physiological signal processing

Energy Technology Data Exchange (ETDEWEB)

Tournier, E; Monge, J; Magnet, C; Sonrel, C

1975-01-01

Improvements made to the general programmed signal acquisition and processing system, Plurimat S, are described, the aim being to obtain a less specialized system adapted to the biological and medical field. In this modified system the acquisition will be simplified. The standard processings offered will be integrated to a real advanced language which will enable the user to create his own processings, the loss of speed being compensated by a greater flexibility and universality. The observation screen will be large and the quality of the recording very good so that a large signal fraction may be displayed. The data will be easily indexed and filed for subsequent display and processing. This system will be used for two kinds of task: it can either be specialized, as an integral part of measurement and diagnostic preparation equipment used routinely in clinical work (e.g. vectocardiographic examination), or its versatility can be used for studies of limited duration to gain information in a given field or to study new diagnosis or treatment methods.

A Review on the Nonlinear Dynamical System Analysis of Electrocardiogram Signal.

Science.gov (United States)

Nayak, Suraj K; Bit, Arindam; Dey, Anilesh; Mohapatra, Biswajit; Pal, Kunal

2018-01-01

Electrocardiogram (ECG) signal analysis has received special attention of the researchers in the recent past because of its ability to divulge crucial information about the electrophysiology of the heart and the autonomic nervous system activity in a noninvasive manner. Analysis of the ECG signals has been explored using both linear and nonlinear methods. However, the nonlinear methods of ECG signal analysis are gaining popularity because of their robustness in feature extraction and classification. The current study presents a review of the nonlinear signal analysis methods, namely, reconstructed phase space analysis, Lyapunov exponents, correlation dimension, detrended fluctuation analysis (DFA), recurrence plot, Poincaré plot, approximate entropy, and sample entropy along with their recent applications in the ECG signal analysis.

A hybrid Constraint Programming/Mixed Integer Programming framework for the preventive signaling maintenance crew scheduling problem

DEFF Research Database (Denmark)

Pour, Shahrzad M.; Drake, John H.; Ejlertsen, Lena Secher

2017-01-01

A railway signaling system is a complex and interdependent system which should ensure the safe operation of trains. We introduce and address a mixed integer optimisation model for the preventive signal maintenance crew scheduling problem in the Danish railway system. The problem contains many...... to feed as ‘warm start’ solutions to a Mixed Integer Programming (MIP) solver for further optimisation. We apply the CP/MIP framework to a section of the Danish rail network and benchmark our results against both direct application of a MIP solver and modelling the problem as a Constraint Optimisation...

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.

A Review on the Nonlinear Dynamical System Analysis of Electrocardiogram Signal

Science.gov (United States)

Mohapatra, Biswajit

2018-01-01

Electrocardiogram (ECG) signal analysis has received special attention of the researchers in the recent past because of its ability to divulge crucial information about the electrophysiology of the heart and the autonomic nervous system activity in a noninvasive manner. Analysis of the ECG signals has been explored using both linear and nonlinear methods. However, the nonlinear methods of ECG signal analysis are gaining popularity because of their robustness in feature extraction and classification. The current study presents a review of the nonlinear signal analysis methods, namely, reconstructed phase space analysis, Lyapunov exponents, correlation dimension, detrended fluctuation analysis (DFA), recurrence plot, Poincaré plot, approximate entropy, and sample entropy along with their recent applications in the ECG signal analysis. PMID:29854361

Automatic analysis of signals during Eddy currents controls

International Nuclear Information System (INIS)

Chiron, D.

1983-06-01

A method and the corresponding instrument have been developed for automatic analysis of Eddy currents testing signals. This apparatus enables at the same time the analysis, every 2 milliseconds, of two signals at two different frequencies. It can be used either on line with an Eddy Current testing instrument or with a magnetic tape recorder [fr

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

frequency, which makes weak reflections more noticeable. The mode mixing phenomenon is observed in several tests, but this does not markedly affect the identification results due to the simple medium in bolt tests. The mode mixing can be reduced by ensemble EMD (EEMD) or complete ensemble EMD with adaptive noise (CEEMDAN), which are powerful tools to used analyze the test signal in a complex medium and may play an important role in future studies. The HHT bolt signal analysis method is a self-adaptive and automatic process, which can be programed as analysis software and will make bolt tests more convenient in practice.

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...

Signal Integrity Analysis of High-Speed Interconnects

CERN Document Server

Oltean Karlsson, A

2007-01-01

LHC detectors and future experiments will produce very large amount of data that will be transferred at multi-Gigabit speeds. At such data rates, signal-integrity effects become important and traditional rules of thumb are no longer enough for the design and layout of the traces. Simulations for signal-integrity effects at board level provide a way to study and validate several scenarios before arriving at a set of optimized design rules prior to building the actual printed circuit board (PCB). This article describes some of the available tools at CERN. Two case studies will be used to highlight the capabilities of these programs.

Subseabed-disposal program: systems-analysis program plan

International Nuclear Information System (INIS)

Klett, R.D.

1981-03-01

This report contains an overview of the Subseabed Nuclear Waste Disposal Program systems analysis program plan, and includes sensitivity, safety, optimization, and cost/benefit analyses. Details of the primary barrier sensitivity analysis and the data acquisition and modeling cost/benefit studies are given, as well as the schedule through the technical, environmental, and engineering feasibility phases of the program

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...

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.

Evaluation of anticipatory signal to steam generator pressure control program for 700 MWe Indian pressurized heavy water reactor

International Nuclear Information System (INIS)

Pahari, S.; Hajela, S.; Rammohan, H. P.; Malhotra, P. K.; Ghadge, S. G.

2012-01-01

700 MWe Indian Pressurized Heavy Water Reactor (IPHWR) is horizontal channel type reactor with partial boiling at channel outlet. Due to boiling, it has a large volume of vapor present in the primary loops. It has two primary loops connected with the help of pressurizer surge line. The pressurizer has a large capacity and is partly filled by liquid and partly by vapor. Large vapor volume improves compressibility of the system. During turbine trip or load rejection, pressure builds up in Steam Generator (SG). This leads to pressurization of Primary Heat Transport System (PHTS). To control pressurization of SG and PHTS, around 70% of the steam generated in SG is dumped into the condenser by opening Condenser Steam Dump Valves (CSDVs) and rest of the steam is released to the atmosphere by opening Atmospheric Steam Discharge Valves (ASDVs) immediately after sensing the event. This is accomplished by adding anticipatory signal to the output of SG pressure controller. Anticipatory signal is proportional to the thermal power of reactor and the proportionality constant is set so that SG pressure controller's output jacks up to ASDV opening range when operating at 100% FP. To simulate this behavior for 700 MWe IPHWR, Primary and secondary heat transport system is modeled. SG pressure control and other process control program have also been modeled to capture overall plant dynamics. Analysis has been carried out with 3-D neutron kinetics coupled thermal hydraulic computer code ATMIKA.T to evaluate the effect of the anticipatory signal on PHT pressure and over all plant dynamics during turbine trip in 700 MWe IPHWR. This paper brings out the results of the analysis with and without considering anticipatory signal in SG pressure control program during turbine trip. (authors)

A Genetic Programming Method for the Identification of Signal Peptides and Prediction of Their Cleavage Sites

Directory of Open Access Journals (Sweden)

David Lennartsson

2004-01-01

Full Text Available A novel approach to signal peptide identification is presented. We use an evolutionary algorithm for automatic evolution of classification programs, so-called programmatic motifs. The variant of evolutionary algorithm used is called genetic programming where a population of solution candidates in the form of full computer programs is evolved, based on training examples consisting of signal peptide sequences. The method is compared with a previous work using artificial neural network (ANN approaches. Some advantages compared to ANNs are noted. The programmatic motif can perform computational tasks beyond that of feed-forward neural networks and has also other advantages such as readability. The best motif evolved was analyzed and shown to detect the h-region of the signal peptide. A powerful parallel computer cluster was used for the experiment.

SPICODYN: A Toolbox for the Analysis of Neuronal Network Dynamics and Connectivity from Multi-Site Spike Signal Recordings.

Science.gov (United States)

Pastore, Vito Paolo; Godjoski, Aleksandar; Martinoia, Sergio; Massobrio, Paolo

2018-01-01

We implemented an automated and efficient open-source software for the analysis of multi-site neuronal spike signals. The software package, named SPICODYN, has been developed as a standalone windows GUI application, using C# programming language with Microsoft Visual Studio based on .NET framework 4.5 development environment. Accepted input data formats are HDF5, level 5 MAT and text files, containing recorded or generated time series spike signals data. SPICODYN processes such electrophysiological signals focusing on: spiking and bursting dynamics and functional-effective connectivity analysis. In particular, for inferring network connectivity, a new implementation of the transfer entropy method is presented dealing with multiple time delays (temporal extension) and with multiple binary patterns (high order extension). SPICODYN is specifically tailored to process data coming from different Multi-Electrode Arrays setups, guarantying, in those specific cases, automated processing. The optimized implementation of the Delayed Transfer Entropy and the High-Order Transfer Entropy algorithms, allows performing accurate and rapid analysis on multiple spike trains from thousands of electrodes.

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

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.

LULU analysis program

International Nuclear Information System (INIS)

Crawford, H.J.; Lindstrom, P.J.

1983-06-01

Our analysis program LULU has proven very useful in all stages of experiment analysis, from prerun detector debugging through final data reduction. It has solved our problem of having arbitrary word length events and is easy enough to use that many separate experimenters are now analyzing with LULU. The ability to use the same software for all stages of experiment analysis greatly eases the programming burden. We may even get around to making the graphics elegant someday

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)

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

Frequency modulation television analysis: Threshold impulse analysis. [with computer program

Science.gov (United States)

Hodge, W. H.

1973-01-01

A computer program is developed to calculate the FM threshold impulse rates as a function of the carrier-to-noise ratio for a specified FM system. The system parameters and a vector of 1024 integers, representing the probability density of the modulating voltage, are required as input parameters. The computer program is utilized to calculate threshold impulse rates for twenty-four sets of measured probability data supplied by NASA and for sinusoidal and Gaussian modulating waveforms. As a result of the analysis several conclusions are drawn: (1) The use of preemphasis in an FM television system improves the threshold by reducing the impulse rate. (2) Sinusoidal modulation produces a total impulse rate which is a practical upper bound for the impulse rates of TV signals providing the same peak deviations. (3) As the moment of the FM spectrum about the center frequency of the predetection filter increases, the impulse rate tends to increase. (4) A spectrum having an expected frequency above (below) the center frequency of the predetection filter produces a higher negative (positive) than positive (negative) impulse rate.

A Program Transformation for Backwards Analysis of Logic Programs

DEFF Research Database (Denmark)

Gallagher, John Patrick

2003-01-01

The input to backwards analysis is a program together with properties that are required to hold at given program points. The purpose of the analysis is to derive initial goals or pre-conditions that guarantee that, when the program is executed, the given properties hold. The solution for logic...... programs presented here is based on a transformation of the input program, which makes explicit the dependencies of the given program points on the initial goals. The transformation is derived from the resultants semantics of logic programs. The transformed program is then analysed using a standard...

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...

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.

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.

Liquid Effluents Program mission analysis

International Nuclear Information System (INIS)

Lowe, S.S.

1994-01-01

Systems engineering is being used to identify work to cleanup the Hanford Site. The systems engineering process transforms an identified mission need into a set of performance parameters and a preferred system configuration. Mission analysis is the first step in the process. Mission analysis supports early decision-making by clearly defining the program objectives, and evaluating the feasibility and risks associated with achieving those objectives. The results of the mission analysis provide a consistent basis for subsequent systems engineering work. A mission analysis was performed earlier for the overall Hanford Site. This work was continued by a ''capstone'' team which developed a top-level functional analysis. Continuing in a top-down manner, systems engineering is now being applied at the program and project levels. A mission analysis was conducted for the Liquid Effluents Program. The results are described herein. This report identifies the initial conditions and acceptable final conditions, defines the programmatic and physical interfaces and sources of constraints, estimates the resources to carry out the mission, and establishes measures of success. The mission analysis reflects current program planning for the Liquid Effluents Program as described in Liquid Effluents FY 1995 Multi-Year Program Plan

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

Correlation anlaysis of plasma fluctuation signals

International Nuclear Information System (INIS)

Wan Baonian; Wang Zhaoshen

1987-01-01

The application of correlation analysis to identify waves and instabilities in plasma is presented. First, the principle of correlation analysis and its application to diagnose plasma fluctuation signals are given. Then, the data acqusition system, application program and calibration method are described. Finally, experimental results from a mirror device are given

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.

Fast digitizing and digital signal processing of detector signals

International Nuclear Information System (INIS)

Hannaske, Roland

2008-01-01

A fast-digitizer data acquisition system recently installed at the neutron time-of-flight experiment nELBE, which is located at the superconducting electron accelerator ELBE of Forschungszentrum Dresden-Rossendorf, is tested with two different detector types. Preamplifier signals from a high-purity germanium detector are digitized, stored and finally processed. For a precise determination of the energy of the detected radiation, the moving-window deconvolution algorithm is used to compensate the ballistic deficit and different shaping algorithms are applied. The energy resolution is determined in an experiment with γ-rays from a 22 Na source and is compared to the energy resolution achieved with analogously processed signals. On the other hand, signals from the photomultipliers of barium fluoride and plastic scintillation detectors are digitized. These signals have risetimes of a few nanoseconds only. The moment of interaction of the radiation with the detector is determined by methods of digital signal processing. Therefore, different timing algorithms are implemented and tested with data from an experiment at nELBE. The time resolutions achieved with these algorithms are compared to each other as well as to reference values coming from analog signal processing. In addition to these experiments, some properties of the digitizing hardware are measured and a program for the analysis of stored, digitized data is developed. The analysis of the signals shows that the energy resolution achieved with the 10-bit digitizer system used here is not competitive to a 14-bit peak-sensing ADC, although the ballistic deficit can be fully corrected. However, digital methods give better result in sub-ns timing than analog signal processing. (orig.)

Gear wear monitoring by modulation signal bispectrum based on motor current signal analysis

Science.gov (United States)

Zhang, Ruiliang; Gu, Fengshou; Mansaf, Haram; Wang, Tie; Ball, Andrew D.

2017-09-01

Gears are important mechanical components for power transmissions. Tooth wear is one of the most common failure modes, which can present throughout a gear's lifetime. It is significant to accurately monitor gear wear progression in order to take timely predictive maintenances. Motor current signature analysis (MCSA) is an effective and non-intrusive approach which is able to monitor faults from both electrical and mechanical systems. However, little research has been reported in monitoring the gear wear and estimating its severity based on MCSA. This paper presents a novel gear wear monitoring method through a modulation signal bispectrum based motor current signal analysis (MSB-MCSA). For a steady gear transmission, it is inevitable to exist load and speed oscillations due to various errors including wears. These oscillations can induce small modulations in the current signals of the driving motor. MSB is particularly effective in characterising such small modulation signals. Based on these understandings, the monitoring process was implemented based on the current signals from a run-to-failure test of an industrial two stages helical gearbox under a moderate accelerated fatigue process. At the initial operation of the test, MSB analysis results showed that the peak values at the bifrequencies of gear rotations and the power supply can be effective monitoring features for identifying faulty gears and wear severity as they exhibit agreeable changes with gear loads. A monotonically increasing trend established by these features allows a clear indication of the gear wear progression. The dismantle inspection at 477 h of operation, made when one of the monitored features is about 123% higher than its baseline, has found that there are severe scuffing wear marks on a number of tooth surfaces on the driving gear, showing that the gear endures a gradual wear process during its long test operation. Therefore, it is affirmed that the MSB-MSCA approach proposed is reliable

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

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

Signal sciences workshop proceedings

Energy Technology Data Exchange (ETDEWEB)

Candy, J.V.

1997-05-01

This meeting is aimed primarily at signal processing and controls. The technical program for the 1997 Workshop includes a variety of efforts in the Signal Sciences with applications in the Microtechnology Area a new program at LLNL and a future area of application for both Signal/Image Sciences. Special sessions organized by various individuals in Seismic and Optical Signal Processing as well as Micro-Impulse Radar Processing highlight the program, while the speakers at the Signal Processing Applications session discuss various applications of signal processing/control to real world problems. For the more theoretical, a session on Signal Processing Algorithms was organized as well as for the more pragmatic, featuring a session on Real-Time Signal Processing.

Signal sciences workshop. Proceedings

International Nuclear Information System (INIS)

Candy, J.V.

1997-01-01

This meeting is aimed primarily at signal processing and controls. The technical program for the 1997 Workshop includes a variety of efforts in the Signal Sciences with applications in the Microtechnology Area a new program at LLNL and a future area of application for both Signal/Image Sciences. Special sessions organized by various individuals in Seismic and Optical Signal Processing as well as Micro-Impulse Radar Processing highlight the program, while the speakers at the Signal Processing Applications session discuss various applications of signal processing/control to real world problems. For the more theoretical, a session on Signal Processing Algorithms was organized as well as for the more pragmatic, featuring a session on Real-Time Signal Processing

PASA - A Program for Automated Protein NMR Backbone Signal Assignment by Pattern-Filtering Approach

International Nuclear Information System (INIS)

Xu Yizhuang; Wang Xiaoxia; Yang Jun; Vaynberg, Julia; Qin Jun

2006-01-01

We present a new program, PASA (Program for Automated Sequential Assignment), for assigning protein backbone resonances based on multidimensional heteronuclear NMR data. Distinct from existing programs, PASA emphasizes a per-residue-based pattern-filtering approach during the initial stage of the automated 13 C α and/or 13 C β chemical shift matching. The pattern filter employs one or multiple constraints such as 13 C α /C β chemical shift ranges for different amino acid types and side-chain spin systems, which helps to rule out, in a stepwise fashion, improbable assignments as resulted from resonance degeneracy or missing signals. Such stepwise filtering approach substantially minimizes early false linkage problems that often propagate, amplify, and ultimately cause complication or combinatorial explosion of the automation process. Our program (http://www.lerner.ccf.org/moleccard/qin/) was tested on four representative small-large sized proteins with various degrees of resonance degeneracy and missing signals, and we show that PASA achieved the assignments efficiently and rapidly that are fully consistent with those obtained by laborious manual protocols. The results demonstrate that PASA may be a valuable tool for NMR-based structural analyses, genomics, and proteomics

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

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.

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

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.

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.

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.

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)

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.

Chloroplasts activity and PAP-signaling regulate programmed cell death in Arabidopsis

KAUST Repository

Bruggeman, Quentin

2016-01-09

Programmed cell death (PCD) is a crucial process both for plant development and responses to biotic and abiotic stress. There is accumulating evidence that chloroplasts may play a central role during plant PCD as for mitochondria in animal cells, but it is still unclear whether they participate in PCD onset, execution, or both. To tackle this question, we have analyzed the contribution of chloroplast function to the cell death phenotype of the myoinositol phosphate synthase1 (mips1) mutant that forms spontaneous lesions in a light-dependent manner. We show that photosynthetically active chloroplasts are required for PCD to occur in mips1, but this process is independent of the redox state of the chloroplast. Systematic genetic analyses with retrograde signaling mutants reveal that 3’-phosphoadenosine 5’-phosphate, a chloroplast retrograde signal that modulates nuclear gene expression in response to stress, can inhibit cell death and compromises plant innate immunity via inhibition of the RNA-processing 5’-3’ exoribonucleases. Our results provide evidence for the role of chloroplast-derived signal and RNA metabolism in the control of cell death and biotic stress response. © 2016 American Society of Plant Biologists. All Rights Reserved.

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.

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

Real-time spectral analysis of HRV signals: an interactive and user-friendly PC system.

Science.gov (United States)

Basano, L; Canepa, F; Ottonello, P

1998-01-01

We present a real-time system, built around a PC and a low-cost data acquisition board, for the spectral analysis of the heart rate variability signal. The Windows-like operating environment on which it is based makes the computer program very user-friendly even for non-specialized personnel. The Power Spectral Density is computed through the use of a hybrid method, in which a classical FFT analysis follows an autoregressive finite-extension of data; the stationarity of the sequence is continuously checked. The use of this algorithm gives a high degree of robustness of the spectral estimation. Moreover, always in real time, the FFT of every data block is computed and displayed in order to corroborate the results as well as to allow the user to interactively choose a proper AR model order.

