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Sample records for multivariate event time

  1. Contamination Event Detection with Multivariate Time-Series Data in Agricultural Water Monitoring

    Directory of Open Access Journals (Sweden)

    Yingchi Mao

    2017-12-01

    Full Text Available Time series data of multiple water quality parameters are obtained from the water sensor networks deployed in the agricultural water supply network. The accurate and efficient detection and warning of contamination events to prevent pollution from spreading is one of the most important issues when pollution occurs. In order to comprehensively reduce the event detection deviation, a spatial–temporal-based event detection approach with multivariate time-series data for water quality monitoring (M-STED was proposed. The M-STED approach includes three parts. The first part is that M-STED adopts a Rule K algorithm to select backbone nodes as the nodes in the CDS, and forward the sensed data of multiple water parameters. The second part is to determine the state of each backbone node with back propagation neural network models and the sequential Bayesian analysis in the current timestamp. The third part is to establish a spatial model with Bayesian networks to estimate the state of the backbones in the next timestamp and trace the “outlier” node to its neighborhoods to detect a contamination event. The experimental results indicate that the average detection rate is more than 80% with M-STED and the false detection rate is lower than 9%, respectively. The M-STED approach can improve the rate of detection by about 40% and reduce the false alarm rate by about 45%, compared with the event detection with a single water parameter algorithm, S-STED. Moreover, the proposed M-STED can exhibit better performance in terms of detection delay and scalability.

  2. Multivariate Time Series Search

    Data.gov (United States)

    National Aeronautics and Space Administration — Multivariate Time-Series (MTS) are ubiquitous, and are generated in areas as disparate as sensor recordings in aerospace systems, music and video streams, medical...

  3. Advanced event reweighting using multivariate analysis

    International Nuclear Information System (INIS)

    Martschei, D; Feindt, M; Honc, S; Wagner-Kuhr, J

    2012-01-01

    Multivariate analysis (MVA) methods, especially discrimination techniques such as neural networks, are key ingredients in modern data analysis and play an important role in high energy physics. They are usually trained on simulated Monte Carlo (MC) samples to discriminate so called 'signal' from 'background' events and are then applied to data to select real events of signal type. We here address procedures that improve this work flow. This will be the enhancement of data / MC agreement by reweighting MC samples on a per event basis. Then training MVAs on real data using the sPlot technique will be discussed. Finally we will address the construction of MVAs whose discriminator is independent of a certain control variable, i.e. cuts on this variable will not change the discriminator shape.

  4. Multivariate Time Series Decomposition into Oscillation Components.

    Science.gov (United States)

    Matsuda, Takeru; Komaki, Fumiyasu

    2017-08-01

    Many time series are considered to be a superposition of several oscillation components. We have proposed a method for decomposing univariate time series into oscillation components and estimating their phases (Matsuda & Komaki, 2017 ). In this study, we extend that method to multivariate time series. We assume that several oscillators underlie the given multivariate time series and that each variable corresponds to a superposition of the projections of the oscillators. Thus, the oscillators superpose on each variable with amplitude and phase modulation. Based on this idea, we develop gaussian linear state-space models and use them to decompose the given multivariate time series. The model parameters are estimated from data using the empirical Bayes method, and the number of oscillators is determined using the Akaike information criterion. Therefore, the proposed method extracts underlying oscillators in a data-driven manner and enables investigation of phase dynamics in a given multivariate time series. Numerical results show the effectiveness of the proposed method. From monthly mean north-south sunspot number data, the proposed method reveals an interesting phase relationship.

  5. Geometric noise reduction for multivariate time series.

    Science.gov (United States)

    Mera, M Eugenia; Morán, Manuel

    2006-03-01

    We propose an algorithm for the reduction of observational noise in chaotic multivariate time series. The algorithm is based on a maximum likelihood criterion, and its goal is to reduce the mean distance of the points of the cleaned time series to the attractor. We give evidence of the convergence of the empirical measure associated with the cleaned time series to the underlying invariant measure, implying the possibility to predict the long run behavior of the true dynamics.

  6. Network structure of multivariate time series.

    Science.gov (United States)

    Lacasa, Lucas; Nicosia, Vincenzo; Latora, Vito

    2015-10-21

    Our understanding of a variety of phenomena in physics, biology and economics crucially depends on the analysis of multivariate time series. While a wide range tools and techniques for time series analysis already exist, the increasing availability of massive data structures calls for new approaches for multidimensional signal processing. We present here a non-parametric method to analyse multivariate time series, based on the mapping of a multidimensional time series into a multilayer network, which allows to extract information on a high dimensional dynamical system through the analysis of the structure of the associated multiplex network. The method is simple to implement, general, scalable, does not require ad hoc phase space partitioning, and is thus suitable for the analysis of large, heterogeneous and non-stationary time series. We show that simple structural descriptors of the associated multiplex networks allow to extract and quantify nontrivial properties of coupled chaotic maps, including the transition between different dynamical phases and the onset of various types of synchronization. As a concrete example we then study financial time series, showing that a multiplex network analysis can efficiently discriminate crises from periods of financial stability, where standard methods based on time-series symbolization often fail.

  7. Multivariable dynamic calculus on time scales

    CERN Document Server

    Bohner, Martin

    2016-01-01

    This book offers the reader an overview of recent developments of multivariable dynamic calculus on time scales, taking readers beyond the traditional calculus texts. Covering topics from parameter-dependent integrals to partial differentiation on time scales, the book’s nine pedagogically oriented chapters provide a pathway to this active area of research that will appeal to students and researchers in mathematics and the physical sciences. The authors present a clear and well-organized treatment of the concept behind the mathematics and solution techniques, including many practical examples and exercises.

  8. Time varying, multivariate volume data reduction

    Energy Technology Data Exchange (ETDEWEB)

    Ahrens, James P [Los Alamos National Laboratory; Fout, Nathaniel [UC DAVIS; Ma, Kwan - Liu [UC DAVIS

    2010-01-01

    Large-scale supercomputing is revolutionizing the way science is conducted. A growing challenge, however, is understanding the massive quantities of data produced by large-scale simulations. The data, typically time-varying, multivariate, and volumetric, can occupy from hundreds of gigabytes to several terabytes of storage space. Transferring and processing volume data of such sizes is prohibitively expensive and resource intensive. Although it may not be possible to entirely alleviate these problems, data compression should be considered as part of a viable solution, especially when the primary means of data analysis is volume rendering. In this paper we present our study of multivariate compression, which exploits correlations among related variables, for volume rendering. Two configurations for multidimensional compression based on vector quantization are examined. We emphasize quality reconstruction and interactive rendering, which leads us to a solution using graphics hardware to perform on-the-fly decompression during rendering. In this paper we present a solution which addresses the need for data reduction in large supercomputing environments where data resulting from simulations occupies tremendous amounts of storage. Our solution employs a lossy encoding scheme to acrueve data reduction with several options in terms of rate-distortion behavior. We focus on encoding of multiple variables together, with optional compression in space and time. The compressed volumes can be rendered directly with commodity graphics cards at interactive frame rates and rendering quality similar to that of static volume renderers. Compression results using a multivariate time-varying data set indicate that encoding multiple variables results in acceptable performance in the case of spatial and temporal encoding as compared to independent compression of variables. The relative performance of spatial vs. temporal compression is data dependent, although temporal compression has the

  9. Interpretable Early Classification of Multivariate Time Series

    Science.gov (United States)

    Ghalwash, Mohamed F.

    2013-01-01

    Recent advances in technology have led to an explosion in data collection over time rather than in a single snapshot. For example, microarray technology allows us to measure gene expression levels in different conditions over time. Such temporal data grants the opportunity for data miners to develop algorithms to address domain-related problems,…

  10. Multiplexing real-time timed events

    NARCIS (Netherlands)

    Holenderski, M.J.; Cools, W.A.; Bril, R.J.; Lukkien, J.J.

    2009-01-01

    This paper presents the design and implementation of RELTEQ, a timed event management algorithm based on relative event times, supporting long event interarrival time, long lifetime of the event queue, no drift and low overhead. It is targeted at embedded operating systems. RELTEQ has been conceived

  11. Small Sample Properties of Bayesian Multivariate Autoregressive Time Series Models

    Science.gov (United States)

    Price, Larry R.

    2012-01-01

    The aim of this study was to compare the small sample (N = 1, 3, 5, 10, 15) performance of a Bayesian multivariate vector autoregressive (BVAR-SEM) time series model relative to frequentist power and parameter estimation bias. A multivariate autoregressive model was developed based on correlated autoregressive time series vectors of varying…

  12. Multivariate Volatility Impulse Response Analysis of GFC News Events

    NARCIS (Netherlands)

    D.E. Allen (David); M.J. McAleer (Michael); R.J. Powell (Robert); A.K. Singh (Abhay)

    2015-01-01

    textabstractThis paper applies the Hafner and Herwartz (2006) (hereafter HH) approach to the analysis of multivariate GARCH models using volatility impulse response analysis. The data set features ten years of daily returns series for the New York Stock Exchange Index and the FTSE 100 index from the

  13. Multivariate Volatility Impulse Response Analysis of GFC News Events

    NARCIS (Netherlands)

    D.E. Allen (David); M.J. McAleer (Michael); R.J. Powell (Robert)

    2015-01-01

    markdownabstract__Abstract__ This paper applies the Hafner and Herwartz (2006) (hereafter HH) approach to the analysis of multivariate GARCH models using volatility impulse response analysis. The data set features ten years of daily returns series for the New York Stock Exchange Index and the

  14. Fast and Flexible Multivariate Time Series Subsequence Search

    Data.gov (United States)

    National Aeronautics and Space Administration — Multivariate Time-Series (MTS) are ubiquitous, and are generated in areas as disparate as sensor recordings in aerospace systems, music and video streams, medical...

  15. DTW-APPROACH FOR UNCORRELATED MULTIVARIATE TIME SERIES IMPUTATION

    OpenAIRE

    Phan , Thi-Thu-Hong; Poisson Caillault , Emilie; Bigand , André; Lefebvre , Alain

    2017-01-01

    International audience; Missing data are inevitable in almost domains of applied sciences. Data analysis with missing values can lead to a loss of efficiency and unreliable results, especially for large missing sub-sequence(s). Some well-known methods for multivariate time series imputation require high correlations between series or their features. In this paper , we propose an approach based on the shape-behaviour relation in low/un-correlated multivariate time series under an assumption of...

  16. Multivariate performance reliability prediction in real-time

    International Nuclear Information System (INIS)

    Lu, S.; Lu, H.; Kolarik, W.J.

