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Sample records for signal analysis program

  1. [Application of the mixed programming with Labview and Matlab in biomedical signal analysis].

    Yu, Lu; Zhang, Yongde; Sha, Xianzheng

    2011-01-01

    This paper introduces the method of mixed programming with Labview and Matlab, and applies this method in a pulse wave pre-processing and feature detecting system. The method has been proved suitable, efficient and accurate, which has provided a new kind of approach for biomedical signal analysis.

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

    Yujie Li

    2018-01-01

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

  3. Method of signal analysis

    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

  4. Signal flow analysis

    Abrahams, J R; Hiller, N

    1965-01-01

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

  5. Biomedical signal analysis

    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.

  6. Two-dimensional signal analysis

    Garello, René

    2010-01-01

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

  7. Wavelet analysis for nonstationary signals

    Penha, Rosani Maria Libardi da

    1999-01-01

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

  8. Multiscale Signal Analysis and Modeling

    Zayed, Ahmed

    2013-01-01

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

  9. Semi-classical signal analysis

    Laleg-Kirati, Taous-Meriem

    2012-09-30

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

  10. Wnt signaling inhibits CTL memory programming.

    Xiao, Zhengguo; Sun, Zhifeng; Smyth, Kendra; Li, Lei

    2013-12-01

    Induction of functional CTLs is one of the major goals for vaccine development and cancer therapy. Inflammatory cytokines are critical for memory CTL generation. Wnt signaling is important for CTL priming and memory formation, but its role in cytokine-driven memory CTL programming is unclear. We found that wnt signaling inhibited IL-12-driven CTL activation and memory programming. This impaired memory CTL programming was attributed to up-regulation of eomes and down-regulation of T-bet. Wnt signaling suppressed the mTOR pathway during CTL activation, which was different to its effects on other cell types. Interestingly, the impaired memory CTL programming by wnt was partially rescued by mTOR inhibitor rapamycin. In conclusion, we found that crosstalk between wnt and the IL-12 signaling inhibits T-bet and mTOR pathways and impairs memory programming which can be recovered in part by rapamycin. In addition, direct inhibition of wnt signaling during CTL activation does not affect CTL memory programming. Therefore, wnt signaling may serve as a new tool for CTL manipulation in autoimmune diseases and immune therapy for certain cancers. Copyright © 2013 Elsevier Ltd. All rights reserved.

  11. Biological signals classification and analysis

    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 ...

  12. Book: Marine Bioacoustic Signal Processing and Analysis

    2011-09-30

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

  13. Signal analysis of ventricular fibrillation

    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

  14. Semi-classical signal analysis

    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

  15. SIGPROC: Pulsar Signal Processing Programs

    Lorimer, D. R.

    2011-07-01

    SIGPROC is a package designed to standardize the initial analysis of the many types of fast-sampled pulsar data. Currently recognized machines are the Wide Band Arecibo Pulsar Processor (WAPP), the Penn State Pulsar Machine (PSPM), the Arecibo Observatory Fourier Transform Machine (AOFTM), the Berkeley Pulsar Processors (BPP), the Parkes/Jodrell 1-bit filterbanks (SCAMP) and the filterbank at the Ooty radio telescope (OOTY). The SIGPROC tools should help users look at their data quickly, without the need to write (yet) another routine to read data or worry about big/little endian compatibility (byte swapping is handled automatically).

  16. Signal and image multiresolution analysis

    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

  17. Signal analysis for failure detection

    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

  18. Logic integer programming models for signaling networks.

    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.

  19. Ecosystem Analysis Program

    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

  20. Static Mapping of Functional Programs: An Example in Signal Processing

    Jack B. Dennis

    1996-01-01

    Full Text Available Complex signal-processing problems are naturally described by compositions of program modules that process streams of data. In this article we discuss how such compositions may be analyzed and mapped onto multiprocessor computers to effectively exploit the massive parallelism of these applications. The methods are illustrated with an example of signal processing for an optical surveillance problem. Program transformation and analysis are used to construct a program description tree that represents the given computation as an acyclic interconnection of stream-processing modules. Each module may be mapped to a set of threads run on a group of processing elements of a target multiprocessor. Performance is considered for two forms of multiprocessor architecture, one based on conventional DSP technology and the other on a multithreaded-processing element design.

  1. General programmed system for physiological signal processing

    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.

  2. LULU analysis program

    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

  3. Radar signal analysis and processing using Matlab

    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.

  4. Sentiment analysis for PTSD signals

    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.

  5. Biodiesel Emissions Analysis Program

    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.

  6. Multivariate Analysis for the Processing of Signals

    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

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

    Vivaldi, E A; Maldonado, P

    2001-08-01

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

  8. Programs for control of an analog-signal switching network

    D'Ottavio, T.; Enriquez, R.; Katz, R.; Skelly, J.

    1989-01-01

    A suite of programs has been developed to control the network of analog-signal switching multiplexers in the AGS complex. The software is driven by a relational database which describes the architecture of the multiplexer tree and the set of available analog signals. Signals are routed through a three-layer multiplexer tree, to be made available at four consoles each with three 4-trace oscilloscopes. A menu-structured operator interface program is available at each console, to accept requests to route any available analog signal to any of that console's 12 oscilloscope traces. A common routing-server program provides automatic routing-server program provides automatic routing of requested signals through the layers of multiplexers, maintaining a reservation database to denote free and in-use trunks. Expansion of the analog signal system is easily accommodated in software by adding new signals, trunks, multiplexers, or consoles to the database. Programmatic control of the triggering signals for each of the oscilloscopes is also provided. 3 refs., 4 figs., 3 tabs

  9. Knee joint vibroarthrographic signal processing and analysis

    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.

  10. Probabilistic Structural Analysis Program

    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.

  11. Programming an offline-analyzer of motor imagery signals via python language.

    Alonso-Valerdi, Luz María; Sepulveda, Francisco

    2011-01-01

    Brain Computer Interface (BCI) systems control the user's environment via his/her brain signals. Brain signals related to motor imagery (MI) have become a widespread method employed by the BCI community. Despite the large number of references describing the MI signal treatment, there is not enough information related to the available programming languages that could be suitable to develop a specific-purpose MI-based BCI. The present paper describes the development of an offline-analysis system based on MI-EEG signals via open-source programming languages, and the assessment of the system using electrical activity recorded from three subjects. The analyzer recognized at least 63% of the MI signals corresponding to three classes. The results of the offline analysis showed a promising performance considering that the subjects have never undergone MI trainings.

  12. NET-2 Network Analysis Program

    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.)

  13. Signal analysis of Hindustani classical music

    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...

  14. Signals and transforms in linear systems analysis

    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...

  15. Study of interhemispheric asymmetries in electroencephalographic signals by frequency analysis

    Zapata, J F; Garzon, J

    2011-01-01

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

  16. Multitaper spectral analysis of atmospheric radar signals

    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.

  17. Developing Breast Cancer Program at Xavier; Genomic and Proteomic Analysis of Signaling Pathways Involved in Xenohormone and MEK5 Regulation of Breast Cancer

    2010-05-01

    Tagatose are rare. In this study we have determined the effect of these rare ketohexoses on breast cancer cell proliferation and estrogen signalling...Cancer Center (TCC) will build a core of human talent that will address scientific problems such as drug resistance and the effect of environmental agents...pathways for ER(+) (MCF-7) and ER(-) (MCF-7-MEK5) as potentially more effective therapeutic targets. 11 Abstract of RCMI proposal submitted to

  18. Programming signal processing applications on heterogeneous wireless sensor platforms

    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

  19. Signal Timing Optimization Based on Fuzzy Compromise Programming for Isolated Signalized Intersection

    Dexin Yu

    2016-01-01

    Full Text Available In order to optimize the signal timing for isolated intersection, a new method based on fuzzy programming approach is proposed in this paper. Considering the whole operation efficiency of the intersection comprehensively, traffic capacity, vehicle cycle delay, cycle stops, and exhaust emission are chosen as optimization goals to establish a multiobjective function first. Then fuzzy compromise programming approach is employed to give different weight coefficients to various optimization objectives for different traffic flow ratios states. And then the multiobjective function is converted to a single objective function. By using genetic algorithm, the optimized signal cycle and effective green time can be obtained. Finally, the performance of the traditional method and new method proposed in this paper is compared and analyzed through VISSIM software. It can be concluded that the signal timing optimized in this paper can effectively reduce vehicle delays and stops, which can improve traffic capacity of the intersection as well.

  20. Environmental conditions analysis program

    Holten, J.

    1991-01-01

    The PC-based program discussed in this paper has the capability of determining the steady state temperatures of environmental zones (rooms). A program overview will be provided along with examples of formula use. Required input and output from the program will also be discussed. Specific application of plant monitored temperatures and utilization of this program will be offered. The presentation will show how the program can project individual room temperature profiles without continual temperature monitoring of equipment. A discussion will also be provided for the application of the program generated data. Evaluations of anticipated or planned plant modifications and the use of the subject program will also be covered

  1. Nonlinear programming analysis and methods

    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.

  2. No-signaling quantum key distribution: solution by linear programming

    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.

  3. Resistance Training Exercise Program for Intervention to Enhance Gait Function in Elderly Chronically Ill Patients: Multivariate Multiscale Entropy for Center of Pressure Signal Analysis

    Ming-Shu Chen

    2014-01-01

    Full Text Available Falls are unpredictable accidents, and the resulting injuries can be serious in the elderly, particularly those with chronic diseases. Regular exercise is recommended to prevent and treat hypertension and other chronic diseases by reducing clinical blood pressure. The “complexity index” (CI, based on multiscale entropy (MSE algorithm, has been applied in recent studies to show a person’s adaptability to intrinsic and external perturbations and widely used measure of postural sway or stability. The multivariate multiscale entropy (MMSE was advanced algorithm used to calculate the complexity index (CI values of the center of pressure (COP data. In this study, we applied the MSE & MMSE to analyze gait function of 24 elderly, chronically ill patients (44% female; 56% male; mean age, 67.56±10.70 years with either cardiovascular disease, diabetes mellitus, or osteoporosis. After a 12-week training program, postural stability measurements showed significant improvements. Our results showed beneficial effects of resistance training, which can be used to improve postural stability in the elderly and indicated that MMSE algorithms to calculate CI of the COP data were superior to the multiscale entropy (MSE algorithm to identify the sense of balance in the elderly.

  4. Cellular signaling identifiability analysis: a case study.

    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.

  5. Reverse engineering GTPase programming languages with reconstituted signaling networks.

    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.

  6. Static Analysis of Mobile Programs

    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

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

    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.

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

    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.

  9. Electromagnetic modeling method for eddy current signal analysis

    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

  10. Programs for nuclear data analysis

    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)

  11. GAP Analysis Program (GAP)

    Kansas Data Access and Support Center — The Kansas GAP Analysis Land Cover database depicts 43 land cover classes for the state of Kansas. The database was generated using a two-stage hybrid classification...

  12. Liquid Effluents Program mission analysis

    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

  13. Static Analysis of Functional Programs

    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

  14. Analysis of computer programming languages

    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

  15. Programmable delay circuit for sparker signal analysis

    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...

  16. Analog and digital signal analysis from basics to applications

    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...

  17. XML Graphs in Program Analysis

    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...

  18. Seismic analysis program group: SSAP

    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)

  19. Program Analysis Scenarios in Rascal

    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

  20. Develop advanced nonlinear signal analysis topographical mapping system

    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

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

    Kil-Mo Koo

    2012-01-01

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

  2. Matlab programming for numerical analysis

    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

  3. R data analysis without programming

    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

  4. Acoustic signal analysis in the creeping discharge

    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

  5. Signal Analysis for Radiation Event Identification

    Steven A. Wallace

    2004-12-30

    The method of digitizing the scintillation output signals from a lithiated sol-gel based glass is described. The design considerations for using the lithiated scintillator for the detection of Special Nuclear Material (SNM) is presented.

  6. Schottky signal analysis: tune and chromaticity computation

    Chanon, Ondine

    2016-01-01

    Schottky monitors are used to determine important beam parameters in a non-destructive way. The Schottky signal is due to the internal statistical fluctuations of the particles inside the beam. In this report, after explaining the different components of a Schottky signal, an algorithm to compute the betatron tune is presented, followed by some ideas to compute machine chromaticity. The tests have been performed with offline and/or online LHC data.

  7. Massive Signal Analysis with Hadoop (Invited)

    Addair, T.

    2013-12-01

    The Geophysical Monitoring Program (GMP) at Lawrence Livermore National Laboratory is in the process of transitioning from a primarily human-driven analysis pipeline to a more automated and exploratory system. Waveform correlation represents a significant part of this effort, and the results that come out of this processing could lead to the development of more sophisticated event detection and analysis systems that require less human interaction, and address fundamental shortcomings in existing systems. Furthermore, use of distributed IO systems fundamentally addresses a scalability concern for the GMP as our data holdings continue to grow rapidly. As the data volume increases, it becomes less reasonable to rely upon human analysts to sift through all the information. Not only is more automation essential to keeping up with the ingestion rate, but so too do we require faster and more sophisticated tools for visualizing and interacting with the data. These issues of scalability are not unique to GMP or the seismic domain. All across the lab, and throughout industry, we hear about the promise of 'big data' to address the need of quickly analyzing vast amounts of data in fundamentally new ways. Our waveform correlation system finds and correlates nearby seismic events across the entire Earth. In our original implementation of the system, we processed some 50 TB of data on an in-house traditional HPC cluster (44 cores, 1 filesystem) over the span of 42 days. Having determined the primary bottleneck in the performance to be reading waveforms off a single BlueArc file server, we began investigating distributed IO solutions like Hadoop. As a test case, we took a 1 TB subset of our data and ported it to Livermore Computing's development Hadoop cluster. Through a pilot project sponsored by Livermore Computing (LC), the GMP successfully implemented the waveform correlation system in the Hadoop distributed MapReduce computing framework. Hadoop is an open source

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

    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 ...

  9. An Analysis of Programming Beginners' Source Programs

    Matsuyama, Chieko; Nakashima, Toyoshiro; Ishii, Naohiro

    The production of animations was made the subject of a university programming course in order to make students understand the process of program creation, and so that students could tackle programming with interest. In this paper, the formats and composition of the programs which students produced were investigated. As a result, it was found that there were a lot of problems related to such matters as how to use indent, how to apply comments and functions etc. for the format and the composition of the source codes.

  10. Orbiter CCTV video signal noise analysis

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

    1977-01-01

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

  11. Automatic analysis of signals during Eddy currents controls

    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

  12. The Photoplethismographic Signal Processed with Nonlinear Time Series Analysis Tools

    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

  13. Compressive Sensing: Analysis of Signals in Radio Astronomy

    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.

  14. Source Signals Separation and Reconstruction Following Principal Component Analysis

    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.

  15. A Program Transformation for Backwards Analysis of Logic Programs

    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...

  16. Pattern theory the stochastic analysis of real-world signals

    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

  17. Analysis and prediction of leucine-rich nuclear export signals

    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...

  18. Small-signal analysis of granular semiconductors

    Varpula, Aapo; Sinkkonen, Juha; Novikov, Sergey, E-mail: aapo.varpula@tkk.f [Department of Micro and Nanosciences, Aalto University, PO Box 13500, FI-00076 Aalto, Espoo (Finland)

    2010-11-01

    The small-signal ac response of granular n-type semiconductors is calculated analytically using the drift-diffusion theory when electronic trapping at grain boundaries is present. An electrical equivalent circuit (EEC) model of a granular n-type semiconductor is presented. The analytical model is verified with numerical simulation performed by SILVACO ATLAS. The agreement between the analytical and numerical results is very good in a broad frequency range at low dc bias voltages.

  19. Small-signal analysis of granular semiconductors

    Varpula, Aapo; Sinkkonen, Juha; Novikov, Sergey

    2010-01-01

    The small-signal ac response of granular n-type semiconductors is calculated analytically using the drift-diffusion theory when electronic trapping at grain boundaries is present. An electrical equivalent circuit (EEC) model of a granular n-type semiconductor is presented. The analytical model is verified with numerical simulation performed by SILVACO ATLAS. The agreement between the analytical and numerical results is very good in a broad frequency range at low dc bias voltages.

  20. Analysis of transient signals by Wavelet transform

    Penha, Rosani Libardi da; Silva, Aucyone A. da; Ting, Daniel K.S.; Oliveira Neto, Jose Messias de

    2000-01-01

    The objective of this work is to apply the Wavelet Transform in transient signals. The Wavelet technique can outline the short time events that are not easily detected using traditional techniques. In this work, the Wavelet Transform is compared with Fourier Transform, by using simulated data and rotor rig data. This data contain known transients. The wavelet could follow all the transients, what do not happen to the Fourier techniques. (author)

  1. Large scale analysis of signal reachability.

    Todor, Andrei; Gabr, Haitham; Dobra, Alin; Kahveci, Tamer

    2014-06-15

    Major disorders, such as leukemia, have been shown to alter the transcription of genes. Understanding how gene regulation is affected by such aberrations is of utmost importance. One promising strategy toward this objective is to compute whether signals can reach to the transcription factors through the transcription regulatory network (TRN). Due to the uncertainty of the regulatory interactions, this is a #P-complete problem and thus solving it for very large TRNs remains to be a challenge. We develop a novel and scalable method to compute the probability that a signal originating at any given set of source genes can arrive at any given set of target genes (i.e., transcription factors) when the topology of the underlying signaling network is uncertain. Our method tackles this problem for large networks while providing a provably accurate result. Our method follows a divide-and-conquer strategy. We break down the given network into a sequence of non-overlapping subnetworks such that reachability can be computed autonomously and sequentially on each subnetwork. We represent each interaction using a small polynomial. The product of these polynomials express different scenarios when a signal can or cannot reach to target genes from the source genes. We introduce polynomial collapsing operators for each subnetwork. These operators reduce the size of the resulting polynomial and thus the computational complexity dramatically. We show that our method scales to entire human regulatory networks in only seconds, while the existing methods fail beyond a few tens of genes and interactions. We demonstrate that our method can successfully characterize key reachability characteristics of the entire transcriptions regulatory networks of patients affected by eight different subtypes of leukemia, as well as those from healthy control samples. All the datasets and code used in this article are available at bioinformatics.cise.ufl.edu/PReach/scalable.htm. © The Author 2014

  2. A versatile Moessbauer analysis program

    Jernberg, P.; Sundqvist, T.

    1983-06-01

    MDA - Moessbauer Data Analysis, is a user oriented computer program, aiming to simulate a Moessbauer transmission spectrum, given by a set of parameters, and compare it with experimental data. The calculation considers a number of experimental situations and the comparisons can be made by least squares sums or by plotting the simulated and the measured spectrum. A fitting routine, minimizing the least squares sum, can be used to find the parameters characterizing the measured spectrum.(author)

  3. Signal analysis of steam line acoustics

    Martin, C. Samuel

    2003-01-01

    The vibration of nuclear steam piping is usually associated with pressure fluctuations emanating from flow disturbances such as steam generator nozzles, bends, or other pipe fittings. Flow separation at pipe tees and within steam chest manifolds or headers generate pressure fluctuations that propagate both upstream to steam generators as well as downstream to the steam turbine. Steady-state acoustic oscillations at various frequencies occur within the piping, possibly exciting structural vibrations. This paper focuses on the assessment of the origin of the disturbances using signal analyses of two dynamic pressure recordings from pressure transducers located along straight runs in the steam piping. The technique involves performing the cross spectrum to two dynamic pressure signals in piping between (1) the steam generator and steam chest header, and (2) between the header and steam turbine outlet. If, at a specified frequency, no causality occurs between the two signals then the cross spectra magnitude will be negligible. Of interest here is the value of the phase between the two signals for frequencies for which the magnitude of the cross spectrum is not negligible. It is shown in the paper that the direction of the dominant waves at all frequencies can be related to the phase angle from the cross spectrum. It has to be realized that pressure waves emanating from one source such as a steam generator will propagate along uniform steam pipes with little transformation or attenuation, but will be reflected at fittings and at inlets and outlets. Hence, the eventual steady-state time record at a given location in the piping is a result of not only the disturbance, but also reflections of earlier pulsations. Cross-spectral analyses has been employed to determine the direction of the dominant acoustic waves in the piping for various frequencies for which there are signals. To prove the technique, synthetic spectra are generated comprised of harmonic waves moving both

  4. Analysis of signal acquisition in GPS receiver software

    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

  5. Lactation Biology Symposium: Lactocrine signaling and developmental programming

    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...

  6. Subseabed-disposal program: systems-analysis program plan

    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

  7. Differential TCR signals for T helper cell programming.

    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.

  8. Signal integrity analysis on discontinuous microstrip line

    Qiao, Qingyang; Dai, Yawen; Chen, Zipeng

    2013-01-01

    In high speed PCB design, microstirp lines were used to control the impedance, however, the discontinuous microstrip line can cause signal integrity problems. In this paper, we use the transmission line theory to study the characteristics of microstrip lines. Research results indicate that the discontinuity such as truncation, gap and size change result in the problems such as radiation, reflection, delay and ground bounce. We change the discontinuities to distributed parameter circuits, analysed the steady-state response and transient response and the phase delay. The transient response cause radiation and voltage jump.