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.

Static Analysis of Mobile Programs

Science.gov (United States)

2017-02-01

and not allowed, to do. The second issue was that a fully static analysis was never a realistic possibility, because Java , the programming langauge...scale to large programs it had to handle essentially all of the features of Java and could also be used as a general-purpose analysis engine. The...static analysis of imperative languages. • A framework for adding specifications about the behavior of methods, including methods that were

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)

Non Linear Programming (NLP) formulation for quantitative modeling of protein signal transduction pathways.

Science.gov (United States)

Mitsos, Alexander; Melas, Ioannis N; Morris, Melody K; Saez-Rodriguez, Julio; Lauffenburger, Douglas A; Alexopoulos, Leonidas G

2012-01-01

Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i) excessive CPU time requirements and ii) loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP) formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms.

Non Linear Programming (NLP formulation for quantitative modeling of protein signal transduction pathways.

Directory of Open Access Journals (Sweden)

Alexander Mitsos

Full Text Available Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i excessive CPU time requirements and ii loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms.

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

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.

Development of spectral analysis math models and software program and spectral analyzer, digital converter interface equipment design

Science.gov (United States)

Hayden, W. L.; Robinson, L. H.

1972-01-01

Spectral analyses of angle-modulated communication systems is studied by: (1) performing a literature survey of candidate power spectrum computational techniques, determining the computational requirements, and formulating a mathematical model satisfying these requirements; (2) implementing the model on UNIVAC 1230 digital computer as the Spectral Analysis Program (SAP); and (3) developing the hardware specifications for a data acquisition system which will acquire an input modulating signal for SAP. The SAP computational technique uses extended fast Fourier transform and represents a generalized approach for simple and complex modulating signals.

Single Event Upset Analysis: On-orbit performance of the Alpha Magnetic Spectrometer Digital Signal Processor Memory aboard the International Space Station

Science.gov (United States)

Li, Jiaqiang; Choutko, Vitaly; Xiao, Liyi

2018-03-01

Based on the collection of error data from the Alpha Magnetic Spectrometer (AMS) Digital Signal Processors (DSP), on-orbit Single Event Upsets (SEUs) of the DSP program memory are analyzed. The daily error distribution and time intervals between errors are calculated to evaluate the reliability of the system. The particle density distribution of International Space Station (ISS) orbit is presented and the effects from the South Atlantic Anomaly (SAA) and the geomagnetic poles are analyzed. The impact of solar events on the DSP program memory is carried out combining data analysis and Monte Carlo simulation (MC). From the analysis and simulation results, it is concluded that the area corresponding to the SAA is the main source of errors on the ISS orbit. Solar events can also cause errors on DSP program memory, but the effect depends on the on-orbit particle density.

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.

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

Abnormal Signal Analysis for a Change of the R-C Passive Elements in a Equivalent Circuit Modeling under a High Temperature Accident Condition

International Nuclear Information System (INIS)

Koo, Kil-Mo; Song, Yong-Mann; Ahan, Kwang-Il; Ha, Jea-Joo

2007-01-01

An electrical signal should be checked to see whether it lies within its expected electrical range when there is a doubtful condition. The normal signal level for pressure, flow, level and resistance temperature detector sensors is 4 - 20mA for most instruments as an industrial process control standard. In the case of an abnormal signal level from an instrument under a severe accident condition, it is necessary to obtain a more accurate signal validation to operate a system in a control room in NPPs. Diagnostics and analysis for some abnormal signals have been performed through an important equivalent circuits modeling for passive elements under severe accident conditions. Unlike the design basis accidents, there are some inherent uncertainties for the instrumentation capabilities under severe accident conditions. In this paper, to implement a diagnostic analysis for an equivalent circuits modeling, a kind of linked LabVIEW program for each PSpice and MULTISim code is introduced as a one body order system, which can obtain some abnormal signal patterns by a special function such as an advanced simulation tool for each PSpice and Multi-SIM code as a means of a function for a PC based ASSA (abnormal signal simulation analyzer) module

Abnormal Signal Analysis for a Change of the R-C Passive Elements in a Equivalent Circuit Modeling under a High Temperature Accident Condition

Energy Technology Data Exchange (ETDEWEB)

Koo, Kil-Mo; Song, Yong-Mann; Ahan, Kwang-Il; Ha, Jea-Joo [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2007-07-01

An electrical signal should be checked to see whether it lies within its expected electrical range when there is a doubtful condition. The normal signal level for pressure, flow, level and resistance temperature detector sensors is 4 - 20mA for most instruments as an industrial process control standard. In the case of an abnormal signal level from an instrument under a severe accident condition, it is necessary to obtain a more accurate signal validation to operate a system in a control room in NPPs. Diagnostics and analysis for some abnormal signals have been performed through an important equivalent circuits modeling for passive elements under severe accident conditions. Unlike the design basis accidents, there are some inherent uncertainties for the instrumentation capabilities under severe accident conditions. In this paper, to implement a diagnostic analysis for an equivalent circuits modeling, a kind of linked LabVIEW program for each PSpice and MULTISim code is introduced as a one body order system, which can obtain some abnormal signal patterns by a special function such as an advanced simulation tool for each PSpice and Multi-SIM code as a means of a function for a PC based ASSA (abnormal signal simulation analyzer) module.

XML Graphs in Program Analysis

DEFF Research Database (Denmark)

Møller, Anders; Schwartzbach, Michael I.

2011-01-01

of XML graphs against different XML schema languages, and provide a software package that enables others to make use of these ideas. We also survey the use of XML graphs for program analysis with four very different languages: XACT (XML in Java), Java Servlets (Web application programming), XSugar......XML graphs have shown to be a simple and effective formalism for representing sets of XML documents in program analysis. It has evolved through a six year period with variants tailored for a range of applications. We present a unified definition, outline the key properties including validation...

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...

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.

Stress analysis program system for nuclear vessel: STANSAS

International Nuclear Information System (INIS)

Okamoto, Asao; Michikami, Shinsuke

1979-01-01

IHI has developed a computer system of stress analysis and evaluation for nuclear vessels: STANSAS (STress ANalysis System for Axi-symmetric Structure). The system consists of more than twenty independent programs divided into the following six parts. 1. Programs for opening design by code rule. 2. Calculation model generating programs. 3. Load defining programs. 4. Structural analysis programs. 5. Load data/calculation results plotting programs. 6. Stress evaluation programs. Each program is connected with its pre- or post-processor through three data-bases which enable automatic data transfer. The user can make his choice of structural analysis programs in accordance with the problem to be solved. The interface to STANSAS can be easily installed in generalized structural analysis programs such as NASTRAN and MARC. For almost all tables and figures in the stress report, STANSAS has the function to print or plot out. The complicated procedures of ''Design by Analysis'' for pressure vessels have been well standardized by STANSAS. The system will give a high degree of efficiency and confidence to the design work. (author)

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

International Nuclear Information System (INIS)

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

1998-01-01

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

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

Directed random walks and constraint programming reveal active pathways in hepatocyte growth factor signaling.

Science.gov (United States)

Kittas, Aristotelis; Delobelle, Aurélien; Schmitt, Sabrina; Breuhahn, Kai; Guziolowski, Carito; Grabe, Niels

2016-01-01

An effective means to analyze mRNA expression data is to take advantage of established knowledge from pathway databases, using methods such as pathway-enrichment analyses. However, pathway databases are not case-specific and expression data could be used to infer gene-regulation patterns in the context of specific pathways. In addition, canonical pathways may not always describe the signaling mechanisms properly, because interactions can frequently occur between genes in different pathways. Relatively few methods have been proposed to date for generating and analyzing such networks, preserving the causality between gene interactions and reasoning over the qualitative logic of regulatory effects. We present an algorithm (MCWalk) integrated with a logic programming approach, to discover subgraphs in large-scale signaling networks by random walks in a fully automated pipeline. As an exemplary application, we uncover the signal transduction mechanisms in a gene interaction network describing hepatocyte growth factor-stimulated cell migration and proliferation from gene-expression measured with microarray and RT-qPCR using in-house perturbation experiments in a keratinocyte-fibroblast co-culture. The resulting subgraphs illustrate possible associations of hepatocyte growth factor receptor c-Met nodes, differentially expressed genes and cellular states. Using perturbation experiments and Answer Set programming, we are able to select those which are more consistent with the experimental data. We discover key regulator nodes by measuring the frequency with which they are traversed when connecting signaling between receptors and significantly regulated genes and predict their expression-shift consistently with the measured data. The Java implementation of MCWalk is publicly available under the MIT license at: https://bitbucket.org/akittas/biosubg. © 2015 FEBS.

Scaling proprioceptor gene transcription by retrograde NT3 signaling.

Directory of Open Access Journals (Sweden)

Jun Lee

Full Text Available Cell-type specific intrinsic programs instruct neuronal subpopulations before target-derived factors influence later neuronal maturation. Retrograde neurotrophin signaling controls neuronal survival and maturation of dorsal root ganglion (DRG sensory neurons, but how these potent signaling pathways intersect with transcriptional programs established at earlier developmental stages remains poorly understood. Here we determine the consequences of genetic alternation of NT3 signaling on genome-wide transcription programs in proprioceptors, an important sensory neuron subpopulation involved in motor reflex behavior. We find that the expression of many proprioceptor-enriched genes is dramatically altered by genetic NT3 elimination, independent of survival-related activities. Combinatorial analysis of gene expression profiles with proprioceptors isolated from mice expressing surplus muscular NT3 identifies an anticorrelated gene set with transcriptional levels scaled in opposite directions. Voluntary running experiments in adult mice further demonstrate the maintenance of transcriptional adjustability of genes expressed by DRG neurons, pointing to life-long gene expression plasticity in sensory neurons.

Energy Analysis Program 1990 annual report

Energy Technology Data Exchange (ETDEWEB)

1992-01-01

The Energy Analysis Program has played an active role in the analysis and discussion of energy and environmental issues at several levels. (1) at the international level, with programs as developing scenarios for long-term energy demand in developing countries and organizing leading an analytic effort, ``Energy Efficiency, Developing Countries, and Eastern Europe,`` part of a major effort to increase support for energy efficiency programs worldwide; (2) at national level, the Program has been responsible for assessing energy forecasts and policies affecting energy use (e.g., appliance standards, National Energy Strategy scenarios); and (3) at the state and utility levels, the Program has been a leader in promoting integrated resource utility planning; the collaborative process has led to agreement on a new generation of utility demand-site programs in California, providing an opportunity to use knowledge and analytic techniques of the Program`s researchers. We continue to place highest on analyzing energy efficiency, with particular attention given to energy use in buildings. The Program continues its active analysis of international energy issues in Asia (including China), the Soviet Union, South America, and Western Europe. Analyzing the costs and benefits of different levels of standards for residential appliances continues to be the largest single area of research within the Program. The group has developed and applied techniques for forecasting energy demand (or constructing scenarios) for the United States. We have built a new model of industrial energy demand, are in the process of making major changes in our tools for forecasting residential energy demand, have built an extensive and documented energy conservation supply curve of residential energy use, and are beginning an analysis of energy-demand forecasting for commercial buildings.

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...

Conducting a SWOT Analysis for Program Improvement

Science.gov (United States)

Orr, Betsy

2013-01-01

A SWOT (strengths, weaknesses, opportunities, and threats) analysis of a teacher education program, or any program, can be the driving force for implementing change. A SWOT analysis is used to assist faculty in initiating meaningful change in a program and to use the data for program improvement. This tool is useful in any undergraduate or degree…

Medical Signal-Conditioning and Data-Interface System

Science.gov (United States)

Braun, Jeffrey; Jacobus, charles; Booth, Scott; Suarez, Michael; Smith, Derek; Hartnagle, Jeffrey; LePrell, Glenn

2006-01-01

A general-purpose portable, wearable electronic signal-conditioning and data-interface system is being developed for medical applications. The system can acquire multiple physiological signals (e.g., electrocardiographic, electroencephalographic, and electromyographic signals) from sensors on the wearer s body, digitize those signals that are received in analog form, preprocess the resulting data, and transmit the data to one or more remote location(s) via a radiocommunication link and/or the Internet. The system includes a computer running data-object-oriented software that can be programmed to configure the system to accept almost any analog or digital input signals from medical devices. The computing hardware and software implement a general-purpose data-routing-and-encapsulation architecture that supports tagging of input data and routing the data in a standardized way through the Internet and other modern packet-switching networks to one or more computer(s) for review by physicians. The architecture supports multiple-site buffering of data for redundancy and reliability, and supports both real-time and slower-than-real-time collection, routing, and viewing of signal data. Routing and viewing stations support insertion of automated analysis routines to aid in encoding, analysis, viewing, and diagnosis.

A computer program for activation analysis

International Nuclear Information System (INIS)

Rantanen, J.; Rosenberg, R.J.

1983-01-01

A computer program for calculating the results of activation analysis is described. The program comprises two gamma spectrum analysis programs, STOAV and SAMPO and one program for calculating elemental concentrations, KVANT. STOAV is based on a simple summation of channels and SAMPO is based on fitting of mathematical functions. The programs are tested by analyzing the IAEA G-1 test spectra. In the determination of peak location SAMPO is somewhat better than STOAV and in the determination of peak area SAMPO is more than twice as accurate as STOAV. On the other hand, SAMPO is three times as expensive as STOAV with the use of a Cyber 170 computer. (author)

Barcoding T Cell Calcium Response Diversity with Methods for Automated and Accurate Analysis of Cell Signals (MAAACS)

Science.gov (United States)

Sergé, Arnauld; Bernard, Anne-Marie; Phélipot, Marie-Claire; Bertaux, Nicolas; Fallet, Mathieu; Grenot, Pierre; Marguet, Didier; He, Hai-Tao; Hamon, Yannick

2013-01-01

We introduce a series of experimental procedures enabling sensitive calcium monitoring in T cell populations by confocal video-microscopy. Tracking and post-acquisition analysis was performed using Methods for Automated and Accurate Analysis of Cell Signals (MAAACS), a fully customized program that associates a high throughput tracking algorithm, an intuitive reconnection routine and a statistical platform to provide, at a glance, the calcium barcode of a population of individual T-cells. Combined with a sensitive calcium probe, this method allowed us to unravel the heterogeneity in shape and intensity of the calcium response in T cell populations and especially in naive T cells, which display intracellular calcium oscillations upon stimulation by antigen presenting cells. PMID:24086124

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

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.

Probabilistic Output Analysis by Program Manipulation

DEFF Research Database (Denmark)

Rosendahl, Mads; Kirkeby, Maja Hanne

2015-01-01

The aim of a probabilistic output analysis is to derive a probability distribution of possible output values for a program from a probability distribution of its input. We present a method for performing static output analysis, based on program transformation techniques. It generates a probability...

Monitoring of electric-cardio signals based on DSP

Science.gov (United States)

Yan, Yi-xin; Sun, Hui-nan; Lv, Shuang

2008-10-01

Monitoring of electric-cardio signals is the most direct method of discovering heart diseases. This article presents an electric-cardio signal acquisition and processing system based on DSP. According to the features of electric-cardio signals, the proposed system uses the AgCl electrode as electric-cardio signals sensor, and acquires analog signals with AD620 as the prepositional amplifier, and the digital system equipped is with TMS320LF2407A DSP. The design of digital filter and the analysis of heart rate variation are realized by programming in the DSP. Finally the ECG is obtained with P and T waves along with obvious QRS multi-wave characteristics. The system has low power dissipation, low cost and high precision, which meets the requirements for medical instruments.

Nonlinear programming analysis and methods

CERN Document Server

Avriel, Mordecai

2012-01-01

This text provides an excellent bridge between principal theories and concepts and their practical implementation. Topics include convex programming, duality, generalized convexity, analysis of selected nonlinear programs, techniques for numerical solutions, and unconstrained optimization methods.

Energy Analysis Program 1990 annual report

International Nuclear Information System (INIS)

1992-01-01

The Energy Analysis Program has played an active role in the analysis and discussion of energy and environmental issues at several levels. (1) at the international level, with programs as developing scenarios for long-term energy demand in developing countries and organizing leading an analytic effort, ''Energy Efficiency, Developing Countries, and Eastern Europe,'' part of a major effort to increase support for energy efficiency programs worldwide; (2) at national level, the Program has been responsible for assessing energy forecasts and policies affecting energy use (e.g., appliance standards, National Energy Strategy scenarios); and (3) at the state and utility levels, the Program has been a leader in promoting integrated resource utility planning; the collaborative process has led to agreement on a new generation of utility demand-site programs in California, providing an opportunity to use knowledge and analytic techniques of the Program's researchers. We continue to place highest on analyzing energy efficiency, with particular attention given to energy use in buildings. The Program continues its active analysis of international energy issues in Asia (including China), the Soviet Union, South America, and Western Europe. Analyzing the costs and benefits of different levels of standards for residential appliances continues to be the largest single area of research within the Program. The group has developed and applied techniques for forecasting energy demand (or constructing scenarios) for the United States. We have built a new model of industrial energy demand, are in the process of making major changes in our tools for forecasting residential energy demand, have built an extensive and documented energy conservation supply curve of residential energy use, and are beginning an analysis of energy-demand forecasting for commercial buildings

Development of a noise reduction program of a prompt gamma spectrum based on principal component analysis for an explosive detection

International Nuclear Information System (INIS)

Lee, Yun Hee; Im, Hee Jung; Song, Byung ChoI; Park, Yong Joon; Kim, Won Ho; Cho, Jung Hwan

2005-01-01

This work demonstrates a developed program to reduce noises of a prompt gamma-ray spectrum measured by irradiating neutrons into baggage. The noises refer to random variations mainly caused by electrical fluctuations and also by a measurement time. Especially, since the short measurement time yields such a noisy spectrum in which its special peak can not be observed, it is necessary to extract its characteristic signals from the spectrum to identify an explosive hidden in luggage. Principal component analysis(PCA) that is a multivariate statistical technique is closely related to singular value decomposition(SVD). The SVD-based PCA decreases the noise by reconstructing the spectrum after determining the number of principal components corresponding important signals based on the history data that sufficiently describe its population. In this study, we present a visualized program of the above procedure using the MATLAB 7.04 programming language. When our program is started, it requires an arbitrary measured spectrum to be reduced and history spectra as input files. If user selects the files with menu, our program automatically carries out the PCA procedure and provides its noise-reduced spectrum plot as well as the original spectrum plot into an output window. In addition, user can obtain signal-to-noise ratio of an interesting peak by defining the peak and noise ranges with menu

Analysis of computer programming languages

International Nuclear Information System (INIS)

Risset, Claude Alain

1967-01-01

This research thesis aims at trying to identify some methods of syntax analysis which can be used for computer programming languages while putting aside computer devices which influence the choice of the programming language and methods of analysis and compilation. In a first part, the author proposes attempts of formalization of Chomsky grammar languages. In a second part, he studies analytical grammars, and then studies a compiler or analytic grammar for the Fortran language

Dendritic cell maturation: functional specialization through signaling specificity and transcriptional programming.

Science.gov (United States)

Dalod, Marc; Chelbi, Rabie; Malissen, Bernard; Lawrence, Toby

2014-05-16

Dendritic cells (DC) are key regulators of both protective immune responses and tolerance to self-antigens. Soon after their discovery in lymphoid tissues by Steinman and Cohn, as cells with the unique ability to prime naïve antigen-specific T cells, it was realized that DC can exist in at least two distinctive states characterized by morphological, phenotypic and functional changes-this led to the description of DC maturation. It is now well appreciated that there are several subsets of DC in both lymphoid and non-lymphoid tissues of mammals, and these cells show remarkable functional specialization and specificity in their roles in tolerance and immunity. This review will focus on the specific characteristics of DC subsets and how their functional specialization may be regulated by distinctive gene expression programs and signaling responses in both steady-state and in the context of inflammation. In particular, we will highlight the common and distinctive genes and signaling pathways that are associated with the functional maturation of DC subsets. © 2014 The Authors.

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.