    2001-01-01

    This paper presents a technique for predicting system performance reliability in real-time considering multiple failure modes. The technique includes on-line multivariate monitoring and forecasting of selected performance measures and conditional performance reliability estimates. The performance measures across time are treated as a multivariate time series. A state-space approach is used to model the multivariate time series. Recursive forecasting is performed by adopting Kalman filtering. The predicted mean vectors and covariance matrix of performance measures are used for the assessment of system survival/reliability with respect to the conditional performance reliability. The technique and modeling protocol discussed in this paper provide a means to forecast and evaluate the performance of an individual system in a dynamic environment in real-time. The paper also presents an example to demonstrate the technique

  17. Drunk driving detection based on classification of multivariate time series.

    Science.gov (United States)

    Li, Zhenlong; Jin, Xue; Zhao, Xiaohua

    2015-09-01

    This paper addresses the problem of detecting drunk driving based on classification of multivariate time series. First, driving performance measures were collected from a test in a driving simulator located in the Traffic Research Center, Beijing University of Technology. Lateral position and steering angle were used to detect drunk driving. Second, multivariate time series analysis was performed to extract the features. A piecewise linear representation was used to represent multivariate time series. A bottom-up algorithm was then employed to separate multivariate time series. The slope and time interval of each segment were extracted as the features for classification. Third, a support vector machine classifier was used to classify driver's state into two classes (normal or drunk) according to the extracted features. The proposed approach achieved an accuracy of 80.0%. Drunk driving detection based on the analysis of multivariate time series is feasible and effective. The approach has implications for drunk driving detection. Copyright © 2015 Elsevier Ltd and National Safety Council. All rights reserved.

  18. Constructing ordinal partition transition networks from multivariate time series.

    Science.gov (United States)

    Zhang, Jiayang; Zhou, Jie; Tang, Ming; Guo, Heng; Small, Michael; Zou, Yong

    2017-08-10

    A growing number of algorithms have been proposed to map a scalar time series into ordinal partition transition networks. However, most observable phenomena in the empirical sciences are of a multivariate nature. We construct ordinal partition transition networks for multivariate time series. This approach yields weighted directed networks representing the pattern transition properties of time series in velocity space, which hence provides dynamic insights of the underling system. Furthermore, we propose a measure of entropy to characterize ordinal partition transition dynamics, which is sensitive to capturing the possible local geometric changes of phase space trajectories. We demonstrate the applicability of pattern transition networks to capture phase coherence to non-coherence transitions, and to characterize paths to phase synchronizations. Therefore, we conclude that the ordinal partition transition network approach provides complementary insight to the traditional symbolic analysis of nonlinear multivariate time series.

  19. Multivariate time series modeling of selected childhood diseases in ...

    African Journals Online (AJOL)

    This paper is focused on modeling the five most prevalent childhood diseases in Akwa Ibom State using a multivariate approach to time series. An aggregate of 78,839 reported cases of malaria, upper respiratory tract infection (URTI), Pneumonia, anaemia and tetanus were extracted from five randomly selected hospitals in ...

  20. multivariate time series modeling of selected childhood diseases

    African Journals Online (AJOL)

    2016-06-17

    Jun 17, 2016 ... KEYWORDS: Multivariate Approach, Pre-whitening, Vector Time Series, .... Alternatively, the process may be written in mean adjusted form as .... The AIC criterion asymptotically over estimates the order with positive probability, whereas the BIC and HQC criteria ... has the same asymptotic distribution as Ǫ.

  1. Effectiveness of Multivariate Time Series Classification Using Shapelets

    Directory of Open Access Journals (Sweden)

    A. P. Karpenko

    2015-01-01

    Full Text Available Typically, time series classifiers require signal pre-processing (filtering signals from noise and artifact removal, etc., enhancement of signal features (amplitude, frequency, spectrum, etc., classification of signal features in space using the classical techniques and classification algorithms of multivariate data. We consider a method of classifying time series, which does not require enhancement of the signal features. The method uses the shapelets of time series (time series shapelets i.e. small fragments of this series, which reflect properties of one of its classes most of all.Despite the significant number of publications on the theory and shapelet applications for classification of time series, the task to evaluate the effectiveness of this technique remains relevant. An objective of this publication is to study the effectiveness of a number of modifications of the original shapelet method as applied to the multivariate series classification that is a littlestudied problem. The paper presents the problem statement of multivariate time series classification using the shapelets and describes the shapelet–based basic method of binary classification, as well as various generalizations and proposed modification of the method. It also offers the software that implements a modified method and results of computational experiments confirming the effectiveness of the algorithmic and software solutions.The paper shows that the modified method and the software to use it allow us to reach the classification accuracy of about 85%, at best. The shapelet search time increases in proportion to input data dimension.

  2. Multivariate time series analysis with R and financial applications

    CERN Document Server

    Tsay, Ruey S

    2013-01-01

    Since the publication of his first book, Analysis of Financial Time Series, Ruey Tsay has become one of the most influential and prominent experts on the topic of time series. Different from the traditional and oftentimes complex approach to multivariate (MV) time series, this sequel book emphasizes structural specification, which results in simplified parsimonious VARMA modeling and, hence, eases comprehension. Through a fundamental balance between theory and applications, the book supplies readers with an accessible approach to financial econometric models and their applications to real-worl

  3. Multivariate Option Pricing with Time Varying Volatility and Correlations

    DEFF Research Database (Denmark)

    Rombouts, Jeroen V.K.; Stentoft, Lars Peter

    In recent years multivariate models for asset returns have received much attention, in particular this is the case for models with time varying volatility. In this paper we consider models of this class and examine their potential when it comes to option pricing. Specifically, we derive the risk...... neutral dynamics for a general class of multivariate heteroskedastic models, and we provide a feasible way to price options in this framework. Our framework can be used irrespective of the assumed underlying distribution and dynamics, and it nests several important special cases. We provide an application...... to options on the minimum of two indices. Our results show that not only is correlation important for these options but so is allowing this correlation to be dynamic. Moreover, we show that for the general model exposure to correlation risk carries an important premium, and when this is neglected option...

  4. The LCLS Timing Event System

    Energy Technology Data Exchange (ETDEWEB)

    Dusatko, John; Allison, S.; Browne, M.; Krejcik, P.; /SLAC

    2012-07-23

    The Linac Coherent Light Source requires precision timing trigger signals for various accelerator diagnostics and controls at SLAC-NAL. A new timing system has been developed that meets these requirements. This system is based on COTS hardware with a mixture of custom-designed units. An added challenge has been the requirement that the LCLS Timing System must co-exist and 'know' about the existing SLC Timing System. This paper describes the architecture, construction and performance of the LCLS timing event system.

  5. Multivariate algorithms for initiating event detection and identification in nuclear power plants

    International Nuclear Information System (INIS)

    Wu, Shun-Chi; Chen, Kuang-You; Lin, Ting-Han; Chou, Hwai-Pwu

    2018-01-01

    Highlights: •Multivariate algorithms for NPP initiating event detection and identification. •Recordings from multiple sensors are simultaneously considered for detection. •Both spatial and temporal information is used for event identification. •Untrained event isolation avoids falsely relating an untrained event. •Efficacy of the algorithms is verified with data from the Maanshan NPP simulator. -- Abstract: To prevent escalation of an initiating event into a severe accident, promptly detecting its occurrence and precisely identifying its type are essential. In this study, several multivariate algorithms for initiating event detection and identification are proposed to help maintain safe operations of nuclear power plants (NPPs). By monitoring changes in the NPP sensing variables, an event is detected when the preset thresholds are exceeded. Unlike existing approaches, recordings from sensors of the same type are simultaneously considered for detection, and no subjective reasoning is involved in setting these thresholds. To facilitate efficient event identification, a spatiotemporal feature extractor is proposed. The extracted features consist of the temporal traits used by existing techniques and the spatial signature of an event. Through an F-score-based feature ranking, only those that are most discriminant in classifying the events under consideration will be retained for identification. Moreover, an untrained event isolation scheme is introduced to avoid relating an untrained event to those in the event dataset so that improper recovery actions can be prevented. Results from experiments containing data of 12 event classes and a total of 125 events generated using a Taiwan’s Maanshan NPP simulator are provided to illustrate the efficacy of the proposed algorithms.

  6. Behavioral event occurrence differs between behavioral states in Sotalia guianensis (Cetarctiodactyla: Delphinidae dolphins: a multivariate approach

    Directory of Open Access Journals (Sweden)

    Rodrigo H. Tardin

    2014-02-01

    Full Text Available Difficulties in quantifying behavioral events can cause loss of information about cetacean behavior, especially behaviors whose functions are still debated. The lack of knowledge is greater for South American species such as Sotalia guianensis (Van Benédén, 1864. Our objective was to contextualize the behavioral events inside behavioral states using a Permutational Multivariate Analysis of Variance (MANOVA. Three events occurred in the Feeding, Socio-Sexual and Travelling states (Porpoising, Side flop, Tail out dive, and five events occurred in the Feeding and Travelling states (Back flop, Horizontal jump, Lobtail, Spy-hop, Partial flop ahead. Three events (Belly exposure, Club, and Heading occurred exclusively in the Socio-sexual state. Partial Back flop and Head flop occurred exclusively in the Feeding state. For the events that occurred in multiple states, we observed that some events occurred more frequently in one of the states (p < 0.001, such as Lobtail, Tail out dive horizontal Jump, Partial flop ahead and Side flop. Our multivariate analysis, which separated Socio-sexual behavior from Feeding and Travelling, showed that the abundance of behavioral events differs between states. This differentiation indicates that some events are associated with specific behavioral states. Almost 40% of the events observed were exclusively performed in one state, which indicates a high specialization for some events. Proper discrimination and contextualization of behavioral events may be efficient tools to better understand dolphin behaviors. Similar studies in other habitats and with other species, will help build a broader scenario to aid our understanding of the functions of dolphin behavioral events.

  7. Clustering Multivariate Time Series Using Hidden Markov Models

    Directory of Open Access Journals (Sweden)

    Shima Ghassempour

    2014-03-01

    Full Text Available In this paper we describe an algorithm for clustering multivariate time series with variables taking both categorical and continuous values. Time series of this type are frequent in health care, where they represent the health trajectories of individuals. The problem is challenging because categorical variables make it difficult to define a meaningful distance between trajectories. We propose an approach based on Hidden Markov Models (HMMs, where we first map each trajectory into an HMM, then define a suitable distance between HMMs and finally proceed to cluster the HMMs with a method based on a distance matrix. We test our approach on a simulated, but realistic, data set of 1,255 trajectories of individuals of age 45 and over, on a synthetic validation set with known clustering structure, and on a smaller set of 268 trajectories extracted from the longitudinal Health and Retirement Survey. The proposed method can be implemented quite simply using standard packages in R and Matlab and may be a good candidate for solving the difficult problem of clustering multivariate time series with categorical variables using tools that do not require advanced statistic knowledge, and therefore are accessible to a wide range of researchers.