  9. Applications of wavelet transforms for nuclear power plant signal analysis

    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)

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

    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

  11. Signal-dependent independent component analysis by tunable mother wavelets

    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

  12. Transistor Small Signal Analysis under Radiation Effects

    Sharshar, K.A.A.

    2004-01-01

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

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

    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.

  14. Planetary Protection Bioburden Analysis Program

    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

  15. A review of intelligent systems for heart sound signal analysis.

    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.

  16. Mathematical principles of signal processing Fourier and wavelet analysis

    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...

  17. Conducting a SWOT Analysis for Program Improvement

    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…

  18. XML Graphs in Program Analysis

    Møller, Anders; Schwartzbach, Michael Ignatieff

    2007-01-01

    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...... 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 four very different applications: XML in Java, Java Servlets and JSP, transformations between XML and non-XML data, and XSLT....

  19. Safeguard Vulnerability Analysis Program (SVAP)

    Gilman, F.M.; Dittmore, M.H.; Orvis, W.J.; Wahler, P.S.

    1980-01-01

    This report gives an overview of the Safeguard Vulnerability Analysis Program (SVAP) developed at Lawrence Livermore National Laboratory. SVAP was designed as an automated method of analyzing the safeguard systems at nuclear facilities for vulnerabilities relating to the theft or diversion of nuclear materials. SVAP addresses one class of safeguard threat: theft or diversion of nuclear materials by nonviolent insiders, acting individually or in collusion. SVAP is a user-oriented tool which uses an interactive input medium for preprocessing the large amounts of safeguards data. Its output includes concise summary data as well as detailed vulnerability information

  20. On semi-classical questions related to signal analysis

    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.

  1. The Signal and Noise Analysis of Direct Conversion EHM Transceivers

    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.

  2. Personal Computer Transport Analysis Program

    DiStefano, Frank, III; Wobick, Craig; Chapman, Kirt; McCloud, Peter

    2012-01-01

    The Personal Computer Transport Analysis Program (PCTAP) is C++ software used for analysis of thermal fluid systems. The program predicts thermal fluid system and component transients. The output consists of temperatures, flow rates, pressures, delta pressures, tank quantities, and gas quantities in the air, along with air scrubbing component performance. PCTAP s solution process assumes that the tubes in the system are well insulated so that only the heat transfer between fluid and tube wall and between adjacent tubes is modeled. The system described in the model file is broken down into its individual components; i.e., tubes, cold plates, heat exchangers, etc. A solution vector is built from the components and a flow is then simulated with fluid being transferred from one component to the next. The solution vector of components in the model file is built at the initiation of the run. This solution vector is simply a list of components in the order of their inlet dependency on other components. The component parameters are updated in the order in which they appear in the list at every time step. Once the solution vectors have been determined, PCTAP cycles through the components in the solution vector, executing their outlet function for each time-step increment.

  3. A general numerical analysis program for the superconducting quasiparticle mixer

    Hicks, R. G.; Feldman, M. J.; Kerr, A. R.

    1986-01-01

    A user-oriented computer program SISCAP (SIS Computer Analysis Program) for analyzing SIS mixers is described. The program allows arbitrary impedance terminations to be specified at all LO harmonics and sideband frequencies. It is therefore able to treat a much more general class of SIS mixers than the widely used three-frequency analysis, for which the harmonics are assumed to be short-circuited. An additional program, GETCHI, provides the necessary input data to program SISCAP. The SISCAP program performs a nonlinear analysis to determine the SIS junction voltage waveform produced by the local oscillator. The quantum theory of mixing is used in its most general form, treating the large signal properties of the mixer in the time domain. A small signal linear analysis is then used to find the conversion loss and port impedances. The noise analysis includes thermal noise from the termination resistances and shot noise from the periodic LO current. Quantum noise is not considered. Many aspects of the program have been adequately verified and found accurate.

  4. Epoch-based analysis of speech signals

    on speech production characteristics, but also helps in accurate analysis of speech. .... include time delay estimation, speech enhancement from single and multi- ...... log. (. E[k]. ∑K−1 l=0. E[l]. ) ,. (7) where K is the number of samples in the ...

  5. Improving detector signal processing with pulse height analysis in Moessbauer spectrometers

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

    2007-01-01

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

  6. ASAP- ARTIFICIAL SATELLITE ANALYSIS PROGRAM

    Kwok, J.

    1994-01-01

    The Artificial Satellite Analysis Program (ASAP) is a general orbit prediction program which incorporates sufficient orbit modeling accuracy for mission design, maneuver analysis, and mission planning. ASAP is suitable for studying planetary orbit missions with spacecraft trajectories of reconnaissance (flyby) and exploratory (mapping) nature. Sample data is included for a geosynchronous station drift cycle study, a Venus radar mapping strategy, a frozen orbit about Mars, and a repeat ground trace orbit. ASAP uses Cowell's method in the numerical integration of the equations of motion. The orbital mechanics calculation contains perturbations due to non-sphericity (up to a 40 X 40 field) of the planet, lunar and solar effects, and drag and solar radiation pressure. An 8th order Runge-Kutta integration scheme with variable step size control is used for efficient propagation. The input includes the classical osculating elements, orbital elements of the sun relative to the planet, reference time and dates, drag coefficient, gravitational constants, and planet radius, rotation rate, etc. The printed output contains Cartesian coordinates, velocity, equinoctial elements, and classical elements for each time step or event step. At each step, selected output is added to a plot file. The ASAP package includes a program for sorting this plot file. LOTUS 1-2-3 is used in the supplied examples to graph the results, but any graphics software package could be used to process the plot file. ASAP is not written to be mission-specific. Instead, it is intended to be used for most planetary orbiting missions. As a consequence, the user has to have some basic understanding of orbital mechanics to provide the correct input and interpret the subsequent output. ASAP is written in FORTRAN 77 for batch execution and has been implemented on an IBM PC compatible computer operating under MS-DOS. The ASAP package requires a math coprocessor and a minimum of 256K RAM. This program was last

  7. Canonical wnt signaling regulates atrioventricular junction programming and electrophysiological properties

    Gillers, Benjamin S.; Chiplunkar, Aditi; Aly, Haytham; Valenta, Tomas; Basler, Konrad; Christoffels, Vincent M.; Efimov, Igor R.; Boukens, Bastiaan J.; Rentschler, Stacey

    2015-01-01

    Proper patterning of the atrioventricular canal (AVC) is essential for delay of electrical impulses between atria and ventricles, and defects in AVC maturation can result in congenital heart disease. To determine the role of canonical Wnt signaling in the myocardium during AVC development. We used a

  8. Basic digital signal processing

    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.

  9. Artificial intelligence applied to process signal analysis

    Corsberg, Dan

    1988-01-01

    Many space station processes are highly complex systems subject to sudden, major transients. In any complex process control system, a critical aspect of the human/machine interface is the analysis and display of process information. Human operators can be overwhelmed by large clusters of alarms that inhibit their ability to diagnose and respond to a disturbance. Using artificial intelligence techniques and a knowledge base approach to this problem, the power of the computer can be used to filter and analyze plant sensor data. This will provide operators with a better description of the process state. Once a process state is recognized, automatic action could be initiated and proper system response monitored.

  10. Music Structure Analysis from Acoustic Signals

    Dannenberg, Roger B.; Goto, Masataka

    Music is full of structure, including sections, sequences of distinct musical textures, and the repetition of phrases or entire sections. The analysis of music audio relies upon feature vectors that convey information about music texture or pitch content. Texture generally refers to the average spectral shape and statistical fluctuation, often reflecting the set of sounding instruments, e.g., strings, vocal, or drums. Pitch content reflects melody and harmony, which is often independent of texture. Structure is found in several ways. Segment boundaries can be detected by observing marked changes in locally averaged texture.

  11. siGnum: graphical user interface for EMG signal analysis.

    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.

  12. Reliability analysis for Atucha II reactor protection system signals

    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

  13. Reliability analysis for Atucha II reactor protection system signals

    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)

  14. Acceleration Signal Characteristics for Intuitional Mass Analysis of Metallic Loose Parts

    Lee, Kwang-Hyun; Jung, Chang-Gyu

    2016-01-01

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

  15. Acceleration Signal Characteristics for Intuitional Mass Analysis of Metallic Loose Parts

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

    2016-10-15

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

  16. Postprocessing algorithm for automated analysis of pelvic intraoperative neuromonitoring signals

    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.

  17. The speech signal segmentation algorithm using pitch synchronous analysis

    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.

  18. Time-Frequency Analysis of Signals Generated by Rotating Machines

    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.

  19. Analysis of musical expression in audio signals

    Dixon, Simon

    2003-01-01

    In western art music, composers communicate their work to performers via a standard notation which specificies the musical pitches and relative timings of notes. This notation may also include some higher level information such as variations in the dynamics, tempo and timing. Famous performers are characterised by their expressive interpretation, the ability to convey structural and emotive information within the given framework. The majority of work on audio content analysis focusses on retrieving score-level information; this paper reports on the extraction of parameters describing the performance, a task which requires a much higher degree of accuracy. Two systems are presented: BeatRoot, an off-line beat tracking system which finds the times of musical beats and tracks changes in tempo throughout a performance, and the Performance Worm, a system which provides a real-time visualisation of the two most important expressive dimensions, tempo and dynamics. Both of these systems are being used to process data for a large-scale study of musical expression in classical and romantic piano performance, which uses artificial intelligence (machine learning) techniques to discover fundamental patterns or principles governing expressive performance.

  20. A program for activation analysis data processing

    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)

  1. Signal Integrity Analysis of High-Speed Interconnects

    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.

  2. Structural diversity of frameshifting signals : reprogramming the programmed

    Yu, Chien-Hung

    2011-01-01

    Programmed ribosomal frameshifting (PRF) is one kind of recoding events that is mostly utilized by RNA viruses to synthesize more proteins with defined ratio from their compact genome and it is known that the stoichiometric is critical to virus infection and propagation. Two cis-acting RNA elements

  3. Frames and operator theory in analysis and signal processing

    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...

  4. Power system small signal stability analysis and control

    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

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

    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

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

    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.

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

    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

  8. Water Quality Analysis Simulation Program (WASP)

    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.

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

    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.

  10. DEAP: A Database for Emotion Analysis Using Physiological Signals

    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

  11. Joint time frequency analysis in digital signal processing

    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...

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

    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.

  13. Program Analysis as Model Checking

    Olesen, Mads Chr.

    Software programs are proliferating throughout modern life, to a point where even the simplest appliances such as lightbulbs contain software, in addition to the software embedded in cars and airplanes. The correct functioning of these programs is therefore of the utmost importance, for the quality...

  14. Signal Adaptive System for Space/Spatial-Frequency Analysis

    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.

  15. Phosphoproteomics-based systems analysis of signal transduction networks

    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.

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

    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)

  17. A computer program for activation analysis

    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)

  18. RAWS II: A MULTIPLE REGRESSION ANALYSIS PROGRAM,

    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)

  19. Probabilistic Output Analysis by Program Manipulation

    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...

  20. Status of CHAP: composite HTGR analysis program

    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

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

    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.

  2. SURFACE ELECTROMYOGRAPHY IN BIOMECHANICS: APPLICATIONS AND SIGNAL ANALYSIS ASPECTS

    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.

  3. Analysis of room transfer function and reverberant signal statistics

    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...

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

    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.

  5. Correlation analysis of respiratory signals by using parallel coordinate plots.

    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.

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

    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

  7. Modelling and Analysis of Biochemical Signalling Pathway Cross-talk

    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.

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

    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.

  9. A signal processing analysis of Purkinje cells in vitro

    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.

  10. Inclusiveness program - a SWOT analysis

    Dósa, M.; Szegő, K.

    2017-09-01

    The Inclusiveness Program was created with the aim to integrate currently under-represented countries into the mainstream of European planetary research. Main stages of the working plan include setting up a database containing all the research institutes and universities where astronomical or geophysical research is carried out. It is necessary to identify their problems and needs. Challenging part of the project is to find exact means that help their work in a sustainable way. Strengths, weaknesses, opportunities and threats of the program were identified based on feedback from the inclusiveness community. Our conclusions, further suggestions are presented.

  11. Signal correlations in biomass combustion. An information theoretic analysis

    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

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

    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.

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

    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...

  14. Advanced Signal Analysis for Forensic Applications of Ground Penetrating Radar

    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.

  15. Signal analysis and processing for SmartPET

    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

  16. Analysis and logical modeling of biological signaling transduction networks

    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.

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

    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

  18. The PUMA test program and data analysis

    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

  19. A Review of Sleep Disorder Diagnosis by Electromyogram Signal Analysis.

    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.

  20. Probabilistic Resource Analysis by Program Transformation

    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...

  1. Evaluating Dynamic Analysis Techniques for Program Comprehension

    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.

  2. Random signal tomographical analysis of two-phase flow

    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

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

    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.

  4. Unveiling Hidden Dynamics of Hippo Signalling: A Systems Analysis

    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.

  5. Decision Vulnerability Analysis (DVA) Program

    2014-05-01

    31 14 Graphical Representation of the Summary Judgments of the Effectiveness, Vulnerability, and Understanding of the Subsystems’ as Judged by...posed several challenges. Numerous organizational typologies have been suggested over the years ( Robbins , 1994), and these typologies are often based...structure and functioning from a typology perspective ( Robbins , 1994), excerpts from a task analysis that described how the analysts currently performed

  6. Energy Analysis Program 1990 annual report

    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.

  7. Dynamic analysis program for frame structure

    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.)

  8. Digital signal processing and spectral analysis for scientists concepts and applications

    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...

  9. Interleukin-2 signaling pathway analysis by quantitative phosphoproteomics

    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....

  10. The nuclear analysis program at MURR

    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

  11. Energy Analysis Program 1990 annual report

    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

  12. Energy Analysis Program 1990 annual report

    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.

  13. Analysis of Voltage Signals from Superconducting Accelerator Magnets

    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.

  14. Advanced Time-Frequency Representation in Voice Signal Analysis

    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.

  15. Advances in Photopletysmography Signal Analysis for Biomedical Applications

    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.

  16. Continuous EEG signal analysis for asynchronous BCI application.

    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.

  17. Artifact suppression and analysis of brain activities with electroencephalography signals.

    Rashed-Al-Mahfuz, Md; Islam, Md Rabiul; Hirose, Keikichi; Molla, Md Khademul Islam

    2013-06-05

    Brain-computer interface is a communication system that connects the brain with computer (or other devices) but is not dependent on the normal output of the brain (i.e., peripheral nerve and muscle). Electro-oculogram is a dominant artifact which has a significant negative influence on further analysis of real electroencephalography data. This paper presented a data adaptive technique for artifact suppression and brain wave extraction from electroencephalography signals to detect regional brain activities. Empirical mode decomposition based adaptive thresholding approach was employed here to suppress the electro-oculogram artifact. Fractional Gaussian noise was used to determine the threshold level derived from the analysis data without any training. The purified electroencephalography signal was composed of the brain waves also called rhythmic components which represent the brain activities. The rhythmic components were extracted from each electroencephalography channel using adaptive wiener filter with the original scale. The regional brain activities were mapped on the basis of the spatial distribution of rhythmic components, and the results showed that different regions of the brain are activated in response to different stimuli. This research analyzed the activities of a single rhythmic component, alpha with respect to different motor imaginations. The experimental results showed that the proposed method is very efficient in artifact suppression and identifying individual motor imagery based on the activities of alpha component.

  18. Improved signal analysis for motional Stark effect data

    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

  19. Signal analysis of accelerometry data using gravity-based modeling

    Davey, Neil P.; James, Daniel A.; Anderson, Megan E.

    2004-03-01

    Triaxial accelerometers have been used to measure human movement parameters in swimming. Interpretation of data is difficult due to interference sources including interaction of external bodies. In this investigation the authors developed a model to simulate the physical movement of the lower back. Theoretical accelerometery outputs were derived thus giving an ideal, or noiseless dataset. An experimental data collection apparatus was developed by adapting a system to the aquatic environment for investigation of swimming. Model data was compared against recorded data and showed strong correlation. Comparison of recorded and modeled data can be used to identify changes in body movement, this is especially useful when cyclic patterns are present in the activity. Strong correlations between data sets allowed development of signal processing algorithms for swimming stroke analysis using first the pure noiseless data set which were then applied to performance data. Video analysis was also used to validate study results and has shown potential to provide acceptable results.

  20. Leak detection in pipelines through spectral analysis of pressure signals

    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.

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

    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)

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

    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.

  3. Spectral analysis of highly aliased sea-level signals

    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.

  4. Performance analysis of signaling protocols on OBS switches

    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.

  5. Analysis of acoustic sound signal for ONB measurement

    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

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

    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.

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

    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.

  8. Acoustic cardiac signals analysis: a Kalman filter–based approach

    Salleh SH

    2012-06-01

    Full Text Available Sheik Hussain Salleh,1 Hadrina Sheik Hussain,2 Tan Tian Swee,2 Chee-Ming Ting,2 Alias Mohd Noor,2 Surasak Pipatsart,3 Jalil Ali,4 Preecha P Yupapin31Department of Biomedical Instrumentation and Signal Processing, Universiti Teknologi Malaysia, Skudai, Malaysia; 2Centre for Biomedical Engineering Transportation Research Alliance, Universiti Teknologi Malaysia, Johor Bahru, Malaysia; 3Nanoscale Science and Engineering Research Alliance, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand; 4Institute of Advanced Photonics Science, Universiti Teknologi Malaysia, Johor Bahru, MalaysiaAbstract: Auscultation of the heart is accompanied by both electrical activity and sound. Heart auscultation provides clues to diagnose many cardiac abnormalities. Unfortunately, detection of relevant symptoms and diagnosis based on heart sound through a stethoscope is difficult. The reason GPs find this difficult is that the heart sounds are of short duration and separated from one another by less than 30 ms. In addition, the cost of false positives constitutes wasted time and emotional anxiety for both patient and GP. Many heart diseases cause changes in heart sound, waveform, and additional murmurs before other signs and symptoms appear. Heart-sound auscultation is the primary test conducted by GPs. These sounds are generated primarily by turbulent flow of blood in the heart. Analysis of heart sounds requires a quiet environment with minimum ambient noise. In order to address such issues, the technique of denoising and estimating the biomedical heart signal is proposed in this investigation. Normally, the performance of the filter naturally depends on prior information related to the statistical properties of the signal and the background noise. This paper proposes Kalman filtering for denoising statistical heart sound. The cycles of heart sounds are certain to follow first-order Gauss–Markov process. These cycles are observed with additional noise

  9. SIMS analysis: Development and evaluation program summary

    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

  10. A new LMS algorithm for analysis of atrial fibrillation signals.

    Ciaccio, Edward J; Biviano, Angelo B; Whang, William; Garan, Hasan

    2012-03-26

    A biomedical signal can be defined by its extrinsic features (x-axis and y-axis shift and scale) and intrinsic features (shape after normalization of extrinsic features). In this study, an LMS algorithm utilizing the method of differential steepest descent is developed, and is tested by normalization of extrinsic features in complex fractionated atrial electrograms (CFAE). Equations for normalization of x-axis and y-axis shift and scale are first derived. The algorithm is implemented for real-time analysis of CFAE acquired during atrial fibrillation (AF). Data was acquired at a 977 Hz sampling rate from 10 paroxysmal and 10 persistent AF patients undergoing clinical electrophysiologic study and catheter ablation therapy. Over 24 trials, normalization characteristics using the new algorithm with four weights were compared to the Widrow-Hoff LMS algorithm with four tapped delays. The time for convergence, and the mean squared error (MSE) after convergence, were compared. The new LMS algorithm was also applied to lead aVF of the electrocardiogram in one patient with longstanding persistent AF, to enhance the F wave and to monitor extrinsic changes in signal shape. The average waveform over a 25 s interval was used as a prototypical reference signal for matching with the aVF lead. Based on the derivation equations, the y-shift and y-scale adjustments of the new LMS algorithm were shown to be equivalent to the scalar form of the Widrow-Hoff LMS algorithm. For x-shift and x-scale adjustments, rather than implementing a long tapped delay as in Widrow-Hoff LMS, the new method uses only two weights. After convergence, the MSE for matching paroxysmal CFAE averaged 0.46 ± 0.49 μV(2)/sample for the new LMS algorithm versus 0.72 ± 0.35 μV(2)/sample for Widrow-Hoff LMS. The MSE for matching persistent CFAE averaged 0.55 ± 0.95 μV(2)/sample for the new LMS algorithm versus 0.62 ± 0.55 μV(2)/sample for Widrow-Hoff LMS. There were no significant differences in estimation

  11. A new LMS algorithm for analysis of atrial fibrillation signals

    Ciaccio Edward J

    2012-03-01

    Full Text Available Abstract Background A biomedical signal can be defined by its extrinsic features (x-axis and y-axis shift and scale and intrinsic features (shape after normalization of extrinsic features. In this study, an LMS algorithm utilizing the method of differential steepest descent is developed, and is tested by normalization of extrinsic features in complex fractionated atrial electrograms (CFAE. Method Equations for normalization of x-axis and y-axis shift and scale are first derived. The algorithm is implemented for real-time analysis of CFAE acquired during atrial fibrillation (AF. Data was acquired at a 977 Hz sampling rate from 10 paroxysmal and 10 persistent AF patients undergoing clinical electrophysiologic study and catheter ablation therapy. Over 24 trials, normalization characteristics using the new algorithm with four weights were compared to the Widrow-Hoff LMS algorithm with four tapped delays. The time for convergence, and the mean squared error (MSE after convergence, were compared. The new LMS algorithm was also applied to lead aVF of the electrocardiogram in one patient with longstanding persistent AF, to enhance the F wave and to monitor extrinsic changes in signal shape. The average waveform over a 25 s interval was used as a prototypical reference signal for matching with the aVF lead. Results Based on the derivation equations, the y-shift and y-scale adjustments of the new LMS algorithm were shown to be equivalent to the scalar form of the Widrow-Hoff LMS algorithm. For x-shift and x-scale adjustments, rather than implementing a long tapped delay as in Widrow-Hoff LMS, the new method uses only two weights. After convergence, the MSE for matching paroxysmal CFAE averaged 0.46 ± 0.49μV2/sample for the new LMS algorithm versus 0.72 ± 0.35μV2/sample for Widrow-Hoff LMS. The MSE for matching persistent CFAE averaged 0.55 ± 0.95μV2/sample for the new LMS algorithm versus 0.62 ± 0.55μV2/sample for Widrow

  12. Studying creativity training programs: A methodological analysis

    Valgeirsdóttir, Dagný; Onarheim, Balder

    2017-01-01

    Throughout decades of creativity research, a range of creativity training programs have been developed, tested, and analyzed. In 2004 Scott and colleagues published a meta‐analysis of all creativity training programs to date, and the review presented here sat out to identify and analyze studies...... published since the seminal 2004 review. Focusing on quantitative studies of creativity training programs for adults, our systematic review resulted in 22 publications. All studies were analyzed, but comparing the reported effectiveness of training across studies proved difficult due to methodological...... inconsistencies, variations in reporting of results as well as types of measures used. Thus a consensus for future studies is called for to answer the question: Which elements make one creativity training program more effective than another? This is a question of equal relevance to academia and industry...