Energy Analysis Program 1990 annual report

Energy Technology Data Exchange (ETDEWEB)

1992-01-01

The Energy Analysis Program has played an active role in the analysis and discussion of energy and environmental issues at several levels. (1) at the international level, with programs as developing scenarios for long-term energy demand in developing countries and organizing leading an analytic effort, Energy Efficiency, Developing Countries, and Eastern Europe,'' part of a major effort to increase support for energy efficiency programs worldwide; (2) at national level, the Program has been responsible for assessing energy forecasts and policies affecting energy use (e.g., appliance standards, National Energy Strategy scenarios); and (3) at the state and utility levels, the Program has been a leader in promoting integrated resource utility planning; the collaborative process has led to agreement on a new generation of utility demand-site programs in California, providing an opportunity to use knowledge and analytic techniques of the Program's researchers. We continue to place highest on analyzing energy efficiency, with particular attention given to energy use in buildings. The Program continues its active analysis of international energy issues in Asia (including China), the Soviet Union, South America, and Western Europe. Analyzing the costs and benefits of different levels of standards for residential appliances continues to be the largest single area of research within the Program. The group has developed and applied techniques for forecasting energy demand (or constructing scenarios) for the United States. We have built a new model of industrial energy demand, are in the process of making major changes in our tools for forecasting residential energy demand, have built an extensive and documented energy conservation supply curve of residential energy use, and are beginning an analysis of energy-demand forecasting for commercial buildings.

Enhancement of the automatic ultrasonic signal processing system using digital technology

International Nuclear Information System (INIS)

Koo, In Soo; Park, H. Y.; Suh, Y. S.; Kim, D. Hoon; Huh, S.; Sung, S. H.; Jang, G. S.; Ryoo, S. G.; Choi, J. H.; Kim, Y. H.; Lee, J. C.; Kim, D. Hyun; Park, H. J.; Kim, Y. C.; Lee, J. P.; Park, C. H.; Kim, M. S.

1999-12-01

The objective of this study is to develop the automatic ultrasonic signal processing system which can be used in the inspection equipment to assess the integrity of the reactor vessel by enhancing the performance of the ultrasonic signal processing system. Main activities of this study divided into three categories such as the development of the circuits for generating ultrasonic signal and receiving the signal from the inspection equipment, the development of signal processing algorithm and H/W of the data processing system, and the development of the specification for application programs and system S/W for the analysis and evaluation computer. The results of main activities are as follows 1) the design of the ultrasonic detector and the automatic ultrasonic signal processing system by using the investigation of the state-of-the-art technology in the inside and outside of the country. 2) the development of H/W and S/W of the data processing system based on the results. Especially, the H/W of the data processing system, which have both advantages of digital and analog controls through the real-time digital signal processing, was developed using the DSP which can process the digital signal in the real-time, and was developed not only firmware of the data processing system in order for the peripherals but also the test algorithm of specimen for the calibration. The application programs and the system S/W of the analysis/evaluation computer were developed. Developed equipment was verified by the performance test. Based on developed prototype for the automatic ultrasonic signal processing system, the localization of the overall ultrasonic inspection equipment for nuclear industries would be expected through the further studies of the H/W establishment of real applications, developing the S/W specification of the analysis computer. (author)

Digital signal processing with Matlab examples

CERN Document Server

Giron-Sierra, Jose Maria

2017-01-01

This is the first volume in a trilogy on modern Signal Processing. The three books provide a concise exposition of signal processing topics, and a guide to support individual practical exploration based on MATLAB programs. This book includes MATLAB codes to illustrate each of the main steps of the theory, offering a self-contained guide suitable for independent study. The code is embedded in the text, helping readers to put into practice the ideas and methods discussed. The book is divided into three parts, the first of which introduces readers to periodic and non-periodic signals. The second part is devoted to filtering, which is an important and commonly used application. The third part addresses more advanced topics, including the analysis of real-world non-stationary signals and data, e.g. structural fatigue, earthquakes, electro-encephalograms, birdsong, etc. The book’s last chapter focuses on modulation, an example of the intentional use of non-stationary signals.

The Y2K program for scientific-analysis computer programs at AECL

International Nuclear Information System (INIS)

Popovic, J.; Gaver, C.; Chapman, D.

1999-01-01

The evaluation of scientific-analysis computer programs for year-2000 compliance is part of AECL' s year-2000 (Y2K) initiative, which addresses both the infrastructure systems at AECL and AECL's products and services. This paper describes the Y2K-compliance program for scientific-analysis computer codes. This program involves the integrated evaluation of the computer hardware, middleware, and third-party software in addition to the scientific codes developed in-house. The project involves several steps: the assessment of the scientific computer programs for Y2K compliance, performing any required corrective actions, porting the programs to Y2K-compliant platforms, and verification of the programs after porting. Some programs or program versions, deemed no longer required in the year 2000 and beyond, will be retired and archived. (author)

The Y2K program for scientific-analysis computer programs at AECL

International Nuclear Information System (INIS)

Popovic, J.; Gaver, C.; Chapman, D.

1999-01-01

The evaluation of scientific analysis computer programs for year-2000 compliance is part of AECL's year-2000 (Y2K) initiative, which addresses both the infrastructure systems at AECL and AECL's products and services. This paper describes the Y2K-compliance program for scientific-analysis computer codes. This program involves the integrated evaluation of the computer hardware, middleware, and third-party software in addition to the scientific codes developed in-house. The project involves several steps: the assessment of the scientific computer programs for Y2K compliance, performing any required corrective actions, porting the programs to Y2K-compliant platforms, and verification of the programs after porting. Some programs or program versions, deemed no longer required in the year 2000 and beyond, will be retired and archived. (author)

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...

An implementation of signal processing algorithms for ultrasonic NDE

International Nuclear Information System (INIS)

Ericsson, L.; Stepinski, T.

1994-01-01

Probability of detection flaws during ultrasonic pulse-echo inspection is often limited by the presence of backscattered echoes from the material structure. A digital signal processing technique for removal of this material noise, referred to as split spectrum processing (SSP), has been developed and verified using laboratory experiments during the last decade. The authors have performed recently a limited scale evaluation of various SSP techniques for ultrasonic signals acquired during the inspection of welds in austenitic steel. They have obtained very encouraging results that indicate promising capabilities of the SSP for inspection of nuclear power plants. Thus, a more extensive investigation of the technique using large amounts of ultrasonic data is motivated. This analysis should employ different combinations of materials, flaws and transducers. Due to the considerable number of ultrasonic signals required to verify the technique for future practical use, a custom-made computer software is necessary. At the request of the Swedish nuclear power industry the authors have developed such a program package. The program provides a user-friendly graphical interface and is intended for processing of B-scan data in a flexible way. Assembled in the program are a number of signal processing algorithms including traditional Split Spectrum Processing and the more recent Cut Spectrum Processing algorithm developed by them. The program and some results obtained using the various algorithms are presented in the paper

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.

Programs for nuclear data analysis

International Nuclear Information System (INIS)

Bell, R.A.I.

1975-01-01

The following report details a number of programs and subroutines which are useful for analysis of data from nuclear physics experiments. Most of them are available from pool pack 005 on the IBM1800 computer. All of these programs are stored there as core loads, and the subroutines and functions in relocatable format. The nature and location of other programs are specified as appropriate. (author)

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)

Automatic identification of epileptic seizures from EEG signals using linear programming boosting.

Science.gov (United States)

Hassan, Ahnaf Rashik; Subasi, Abdulhamit

2016-11-01

Computerized epileptic seizure detection is essential for expediting epilepsy diagnosis and research and for assisting medical professionals. Moreover, the implementation of an epilepsy monitoring device that has low power and is portable requires a reliable and successful seizure detection scheme. In this work, the problem of automated epilepsy seizure detection using singe-channel EEG signals has been addressed. At first, segments of EEG signals are decomposed using a newly proposed signal processing scheme, namely complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN). Six spectral moments are extracted from the CEEMDAN mode functions and train and test matrices are formed afterward. These matrices are fed into the classifier to identify epileptic seizures from EEG signal segments. In this work, we implement an ensemble learning based machine learning algorithm, namely linear programming boosting (LPBoost) to perform classification. The efficacy of spectral features in the CEEMDAN domain is validated by graphical and statistical analyses. The performance of CEEMDAN is compared to those of its predecessors to further inspect its suitability. The effectiveness and the appropriateness of LPBoost are demonstrated as opposed to the commonly used classification models. Resubstitution and 10 fold cross-validation error analyses confirm the superior algorithm performance of the proposed scheme. The algorithmic performance of our epilepsy seizure identification scheme is also evaluated against state-of-the-art works in the literature. Experimental outcomes manifest that the proposed seizure detection scheme performs better than the existing works in terms of accuracy, sensitivity, specificity, and Cohen's Kappa coefficient. It can be anticipated that owing to its use of only one channel of EEG signal, the proposed method will be suitable for device implementation, eliminate the onus of clinicians for analyzing a large bulk of data manually, and

Dynamic analysis program for frame structure

International Nuclear Information System (INIS)

Ando, Kozo; Chiba, Toshio

1975-01-01

A general purpose computer program named ISTRAN/FD (Isub(HI) STRucture ANalysis/Frame structure, Dynamic analysis) has been developed for dynamic analysis of three-dimensional frame structures. This program has functions of free vibration analysis, seismic response analysis, graphic display by plotter and CRT, etc. This paper introduces ISTRAN/FD; examples of its application are shown with various problems : idealization of the cantilever, dynamic analysis of the main tower of the suspension bridge, three-dimensional vibration in the plate girder bridge, seismic response in the boiler steel structure, and dynamic properties of the underground LNG tank. In this last example, solid elements, in addition to beam elements, are especially used for the analysis. (auth.)

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"--

A program for activation analysis data processing

International Nuclear Information System (INIS)

Janczyszyn, J.; Loska, L.; Taczanowski, S.

1978-01-01

An ALGOL program for activation analysis data handling is presented. The program may be used either for single channel spectrometry data or for multichannel spectrometry. The calculation of instrumental error and of analysis standard deviation is carried out. The outliers are tested, and the regression line diagram with the related observations are plotted by the program. (author)

Capture programs, analysis, data graphication for the study of the thermometry of the TRIGA Mark III reactor core

International Nuclear Information System (INIS)

Paredes G, L.C.

1991-05-01

This document covers the explanation of the capture programs, analysis and graphs of the data obtained during the measurement of the temperatures of the instrumented fuel element of the TRIGA Mark III reactor and of the coolant one near to this fuel, using the conversion card from Analogic to Digital of 'Data Translation', and using a signal conditioner for five temperature measurers with the help of thermo par type K, developed by the Simulation and Control of the nuclear systems management department, which gives a signal from 0 to 10 Vcd for an interval of temperature of 0 to 1000 C. (Author)

Proceedings of the IEEE Machine Learning for Signal Processing XVII

DEFF Research Database (Denmark)

The seventeenth of a series of workshops sponsored by the IEEE Signal Processing Society and organized by the Machine Learning for Signal Processing Technical Committee (MLSP-TC). The field of machine learning has matured considerably in both methodology and real-world application domains and has...... become particularly important for solution of problems in signal processing. As reflected in this collection, machine learning for signal processing combines many ideas from adaptive signal/image processing, learning theory and models, and statistics in order to solve complex real-world signal processing......, and two papers from the winners of the Data Analysis Competition. The program included papers in the following areas: genomic signal processing, pattern recognition and classification, image and video processing, blind signal processing, models, learning algorithms, and applications of machine learning...

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.

Static Analysis of Functional Programs

NARCIS (Netherlands)

van den Berg, Klaas; van den Broek, P.M.

1994-01-01

In this paper, the static analysis of programs in the functional programming language Miranda is described based on two graph models. A new control-flow graph model of Miranda definitions is presented, and a model with four classes of caligraphs. Standard software metrics are applicable to these

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

Digital signal processing for He3 proportional counter

International Nuclear Information System (INIS)

Zeynalov, Sh.S.; Ahmadov, Q.S.

2010-01-01

Full text : Data acquisition systems for nuclear spectroscopy have traditionally been based on systems with analog shaping amplifiers followed by analog-to-digital converters. Recently, however, new systems based on digital signal processing make possible to replace the analog shaping and timing circuitry the numerical algorithms to derive properties of the pulse such as its amplitude. DSP is a fully numerical analysis of the detector pulse signals and this technique demonstrates significant advantages over analog systems in some circumstances. From a mathematical point of view, one can consider the signal evolution from the detector to the ADC as a sequence of transformations that can be described by precisely defined mathematical expressions. Digital signal processing with ADCs has the possibility to utilize further information on the signal pulses from radiation detectors. In the experiment each step of the signal generation in the 3He filled proportional counter was described using digital signal processing techniques (DSP). The electronic system has consisted of a detector, a preamplifier and a digital oscilloscope. The pulses from the detector were digitized using a digital storage oscilloscope. This oscilloscope allowed signal digitization with accuracy of 8 bit (256 levels) and with frequency of up to 5 * 10 8 samples/s. As a neutron source was used Cf-252. To obtain detector output current pulse I(t) created by the motions of the ions/electrons pairs was written an algorithm which can easily be programmed using modern computer programming languages.

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.

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...

Analysis of interference of QPSK and QDPSK modulation signals by mathematical

Science.gov (United States)

Li, Dairuo; Xu, Kai

2017-03-01

In today's society, with the rapid development and extensive application of the information technology of the network central station and the integrated information system technology, information plays an important role in the military communication, mastering the information right to the competition Important role, how to protect one's own security, smooth access to and transmission of information, and to maximize the elimination of interference has become an important issue at home and abroad. QPSK modulation and its improved QPSK modulation as the mainstream signal modulation, the most widely used. In this paper, the principle of QPSK and QDPSK modulation and demodulation are introduced in this paper. Then, how to interfere with QPSK modulation signal is analyzed, and the interference of QPSK modulation signal is simulated by Matlab scripting program, which can be used in the next step. And to study the next step of anti-jamming measures provided the basis and preparatory work.

Analysis of Logic Programs Using Regular Tree Languages

DEFF Research Database (Denmark)

Gallagher, John Patrick

2012-01-01

The eld of nite tree automata provides fundamental notations and tools for reasoning about set of terms called regular or recognizable tree languages. We consider two kinds of analysis using regular tree languages, applied to logic programs. The rst approach is to try to discover automatically...... a tree automaton from a logic program, approximating its minimal Herbrand model. In this case the input for the analysis is a program, and the output is a tree automaton. The second approach is to expose or check properties of the program that can be expressed by a given tree automaton. The input...... to the analysis is a program and a tree automaton, and the output is an abstract model of the program. These two contrasting abstract interpretations can be used in a wide range of analysis and verication problems....

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.

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.

Pointer Analysis for JavaScript Programming Tools

DEFF Research Database (Denmark)

Feldthaus, Asger

Tools that can assist the programmer with tasks, such as, refactoring or code navigation, have proven popular for Java, C#, and other programming languages. JavaScript is a widely used programming language, and its users could likewise benefit from such tools, but the dynamic nature of the language...... is an obstacle for the development of these. Because of this, tools for JavaScript have long remained ineffective compared to those for many other programming languages. Static pointer analysis can provide a foundation for more powerful tools, although the design of this analysis is itself a complicated endeavor....... In this work, we explore techniques for performing pointer analysis of JavaScript programs, and we find novel applications of these techniques. In particular, we demonstrate how these can be used for code navigation, automatic refactoring, semi-automatic refactoring of incomplete programs, and checking of type...

Proteomic analysis of the signaling pathway mediated by the heterotrimeric G? protein Pga1 of Penicillium chrysogenum

OpenAIRE

Carrasco-Navarro, Ulises; Vera-Estrella, Rosario; Barkla, Bronwyn J.; Z??iga-Le?n, Eduardo; Reyes-Vivas, Horacio; Fern?ndez, Francisco J.; Fierro, Francisco

2016-01-01

Background The heterotrimeric G? protein Pga1-mediated signaling pathway regulates the entire developmental program in Penicillium chrysogenum, from spore germination to the formation of conidia. In addition it participates in the regulation of penicillin biosynthesis. We aimed to advance the understanding of this key signaling pathway using a proteomics approach, a powerful tool to identify effectors participating in signal transduction pathways. Results Penicillium chrysogenum mutants with ...

Biodiesel Emissions Analysis Program

Science.gov (United States)

Using existing data, the EPA's biodiesel emissions analysis program sought to quantify the air pollution emission effects of biodiesel for diesel engines that have not been specifically modified to operate on biodiesel.

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.

SignalR blueprints

CERN Document Server

Ingebrigtsen, Einar

2015-01-01

This book is designed for software developers, primarily those with knowledge of C#, .NET, and JavaScript. Good knowledge and understanding of SignalR is assumed to allow efficient programming of core elements and applications in SignalR.

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

Probabilistic Structural Analysis Program

Science.gov (United States)

Pai, Shantaram S.; Chamis, Christos C.; Murthy, Pappu L. N.; Stefko, George L.; Riha, David S.; Thacker, Ben H.; Nagpal, Vinod K.; Mital, Subodh K.

2010-01-01

NASA/NESSUS 6.2c is a general-purpose, probabilistic analysis program that computes probability of failure and probabilistic sensitivity measures of engineered systems. Because NASA/NESSUS uses highly computationally efficient and accurate analysis techniques, probabilistic solutions can be obtained even for extremely large and complex models. Once the probabilistic response is quantified, the results can be used to support risk-informed decisions regarding reliability for safety-critical and one-of-a-kind systems, as well as for maintaining a level of quality while reducing manufacturing costs for larger-quantity products. NASA/NESSUS has been successfully applied to a diverse range of problems in aerospace, gas turbine engines, biomechanics, pipelines, defense, weaponry, and infrastructure. This program combines state-of-the-art probabilistic algorithms with general-purpose structural analysis and lifting methods to compute the probabilistic response and reliability of engineered structures. Uncertainties in load, material properties, geometry, boundary conditions, and initial conditions can be simulated. The structural analysis methods include non-linear finite-element methods, heat-transfer analysis, polymer/ceramic matrix composite analysis, monolithic (conventional metallic) materials life-prediction methodologies, boundary element methods, and user-written subroutines. Several probabilistic algorithms are available such as the advanced mean value method and the adaptive importance sampling method. NASA/NESSUS 6.2c is structured in a modular format with 15 elements.

Using answer set programming to integrate RNA expression with signalling pathway information to infer how mutations affect ageing.

Science.gov (United States)

Papatheodorou, Irene; Ziehm, Matthias; Wieser, Daniela; Alic, Nazif; Partridge, Linda; Thornton, Janet M

2012-01-01

A challenge of systems biology is to integrate incomplete knowledge on pathways with existing experimental data sets and relate these to measured phenotypes. Research on ageing often generates such incomplete data, creating difficulties in integrating RNA expression with information about biological processes and the phenotypes of ageing, including longevity. Here, we develop a logic-based method that employs Answer Set Programming, and use it to infer signalling effects of genetic perturbations, based on a model of the insulin signalling pathway. We apply our method to RNA expression data from Drosophila mutants in the insulin pathway that alter lifespan, in a foxo dependent fashion. We use this information to deduce how the pathway influences lifespan in the mutant animals. We also develop a method for inferring the largest common sub-paths within each of our signalling predictions. Our comparisons reveal consistent homeostatic mechanisms across both long- and short-lived mutants. The transcriptional changes observed in each mutation usually provide negative feedback to signalling predicted for that mutation. We also identify an S6K-mediated feedback in two long-lived mutants that suggests a crosstalk between these pathways in mutants of the insulin pathway, in vivo. By formulating the problem as a logic-based theory in a qualitative fashion, we are able to use the efficient search facilities of Answer Set Programming, allowing us to explore larger pathways, combine molecular changes with pathways and phenotype and infer effects on signalling in in vivo, whole-organism, mutants, where direct signalling stimulation assays are difficult to perform. Our methods are available in the web-service NetEffects: http://www.ebi.ac.uk/thornton-srv/software/NetEffects.

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...

The nuclear analysis program at MURR

International Nuclear Information System (INIS)

Glascock, M.D.