  8. Optimal model-free prediction from multivariate time series

    Science.gov (United States)

    Runge, Jakob; Donner, Reik V.; Kurths, Jürgen

    2015-05-01

    Forecasting a time series from multivariate predictors constitutes a challenging problem, especially using model-free approaches. Most techniques, such as nearest-neighbor prediction, quickly suffer from the curse of dimensionality and overfitting for more than a few predictors which has limited their application mostly to the univariate case. Therefore, selection strategies are needed that harness the available information as efficiently as possible. Since often the right combination of predictors matters, ideally all subsets of possible predictors should be tested for their predictive power, but the exponentially growing number of combinations makes such an approach computationally prohibitive. Here a prediction scheme that overcomes this strong limitation is introduced utilizing a causal preselection step which drastically reduces the number of possible predictors to the most predictive set of causal drivers making a globally optimal search scheme tractable. The information-theoretic optimality is derived and practical selection criteria are discussed. As demonstrated for multivariate nonlinear stochastic delay processes, the optimal scheme can even be less computationally expensive than commonly used suboptimal schemes like forward selection. The method suggests a general framework to apply the optimal model-free approach to select variables and subsequently fit a model to further improve a prediction or learn statistical dependencies. The performance of this framework is illustrated on a climatological index of El Niño Southern Oscillation.

  9. Recurrent Neural Networks for Multivariate Time Series with Missing Values.

    Science.gov (United States)

    Che, Zhengping; Purushotham, Sanjay; Cho, Kyunghyun; Sontag, David; Liu, Yan

    2018-04-17

    Multivariate time series data in practical applications, such as health care, geoscience, and biology, are characterized by a variety of missing values. In time series prediction and other related tasks, it has been noted that missing values and their missing patterns are often correlated with the target labels, a.k.a., informative missingness. There is very limited work on exploiting the missing patterns for effective imputation and improving prediction performance. In this paper, we develop novel deep learning models, namely GRU-D, as one of the early attempts. GRU-D is based on Gated Recurrent Unit (GRU), a state-of-the-art recurrent neural network. It takes two representations of missing patterns, i.e., masking and time interval, and effectively incorporates them into a deep model architecture so that it not only captures the long-term temporal dependencies in time series, but also utilizes the missing patterns to achieve better prediction results. Experiments of time series classification tasks on real-world clinical datasets (MIMIC-III, PhysioNet) and synthetic datasets demonstrate that our models achieve state-of-the-art performance and provide useful insights for better understanding and utilization of missing values in time series analysis.

  10. Multivariate time series with linear state space structure

    CERN Document Server

    Gómez, Víctor

    2016-01-01

    This book presents a comprehensive study of multivariate time series with linear state space structure. The emphasis is put on both the clarity of the theoretical concepts and on efficient algorithms for implementing the theory. In particular, it investigates the relationship between VARMA and state space models, including canonical forms. It also highlights the relationship between Wiener-Kolmogorov and Kalman filtering both with an infinite and a finite sample. The strength of the book also lies in the numerous algorithms included for state space models that take advantage of the recursive nature of the models. Many of these algorithms can be made robust, fast, reliable and efficient. The book is accompanied by a MATLAB package called SSMMATLAB and a webpage presenting implemented algorithms with many examples and case studies. Though it lays a solid theoretical foundation, the book also focuses on practical application, and includes exercises in each chapter. It is intended for researchers and students wor...

  11. A Multivariate Time Series Method for Monte Carlo Reactor Analysis

    International Nuclear Information System (INIS)

    Taro Ueki

    2008-01-01

    A robust multivariate time series method has been established for the Monte Carlo calculation of neutron multiplication problems. The method is termed Coarse Mesh Projection Method (CMPM) and can be implemented using the coarse statistical bins for acquisition of nuclear fission source data. A novel aspect of CMPM is the combination of the general technical principle of projection pursuit in the signal processing discipline and the neutron multiplication eigenvalue problem in the nuclear engineering discipline. CMPM enables reactor physicists to accurately evaluate major eigenvalue separations of nuclear reactors with continuous energy Monte Carlo calculation. CMPM was incorporated in the MCNP Monte Carlo particle transport code of Los Alamos National Laboratory. The great advantage of CMPM over the traditional Fission Matrix method is demonstrated for the three space-dimensional modeling of the initial core of a pressurized water reactor

  12. Multivariate Sensitivity Analysis of Time-of-Flight Sensor Fusion

    Science.gov (United States)

    Schwarz, Sebastian; Sjöström, Mårten; Olsson, Roger

    2014-09-01

    Obtaining three-dimensional scenery data is an essential task in computer vision, with diverse applications in various areas such as manufacturing and quality control, security and surveillance, or user interaction and entertainment. Dedicated Time-of-Flight sensors can provide detailed scenery depth in real-time and overcome short-comings of traditional stereo analysis. Nonetheless, they do not provide texture information and have limited spatial resolution. Therefore such sensors are typically combined with high resolution video sensors. Time-of-Flight Sensor Fusion is a highly active field of research. Over the recent years, there have been multiple proposals addressing important topics such as texture-guided depth upsampling and depth data denoising. In this article we take a step back and look at the underlying principles of ToF sensor fusion. We derive the ToF sensor fusion error model and evaluate its sensitivity to inaccuracies in camera calibration and depth measurements. In accordance with our findings, we propose certain courses of action to ensure high quality fusion results. With this multivariate sensitivity analysis of the ToF sensor fusion model, we provide an important guideline for designing, calibrating and running a sophisticated Time-of-Flight sensor fusion capture systems.

  13. Multivariate analysis methods to tag b quark events at LEP/SLC

    International Nuclear Information System (INIS)

    Brandl, B.; Falvard, A.; Guicheney, C.; Henrard, P.; Jousset, J.; Proriol, J.

    1992-01-01

    Multivariate analyses are applied to tag Z → bb-bar events at LEP/SLC. They are based on the specific b-event shape caused by the large b-quark mass. Discriminant analyses, classification trees and neural networks are presented and their performances are compared. It is shown that the neural network approach, due to its non-linearity, copes best with the complexity of the problem. As an example for an application of the developed methods the measurement of Γ(Z → bb-bar) is discussed. The usefulness of methods based on the global event shape is limited by the uncertainties introduced by the necessity of event simulation. As solution a double tag method is presented which can be applied to many tasks of LEP/SLC heavy flavour physics. (author) 29 refs.; 6 figs.; 1 tab

  14. Multivariable analysis of a failure event of pressure regulator in a BWR; Analisis multivariable de un evento de falla del regulador de presion en un BWR

    Energy Technology Data Exchange (ETDEWEB)

    Castillo D, R.; Ortiz V, J. [ININ, Carretera Mexico-Toluca s/n, 52750 Ocoyoacac, Estado de Mexico (Mexico); Calleros M, G. [Comision Federal de Electricidad, Central Nucleoelectrica Laguna Verde, Carretera Cardel-Nautla, Km. 43.5, Veracruz (Mexico)], e-mail: rogelio.castillo@inin.gob.mx

    2009-10-15

    The boiling water reactors can experiment three types of instabilities: one caused by the controllers failure of plant, another renowned instability by reactivity and the last knew as thermal hydraulics instability. An event of pressure regulator failure of electro-hydraulic control of Unit 1 of nuclear power plant of Laguna Verde was analyzed, which caused power oscillations that were increasing their magnitude in the time course. The event has been analyzed using the Fourier transformation in short time for time-frequency analysis and for the frequency domain be employment the power spectral density. Both techniques reported a resonance to oscillation frequency of 0.055 Hz in the power spectrum, this frequency is of observed order of magnitude when fail the reactor control systems. However, these analysis did not allow to study the interrelation of event signals. Of the previous studies, were obtained power spectral densities containing picks and valleys related with the dynamic behaviour of reactor, which includes the control systems performance. For a pick or present valley to a specific frequency in the power spectrum for one of previous variables, can determine the influence of other variables on the pick or valley by relative contribution of power. This method was established in a developed program of name Noise, which uses a multivariable autoregressive model to obtain the autoregressive coefficients, and starting from them the relative contribution of power is determined. Basically two important results were obtained, the first is related with the influence of feed water flow on the other variables to the frequency of 0.055 Hz, the second is related with the instability by reactivity and confirms that this way was not excited during the event. (Author)

  15. Models and analysis for multivariate failure time data

    Science.gov (United States)

    Shih, Joanna Huang

    The goal of this research is to develop and investigate models and analytic methods for multivariate failure time data. We compare models in terms of direct modeling of the margins, flexibility of dependency structure, local vs. global measures of association, and ease of implementation. In particular, we study copula models, and models produced by right neutral cumulative hazard functions and right neutral hazard functions. We examine the changes of association over time for families of bivariate distributions induced from these models by displaying their density contour plots, conditional density plots, correlation curves of Doksum et al, and local cross ratios of Oakes. We know that bivariate distributions with same margins might exhibit quite different dependency structures. In addition to modeling, we study estimation procedures. For copula models, we investigate three estimation procedures. the first procedure is full maximum likelihood. The second procedure is two-stage maximum likelihood. At stage 1, we estimate the parameters in the margins by maximizing the marginal likelihood. At stage 2, we estimate the dependency structure by fixing the margins at the estimated ones. The third procedure is two-stage partially parametric maximum likelihood. It is similar to the second procedure, but we estimate the margins by the Kaplan-Meier estimate. We derive asymptotic properties for these three estimation procedures and compare their efficiency by Monte-Carlo simulations and direct computations. For models produced by right neutral cumulative hazards and right neutral hazards, we derive the likelihood and investigate the properties of the maximum likelihood estimates. Finally, we develop goodness of fit tests for the dependency structure in the copula models. We derive a test statistic and its asymptotic properties based on the test of homogeneity of Zelterman and Chen (1988), and a graphical diagnostic procedure based on the empirical Bayes approach. We study the

  16. A statistical approach for segregating cognitive task stages from multivariate fMRI BOLD time series

    Directory of Open Access Journals (Sweden)