  13. Damage analysis and fundamental studies program

    Doran, D.G.; Farrar, H. IV; Goland, A.N.

    1978-01-01

    The Damage Analysis and Fundamental Studies (DAFS) Task Group has been formed by the Office of Fusion Energy to develop procedures for applying data obtained in various irradiation test facilities to projected fusion environments. A long-range program plan has been prepared and implementation has begun. The plan and technical status are briefly described

  14. Counter Trafficking System Development "Analysis Training Program"

    Peterson, Dennis C. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2010-12-01

    This document will detail the training curriculum for the Counter-Trafficking System Development (CTSD) Analysis Modules and Lesson Plans are derived from the United States Military, Department of Energy doctrine and Lawrence Livermore National Laboratory (LLNL), Global Security (GS) S Program.

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

    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

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

    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

  17. On semi-classical questions related to signal analysis

    Helffer, Bernard; Laleg-Kirati, Taous-Meriem

    2011-01-01

    . 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.

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

    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.

  19. A review of signals used in sleep analysis

    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)

  20. Symbolic transfer entropy-based premature signal analysis

    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)

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

    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

  2. Static Analysis of Lockless Microcontroller C Programs

    Eva Beckschulze

    2012-11-01

    Full Text Available Concurrently accessing shared data without locking is usually a subject to race conditions resulting in inconsistent or corrupted data. However, there are programs operating correctly without locking by exploiting the atomicity of certain operations on a specific hardware. In this paper, we describe how to precisely analyze lockless microcontroller C programs with interrupts by taking the hardware architecture into account. We evaluate this technique in an octagon-based value range analysis using access-based localization to increase efficiency.

  3. Refined generalized multiscale entropy analysis for physiological signals

    Liu, Yunxiao; Lin, Youfang; Wang, Jing; Shang, Pengjian

    2018-01-01

    Multiscale entropy analysis has become a prevalent complexity measurement and been successfully applied in various fields. However, it only takes into account the information of mean values (first moment) in coarse-graining procedure. Then generalized multiscale entropy (MSEn) considering higher moments to coarse-grain a time series was proposed and MSEσ2 has been implemented. However, the MSEσ2 sometimes may yield an imprecise estimation of entropy or undefined entropy, and reduce statistical reliability of sample entropy estimation as scale factor increases. For this purpose, we developed the refined model, RMSEσ2, to improve MSEσ2. Simulations on both white noise and 1 / f noise show that RMSEσ2 provides higher entropy reliability and reduces the occurrence of undefined entropy, especially suitable for short time series. Besides, we discuss the effect on RMSEσ2 analysis from outliers, data loss and other concepts in signal processing. We apply the proposed model to evaluate the complexity of heartbeat interval time series derived from healthy young and elderly subjects, patients with congestive heart failure and patients with atrial fibrillation respectively, compared to several popular complexity metrics. The results demonstrate that RMSEσ2 measured complexity (a) decreases with aging and diseases, and (b) gives significant discrimination between different physiological/pathological states, which may facilitate clinical application.

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

    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.

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

    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.

  6. Fourier and wavelet analysis of skin laser doppler flowmetry signals

    Qi, Wei

    2011-01-01

    ObjectiveThis thesis examines the measurement of skin microvascular blood flows from Laser Doppler Flowmetry (LDF) signals. Both healthy subjects and those with features of the metabolic syndrome are studied using signal processing techniques such as the Fourier and Wavelet transforms. An aim of this study is to investigate whether change in blood flow at rest can be detected from the spectral content of the processed signals in the diferent subject groups. Additionally the effect of insulin ...

  7. An Analysis of the Influence of Signals Intelligence Through Wargaming

    McCaffrey, Charles

    2000-01-01

    Signals intelligence (SIGINT), information derived from the monitoring, interception, decryption and evaluation of an adversary's electronic communications, has long been viewed as a significant factor in modem warfare...

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

    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

  9. Brain Network Analysis from High-Resolution EEG Signals

    de Vico Fallani, Fabrizio; Babiloni, Fabio

    lattice and a random structure. Such a model has been designated as "small-world" network in analogy with the concept of the small-world phenomenon observed more than 30 years ago in social systems. In a similar way, many types of functional brain networks have been analyzed according to this mathematical approach. In particular, several studies based on different imaging techniques (fMRI, MEG and EEG) have found that the estimated functional networks showed small-world characteristics. In the functional brain connectivity context, these properties have been demonstrated to reflect an optimal architecture for the information processing and propagation among the involved cerebral structures. However, the performance of cognitive and motor tasks as well as the presence of neural diseases has been demonstrated to affect such a small-world topology, as revealed by the significant changes of L and C. Moreover, some functional brain networks have been mostly found to be very unlike the random graphs in their degree-distribution, which gives information about the allocation of the functional links within the connectivity pattern. It was demonstrated that the degree distributions of these networks follow a power-law trend. For this reason those networks are called "scale-free". They still exhibit the small-world phenomenon but tend to contain few nodes that act as highly connected "hubs". Scale-free networks are known to show resistance to failure, facility of synchronization and fast signal processing. Hence, it would be important to see whether the scaling properties of the functional brain networks are altered under various pathologies or experimental tasks. The present Chapter proposes a theoretical graph approach in order to evaluate the functional connectivity patterns obtained from high-resolution EEG signals. In this way, the "Brain Network Analysis" (in analogy with the Social Network Analysis that has emerged as a key technique in modern sociology) represents an

  10. Statis Program Analysis for Reliable, Trusted Apps

    2017-02-01

    and prevent errors in their Java programs. The Checker Framework includes compiler plug-ins (“checkers”) that find bugs or verify their absence. It...versions of the Java language. 4.8 DATAFLOW FRAMEWORK The dataflow framework enables more accurate analysis of source code. (Despite their similar...names, the dataflow framework is independent of the (Information) Flow Checker of chapter 2.) In Java code, a given operation may be permitted or

  11. Developing a meaningful QA trend analysis program

    Sternberg, A.

    1987-01-01

    A trend analysis program is being developed by the nuclear quality assurance (NQA) department at Public Service Electric and Gas Company, adapted from the principles advocated by W. Edwards Deming using statistical process control methods. It deals with identifying performance indicators that monitor the activities of a process considering both inputs and outputs, determining whether the process is stable or unstable, taking actions accordingly, and continuing to monitor the process with the objective of continual improvement of quality

  12. Reconstruction and signal propagation analysis of the Syk signaling network in breast cancer cells.

    Aurélien Naldi

    2017-03-01

    Full Text Available The ability to build in-depth cell signaling networks from vast experimental data is a key objective of computational biology. The spleen tyrosine kinase (Syk protein, a well-characterized key player in immune cell signaling, was surprisingly first shown by our group to exhibit an onco-suppressive function in mammary epithelial cells and corroborated by many other studies, but the molecular mechanisms of this function remain largely unsolved. Based on existing proteomic data, we report here the generation of an interaction-based network of signaling pathways controlled by Syk in breast cancer cells. Pathway enrichment of the Syk targets previously identified by quantitative phospho-proteomics indicated that Syk is engaged in cell adhesion, motility, growth and death. Using the components and interactions of these pathways, we bootstrapped the reconstruction of a comprehensive network covering Syk signaling in breast cancer cells. To generate in silico hypotheses on Syk signaling propagation, we developed a method allowing to rank paths between Syk and its targets. We first annotated the network according to experimental datasets. We then combined shortest path computation with random walk processes to estimate the importance of individual interactions and selected biologically relevant pathways in the network. Molecular and cell biology experiments allowed to distinguish candidate mechanisms that underlie the impact of Syk on the regulation of cortactin and ezrin, both involved in actin-mediated cell adhesion and motility. The Syk network was further completed with the results of our biological validation experiments. The resulting Syk signaling sub-networks can be explored via an online visualization platform.

  13. Spectrogram Image Analysis of Error Signals for Minimizing Impulse Noise

    Jeakwan Kim

    2016-01-01

    Full Text Available This paper presents the theoretical and experimental study on the spectrogram image analysis of error signals for minimizing the impulse input noises in the active suppression of noise. Impulse inputs of some specific wave patterns as primary noises to a one-dimensional duct with the length of 1800 mm are shown. The convergence speed of the adaptive feedforward algorithm based on the least mean square approach was controlled by a normalized step size which was incorporated into the algorithm. The variations of the step size govern the stability as well as the convergence speed. Because of this reason, a normalized step size is introduced as a new method for the control of impulse noise. The spectrogram images which indicate the degree of the attenuation of the impulse input noises are considered to represent the attenuation with the new method. The algorithm is extensively investigated in both simulation and real-time control experiment. It is demonstrated that the suggested algorithm worked with a nice stability and performance against impulse noises. The results in this study can be used for practical active noise control systems.

  14. Signal Integrity Analysis in Single and Bundled Carbon Nanotube Interconnects

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

    2013-01-01

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

  15. Structural Analysis of Kufasat Using Ansys Program

    Al-Maliky, Firas T.; AlBermani, Mohamed J.

    2018-03-01

    The current work focuses on vibration and modal analysis of KufaSat structure using ANSYS 16 program. Three types of Aluminum alloys (5052-H32, 6061-T6 and 7075-T6) were selected for investigation of the structure under design loads. Finite element analysis (FEA) in design static load of 51 g was performed. The natural frequencies for five modes were estimated using modal analysis. In order to ensure that KufaSat could withstand with various conditions during launch, the Margin of safety was calculated. The results of deformation and Von Mises stress for linear buckling analysis were also performed. The comparison of data was done to select the optimum material for KufaSat structures.

  16. Analysis of small-signal intensity modulation of semiconductor ...

    This paper demonstrates theoretical characterization of intensity modulation of semiconductor lasers (SL's). The study is based on a small-signal model to solve the laser rate equations taking into account suppression of optical gain. Analytical forms of the small-signal modulation response and modulation bandwidth are ...

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

    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.

  18. Signal analysis approach to ultrasonic evaluation of diffusion bond quality

    Thomas, Graham; Chinn, Diane

    1999-01-01

    Solid state bonds like the diffusion bond are attractive techniques for joining dissimilar materials since they are not prone to the defects that occur with fusion welding. Ultrasonic methods can detect the presence of totally unbonded regions but have difficulty sensing poor bonded areas where the substrates are in intimate contact. Standard ultrasonic imaging is based on amplitude changes in the signal reflected from the bond interface. Unfortunately, amplitude alone is not sensitive to bond quality. We demonstrated that there is additional information in the ultrasonic signal that correlates with bond quality. In our approach, we interrogated a set of dissimilar diffusion bonded samples with broad band ultrasonic signals. The signals were digitally processed and the characteristics of the signals that corresponded to bond quality were determined. These characteristics or features were processed with pattern recognition algorithms to produce predictions of bond quality. The predicted bond quality was then compared with the destructive measurement to assess the classification capability of the ultrasonic technique

  19. Carbon price signal. Impact Analysis on the European Electricity System

    2016-03-01

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

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

    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.

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

    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

  2. Energy Analysis Program. 1992 Annual report

    1993-06-01

    The Program became deeply involved in establishing 4 Washington, D.C., project office diving the last few months of fiscal year 1942. This project office, which reports to the Energy & Environment Division, will receive the majority of its support from the Energy Analysis Program. We anticipate having two staff scientists and support personnel in offices within a few blocks of DOE. Our expectation is that this office will carry out a series of projects that are better managed closer to DOE. We also anticipate that our representation in Washington will improve and we hope to expand the Program, its activities, and impact, in police-relevant analyses. In spite of the growth that we have achieved, the Program continues to emphasize (1) energy efficiency of buildings, (2) appliance energy efficiency standards, (3) energy demand forecasting, (4) utility policy studies, especially integrated resource planning issues, and (5) international energy studies, with considerate emphasis on developing countries and economies in transition. These continuing interests are reflected in the articles that appear in this report.

  3. Applications of Hilbert Spectral Analysis for Speech and Sound Signals

    Huang, Norden E.

    2003-01-01

    A new method for analyzing nonlinear and nonstationary data has been developed, and the natural applications are to speech and sound signals. The key part of the method is the Empirical Mode Decomposition method with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF). An IMF is defined as any function having the same numbers of zero-crossing and extrema, and also having symmetric envelopes defined by the local maxima and minima respectively. The IMF also admits well-behaved Hilbert transform. This decomposition method is adaptive, and, therefore, highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it is applicable to nonlinear and nonstationary processes. With the Hilbert transform, the Intrinsic Mode Functions yield instantaneous frequencies as functions of time, which give sharp identifications of imbedded structures. This method invention can be used to process all acoustic signals. Specifically, it can process the speech signals for Speech synthesis, Speaker identification and verification, Speech recognition, and Sound signal enhancement and filtering. Additionally, as the acoustical signals from machinery are essentially the way the machines are talking to us. Therefore, the acoustical signals, from the machines, either from sound through air or vibration on the machines, can tell us the operating conditions of the machines. Thus, we can use the acoustic signal to diagnosis the problems of machines.

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

    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)

  5. A signal detection theory analysis of an unconscious perception effect.

    Haase, S J; Theios, J; Jenison, R

    1999-07-01

    The independent observation model (Macmillan & Creelman, 1991) is fitted to detection-identification data collected under conditions of heavy masking. The model accurately predicts a quantitative relationship between stimulus detection and stimulus identification over a wide range of detection performance. This model can also be used to offer a signal detection interpretation of the common finding of above-chance identification following a missed signal. While our finding is not a new one, the stimuli used in this experiment (redundant three-letter strings) differ slightly from those used in traditional signal detection work. Also, the stimuli were presented very briefly and heavily masked, conditions typical in the study of unconscious perception effects.

  6. Analysis of Ultrasonic Transmitted Signal for Apple using Wavelet Transform

    Kim, Ki Bok; Lee, Sang Dae; Choi, Man Yong; Kim, Man Soo

    2005-01-01

    This study was conducted to analyze the ultrasonic transmitted signal for apple using wavelet transform. Fruit consists of nonlinear visco-elastic properties such as flesh, an ovary and rind and lienee most ultrasonic wave is attenuated and its frequency is shifted during passing the fruit. Thus it is not easy to evaluate the internal quality of the fruit using typical ultrasonic parameters such as wave velocity, attenuation, and frequency spectrum. The discrete wavelet transform was applied to the ultrasonic transmitted signal for apple. The magnitude of the first peak frequency of the wavelet basis from the ultrasonic transmitted signal showed a close correlation to the storage time of apple

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

    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.

  8. Performance analysis of NOAA tropospheric signal delay model

    Ibrahim, Hassan E; El-Rabbany, Ahmed

    2011-01-01

    Tropospheric delay is one of the dominant global positioning system (GPS) errors, which degrades the positioning accuracy. Recent development in tropospheric modeling relies on implementation of more accurate numerical weather prediction (NWP) models. In North America one of the NWP-based tropospheric correction models is the NOAA Tropospheric Signal Delay Model (NOAATrop), which was developed by the US National Oceanic and Atmospheric Administration (NOAA). Because of its potential to improve the GPS positioning accuracy, the NOAATrop model became the focus of many researchers. In this paper, we analyzed the performance of the NOAATrop model and examined its effect on ionosphere-free-based precise point positioning (PPP) solution. We generated 3 year long tropospheric zenith total delay (ZTD) data series for the NOAATrop model, Hopfield model, and the International GNSS Services (IGS) final tropospheric correction product, respectively. These data sets were generated at ten IGS reference stations spanning Canada and the United States. We analyzed the NOAATrop ZTD data series and compared them with those of the Hopfield model. The IGS final tropospheric product was used as a reference. The analysis shows that the performance of the NOAATrop model is a function of both season (time of the year) and geographical location. However, its performance was superior to the Hopfield model in all cases. We further investigated the effect of implementing the NOAATrop model on the ionosphere-free-based PPP solution convergence and accuracy. It is shown that the use of the NOAATrop model improved the PPP solution convergence by 1%, 10% and 15% for the latitude, longitude and height components, respectively

  9. Sediment Analysis Using a Structured Programming Approach

    Daniela Arias-Madrid

    2012-12-01

    Full Text Available This paper presents an algorithm designed for the analysis of a sedimentary sample of unconsolidated material and seeks to identify very quickly the main features that occur in a sediment and thus classify them fast and efficiently. For this purpose, it requires that the weight of each particle size to be entered in the program and using the method of Moments, which is based on four equations representing the mean, standard deviation, skewness and kurtosis, is found the attributes of the sample in few seconds. With the program these calculations are performed in an effective and more accurately way, obtaining also the explanations of the results of the features such as grain size, sorting, symmetry and origin, which helps to improve the study of sediments and in general the study of sedimentary rocks.

  10. Computer programs for analysis of geophysical data

    Rozhkov, M.; Nakanishi, K.

    1994-06-01

    This project is oriented toward the application of the mobile seismic array data analysis technique in seismic investigations of the Earth (the noise-array method). The technique falls into the class of emission tomography methods but, in contrast to classic tomography, 3-D images of the microseismic activity of the media are obtained by passive seismic antenna scanning of the half-space, rather than by solution of the inverse Radon`s problem. It is reasonable to expect that areas of geothermal activity, active faults, areas of volcanic tremors and hydrocarbon deposits act as sources of intense internal microseismic activity or as effective sources for scattered (secondary) waves. The conventional approaches of seismic investigations of a geological medium include measurements of time-limited determinate signals from artificial or natural sources. However, the continuous seismic oscillations, like endogenous microseisms, coda and scattering waves, can give very important information about the structure of the Earth. The presence of microseismic sources or inhomogeneities within the Earth results in the appearance of coherent seismic components in a stochastic wave field recorded on the surface by a seismic array. By careful processing of seismic array data, these coherent components can be used to develop a 3-D model of the microseismic activity of the media or images of the noisy objects. Thus, in contrast to classic seismology where narrow windows are used to get the best time resolution of seismic signals, our model requires long record length for the best spatial resolution.

  11. Computer programs for analysis of geophysical data

    Rozhkov, M.; Nakanishi, K.