1993-01-01

The University of Missouri-Columbia (MU) has continually upgraded research facilities and programs at the MU research reactor (MURR) throughout its 26-yr history. The Nuclear Analysis Program (NAP) area has participated in these upgrades over the years. As one of the largest activation analysis laboratories on a university campus, the activities of the NAP are broadly representative of the diversity of applications for activation analysis and related nuclear science. This paper describes the MURR's NAP and several of the research, education, and service projects in which the laboratory is currently engaged

Syntheses by rules of the speech signal in its amplitude-time representation - melody study - phonetic, translation program

International Nuclear Information System (INIS)

Santamarina, Carole

1975-01-01

The present paper deals with the real-time speech synthesis implemented on a minicomputer. A first program translates the orthographic text into a string of phonetic codes, which is then processed by the synthesis program itself. The method used, a synthesis by rules, directly computes the speech signal in its amplitude-time representation. Emphasis has been put on special cases (diphthongs, 'e muet', consonant-consonant transition) and the implementation of the rhythm and of the melody. (author) [fr

Program Analysis and Its Relevance for Educational Research

Directory of Open Access Journals (Sweden)

Bernd Käpplinger

2008-01-01

Full Text Available Program analyses are frequently used in research on continuing education. The use of such analyses will be described in this article. Existing data sources, research topics, qualitative, quantitative and mixed methods, will be discussed. Three types of program analysis will be developed. The article ends with a discussion of the advantages and disadvantages of program analysis in contrast to questionnaires. Future developments and challenges will be sketched in the conclusion. Recommendations for the future development of program analysis will be given. URN: urn:nbn:de:0114-fqs0801379

Differential TCR signals for T helper cell programming.

Science.gov (United States)

Morel, Penelope A

2018-05-02

Upon encounter with their cognate antigen naïve CD4 T cells become activated and are induced to differentiate into several possible T helper (Th) cell subsets. This differentiation depends on a number of factors including antigen presenting cells, cytokines and costimulatory molecules. The strength of the T cell receptor (TCR) signal, related to the affinity of TCR for antigen and antigen dose, has emerged as a dominant factor in determining Th cell fate. Recent studies have revealed that TCR signals of high or low strength do not simply induce quantitatively different signals in the T cells, but rather qualitatively distinct pathways can be induced based on TCR signal strength. This review examines the recent literature in this area and highlights important new developments in our understanding of Th cell differentiation and TCR signal strength. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Integrating computer programs for engineering analysis and design

Science.gov (United States)

Wilhite, A. W.; Crisp, V. K.; Johnson, S. C.

1983-01-01

The design of a third-generation system for integrating computer programs for engineering and design has been developed for the Aerospace Vehicle Interactive Design (AVID) system. This system consists of an engineering data management system, program interface software, a user interface, and a geometry system. A relational information system (ARIS) was developed specifically for the computer-aided engineering system. It is used for a repository of design data that are communicated between analysis programs, for a dictionary that describes these design data, for a directory that describes the analysis programs, and for other system functions. A method is described for interfacing independent analysis programs into a loosely-coupled design system. This method emphasizes an interactive extension of analysis techniques and manipulation of design data. Also, integrity mechanisms exist to maintain database correctness for multidisciplinary design tasks by an individual or a team of specialists. Finally, a prototype user interface program has been developed to aid in system utilization.

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.

Digital signal processing for He3 proportional counter

International Nuclear Information System (INIS)

Ahmadov, Q.S.; Institute of Radiation Problems, ANAS, Baku

2011-01-01

Full text: Data acquisition systems for nuclear spectroscopy have traditionally been based on systems with analog shaping amplifiers followed by analog-to-digital converters. Recently, however, new systems based on digital signal processing allow us to replace the analog shaping and timing circuitry the numerical algorithms to derive properties of the pulse such as its amplitude. DSP is a fully numerical analysis of the detector pulse signals and this technique demonstrates significant advantages over analog systems in some circumstances. From a mathematical point of view, one can consider the signal evolution from the detector to the ADC as a sequence of transformations that can be described by precisely defined mathematical expressions.Digital signal processing with ADCs has the possibility to utilize further information on the signal pulses from radiation detectors [1] [2]. In the experiment each step of the signal generation in the 3He filled proportional counter was described using digital signal processing techniques (DSP). The electronic system has consisted of a detector, a preamplifier and a digital oscilloscope. The pulses from the detector were digitized using a OTSZS-02 (250USB)-4 digital storage oscilloscope from ZAO R UDNEV-SHILYAYEV . This oscilloscope allowed signal digitization with accuracy of 8 bit(256 levels) and with frequency of up to 5.10''8 samples/s. As a neutron source was used Cf-252.To obtain detector output current pulse I(t) created by the motions of the ions/electrons pairs was written an algorithm which can easily be programmed using modern computer programming languages

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.

Status of CHAP: composite HTGR analysis program

International Nuclear Information System (INIS)

Secker, P.A.; Gilbert, J.S.

1975-12-01

Development of an HTGR accident simulation program is in progress for the prediction of the overall HTGR plant transient response to various initiating events. The status of the digital computer program named CHAP (Composite HTGR Analysis Program) as of June 30, 1975, is given. The philosophy, structure, and capabilities of the CHAP code are discussed. Mathematical descriptions are given for those HTGR components that have been modeled. Component model validation and evaluation using auxiliary analysis codes are also discussed

Application of an automatic pattern recognition for aleatory signals for the surveillance of nuclear reactor and rotating machinery

International Nuclear Information System (INIS)

Nascimento, J.A. do.

1982-02-01

An automatic pattern recognition program PSDREC, developed for the surveillance of nuclear reactor and rotating machinery is described and the relevant theory is outlined. Pattern recognition analysis of noise signals is a powerful technique for assessing 'system normality' in dynamic systems. This program, with applies 8 statistical tests to calculated power spectral density (PSD) distribution, was earlier installed in a PDP-11/45 computer at IPEN. To analyse recorded signals from three systems, namely an operational BWR power reactor (neutron signals), a water pump and a diesel engine (vibration signals) this technique was used. Results of the tests are considered satisfactory. (Author) [pt

Single-shell tank retrieval program mission analysis report

Energy Technology Data Exchange (ETDEWEB)

Stokes, W.J.

1998-08-11

This Mission Analysis Report was prepared to provide the foundation for the Single-Shell Tank (SST) Retrieval Program, a new program responsible for waste removal for the SSTS. The SST Retrieval Program is integrated with other Tank Waste Remediation System activities that provide the management, technical, and operations elements associated with planning and execution of SST and SST Farm retrieval and closure. This Mission Analysis Report provides the basis and strategy for developing a program plan for SST retrieval. This Mission Analysis Report responds to a US Department of Energy request for an alternative single-shell tank retrieval approach (Taylor 1997).

Single-shell tank retrieval program mission analysis report

International Nuclear Information System (INIS)

Stokes, W.J.

1998-01-01

This Mission Analysis Report was prepared to provide the foundation for the Single-Shell Tank (SST) Retrieval Program, a new program responsible for waste removal for the SSTS. The SST Retrieval Program is integrated with other Tank Waste Remediation System activities that provide the management, technical, and operations elements associated with planning and execution of SST and SST Farm retrieval and closure. This Mission Analysis Report provides the basis and strategy for developing a program plan for SST retrieval. This Mission Analysis Report responds to a US Department of Energy request for an alternative single-shell tank retrieval approach (Taylor 1997)

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.

Program Analysis Scenarios in Rascal

NARCIS (Netherlands)

M.A. Hills (Mark); P. Klint (Paul); J.J. Vinju (Jurgen); F. Durán

2012-01-01

textabstractRascal is a meta programming language focused on the implementation of domain-specific languages and on the rapid construction of tools for software analysis and software transformation. In this paper we focus on the use of Rascal for software analysis. We illustrate a range of scenarios

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)

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.

Matlab programming for numerical analysis

CERN Document Server

Lopez, Cesar

2014-01-01

MATLAB is a high-level language and environment for numerical computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java. Programming MATLAB for Numerical Analysis introduces you to the MATLAB language with practical hands-on instructions and results, allowing you to quickly achieve your goals. You will first become

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

Directory of Open Access Journals (Sweden)

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.

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

Directory of Open Access Journals (Sweden)

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.

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.

Seismic analysis program group: SSAP

International Nuclear Information System (INIS)

Uchida, Masaaki

2002-05-01

A group of programs SSAP has been developed, each member of which performs seismic calculation using simple single-mass system model or multi-mass system model. For response of structures to a transverse s-wave, a single-mass model program calculating response spectrum and a multi-mass model program are available. They perform calculation using the output of another program, which produces simulated earthquakes having the so-called Ohsaki-spectrum characteristic. Another program has been added, which calculates the response of one-dimensional multi-mass systems to vertical p-wave input. It places particular emphasis on the analysis of the phenomena observed at some shallow earthquakes in which stones jump off the ground. Through a series of test calculations using these programs, some interesting information has been derived concerning the validity of superimposing single-mass model calculation, and also the condition for stones to jump. (author)

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

Directory of Open Access Journals (Sweden)

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

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.

The DECMU: a digital device for delayed analysis of multi-frequency eddy current signals

International Nuclear Information System (INIS)

Pigeon, Michel.

1981-08-01

A delayed data analysis system has been realized by the CEA and Intercontrole for in-service inspection of steam generators of nuclear plants by multifrequency eddy current testing. This device allows, out of the plant, adjustment during switching of the probes, graph recording and analysis for defect signal qualification. The equipment contains an analog mixing device, as IC3FA multi-frequency appartus, but has in addition a memory allowing data cycling and signal isolation for adjustment or analysis [fr

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.

Lactation Biology Symposium: Lactocrine signaling and developmental programming

Science.gov (United States)

Lactocrine signaling is defined as transmission of bioactive factors from mother to offspring as a consequence of nursing. Lactocrine transmission of signaling molecules may be an evolutionarily conserved process through which bioactive factors necessary for support of neonatal development are deliv...

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

RAWS II: A MULTIPLE REGRESSION ANALYSIS PROGRAM,

Science.gov (United States)

This memorandum gives instructions for the use and operation of a revised version of RAWS, a multiple regression analysis program. The program...of preprocessed data, the directed retention of variable, listing of the matrix of the normal equations and its inverse, and the bypassing of the regression analysis to provide the input variable statistics only. (Author)

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.

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)

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

Effective Analysis of C Programs by Rewriting Variability

DEFF Research Database (Denmark)

Iosif-Lazar, Alexandru Florin; Melo, Jean; Dimovski, Aleksandar

2017-01-01

and effective analysis and verification of real-world C program families. Importance. We report some interesting variability-related bugs that we discovered using various state-of-the-art single-program C verification tools, such as Frama-C, Clang, LLBMC.......Context. Variability-intensive programs (program families) appear in many application areas and for many reasons today. Different family members, called variants, are derived by switching statically configurable options (features) on and off, while reuse of the common code is maximized. Inquiry....... Verification of program families is challenging since the number of variants is exponential in the number of features. Existing single-program analysis and verification tools cannot be applied directly to program families, and designing and implementing the corresponding variability-aware versions is tedious...

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.

R data analysis without programming

CERN Document Server

Gerbing, David W

2013-01-01

This book prepares readers to analyze data and interpret statistical results using R more quickly than other texts. R is a challenging program to learn because code must be created to get started. To alleviate that challenge, Professor Gerbing developed lessR. LessR extensions remove the need to program. By introducing R through less R, readers learn how to organize data for analysis, read the data into R, and produce output without performing numerous functions and programming exercises first. With lessR, readers can select the necessary procedure and change the relevant variables without pro

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

Probabilistic Resource Analysis by Program Transformation

DEFF Research Database (Denmark)

Kirkeby, Maja Hanne; Rosendahl, Mads

2016-01-01

The aim of a probabilistic resource analysis is to derive a probability distribution of possible resource usage for a program from a probability distribution of its input. We present an automated multi-phase rewriting based method to analyze programs written in a subset of C. It generates...

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

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.

Seals Research at AlliedSignal

Science.gov (United States)

Ullah, M. Rifat

1996-01-01

A consortium has been formed to address seal problems in the Aerospace sector of Allied Signal, Inc. The consortium is represented by makers of Propulsion Engines, Auxiliary Power Units, Gas Turbine Starters, etc. The goal is to improve Face Seal reliability, since Face Seals have become reliability drivers in many of our product lines. Several research programs are being implemented simultaneously this year. They include: Face Seal Modeling and Analysis Methodology; Oil Cooling of Seals; Seal Tracking Dynamics; Coking Formation & Prevention; and Seal Reliability Methods.

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

Work program analysis - defining the capability/risk plan

International Nuclear Information System (INIS)

Hrinivich, W.A.

2004-01-01

Bruce Power has developed and implemented an analysis methodology (Work Program Analysis) to assess and address corporate business risk associated with work group capability. Work Program Analysis is proving to be an excellent tool for identifying and supporting key business decisions facing the line and senior management at Bruce Power. The following describes the methodology, its application and the results achieved. (author)

An Effective Model of the Retinoic Acid Induced HL-60 Differentiation Program.

Science.gov (United States)

Tasseff, Ryan; Jensen, Holly A; Congleton, Johanna; Dai, David; Rogers, Katharine V; Sagar, Adithya; Bunaciu, Rodica P; Yen, Andrew; Varner, Jeffrey D

2017-10-30

In this study, we present an effective model All-Trans Retinoic Acid (ATRA)-induced differentiation of HL-60 cells. The model describes reinforcing feedback between an ATRA-inducible signalsome complex involving many proteins including Vav1, a guanine nucleotide exchange factor, and the activation of the mitogen activated protein kinase (MAPK) cascade. We decomposed the effective model into three modules; a signal initiation module that sensed and transformed an ATRA signal into program activation signals; a signal integration module that controlled the expression of upstream transcription factors; and a phenotype module which encoded the expression of functional differentiation markers from the ATRA-inducible transcription factors. We identified an ensemble of effective model parameters using measurements taken from ATRA-induced HL-60 cells. Using these parameters, model analysis predicted that MAPK activation was bistable as a function of ATRA exposure. Conformational experiments supported ATRA-induced bistability. Additionally, the model captured intermediate and phenotypic gene expression data. Knockout analysis suggested Gfi-1 and PPARg were critical to the ATRAinduced differentiation program. These findings, combined with other literature evidence, suggested that reinforcing feedback is central to hyperactive signaling in a diversity of cell fate programs.

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

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.

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...

Computer program for analysis of hemodynamic response to head-up tilt test

Science.gov (United States)

ŚwiÄ tek, Eliza; Cybulski, Gerard; Koźluk, Edward; PiÄ tkowska, Agnieszka; Niewiadomski, Wiktor

2014-11-01

The aim of this work was to create a computer program, written in the MATLAB environment, which enables the visualization and analysis of hemodynamic parameters recorded during a passive tilt test using the CNS Task Force Monitor System. The application was created to help in the assessment of the relationship between the values and dynamics of changes of the selected parameters and the risk of orthostatic syncope. The signal analysis included: R-R intervals (RRI), heart rate (HR), systolic blood pressure (sBP), diastolic blood pressure (dBP), mean blood pressure (mBP), stroke volume (SV), stroke index (SI), cardiac output (CO), cardiac index (CI), total peripheral resistance (TPR), total peripheral resistance index (TPRI), ventricular ejection time (LVET) and thoracic fluid content (TFC). The program enables the user to visualize waveforms for a selected parameter and to perform smoothing with selected moving average parameters. It allows one to construct the graph of means for any range, and the Poincare plot for a selected time range. The program automatically determines the average value of the parameter before tilt, its minimum and maximum value immediately after changing positions and the times of their occurrence. It is possible to correct the automatically detected points manually. For the RR interval, it determines the acceleration index (AI) and the brake index (BI). It is possible to save calculated values to an XLS with a name specified by user. The application has a user-friendly graphical interface and can run on a computer that has no MATLAB software.

Analysis and Implement of Broadcast Program Monitoring Data

Directory of Open Access Journals (Sweden)

Song Jin Bao

2016-01-01

Full Text Available With the rapid development of the radio and TV industry and the implementation of INT (the integration of telecommunications networks, cable TV networks and the Internet, the contents of programs and advertisements is showing massive, live and interactive trends. In order to meet the security of radio and television, the broadcast of information have to be controlled and administered. In order to master the latest information of public opinion trends through radio and television network, it is necessary research the specific industry applications of broadcast program monitoring. In this paper, the importance of broadcast monitoring in public opinion analysis is firstly analysed. The monitoring radio and television programs broadcast system architecture is proposed combining with the practice, focusing on the technical requirements and implementation process of program broadcast, advertisement broadcast and TV station broadcast monitoring. The more efficient information is generated through statistical analysis, which provides data analysis for radio and television public opinion analysis.

Development of Performance Analysis Program for an Axial Compressor with Meanline Analysis

International Nuclear Information System (INIS)

Park, Jun Young; Park, Moo Ryong; Choi, Bum Suk; Song, Je Wook

2009-01-01

Axial-flow compressor is one of the most important parts of gas turbine units with axial turbine and combustor. Therefore, precise prediction of performance is very important for development of new compressor or modification of existing one. Meanline analysis is a simple, fast and powerful method for performance prediction of axial-flow compressors with different geometries. So, Meanline analysis is frequently used in preliminary design stage and performance analysis for given geometry data. Much correlations for meanline analysis have been developed theoretically and experimentally for estimating various types of losses and flow deviation angle for long time. In present study, meanline analysis program was developed to estimate compressor losses, incidence angles, deviation angles, stall and surge conditions with many correlations. Performance prediction of one stage axial compressors is conducted with this meanline analysis program. The comparison between experimental and numerical results show a good agreement. This meanline analysis program can be used for various types of single stage axial-flow compressors with different geometries, as well as multistage axial-flow compressors

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.

Program packages for dynamics systems analysis and design

International Nuclear Information System (INIS)

Athani, V.V.

1976-01-01

The development of computer program packages for dynamic system analysis and design are reported. The purpose of developing these program packages is to take the burden of writing computer programs off the mind of the system engineer and to enable him to concentrate on his main system analysis and design work. Towards this end, four standard computer program packages have been prepared : (1) TFANA - starting from system transfer function this program computes transient response, frequency response, root locus and stability by Routh Hurwitz criterion, (2) TFSYN - classical synthesis using algebraic method of Shipley, (3) MODANA - starting from state equations of the system this program computes solution of state equations, controllability, observability and stability, (4) OPTCON - This program obtains solutions of (i) linear regulator problem, (ii) servomechanism problems and (iii) problem of pole placement. The paper describes these program packages with the help of flowcharts and illustrates their use with the help of examples. (author)

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)

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.

Language-Agnostic Reproducible Data Analysis Using Literate Programming.

Science.gov (United States)

Vassilev, Boris; Louhimo, Riku; Ikonen, Elina; Hautaniemi, Sampsa

2016-01-01

A modern biomedical research project can easily contain hundreds of analysis steps and lack of reproducibility of the analyses has been recognized as a severe issue. While thorough documentation enables reproducibility, the number of analysis programs used can be so large that in reality reproducibility cannot be easily achieved. Literate programming is an approach to present computer programs to human readers. The code is rearranged to follow the logic of the program, and to explain that logic in a natural language. The code executed by the computer is extracted from the literate source code. As such, literate programming is an ideal formalism for systematizing analysis steps in biomedical research. We have developed the reproducible computing tool Lir (literate, reproducible computing) that allows a tool-agnostic approach to biomedical data analysis. We demonstrate the utility of Lir by applying it to a case study. Our aim was to investigate the role of endosomal trafficking regulators to the progression of breast cancer. In this analysis, a variety of tools were combined to interpret the available data: a relational database, standard command-line tools, and a statistical computing environment. The analysis revealed that the lipid transport related genes LAPTM4B and NDRG1 are coamplified in breast cancer patients, and identified genes potentially cooperating with LAPTM4B in breast cancer progression. Our case study demonstrates that with Lir, an array of tools can be combined in the same data analysis to improve efficiency, reproducibility, and ease of understanding. Lir is an open-source software available at github.com/borisvassilev/lir.

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.

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)

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)

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.

The signal extraction of fetal heart rate based on wavelet transform and BP neural network

Science.gov (United States)

Yang, Xiao Hong; Zhang, Bang-Cheng; Fu, Hu Dai

2005-04-01

This paper briefly introduces the collection and recognition of bio-medical signals, designs the method to collect FM signals. A detailed discussion on the system hardware, structure and functions is also given. Under LabWindows/CVI,the hardware and the driver do compatible, the hardware equipment work properly actively. The paper adopts multi threading technology for real-time analysis and makes use of latency time of CPU effectively, expedites program reflect speed, improves the program to perform efficiency. One threading is collecting data; the other threading is analyzing data. Using the method, it is broaden to analyze the signal in real-time. Wavelet transform to remove the main interference in the FM and by adding time-window to recognize with BP network; Finally the results of collecting signals and BP networks are discussed. 8 pregnant women's signals of FM were collected successfully by using the sensor. The correctness rate of BP network recognition is about 83.3% by using the above measure.