    Charmaine eDemanuele

    2015-10-01

    Full Text Available Multivariate pattern analysis can reveal new information from neuroimaging data to illuminate human cognition and its disturbances. Here, we develop a methodological approach, based on multivariate statistical/machine learning and time series analysis, to discern cognitive processing stages from fMRI blood oxygenation level dependent (BOLD time series. We apply this method to data recorded from a group of healthy adults whilst performing a virtual reality version of the delayed win-shift radial arm maze task. This task has been frequently used to study working memory and decision making in rodents. Using linear classifiers and multivariate test statistics in conjunction with time series bootstraps, we show that different cognitive stages of the task, as defined by the experimenter, namely, the encoding/retrieval, choice, reward and delay stages, can be statistically discriminated from the BOLD time series in brain areas relevant for decision making and working memory. Discrimination of these task stages was significantly reduced during poor behavioral performance in dorsolateral prefrontal cortex (DLPFC, but not in the primary visual cortex (V1. Experimenter-defined dissection of time series into class labels based on task structure was confirmed by an unsupervised, bottom-up approach based on Hidden Markov Models. Furthermore, we show that different groupings of recorded time points into cognitive event classes can be used to test hypotheses about the specific cognitive role of a given brain region during task execution. We found that whilst the DLPFC strongly differentiated between task stages associated with different memory loads, but not between different visual-spatial aspects, the reverse was true for V1. Our methodology illustrates how different aspects of cognitive information processing during one and the same task can be separated and attributed to specific brain regions based on information contained in multivariate patterns of voxel

  17. Joint Models of Longitudinal and Time-to-Event Data with More Than One Event Time Outcome: A Review.

    Science.gov (United States)

    Hickey, Graeme L; Philipson, Pete; Jorgensen, Andrea; Kolamunnage-Dona, Ruwanthi

    2018-01-31

    Methodological development and clinical application of joint models of longitudinal and time-to-event outcomes have grown substantially over the past two decades. However, much of this research has concentrated on a single longitudinal outcome and a single event time outcome. In clinical and public health research, patients who are followed up over time may often experience multiple, recurrent, or a succession of clinical events. Models that utilise such multivariate event time outcomes are quite valuable in clinical decision-making. We comprehensively review the literature for implementation of joint models involving more than a single event time per subject. We consider the distributional and modelling assumptions, including the association structure, estimation approaches, software implementations, and clinical applications. Research into this area is proving highly promising, but to-date remains in its infancy.

  18. A Framework and Algorithms for Multivariate Time Series Analytics (MTSA): Learning, Monitoring, and Recommendation

    Science.gov (United States)

    Ngan, Chun-Kit

    2013-01-01

    Making decisions over multivariate time series is an important topic which has gained significant interest in the past decade. A time series is a sequence of data points which are measured and ordered over uniform time intervals. A multivariate time series is a set of multiple, related time series in a particular domain in which domain experts…

  19. A climate-based multivariate extreme emulator of met-ocean-hydrological events for coastal flooding

    Science.gov (United States)

    Camus, Paula; Rueda, Ana; Mendez, Fernando J.; Tomas, Antonio; Del Jesus, Manuel; Losada, Iñigo J.

    2015-04-01

    Atmosphere-ocean general circulation models (AOGCMs) are useful to analyze large-scale climate variability (long-term historical periods, future climate projections). However, applications such as coastal flood modeling require climate information at finer scale. Besides, flooding events depend on multiple climate conditions: waves, surge levels from the open-ocean and river discharge caused by precipitation. Therefore, a multivariate statistical downscaling approach is adopted to reproduce relationships between variables and due to its low computational cost. The proposed method can be considered as a hybrid approach which combines a probabilistic weather type downscaling model with a stochastic weather generator component. Predictand distributions are reproduced modeling the relationship with AOGCM predictors based on a physical division in weather types (Camus et al., 2012). The multivariate dependence structure of the predictand (extreme events) is introduced linking the independent marginal distributions of the variables by a probabilistic copula regression (Ben Ayala et al., 2014). This hybrid approach is applied for the downscaling of AOGCM data to daily precipitation and maximum significant wave height and storm-surge in different locations along the Spanish coast. Reanalysis data is used to assess the proposed method. A commonly predictor for the three variables involved is classified using a regression-guided clustering algorithm. The most appropriate statistical model (general extreme value distribution, pareto distribution) for daily conditions is fitted. Stochastic simulation of the present climate is performed obtaining the set of hydraulic boundary conditions needed for high resolution coastal flood modeling. References: Camus, P., Menéndez, M., Méndez, F.J., Izaguirre, C., Espejo, A., Cánovas, V., Pérez, J., Rueda, A., Losada, I.J., Medina, R. (2014b). A weather-type statistical downscaling framework for ocean wave climate. Journal of

  20. Symbolic Time Separation of Events

    DEFF Research Database (Denmark)

    Amon, Tod; Hulgaard, Henrik

    1999-01-01

    We extend the TSE~\\cite{Hulgaard95} timing analysis algorithm into the symbolic domain, that is, we allow symbolic variables to be used to specify unknown parameters of the model (essentially, unknown delays) and verification algorithms which are capable of identifying not just failure or success...

  1. Multivariate time-varying volatility modeling using probabilistic fuzzy systems

    NARCIS (Netherlands)

    Basturk, N.; Almeida, R.J.; Golan, R.; Kaymak, U.

    2016-01-01

    Methods to accurately analyze financial risk have drawn considerable attention in financial institutions. One difficulty in financial risk analysis is the fact that banks and other financial institutions invest in several assets which show time-varying volatilities and hence time-varying financial

  2. Visual pattern discovery in timed event data

    Science.gov (United States)

    Schaefer, Matthias; Wanner, Franz; Mansmann, Florian; Scheible, Christian; Stennett, Verity; Hasselrot, Anders T.; Keim, Daniel A.

    2011-01-01

    Business processes have tremendously changed the way large companies conduct their business: The integration of information systems into the workflows of their employees ensures a high service level and thus high customer satisfaction. One core aspect of business process engineering are events that steer the workflows and trigger internal processes. Strict requirements on interval-scaled temporal patterns, which are common in time series, are thereby released through the ordinal character of such events. It is this additional degree of freedom that opens unexplored possibilities for visualizing event data. In this paper, we present a flexible and novel system to find significant events, event clusters and event patterns. Each event is represented as a small rectangle, which is colored according to categorical, ordinal or intervalscaled metadata. Depending on the analysis task, different layout functions are used to highlight either the ordinal character of the data or temporal correlations. The system has built-in features for ordering customers or event groups according to the similarity of their event sequences, temporal gap alignment and stacking of co-occurring events. Two characteristically different case studies dealing with business process events and news articles demonstrate the capabilities of our system to explore event data.

  3. Dynamic Factor Analysis of Nonstationary Multivariate Time Series.

    Science.gov (United States)

    Molenaar, Peter C. M.; And Others

    1992-01-01

    The dynamic factor model proposed by P. C. Molenaar (1985) is exhibited, and a dynamic nonstationary factor model (DNFM) is constructed with latent factor series that have time-varying mean functions. The use of a DNFM is illustrated using data from a television viewing habits study. (SLD)

  4. Multivariate Prediction Equations for HbA1c Lowering, Weight Change, and Hypoglycemic Events Associated with Insulin Rescue Medication in Type 2 Diabetes Mellitus: Informing Economic Modeling.

    Science.gov (United States)

    Willis, Michael; Asseburg, Christian; Nilsson, Andreas; Johnsson, Kristina; Kartman, Bernt

    2017-03-01

    Type 2 diabetes mellitus (T2DM) is chronic and progressive and the cost-effectiveness of new treatment interventions must be established over long time horizons. Given the limited durability of drugs, assumptions regarding downstream rescue medication can drive results. Especially for insulin, for which treatment effects and adverse events are known to depend on patient characteristics, this can be problematic for health economic evaluation involving modeling. To estimate parsimonious multivariate equations of treatment effects and hypoglycemic event risks for use in parameterizing insulin rescue therapy in model-based cost-effectiveness analysis. Clinical evidence for insulin use in T2DM was identified in PubMed and from published reviews and meta-analyses. Study and patient characteristics and treatment effects and adverse event rates were extracted and the data used to estimate parsimonious treatment effect and hypoglycemic event risk equations using multivariate regression analysis. Data from 91 studies featuring 171 usable study arms were identified, mostly for premix and basal insulin types. Multivariate prediction equations for glycated hemoglobin A 1c lowering and weight change were estimated separately for insulin-naive and insulin-experienced patients. Goodness of fit (R 2 ) for both outcomes were generally good, ranging from 0.44 to 0.84. Multivariate prediction equations for symptomatic, nocturnal, and severe hypoglycemic events were also estimated, though considerable heterogeneity in definitions limits their usefulness. Parsimonious and robust multivariate prediction equations were estimated for glycated hemoglobin A 1c and weight change, separately for insulin-naive and insulin-experienced patients. Using these in economic simulation modeling in T2DM can improve realism and flexibility in modeling insulin rescue medication. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All

  5. A multivariate time series approach to modeling and forecasting demand in the emergency department.

    Science.gov (United States)

    Jones, Spencer S; Evans, R Scott; Allen, Todd L; Thomas, Alun; Haug, Peter J; Welch, Shari J; Snow, Gregory L

    2009-02-01

    The goals of this investigation were to study the temporal relationships between the demands for key resources in the emergency department (ED) and the inpatient hospital, and to develop multivariate forecasting models. Hourly data were collected from three diverse hospitals for the year 2006. Descriptive analysis and model fitting were carried out using graphical and multivariate time series methods. Multivariate models were compared to a univariate benchmark model in terms of their ability to provide out-of-sample forecasts of ED census and the demands for diagnostic resources. Descriptive analyses revealed little temporal interaction between the demand for inpatient resources and the demand for ED resources at the facilities considered. Multivariate models provided more accurate forecasts of ED census and of the demands for diagnostic resources. Our results suggest that multivariate time series models can be used to reliably forecast ED patient census; however, forecasts of the demands for diagnostic resources were not sufficiently reliable to be useful in the clinical setting.

  6. Training and evaluation of neural networks for multi-variate time series processing

    DEFF Research Database (Denmark)

    Fog, Torben L.; Larsen, Jan; Hansen, Lars Kai

    1995-01-01

    We study the training and generalization for multi-variate time series processing. It is suggested to used a quasi-maximum likelihood approach rather than the standard sum of squared errors, thus taking dependencies among the errors of the individual time series into account. This may lead...... to improved generalization performance. Further, we extend the optimal brain damage pruning technique to the multi-variate case. A key ingredient is an algebraic expression for the generalization ability of a multi-variate model. The variability of the suggested techniques are successfully demonstrated...

  7. Discrete Events as Units of Perceived Time

    Science.gov (United States)

    Liverence, Brandon M.; Scholl, Brian J.