    1994-06-01

    This project is oriented toward the application of the mobile seismic array data analysis technique in seismic investigations of the Earth (the noise-array method). The technique falls into the class of emission tomography methods but, in contrast to classic tomography, 3-D images of the microseismic activity of the media are obtained by passive seismic antenna scanning of the half-space, rather than by solution of the inverse Radon's problem. It is reasonable to expect that areas of geothermal activity, active faults, areas of volcanic tremors and hydrocarbon deposits act as sources of intense internal microseismic activity or as effective sources for scattered (secondary) waves. The conventional approaches of seismic investigations of a geological medium include measurements of time-limited determinate signals from artificial or natural sources. However, the continuous seismic oscillations, like endogenous microseisms, coda and scattering waves, can give very important information about the structure of the Earth. The presence of microseismic sources or inhomogeneities within the Earth results in the appearance of coherent seismic components in a stochastic wave field recorded on the surface by a seismic array. By careful processing of seismic array data, these coherent components can be used to develop a 3-D model of the microseismic activity of the media or images of the noisy objects. Thus, in contrast to classic seismology where narrow windows are used to get the best time resolution of seismic signals, our model requires long record length for the best spatial resolution

  12. Measurement of transient two-phase flow velocity using statistical signal analysis of impedance probe signals

    Leavell, W.H.; Mullens, J.A.

    1981-01-01

    A computational algorithm has been developed to measure transient, phase-interface velocity in two-phase, steam-water systems. The algorithm will be used to measure the transient velocity of steam-water mixture during simulated PWR reflood experiments. By utilizing signals produced by two, spatially separated impedance probes immersed in a two-phase mixture, the algorithm computes the average transit time of mixture fluctuations moving between the two probes. This transit time is computed by first, measuring the phase shift between the two probe signals after transformation to the frequency domain and then computing the phase shift slope by a weighted least-squares fitting technique. Our algorithm, which has been tested with both simulated and real data, is able to accurately track velocity transients as fast as 4 m/s/s

  13. Analysis of the Education Program Approval Process: A Program Evaluation.

    Fountaine, Charles A.; And Others

    A study of the education program approval process involving the Veterans Administration (VA) and the State Approving Agencies (SAAs) had the following objectives: to describe the present education program approval process; to determine time and costs associated with the education program approval process; to describe the approval process at…

  14. Analysis of Design of Mixed-Signal Electronic Packaging

    Pileggi, Lawrence

    1999-01-01

    The objective of this project is to develop innovative algorithms and prototype tools that will help facilitate the design of mixed signal multi-chip modules and packaging in a manner that is similar...

  15. Research Article Genetic Analysis of Signal Peptides in Amphibian ...

    USUARIO

    Depending on the genus, the whole structure could be duplicated in tandem or scattered ..... signalling, presumably for translocating the lipid bilayer during synthesis. .... revised classification of extant frogs, salamanders, and caecilians.

  16. small signal analysis of load angle governing and excitation control

    Dr Obe

    system stabilizers (PSS) or using terminal voltage for control of exciter and speed signal for governor. ... Vfd= generator field voltage. Xd, Xq ... each other in the frequency domain, and therefore ..... angle sensing equipment, relays and.

  17. Emg Signal Analysis of Healthy and Neuropathic Individuals

    Gupta, Ashutosh; Sayed, Tabassum; Garg, Ridhi; Shreyam, Richa

    2017-08-01

    Electromyography is a method to evaluate levels of muscle activity. When a muscle contracts, an action potential is generated and this circulates along the muscular fibers. In electromyography, electrodes are connected to the skin and the electrical activity of muscles is measured and graph is plotted. The surface EMG signals picked up during the muscular activity are interfaced with a system. The EMG signals from individual suffering from Neuropathy and healthy individual, so obtained, are processed and analyzed using signal processing techniques. This project includes the investigation and interpretation of EMG signals of healthy and Neuropathic individuals using MATLAB. The prospective use of this study is in developing the prosthetic device for the people with Neuropathic disability.

  18. Analysis of small-signal intensity modulation of semiconductor ...

    Computer simulation of the model is applied to 1.55-µm ... Semiconductor laser; small-signal modulation; modulation response; gain suppression. ... originates from intraband relaxation processes of charge carriers that extend for times as ...

  19. Analysis of the finescale timing of repeated signals: does shell rapping in hermit crabs signal stamina?

    Briffa; Elwood

    2000-01-01

    Hermit crabs, Pagurus bernhardus, sometimes exchange shells after a period of shell rapping, when the initiating or attacking crab brings its shell rapidly and repeatedly into contact with the shell of the noninitiator or defender in a series of bouts. Bouts are separated by pauses, and raps within bouts are separated by very short periods called 'gaps'. Since within-contest variation is missed when signals are studied by averaging performance rates over entire contests, we analysed the fine within-bout structure of this repeated, aggressive signal. We found that the pattern is consistent with high levels of fatigue in initiators. The duration of the gaps between individual raps increased both within bouts and from bout to bout, and we conclude that this activity is costly to perform. Furthermore, long pauses between bouts is correlated with increased vigour of rapping in the subsequent bout, which suggests that the pause allows for recovery from fatigue induced by rapping. These between-bout pauses may be assessed by noninitiators and provide a signal of stamina. Copyright 2000 The Association for the Study of Animal Behaviour.

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

    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...

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

    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.

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

    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

  3. Conditional Random Fields for Morphological Analysis of Wireless ECG Signals

    Natarajan, Annamalai; Gaiser, Edward; Angarita, Gustavo; Malison, Robert; Ganesan, Deepak; Marlin, Benjamin

    2014-01-01

    Thanks to advances in mobile sensing technologies, it has recently become practical to deploy wireless electrocardiograph sensors for continuous recording of ECG signals. This capability has diverse applications in the study of human health and behavior, but to realize its full potential, new computational tools are required to effectively deal with the uncertainty that results from the noisy and highly non-stationary signals collected using these devices. In this work, we present a novel app...

  4. Signals analysis of fluxgate array for wire rope defaults

    Gu Wei; Chu Jianxin

    2005-01-01

    In order to detecting the magnetic leakage fields of the wire rope defaults, a transducer made up of the fluxgate array is designed, and a series of the characteristic values of wire rope defaults signals are defined. By processing the characteristic signals, the LF or LMA of wire rope are distinguished, and the default extent is estimated. The experiment results of the new method for detecting the wire rope faults are introduced

  5. Enhanced Phosphoproteomic Profiling Workflow For Growth Factor Signaling Analysis

    Sylvester, Marc; Burbridge, Mike; Leclerc, Gregory

    2010-01-01

    Background Our understanding of complex signaling networks is still fragmentary. Isolated processes have been studied extensively but cross-talk is omnipresent and precludes intuitive predictions of signaling outcomes. The need for quantitative data on dynamic systems is apparent especially for our...... understanding of pathological processes. In our study we create and integrate data on phosphorylations that are initiated by several growth factor receptors. We present an approach for quantitative, time-resolved phosphoproteomic profiling that integrates the important contributions by phosphotyrosines. Methods...

  6. Brain Signal Analysis Using Different Types of Music

    Siti Ayuni Mohd Nasir; Wan Mahani Hafizah Wan Mahmud

    2015-01-01

    Music is able to improve certain functions of human body physiologically and psychologically. Music also can improve attention, memory, and even mental math ability by listening to the music before performing any task. The purpose of this study is to study the relation between types of music and brainwaves signal that is differences in state of relaxation and attention states. The Electroencephalography (EEG) signal was recorded using PowerLab, Dual Bio Amp and computer to observes and record...

  7. Large-signal stability analysis of PWM converters

    Huynh, P.T. [Philips Labs., Briarcliff Manor, NY (United States); Cho, B.H. [Seoul National Univ. (Korea, Republic of). Dept. of Electrical Engineering

    1995-12-31

    Investigation of the effects of existing nonlinearities on the stability of PWM converters is performed. The bilinear structure, the duty cycle saturation, and the opamp saturation are the principal nonlinearities in PWM converters. These nonlinearities are incorporated in the large-signal analytical models of PWM converters, and the basic input-output stability theory is applied to analyze their stability. Design and optimization of the small-signal loop gains to counteract the undesirable nonlinear effects are also discussed.

  8. Note for the Mirnov signal analysis in tokamaks

    Kikuchi, M.

    1985-05-01

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

  9. Interactive Programming and Analysis Aids (IPAA)

    1978-06-01

    PAGE 2. GOVT ACCESSION NO.J I JBBIITWj ’"" —— ■ "- INTERACTIVE PROGRAMMING AND ANALYSIS AIDS (IPÄA). 7^ 9. PERFORMING ORGANIZATION ...H fll u u u j o^ o f-« w « » m ^ r>» • ff> o fH CM w * «n >II N ec o^ o »^ ew « isik.f.^iiki>.i«.i^coco<s(Oflos>cocoa> coff >0^ovo«oko^3^a

  10. Analysis of an image quality assurance program

    Goethlin, J.H.; Alders, B.

    1985-01-01

    Reject film analysis before and after the introduction of a quality assurance program showed a 45% decrease in rejected films. The main changes in equipment and routines were: 1. Increased control of film processors and X-ray generators. 2. New film casettes and screens. 3. Decreased number of film sizes. 4. Information to and supervision of radiographing personnel. Savings in costs and increased income from an increased amount of out-patients corresponded to about 4.5% of the total cost of operating and maintaining the department. (orig.)

  11. Statistical 21-cm Signal Separation via Gaussian Process Regression Analysis

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

    2018-05-01

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

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

    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.

  13. Stem cell signaling. An integral program for tissue renewal and regeneration : Wnt signaling and stem cell control

    Clevers, Hans; Loh, Kyle M; Nusse, Roel

    2014-01-01

    Stem cells fuel tissue development, renewal, and regeneration, and these activities are controlled by the local stem cell microenvironment, the "niche." Wnt signals emanating from the niche can act as self-renewal factors for stem cells in multiple mammalian tissues. Wnt proteins are lipid-modified,

  14. Safety analysis of urban signalized intersections under mixed traffic.

    S, Anjana; M V L R, Anjaneyulu

    2015-02-01

    This study examined the crash causative factors of signalized intersections under mixed traffic using advanced statistical models. Hierarchical Poisson regression and logistic regression models were developed to predict the crash frequency and severity of signalized intersection approaches. The prediction models helped to develop general safety countermeasures for signalized intersections. The study shows that exclusive left turn lanes and countdown timers are beneficial for improving the safety of signalized intersections. Safety is also influenced by the presence of a surveillance camera, green time, median width, traffic volume, and proportion of two wheelers in the traffic stream. The factors that influence the severity of crashes were also identified in this study. As a practical application, the safe values of deviation of green time provided from design green time, with varying traffic volume, is presented in this study. This is a useful tool for setting the appropriate green time for a signalized intersection approach with variations in the traffic volume. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

    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)

  16. Conditional Random Fields for Morphological Analysis of Wireless ECG Signals

    Natarajan, Annamalai; Gaiser, Edward; Angarita, Gustavo; Malison, Robert; Ganesan, Deepak; Marlin, Benjamin

    2015-01-01

    Thanks to advances in mobile sensing technologies, it has recently become practical to deploy wireless electrocardiograph sensors for continuous recording of ECG signals. This capability has diverse applications in the study of human health and behavior, but to realize its full potential, new computational tools are required to effectively deal with the uncertainty that results from the noisy and highly non-stationary signals collected using these devices. In this work, we present a novel approach to the problem of extracting the morphological structure of ECG signals based on the use of dynamically structured conditional random field (CRF) models. We apply this framework to the problem of extracting morphological structure from wireless ECG sensor data collected in a lab-based study of habituated cocaine users. Our results show that the proposed CRF-based approach significantly out-performs independent prediction models using the same features, as well as a widely cited open source toolkit. PMID:26726321

  17. Reference analysis of the signal + background model in counting experiments

    Casadei, D.

    2012-01-01

    The model representing two independent Poisson processes, labelled as ``signal'' and ``background'' and both contributing additively to the total number of counted events, is considered from a Bayesian point of view. This is a widely used model for the searches of rare or exotic events in presence of a background source, as for example in the searches performed by high-energy physics experiments. In the assumption of prior knowledge about the background yield, a reference prior is obtained for the signal alone and its properties are studied. Finally, the properties of the full solution, the marginal reference posterior, are illustrated with few examples.

  18. Essential Role of DAP12 Signaling in Macrophage Programming into a Fusion-Competent State

    Helming, Laura; Tomasello, Elena; Kyriakides, Themis R.; Martinez, Fernando O.; Takai, Toshiyuki; Gordon, Siamon; Vivier, Eric

    2009-01-01

    Multinucleated giant cells, formed by fusion of macrophages, are a hallmark of granulomatous inflammation. With a genetic approach, we show that signaling through the adaptor protein DAP12 (DNAX activating protein of 12 kD), its associated receptor triggering receptor expressed by myeloid cells 2 (TREM-2), and the downstream protein tyrosine kinase Syk is required for the cytokine-induced formation of giant cells and that overexpression of DAP12 potentiates macrophage fusion. We also present evidence that DAP12 is a general macrophage fusion regulator and is involved in modulating the expression of several macrophage-associated genes, including those encoding known mediators of macrophage fusion, such as DC-STAMP and Cadherin 1. Thus, DAP12 is involved in programming of macrophages through the regulation of gene and protein expression to induce a fusion-competent state. PMID:18957693

  19. Cardiac Development and Transcription Factors: Insulin Signalling, Insulin Resistance, and Intrauterine Nutritional Programming of Cardiovascular Disease

    Govindsamy, Annelene; Naidoo, Strinivasen

    2018-01-01

    Programming with an insult or stimulus during critical developmental life stages shapes metabolic disease through divergent mechanisms. Cardiovascular disease increasingly contributes to global morbidity and mortality, and the heart as an insulin-sensitive organ may become insulin resistant, which manifests as micro- and/or macrovascular complications due to diabetic complications. Cardiogenesis is a sequential process during which the heart develops into a mature organ and is regulated by several cardiac-specific transcription factors. Disrupted cardiac insulin signalling contributes to cardiac insulin resistance. Intrauterine under- or overnutrition alters offspring cardiac structure and function, notably cardiac hypertrophy, systolic and diastolic dysfunction, and hypertension that precede the onset of cardiovascular disease. Optimal intrauterine nutrition and oxygen saturation are required for normal cardiac development in offspring and the maintenance of their cardiovascular physiology. PMID:29484207

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

    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...

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

    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.

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

    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.

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

    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.

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

    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.

  5. Analysis on geometry-aware received signal strength based ...

    These handle different scenarios such as environment, adaptation, hybridization and the choice of context is dependent on user requirements. This paper present geometry-aware received signal strength (RSS) based positioning techniques where the influences of the geometries of the BSs (where location estimation ...

  6. Conceptual analysis of social signals: the importance of clarifying terminology

    Mehu, Marc; D'Errico, Francesca; Heylen, Dirk K.J.

    2012-01-01

    As a burgeoning field, Social Signal Processing (SSP) needs a solid grounding in the disciplines that have developed important concepts in the study of communication. However, the number and diversity of terms developed in linguistics, psychology, and the behavioural sciences may seem confusing for

  7. The spectral analysis of cyclo-non-stationary signals

    Abboud, D.; Baudin, S.; Antoni, J.; Rémond, D.; Eltabach, M.; Sauvage, O.

    2016-06-01

    Condition monitoring of rotating machines in speed-varying conditions remains a challenging task and an active field of research. Specifically, the produced vibrations belong to a particular class of non-stationary signals called cyclo-non-stationary: although highly non-stationary, they contain hidden periodicities related to the shaft angle; the phenomenon of long term modulations is what makes them different from cyclostationary signals which are encountered under constant speed regimes. In this paper, it is shown that the optimal way of describing cyclo-non-stationary signals is jointly in the time and the angular domains. While the first domain describes the waveform characteristics related to the system dynamics, the second one reveals existing periodicities linked to the system kinematics. Therefore, a specific class of signals - coined angle-time cyclostationary is considered, expressing the angle-time interaction. Accordingly, the related spectral representations, the order-frequency spectral correlation and coherence functions are proposed and their efficiency is demonstrated on two industrial cases.

  8. Optimum short-time polynomial regression for signal analysis

    A Sreenivasa Murthy

    the Proceedings of European Signal Processing Conference. (EUSIPCO) 2008. ... In a seminal paper, Savitzky and Golay [4] showed that short-time polynomial modeling is ...... We next consider a linearly frequency-modulated chirp with an exponentially .... 1 http://www.physionet.org/physiotools/matlab/ECGwaveGen/.

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

    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.

  10. Resonance detection of EEG signals using two-layer wavelet analysis

    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

  11. Utility green pricing programs: a statistical analysis of program effectiveness

    Ryan, W.; Scott, O.; Lori, B.; Blair, S.

    2005-01-01

    Utility green pricing programs represent one way in which consumers can voluntarily support the development of renewable energy. The design features and effectiveness of these programs varies considerably. Based on a survey of utility program managers in the United States, this article provides insight into which program features might help maximize both customer participation in green pricing programs and the amount of renewable energy purchased by customers in those programs. We find that program length has a substantial impact on customer participation and purchases; to achieve higher levels of success, utilities will need to remain committed to their product offering for some time. Our findings also suggest that utilities should consider higher renewable energy purchase thresholds for residential customers in order to maximize renewable energy sales. Smaller utilities are found to be more successful than larger utilities, and we find some evidence that providing private benefits to nonresidential participants can enhance success. Interestingly, we find little evidence that the cost of the green pricing product greatly impacts customer participation and renewable energy sales, at least over the narrow range of premiums embedded in our data set, and for the initial set of green power purchasers. (author)

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

    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.

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

    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.

  14. Traffic analysis and signal processing in optical packet switched networks

    Fjelde, Tina

    2002-01-01

    /s optical packet switched network exploiting the best of optics and electronics, is used as a thread throughout the thesis. An overview of the DAVID network architecture is given, focussing on the MAN and WAN architecture as well as the MPLS-based network hierarchy. Subsequently, the traffic performance...... of the DAVID core optical packet router, which exploits wavelength conversion and fibre delay-line buffers for contention resolution, is analysed using a numerical model developed for that purpose. The robustness of the shared recirculating loop buffer with respect to´bursty traffic is demonstrated...... the injection of an additional clock signal into the IWC is presented. Results show very good transmission capabilities combined with a high-speed response. It is argued that signal regeneration is an inherent attribute of the IWC employed as a wavelength converter due to the sinusoidal transfer function...

  15. Genetic analysis of gravity signal transduction in roots

    Masson, Patrick; Strohm, Allison; Baldwin, Katherine

    To grow downward into the soil, roots use gravity as a guide. Specialized cells, named stato-cytes, enable this directional growth response by perceiving gravity. Located in the columella region of the cap, these cells sense a reorientation of the root within the gravity field through the sedimentation of, and/or tension/pressure exerted by, dense amyloplasts. This process trig-gers a gravity signal transduction pathway that leads to a fast alkalinization of the cytoplasm and a change in the distribution of the plasma membrane-associated auxin-efflux carrier PIN3. The latter protein is uniformly distributed within the plasma membrane on all sides of the cell in vertically oriented roots. However, it quickly accumulates at the bottom side upon gravis-timulation. This process correlates with a preferential transport of auxin to the bottom side of the root cap, resulting in a lateral gradient across the tip. This gradient is then transported to the elongation zone where it promotes differential cellular elongation, resulting in downward curvature. We isolated mutations that affect gravity signal transduction at a step that pre-cedes cytoplasmic alkalinization and/or PIN3 relocalization and lateral auxin transport across the cap. arg1 and arl2 mutations identify a common genetic pathway that is needed for all three gravity-induced processes in the cap statocytes, indicating these genes function early in the pathway. On the other hand, adk1 affects gravity-induced PIN3 relocalization and lateral auxin transport, but it does not interfere with cytoplasmic alkalinization. ARG1 and ARL2 encode J-domain proteins that are associated with membranes of the vesicular trafficking path-way whereas ADK1 encodes adenosine kinase, an enzyme that converts adenosine derived from nucleic acid metabolism and the AdoMet cycle into AMP, thereby alleviating feedback inhibi-tion of this important methyl-donor cycle. Because mutations in ARG1 (and ARL2) do not completely eliminate

  16. Computer programs simplify optical system analysis

    1965-01-01

    The optical ray-trace computer program performs geometrical ray tracing. The energy-trace program calculates the relative monochromatic flux density on a specific target area. This program uses the ray-trace program as a subroutine to generate a representation of the optical system.

  17. Analysis of Enhanced Velocity Signals Observed during Solar Flares ...

    2003-10-28

    Oct 28, 2003 ... close to the vicinity of the hard X-ray source regions as observed with. RHESSI. The power maps of the active region show enhancement in the frequency regime 5–6.5mHz, while there is feeble or no enhancement of these signals in 2–4 mHz frequency band. High energy particles with sufficient momentum ...

  18. Diagnostic analysis of vibration signals using adaptive digital filtering techniques

    Jewell, R. E.; Jones, J. H.; Paul, J. E.

    1983-01-01

    Signal enhancement techniques are described using recently developed digital adaptive filtering equipment. Adaptive filtering concepts are not new; however, as a result of recent advances in microprocessor-based electronics, hardware has been developed that has stable characteristics and of a size exceeding 1000th order. Selected data processing examples are presented illustrating spectral line enhancement, adaptive noise cancellation, and transfer function estimation in the presence of corrupting noise.