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

User's guide for signal validation software: Final report

International Nuclear Information System (INIS)

Swisher, V.I.

1987-09-01

Northeast Utilities has implemented a real-time signal validation program into the safety parameter display systems (SPDS) at Millstone Units 2 and 3. Signal validation has been incorporated to improve the reliability of the information being used in the SPDS. Signal validation uses Parity Space Vector Analysis to process SPDS sensor data. The Parity Space algorithm determines consistency among independent, redundant input measurements. This information is then used to calculate a validated estimate of that parameter. Additional logic is incorporated to compare partially redundant measurement data. In both plants the SPDS has been designed to monitor the status of critical safety functions (CSFs) and provide information that can be used with plant-specific emergency operating procedures (EOPs). However the CSF logic, EOPs, and complement of plant sensors vary for these plants due to their different design characteristics (MP2 - 870 MWe Combustion Engineering PWR, MP3 - 1150 MWe Westinghouse PWR). These differences in plant design and information requirements result in a variety of signal validation applications

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)

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

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

WellReader: a MATLAB program for the analysis of fluorescence and luminescence reporter gene data.

Science.gov (United States)

Boyer, Frédéric; Besson, Bruno; Baptist, Guillaume; Izard, Jérôme; Pinel, Corinne; Ropers, Delphine; Geiselmann, Johannes; de Jong, Hidde

2010-05-01

Fluorescent and luminescent reporter gene systems in combination with automated microplate readers allow real-time monitoring of gene expression on the population level at high precision and sampling density. This generates large amounts of data for the analysis of which computer tools are missing to date. We have developed WellReader, a MATLAB program for the analysis of fluorescent and luminescent reporter gene data. WellReader allows the user to load the output files of microplate readers, remove outliers, correct for background effects and smooth and fit the data. Moreover, it computes biologically relevant quantities from the measured signals, notably promoter activities and protein concentrations, and compares the resulting expression profiles of different genes under different conditions. WellReader is available under a LGPL licence at http://prabi1.inrialpes.fr/trac/wellreader.

The PUMA test program and data analysis

International Nuclear Information System (INIS)

Han, J.T.; Morrison, D.L.

1997-01-01

The PUMA test program is sponsored by the U.S. Nuclear Regulatory Commission to provide data that are relevant to various Boiling Water Reactor phenomena. The author briefly describes the PUMA test program and facility, presents the objective of the program, provides data analysis for a large-break loss-of-coolant accident test, and compares the data with a RELAP5/MOD 3.1.2 calculation

Assessment of non-linear analysis finite element program (NONSAP) for inelastic analysis

International Nuclear Information System (INIS)

Chang, T.Y.; Prachuktam, S.; Reich, M.

1976-11-01

An assessment on a nonlinear structural analysis finite element program called NONSAP is given with respect to its inelastic analysis capability for pressure vessels and components. The assessment was made from the review of its theoretical basis and bench mark problem runs. It was found that NONSAP has only limited capability for inelastic analysis. However, the program was written flexible enough that it can be easily extended or modified to suit the user's need. Moreover, some of the numerical difficulties in using NONSAP are pointed out

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 performed in cooperation with the SALE program, (1)

International Nuclear Information System (INIS)

Tuboya, Takao; Wada, Yukio; Suzuki, Takeshi

1978-01-01

One of the objects of the SALE (Safeguard Analytical Laboratory Evaluation) program is a development of technique in safeguard and accountability. The SALE program was established by the United States Atomic Energy Commission's New Brunswick Laboratory in 1970. Six years later, SALE program has grown into a worldwide quality control program, receiving analysis results from about 60 laboratories that includes 19 non-U.S. laboratories. All laboratories, participating at present or in the past in the SALE program are listed in Table 1. By 1973, the program was expanded to include six different materials; uranium dioxide (UO 2 ), uranyl nitrate (U-NO 3 ), plutonium dioxide (PuO 2 ), plutonium nitrate (Pu-NO 3 ), uranium-plutonium mixed oxides [(Pu,U)O 2 ], and uranium-plutonium mixed nitrates (Pu-U-NO 3 ). PNC has joined in this program in 1975 for the analysis of samples shown in Table 2. SALE program participants analyze, on a bimonthly basis, materials supplied by the New Brunswick Laboratory (NBL) and report measurement results to NBL for evaluation and inclusion in the bimonthly reports. Present paper describes analysis result and evaluations for these samples which were measured in 1975 -- 1976. (author)

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.

Expert system for eddy current signal analysis: non destructive testing of steam generator tubings

International Nuclear Information System (INIS)

Benoist, B.

1991-01-01

Automatic analysis, by computer, of defect signals in steam generator tubes, based on Eddy current multifrequency technique, is must often inefficient due to pilgrim noise. The first step is to use a method that allows us to eleminate the noise: the adaptative interpolation. Thanks to this method, which ensures reliable data on each channel, the analysis can be realised by taking into account the data corresponding to each basic or mixed channel. By correlating these diverse data, we can class the signals according to two types of defects: single defects (symmetrical), multiple defects (several in the same place). The second step is to use an expert system which allows a reliable diagnosis for whatever family the defect belongs to. According to this classification, analysis is continued and results in the characterization of the defect. The expert system has already been developed with the general purpose application expert system shell SUPER, which is briefly described. The knowledge base (SOCRATE) and the specific tools developed for this application are thoroughly described. The first results obtained with signals corresponding to real defects, that have been recorded in different places, are presented and discussed. The expert system is revealed efficient in all the studied cases, even with signals obtained in very noisy environments [fr

GUI program to compute probabilistic seismic hazard analysis

International Nuclear Information System (INIS)

Shin, Jin Soo; Chi, H. C.; Cho, J. C.; Park, J. H.; Kim, K. G.; Im, I. S.

2006-12-01

The development of program to compute probabilistic seismic hazard is completed based on Graphic User Interface(GUI). The main program consists of three part - the data input processes, probabilistic seismic hazard analysis and result output processes. The probabilistic seismic hazard analysis needs various input data which represent attenuation formulae, seismic zoning map, and earthquake event catalog. The input procedure of previous programs based on text interface take a much time to prepare the data. The data cannot be checked directly on screen to prevent input erroneously in existing methods. The new program simplifies the input process and enable to check the data graphically in order to minimize the artificial error within limits of the possibility

TRU Waste Management Program. Cost/schedule optimization analysis

International Nuclear Information System (INIS)

Detamore, J.A.; Raudenbush, M.H.; Wolaver, R.W.; Hastings, G.A.

1985-10-01

This Current Year Work Plan presents in detail a description of the activities to be performed by the Joint Integration Office Rockwell International (JIO/RI) during FY86. It breaks down the activities into two major work areas: Program Management and Program Analysis. Program Management is performed by the JIO/RI by providing technical planning and guidance for the development of advanced TRU waste management capabilities. This includes equipment/facility design, engineering, construction, and operations. These functions are integrated to allow transition from interim storage to final disposition. JIO/RI tasks include program requirements identification, long-range technical planning, budget development, program planning document preparation, task guidance development, task monitoring, task progress information gathering and reporting to DOE, interfacing with other agencies and DOE lead programs, integrating public involvement with program efforts, and preparation of reports for DOE detailing program status. Program Analysis is performed by the JIO/RI to support identification and assessment of alternatives, and development of long-term TRU waste program capabilities. These analyses include short-term analyses in response to DOE information requests, along with performing an RH Cost/Schedule Optimization report. Systems models will be developed, updated, and upgraded as needed to enhance JIO/RI's capability to evaluate the adequacy of program efforts in various fields. A TRU program data base will be maintained and updated to provide DOE with timely responses to inventory related questions

Evaluation of Fourier integral. Spectral analysis of seismic events

International Nuclear Information System (INIS)

Chitaru, Cristian; Enescu, Dumitru

2003-01-01

Spectral analysis of seismic events represents a method for great earthquake prediction. The seismic signal is not a sinusoidal signal; for this, it is necessary to find a method for best approximation of real signal with a sinusoidal signal. The 'Quanterra' broadband station allows the data access in numerical and/or graphical forms. With the numerical form we can easily make a computer program (MSOFFICE-EXCEL) for spectral analysis. (authors)

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...

Supplementary report: millimeter wave study program

International Nuclear Information System (INIS)

Jory, H.R.; Symons, R.S.

1976-02-01

This report describes work done during the months of December 1975 and January 1976, following the writing of the final report on the millimeter wave study program for generation of 100 kW or more power at 120 GHz. The work has been directed to three areas for application to gyrotron devices, small signal analysis, electron beam simulation, and microwave measurements on cavity coupling. A small signal analysis is presented, which allows determination of beam loading in cavities. The results are similar to previous published work, but contain a higher order relativistic correction. The electron beam simulations include two magnetron type guns and one based on electrostatic lenses

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

Exhaustively characterizing feasible logic models of a signaling network using Answer Set Programming.

Science.gov (United States)

Guziolowski, Carito; Videla, Santiago; Eduati, Federica; Thiele, Sven; Cokelaer, Thomas; Siegel, Anne; Saez-Rodriguez, Julio

2013-09-15

Logic modeling is a useful tool to study signal transduction across multiple pathways. Logic models can be generated by training a network containing the prior knowledge to phospho-proteomics data. The training can be performed using stochastic optimization procedures, but these are unable to guarantee a global optima or to report the complete family of feasible models. This, however, is essential to provide precise insight in the mechanisms underlaying signal transduction and generate reliable predictions. We propose the use of Answer Set Programming to explore exhaustively the space of feasible logic models. Toward this end, we have developed caspo, an open-source Python package that provides a powerful platform to learn and characterize logic models by leveraging the rich modeling language and solving technologies of Answer Set Programming. We illustrate the usefulness of caspo by revisiting a model of pro-growth and inflammatory pathways in liver cells. We show that, if experimental error is taken into account, there are thousands (11 700) of models compatible with the data. Despite the large number, we can extract structural features from the models, such as links that are always (or never) present or modules that appear in a mutual exclusive fashion. To further characterize this family of models, we investigate the input-output behavior of the models. We find 91 behaviors across the 11 700 models and we suggest new experiments to discriminate among them. Our results underscore the importance of characterizing in a global and exhaustive manner the family of feasible models, with important implications for experimental design. caspo is freely available for download (license GPLv3) and as a web service at http://caspo.genouest.org/. Supplementary materials are available at Bioinformatics online. santiago.videla@irisa.fr.

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

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.

Evaluating Dynamic Analysis Techniques for Program Comprehension

NARCIS (Netherlands)

Cornelissen, S.G.M.

2009-01-01

Program comprehension is an essential part of software development and software maintenance, as software must be sufficiently understood before it can be properly modified. One of the common approaches in getting to understand a program is the study of its execution, also known as dynamic analysis.

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.

Diversity combining in laser Doppler vibrometry for improved signal reliability

International Nuclear Information System (INIS)

Dräbenstedt, Alexander

2014-01-01

Because of the speckle nature of the light reflected from rough surfaces the signal quality of a vibrometer suffers from varying signal power. Deep signal outages manifest themselves as noise bursts and spikes in the demodulated velocity signal. Here we show that the signal quality of a single point vibrometer can be substantially improved by diversity reception. This concept is widely used in RF communication and can be transferred into optical interferometry. When two statistically independent measurement channels are available which measure the same motion on the same spot, the probability for both channels to see a signal drop-out at the same time is very low. We built a prototype instrument that uses polarization diversity to constitute two independent reception channels that are separately demodulated into velocity signals. Send and receive beams go through different parts of the aperture so that the beams can be spatially separated. The two velocity channels are mixed into one more reliable signal by a PC program in real time with the help of the signal power information. An algorithm has been developed that ensures a mixing of two or more channels with minimum resulting variance. The combination algorithm delivers also an equivalent signal power for the combined signal. The combined signal lacks the vast majority of spikes that are present in the raw signals and it extracts the true vibration information present in both channels. A statistical analysis shows that the probability for deep signal outages is largely decreased. A 60 fold improvement can be shown. The reduction of spikes and noise bursts reduces the noise in the spectral analysis of vibrations too. Over certain frequency bands a reduction of the noise density by a factor above 10 can be shown

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.

Water Quality Analysis Simulation Program (WASP)

Science.gov (United States)

The Water Quality Analysis Simulation Program (WASP) model helps users interpret and predict water quality responses to natural phenomena and manmade pollution for various pollution management decisions.

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)

SIMS analysis: Development and evaluation program summary

International Nuclear Information System (INIS)

Groenewold, G.S.; Appelhans, A.D.; Ingram, J.C.; Delmore, J.E.; Dahl, D.A.

1996-11-01

This report provides an overview of the ''SIMS Analysis: Development and Evaluation Program'', which was executed at the Idaho National Engineering Laboratory from mid-FY-92 to the end of FY-96. It should be noted that prior to FY-1994 the name of the program was ''In-Situ SIMS Analysis''. This report will not go into exhaustive detail regarding program accomplishments, because this information is contained in annual reports which are referenced herein. In summary, the program resulted in the design and construction of an ion trap secondary ion mass spectrometer (IT-SIMS), which is capable of the rapid analysis of environmental samples for adsorbed surface contaminants. This instrument achieves efficient secondary ion desorption by use of a molecular, massive ReO 4 - primary ion particle. The instrument manages surface charge buildup using a self-discharging principle, which is compatible with the pulsed nature of the ion trap. The instrument can achieve high selectivity and sensitivity using its selective ion storage and MS/MS capability. The instrument was used for detection of tri-n-butyl phosphate, salt cake (tank cake) characterization, and toxic metal speciation studies (specifically mercury). Technology transfer was also an important component of this program. The approach that was taken toward technology transfer was that of component transfer. This resulted in transfer of data acquisition and instrument control software in FY-94, and ongoing efforts to transfer primary ion gun and detector technology to other manufacturers

Artificial intelligence/fuzzy logic method for analysis of combined signals from heavy metal chemical sensors

International Nuclear Information System (INIS)

Turek, M.; Heiden, W.; Riesen, A.; Chhabda, T.A.; Schubert, J.; Zander, W.; Krueger, P.; Keusgen, M.; Schoening, M.J.

2009-01-01

The cross-sensitivity of chemical sensors for several metal ions resembles in a way the overlapping sensitivity of some biological sensors, like the optical colour receptors of human retinal cone cells. While it is difficult to assign crisp classification values to measurands based on complex overlapping sensory signals, fuzzy logic offers a possibility to mathematically model such systems. Current work goes into the direction of mixed heavy metal solutions and the combination of fuzzy logic with heavy metal-sensitive, silicon-based chemical sensors for training scenarios of arbitrary sensor/probe combinations in terms of an electronic tongue. Heavy metals play an important role in environmental analysis. As trace elements as well as water impurities released from industrial processes they occur in the environment. In this work, the development of a new fuzzy logic method based on potentiometric measurements performed with three different miniaturised chalcogenide glass sensors in different heavy metal solutions will be presented. The critical validation of the developed fuzzy logic program will be demonstrated by means of measurements in unknown single- and multi-component heavy metal solutions. Limitations of this program and a comparison between calculated and expected values in terms of analyte composition and heavy metal ion concentration will be shown and discussed.

Artificial intelligence/fuzzy logic method for analysis of combined signals from heavy metal chemical sensors

Energy Technology Data Exchange (ETDEWEB)

Turek, M. [Institute of Nano- and Biotechnologies (INB), Aachen University of Applied Sciences, Campus Juelich, Juelich (Germany); Institute of Bio- and Nanosystems (IBN), Research Centre Juelich GmbH, Juelich (Germany); Heiden, W.; Riesen, A. [Bonn-Rhein-Sieg University of Applied Sciences, Sankt Augustin (Germany); Chhabda, T.A. [Institute of Nano- and Biotechnologies (INB), Aachen University of Applied Sciences, Campus Juelich, Juelich (Germany); Schubert, J.; Zander, W. [Institute of Bio- and Nanosystems (IBN), Research Centre Juelich GmbH, Juelich (Germany); Krueger, P. [Institute of Biochemistry and Molecular Biology, RWTH Aachen, Aachen (Germany); Keusgen, M. [Institute for Pharmaceutical Chemistry, Philipps-University Marburg, Marburg (Germany); Schoening, M.J. [Institute of Nano- and Biotechnologies (INB), Aachen University of Applied Sciences, Campus Juelich, Juelich (Germany); Institute of Bio- and Nanosystems (IBN), Research Centre Juelich GmbH, Juelich (Germany)], E-mail: m.j.schoening@fz-juelich.de

2009-10-30

The cross-sensitivity of chemical sensors for several metal ions resembles in a way the overlapping sensitivity of some biological sensors, like the optical colour receptors of human retinal cone cells. While it is difficult to assign crisp classification values to measurands based on complex overlapping sensory signals, fuzzy logic offers a possibility to mathematically model such systems. Current work goes into the direction of mixed heavy metal solutions and the combination of fuzzy logic with heavy metal-sensitive, silicon-based chemical sensors for training scenarios of arbitrary sensor/probe combinations in terms of an electronic tongue. Heavy metals play an important role in environmental analysis. As trace elements as well as water impurities released from industrial processes they occur in the environment. In this work, the development of a new fuzzy logic method based on potentiometric measurements performed with three different miniaturised chalcogenide glass sensors in different heavy metal solutions will be presented. The critical validation of the developed fuzzy logic program will be demonstrated by means of measurements in unknown single- and multi-component heavy metal solutions. Limitations of this program and a comparison between calculated and expected values in terms of analyte composition and heavy metal ion concentration will be shown and discussed.

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.

A web-based quantitative signal detection system on adverse drug reaction in China.

Science.gov (United States)

Li, Chanjuan; Xia, Jielai; Deng, Jianxiong; Chen, Wenge; Wang, Suzhen; Jiang, Jing; Chen, Guanquan

2009-07-01

To establish a web-based quantitative signal detection system for adverse drug reactions (ADRs) based on spontaneous reporting to the Guangdong province drug-monitoring database in China. Using Microsoft Visual Basic and Active Server Pages programming languages and SQL Server 2000, a web-based system with three software modules was programmed to perform data preparation and association detection, and to generate reports. Information component (IC), the internationally recognized measure of disproportionality for quantitative signal detection, was integrated into the system, and its capacity for signal detection was tested with ADR reports collected from 1 January 2002 to 30 June 2007 in Guangdong. A total of 2,496 associations including known signals were mined from the test database. Signals (e.g., cefradine-induced hematuria) were found early by using the IC analysis. In addition, 291 drug-ADR associations were alerted for the first time in the second quarter of 2007. The system can be used for the detection of significant associations from the Guangdong drug-monitoring database and could be an extremely useful adjunct to the expert assessment of very large numbers of spontaneously reported ADRs for the first time in China.

FPGA-based electrocardiography (ECG signal analysis system using least-square linear phase finite impulse response (FIR filter

Directory of Open Access Journals (Sweden)

Mohamed G. Egila

2016-12-01

Full Text Available This paper presents a proposed design for analyzing electrocardiography (ECG signals. This methodology employs highpass least-square linear phase Finite Impulse Response (FIR filtering technique to filter out the baseline wander noise embedded in the input ECG signal to the system. Discrete Wavelet Transform (DWT was utilized as a feature extraction methodology to extract the reduced feature set from the input ECG signal. The design uses back propagation neural network classifier to classify the input ECG signal. The system is implemented on Xilinx 3AN-XC3S700AN Field Programming Gate Array (FPGA board. A system simulation has been done. The design is compared with some other designs achieving total accuracy of 97.8%, and achieving reduction in utilizing resources on FPGA implementation.

Control system design and analysis using the INteractive Controls Analysis (INCA) program

Science.gov (United States)

Bauer, Frank H.; Downing, John P.

1987-01-01

The INteractive Controls Analysis (INCA) program was developed at the Goddard Space Flight Center to provide a user friendly efficient environment for the design and analysis of linear control systems. Since its inception, INCA has found extensive use in the design, development, and analysis of control systems for spacecraft, instruments, robotics, and pointing systems. Moreover, the results of the analytic tools imbedded in INCA have been flight proven with at least three currently orbiting spacecraft. This paper describes the INCA program and illustrates, using a flight proven example, how the package can perform complex design analyses with relative ease.