    2012-01-01

    In visual images, we perceive both space (as a continuous visual medium) and objects (that inhabit space). Similarly, in dynamic visual experience, we perceive both continuous time and discrete events. What is the relationship between these units of experience? The most intuitive answer may be similar to the spatial case: time is perceived as an…

  8. Asymptotics for the conditional-sum-of-squares estimator in multivariate fractional time series models

    DEFF Research Database (Denmark)

    Ørregård Nielsen, Morten

    This paper proves consistency and asymptotic normality for the conditional-sum-of-squares estimator, which is equivalent to the conditional maximum likelihood estimator, in multivariate fractional time series models. The model is parametric and quite general, and, in particular, encompasses...... the multivariate non-cointegrated fractional ARIMA model. The novelty of the consistency result, in particular, is that it applies to a multivariate model and to an arbitrarily large set of admissible parameter values, for which the objective function does not converge uniformly in probablity, thus making...

  9. Multivariate evaluation of brain function by measuring regional cerebral blood flow and event-related potentials

    Energy Technology Data Exchange (ETDEWEB)

    Koga, Yoshihiko; Mochida, Masahiko; Shutara, Yoshikazu; Nakagawa, Kazumi [Kyorin Univ., Mitaka, Tokyo (Japan). School of Medicine; Nagata, Ken

    1998-07-01

    To measure the effect of events on human cognitive function, effects of odors by measurement regional cerebral blood flow (rCBF) and P300 were evaluated during the auditory odd-ball exercise. PET showed the increase in rCBF on the right hemisphere of the brain by coffee aroma. rCBF was measured by PET in 9 of right-handed healthy adults men, and P300 was by event-related potential (ERP) in each sex of 20 right-handed healthy adults. ERP showed the difference of the P300 amplitude between men and women, and showed the tendency, by odors except the lavender oil, that women had higher in the P300 amplitude than men. These results suggest the presence of effects on the cognitive function through emotional actions. Next, the relationship between rCBF and ERP were evaluated. The subjects were 9 of the right-handed healthy adults (average: 25.6{+-}3.4 years old). rCBF by PET and P300 amplitude by ERP were simultaneously recorded during the auditory odd-ball exercise using the tone-burst method (2 kHz of the low frequency aimed stimuli and 1 kHz of the high frequency non-aimed stimuli). The rCBF value was the highest at the transverse gyrus of Heschl and the lowest at the piriform cortex among 24 regions of interest (ROI) from both sides. The difference of P300 peak latent time among ROI was almost the same. The brain waves from Cz and Pz were similar and the average amplitude was highest at Pz. We found the high correlation in the right piriform cortex (Fz), and right (Fz, Cz) and left (Cz, Pz) transverse gyrus of Heschl between the P300 amplitude and rCBF. (K.H.)

  10. Multivariate evaluation of brain function by measuring regional cerebral blood flow and event-related potentials

    International Nuclear Information System (INIS)

    Koga, Yoshihiko; Mochida, Masahiko; Shutara, Yoshikazu; Nakagawa, Kazumi; Nagata, Ken

    1998-01-01

    To measure the effect of events on human cognitive function, effects of odors by measurement regional cerebral blood flow (rCBF) and P300 were evaluated during the auditory odd-ball exercise. PET showed the increase in rCBF on the right hemisphere of the brain by coffee aroma. rCBF was measured by PET in 9 of right-handed healthy adults men, and P300 was by event-related potential (ERP) in each sex of 20 right-handed healthy adults. ERP showed the difference of the P300 amplitude between men and women, and showed the tendency, by odors except the lavender oil, that women had higher in the P300 amplitude than men. These results suggest the presence of effects on the cognitive function through emotional actions. Next, the relationship between rCBF and ERP were evaluated. The subjects were 9 of the right-handed healthy adults (average: 25.6±3.4 years old). rCBF by PET and P300 amplitude by ERP were simultaneously recorded during the auditory odd-ball exercise using the tone-burst method (2 kHz of the low frequency aimed stimuli and 1 kHz of the high frequency non-aimed stimuli). The rCBF value was the highest at the transverse gyrus of Heschl and the lowest at the piriform cortex among 24 regions of interest (ROI) from both sides. The difference of P300 peak latent time among ROI was almost the same. The brain waves from Cz and Pz were similar and the average amplitude was highest at Pz. We found the high correlation in the right piriform cortex (Fz), and right (Fz, Cz) and left (Cz, Pz) transverse gyrus of Heschl between the P300 amplitude and rCBF. (K.H.)

  11. Automatically ordering events and times in text

    CERN Document Server

    Derczynski, Leon R A

    2017-01-01

    The book offers a detailed guide to temporal ordering, exploring open problems in the field and providing solutions and extensive analysis. It addresses the challenge of automatically ordering events and times in text. Aided by TimeML, it also describes and presents concepts relating to time in easy-to-compute terms. Working out the order that events and times happen has proven difficult for computers, since the language used to discuss time can be vague and complex. Mapping out these concepts for a computational system, which does not have its own inherent idea of time, is, unsurprisingly, tough. Solving this problem enables powerful systems that can plan, reason about events, and construct stories of their own accord, as well as understand the complex narratives that humans express and comprehend so naturally. This book presents a theory and data-driven analysis of temporal ordering, leading to the identification of exactly what is difficult about the task. It then proposes and evaluates machine-learning so...

  12. A Sandwich-Type Standard Error Estimator of SEM Models with Multivariate Time Series

    Science.gov (United States)

    Zhang, Guangjian; Chow, Sy-Miin; Ong, Anthony D.

    2011-01-01

    Structural equation models are increasingly used as a modeling tool for multivariate time series data in the social and behavioral sciences. Standard error estimators of SEM models, originally developed for independent data, require modifications to accommodate the fact that time series data are inherently dependent. In this article, we extend a…

  13. Time scales in tidal disruption events

    Directory of Open Access Journals (Sweden)

    Krolik J.

    2012-12-01

    Full Text Available We explore the temporal structure of tidal disruption events pointing out the corresponding transitions in the lightcurves of the thermal accretion disk and of the jet emerging from such events. The hydrodynamic time scale of the disrupted star is the minimal time scale of building up the accretion disk and the jet and it sets a limit on the rise time. This suggest that Swift J1644+57, that shows several flares with a rise time as short as a few hundred seconds could not have arisen from a tidal disruption of a main sequence star whose hydrodynamic time is a few hours. The disrupted object must have been a white dwarf. A second important time scale is the Eddington time in which the accretion rate changes form super to sub Eddington. It is possible that such a transition was observed in the light curve of Swift J2058+05. If correct this provides interesting constraints on the parameters of the system.

  14. NavyTime: Event and Time Ordering from Raw Text

    Science.gov (United States)

    2013-06-01

    time-time, and event-DCT (DCT is the doc- ument creation time). 74 Event Extraction F1 ATT-1 81.05 NavyTime 80.30 KUL 79.32 cleartk -4 & cleartk -3...71.88 KUL 70.17 cleartk 67.87 NavyTime 67.48 Temp:ESA 54.55 JU-CSE 52.69 Temp:WNet 50.00 FSS-TimEx 42.94 Tense and Aspect Attributes System Tense F1...Aspect F1 cleartk 62.18 70.40 NavyTime 61.67 72.43 ATT 59.47 73.50 JU-CSE 58.62 72.14 KUL 49.70 63.20 not all systems participated Figure 1: Complete

  15. Multivariate hydrological frequency analysis for extreme events using Archimedean copula. Case study: Lower Tunjuelo River basin (Colombia)

    Science.gov (United States)

    Gómez, Wilmar

    2017-04-01

    By analyzing the spatial and temporal variability of extreme precipitation events we can prevent or reduce the threat and risk. Many water resources projects require joint probability distributions of random variables such as precipitation intensity and duration, which can not be independent with each other. The problem of defining a probability model for observations of several dependent variables is greatly simplified by the joint distribution in terms of their marginal by taking copulas. This document presents a general framework set frequency analysis bivariate and multivariate using Archimedean copulas for extreme events of hydroclimatological nature such as severe storms. This analysis was conducted in the lower Tunjuelo River basin in Colombia for precipitation events. The results obtained show that for a joint study of the intensity-duration-frequency, IDF curves can be obtained through copulas and thus establish more accurate and reliable information from design storms and associated risks. It shows how the use of copulas greatly simplifies the study of multivariate distributions that introduce the concept of joint return period used to represent the needs of hydrological designs properly in frequency analysis.

  16. Rotation in the Dynamic Factor Modeling of Multivariate Stationary Time Series.

    Science.gov (United States)

    Molenaar, Peter C. M.; Nesselroade, John R.

    2001-01-01

    Proposes a special rotation procedure for the exploratory dynamic factor model for stationary multivariate time series. The rotation procedure applies separately to each univariate component series of a q-variate latent factor series and transforms such a component, initially represented as white noise, into a univariate moving-average.…

  17. Dynamic factor analysis in the frequency domain: causal modeling of multivariate psychophysiological time series

    NARCIS (Netherlands)

    Molenaar, P.C.M.

    1987-01-01

    Outlines a frequency domain analysis of the dynamic factor model and proposes a solution to the problem of constructing a causal filter of lagged factor loadings. The method is illustrated with applications to simulated and real multivariate time series. The latter applications involve topographic

  18. Rotation in the dynamic factor modeling of multivariate stationary time series.

    NARCIS (Netherlands)

    Molenaar, P.C.M.; Nesselroade, J.R.

    2001-01-01

    A special rotation procedure is proposed for the exploratory dynamic factor model for stationary multivariate time series. The rotation procedure applies separately to each univariate component series of a q-variate latent factor series and transforms such a component, initially represented as white

  19. Principal response curves: analysis of time-dependent multivariate responses of biological community to stress

    NARCIS (Netherlands)

    Brink, van den P.J.; Braak, ter C.J.F.