  19. A new LMS algorithm for analysis of atrial fibrillation signals

    Ciaccio Edward J; Biviano Angelo B; Whang William; Garan Hasan

    2012-01-01

    Abstract Background A biomedical signal can be defined by its extrinsic features (x-axis and y-axis shift and scale) and intrinsic features (shape after normalization of extrinsic features). In this study, an LMS algorithm utilizing the method of differential steepest descent is developed, and is tested by normalization of extrinsic features in complex fractionated atrial electrograms (CFAE). Method Equations for normalization of x-axis and y-axis shift and scale are first derived. The algori...

  20. Nonlinear complexity analysis of brain FMRI signals in schizophrenia.

    Moses O Sokunbi

    Full Text Available We investigated the differences in brain fMRI signal complexity in patients with schizophrenia while performing the Cyberball social exclusion task, using measures of Sample entropy and Hurst exponent (H. 13 patients meeting diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM IV criteria for schizophrenia and 16 healthy controls underwent fMRI scanning at 1.5 T. The fMRI data of both groups of participants were pre-processed, the entropy characterized and the Hurst exponent extracted. Whole brain entropy and H maps of the groups were generated and analysed. The results after adjusting for age and sex differences together show that patients with schizophrenia exhibited higher complexity than healthy controls, at mean whole brain and regional levels. Also, both Sample entropy and Hurst exponent agree that patients with schizophrenia have more complex fMRI signals than healthy controls. These results suggest that schizophrenia is associated with more complex signal patterns when compared to healthy controls, supporting the increase in complexity hypothesis, where system complexity increases with age or disease, and also consistent with the notion that schizophrenia is characterised by a dysregulation of the nonlinear dynamics of underlying neuronal systems.

  1. Distributed sensing signal analysis of deformable plate/membrane mirrors

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

    2017-11-01

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

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

    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.

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

    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

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

    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)

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

    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.

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

    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

  7. Genetic Analysis of Gravity Signal Transduction in Arabidopsis Roots

    Masson, Patrick; Strohm, Allison; Barker, Richard; Su, Shih-Heng

    Like most other plant organs, roots use gravity as a directional guide for growth. Specialized cells within the columella region of the root cap (the statocytes) sense the direction of gravity through the sedimentation of starch-filled plastids (amyloplasts). Amyloplast movement and/or pressure on sensitive membranes triggers a gravity signal transduction pathway within these cells, which leads to a fast transcytotic relocalization of plasma-membrane associated auxin-efflux carrier proteins of the PIN family (PIN3 and PIN7) toward the bottom membrane. This leads to a polar transport of auxin toward the bottom flank of the cap. The resulting lateral auxin gradient is then transmitted toward the elongation zones where it triggers a curvature that ultimately leads to a restoration of vertical downward growth. Our laboratory is using strategies derived from genetics and systems biology to elucidate the molecular mechanisms that modulate gravity sensing and signal transduction in the columella cells of the root cap. Our previous research uncovered two J-domain-containing proteins, ARG1 and ARL2, as contributing to this process. Mutations in the corresponding paralogous genes led to alterations of root and hypocotyl gravitropism accompanied by an inability for the statocytes to develop a cytoplasmic alkalinization, relocalize PIN3, and transport auxin laterally, in response to gravistimulation. Both proteins are associated peripherally to membranes belonging to various compartments of the vesicular trafficking pathway, potentially modulating the trafficking of defined proteins between plasma membrane and endosomes. MAR1 and MAR2, on the other end, are distinct proteins of the plastidic outer envelope protein import TOC complex (the transmembrane channel TOC75 and the receptor TOC132, respectively). Mutations in the corresponding genes enhance the gravitropic defects of arg1. Using transformation-rescue experiments with truncated versions of TOC132 (MAR2), we have shown

  8. Detection of geodesic acoustic mode oscillations, using multiple signal classification analysis of Doppler backscattering signal on Tore Supra

    Vermare, L.; Hennequin, P.; Gürcan, Ö.D.

    2012-01-01

    This paper presents the first observation of geodesic acoustic modes (GAMs) on Tore Supra plasmas. Using the Doppler backscattering system, the oscillations of the plasma flow velocity, localized between r/a = 0.85 and r/a = 0.95, and with a frequency, typically around 10 kHz, have been observed at the plasma edge in numerous discharges. When the additional heating power is varied, the frequency is found to scale with C s /R. The MUltiple SIgnal Classification (MUSIC) algorithm is employed to access the temporal evolution of the perpendicular velocity of density fluctuations. The method is presented in some detail, and is validated and compared against standard methods, such as the conventional fast Fourier transform method, using a synthetic signal. It stands out as a powerful data analysis method to follow the Doppler frequency with a high temporal resolution, which is important in order to extract the dynamics of GAMs. (paper)

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

    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.

  10. Intrasystem Electromagnetic Compatibility Analysis Program. Volume III. Computer Program Documentation

    1974-12-01

    Cor intied) PROGRAM NAME SIMBOL DEFINITION FQEPDB fep IN dB FQEPL LOWER INTERVAL BOUNDARY FREQ OF fep FQEPU UPPER INTERVAL BOUNDARY FREQ OF f .4, fep...I• TOR. VARIABLES L __G~~ NM SIMBOL DEFINITION BWFE 1 BANDWIDTH FACTOR OF EM’TR BANDWIDTH FACTOR OF RCPT EINTB INTEGRATBD MARGIN BROAD BAND COMPON

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

    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)

  12. Design and analysis of UW-OFDM signals.

    Huemer, Mario; Hofbauer, Christian; Onic, Alexander; Huber, Johannes B

    2014-10-01

    Unique word-orthogonal frequency division multiplexing (UW-OFDM) is a novel signaling concept where the guard interval is implemented as a deterministic sequence, the so-called unique word. The UW is generated by introducing a certain level of redundancy in the frequency domain. Different data estimation strategies and the favourable bit error ratio (BER) performance of UW-OFDM, as well as comparisons to competing concepts have already extensively been discussed in previous papers. This work focuses on the different possibilities on how to generate UW-OFDM signals. The optimality of the two-step over the direct approach in systematic UW-OFDM is proved analytically, we present a heuristic algorithm that allows a fast numerical optimization of the redundant subcarrier positions, and we show that our original intuitive approach of spreading the redundant subcarriers in systematically encoded UW-OFDM by minimizing the mean redundant energy is practically also optimum w.r.t. transceiver based cost functions. Finally, we derive closed form approximations of the statistical symbol distributions on individual subcarriers as well as the redundant energy distribution and compare them with numerically found results.

  13. RAMPAC: a Program for Analysis of Complicated Raman Spectra

    de Mul, F.F.M.; Greve, Jan

    1993-01-01

    A computer program for the analysis of complicated (e.g. multi-line) Raman spectra is described. The program includes automatic peak search, various procedures for background determination, peak fit and spectrum deconvolution and extensive spectrum handling procedures.

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

    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

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

    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.

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

    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.

  17. Analysis of impulse signals with Hylaty ELF station

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

    2012-04-01

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

  18. Applied Fourier analysis from signal processing to medical imaging

    Olson, Tim

    2017-01-01

    The first of its kind, this focused textbook serves as a self-contained resource for teaching from scratch the fundamental mathematics of Fourier analysis and illustrating some of its most current, interesting applications, including medical imaging and radar processing. Developed by the author from extensive classroom teaching experience, it provides a breadth of theory that allows students to appreciate the utility of the subject, but at as accessible a depth as possible. With myriad applications included, this book can be adapted to a one or two semester course in Fourier Analysis or serve as the basis for independent study. Applied Fourier Analysis assumes no prior knowledge of analysis from its readers, and begins by making the transition from linear algebra to functional analysis. It goes on to cover basic Fourier series and Fourier transforms before delving into applications in sampling and interpolation theory, digital communications, radar processing, medical i maging, and heat and wave equations. Fo...

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

    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

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

    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

  1. Ber analysis of the box relaxation for BPSK signal recovery

    Thrampoulidis, Christos; Abbasi, Ehsan; Xu, Weiyu; Hassibi, Babak

    2016-01-01

    We study the problem of recovering an n-dimensional BPSK signal from m linear noise-corrupted measurements using the box relaxation method which relaxes the discrete set {±1}n to the convex set [-1,1]n to obtain a convex optimization algorithm followed by hard thresholding. When the noise and measurement matrix have iid standard normal entries, we obtain an exact expression for the bit-wise probability of error Pe in the limit of n and m growing and m/n fixed. At high SNR our result shows that the Pe of box relaxation is within 3dB of the matched filter bound (MFB) for square systems, and that it approaches the (MFB) as m grows large compared to n. Our results also indicate that as m, n → ∞, for any fixed set of size k, the error events of the corresponding k bits in the box relaxation method are independent.

  2. Ber analysis of the box relaxation for BPSK signal recovery

    Thrampoulidis, Christos

    2016-06-24

    We study the problem of recovering an n-dimensional BPSK signal from m linear noise-corrupted measurements using the box relaxation method which relaxes the discrete set {±1}n to the convex set [-1,1]n to obtain a convex optimization algorithm followed by hard thresholding. When the noise and measurement matrix have iid standard normal entries, we obtain an exact expression for the bit-wise probability of error Pe in the limit of n and m growing and m/n fixed. At high SNR our result shows that the Pe of box relaxation is within 3dB of the matched filter bound (MFB) for square systems, and that it approaches the (MFB) as m grows large compared to n. Our results also indicate that as m, n → ∞, for any fixed set of size k, the error events of the corresponding k bits in the box relaxation method are independent.

  3. lpNet: a linear programming approach to reconstruct signal transduction networks.

    Matos, Marta R A; Knapp, Bettina; Kaderali, Lars

    2015-10-01

    With the widespread availability of high-throughput experimental technologies it has become possible to study hundreds to thousands of cellular factors simultaneously, such as coding- or non-coding mRNA or protein concentrations. Still, extracting information about the underlying regulatory or signaling interactions from these data remains a difficult challenge. We present a flexible approach towards network inference based on linear programming. Our method reconstructs the interactions of factors from a combination of perturbation/non-perturbation and steady-state/time-series data. We show both on simulated and real data that our methods are able to reconstruct the underlying networks fast and efficiently, thus shedding new light on biological processes and, in particular, into disease's mechanisms of action. We have implemented the approach as an R package available through bioconductor. This R package is freely available under the Gnu Public License (GPL-3) from bioconductor.org (http://bioconductor.org/packages/release/bioc/html/lpNet.html) and is compatible with most operating systems (Windows, Linux, Mac OS) and hardware architectures. bettina.knapp@helmholtz-muenchen.de Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  4. Analysis of Arm Movement Prediction by Using the Electroencephalography Signal

    Reza Darmakusuma

    2016-04-01

    Full Text Available Various technological approaches have been developed in order to help those people who are unfortunateenough to be afflicted with different types of paralysis which limit them in performing their daily life activitiesindependently. One of the proposed technologies is the Brain-Computer Interface (BCI. The BCI system uses electroencephalography (EEG which is generated by the subject’s mental activityas input, and converts it into commands. Some previous experiments have shown the capability of the BCI system to predict the movement intention before the actual movement is onset. Thus research has predicted the movement by discriminating between data in the “rest” condition, wherethere is no movement intention, with “pre-movement” condition, where movement intention is detected before actual movement occurs. This experiment, however, was done to analyze the system for which machine learning was applied to data obtained in a continuous time interval, between 3 seconds before the movement was detected until 1 second after the actual movement was onset. This experiment shows that the system can discriminate the “pre-movement” condition and “rest” condition by using the EEG signal in 7-30 Hzwhere the Mu and Beta rhythm can be discovered with an average True Positive Rate (TPR value of 0.64 ± 0.11 and an average False Positive Rate (FPR of 0.17 ± 0.08. This experiment also shows that by using EEG signals obtained nearing the movement onset, the system has higher TPR or a detection rate in predicting the movement intention.

  5. Work program analysis - defining the capability/risk plan

    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)

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

    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)

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

    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,

  8. HTC Experimental Program: Validation and Calculational Analysis

    Fernex, F.; Ivanova, T.; Bernard, F.; Letang, E. [Inst Radioprotect and Surete Nucl, F-92262 Fontenay Aux Roses (France); Fouillaud, P. [CEA Valduc, Serv Rech Neutron and Critcite, 21 - Is-sur-Tille (France); Thro, J. F. [AREVA NC, F-78000 Versailles (France)

    2009-05-15

    In the 1980's a series of the Haut Taux de Combustion (HTC) critical experiments with fuel pins in a water-moderated lattice was conducted at the Apparatus B experimental facility in Valduc (Commissariat a I'Energie Atomique, France) with the support of the Institut de Radioprotection et de Surete Nucleaire and AREVA NC. Four series of experiments were designed to assess profit associated with actinide-only burnup credit in the criticality safety evaluation for fuel handling, pool storage, and spent-fuel cask conditions. The HTC rods, specifically fabricated for the experiments, simulated typical pressurized water reactor uranium oxide spent fuel that had an initial enrichment of 4. 5 wt% {sup 235}U and was burned to 37.5 GWd/tonne U. The configurations have been modeled with the CRISTAL criticality package and SCALE 5.1 code system. Sensitivity/uncertainty analysis has been employed to evaluate the HTC experiments and to study their applicability for validation of burnup credit calculations. This paper presents the experimental program, the principal results of the experiment evaluation, and modeling. The HTC data applicability to burnup credit validation is demonstrated with an example of spent-fuel storage models. (authors)

  9. Dissimilar weld failure analysis and development program

    Holko, K.H.; Li, C.C.

    1982-01-01

    The problem of dissimilar weld cracking and failure is examined. This problem occurs in boiler superheater and reheater sections as well as main steam piping. Typically, a dissimilar weld joins low-alloy steel tubing such as Fe-2-1/4 Cr-1Mo to stainless steel tubing such as 321H and 304H. Cracking and failure occur in the low-alloy steel heat-affected zone very close to the weld interface. The 309 stainless steel filler previously used has been replaced with nickel-base fillers such as Inconel 132, Inconel 182, and Incoweld A. This change has extended the time to cracking and failure, but has not solved the problem. To illustrate and define the problem, the metallography of damaged and failed dissimilar welds is described. Results of mechanical tests of dissimilar welds removed from service are presented, and factors believed to be influential in causing damage and failure are discussed. In addition, the importance of dissimilar weldment service history is demonstrated, and the Dissimilar Weld Failure Analysis and Development Program is described. 15 figures

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

    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.

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

    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

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

    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.

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

    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)

  14. Genetic Analysis of Gravity Signal Transduction in Arabidopsis thaliana Seedlings

    Boonsirichai, K.; Harrison, B.; Stanga, J.; Young, L.-S.; Neal, C.; Sabat, G.; Murthy, N.; Harms, A.; Sedbrook, J.; Masson, P.

    The primary roots of Arabidopsis thaliana seedlings respond to gravity stimulation by developing a tip curvature that results from differential cellular elongation on opposite flanks of the elongation zone. This curvature appears modulated by a lateral gradient of auxin that originates in the gravity-perceiving cells (statocytes) of the root cap through an apparent lateral repositioning of a component the auxin efflux carrier complex within these cells (Friml et al, 2002, Nature 415: 806-809). Unfortunately, little is known about the molecular mechanisms that govern early phases of gravity perception and signal transduction within the root-cap statocytes. We have used a molecular genetic approach to uncover some of these mechanisms. Mutations in the Arabidopsis ARG1 and ARL2 genes, which encode J-domain proteins, resulted in specific alterations in root and hypocotyl gravitropism, without pleiotropic phenotypes. Interestingly, ARG1 and ARL2 appear to function in the same genetic pathway. A combination of molecular genetic, biochemical and cell-biological approaches were used to demonstrate that ARG1 functions in early phases of gravity signal transduction within the root and hypocotyl statocytes, and is needed for efficient lateral auxin transport within the cap. The ARG1 protein is associated with components of the secretory and/or endosomal pathways, suggesting its role in the recycling of components of the auxin efflux carrier complex between plasma membrane and endosome (Boonsirichai et al, 2003, Plant Cell 15:2612-2625). Genetic modifiers of arg1-2 were isolated and shown to enhance the gravitropic defect of arg1-2, while resulting in little or no gravitropic defects in a wild type ARG1 background. A slight tendency for arg1-2;mar1-1 and arg1-2;mar2-1 double-mutant organs to display an opposite gravitropic response compared to wild type suggests that all three genes contribute to the interpretation of the gravity-vector information by seedling organs. The

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

    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

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

    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"--

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

    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)

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

    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.

  19. Coupling detrended fluctuation analysis for analyzing coupled nonstationary signals

    Hedayatifar, L.; Vahabi, M.; Jafari, G. R.

    2011-08-01

    When many variables are coupled to each other, a single case study could not give us thorough and precise information. When these time series are stationary, different methods of random matrix analysis and complex networks can be used. But, in nonstationary cases, the multifractal-detrended-cross-correlation-analysis (MF-DXA) method was introduced for just two coupled time series. In this article, we have extended the MF-DXA to the method of coupling detrended fluctuation analysis (CDFA) for the case when more than two series are correlated to each other. Here, we have calculated the multifractal properties of the coupled time series, and by comparing CDFA results of the original series with those of the shuffled and surrogate series, we can estimate the source of multifractality and the extent to which our series are coupled to each other. We illustrate the method by selected examples from air pollution and foreign exchange rates.

  20. Fusion genetic analysis of jasmonate-signalling mutants in Arabidopsis

    Jensen, Anders Bøgh; Raventos, D.; Mundy, John Williams

    2002-01-01

    as two recessive mutants, designated joe1 and 2, that overexpress the reporter. Genetic analysis indicated that reporter overexpression in the joe mutants requires COI. joe1 responded to MeJA with increased anthocyanin accumulation, while joe2 responded with decreased root growth inhibition. In addition...... activity was also induced by the protein kinase inhibitor staurosporine and antagonized by the protein phosphatase inhibitor okadaic acid. FLUC bio-imaging, RNA gel-blot analysis and progeny analyses identified three recessive mutants that underexpress the FLUC reporter, designated jue1, 2 and 3, as well...

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

    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

  2. Robust signal selection for lineair prediction analysis of voiced speech

    Ma, C.; Kamp, Y.; Willems, L.F.

    1993-01-01

    This paper investigates a weighted LPC analysis of voiced speech. In view of the speech production model, the weighting function is either chosen to be the short-time energy function of the preemphasized speech sample sequence with certain delays or is obtained by thresholding the short-time energy

  3. Review: Music analysis and retrieval systems for audio signals

    van den Broek, Egon

    2005-01-01

    This paper provides an overview of four years of the authors’ research on music information retrieval (MIR), omitting technical details. An overview of terminology, music analysis techniques, and research done in the last five years is also provided. Some of the results achieved by the authors are

  4. Computer program for compressible flow network analysis

    Wilton, M. E.; Murtaugh, J. P.

    1973-01-01

    Program solves problem of an arbitrarily connected one dimensional compressible flow network with pumping in the channels and momentum balancing at flow junctions. Program includes pressure drop calculations for impingement flow and flow through pin fin arrangements, as currently found in many air cooled turbine bucket and vane cooling configurations.

  5. Mixed Vehicle Flow At Signalized Intersection: Markov Chain Analysis

    Gertsbakh Ilya B.

    2015-09-01

    Full Text Available We assume that a Poisson flow of vehicles arrives at isolated signalized intersection, and each vehicle, independently of others, represents a random number X of passenger car units (PCU’s. We analyze numerically the stationary distribution of the queue process {Zn}, where Zn is the number of PCU’s in a queue at the beginning of the n-th red phase, n → ∞. We approximate the number Yn of PCU’s arriving during one red-green cycle by a two-parameter Negative Binomial Distribution (NBD. The well-known fact is that {Zn} follow an infinite-state Markov chain. We approximate its stationary distribution using a finite-state Markov chain. We show numerically that there is a strong dependence of the mean queue length E[Zn] in equilibrium on the input distribution of Yn and, in particular, on the ”over dispersion” parameter γ= Var[Yn]/E[Yn]. For Poisson input, γ = 1. γ > 1 indicates presence of heavy-tailed input. In reality it means that a relatively large ”portion” of PCU’s, considerably exceeding the average, may arrive with high probability during one red-green cycle. Empirical formulas are presented for an accurate estimation of mean queue length as a function of load and g of the input flow. Using the Markov chain technique, we analyze the mean ”virtual” delay time for a car which always arrives at the beginning of the red phase.

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

    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

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

    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.

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

    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.