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.

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.

The use of a break-even analysis: financial analysis of a fast-track program.

Science.gov (United States)

Saywell, R M; Cordell, W H; Nyhuis, A W; Giles, B K; Culler, S D; Woods, J R; Chu, D K; McKinzie, J P; Rodman, G H

1995-08-01

To calculate the financial break-even point and illustrate how changes in third-party reimbursement and eligibility could affect a program's fiscal standing. Demographic, clinical, and financial data were collected retrospectively for 446 patients treated in a fast-track program during June 1993. The fast-track program is located within the confines of the emergency medicine and trauma center at a 1,050-bed tertiary care Midwestern teaching hospital and provides urgent treatment to minimally ill patients. A financial break-even analysis was performed to determine the point where the program generated enough revenue to cover its total variable and fixed costs, both direct and indirect. Given the relatively low average collection rate (62%) and high percentage of uninsured patients (31%), the analysis showed that the program's revenues covered its direct costs but not all of the indirect costs. Examining collection rates or payer class mix without examining both costs and revenues may lead to an erroneous conclusion about a program's fiscal viability. Sensitivity analysis also shows that relatively small changes in third-party coverage or eligibility (income) requirements can have a large impact on the program's financial solvency and break-even volumes.

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.

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.

GUI program to compute probabilistic seismic hazard analysis

International Nuclear Information System (INIS)

Shin, Jin Soo; Chi, H. C.; Cho, J. C.; Park, J. H.; Kim, K. G.; Im, I. S.

2005-12-01

The first stage of development of program to compute probabilistic seismic hazard is completed based on Graphic User Interface (GUI). The main program consists of three part - the data input processes, probabilistic seismic hazard analysis and result output processes. The first part has developed and others are developing now in this term. The probabilistic seismic hazard analysis needs various input data which represent attenuation formulae, seismic zoning map, and earthquake event catalog. The input procedure of previous programs based on text interface take a much time to prepare the data. The data cannot be checked directly on screen to prevent input erroneously in existing methods. The new program simplifies the input process and enable to check the data graphically in order to minimize the artificial error within the limits of the possibility

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.

A cost analysis of Colorado's 1991-92 oxygenated fuels program

International Nuclear Information System (INIS)

Manderino, L.A.; Bowles, S.L.

1993-01-01

This paper discusses the methodology used to conduct a cost analysis of Colorado's 1991-92 Oxygenated Fuels Program. This program requires the use of oxygenated fuels during the winter season in Denver and surrounding areas. The cost analysis was conducted as part of an overall cost-effectiveness study of the 1991-92 program conducted by PRC Environmental Management, Inc. (PRC). The paper, however, focuses on cost analysis and does not consider potential benefits of the program. The study analyzed costs incurred by different segments of society, including government, industry, and consumers. Because the analysis focused on a specific program year, neither past nor future costs were studied. The discussion of government costs includes the agencies interviewed and the types of costs associated with government administration and enforcement of the program. The methodology used to calculate costs to private industry is also present. The study examined the costs to fuel refineries, pipelines, and blenders, as well as fuel retailers and automobile fleet operators. Finally, the paper discusses the potential costs incurred by the consumer purchasing oxygenated fuels. Costs associated with issues such as vehicle driveability, automobile parts durability and performance, and fuel economy are also examined. A summary of all costs by category is presented along with an analysis of the major cost components. These include costs which are sensitive to specific circumstances and which may vary among programs

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…

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

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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.

Validation of the TEXSAN thermal-hydraulic analysis program

International Nuclear Information System (INIS)

Burns, S.P.; Klein, D.E.

1992-01-01

The TEXSAN thermal-hydraulic analysis program has been developed by the University of Texas at Austin (UT) to simulate buoyancy driven fluid flow and heat transfer in spent fuel and high level nuclear waste (HLW) shipping applications. As part of the TEXSAN software quality assurance program, the software has been subjected to a series of test cases intended to validate its capabilities. The validation tests include many physical phenomena which arise in spent fuel and HLW shipping applications. This paper describes some of the principal results of the TEXSAN validation tests and compares them to solutions available in the open literature. The TEXSAN validation effort has shown that the TEXSAN program is stable and consistent under a range of operating conditions and provides accuracy comparable with other heat transfer programs and evaluation techniques. The modeling capabilities and the interactive user interface employed by the TEXSAN program should make it a useful tool in HLW transportation analysis

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.

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

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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.

Signaling Role of Fructose Mediated by FINS1/FBP in Arabidopsis thaliana

Science.gov (United States)

Cho, Young-Hee; Yoo, Sang-Dong

2011-01-01

Sugars are evolutionarily conserved signaling molecules that regulate the growth and development of both unicellular and multicellular organisms. As sugar-producing photosynthetic organisms, plants utilize glucose as one of their major signaling molecules. However, the details of other sugar signaling molecules and their regulatory factors have remained elusive, due to the complexity of the metabolite and hormone interactions that control physiological and developmental programs in plants. We combined information from a gain-of-function cell-based screen and a loss-of-function reverse-genetic analysis to demonstrate that fructose acts as a signaling molecule in Arabidopsis thaliana. Fructose signaling induced seedling developmental arrest and interacted with plant stress hormone signaling in a manner similar to that of glucose. For fructose signaling responses, the plant glucose sensor HEXOKINASE1 (HXK1) was dispensable, while FRUCTOSE INSENSITIVE1 (FINS1), a putative FRUCTOSE-1,6-BISPHOSPHATASE, played a crucial role. Interestingly, FINS1 function in fructose signaling appeared to be independent of its catalytic activity in sugar metabolism. Genetic analysis further indicated that FINS1–dependent fructose signaling may act downstream of the abscisic acid pathway, in spite of the fact that HXK1–dependent glucose signaling works upstream of hormone synthesis. Our findings revealed that multiple layers of controls by fructose, glucose, and abscisic acid finely tune the plant autotrophic transition and modulate early seedling establishment after seed germination. PMID:21253566

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.

A fast circuit analysis program based on microcomputer

International Nuclear Information System (INIS)

Hu Guoji

1988-01-01

A fast circuit analysis program (FCAP) is introduced. The program may be used to analyse DC operating point, frequency and transient response of fast circuit. The feature is that the model of active element is not specified. Users may choose one of many equivalent circuits. Written in FORTRAN 77, FCAP can be run on IBM PC and its compatible computers. It can be used as an assistant tool of analysis and design for fast circuits

Analysis of EMG Signals in Aggressive and Normal Activities by Using Higher-Order Spectra

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Necmettin Sezgin

2012-01-01

Full Text Available The analysis and classification of electromyography (EMG signals are very important in order to detect some symptoms of diseases, prosthetic arm/leg control, and so on. In this study, an EMG signal was analyzed using bispectrum, which belongs to a family of higher-order spectra. An EMG signal is the electrical potential difference of muscle cells. The EMG signals used in the present study are aggressive or normal actions. The EMG dataset was obtained from the machine learning repository. First, the aggressive and normal EMG activities were analyzed using bispectrum and the quadratic phase coupling of each EMG episode was determined. Next, the features of the analyzed EMG signals were fed into learning machines to separate the aggressive and normal actions. The best classification result was 99.75%, which is sufficient to significantly classify the aggressive and normal actions.

Analysis of EMG Signals in Aggressive and Normal Activities by Using Higher-Order Spectra

Science.gov (United States)

Sezgin, Necmettin

2012-01-01

The analysis and classification of electromyography (EMG) signals are very important in order to detect some symptoms of diseases, prosthetic arm/leg control, and so on. In this study, an EMG signal was analyzed using bispectrum, which belongs to a family of higher-order spectra. An EMG signal is the electrical potential difference of muscle cells. The EMG signals used in the present study are aggressive or normal actions. The EMG dataset was obtained from the machine learning repository. First, the aggressive and normal EMG activities were analyzed using bispectrum and the quadratic phase coupling of each EMG episode was determined. Next, the features of the analyzed EMG signals were fed into learning machines to separate the aggressive and normal actions. The best classification result was 99.75%, which is sufficient to significantly classify the aggressive and normal actions. PMID:23193379

Characterizing scaling properties of complex signals with missed data segments using the multifractal analysis

Science.gov (United States)

Pavlov, A. N.; Pavlova, O. N.; Abdurashitov, A. S.; Sindeeva, O. A.; Semyachkina-Glushkovskaya, O. V.; Kurths, J.

2018-01-01

The scaling properties of complex processes may be highly influenced by the presence of various artifacts in experimental recordings. Their removal produces changes in the singularity spectra and the Hölder exponents as compared with the original artifacts-free data, and these changes are significantly different for positively correlated and anti-correlated signals. While signals with power-law correlations are nearly insensitive to the loss of significant parts of data, the removal of fragments of anti-correlated signals is more crucial for further data analysis. In this work, we study the ability of characterizing scaling features of chaotic and stochastic processes with distinct correlation properties using a wavelet-based multifractal analysis, and discuss differences between the effect of missed data for synchronous and asynchronous oscillatory regimes. We show that even an extreme data loss allows characterizing physiological processes such as the cerebral blood flow dynamics.

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

Science.gov (United States)

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

2010-04-01

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

EDDYTRAN program system for eddy current, electromagnetic force and structural analysis

International Nuclear Information System (INIS)

Kameari, A.; Nikura, S.

1983-01-01

A computer program system (EDDYTRAN), which is applicable to torus structures of magnetic fusion devices, has been developed to calculate the eddy current, electromagnetic force and structural analysis. The program system is designed to perform the following functions sequentially: 1) generation of model mesh and other data such as electromagnetic and mechanical properties of finite elements and boundary conditions, 2) calculations of eddy currents and electromagnetic forces, 3) transformation of the resultant force to load data fit to the structural analysis program, 4) structural analysis and 5) post-processing of the results. The EDDYTRAN utilizes the EDDYCUFF (EDDY CUrrent, magnetic Field and electromagnetic Force) program and the NASTRAN (NASA STRuctural ANalysis) program. Here, the EDDYCUFF program which has been developed by the authors is a generalized computer program to calculate transient eddy currents, resultant magnetic fields and electromagnetic forces in the conductive components. This paper describes the outline of the EDDYTRAN program system and preliminary results obtained through the application to the Tokamak reactor design which was performed for the Japan Atomic Energy Research Institute

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 review of signals used in sleep analysis

International Nuclear Information System (INIS)

Roebuck, A; Monasterio, V; Gederi, E; Osipov, M; Behar, J; Clifford, G D; Malhotra, A; Penzel, T

2014-01-01

This article presents a review of signals used for measuring physiology and activity during sleep and techniques for extracting information from these signals. We examine both clinical needs and biomedical signal processing approaches across a range of sensor types. Issues with recording and analysing the signals are discussed, together with their applicability to various clinical disorders. Both univariate and data fusion (exploiting the diverse characteristics of the primary recorded signals) approaches are discussed, together with a comparison of automated methods for analysing sleep. (topical review)

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

Multi-Year Program under Budget Constraints Using Multi-Criteria Analysis

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Surya Adiguna

2017-09-01

Full Text Available Road investment appraisal requires joint consideration of multiple criteria which are related to engineering, economic, social and environmental impacts. The investment consideration could be based on the economic analysis but however for some factors, such as environmental, social, and political, are difficult to quantify in monetary term. The multi-criteria analysis is the alternative tool which caters the requirements of the issues above. The research, which is based on 102 class D and class E paved road sections in Kenya, is about to optimize road network investment under budget constraints by applying a multi-criteria analysis (MCA method and compare it with the conventional economic analysis. The MCA is developed from hierarchy structure which is considered as the analytical framework. The framework is based on selected criteria and weights which are assigned from Kenya road policy. The HDM-4 software is applied as decision-making tool to obtain the best investment alternatives and road work programs from both MCA and economic analysis. The road work programs will be the results from the analysis using both MCA and economic analysis within HDM-4 software to see the difference and compare the results between both programs. The results from MCA show 51 road sections need periodic work, which is overlay or resealing. Meanwhile, 51 others need rehabilitation or reconstruction. The five years road work program which based on economic analysis result shows that it costs almost Kenyan Shilling (KES 130 billion to maintain the class D and E paved road in Kenya. Meanwhile, the MCA only requires KES 59.5 billion for 5 years program. These results show huge margin between two analyses and somehow MCA result provides more efficient work program compared to economic analysis.

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.

Energy Analysis of Decoders for Rakeness-Based Compressed Sensing of ECG Signals.

Science.gov (United States)

Pareschi, Fabio; Mangia, Mauro; Bortolotti, Daniele; Bartolini, Andrea; Benini, Luca; Rovatti, Riccardo; Setti, Gianluca

2017-12-01

In recent years, compressed sensing (CS) has proved to be effective in lowering the power consumption of sensing nodes in biomedical signal processing devices. This is due to the fact the CS is capable of reducing the amount of data to be transmitted to ensure correct reconstruction of the acquired waveforms. Rakeness-based CS has been introduced to further reduce the amount of transmitted data by exploiting the uneven distribution to the sensed signal energy. Yet, so far no thorough analysis exists on the impact of its adoption on CS decoder performance. The latter point is of great importance, since body-area sensor network architectures may include intermediate gateway nodes that receive and reconstruct signals to provide local services before relaying data to a remote server. In this paper, we fill this gap by showing that rakeness-based design also improves reconstruction performance. We quantify these findings in the case of ECG signals and when a variety of reconstruction algorithms are used either in a low-power microcontroller or a heterogeneous mobile computing platform.

Analysis of Voltage Signals from Superconducting Accelerator Magnets

Energy Technology Data Exchange (ETDEWEB)

Lizarazo, J.; Caspi, S.; Ferracin, P.; Joseph, J.; Lietzke, A. F.; Sabbi, G. L.; Wang, X.

2009-10-30

We present two techniques used in the analysis of voltage tap data collected during recent tests of superconducting magnets developed by the Superconducting Magnet Program at Lawrence Berkeley National Laboratory. The first technique was used on a quadrupole to provide information about quench origins that could not be obtained using the time-of-flight method. The second technique illustrates the use of data from transient flux imbalances occurring during magnet ramping to diagnose changes in the current-temperature margin of a superconducting cable. In both cases, the results of this analysis contributed to make improvements on subsequent magnets.

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

International Nuclear Information System (INIS)

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

2006-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

Javed, Faizan; Venkatachalam, P A; H, Ahmad Fadzil M [Signal and Imaging Processing and Tele-Medicine Technology Research Group, Department of Electrical and Electronics Engineering, Universiti Teknologi PETRONAS, 31750 Tronoh, Perak (Malaysia)

2006-04-01

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

Application of pattern recognition technique on randon signals for automatic monitoring of dynamic systems with emphasis on nuclear reactors

International Nuclear Information System (INIS)

Nascimento, J.A. do.

1981-01-01

The time varying or noise component of dynamic system parameters contains information on the system state. Pattern recognition analysis of noise signals for such systems is a powerful technique for assessing 'system normality' or 'correct operation'. Data analysis with modern small computers enables the otherwise unmanageable volumes of data to be processed on line and the results presented in a meaningful form. These informations provide necessary data for maintaining the system at optimum operating conditions. An automatic pattern recognition program, PSDREC, developmed for the surveillance of nuclear reactor and rotating machinery is described, and the relevant theory is outlined. This program, which applies 8 statistical tests to calculated power spectral density (PSD) distributions, was earlier installed in a PDP-11/45 computer at IPEN. In this work it has been used to separately analyse recorded signals from three systems, namely an operational BWR power reactor (neutron signals), a water pump and a diesel motor (vibration signals). The latter two were, respectively, operated over a wide-range of flow and load conditions. The statistical tests were applied to frequency bands of (0,1-40) Hz, (0-1000) Hz and (0,20000) Hz. for the BWR, pump and diesel signal data, respectively. Operation and analysis conditions are given together with representative graphs of the analysed PSD distributions. Results of the tests - discussed in some detail - are considered to be satisfactory. (Author) [pt

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

Directory of Open Access Journals (Sweden)

Zhang Haijian

2010-01-01

Full Text Available Spectral correlation theory for cyclostationary time-series signals has been studied for decades. Explicit formulas of spectral correlation function for various types of analog-modulated and digital-modulated signals are already derived. In this paper, we investigate and exploit the cyclostationarity characteristics for two kinds of multicarrier modulated (MCM signals: conventional OFDM and filter bank based multicarrier (FBMC signals. The spectral correlation characterization of MCM signal can be described by a special linear periodic time-variant (LPTV system. Using this LPTV description, we have derived the explicit theoretical formulas of nonconjugate and conjugate cyclic autocorrelation function (CAF and spectral correlation function (SCF for OFDM and FBMC signals. According to theoretical spectral analysis, Cyclostationary Signatures (CS are artificially embedded into MCM signal and a low-complexity signature detector is, therefore, presented for detecting MCM signal. Theoretical analysis and simulation results demonstrate the efficiency and robustness of this CS detector compared to traditionary energy detector.

Sinusoidal Representation of Acoustic Signals

Science.gov (United States)

Honda, Masaaki

Sinusoidal representation of acoustic signals has been an important tool in speech and music processing like signal analysis, synthesis and time scale or pitch modifications. It can be applicable to arbitrary signals, which is an important advantage over other signal representations like physical modeling of acoustic signals. In sinusoidal representation, acoustic signals are composed as sums of sinusoid (sine wave) with different amplitudes, frequencies and phases, which is based on the timedependent short-time Fourier transform (STFT). This article describes the principles of acoustic signal analysis/synthesis based on a sinusoid representation with focus on sine waves with rapidly varying frequency.

Applying computer modeling to eddy current signal analysis for steam generator and heat exchanger tube inspections

International Nuclear Information System (INIS)

Sullivan, S.P.; Cecco, V.S.; Carter, J.R.; Spanner, M.; McElvanney, M.; Krause, T.W.; Tkaczyk, R.

2000-01-01

Licensing requirements for eddy current inspections for nuclear steam generators and heat exchangers are becoming increasingly stringent. The traditional industry-standard method of comparing inspection signals with flaw signals from simple in-line calibration standards is proving to be inadequate. A more complete understanding of eddy current and magnetic field interactions with flaws and other anomalies is required for the industry to generate consistently reliable inspections. Computer modeling is a valuable tool in improving the reliability of eddy current signal analysis. Results from computer modeling are helping inspectors to properly discriminate between real flaw signals and false calls, and improving reliability in flaw sizing. This presentation will discuss complementary eddy current computer modeling techniques such as the Finite Element Method (FEM), Volume Integral Method (VIM), Layer Approximation and other analytic methods. Each of these methods have advantages and limitations. An extension of the Layer Approximation to model eddy current probe responses to ferromagnetic materials will also be presented. Finally examples will be discussed demonstrating how some significant eddy current signal analysis problems have been resolved using appropriate electromagnetic computer modeling tools

The Necessity of Functional Analysis for Space Exploration Programs

Science.gov (United States)

Morris, A. Terry; Breidenthal, Julian C.

2011-01-01

As NASA moves toward expanded commercial spaceflight within its human exploration capability, there is increased emphasis on how to allocate responsibilities between government and commercial organizations to achieve coordinated program objectives. The practice of program-level functional analysis offers an opportunity for improved understanding of collaborative functions among heterogeneous partners. Functional analysis is contrasted with the physical analysis more commonly done at the program level, and is shown to provide theoretical performance, risk, and safety advantages beneficial to a government-commercial partnership. Performance advantages include faster convergence to acceptable system solutions; discovery of superior solutions with higher commonality, greater simplicity and greater parallelism by substituting functional for physical redundancy to achieve robustness and safety goals; and greater organizational cohesion around program objectives. Risk advantages include avoidance of rework by revelation of some kinds of architectural and contractual mismatches before systems are specified, designed, constructed, or integrated; avoidance of cost and schedule growth by more complete and precise specifications of cost and schedule estimates; and higher likelihood of successful integration on the first try. Safety advantages include effective delineation of must-work and must-not-work functions for integrated hazard analysis, the ability to formally demonstrate completeness of safety analyses, and provably correct logic for certification of flight readiness. The key mechanism for realizing these benefits is the development of an inter-functional architecture at the program level, which reveals relationships between top-level system requirements that would otherwise be invisible using only a physical architecture. This paper describes the advantages and pitfalls of functional analysis as a means of coordinating the actions of large heterogeneous organizations

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

International Nuclear Information System (INIS)

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

2014-01-01

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

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.