    1999-01-01

    In this paper a novel multivariate method is proposed for the analysis of community response data from designed experiments repeatedly sampled in time. The long-term effects of the insecticide chlorpyrifos on the invertebrate community and the dissolved oxygen (DO)–pH–alkalinity–conductivity

  20. Development and validation of multivariable predictive model for thromboembolic events in lymphoma patients.

    Science.gov (United States)

    Antic, Darko; Milic, Natasa; Nikolovski, Srdjan; Todorovic, Milena; Bila, Jelena; Djurdjevic, Predrag; Andjelic, Bosko; Djurasinovic, Vladislava; Sretenovic, Aleksandra; Vukovic, Vojin; Jelicic, Jelena; Hayman, Suzanne; Mihaljevic, Biljana

    2016-10-01

    Lymphoma patients are at increased risk of thromboembolic events but thromboprophylaxis in these patients is largely underused. We sought to develop and validate a simple model, based on individual clinical and laboratory patient characteristics that would designate lymphoma patients at risk for thromboembolic event. The study population included 1,820 lymphoma patients who were treated in the Lymphoma Departments at the Clinics of Hematology, Clinical Center of Serbia and Clinical Center Kragujevac. The model was developed using data from a derivation cohort (n = 1,236), and further assessed in the validation cohort (n = 584). Sixty-five patients (5.3%) in the derivation cohort and 34 (5.8%) patients in the validation cohort developed thromboembolic events. The variables independently associated with risk for thromboembolism were: previous venous and/or arterial events, mediastinal involvement, BMI>30 kg/m(2) , reduced mobility, extranodal localization, development of neutropenia and hemoglobin level 3). For patients classified at risk (intermediate and high-risk scores), the model produced negative predictive value of 98.5%, positive predictive value of 25.1%, sensitivity of 75.4%, and specificity of 87.5%. A high-risk score had positive predictive value of 65.2%. The diagnostic performance measures retained similar values in the validation cohort. Developed prognostic Thrombosis Lymphoma - ThroLy score is more specific for lymphoma patients than any other available score targeting thrombosis in cancer patients. Am. J. Hematol. 91:1014-1019, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  1. Multivariate time series clustering on geophysical data recorded at Mt. Etna from 1996 to 2003

    Science.gov (United States)

    Di Salvo, Roberto; Montalto, Placido; Nunnari, Giuseppe; Neri, Marco; Puglisi, Giuseppe

    2013-02-01

    Time series clustering is an important task in data analysis issues in order to extract implicit, previously unknown, and potentially useful information from a large collection of data. Finding useful similar trends in multivariate time series represents a challenge in several areas including geophysics environment research. While traditional time series analysis methods deal only with univariate time series, multivariate time series analysis is a more suitable approach in the field of research where different kinds of data are available. Moreover, the conventional time series clustering techniques do not provide desired results for geophysical datasets due to the huge amount of data whose sampling rate is different according to the nature of signal. In this paper, a novel approach concerning geophysical multivariate time series clustering is proposed using dynamic time series segmentation and Self Organizing Maps techniques. This method allows finding coupling among trends of different geophysical data recorded from monitoring networks at Mt. Etna spanning from 1996 to 2003, when the transition from summit eruptions to flank eruptions occurred. This information can be used to carry out a more careful evaluation of the state of volcano and to define potential hazard assessment at Mt. Etna.

  2. Testing for Change in Mean of Independent Multivariate Observations with Time Varying Covariance

    Directory of Open Access Journals (Sweden)

    Mohamed Boutahar

    2012-01-01

    Full Text Available We consider a nonparametric CUSUM test for change in the mean of multivariate time series with time varying covariance. We prove that under the null, the test statistic has a Kolmogorov limiting distribution. The asymptotic consistency of the test against a large class of alternatives which contains abrupt, smooth and continuous changes is established. We also perform a simulation study to analyze the size distortion and the power of the proposed test.

  3. Multivariate pattern analysis of MEG and EEG: A comparison of representational structure in time and space.

    Science.gov (United States)

    Cichy, Radoslaw Martin; Pantazis, Dimitrios

    2017-09-01

    Multivariate pattern analysis of magnetoencephalography (MEG) and electroencephalography (EEG) data can reveal the rapid neural dynamics underlying cognition. However, MEG and EEG have systematic differences in sampling neural activity. This poses the question to which degree such measurement differences consistently bias the results of multivariate analysis applied to MEG and EEG activation patterns. To investigate, we conducted a concurrent MEG/EEG study while participants viewed images of everyday objects. We applied multivariate classification analyses to MEG and EEG data, and compared the resulting time courses to each other, and to fMRI data for an independent evaluation in space. We found that both MEG and EEG revealed the millisecond spatio-temporal dynamics of visual processing with largely equivalent results. Beyond yielding convergent results, we found that MEG and EEG also captured partly unique aspects of visual representations. Those unique components emerged earlier in time for MEG than for EEG. Identifying the sources of those unique components with fMRI, we found the locus for both MEG and EEG in high-level visual cortex, and in addition for MEG in low-level visual cortex. Together, our results show that multivariate analyses of MEG and EEG data offer a convergent and complimentary view on neural processing, and motivate the wider adoption of these methods in both MEG and EEG research. Copyright © 2017 Elsevier Inc. All rights reserved.

  4. Interval-Censored Time-to-Event Data Methods and Applications

    CERN Document Server

    Chen, Ding-Geng

    2012-01-01

    Interval-Censored Time-to-Event Data: Methods and Applications collects the most recent techniques, models, and computational tools for interval-censored time-to-event data. Top biostatisticians from academia, biopharmaceutical industries, and government agencies discuss how these advances are impacting clinical trials and biomedical research. Divided into three parts, the book begins with an overview of interval-censored data modeling, including nonparametric estimation, survival functions, regression analysis, multivariate data analysis, competing risks analysis, and other models for interva

  5. Bayesian inference for multivariate point processes observed at sparsely distributed times

    DEFF Research Database (Denmark)

    Rasmussen, Jakob Gulddahl; Møller, Jesper; Aukema, B.H.

    We consider statistical and computational aspects of simulation-based Bayesian inference for a multivariate point process which is only observed at sparsely distributed times. For specicity we consider a particular data set which has earlier been analyzed by a discrete time model involving unknown...... normalizing constants. We discuss the advantages and disadvantages of using continuous time processes compared to discrete time processes in the setting of the present paper as well as other spatial-temporal situations. Keywords: Bark beetle, conditional intensity, forest entomology, Markov chain Monte Carlo...

  6. Multivariate stochastic analysis for Monthly hydrological time series at Cuyahoga River Basin

    Science.gov (United States)

    zhang, L.

    2011-12-01

    Copula has become a very powerful statistic and stochastic methodology in case of the multivariate analysis in Environmental and Water resources Engineering. In recent years, the popular one-parameter Archimedean copulas, e.g. Gumbel-Houggard copula, Cook-Johnson copula, Frank copula, the meta-elliptical copula, e.g. Gaussian Copula, Student-T copula, etc. have been applied in multivariate hydrological analyses, e.g. multivariate rainfall (rainfall intensity, duration and depth), flood (peak discharge, duration and volume), and drought analyses (drought length, mean and minimum SPI values, and drought mean areal extent). Copula has also been applied in the flood frequency analysis at the confluences of river systems by taking into account the dependence among upstream gauge stations rather than by using the hydrological routing technique. In most of the studies above, the annual time series have been considered as stationary signal which the time series have been assumed as independent identically distributed (i.i.d.) random variables. But in reality, hydrological time series, especially the daily and monthly hydrological time series, cannot be considered as i.i.d. random variables due to the periodicity existed in the data structure. Also, the stationary assumption is also under question due to the Climate Change and Land Use and Land Cover (LULC) change in the fast years. To this end, it is necessary to revaluate the classic approach for the study of hydrological time series by relaxing the stationary assumption by the use of nonstationary approach. Also as to the study of the dependence structure for the hydrological time series, the assumption of same type of univariate distribution also needs to be relaxed by adopting the copula theory. In this paper, the univariate monthly hydrological time series will be studied through the nonstationary time series analysis approach. The dependence structure of the multivariate monthly hydrological time series will be

  7. Constructing networks from a dynamical system perspective for multivariate nonlinear time series.

    Science.gov (United States)

    Nakamura, Tomomichi; Tanizawa, Toshihiro; Small, Michael

    2016-03-01

    We describe a method for constructing networks for multivariate nonlinear time series. We approach the interaction between the various scalar time series from a deterministic dynamical system perspective and provide a generic and algorithmic test for whether the interaction between two measured time series is statistically significant. The method can be applied even when the data exhibit no obvious qualitative similarity: a situation in which the naive method utilizing the cross correlation function directly cannot correctly identify connectivity. To establish the connectivity between nodes we apply the previously proposed small-shuffle surrogate (SSS) method, which can investigate whether there are correlation structures in short-term variabilities (irregular fluctuations) between two data sets from the viewpoint of deterministic dynamical systems. The procedure to construct networks based on this idea is composed of three steps: (i) each time series is considered as a basic node of a network, (ii) the SSS method is applied to verify the connectivity between each pair of time series taken from the whole multivariate time series, and (iii) the pair of nodes is connected with an undirected edge when the null hypothesis cannot be rejected. The network constructed by the proposed method indicates the intrinsic (essential) connectivity of the elements included in the system or the underlying (assumed) system. The method is demonstrated for numerical data sets generated by known systems and applied to several experimental time series.

  8. Multivariate statistical analysis for x-ray photoelectron spectroscopy spectral imaging: Effect of image acquisition time

    International Nuclear Information System (INIS)

    Peebles, D.E.; Ohlhausen, J.A.; Kotula, P.G.; Hutton, S.; Blomfield, C.

    2004-01-01

    The acquisition of spectral images for x-ray photoelectron spectroscopy (XPS) is a relatively new approach, although it has been used with other analytical spectroscopy tools for some time. This technique provides full spectral information at every pixel of an image, in order to provide a complete chemical mapping of the imaged surface area. Multivariate statistical analysis techniques applied to the spectral image data allow the determination of chemical component species, and their distribution and concentrations, with minimal data acquisition and processing times. Some of these statistical techniques have proven to be very robust and efficient methods for deriving physically realistic chemical components without input by the user other than the spectral matrix itself. The benefits of multivariate analysis of the spectral image data include significantly improved signal to noise, improved image contrast and intensity uniformity, and improved spatial resolution - which are achieved due to the effective statistical aggregation of the large number of often noisy data points in the image. This work demonstrates the improvements in chemical component determination and contrast, signal-to-noise level, and spatial resolution that can be obtained by the application of multivariate statistical analysis to XPS spectral images

  9. Uni- and multi-variable modelling of flood losses: experiences gained from the Secchia river inundation event.

    Science.gov (United States)

    Carisi, Francesca; Domeneghetti, Alessio; Kreibich, Heidi; Schröter, Kai; Castellarin, Attilio

    2017-04-01

    Flood risk is function of flood hazard and vulnerability, therefore its accurate assessment depends on a reliable quantification of both factors. The scientific literature proposes a number of objective and reliable methods for assessing flood hazard, yet it highlights a limited understanding of the fundamental damage processes. Loss modelling is associated with large uncertainty which is, among other factors, due to a lack of standard procedures; for instance, flood losses are often estimated based on damage models derived in completely different contexts (i.e. different countries or geographical regions) without checking its applicability, or by considering only one explanatory variable (i.e. typically water depth). We consider the Secchia river flood event of January 2014, when a sudden levee-breach caused the inundation of nearly 200 km2 in Northern Italy. In the aftermath of this event, local authorities collected flood loss data, together with additional information on affected private households and industrial activities (e.g. buildings surface and economic value, number of company's employees and others). Based on these data we implemented and compared a quadratic-regression damage function, with water depth as the only explanatory variable, and a multi-variable model that combines multiple regression trees and considers several explanatory variables (i.e. bagging decision trees). Our results show the importance of data collection revealing that (1) a simple quadratic regression damage function based on empirical data from the study area can be significantly more accurate than literature damage-models derived for a different context and (2) multi-variable modelling may outperform the uni-variable approach, yet it is more difficult to develop and apply due to a much higher demand of detailed data.