  9. Developmental Programming: Prenatal Testosterone Excess and Insulin Signaling Disruptions in Female Sheep.

    Lu, Chunxia; Cardoso, Rodolfo C; Puttabyatappa, Muraly; Padmanabhan, Vasantha

    2016-05-01

    Women with polycystic ovary syndrome often manifest insulin resistance. Using a sheep model of polycystic ovary syndrome-like phenotype, we explored the contribution of androgen and insulin in programming and maintaining disruptions in insulin signaling in metabolic tissues. Phosphorylation of AKT, ERK, GSK3beta, mTOR, and p70S6K was examined in the liver, muscle, and adipose tissue of control and prenatal testosterone (T)-, prenatal T plus androgen antagonist (flutamide)-, and prenatal T plus insulin sensitizer (rosiglitazone)-treated fetuses as well as 2-yr-old females. Insulin-stimulated phospho (p)-AKT was evaluated in control and prenatal T-, prenatal T plus postnatal flutamide-, and prenatal T plus postnatal rosiglitazone-treated females at 3 yr of age. GLUT4 expression was evaluated in the muscle at all time points. Prenatal T treatment increased mTOR, p-p70S6K, and p-GSK3beta levels in the fetal liver with both androgen antagonist and insulin sensitizer preventing the mTOR increase. Both interventions had partial effect in preventing the increase in p-GSK3beta. In the fetal muscle, prenatal T excess decreased p-GSK3beta and GLUT4. The decrease in muscle p-GSK3beta was partially prevented by insulin sensitizer cotreatment. Both interventions partially prevented the decrease in GLUT4. Prenatal T treatment had no effect on basal expression of any of the markers in 2-yr-old females. At 3 yr of age, prenatal T treatment prevented the insulin-stimulated increase in p-AKT in liver and muscle, but not in adipose tissue, and neither postnatal intervention restored p-AKT response to insulin stimulation. Our findings provide evidence that prenatal T excess changes insulin sensitivity in a tissue- and development-specific manner and that both androgens and insulin may be involved in the programming of these metabolic disruptions. © 2016 by the Society for the Study of Reproduction, Inc.

  10. Social Network Analysis of the Farabi Exchange Program: Student Mobility

    Ugurlu, Zeynep

    2016-01-01

    Problem Statement: Exchange programs offer communication channels created through student and instructor exchanges; a flow of information takes place through these channels. The Farabi Exchange Program (FEP) is a student and instructor exchange program between institutions of higher education. Through the use of social network analysis and…

  11. QUASAR - an interactive program for spectrum analysis in personal computers

    Auler, L.T.; Nobrega, J.A.W. da.

    1991-11-01

    The QUASAR software for the interactive analysis and report of energy (pulse-height) and time (multichannel scaling) spectra is described. The operating instructions as well as the mathematical methods and algorithms used by the program are presented in detail. This program is an extension to the PULSAR program. (author)

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

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

    2016-08-01

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

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

    Dong-Sup Lee

    2015-01-01

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

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

    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

  15. Stress analysis program system for nuclear vessel: STANSAS

    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)

  16. Analysis of two dimensional signals via curvelet transform

    Lech, W.; Wójcik, W.; Kotyra, A.; Popiel, P.; Duk, M.

    2007-04-01

    This paper describes an application of curvelet transform analysis problem of interferometric images. Comparing to two-dimensional wavelet transform, curvelet transform has higher time-frequency resolution. This article includes numerical experiments, which were executed on random interferometric image. In the result of nonlinear approximations, curvelet transform obtains matrix with smaller number of coefficients than is guaranteed by wavelet transform. Additionally, denoising simulations show that curvelet could be a very good tool to remove noise from images.

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

    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.

  18. Comparative analysis of programmed cell death pathways in filamentous fungi

    Wortman Jennifer R

    2005-12-01

    Full Text Available Abstract Background Fungi can undergo autophagic- or apoptotic-type programmed cell death (PCD on exposure to antifungal agents, developmental signals, and stress factors. Filamentous fungi can also exhibit a form of cell death called heterokaryon incompatibility (HI triggered by fusion between two genetically incompatible individuals. With the availability of recently sequenced genomes of Aspergillus fumigatus and several related species, we were able to define putative components of fungi-specific death pathways and the ancestral core apoptotic machinery shared by all fungi and metazoa. Results Phylogenetic profiling of HI-associated proteins from four Aspergilli and seven other fungal species revealed lineage-specific protein families, orphan genes, and core genes conserved across all fungi and metazoa. The Aspergilli-specific domain architectures include NACHT family NTPases, which may function as key integrators of stress and nutrient availability signals. They are often found fused to putative effector domains such as Pfs, SesB/LipA, and a newly identified domain, HET-s/LopB. Many putative HI inducers and mediators are specific to filamentous fungi and not found in unicellular yeasts. In addition to their role in HI, several of them appear to be involved in regulation of cell cycle, development and sexual differentiation. Finally, the Aspergilli possess many putative downstream components of the mammalian apoptotic machinery including several proteins not found in the model yeast, Saccharomyces cerevisiae. Conclusion Our analysis identified more than 100 putative PCD associated genes in the Aspergilli, which may help expand the range of currently available treatments for aspergillosis and other invasive fungal diseases. The list includes species-specific protein families as well as conserved core components of the ancestral PCD machinery shared by fungi and metazoa.

  19. Program packages for dynamics systems analysis and design

    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)

  20. Measurement and Analysis of P2P IPTV Program Resource

    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.

  1. Measurement and analysis of P2P IPTV program resource.

    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.

  2. The Y2K program for scientific-analysis computer programs at AECL

    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)

  3. The Y2K program for scientific-analysis computer programs at AECL

    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)

  4. Integrating computer programs for engineering analysis and design

    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.

  5. Analysis of Logic Programs Using Regular Tree Languages

    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....

  6. Program Analysis and Its Relevance for Educational Research

    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

  7. Single-shell tank retrieval program mission analysis report

    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)

  8. Single-shell tank retrieval program mission analysis report

    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).

  9. Signal processing and statistical analysis of spaced-based measurements

    Iranpour, K.

    1996-05-01

    The reports deals with data obtained by the ROSE rocket project. This project was designed to investigate the low altitude auroral instabilities in the electrojet region. The spectral and statistical analyses indicate the existence of unstable waves in the ionized gas in the region. An experimentally obtained dispersion relation for these waves were established. It was demonstrated that the characteristic phase velocities are much lower than what is expected from the standard theoretical results. This analysis of the ROSE data indicate the cascading of energy from lower to higher frequencies. 44 refs., 54 figs

  10. Spatiotemporal Signal Analysis via the Phase Velocity Transform

    Mattor, Nathan

    2000-01-01

    The phase velocity transform (PVT) is an integral transform that divides a function of space and time into components that propagate at uniform phase velocities without distortion. This paper examines the PVT as a method to analyze spatiotemporal fluctuation data. The transform is extended to systems with discretely sampled data on a periodic domain, and applied to data from eight azimuthally distributed probes on the Sustained Spheromak Physics Experiment (SSPX). This reveals features not shown by Fourier analysis, particularly regarding nonsinusoidal mode structure. (c) 2000 The American Physical Society

  11. A Bayesian analysis of pentaquark signals from CLAS data

    David Ireland; Bryan McKinnon; Dan Protopopescu; Pawel Ambrozewicz; Marco Anghinolfi; G. Asryan; Harutyun Avakian; H. Bagdasaryan; Nathan Baillie; Jacques Ball; Nathan Baltzell; V. Batourine; Marco Battaglieri; Ivan Bedlinski; Ivan Bedlinskiy; Matthew Bellis; Nawal Benmouna; Barry Berman; Angela Biselli; Lukasz Blaszczyk; Sylvain Bouchigny; Sergey Boyarinov; Robert Bradford; Derek Branford; William Briscoe; William Brooks; Volker Burkert; Cornel Butuceanu; John Calarco; Sharon Careccia; Daniel Carman; Liam Casey; Shifeng Chen; Lu Cheng; Philip Cole; Patrick Collins; Philip Coltharp; Donald Crabb; Volker Crede; Natalya Dashyan; Rita De Masi; Raffaella De Vita; Enzo De Sanctis; Pavel Degtiarenko; Alexandre Deur; Richard Dickson; Chaden Djalali; Gail Dodge; Joseph Donnelly; David Doughty; Michael Dugger; Oleksandr Dzyubak; Hovanes Egiyan; Kim Egiyan; Lamiaa Elfassi; Latifa Elouadrhiri; Paul Eugenio; Gleb Fedotov; Gerald Feldman; Ahmed Fradi; Herbert Funsten; Michel Garcon; Gagik Gavalian; Nerses Gevorgyan; Gerard Gilfoyle; Kevin Giovanetti; Francois-Xavier Girod; John Goetz; Wesley Gohn; Atilla Gonenc; Ralf Gothe; Keith Griffioen; Michel Guidal; Nevzat Guler; Lei Guo; Vardan Gyurjyan; Kawtar Hafidi; Hayk Hakobyan; Charles Hanretty; Neil Hassall; F. Hersman; Ishaq Hleiqawi; Maurik Holtrop; Charles Hyde; Yordanka Ilieva; Boris Ishkhanov; Eugeny Isupov; D. Jenkins; Hyon-Suk Jo; John Johnstone; Kyungseon Joo; Henry Juengst; Narbe Kalantarians; James Kellie; Mahbubul Khandaker; Wooyoung Kim; Andreas Klein; Franz Klein; Mikhail Kossov; Zebulun Krahn; Laird Kramer; Valery Kubarovsky; Joachim Kuhn; Sergey Kuleshov; Viacheslav Kuznetsov; Jeff Lachniet; Jean Laget; Jorn Langheinrich; D. Lawrence; Kenneth Livingston; Haiyun Lu; Marion MacCormick; Nikolai Markov; Paul Mattione; Bernhard Mecking; Mac Mestayer; Curtis Meyer; Tsutomu Mibe; Konstantin Mikhaylov; Marco Mirazita; Rory Miskimen; Viktor Mokeev; Brahim Moreno; Kei Moriya; Steven Morrow; Maryam Moteabbed; Edwin Munevar Espitia; Gordon Mutchler; Pawel Nadel-Turonski; Rakhsha Nasseripour; Silvia Niccolai; Gabriel Niculescu; Maria-Ioana Niculescu; Bogdan Niczyporuk; Megh Niroula; Rustam Niyazov; Mina Nozar; Mikhail Osipenko; Alexander Ostrovidov; Kijun Park; Evgueni Pasyuk; Craig Paterson; Sergio Pereira; Joshua Pierce; Nikolay Pivnyuk; Oleg Pogorelko; Sergey Pozdnyakov; John Price; Sebastien Procureur; Yelena Prok; Brian Raue; Giovanni Ricco; Marco Ripani; Barry Ritchie; Federico Ronchetti; Guenther Rosner; Patrizia Rossi; Franck Sabatie; Julian Salamanca; Carlos Salgado; Joseph Santoro; Vladimir Sapunenko; Reinhard Schumacher; Vladimir Serov; Youri Sharabian; Dmitri Sharov; Nikolay Shvedunov; Elton Smith; Lee Smith; Daniel Sober; Daria Sokhan; Aleksey Stavinskiy; Samuel Stepanyan; Stepan Stepanyan; Burnham Stokes; Paul Stoler; Steffen Strauch; Mauro Taiuti; David Tedeschi; Ulrike Thoma; Avtandil Tkabladze; Svyatoslav Tkachenko; Clarisse Tur; Maurizio Ungaro; Michael Vineyard; Alexander Vlassov; Daniel Watts; Lawrence Weinstein; Dennis Weygand; M. Williams; Elliott Wolin; M.H. Wood; Amrit Yegneswaran; Lorenzo Zana; Jixie Zhang; Bo Zhao; Zhiwen Zhao

    2008-02-01

    We examine the results of two measurements by the CLAS collaboration, one of which claimed evidence for a $\\Theta^{+}$ pentaquark, whilst the other found no such evidence. The unique feature of these two experiments was that they were performed with the same experimental setup. Using a Bayesian analysis we find that the results of the two experiments are in fact compatible with each other, but that the first measurement did not contain sufficient information to determine unambiguously the existence of a $\\Theta^{+}$. Further, we suggest a means by which the existence of a new candidate particle can be tested in a rigorous manner.

  12. A Bayesian analysis of pentaquark signals from CLAS data

    David Ireland; Bryan McKinnon; Dan Protopopescu; Pawel Ambrozewicz; Marco Anghinolfi; G. Asryan; Harutyun Avakian; H. Bagdasaryan; Nathan Baillie; Jacques Ball; Nathan Baltzell; V. Batourine; Marco Battaglieri; Ivan Bedlinski; Ivan Bedlinskiy; Matthew Bellis; Nawal Benmouna; Barry Berman; Angela Biselli; Lukasz Blaszczyk; Sylvain Bouchigny; Sergey Boyarinov; Robert Bradford; Derek Branford; William Briscoe; William Brooks; Volker Burkert; Cornel Butuceanu; John Calarco; Sharon Careccia; Daniel Carman; Liam Casey; Shifeng Chen; Lu Cheng; Philip Cole; Patrick Collins; Philip Coltharp; Donald Crabb; Volker Crede; Natalya Dashyan; Rita De Masi; Raffaella De Vita; Enzo De Sanctis; Pavel Degtiarenko; Alexandre Deur; Richard Dickson; Chaden Djalali; Gail Dodge; Joseph Donnelly; David Doughty; Michael Dugger; Oleksandr Dzyubak; Hovanes Egiyan; Kim Egiyan; Lamiaa Elfassi; Latifa Elouadrhiri; Paul Eugenio; Gleb Fedotov; Gerald Feldman; Ahmed Fradi; Herbert Funsten; Michel Garcon; Gagik Gavalian; Nerses Gevorgyan; Gerard Gilfoyle; Kevin Giovanetti; Francois-Xavier Girod; John Goetz; Wesley Gohn; Atilla Gonenc; Ralf Gothe; Keith Griffioen; Michel Guidal; Nevzat Guler; Lei Guo; Vardan Gyurjyan; Kawtar Hafidi; Hayk Hakobyan; Charles Hanretty; Neil Hassall; F. Hersman; Ishaq Hleiqawi; Maurik Holtrop; Charles Hyde; Yordanka Ilieva; Boris Ishkhanov; Eugeny Isupov; D. Jenkins; Hyon-Suk Jo; John Johnstone; Kyungseon Joo; Henry Juengst; Narbe Kalantarians; James Kellie; Mahbubul Khandaker; et al

    2007-01-01

    We examine the results of two measurements by the CLAS collaboration, one of which claimed evidence for a Θ + pentaquark, whilst the other found no such evidence. The unique feature of these two experiments was that they were performed with the same experimental setup. Using a Bayesian analysis we find that the results of the two experiments are in fact compatible with each other, but that the first measurement did not contain sufficient information to determine unambiguously the existence of a Θ + . Further, we suggest a means by which the existence of a new candidate particle can be tested in a rigorous manner

  13. Technical Analysis Program / Flight Standards Automation System -

    Department of Transportation — 1-TAP is a national data quality application 2-Logbook is field office tracking and suspense program for investigation tracking and certification tracking 3-Numerous...

  14. An Analysis of Naval Officer Accession Programs

    Lehner, William D

    2008-01-01

    This thesis conducts an extensive literature review of prior studies on the three major commissioning programs for United States naval officers the United States Naval Academy, Naval Reserve Officers...

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

    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.

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

    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

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

    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

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

    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.

  19. A Novel Medical E-Nose Signal Analysis System

    Lu Kou

    2017-04-01

    Full Text Available It has been proven that certain biomarkers in people’s breath have a relationship with diseases and blood glucose levels (BGLs. As a result, it is possible to detect diseases and predict BGLs by analysis of breath samples captured by e-noses. In this paper, a novel optimized medical e-nose system specified for disease diagnosis and BGL prediction is proposed. A large-scale breath dataset has been collected using the proposed system. Experiments have been organized on the collected dataset and the experimental results have shown that the proposed system can well solve the problems of existing systems. The methods have effectively improved the classification accuracy.

  20. Analysis and modelization of short-duration windows of seismic signals

    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

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

    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.

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

    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.

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

    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…

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

    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.

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

    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...

  6. Signal Network Analysis of Plant Genes Responding to Ionizing Radiation

    Kim, Dong Sub; Kim, Jinbaek; Kim, Sang Hoon

    2012-12-01

    In this project, we irradiated Arabidopsis plants with various doses of gamma-rays at the vegetative and reproductive stages to assess their radiation sensitivity. After the gene expression profiles and an analysis of the antioxidant response, we selected several Arabidopsis genes for uses of 'Radio marker genes (RMG)' and conducted over-expression and knock-down experiments to confirm the radio sensitivity. Based on these results, we applied two patents for the detection of two RMG (At3g28210 and At4g37990) and development of transgenic plants. Also, we developed a Genechip for use of high-throughput screening of Arabidopsis genes responding only to ionizing radiation and identified RMG to detect radiation leaks. Based on these results, we applied two patents associated with the use of Genechip for different types of radiation and different growth stages. Also, we conducted co-expression network study of specific expressed probes against gamma-ray stress and identified expressed patterns of duplicated genes formed by whole/500kb segmental genome duplication

  7. Analysis of optical bleaching of OSL signal in sediment quartz

    Przegiętka, K.R.; Chruścińska, A.

    2013-01-01

    The aim of this work was to study the effect of the quality of optical bleaching on the results of OSL (Optically Stimulated Luminescence) dating method. The large aliquots of coarse quartz grains extracted from fluvial deposit were used in the study. The poor, medium and good bleaching were simulated in laboratory with help of Blue LED light source in series of experiments. Then the samples were irradiated with a common laboratory dose. The equivalent doses (DE) were measured by the help of standard Single Aliquot Regeneration (SAR) technique, but obtained DE distributions are analyzed in a new way. The method for recognizing and compensating for partial bleaching is proposed. The conclusions for dating sediment quartz samples are presented and discussed. -- Highlights: ► Bleaching experiments on sediment quartz are performed. ► Blue LED light source incorporated in luminescence reader is used. ► New analysis of data measured by standard SAR OSL technique is proposed. ► The results are promising for recognizing and compensating for partial bleaching

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

    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)

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

    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...

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

    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.

  11. Energy analysis program. 1994 annual report

    Levine, M.D.

    1995-04-01

    This report provides an energy analysis overview. The following topics are described: building energy analysis; urban and energy environmental issues; appliance energy efficiency standards; utility planning and policy; energy efficiency, economics, and policy issues; and international energy and environmental issues.

  12. Analysis of metastasis associated signal regulatory network in colorectal cancer.

    Qi, Lu; Ding, Yanqing

    2018-06-18

    Metastasis is a key factor that affects the survival and prognosis of colorectal cancer patients. To elucidate molecular mechanism associated with the metastasis of colorectal cancer, genes related to the metastasis time of colorectal cancer were screened. Then, a network was constructed with this genes. Data was obtained from colorectal cancer expression profile. Molecular mechanism elucidated the time of tumor metastasis and the expression of genes related to colorectal cancer. We found that metastasis-promoting and metastasis-inhibiting networks included protein hubs of high connectivity. These protein hubs were components of organelles. Some ribosomal proteins promoted the metastasis of colorectal cancer. In some components of organelles, such as proteasomes, mitochondrial ribosome, ATP synthase, and splicing factors, the metastasis of colorectal cancer was inhibited by some sections of these organelles. After performing survival analysis of proteins in organelles, joint survival curve of proteins was constructed in ribosomal network. This joint survival curve showed metastasis was promoted in patients with colorectal cancer (P = 0.0022939). Joint survival curve of proteins was plotted against proteasomes (P = 7 e-07), mitochondrial ribosome (P = 0.0001157), ATP synthase (P = 0.0001936), and splicing factors (P = 1.35e-05). These curves indicate that metastasis of colorectal cancer can be inhibited. After analyzing proteins that bind with organelle components, we also found that some proteins were associated with the time of colorectal cancer metastasis. Hence, different cellular components play different roles in the metastasis of colorectal cancer. Copyright © 2018 Elsevier Inc. All rights reserved.

  13. Effective Analysis of C Programs by Rewriting Variability

    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...

  14. Sensor signal analysis by neural networks for surveillance in nuclear reactors

    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

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

    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.

  16. Programming effort analysis of the ELLPACK language

    Rice, J. R.

    1978-01-01

    ELLPACK is a problem statement language and system for elliptic partial differential equations which is implemented by a FORTRAN preprocessor. ELLPACK's principal purpose is as a tool for the performance evaluation of software. However, it is used here as an example with which to study the programming effort required for problem solving. It is obvious that problem statement languages can reduce programming effort tremendously; the goal is to quantify this somewhat. This is done by analyzing the lengths and effort (as measured by Halstead's software science technique) of various approaches to solving these problems.

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

    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.

  18. TRU Waste Management Program. Cost/schedule optimization analysis

    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

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

    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.

  20. Signals structural analysis and processing: application to acoustic signals recorded during sodium boiling in a nuclear reactor

    Rodriguez, J.

    1986-02-01

    An acoustic system that uses examples to learn the structure of specific signals linked to a corresponding class of physical phenomena, and classify an unknown signal (possibly with noise present) into one of the learned classes is presented. The first stage consists of smoothing the data. The signal is represented as a trace according to background and event. To learn the structures in each class, smoothed, segmented signals are used. For classification, three operations to modify the signal so that it perfectly verifies the model description are available [fr

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

    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.

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

    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.

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

    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.

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

    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...

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

    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.

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

    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)

  7. Digital signal processing for the Johnson noise thermometry: a time series analysis of the Johnson noise

    Moon, Byung Soo; Hwang, In Koo; Chung, Chong Eun; Kwon, Kee Choon; David, E. H.; Kisner, R.A.