A combined method for analysis of the acoustic emission signals from aboveground storage tank bottom

Energy Technology Data Exchange (ETDEWEB)

Yewei Kang; Mingchun Ling; Min Xiong; Yi Sun; Dongjie Tan [PetroChina Pipeline R and D Center, Langfang (China)

2009-07-01

In the late 1980s acoustic emission (AE) technology was first used to assess the corrosion of aboveground storage tank (AST) bottoms. From then on, it attracts great attention because it can do in-service inspection. Recognizing and eliminating noise is still the main challenge due to the small size of the signals in the presence of potential process noise when the AE signals are processed. In this paper a method combining pattern recognition with traditional AE parametric analysis is introduced to assess the corrosion of AST bottom. First, the AE signals are clustered in different clusters by a clustering method based on the distances of AE signal features. The reasonable cluster is selected for next analysis step. Second, a statistical method is used to evaluate the activities of AE on which the final evaluation report is based. Practical inspection is done on a large oil storage tank in the Chongqing distribution station of Lanzhou- Chengdu-Chongqing product oil pipeline of PetroChina Pipeline Company. The analytical result indicates that the combined method is reliable and feasible. (author)

1-D Wavelet Signal Analysis of the Actuators Nonlinearities Impact on the Healthy Control Systems Performance

Directory of Open Access Journals (Sweden)

Nicolae Tudoroiu

2017-09-01

Full Text Available The objective of this paper is to investigate the use of the 1-D wavelet analysis to extract several patterns from signals data sets collected from healthy and faulty input-output signals of control systems as a preliminary step in real-time implementation of fault detection diagnosis and isolation strategies. The 1-D wavelet analysis proved that is an useful tool for signals processing, design and analysis based on wavelet transforms found in a wide range of control systems industrial applications. Based on the fact that in the real life there is a great similitude between the phenomena, we are motivated to extend the applicability of these techniques to solve similar applications from control systems field, such is done in our research work. Their efficiency will be demonstrated on a case study mainly chosen to evaluate the impact of the uncertainties and the nonlinearities of the sensors and actuators on the overall performance of the control systems. The proposed techniques are able to extract in frequency domain some pattern features (signatures of interest directly from the signals data set collected by data acquisition equipment from the control system.

Quantitative measurement of intervertebral disc signal using MRI

International Nuclear Information System (INIS)

Niemelaeinen, R.; Videman, T.; Dhillon, S.S.; Battie, M.C.

2008-01-01

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

Quantitative measurement of intervertebral disc signal using MRI

Energy Technology Data Exchange (ETDEWEB)

Niemelaeinen, R. [Faculty of Rehabilitation Medicine, University of Alberta, Edmonton (Canada)], E-mail: riikka.niemelainen@ualberta.ca; Videman, T. [Faculty of Rehabilitation Medicine, University of Alberta, Edmonton (Canada); Dhillon, S.S. [Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton (Canada); Battie, M.C. [Faculty of Rehabilitation Medicine, University of Alberta, Edmonton (Canada)

2008-03-15

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

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

Signal Quality Improvement Algorithms for MEMS Gyroscope-Based Human Motion Analysis Systems: A Systematic Review

Directory of Open Access Journals (Sweden)

Jiaying Du

2018-04-01

Full Text Available Motion sensors such as MEMS gyroscopes and accelerometers are characterized by a small size, light weight, high sensitivity, and low cost. They are used in an increasing number of applications. However, they are easily influenced by environmental effects such as temperature change, shock, and vibration. Thus, signal processing is essential for minimizing errors and improving signal quality and system stability. The aim of this work is to investigate and present a systematic review of different signal error reduction algorithms that are used for MEMS gyroscope-based motion analysis systems for human motion analysis or have the potential to be used in this area. A systematic search was performed with the search engines/databases of the ACM Digital Library, IEEE Xplore, PubMed, and Scopus. Sixteen papers that focus on MEMS gyroscope-related signal processing and were published in journals or conference proceedings in the past 10 years were found and fully reviewed. Seventeen algorithms were categorized into four main groups: Kalman-filter-based algorithms, adaptive-based algorithms, simple filter algorithms, and compensation-based algorithms. The algorithms were analyzed and presented along with their characteristics such as advantages, disadvantages, and time limitations. A user guide to the most suitable signal processing algorithms within this area is presented.

Signal Quality Improvement Algorithms for MEMS Gyroscope-Based Human Motion Analysis Systems: A Systematic Review.

Science.gov (United States)

Du, Jiaying; Gerdtman, Christer; Lindén, Maria

2018-04-06

Motion sensors such as MEMS gyroscopes and accelerometers are characterized by a small size, light weight, high sensitivity, and low cost. They are used in an increasing number of applications. However, they are easily influenced by environmental effects such as temperature change, shock, and vibration. Thus, signal processing is essential for minimizing errors and improving signal quality and system stability. The aim of this work is to investigate and present a systematic review of different signal error reduction algorithms that are used for MEMS gyroscope-based motion analysis systems for human motion analysis or have the potential to be used in this area. A systematic search was performed with the search engines/databases of the ACM Digital Library, IEEE Xplore, PubMed, and Scopus. Sixteen papers that focus on MEMS gyroscope-related signal processing and were published in journals or conference proceedings in the past 10 years were found and fully reviewed. Seventeen algorithms were categorized into four main groups: Kalman-filter-based algorithms, adaptive-based algorithms, simple filter algorithms, and compensation-based algorithms. The algorithms were analyzed and presented along with their characteristics such as advantages, disadvantages, and time limitations. A user guide to the most suitable signal processing algorithms within this area is presented.

BeHealthy Charities Aid Foundation Program, Russia: a Program Impact Pathways (PIP) analysis.

Science.gov (United States)

Mukhina, Marina; Novikova, Irina

2014-09-01

In 2007, the Charities Aid Foundation Branch in Russia, under the initiative of and with financial support from the Mondelēz International Foundation and Mondelēz International, launched the charitable BeHealthy Program. The program's main focus is the implementation of four interrelated activities: conducting lessons for schoolchildren on healthy nutrition, with an emphasis on breakfast; healthy cooking lessons with children; cultivating nutritional plants; and providing conditions to encourage children to engage in more physical activity. The program serves more than 13,000 children attending public schools in the Leningrad (Lomonosovskii District), Vladimir, and Novgorod regions. BeHealthy provides funding for schools and comprehensive educational materials to help schoolchildren develop habits of healthy nutrition and physical activity, as well as consulting and expert support for school staff and other key stakeholders. The program brings in experts on program implementation and training for teachers. Curriculum support also includes printed and Web-based healthy lifestyle educational materials on best practices and positive experience, as well as meetings and conferences with school representatives and local authorities. One of the biggest challenges for program managers is to fully understand the complexities of the program, and why and how it is expected to induce changes in healthy lifestyle behaviors of the schoolchildren. For more comprehensive understanding, we performed a Program Impact Pathways (PIP) analysis to identify Critical Quality Control Points (CCPs) and a suite of core indicators of the program's impact on healthy lifestyles. The findings were presented at the Healthy Life-styles Program Evaluation Workshop held in Granada, Spain, 13-14 September 2013, under the auspices of the Mondelēz International Foundation. First, we developed an updated logic model based on how the program was executed. We then translated the logic model into a PIP

Towards a time-domain modeling framework for small-signal analysis of unbalanced microgrids

OpenAIRE

Ojo, Y; Schiffer, JF

2017-01-01

Small-signal analysis is one of the most frequently used techniques to assess the operating conditions of power systems. Typically, this analysis is conducted by employing a phasor-based model of the power network derived under the assumption of balanced operating conditions. However, distribution networks and, amongst these, microgrids are often unbalanced. Hence, their analysis requires the development of tools and methods valid under such conditions. Motivated by this, we propose a modelin...

Small-Signal Modeling, Stability Analysis and Design Optimization of Single-Phase Delay-Based PLLs

DEFF Research Database (Denmark)

Golestan, Saeed; Guerrero, Josep M.; Vidal, Ana

2016-01-01

Generally speaking, designing single-phase phaselocked loops (PLLs) is more complicated than three-phase ones, as their implementation often involves the generation of a fictitious orthogonal signal for the frame transformation. In recent years, many approaches to generate the orthogonal signal...... these issues and explore new methods to enhance their performance. The stability analysis, control design guidelines and performance comparison with the state-of-the-art PLLs are presented as well....

Application of spectral analysis for differentiation between metals using signals from eddy-current transducers

OpenAIRE

Abramovych, Anton; Poddubny, Volodymyr

2017-01-01

The authors theoretically and experimentally substantiated the use of the spectral method for processing a signal of the vortex-current metal detector for dichotomous differentiation between metals. Results of experimental research that prove the possibility of using spectral analysis for differentiation between metals were presented. The vortex-current method for detection of hidden metal objects was analyzed. It was indicated that amplitude of output VCD signal is determined by electric con...

Planetary Protection Bioburden Analysis Program

Science.gov (United States)

Beaudet, Robert A.

2013-01-01

This program is a Microsoft Access program that performed statistical analysis of the colony counts from assays performed on the Mars Science Laboratory (MSL) spacecraft to determine the bioburden density, 3-sigma biodensity, and the total bioburdens required for the MSL prelaunch reports. It also contains numerous tools that report the data in various ways to simplify the reports required. The program performs all the calculations directly in the MS Access program. Prior to this development, the data was exported to large Excel files that had to be cut and pasted to provide the desired results. The program contains a main menu and a number of submenus. Analyses can be performed by using either all the assays, or only the accountable assays that will be used in the final analysis. There are three options on the first menu: either calculate using (1) the old MER (Mars Exploration Rover) statistics, (2) the MSL statistics for all the assays, or This software implements penetration limit equations for common micrometeoroid and orbital debris (MMOD) shield configurations, windows, and thermal protection systems. Allowable MMOD risk is formulated in terms of the probability of penetration (PNP) of the spacecraft pressure hull. For calculating the risk, spacecraft geometry models, mission profiles, debris environment models, and penetration limit equations for installed shielding configurations are required. Risk assessment software such as NASA's BUMPERII is used to calculate mission PNP; however, they are unsuitable for use in shield design and preliminary analysis studies. The software defines a single equation for the design and performance evaluation of common MMOD shielding configurations, windows, and thermal protection systems, along with a description of their validity range and guidelines for their application. Recommendations are based on preliminary reviews of fundamental assumptions, and accuracy in predicting experimental impact test results. The software

Process Monitoring by combining several signal-analysis results using fuzzy logic

International Nuclear Information System (INIS)

Schoonwelle, H.; Van der Hagen, T.H.J.J.; Hoogenboom, J.E.

1996-01-01

In order to improve reliability in detecting anomalies in nuclear power plant performance, a method is presented which is based on acquiring various characteristics of signal data using autoregressive, wavelet and fractal-analysis techniques. These characteristics are combined using a decision making approach based on fuzzy logic. This approach is able to detect and distinguish several system states

Measurement and analysis of P2P IPTV program resource.

Science.gov (United States)

Wang, Wenxian; Chen, Xingshu; Wang, Haizhou; Zhang, Qi; Wang, Cheng

2014-01-01

With the rapid development of P2P technology, P2P IPTV applications have received more and more attention. And program resource distribution is very important to P2P IPTV applications. In order to collect IPTV program resources, a distributed multi-protocol crawler is proposed. And the crawler has collected more than 13 million pieces of information of IPTV programs from 2009 to 2012. In addition, the distribution of IPTV programs is independent and incompact, resulting in chaos of program names, which obstructs searching and organizing programs. Thus, we focus on characteristic analysis of program resources, including the distributions of length of program names, the entropy of the character types, and hierarchy depth of programs. These analyses reveal the disorderly naming conventions of P2P IPTV programs. The analysis results can help to purify and extract useful information from chaotic names for better retrieval and accelerate automatic sorting of program and establishment of IPTV repository. In order to represent popularity of programs and to predict user behavior and popularity of hot programs over a period, we also put forward an analytical model of hot programs.

Measurement and Analysis of P2P IPTV Program Resource

Directory of Open Access Journals (Sweden)

Wenxian Wang

2014-01-01

Full Text Available With the rapid development of P2P technology, P2P IPTV applications have received more and more attention. And program resource distribution is very important to P2P IPTV applications. In order to collect IPTV program resources, a distributed multi-protocol crawler is proposed. And the crawler has collected more than 13 million pieces of information of IPTV programs from 2009 to 2012. In addition, the distribution of IPTV programs is independent and incompact, resulting in chaos of program names, which obstructs searching and organizing programs. Thus, we focus on characteristic analysis of program resources, including the distributions of length of program names, the entropy of the character types, and hierarchy depth of programs. These analyses reveal the disorderly naming conventions of P2P IPTV programs. The analysis results can help to purify and extract useful information from chaotic names for better retrieval and accelerate automatic sorting of program and establishment of IPTV repository. In order to represent popularity of programs and to predict user behavior and popularity of hot programs over a period, we also put forward an analytical model of hot programs.

GELATIO: a general framework for modular digital analysis of high-purity Ge detector signals

International Nuclear Information System (INIS)

Agostini, M; Pandola, L; Zavarise, P; Volynets, O

2011-01-01

GELATIO is a new software framework for advanced data analysis and digital signal processing developed for the GERDA neutrinoless double beta decay experiment. The framework is tailored to handle the full analysis flow of signals recorded by high purity Ge detectors and photo-multipliers from the veto counters. It is designed to support a multi-channel modular and flexible analysis, widely customizable by the user either via human-readable initialization files or via a graphical interface. The framework organizes the data into a multi-level structure, from the raw data up to the condensed analysis parameters, and includes tools and utilities to handle the data stream between the different levels. GELATIO is implemented in C++. It relies upon ROOT and its extension TAM, which provides compatibility with PROOF, enabling the software to run in parallel on clusters of computers or many-core machines. It was tested on different platforms and benchmarked in several GERDA-related applications. A stable version is presently available for the GERDA Collaboration and it is used to provide the reference analysis of the experiment data.

GELATIO: a general framework for modular digital analysis of high-purity Ge detector signals

Science.gov (United States)

Agostini, M.; Pandola, L.; Zavarise, P.; Volynets, O.

2011-08-01

GELATIO is a new software framework for advanced data analysis and digital signal processing developed for the GERDA neutrinoless double beta decay experiment. The framework is tailored to handle the full analysis flow of signals recorded by high purity Ge detectors and photo-multipliers from the veto counters. It is designed to support a multi-channel modular and flexible analysis, widely customizable by the user either via human-readable initialization files or via a graphical interface. The framework organizes the data into a multi-level structure, from the raw data up to the condensed analysis parameters, and includes tools and utilities to handle the data stream between the different levels. GELATIO is implemented in C++. It relies upon ROOT and its extension TAM, which provides compatibility with PROOF, enabling the software to run in parallel on clusters of computers or many-core machines. It was tested on different platforms and benchmarked in several GERDA-related applications. A stable version is presently available for the GERDA Collaboration and it is used to provide the reference analysis of the experiment data.

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

Science.gov (United States)

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

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. Project supported by the National Science and Technology, China (Grant No. 2012BAJ15B04), the National Natural Science Foundation of China (Grant Nos. 41071270 and 61473213), the Natural Science Foundation of Hubei Province, China (Grant No. 2015CFB424), the State Key Laboratory Foundation of Satellite Ocean Environment Dynamics, China (Grant No. SOED1405), the Hubei Provincial Key Laboratory Foundation of Metallurgical Industry Process System Science, China (Grant No. Z201303), and the Hubei Key Laboratory Foundation of Transportation Internet of Things, Wuhan University of Technology, China (Grant No.2015III015-B02).

Programmed Fetal Membrane Senescence and Exosome-Mediated Signaling: A Mechanism Associated With Timing of Human Parturition

Directory of Open Access Journals (Sweden)

Ramkumar Menon

2017-08-01

Full Text Available Human parturition is an inflammatory process that involves both fetal and maternal compartments. The precise immune cell interactions have not been well delineated in human uterine tissues during parturition, but insights into human labor initiation have been informed by studies in animal models. Unfortunately, the timing of parturition relative to fetal maturation varies among viviparous species—indicative of different phylogenetic clocks and alarms—but what is clear is that important common pathways must converge to control the birth process. Herein, we hypothesize a novel signaling mechanism initiated by human fetal membrane aging and senescence-associated inflammation. Programmed events of fetal membrane aging coincide with fetal growth and organ maturation. Mechanistically, senescence involves in telomere shortening and activation of p38 mitogen-activated signaling kinase resulting in aging-associated phenotypic transition. Senescent tissues release inflammatory signals that are propagated via exosomes to cause functional changes in maternal uterine tissues. In vitro, oxidative stress causes increased release of inflammatory mediators (senescence-associated secretory phenotype and damage-associated molecular pattern markers that can be packaged inside the exosomes. These exosomes traverse through tissues layers, reach maternal tissues to increase overall inflammatory load transitioning them from a quiescent to active state. Animal model studies have shown that fetal exosomes can travel from fetal to the maternal side. Thus, aging fetal membranes and membrane-derived exosomes cargo fetal signals to the uterus and cervix and may trigger parturition. This review highlights a novel hypothesis in human parturition research based on data from ongoing research using human fetal membrane model system.

Cross Time-Frequency Analysis of Gastrocnemius Electromyographic Signals in Hypertensive and Nonhypertensive Subjects

Science.gov (United States)

Mitchell, Patrick; Krotish, Debra; Shin, Yong-June; Hirth, Victor

2010-12-01

The effects of hypertension are chronic and continuous; it affects gait, balance, and fall risk. Therefore, it is desirable to assess gait health across hypertensive and nonhypertensive subjects in order to prevent or reduce the risk of falls. Analysis of electromyography (EMG) signals can identify age related changes of neuromuscular activation due to various neuropathies and myopathies, but it is difficult to translate these medical changes to clinical diagnosis. To examine and compare geriatrics patients with these gait-altering diseases, we acquire EMG muscle activation signals, and by use of a timesynchronized mat capable of recording pressure information, we localize the EMG data to the gait cycle, ensuring identical comparison across subjects. Using time-frequency analysis on the EMG signal, in conjunction with several parameters obtained from the time-frequency analyses, we can determine the statistical discrepancy between diseases. We base these parameters on physiological manifestations caused by hypertension, as well as other comorbities that affect the geriatrics community. Using these metrics in a small population, we identify a statistical discrepancy between a control group and subjects with hypertension, neuropathy, diabetes, osteoporosis, arthritis, and several other common diseases which severely affect the geriatrics community.

Wavelet transform analysis of transient signals: the seismogram and the electrocardiogram

Energy Technology Data Exchange (ETDEWEB)

Anant, K.S.