  10. Hierarchical Hidden Markov Models for Multivariate Integer-Valued Time-Series

    DEFF Research Database (Denmark)

    Catania, Leopoldo; Di Mari, Roberto

    2018-01-01

    We propose a new flexible dynamic model for multivariate nonnegative integer-valued time-series. Observations are assumed to depend on the realization of two additional unobserved integer-valued stochastic variables which control for the time-and cross-dependence of the data. An Expectation......-Maximization algorithm for maximum likelihood estimation of the model's parameters is derived. We provide conditional and unconditional (cross)-moments implied by the model, as well as the limiting distribution of the series. A Monte Carlo experiment investigates the finite sample properties of our estimation...

  11. Assessment of Multivariate Neural Time Series by Phase Synchrony Clustering in a Time-Frequency-Topography Representation

    Directory of Open Access Journals (Sweden)

    M. A. Porta-Garcia

    2018-01-01

    Full Text Available Most EEG phase synchrony measures are of bivariate nature. Those that are multivariate focus on producing global indices of the synchronization state of the system. Thus, better descriptions of spatial and temporal local interactions are still in demand. A framework for characterization of phase synchrony relationships between multivariate neural time series is presented, applied either in a single epoch or over an intertrial assessment, relying on a proposed clustering algorithm, termed Multivariate Time Series Clustering by Phase Synchrony, which generates fuzzy clusters for each multivalued time sample and thereupon obtains hard clusters according to a circular variance threshold; such cluster modes are then depicted in Time-Frequency-Topography representations of synchrony state beyond mere global indices. EEG signals from P300 Speller sessions of four subjects were analyzed, obtaining useful insights of synchrony patterns related to the ERP and even revealing steady-state artifacts at 7.6 Hz. Further, contrast maps of Levenshtein Distance highlight synchrony differences between ERP and no-ERP epochs, mainly at delta and theta bands. The framework, which is not limited to one synchrony measure, allows observing dynamics of phase changes and interactions among channels and can be applied to analyze other cognitive states rather than ERP versus no ERP.

  12. Online Identification of Multivariable Discrete Time Delay Systems Using a Recursive Least Square Algorithm

    Directory of Open Access Journals (Sweden)

    Saïda Bedoui

    2013-01-01

    Full Text Available This paper addresses the problem of simultaneous identification of linear discrete time delay multivariable systems. This problem involves both the estimation of the time delays and the dynamic parameters matrices. In fact, we suggest a new formulation of this problem allowing defining the time delay and the dynamic parameters in the same estimated vector and building the corresponding observation vector. Then, we use this formulation to propose a new method to identify the time delays and the parameters of these systems using the least square approach. Convergence conditions and statistics properties of the proposed method are also developed. Simulation results are presented to illustrate the performance of the proposed method. An application of the developed approach to compact disc player arm is also suggested in order to validate simulation results.

  13. Multiband Prediction Model for Financial Time Series with Multivariate Empirical Mode Decomposition

    Directory of Open Access Journals (Sweden)

    Md. Rabiul Islam

    2012-01-01

    Full Text Available This paper presents a subband approach to financial time series prediction. Multivariate empirical mode decomposition (MEMD is employed here for multiband representation of multichannel financial time series together. Autoregressive moving average (ARMA model is used in prediction of individual subband of any time series data. Then all the predicted subband signals are summed up to obtain the overall prediction. The ARMA model works better for stationary signal. With multiband representation, each subband becomes a band-limited (narrow band signal and hence better prediction is achieved. The performance of the proposed MEMD-ARMA model is compared with classical EMD, discrete wavelet transform (DWT, and with full band ARMA model in terms of signal-to-noise ratio (SNR and mean square error (MSE between the original and predicted time series. The simulation results show that the MEMD-ARMA-based method performs better than the other methods.

  14. Asymptotic theory for the sample covariance matrix of a heavy-tailed multivariate time series

    DEFF Research Database (Denmark)

    Davis, Richard A.; Mikosch, Thomas Valentin; Pfaffel, Olivier

    2016-01-01

    In this paper we give an asymptotic theory for the eigenvalues of the sample covariance matrix of a multivariate time series. The time series constitutes a linear process across time and between components. The input noise of the linear process has regularly varying tails with index α∈(0,4) in...... particular, the time series has infinite fourth moment. We derive the limiting behavior for the largest eigenvalues of the sample covariance matrix and show point process convergence of the normalized eigenvalues. The limiting process has an explicit form involving points of a Poisson process and eigenvalues...... of a non-negative definite matrix. Based on this convergence we derive limit theory for a host of other continuous functionals of the eigenvalues, including the joint convergence of the largest eigenvalues, the joint convergence of the largest eigenvalue and the trace of the sample covariance matrix...

  15. Identification of Time Varying Civil Engineering Structures using Multivariate Recursive Time Domain Models

    DEFF Research Database (Denmark)

    Andersen, P.; Skjærbæk, P. S.; Kirkegaard, Poul Henning

    with the smoothed quanties which have been obtained from SARCOF. The results show the usefulness of the technique for identification of a time varying civil engineering structure. It is found that all the techniques give reliable estiates of the frequencies of the two lowest modes and the first mode shape. Only...

  16. Understanding characteristics in multivariate traffic flow time series from complex network structure

    Science.gov (United States)

    Yan, Ying; Zhang, Shen; Tang, Jinjun; Wang, Xiaofei

    2017-07-01

    Discovering dynamic characteristics in traffic flow is the significant step to design effective traffic managing and controlling strategy for relieving traffic congestion in urban cities. A new method based on complex network theory is proposed to study multivariate traffic flow time series. The data were collected from loop detectors on freeway during a year. In order to construct complex network from original traffic flow, a weighted Froenius norm is adopt to estimate similarity between multivariate time series, and Principal Component Analysis is implemented to determine the weights. We discuss how to select optimal critical threshold for networks at different hour in term of cumulative probability distribution of degree. Furthermore, two statistical properties of networks: normalized network structure entropy and cumulative probability of degree, are utilized to explore hourly variation in traffic flow. The results demonstrate these two statistical quantities express similar pattern to traffic flow parameters with morning and evening peak hours. Accordingly, we detect three traffic states: trough, peak and transitional hours, according to the correlation between two aforementioned properties. The classifying results of states can actually represent hourly fluctuation in traffic flow by analyzing annual average hourly values of traffic volume, occupancy and speed in corresponding hours.

  17. Investigation of time and weather effects on crash types using full Bayesian multivariate Poisson lognormal models.

    Science.gov (United States)

    El-Basyouny, Karim; Barua, Sudip; Islam, Md Tazul

    2014-12-01

    Previous research shows that various weather elements have significant effects on crash occurrence and risk; however, little is known about how these elements affect different crash types. Consequently, this study investigates the impact of weather elements and sudden extreme snow or rain weather changes on crash type. Multivariate models were used for seven crash types using five years of daily weather and crash data collected for the entire City of Edmonton. In addition, the yearly trend and random variation of parameters across the years were analyzed by using four different modeling formulations. The proposed models were estimated in a full Bayesian context via Markov Chain Monte Carlo simulation. The multivariate Poisson lognormal model with yearly varying coefficients provided the best fit for the data according to Deviance Information Criteria. Overall, results showed that temperature and snowfall were statistically significant with intuitive signs (crashes decrease with increasing temperature; crashes increase as snowfall intensity increases) for all crash types, while rainfall was mostly insignificant. Previous snow showed mixed results, being statistically significant and positively related to certain crash types, while negatively related or insignificant in other cases. Maximum wind gust speed was found mostly insignificant with a few exceptions that were positively related to crash type. Major snow or rain events following a dry weather condition were highly significant and positively related to three crash types: Follow-Too-Close, Stop-Sign-Violation, and Ran-Off-Road crashes. The day-of-the-week dummy variables were statistically significant, indicating a possible weekly variation in exposure. Transportation authorities might use the above results to improve road safety by providing drivers with information regarding the risk of certain crash types for a particular weather condition. Copyright © 2014 Elsevier Ltd. All rights reserved.

  18. Real time computer control of a nonlinear Multivariable System via Linearization and Stability Analysis

    International Nuclear Information System (INIS)

    Raza, K.S.M.

    2004-01-01

    This paper demonstrates that if a complicated nonlinear, non-square, state-coupled multi variable system is smartly linearized and subjected to a thorough stability analysis then we can achieve our design objectives via a controller which will be quite simple (in term of resource usage and execution time) and very efficient (in terms of robustness). Further the aim is to implement this controller via computer in a real time environment. Therefore first a nonlinear mathematical model of the system is achieved. An intelligent work is done to decouple the multivariable system. Linearization and stability analysis techniques are employed for the development of a linearized and mathematically sound control law. Nonlinearities like the saturation in actuators are also been catered. The controller is then discretized using Runge-Kutta integration. Finally the discretized control law is programmed in a computer in a real time environment. The programme is done in RT -Linux using GNU C for the real time realization of the control scheme. The real time processes, like sampling and controlled actuation, and the non real time processes, like graphical user interface and display, are programmed as different tasks. The issue of inter process communication, between real time and non real time task is addressed quite carefully. The results of this research pursuit are presented graphically. (author)

  19. Ecological prediction with nonlinear multivariate time-frequency functional data models

    Science.gov (United States)

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

    2013-01-01

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

  20. Detecting a currency’s dominance using multivariate time series analysis

    Science.gov (United States)

    Syahidah Yusoff, Nur; Sharif, Shamshuritawati

    2017-09-01

    A currency exchange rate is the price of one country’s currency in terms of another country’s currency. There are four different prices; opening, closing, highest, and lowest can be achieved from daily trading activities. In the past, a lot of studies have been carried out by using closing price only. However, those four prices are interrelated to each other. Thus, the multivariate time series can provide more information than univariate time series. Therefore, the enthusiasm of this paper is to compare the results of two different approaches, which are mean vector and Escoufier’s RV coefficient in constructing similarity matrices of 20 world currencies. Consequently, both matrices are used to substitute the correlation matrix required by network topology. With the help of degree centrality measure, we can detect the currency’s dominance for both networks. The pros and cons for both approaches will be presented at the end of this paper.