    2004-06-01

    In this report, we first proved that a random signal obtained by taking the sum of a set of signal frequency signals generates a continuous Markov process. We used this random signal to simulate the Johnson noise and verified that the Johnson noise thermometry can be used to improve the measurements of the reactor coolant temperature within an accuracy of below 0.14%. Secondly, by using this random signal we determined the optimal sampling rate when the frequency band of the Johnson noise signal is given. Also the results of our examination on how good the linearity of the Johnson noise is and how large the relative error of the temperature could become when the temperature increases are described. Thirdly, the results of our analysis on a set of the Johnson noise signal blocks taken from a simple electric circuit are described. We showed that the properties of the continuous Markov process are satisfied even when some channel noises are present. Finally, we describe the algorithm we devised to handle the problem of the time lag in the long-term average or the moving average in a transient state. The algorithm is based on the Haar wavelet and is to estimate the transient temperature that has much smaller time delay. We have shown that the algorithm can track the transient temperature successfully

  8. Automated Program Analysis for Cybersecurity (APAC)

    2016-07-14

    report is the result of contracted fundamental research deemed exempt from public affairs security and policy review in accordance with SAF/AQR memorandum...contracted fundamental research deemed exempt from public affairs security and policy review in accordance with SAF/AQR memorandum dated 10 Dec 08 and...program was to measure the effectiveness and efficiency of the R&D teams in detecting malware in Android applications. In order to achieve this goal

  9. Space Station Program threat and vulnerability analysis

    Van Meter, Steven D.; Veatch, John D.

    1987-01-01

    An examination has been made of the physical security of the Space Station Program at the Kennedy Space Center in a peacetime environment, in order to furnish facility personnel with threat/vulnerability information. A risk-management approach is used to prioritize threat-target combinations that are characterized in terms of 'insiders' and 'outsiders'. Potential targets were identified and analyzed with a view to their attractiveness to an adversary, as well as to the consequentiality of the resulting damage.

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

    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.

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

    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).

  12. Analysis of interference of QPSK and QDPSK modulation signals by mathematical

    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.

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

    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.

  14. Analysis of radiometric signal in sedimentating suspension flow in open channel

    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.

  15. Vital analysis: annotating sensed physiological signals with the stress levels of first responders in action.

    Gomes, P; Kaiseler, M; Queirós, C; Oliveira, M; Lopes, B; Coimbra, M

    2012-01-01

    First responders such as firefighters are exposed to extreme stress and fatigue situations during their work routines. It is thus desirable to monitor their health using wearable sensing but this is a complex and still unsolved research challenge that requires large amounts of properly annotated physiological signals data. In this paper we show that the information gathered by our Vital Analysis Framework can support the annotation of these vital signals with the stress levels perceived by the target user, confirmed by the analysis of more than 4600 hours of data collected from real firefighters in action, including 717 answers to event questionnaires from a total of 454 different events.

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

    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...

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

    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.

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

    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.

  19. VEGF-A isoforms program differential VEGFR2 signal transduction, trafficking and proteolysis

    Gareth W. Fearnley

    2016-05-01

    Full Text Available Vascular endothelial growth factor A (VEGF-A binding to the receptor tyrosine kinase VEGFR2 triggers multiple signal transduction pathways, which regulate endothelial cell responses that control vascular development. Multiple isoforms of VEGF-A can elicit differential signal transduction and endothelial responses. However, it is unclear how such cellular responses are controlled by isoform-specific VEGF-A–VEGFR2 complexes. Increasingly, there is the realization that the membrane trafficking of receptor–ligand complexes influences signal transduction and protein turnover. By building on these concepts, our study shows for the first time that three different VEGF-A isoforms (VEGF-A165, VEGF-A121 and VEGF-A145 promote distinct patterns of VEGFR2 endocytosis for delivery into early endosomes. This differential VEGFR2 endocytosis and trafficking is linked to VEGF-A isoform-specific signal transduction events. Disruption of clathrin-dependent endocytosis blocked VEGF-A isoform-specific VEGFR2 activation, signal transduction and caused substantial depletion in membrane-bound VEGFR1 and VEGFR2 levels. Furthermore, such VEGF-A isoforms promoted differential patterns of VEGFR2 ubiquitylation, proteolysis and terminal degradation. Our study now provides novel insights into how different VEGF-A isoforms can bind the same receptor tyrosine kinase and elicit diverse cellular outcomes.

  20. VEGF-A isoforms program differential VEGFR2 signal transduction, trafficking and proteolysis.

    Fearnley, Gareth W; Smith, Gina A; Abdul-Zani, Izma; Yuldasheva, Nadira; Mughal, Nadeem A; Homer-Vanniasinkam, Shervanthi; Kearney, Mark T; Zachary, Ian C; Tomlinson, Darren C; Harrison, Michael A; Wheatcroft, Stephen B; Ponnambalam, Sreenivasan

    2016-05-15

    Vascular endothelial growth factor A (VEGF-A) binding to the receptor tyrosine kinase VEGFR2 triggers multiple signal transduction pathways, which regulate endothelial cell responses that control vascular development. Multiple isoforms of VEGF-A can elicit differential signal transduction and endothelial responses. However, it is unclear how such cellular responses are controlled by isoform-specific VEGF-A-VEGFR2 complexes. Increasingly, there is the realization that the membrane trafficking of receptor-ligand complexes influences signal transduction and protein turnover. By building on these concepts, our study shows for the first time that three different VEGF-A isoforms (VEGF-A165, VEGF-A121 and VEGF-A145) promote distinct patterns of VEGFR2 endocytosis for delivery into early endosomes. This differential VEGFR2 endocytosis and trafficking is linked to VEGF-A isoform-specific signal transduction events. Disruption of clathrin-dependent endocytosis blocked VEGF-A isoform-specific VEGFR2 activation, signal transduction and caused substantial depletion in membrane-bound VEGFR1 and VEGFR2 levels. Furthermore, such VEGF-A isoforms promoted differential patterns of VEGFR2 ubiquitylation, proteolysis and terminal degradation. Our study now provides novel insights into how different VEGF-A isoforms can bind the same receptor tyrosine kinase and elicit diverse cellular outcomes. © 2016. Published by The Company of Biologists Ltd.

  1. Pointer Analysis for JavaScript Programming Tools

    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...

  2. Geal: A general program for the analysis of alpha spectra

    Garcia-Torano, E.; Acena Barrenechea, M.L.

    1978-01-01

    A computing program for analysis and representation of alpha spectra obtained with surface barrier detectors is described. Several methods for fitting spectra are studied. A monoenergetic line or a doublet previously fitted has been used as a standard for the analyses of all kind of spectra. Some examples of application as well as a list of the program are shown. The program has been written in Fortran V language. (author)

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

    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.

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

    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)

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

    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.

  6. 2011 Biomass Program Platform Peer Review: Analysis

    Haq, Zia [Office of Energy Efficiency and Renewable Energy (EERE), Washington, DC (United States)

    2012-02-01

    This document summarizes the recommendations and evaluations provided by an independent external panel of experts at the 2011 U.S. Department of Energy Biomass Program’s Analysis Platform Review meeting.

  7. A method of signal transmission path analysis for multivariate random processes

    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)

  8. Design and analysis of environmental monitoring programs

    Lophaven, Søren Nymand

    2005-01-01

    This thesis describes statistical methods for modelling space-time phenomena. The methods were applied to data from the Danish marine monitoring program in the Kattegat, measured in the five-year period 1993-1997. The proposed model approaches are characterised as relatively simple methods, which...... into account. Thus, it serves as a compromise between existing methods. The space-time model approaches and geostatistical design methods used in this thesis are generally applicable, i.e. with minor modifications they could equally well be applied within areas such as soil and air pollution. In Danish: Denne...

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

    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

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

    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.

  11. MULGRES: a computer program for stepwise multiple regression analysis

    A. Jeff Martin

    1971-01-01

    MULGRES is a computer program source deck that is designed for multiple regression analysis employing the technique of stepwise deletion in the search for most significant variables. The features of the program, along with inputs and outputs, are briefly described, with a note on machine compatibility.

  12. HAMOC: a computer program for fluid hammer analysis

    Johnson, H.G.

    1975-12-01

    A computer program has been developed for fluid hammer analysis of piping systems attached to a vessel which has undergone a known rapid pressure transient. The program is based on the characteristics method for solution of the partial differential equations of motion and continuity. Column separation logic is included for situations in which pressures fall to saturation values

  13. FY2015 Analysis of the Teamwork USA Program. Memorandum

    Howard, Mark

    2015-01-01

    The Department of Research and Evaluation (DRE) has completed an analysis of the performance of students who participated in the Teamwork USA Program, administered in FY2014 at three District schools. Teamwork USA hopes to improve student achievement at select Title I elementary schools via its Instrumental Music Program grant. This memorandum to…

  14. Statistical analysis of the BOIL program in RSYST-III

    Beck, W.; Hausch, H.J.

    1978-11-01

    The paper describes a statistical analysis in the RSYST-III program system. Using the example of the BOIL program, it is shown how the effects of inaccurate input data on the output data can be discovered. The existing possibilities of data generation, data handling, and data evaluation are outlined. (orig.) [de

  15. A Computer Program for Short Circuit Analysis of Electric Power ...

    The Short Circuit Analysis Program (SCAP) is to be used to assess the composite effects of unbalanced and balanced faults on the overall reliability of electric power system. The program uses the symmetrical components method to compute all phase and sequence quantities for any bus or branch of a given power network ...

  16. Integrated program of using of Probabilistic Safety Analysis in Spain

    1998-01-01

    Since 25 June 1986, when the CSN (Nuclear Safety Conseil) approve the Integrated Program of Probabilistic Safety Analysis, this program has articulated the main activities of CSN. This document summarize the activities developed during these years and reviews the Integrated programme

  17. 7 CFR 1700.32 - Program Accounting and Regulatory Analysis.

    2010-01-01

    ... Administrator with respect to management, information systems, budgets, and other such matters. (a) The... 7 Agriculture 11 2010-01-01 2010-01-01 false Program Accounting and Regulatory Analysis. 1700.32... SERVICE, DEPARTMENT OF AGRICULTURE GENERAL INFORMATION Agency Organization and Functions § 1700.32 Program...

  18. Signaling mechanisms of apoptosis-like programmed cell death in unicellular eukaryotes.

    Shemarova, Irina V

    2010-04-01

    In unicellular eukaryotes, apoptosis-like cell death occurs during development, aging and reproduction, and can be induced by environmental stresses and exposure to toxic agents. The essence of the apoptotic machinery in unicellular organisms is similar to that in mammals, but the apoptotic signal network is less complex and of more ancient origin. The review summarizes current data about key apoptotic proteins and mechanisms of the transduction of apoptotic signals by caspase-like proteases and mitochondrial apoptogenic proteins in unicellular eukaryotes. The roles of receptor-dependent and receptor-independent caspase cascades are reviewed. 2010 Elsevier Inc. All rights reserved.

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

    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

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

    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.

  1. Upper Midwest Gap Analysis Program, Image Processing Protocol

    Lillesand, Thomas

    1998-01-01

    This document presents a series of technical guidelines by which land cover information is being extracted from Landsat Thematic Mapper data as part of the Upper Midwest Gap Analysis Program (UMGAP...

  2. An economic analysis methodology for project evaluation and programming.

    2013-08-01

    Economic analysis is a critical component of a comprehensive project or program evaluation methodology that considers all key : quantitative and qualitative impacts of highway investments. It allows highway agencies to identify, quantify, and value t...

  3. Generalized Aliasing as a Basis for Program Analysis Tools

    O'Callahan, Robert

    2000-01-01

    .... This dissertation describes the design of a system, Ajax, that addresses this problem by using semantics-based program analysis as the basis for a number of different tools to aid Java programmers...

  4. Analysis of Defense Industry Consolidation Effects on Program Acquisition Costs

    Hoff, Russell V

    2007-01-01

    .... This thesis examines whether cost changes are evident following consolidation within the defense industry by conducting a regression analysis of Major Defense Acquisition Programs across 13 broad defense market sectors...

  5. Analysis and Implement of Broadcast Program Monitoring Data

    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.

  6. Vulnerability and Risk Analysis Program: Overview of Assessment Methodology

    2001-01-01

    .... Over the last three years, a team of national laboratory experts, working in partnership with the energy industry, has successfully applied the methodology as part of OCIP's Vulnerability and Risk Analysis Program (VRAP...

  7. Time Aquatic Resources Modeling and Analysis Program (STARMAP)

    Federal Laboratory Consortium — Colorado State University has received funding from the U.S. Environmental Protection Agency (EPA) for its Space-Time Aquatic Resources Modeling and Analysis Program...

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

    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

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

    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.

  10. Generalized sample entropy analysis for traffic signals based on similarity measure

    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.

  11. A fast circuit analysis program based on microcomputer

    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

  12. A program for Warren-Averbach analysis of diffraction data

    Fan, Zhijian; Chen, Bo; Chen, Xiping

    2009-04-01

    X-ray or neutron diffraction experiment can provide microstructural information of crystalline materials. At the moment without the model of micro-structure, Warren-Averbach analysis is regarded as an important tool. For this purpose, a program of Warren-Averbach analysis has been developed. The pro- gram has nearly all basic functions, it can be conveniently used through a graphic user interface as well. In the end, the efficiency of the program is illustrated by an example of ceria. (authors)

  13. Cost-benefit analysis of FBR program

    Suzuki, S [Japan Energy Economic Research Inst., Tokyo

    1975-07-01

    In several countries of the world, both financial and human resources are being invested to the development of fast breeder reactors. Quantitative determination of the benefit which will be expected as the reqard to these efforts of research and development - this is the purpose of the present study. It is cost-benefit analysis. The instances of this analysis are given, namely the work in The Institute of Energy Economics in Japan, and also the one by U.S.AEC. The effect of the development of fast breeder reactors is evaluated in this way ; and problems in the analysis method are indicated. These two works in Japan and the U.S. were performed before the so-called oil crisis.

  14. Cost-benefit analysis of FBR program

    Suzuki, Shinji

    1975-01-01

    In several countries of the world, both financial and human resources are being invested to the development of fast breeder reactors. Quantitative determination of the benefit which will be expected as the reqard to these efforts of research and development - this is the purpose of the present study. It is cost-benefit analysis. The instances of this analysis are given, namely the work in The Institute of Energy Economics in Japan, and also the one by U.S.AEC. The effect of the development of fast breeder reactors is evaluated in this way ; and problems in the analysis method are indicated. These two works in Japan and the U.S. were performed before the so-called oil crisis. (Mori, K.)

  15. Cyclic programmed cell death stimulates hormone signaling and root development in Arabidopsis

    Xuan, Wei; Band, Leah R.; Kumpf, Robert P.; Rybel, De Bert

    2016-01-01

    The plant root cap, surrounding the very tip of the growing root, perceives and transmits environmental signals to the inner root tissues. In Arabidopsis thaliana, auxin released by the root cap contributes to the regular spacing of lateral organs along the primary root axis. Here, we show that

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

    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

  17. Milton Hydro's Energy Drill Program : demand response based on behavioural responses to price signals

    Thorne, D.; Heeney, D.

    2006-01-01

    The Energy Drill Program is a demand response tool and economic instrument based on a fire drill protocol. The aim of the program is to reduce peak demand and emissions and improve system reliability and price volatility. This presentation provided details of an Energy Drill pilot program, conducted in Milton, Ontario. Customized approaches were used in the buildings partaking in the drill, which included the Milton Hydro Headquarters, the Robert Baldwin Public School, and a leisure centre. Building assessments inventoried building systems and equipment usage patterns. Pilot monitoring and evaluation was conducted through the use of checklists completed by marshals and building coordinators. Energy use data was tracked by Milton Hydro, and report cards were sent after each drill. A short-term drop in demand was observed in all the buildings, as well as overall reductions in peak period demand. Energy consumption data for all the buildings were provided. Results of the pilot program suggested that rotating the drills among participating buildings may prove to be a more effective strategy for the program to adopt in future. A greater emphasis on energy efficiency was also recommended. It was concluded that the eventual roll-out strategy should carefully consider the number and types of buildings involved in the program; internal commitment to the program; available resources; and timing for implementation. refs., tabs., figs

  18. Aspects with Program Analysis for Security Policies

    Yang, Fan

    Enforcing security policies to IT systems, especially for a mobile distributed system, is challenging. As society becomes more IT-savvy, our expectations about security and privacy evolve. This is usually followed by changes in regulation in the form of standards and legislation. In many cases......, small modification of the security requirement might lead to substantial changes in a number of modules within a large mobile distributed system. Indeed, security is a crosscutting concern which can spread to many business modules within a system, and is difficult to be integrated in a modular way....... This dissertation explores the principles of adding challenging security policies to existing systems with great flexibility and modularity. The policies concerned cover both classical access control and explicit information flow policies. We built our solution by combining aspect-oriented programming techniques...

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

    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

  20. Simultaneous hit finding and timing method for pulse shape analysis of drift chamber signals

    Schaile, D; Schaile, O; Schwarz, J

    1986-01-01

    An algorithm for the analysis of the digitized signal waveform of drift chamber pulses is described which yields a good multihit resolution and an accurate drift time determination with little processing time. The method has been tested and evaluated with measured pulse shapes from the full size prototype of the OPAL central detector which were digitized by 100 MHz FADCs. (orig.).

  1. Simultaneous hit finding and timing method for pulse shape analysis of drift chamber signals

    Schaile, D; Schaile, O; Schwarz, J

    1986-01-01

    An algorithm for the analysis of the digitized signal waveform of drift chamber pulses is described which yields a good multihit resolution and an accurate drift time determination with little processing time. The method has been tested and evaluated with measured pulse shapes from the full size prototype of the OPAL central detector which were digitized by 100 MHz FADCs.

  2. Analysis performed in cooperation with the SALE program, (1)

    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)

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

    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

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

    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

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

    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

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

    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)

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

    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.

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

    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.

  9. Validation of the TEXSAN thermal-hydraulic analysis program

    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

  10. Experience with a PC-based system for noise and DC signal analysis in PWRs

    Hashemian, H.M.

    1996-01-01

    A data acquisition system that was originally developed for noise diagnostics in PWRs was expanded to include DC signal analysis in addition to noise analysis. The system has been used in PWRs for reactor diagnostics, determination of root cause of process anomalies, instrument calibration verification, measurement of drop time of control and shutdown rods, testing of timing and sequencing of control rod drive mechanisms, emergency diesel generator monitoring, etc. These applications are reviewed in this paper. (author)

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

    Bruggeman, Quentin; Mazubert, Christelle; Prunier, Florence; Lugan, Raphael; Chan, Kai Xun; Phua, Su Yin; Pogson, Barry J.; Krieger-Liszkay, Anja; Delarue, Marianne; Benhamed, Moussa; Bergounioux, Catherine; Raynaud, Cé cile

    2016-01-01

    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

  12. Residual energy applications program systems analysis report

    Yngve, P.W.

    1980-10-01

    Current DOE plans call for building an Energy Applied Systems Test (EAST) Facility at the Savannah River Plant in close proximity to the 140 to 150/sup 0/F waste heat from one of several operating nuclear reactors. The waste water flow from each reactor, approximately 165,000 gpm, provides a unique opportunity to test the performance and operating characteristics of large-scale waste heat power generation and heat pump system concepts. This report provides a preliminary description of the potential end-use market, parametric data on heat pump and the power generation system technology, a preliminary listing of EAST Facility requirements, and an example of an integrated industrial park utilizing the technology to maximize economic pay back. The parametric heat pump analysis concluded that dual-fluid Rankine cycle heat pumps with capacities as high as 400 x 10/sup 6/ Btu/h, can utilize large sources of low temperature residual heat to provide 300/sup 0/F saturatd steam for an industrial park. The before tax return on investment for this concept is 36.2%. The analysis also concluded that smaller modular heat pumps could fulfill the same objective while sacrificing only a moderate rate of return. The parametric power generation analysis concluded that multi-pressure Rankine cycle systems not only are superior to single pressure systems, but can also be developed for large systems (approx. = 17 MW/sub e/). This same technology is applicable to smaller systems at the sacrifice of higher investment per unit output.

  13. The role of radiation damage analysis in the fusion program

    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.)

  14. Reconstruction of cellular signal transduction networks using perturbation assays and linear programming.

    Knapp, Bettina; Kaderali, Lars

    2013-01-01

    Perturbation experiments for example using RNA interference (RNAi) offer an attractive way to elucidate gene function in a high throughput fashion. The placement of hit genes in their functional context and the inference of underlying networks from such data, however, are challenging tasks. One of the problems in network inference is the exponential number of possible network topologies for a given number of genes. Here, we introduce a novel mathematical approach to address this question. We formulate network inference as a linear optimization problem, which can be solved efficiently even for large-scale systems. We use simulated data to evaluate our approach, and show improved performance in particular on larger networks over state-of-the art methods. We achieve increased sensitivity and specificity, as well as a significant reduction in computing time. Furthermore, we show superior performance on noisy data. We then apply our approach to study the intracellular signaling of human primary nave CD4(+) T-cells, as well as ErbB signaling in trastuzumab resistant breast cancer cells. In both cases, our approach recovers known interactions and points to additional relevant processes. In ErbB signaling, our results predict an important role of negative and positive feedback in controlling the cell cycle progression.