1997-06-01

In this dissertation I quantitatively demonstrate how the wavelet transform can be an effective mathematical tool for the analysis of transient signals. The two key signal processing applications of the wavelet transform, namely feature identification and representation (i.e., compression), are shown by solving important problems involving the seismogram and the electrocardiogram. The seismic feature identification problem involved locating in time the P and S phase arrivals. Locating these arrivals accurately (particularly the S phase) has been a constant issue in seismic signal processing. In Chapter 3, I show that the wavelet transform can be used to locate both the P as well as the S phase using only information from single station three-component seismograms. This is accomplished by using the basis function (wave-let) of the wavelet transform as a matching filter and by processing information across scales of the wavelet domain decomposition. The `pick` time results are quite promising as compared to analyst picks. The representation application involved the compression of the electrocardiogram which is a recording of the electrical activity of the heart. Compression of the electrocardiogram is an important problem in biomedical signal processing due to transmission and storage limitations. In Chapter 4, I develop an electrocardiogram compression method that applies vector quantization to the wavelet transform coefficients. The best compression results were obtained by using orthogonal wavelets, due to their ability to represent a signal efficiently. Throughout this thesis the importance of choosing wavelets based on the problem at hand is stressed. In Chapter 5, I introduce a wavelet design method that uses linear prediction in order to design wavelets that are geared to the signal or feature being analyzed. The use of these designed wavelets in a test feature identification application led to positive results. The methods developed in this thesis; the

Intelligent Approach for Analysis of Respiratory Signals and Oxygen Saturation in the Sleep Apnea/Hypopnea Syndrome

Science.gov (United States)

Moret-Bonillo, Vicente; Alvarez-Estévez, Diego; Fernández-Leal, Angel; Hernández-Pereira, Elena

2014-01-01

This work deals with the development of an intelligent approach for clinical decision making in the diagnosis of the Sleep Apnea/Hypopnea Syndrome, SAHS, from the analysis of respiratory signals and oxygen saturation in arterial blood, SaO2. In order to accomplish the task the proposed approach makes use of different artificial intelligence techniques and reasoning processes being able to deal with imprecise data. These reasoning processes are based on fuzzy logic and on temporal analysis of the information. The developed approach also takes into account the possibility of artifacts in the monitored signals. Detection and characterization of signal artifacts allows detection of false positives. Identification of relevant diagnostic patterns and temporal correlation of events is performed through the implementation of temporal constraints. PMID:25035712

A Comparative Study of Compression Methods and the Development of CODEC Program of Biological Signal for Emergency Telemedicine Service

Energy Technology Data Exchange (ETDEWEB)

Yoon, T.S.; Kim, J.S. [Changwon National University, Changwon (Korea); Lim, Y.H. [Visionite Co., Ltd., Seoul (Korea); Yoo, S.K. [Yonsei University, Seoul (Korea)

2003-05-01

In an emergency telemedicine system such as the High-quality Multimedia based Real-time Emergency Telemedicine(HMRET) service, it is very important to examine the status of the patient continuously using the multimedia data including the biological signals(ECG, BP, Respiration, S{sub p}O{sub 2}) of the patient. In order to transmit these data real time through the communication means which have the limited transmission capacity, it is also necessary to compress the biological data besides other multimedia data. For this purpose, we investigate and compare the ECG compression techniques in the time domain and in the wavelet transform domain, and present an effective lossless compression method of the biological signals using JPEG Huffman table for an emergency telemedicine system. And, for the HMRET service, we developed the lossless compression and reconstruction program of the biological signals in MSVC++ 6.0 using DPCM method and JPEG Huffman table, and tested in an internet environment. (author). 15 refs., 17 figs., 7 tabs.

Sleep disordered breathing analysis in a general population using standard pulse oximeter signals.

Science.gov (United States)

Barak-Shinar, Deganit; Amos, Yariv; Bogan, Richard K

2013-09-01

Obstructive sleep apnea reported as the apnea-hypopnea index (AHI) is usually measured in sleep laboratories using a high number of electrodes connected to the patient's body. In this study, we examined the use of a standard pulse oximeter system with an automated analysis based on the photoplethysmograph (PPG) signal for the diagnosis of sleep disordered breathing. Using a standard and simple device with high accuracy might provide a convenient diagnostic or screening solution for patient evaluation at home or in other out of center testing environments. The study included 140 consecutive patients that were referred routinely to a sleep laboratory [SleepMed Inc.] for the diagnosis of sleep disordered breathing. Each patient underwent an overnight polysomnography (PSG) study according to AASM guidelines in an AASM-accredited sleep laboratory. The automatic analysis is based on photoplethysmographic and saturation signals only. Those two signals were recorded for the entire night as part of the full overnight PSG sleep study. The AHI calculated from the PPG analysis is compared to the AHI calculated from the manual scoring gold standard full PSG. The AHI and total respiratory events measured by the pulse oximeter analysis correlated very well with the corresponding results obtained by the gold standard full PSG. The sensitivity and specificity of AHI = or > 5 and 15 levels measured by the analysis are both above 90 %. The sensitivity and positive predictive value for the detection of respiratory event are both above 84 %. The tested system in this study yielded an acceptable result of sleep disordered breathing compared to the gold standard PSG in patients with moderate to severe sleep apnea. Accordingly and given the convenience and simplicity of the standard pulse oximeter device, the new system can be considered suitable for home and ambulatory diagnosis or screening of sleep disordered breathing patients.

Wavelet based analysis of multi-electrode EEG-signals in epilepsy

Science.gov (United States)

Hein, Daniel A.; Tetzlaff, Ronald

2005-06-01

For many epilepsy patients seizures cannot sufficiently be controlled by an antiepileptic pharmacatherapy. Furthermore, only in small number of cases a surgical treatment may be possible. The aim of this work is to contribute to the realization of an implantable seizure warning device. By using recordings of electroenzephalographical(EEG) signals obtained from the department of epileptology of the University of Bonn we studied a recently proposed algorithm for the detection of parameter changes in nonlinear systems. Firstly, after calculating the crosscorrelation function between the signals of two electrodes near the epileptic focus, a wavelet-analysis follows using a sliding window with the so called Mexican-Hat wavelet. Then the Shannon-Entropy of the wavelet-transformed data has been determined providing the information content on a time scale in subject to the dilation of the wavelet-transformation. It shows distinct changes at the seizure onset for all dilations and for all patients.

Supporting secure programming in web applications through interactive static analysis.

Science.gov (United States)

Zhu, Jun; Xie, Jing; Lipford, Heather Richter; Chu, Bill

2014-07-01

Many security incidents are caused by software developers' failure to adhere to secure programming practices. Static analysis tools have been used to detect software vulnerabilities. However, their wide usage by developers is limited by the special training required to write rules customized to application-specific logic. Our approach is interactive static analysis, to integrate static analysis into Integrated Development Environment (IDE) and provide in-situ secure programming support to help developers prevent vulnerabilities during code construction. No additional training is required nor are there any assumptions on ways programs are built. Our work is motivated in part by the observation that many vulnerabilities are introduced due to failure to practice secure programming by knowledgeable developers. We implemented a prototype interactive static analysis tool as a plug-in for Java in Eclipse. Our technical evaluation of our prototype detected multiple zero-day vulnerabilities in a large open source project. Our evaluations also suggest that false positives may be limited to a very small class of use cases.

The role of radiation damage analysis in the fusion program

International Nuclear Information System (INIS)

Doran, D.G.

1983-01-01

The objective of radiation damage analysis is the prediction of the performance of facility components exposed to a radiation environment. The US Magnetic Fusion Energy materials program includes an explicit damage analysis activity within the Damage Analysis and Fundamental Studies (DAFS) Program. Many of the papers in these Proceedings report work done directly or indirectly in support of the DAFS program. The emphasis of this program is on developing procedures, based on an understanding of damage mechanisms, for applying data obtained in diverse radiation environments to the prediction of component behavior in fusion devices. It is assumed that the Fusion Materials Irradiation Test Facility will be available in the late 1980s to test (and calibrate where necessary) correlation procedures to the high fluences expected in commercial reactors. (orig.)

Multiresolution signal decomposition schemes

NARCIS (Netherlands)

J. Goutsias (John); H.J.A.M. Heijmans (Henk)

1998-01-01

textabstract[PNA-R9810] Interest in multiresolution techniques for signal processing and analysis is increasing steadily. An important instance of such a technique is the so-called pyramid decomposition scheme. This report proposes a general axiomatic pyramid decomposition scheme for signal analysis

Auto-identification of engine fault acoustic signal through inverse trigonometric instantaneous frequency analysis

Directory of Open Access Journals (Sweden)

Dayong Ning

2016-03-01

Full Text Available The acoustic signals of internal combustion engines contain valuable information about the condition of engines. These signals can be used to detect incipient faults in engines. However, these signals are complex and composed of a faulty component and other noise signals of background. As such, engine conditions’ characteristics are difficult to extract through wavelet transformation and acoustic emission techniques. In this study, an instantaneous frequency analysis method was proposed. A new time–frequency model was constructed using a fixed amplitude and a variable cycle sine function to fit adjacent points gradually from a time domain signal. The instantaneous frequency corresponds to single value at any time. This study also introduced instantaneous frequency calculation on the basis of an inverse trigonometric fitting method at any time. The mean value of all local maximum values was then considered to identify the engine condition automatically. Results revealed that the mean of local maximum values under faulty conditions differs from the normal mean. An experiment case was also conducted to illustrate the availability of the proposed method. Using the proposed time–frequency model, we can identify engine condition and determine abnormal sound produced by faulty engines.

Complex on the base of the ISKRA 226.6 personal computer for nuclear quadrupole resonance signal processing

International Nuclear Information System (INIS)

Morgunov, V.G.; Kravchenko, Eh.A.

1988-01-01

Complex, designed to conduct investigations by means of nuclear quadrupole resonance (NQR) method, which includes radiospectrometer, multichannel spectrum analyzer and ISKRA 226.6 personal computer, is developed. Analog-to-digital converter (ADC) with buffer storage device, interface and microcomputer are used to process NQR-signals. ADS conversion time is no more, than 50 ns, linearity - 1%. Programs on Fourier analysis of NQR-signals and calculation of relaxation times are developed

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.

Object Classification Based on Analysis of Spectral Characteristics of Seismic Signal Envelopes

Science.gov (United States)

Morozov, Yu. V.; Spektor, A. A.

2017-11-01

A method for classifying moving objects having a seismic effect on the ground surface is proposed which is based on statistical analysis of the envelopes of received signals. The values of the components of the amplitude spectrum of the envelopes obtained applying Hilbert and Fourier transforms are used as classification criteria. Examples illustrating the statistical properties of spectra and the operation of the seismic classifier are given for an ensemble of objects of four classes (person, group of people, large animal, vehicle). It is shown that the computational procedures for processing seismic signals are quite simple and can therefore be used in real-time systems with modest requirements for computational resources.

Adapted wavelet analysis from theory to software

CERN Document Server

Wickerhauser, Mladen Victor

1994-01-01

This detail-oriented text is intended for engineers and applied mathematicians who must write computer programs to perform wavelet and related analysis on real data. It contains an overview of mathematical prerequisites and proceeds to describe hands-on programming techniques to implement special programs for signal analysis and other applications. From the table of contents: - Mathematical Preliminaries - Programming Techniques - The Discrete Fourier Transform - Local Trigonometric Transforms - Quadrature Filters - The Discrete Wavelet Transform - Wavelet Packets - The Best Basis Algorithm - Multidimensional Library Trees - Time-Frequency Analysis - Some Applications - Solutions to Some of the Exercises - List of Symbols - Quadrature Filter Coefficients

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.

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.

Gamma delta T-cell differentiation and effector function programming, TCR signal strength, when and how much?

Science.gov (United States)

Zarin, Payam; Chen, Edward L Y; In, Tracy S H; Anderson, Michele K; Zúñiga-Pflücker, Juan Carlos

2015-07-01

γδ T-cells boast an impressive functional repertoire that can paint them as either champions or villains depending on the environmental and immunological cues. Understanding the function of the various effector γδ subsets necessitates tracing the developmental program of these subsets, including the point of lineage bifurcation from αβ T-cells. Here, we review the importance of signals from the T-cell receptor (TCR) in determining αβ versus γδ lineage fate, and further discuss how the molecular components of this pathway may influence the developmental programming of γδ T-cells functional subsets. Additionally, we discuss the role of temporal windows in restricting the development of IL-17 producing γδ T-cell subtypes, and explore whether fetal and adult hematopoietic progenitors maintain the same potential for giving rise to this important subset. Copyright © 2015 Elsevier Inc. All rights reserved.

Integrated predictive maintenance program vibration and lube oil analysis: Part I - history and the vibration program

Energy Technology Data Exchange (ETDEWEB)

Maxwell, H.

1996-12-01

This paper is the first of two papers which describe the Predictive Maintenance Program for rotating machines at the Palo Verde Nuclear Generating Station. The organization has recently been restructured and significant benefits have been realized by the interaction, or {open_quotes}synergy{close_quotes} between the Vibration Program and the Lube Oil Analysis Program. This paper starts with the oldest part of the program - the Vibration Program and discusses the evolution of the program to its current state. The {open_quotes}Vibration{close_quotes} view of the combined program is then presented.

Integrated predictive maintenance program vibration and lube oil analysis: Part I - history and the vibration program

International Nuclear Information System (INIS)

Maxwell, H.

1996-01-01

This paper is the first of two papers which describe the Predictive Maintenance Program for rotating machines at the Palo Verde Nuclear Generating Station. The organization has recently been restructured and significant benefits have been realized by the interaction, or open-quotes synergyclose quotes between the Vibration Program and the Lube Oil Analysis Program. This paper starts with the oldest part of the program - the Vibration Program and discusses the evolution of the program to its current state. The open-quotes Vibrationclose quotes view of the combined program is then presented

Proteomic analysis of the signaling pathway mediated by the heterotrimeric Gα protein Pga1 of Penicillium chrysogenum.

Science.gov (United States)

Carrasco-Navarro, Ulises; Vera-Estrella, Rosario; Barkla, Bronwyn J; Zúñiga-León, Eduardo; Reyes-Vivas, Horacio; Fernández, Francisco J; Fierro, Francisco

2016-10-06

The heterotrimeric Gα protein Pga1-mediated signaling pathway regulates the entire developmental program in Penicillium chrysogenum, from spore germination to the formation of conidia. In addition it participates in the regulation of penicillin biosynthesis. We aimed to advance the understanding of this key signaling pathway using a proteomics approach, a powerful tool to identify effectors participating in signal transduction pathways. Penicillium chrysogenum mutants with different levels of activity of the Pga1-mediated signaling pathway were used to perform comparative proteomic analyses by 2D-DIGE and LC-MS/MS. Thirty proteins were identified which showed differences in abundance dependent on Pga1 activity level. By modifying the intracellular levels of cAMP we could establish cAMP-dependent and cAMP-independent pathways in Pga1-mediated signaling. Pga1 was shown to regulate abundance of enzymes in primary metabolic pathways involved in ATP, NADPH and cysteine biosynthesis, compounds that are needed for high levels of penicillin production. An in vivo phosphorylated protein containing a pleckstrin homology domain was identified; this protein is a candidate for signal transduction activity. Proteins with possible roles in purine metabolism, protein folding, stress response and morphogenesis were also identified whose abundance was regulated by Pga1 signaling. Thirty proteins whose abundance was regulated by the Pga1-mediated signaling pathway were identified. These proteins are involved in primary metabolism, stress response, development and signal transduction. A model describing the pathways through which Pga1 signaling regulates different cellular processes is proposed.

[Quantitative Analysis of Heavy Metals in Water with LIBS Based on Signal-to-Background Ratio].

Science.gov (United States)

Hu, Li; Zhao, Nan-jing; Liu, Wen-qing; Fang, Li; Zhang, Da-hai; Wang, Yin; Meng, De Shuo; Yu, Yang; Ma, Ming-jun

2015-07-01

There are many influence factors in the precision and accuracy of the quantitative analysis with LIBS technology. According to approximately the same characteristics trend of background spectrum and characteristic spectrum along with the change of temperature through in-depth analysis, signal-to-background ratio (S/B) measurement and regression analysis could compensate the spectral line intensity changes caused by system parameters such as laser power, spectral efficiency of receiving. Because the measurement dates were limited and nonlinear, we used support vector machine (SVM) for regression algorithm. The experimental results showed that the method could improve the stability and the accuracy of quantitative analysis of LIBS, and the relative standard deviation and average relative error of test set respectively were 4.7% and 9.5%. Data fitting method based on signal-to-background ratio(S/B) is Less susceptible to matrix elements and background spectrum etc, and provides data processing reference for real-time online LIBS quantitative analysis technology.

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

Leak detection in pipelines through spectral analysis of pressure signals

Directory of Open Access Journals (Sweden)

Souza A.L.

2000-01-01

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

MITF Modulates Therapeutic Resistance through EGFR Signaling.

Science.gov (United States)

Ji, Zhenyu; Erin Chen, Yiyin; Kumar, Raj; Taylor, Michael; Jenny Njauw, Ching-Ni; Miao, Benchun; Frederick, Dennie T; Wargo, Jennifer A; Flaherty, Keith T; Jönsson, Göran; Tsao, Hensin

2015-07-01

Response to targeted therapies varies significantly despite shared oncogenic mutations. Nowhere is this more apparent than in BRAF (V600E)-mutated melanomas where initial drug response can be striking and yet relapse is commonplace. Resistance to BRAF inhibitors have been attributed to the activation of various receptor tyrosine kinases (RTKs), although the underlying mechanisms have been largely uncharacterized. Here, we found that EGFR-induced vemurafenib resistance is ligand dependent. We employed whole-genome expression analysis and discovered that vemurafenib resistance correlated with the loss of microphthalmia-associated transcription factor (MITF), along with its melanocyte lineage program, and with the activation of EGFR signaling. An inverse relationship between MITF, vemurafenib resistance, and EGFR was then observed in patient samples of recurrent melanoma and was conserved across melanoma cell lines and patients' tumor specimens. Functional studies revealed that MITF depletion activated EGFR signaling and consequently recapitulated the resistance phenotype. In contrast, forced expression of MITF in melanoma and colon cancer cells inhibited EGFR and conferred sensitivity to BRAF/MEK inhibitors. These findings indicate that an "autocrine drug resistance loop" is suppressed by melanocyte lineage signal(s), such as MITF. This resistance loop modulates drug response and could explain the unique sensitivity of melanomas to BRAF inhibition.

Electrophysiological signal analysis and visualization using Cloudwave for epilepsy clinical research.

Science.gov (United States)

Jayapandian, Catherine P; Chen, Chien-Hung; Bozorgi, Alireza; Lhatoo, Samden D; Zhang, Guo-Qiang; Sahoo, Satya S

2013-01-01

Epilepsy is the most common serious neurological disorder affecting 50-60 million persons worldwide. Electrophysiological data recordings, such as electroencephalogram (EEG), are the gold standard for diagnosis and pre-surgical evaluation in epilepsy patients. The increasing trend towards multi-center clinical studies require signal visualization and analysis tools to support real time interaction with signal data in a collaborative environment, which cannot be supported by traditional desktop-based standalone applications. As part of the Prevention and Risk Identification of SUDEP Mortality (PRISM) project, we have developed a Web-based electrophysiology data visualization and analysis platform called Cloudwave using highly scalable open source cloud computing infrastructure. Cloudwave is integrated with the PRISM patient cohort identification tool called MEDCIS (Multi-modality Epilepsy Data Capture and Integration System). The Epilepsy and Seizure Ontology (EpSO) underpins both Cloudwave and MEDCIS to support query composition and result retrieval. Cloudwave is being used by clinicians and research staff at the University Hospital - Case Medical Center (UH-CMC) Epilepsy Monitoring Unit (EMU) and will be progressively deployed at four EMUs in the United States and the United Kingdomas part of the PRISM project.

Analysis of microseismic signals collected on an unstable rock face in the Italian Prealps

Science.gov (United States)

Arosio, Diego; Longoni, Laura; Papini, Monica; Boccolari, Mauro; Zanzi, Luigi

2018-04-01

In this work we present the analysis of more than 9000 signals collected from February 2013 to January 2016 by a microseismic monitoring network installed on a 300 m high limestone cliff in the Italian Prealps. The investigated area was affected by a major rockfall in 1969 and several other minor events up to nowadays. The network features five three-component geophones and a weather station and can be remotely accessed thanks to a dedicated radio link. We first manually classified all the recorded signals and found out that 95 per cent of them are impulsive broad-band disturbances, while about 2 per cent may be related to rockfalls or fracture propagation. Signal parameters in the time and frequency domains were computed during the classification procedure with the aim of developing an automatic classification routine based on linear discriminant analysis. The algorithm proved to have a hit rate higher than 95 per cent and a tolerable false alarm rate and it is now running on the field PC of the acquisition board to autonomously discard useless events. Analysis of lightning data sets provided by the Italian Lightning Detection Network revealed that the large majority of broad-band signals are caused by electromagnetic activity during thunderstorms. Cross-correlation between microseismic signals and meteorological parameters suggests that rainfalls influence the hydrodynamic conditions of the rock mass and can trigger rockfalls and fracture propagation very quickly since the start of a rainfall event. On the other hand, temperature seems to have no influence on the stability conditions of the monitored cliff. The only sensor deployed on the rock pillar next to the 1969 rockfall scarp typically recorded events with higher amplitude as well as energy. We deem that this is due to seismic amplification phenomena and we performed ambient noise recording sessions to validate this hypothesis. Results confirm that seismic amplification occurs, although we were not able to

SIMON. A computer program for reliability and statistical analysis using Monte Carlo simulation. Program description and manual