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

    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.

  16. Analysis of vocal signal in its amplitude - time representation. speech synthesis-by-rules

    Rodet, Xavier

    1977-01-01

    In the first part of this dissertation, the natural speech production and the resulting acoustic waveform are examined under various aspects: communication, phonetics, frequency and temporal analysis. Our own study of direct signal is compared to other researches in these different fields, and fundamental features of vocal signals are described. The second part deals with the numerous methods already used for automatic text-to-speech synthesis. In the last part, we expose the new speech synthesis-by-rule methods that we have worked out, and we present in details the structure of the real-time speech synthesiser that we have implemented on a mini-computer. (author) [fr

  17. Detection of non-stationary leak signals at NPP primary circuit by cross-correlation analysis

    Shimanskij, S.B.

    2007-01-01

    A leak-detection system employing high-temperature microphones has been developed for the RBMK and ATR (Japan) reactors. Further improvement of the system focused on using cross-correlation analysis of the spectral components of the signal to detect a small leak at an early stage of development. Since envelope processes are less affected by distortions than are wave processes, they give a higher-degree of correlation and can be used to detect leaks with lower signal-noise ratios. Many simulation tests performed at nuclear power plants have shown that the proposed methods can be used to detect and find the location of a small leak [ru

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

    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 ...

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

    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.

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

    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.

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

    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

  2. 1-D Wavelet Signal Analysis of the Actuators Nonlinearities Impact on the Healthy Control Systems Performance

    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.

  3. Development of educational program for neutron activation analysis

    Chung, Yong Sam; Moon, Jong Hwa; Kim, Sun Ha; Ryel, Sung; Kang, Young Hwan; Lee, Kil Yong; Yeon, Yeon Yel; Cho, Seung Yeon

    2000-08-01

    This technical report is developed to apply an educational and training program for graduate student and analyst utilizing neutron activation analysis. The contents of guide book consists of five parts as follows; introduction, gamma-ray spectrometry and measurement statistics, its applications, to understand of comprehensive methodology and to utilize a relevant knowledge and information on neutron activation analysis

  4. Planning, Conducting, and Documenting Data Analysis for Program Improvement

    Winer, Abby; Taylor, Cornelia; Derrington, Taletha; Lucas, Anne

    2015-01-01

    This 2015 document was developed to help technical assistance (TA) providers and state staff define and limit the scope of data analysis for program improvement efforts, including the State Systemic Improvement Plan (SSIP); develop a plan for data analysis; document alternative hypotheses and additional analyses as they are generated; and…

  5. Development of educational program for neutron activation analysis

    Chung, Yong Sam; Moon, Jong Hwa; Kim, Sun Ha; Ryel, Sung; Kang, Young Hwan; Lee, Kil Yong; Yeon, Yeon Yel; Cho, Seung Yeon

    2000-08-01

    This technical report is developed to apply an educational and training program for graduate student and analyst utilizing neutron activation analysis. The contents of guide book consists of five parts as follows; introduction, gamma-ray spectrometry and measurement statistics, its applications, to understand of comprehensive methodology and to utilize a relevant knowledge and information on neutron activation analysis.

  6. Linearized Programming of Memristors for Artificial Neuro-Sensor Signal Processing.

    Yang, Changju; Kim, Hyongsuk

    2016-08-19

    A linearized programming method of memristor-based neural weights is proposed. Memristor is known as an ideal element to implement a neural synapse due to its embedded functions of analog memory and analog multiplication. Its resistance variation with a voltage input is generally a nonlinear function of time. Linearization of memristance variation about time is very important for the easiness of memristor programming. In this paper, a method utilizing an anti-serial architecture for linear programming is proposed. The anti-serial architecture is composed of two memristors with opposite polarities. It linearizes the variation of memristance due to complimentary actions of two memristors. For programming a memristor, additional memristor with opposite polarity is employed. The linearization effect of weight programming of an anti-serial architecture is investigated and memristor bridge synapse which is built with two sets of anti-serial memristor architecture is taken as an application example of the proposed method. Simulations are performed with memristors of both linear drift model and nonlinear model.

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

    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

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

    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.

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

    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.

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

    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.

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

    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

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

    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.

  13. Energy analysis program. 1995 Annual report

    Levine, M.D.

    1996-05-01

    This year the role of energy technology research and analysis supporting governmental and public interests is again being challenged at high levels of government. This situation is not unlike that of the early 1980s, when the Administration questioned the relevance of a federal commitment to applied energy research, especially for energy efficiency and renewable energy technologies. Then Congress continued to support such activities, deeming them important to the nation`s interest. Today, Congress itself is challenging many facets of the federal role in energy. The Administration is also selectively reducing its support, primarily for the pragmatic objective of reducing federal expenditures, rather than because of principles opposing a public role in energy. this report is divided into three sections: International Energy and the global environment; Energy, economics, markets, and policy; and Buildings and their environment.

  14. Blind Extraction of Chaotic Signals by Using the Fast Independent Component Analysis Algorithm

    Hong-Bin, Chen; Jiu-Chao, Feng; Yong, Fang

    2008-01-01

    We report the results of using the fast independent component analysis (FastICA) algorithm to realize blind extraction of chaotic signals. Two cases are taken into consideration: namely, the mixture is noiseless or contaminated by noise. Pre-whitening is employed to reduce the effect of noise before using the FastICA algorithm. The correlation coefficient criterion is adopted to evaluate the performance, and the success rate is defined as a new criterion to indicate the performance with respect to noise or different mixing matrices. Simulation results show that the FastICA algorithm can extract the chaotic signals effectively. The impact of noise, the length of a signal frame, the number of sources and the number of observed mixtures on the performance is investigated in detail. It is also shown that regarding a noise as an independent source is not always correct

  15. Alcoholic extraction enables EPR analysis to characterize radiation-induced cellulosic signals in spices.

    Ahn, Jae-Jun; Sanyal, Bhaskar; Akram, Kashif; Kwon, Joong-Ho

    2014-11-19

    Different spices such as turmeric, oregano, and cinnamon were γ-irradiated at 1 and 10 kGy. The electron paramagnetic resonance (EPR) spectra of the nonirradiated samples were characterized by a single central signal (g = 2.006), the intensity of which was significantly enhanced upon irradiation. The EPR spectra of the irradiated spice samples were characterized by an additional triplet signal at g = 2.006 with a hyperfine coupling constant of 3 mT, associated with the cellulose radical. EPR analysis on various sample pretreatments in the irradiated spice samples demonstrated that the spectral features of the cellulose radical varied on the basis of the pretreatment protocol. Alcoholic extraction pretreatment produced considerable improvements of the EPR signals of the irradiated spice samples relative to the conventional oven and freeze-drying techniques. The alcoholic extraction process is therefore proposed as the most suitable sample pretreatment for unambiguous detection of irradiated spices by EPR spectroscopy.

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

    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.

  17. Power spectrum analysis of the x-ray scatter signal in mammography and breast tomosynthesis projections.

    Sechopoulos, Ioannis; Bliznakova, Kristina; Fei, Baowei

    2013-10-01

    power spectrum reflected a fast drop-off with increasing spatial frequency, with a reduction of four orders of magnitude by 0.1 lp/mm. The β values for the scatter signal were 6.14 and 6.39 for the 0° and 30° projections, respectively. Although the low-frequency characteristics of scatter in mammography and breast tomosynthesis were known, a quantitative analysis of the frequency domain characteristics of this signal was needed in order to optimize previously proposed software-based x-ray scatter reduction algorithms for these imaging modalities.

  18. Analysis of cutting force signals by wavelet packet transform for surface roughness monitoring in CNC turning

    García Plaza, E.; Núñez López, P. J.

    2018-01-01

    On-line monitoring of surface finish in machining processes has proven to be a substantial advancement over traditional post-process quality control techniques by reducing inspection times and costs and by avoiding the manufacture of defective products. This study applied techniques for processing cutting force signals based on the wavelet packet transform (WPT) method for the monitoring of surface finish in computer numerical control (CNC) turning operations. The behaviour of 40 mother wavelets was analysed using three techniques: global packet analysis (G-WPT), and the application of two packet reduction criteria: maximum energy (E-WPT) and maximum entropy (SE-WPT). The optimum signal decomposition level (Lj) was determined to eliminate noise and to obtain information correlated to surface finish. The results obtained with the G-WPT method provided an in-depth analysis of cutting force signals, and frequency ranges and signal characteristics were correlated to surface finish with excellent results in the accuracy and reliability of the predictive models. The radial and tangential cutting force components at low frequency provided most of the information for the monitoring of surface finish. The E-WPT and SE-WPT packet reduction criteria substantially reduced signal processing time, but at the expense of discarding packets with relevant information, which impoverished the results. The G-WPT method was observed to be an ideal procedure for processing cutting force signals applied to the real-time monitoring of surface finish, and was estimated to be highly accurate and reliable at a low analytical-computational cost.

  19. Analysis of cross-correlations in electroencephalogram signals as an approach to proactive diagnosis of schizophrenia

    Timashev, Serge F.; Panischev, Oleg Yu.; Polyakov, Yuriy S.; Demin, Sergey A.; Kaplan, Alexander Ya.

    2012-02-01

    We apply flicker-noise spectroscopy (FNS), a time series analysis method operating on structure functions and power spectrum estimates, to study the clinical electroencephalogram (EEG) signals recorded in children/adolescents (11 to 14 years of age) with diagnosed schizophrenia-spectrum symptoms at the National Center for Psychiatric Health (NCPH) of the Russian Academy of Medical Sciences. The EEG signals for these subjects were compared with the signals for a control sample of chronically depressed children/adolescents. The purpose of the study is to look for diagnostic signs of subjects' susceptibility to schizophrenia in the FNS parameters for specific electrodes and cross-correlations between the signals simultaneously measured at different points on the scalp. Our analysis of EEG signals from scalp-mounted electrodes at locations F3 and F4, which are symmetrically positioned in the left and right frontal areas of cerebral cortex, respectively, demonstrates an essential role of frequency-phase synchronization, a phenomenon representing specific correlations between the characteristic frequencies and phases of excitations in the brain. We introduce quantitative measures of frequency-phase synchronization and systematize the values of FNS parameters for the EEG data. The comparison of our results with the medical diagnoses for 84 subjects performed at NCPH makes it possible to group the EEG signals into 4 categories corresponding to different risk levels of subjects' susceptibility to schizophrenia. We suggest that the introduced quantitative characteristics and classification of cross-correlations may be used for the diagnosis of schizophrenia at the early stages of its development.

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

    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.

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

    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.

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

    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.

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

    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.

  4. Signal analysis of acoustic and flow-induced vibrations of BWR main steam line

    Espinosa-Paredes, G., E-mail: gepe@xanum.uam.mx [División de Ciencias Básicas e Ingeniería, Universidad Autónoma Metropolitana-Iztapalapa, México, D.F. 09340 (Mexico); Prieto-Guerrero, A. [División de Ciencias Básicas e Ingeniería, Universidad Autónoma Metropolitana-Iztapalapa, México, D.F. 09340 (Mexico); Núñez-Carrera, A. [Comisión Nacional de Seguridad Nuclear y Salvaguardias, Doctor Barragán 779, Col. Narvarte, México, D.F. 03020 (Mexico); Vázquez-Rodríguez, A. [División de Ciencias Básicas e Ingeniería, Universidad Autónoma Metropolitana-Iztapalapa, México, D.F. 09340 (Mexico); Centeno-Pérez, J. [Instituto Politécnico Nacional, Escuela Superior de Física y Matemáticas Unidad Profesional “Adolfo López Mateos”, Av. IPN, s/n, México, D.F. 07738 (Mexico); Espinosa-Martínez, E.-G. [Departamento de Sistemas Energéticos, Universidad Nacional Autónoma de México, México, D.F. 04510 (Mexico); and others

    2016-05-15

    Highlights: • Acoustic and flow-induced vibrations of BWR are analyzed. • BWR performance after extended power uprate is considered. • Effect of acoustic side branches (ASB) is analyzed. • The ASB represents a reduction in the acoustic loads to the steam dryer. • Methodology developed for simultaneous analyzing the signals in the MSL. - Abstract: The aim of this work is the signal analysis of acoustic waves due to phenomenon known as singing in Safety Relief Valves (SRV) of the main steam lines (MSL) in a typical BWR5. The acoustic resonance in SRV standpipes and fluctuating pressure is propagated from SRV to the dryer through the MSL. The signals are analyzed with a novel method based on the Multivariate Empirical Mode Decomposition (M-EMD). The M-EMD algorithm has the potential to find common oscillatory modes (IMF) within multivariate data. Based on this fact, we implement the M-EMD technique to find the oscillatory mode in BWR considering the measurements obtained collected by the strain gauges located around the MSL. These IMF, analyzed simultaneously in time, allow obtaining an estimation of the effects of the multiple-SRV in the MSL. Two scenarios are analyzed: the first is the signal obtained before the installation of the acoustic dampers (ASB), and the second, the signal obtained after installation. The results show the effectiveness of the ASB to damp the strong resonances when the steam flow increases, which represents an important reduction in the acoustic loads to the steam dryer.

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

    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.

  6. Signal analysis of acoustic and flow-induced vibrations of BWR main steam line

    Espinosa-Paredes, G.; Prieto-Guerrero, A.; Núñez-Carrera, A.; Vázquez-Rodríguez, A.; Centeno-Pérez, J.; Espinosa-Martínez, E.-G.

    2016-01-01

    Highlights: • Acoustic and flow-induced vibrations of BWR are analyzed. • BWR performance after extended power uprate is considered. • Effect of acoustic side branches (ASB) is analyzed. • The ASB represents a reduction in the acoustic loads to the steam dryer. • Methodology developed for simultaneous analyzing the signals in the MSL. - Abstract: The aim of this work is the signal analysis of acoustic waves due to phenomenon known as singing in Safety Relief Valves (SRV) of the main steam lines (MSL) in a typical BWR5. The acoustic resonance in SRV standpipes and fluctuating pressure is propagated from SRV to the dryer through the MSL. The signals are analyzed with a novel method based on the Multivariate Empirical Mode Decomposition (M-EMD). The M-EMD algorithm has the potential to find common oscillatory modes (IMF) within multivariate data. Based on this fact, we implement the M-EMD technique to find the oscillatory mode in BWR considering the measurements obtained collected by the strain gauges located around the MSL. These IMF, analyzed simultaneously in time, allow obtaining an estimation of the effects of the multiple-SRV in the MSL. Two scenarios are analyzed: the first is the signal obtained before the installation of the acoustic dampers (ASB), and the second, the signal obtained after installation. The results show the effectiveness of the ASB to damp the strong resonances when the steam flow increases, which represents an important reduction in the acoustic loads to the steam dryer.

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

    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.

  8. Digital system for acquiring signals from photodiode arrays. No. Program Element 2317-08-03

    Le Guen, M.; Meric, B.

    1981-01-01

    A model of circuit allowing the digitization and the memorization of signals coming from linear arrays of photodiodes have been realized. The authors first recall the organization and present in the second part some test results on experimental sites. The model consists of 1 - an acquisition, memorization and visualization card (AMV card) for the data from RETICON 121 photodiode strips, 2 - a series transfer card for the memorized data, and 3 - an interface and multiplexing card associated with a system using a 6800 microprocessor allowing the management of eight acquisition cards [fr

  9. Optics Program Simplifies Analysis and Design

    2007-01-01

    Engineers at Goddard Space Flight Center partnered with software experts at Mide Technology Corporation, of Medford, Massachusetts, through a Small Business Innovation Research (SBIR) contract to design the Disturbance-Optics-Controls-Structures (DOCS) Toolbox, a software suite for performing integrated modeling for multidisciplinary analysis and design. The DOCS Toolbox integrates various discipline models into a coupled process math model that can then predict system performance as a function of subsystem design parameters. The system can be optimized for performance; design parameters can be traded; parameter uncertainties can be propagated through the math model to develop error bounds on system predictions; and the model can be updated, based on component, subsystem, or system level data. The Toolbox also allows the definition of process parameters as explicit functions of the coupled model and includes a number of functions that analyze the coupled system model and provide for redesign. The product is being sold commercially by Nightsky Systems Inc., of Raleigh, North Carolina, a spinoff company that was formed by Mide specifically to market the DOCS Toolbox. Commercial applications include use by any contractors developing large space-based optical systems, including Lockheed Martin Corporation, The Boeing Company, and Northrup Grumman Corporation, as well as companies providing technical audit services, like General Dynamics Corporation

  10. Using Dynamic Fourier Analysis to Discriminate Between Seismic Signals from Natural Earthquakes and Mining Explosions

    Maria C. Mariani

    2017-08-01

    Full Text Available A sequence of intraplate earthquakes occurred in Arizona at the same location where miningexplosions were carried out in previous years. The explosions and some of the earthquakes generatedvery similar seismic signals. In this study Dynamic Fourier Analysis is used for discriminating signalsoriginating from natural earthquakes and mining explosions. Frequency analysis of seismogramsrecorded at regional distances shows that compared with the mining explosions the earthquake signalshave larger amplitudes in the frequency interval ~ 6 to 8 Hz and significantly smaller amplitudes inthe frequency interval ~ 2 to 4 Hz. This type of analysis permits identifying characteristics in theseismograms frequency yielding to detect potentially risky seismic events.

  11. Detection method of nonlinearity errors by statistical signal analysis in heterodyne Michelson interferometer.

    Hu, Juju; Hu, Haijiang; Ji, Yinghua

    2010-03-15

    Periodic nonlinearity that ranges from tens of nanometers to a few nanometers in heterodyne interferometer limits its use in high accuracy measurement. A novel method is studied to detect the nonlinearity errors based on the electrical subdivision and the analysis method of statistical signal in heterodyne Michelson interferometer. Under the movement of micropositioning platform with the uniform velocity, the method can detect the nonlinearity errors by using the regression analysis and Jackknife estimation. Based on the analysis of the simulations, the method can estimate the influence of nonlinearity errors and other noises for the dimensions measurement in heterodyne Michelson interferometer.

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

    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.

  13. Automated eddy current signal processing: operation between declarative and procedural programming

    Zorgati, R.; Georgel, B.; Duvaut, P.; Doligez, T.; Garreau, D.

    1993-09-01

    In this paper we present the problem of cooperation between numerical and symbolical programming. This cooperation enables an efficient substitution of some human based decisions. This approach is applied to Eddy current testing of steam generator tubes. We illustrate our purpose with results obtained with the mock-up Extraction. (authors). 1 fig., 5 refs

  14. Programmed Lab Experiments for Biochemical Investigation of Quorum-Sensing Signal Molecules in Rhizospheric Soil Bacteria

    Nievas, Fiorela L.; Bogino, Pablo C.; Giordano, Walter

    2016-01-01

    Biochemistry courses in the Department of Molecular Biology at the National University of Río Cuarto, Argentina, are designed for undergraduate students in biology, microbiology, chemistry, agronomy, and veterinary medicine. Microbiology students typically have previous coursework in general, analytical, and organic chemistry. Programmed sequences…

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

    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

  16. GUI program to compute probabilistic seismic hazard analysis

    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

  17. GUI program to compute probabilistic seismic hazard analysis

    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

  18. A comparative analysis of influenza vaccination programs.

    Shweta Bansal

    2006-10-01

    Full Text Available BACKGROUND: The threat of avian influenza and the 2004-2005 influenza vaccine supply shortage in the United States have sparked a debate about optimal vaccination strategies to reduce the burden of morbidity and mortality caused by the influenza virus. METHODS AND FINDINGS: We present a comparative analysis of two classes of suggested vaccination strategies: mortality-based strategies that target high-risk populations and morbidity-based strategies that target high-prevalence populations. Applying the methods of contact network epidemiology to a model of disease transmission in a large urban population, we assume that vaccine supplies are limited and then evaluate the efficacy of these strategies across a wide range of viral transmission rates and for two different age-specific mortality distributions. We find that the optimal strategy depends critically on the viral transmission level (reproductive rate of the virus: morbidity-based strategies outperform mortality-based strategies for moderately transmissible strains, while the reverse is true for highly transmissible strains. These results hold for a range of mortality rates reported for prior influenza epidemics and pandemics. Furthermore, we show that vaccination delays and multiple introductions of disease into the community have a more detrimental impact on morbidity-based strategies than mortality-based strategies. CONCLUSIONS: If public health officials have reasonable estimates of the viral transmission rate and the frequency of new introductions into the community prior to an outbreak, then these methods can guide the design of optimal vaccination priorities. When such information is unreliable or not available, as is often the case, this study recommends mortality-based vaccination priorities.

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

    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.

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

    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