  1. Time-series panel analysis (TSPA): multivariate modeling of temporal associations in psychotherapy process.

    Science.gov (United States)

    Ramseyer, Fabian; Kupper, Zeno; Caspar, Franz; Znoj, Hansjörg; Tschacher, Wolfgang

    2014-10-01

    Processes occurring in the course of psychotherapy are characterized by the simple fact that they unfold in time and that the multiple factors engaged in change processes vary highly between individuals (idiographic phenomena). Previous research, however, has neglected the temporal perspective by its traditional focus on static phenomena, which were mainly assessed at the group level (nomothetic phenomena). To support a temporal approach, the authors introduce time-series panel analysis (TSPA), a statistical methodology explicitly focusing on the quantification of temporal, session-to-session aspects of change in psychotherapy. TSPA-models are initially built at the level of individuals and are subsequently aggregated at the group level, thus allowing the exploration of prototypical models. TSPA is based on vector auto-regression (VAR), an extension of univariate auto-regression models to multivariate time-series data. The application of TSPA is demonstrated in a sample of 87 outpatient psychotherapy patients who were monitored by postsession questionnaires. Prototypical mechanisms of change were derived from the aggregation of individual multivariate models of psychotherapy process. In a 2nd step, the associations between mechanisms of change (TSPA) and pre- to postsymptom change were explored. TSPA allowed a prototypical process pattern to be identified, where patient's alliance and self-efficacy were linked by a temporal feedback-loop. Furthermore, therapist's stability over time in both mastery and clarification interventions was positively associated with better outcomes. TSPA is a statistical tool that sheds new light on temporal mechanisms of change. Through this approach, clinicians may gain insight into prototypical patterns of change in psychotherapy. PsycINFO Database Record (c) 2014 APA, all rights reserved.

  2. A Personalized Predictive Framework for Multivariate Clinical Time Series via Adaptive Model Selection.

    Science.gov (United States)

    Liu, Zitao; Hauskrecht, Milos

    2017-11-01

    Building of an accurate predictive model of clinical time series for a patient is critical for understanding of the patient condition, its dynamics, and optimal patient management. Unfortunately, this process is not straightforward. First, patient-specific variations are typically large and population-based models derived or learned from many different patients are often unable to support accurate predictions for each individual patient. Moreover, time series observed for one patient at any point in time may be too short and insufficient to learn a high-quality patient-specific model just from the patient's own data. To address these problems we propose, develop and experiment with a new adaptive forecasting framework for building multivariate clinical time series models for a patient and for supporting patient-specific predictions. The framework relies on the adaptive model switching approach that at any point in time selects the most promising time series model out of the pool of many possible models, and consequently, combines advantages of the population, patient-specific and short-term individualized predictive models. We demonstrate that the adaptive model switching framework is very promising approach to support personalized time series prediction, and that it is able to outperform predictions based on pure population and patient-specific models, as well as, other patient-specific model adaptation strategies.

  3. Modeling multivariate time series on manifolds with skew radial basis functions.

    Science.gov (United States)

    Jamshidi, Arta A; Kirby, Michael J

    2011-01-01

    We present an approach for constructing nonlinear empirical mappings from high-dimensional domains to multivariate ranges. We employ radial basis functions and skew radial basis functions for constructing a model using data that are potentially scattered or sparse. The algorithm progresses iteratively, adding a new function at each step to refine the model. The placement of the functions is driven by a statistical hypothesis test that accounts for correlation in the multivariate range variables. The test is applied on training and validation data and reveals nonstatistical or geometric structure when it fails. At each step, the added function is fit to data contained in a spatiotemporally defined local region to determine the parameters--in particular, the scale of the local model. The scale of the function is determined by the zero crossings of the autocorrelation function of the residuals. The model parameters and the number of basis functions are determined automatically from the given data, and there is no need to initialize any ad hoc parameters save for the selection of the skew radial basis functions. Compactly supported skew radial basis functions are employed to improve model accuracy, order, and convergence properties. The extension of the algorithm to higher-dimensional ranges produces reduced-order models by exploiting the existence of correlation in the range variable data. Structure is tested not just in a single time series but between all pairs of time series. We illustrate the new methodologies using several illustrative problems, including modeling data on manifolds and the prediction of chaotic time series.

  4. Testing the structure of earthquake networks from multivariate time series of successive main shocks in Greece

    Science.gov (United States)

    Chorozoglou, D.; Kugiumtzis, D.; Papadimitriou, E.

    2018-06-01

    The seismic hazard assessment in the area of Greece is attempted by studying the earthquake network structure, such as small-world and random. In this network, a node represents a seismic zone in the study area and a connection between two nodes is given by the correlation of the seismic activity of two zones. To investigate the network structure, and particularly the small-world property, the earthquake correlation network is compared with randomized ones. Simulations on multivariate time series of different length and number of variables show that for the construction of randomized networks the method randomizing the time series performs better than methods randomizing directly the original network connections. Based on the appropriate randomization method, the network approach is applied to time series of earthquakes that occurred between main shocks in the territory of Greece spanning the period 1999-2015. The characterization of networks on sliding time windows revealed that small-world structure emerges in the last time interval, shortly before the main shock.

  5. Real time optimization of solar powered direct contact membrane distillation based on multivariable extremum seeking

    KAUST Repository

    Karam, Ayman M.; Laleg-Kirati, Taous-Meriem

    2015-01-01

    This paper presents a real time optimization scheme for a solar powered direct contact membrane distillation (DCMD) water desalination system. The sun and weather conditions vary and are inconsistent throughout the day. Therefore, the solar powered DCMD feed inlet temperature is never constant, which influences the distilled water flux. The problem of DCMD process optimization has not been studied enough. In this work, the response of the process under various feed inlet temperatures is investigated, which demonstrates the need for an optimal controller. To address this issue, we propose a multivariable Newton-based extremum seeking controller which optimizes the inlet feed and permeate mass flow rates as the feed inlet temperature varies. Results are presented and discussed for a realistic temperature profile.

  6. Forecasting electric vehicles sales with univariate and multivariate time series models: The case of China.

    Science.gov (United States)

    Zhang, Yong; Zhong, Miner; Geng, Nana; Jiang, Yunjian

    2017-01-01

    The market demand for electric vehicles (EVs) has increased in recent years. Suitable models are necessary to understand and forecast EV sales. This study presents a singular spectrum analysis (SSA) as a univariate time-series model and vector autoregressive model (VAR) as a multivariate model. Empirical results suggest that SSA satisfactorily indicates the evolving trend and provides reasonable results. The VAR model, which comprised exogenous parameters related to the market on a monthly basis, can significantly improve the prediction accuracy. The EV sales in China, which are categorized into battery and plug-in EVs, are predicted in both short term (up to December 2017) and long term (up to 2020), as statistical proofs of the growth of the Chinese EV industry.

  7. Time-varying correlations in global real estate markets: A multivariate GARCH with spatial effects approach

    Science.gov (United States)

    Gu, Huaying; Liu, Zhixue; Weng, Yingliang

    2017-04-01

    The present study applies the multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) with spatial effects approach for the analysis of the time-varying conditional correlations and contagion effects among global real estate markets. A distinguishing feature of the proposed model is that it can simultaneously capture the spatial interactions and the dynamic conditional correlations compared with the traditional MGARCH models. Results reveal that the estimated dynamic conditional correlations have exhibited significant increases during the global financial crisis from 2007 to 2009, thereby suggesting contagion effects among global real estate markets. The analysis further indicates that the returns of the regional real estate markets that are in close geographic and economic proximities exhibit strong co-movement. In addition, evidence of significantly positive leverage effects in global real estate markets is also determined. The findings have significant implications on global portfolio diversification opportunities and risk management practices.

  8. Real time optimization of solar powered direct contact membrane distillation based on multivariable extremum seeking

    KAUST Repository

    Karam, Ayman M.

    2015-09-21

    This paper presents a real time optimization scheme for a solar powered direct contact membrane distillation (DCMD) water desalination system. The sun and weather conditions vary and are inconsistent throughout the day. Therefore, the solar powered DCMD feed inlet temperature is never constant, which influences the distilled water flux. The problem of DCMD process optimization has not been studied enough. In this work, the response of the process under various feed inlet temperatures is investigated, which demonstrates the need for an optimal controller. To address this issue, we propose a multivariable Newton-based extremum seeking controller which optimizes the inlet feed and permeate mass flow rates as the feed inlet temperature varies. Results are presented and discussed for a realistic temperature profile.

  9. Multivariate analyses of small theropod dinosaur teeth and implications for paleoecological turnover through time.

    Directory of Open Access Journals (Sweden)

    Derek W Larson

    Full Text Available Isolated small theropod teeth are abundant in vertebrate microfossil assemblages, and are frequently used in studies of species diversity in ancient ecosystems. However, determining the taxonomic affinities of these teeth is problematic due to an absence of associated diagnostic skeletal material. Species such as Dromaeosaurus albertensis, Richardoestesia gilmorei, and Saurornitholestes langstoni are known from skeletal remains that have been recovered exclusively from the Dinosaur Park Formation (Campanian. It is therefore likely that teeth from different formations widely disparate in age or geographic position are not referable to these species. Tooth taxa without any associated skeletal material, such as Paronychodon lacustris and Richardoestesia isosceles, have also been identified from multiple localities of disparate ages throughout the Late Cretaceous. To address this problem, a dataset of measurements of 1183 small theropod teeth (the most specimen-rich theropod tooth dataset ever constructed from North America ranging in age from Santonian through Maastrichtian were analyzed using multivariate statistical methods: canonical variate analysis, pairwise discriminant function analysis, and multivariate analysis of variance. The results indicate that teeth referred to the same taxon from different formations are often quantitatively distinct. In contrast, isolated teeth found in time equivalent formations are not quantitatively distinguishable from each other. These results support the hypothesis that small theropod taxa, like other dinosaurs in the Late Cretaceous, tend to be exclusive to discrete host formations. The methods outlined have great potential for future studies of isolated teeth worldwide, and may be the most useful non-destructive technique known of extracting the most data possible from isolated and fragmentary specimens. The ability to accurately assess species diversity and turnover through time based on isolated teeth

  10. Multivariate Analyses of Small Theropod Dinosaur Teeth and Implications for Paleoecological Turnover through Time

    Science.gov (United States)

    Larson, Derek W.; Currie, Philip J.

    2013-01-01

    Isolated small theropod teeth are abundant in vertebrate microfossil assemblages, and are frequently used in studies of species diversity in ancient ecosystems. However, determining the taxonomic affinities of these teeth is problematic due to an absence of associated diagnostic skeletal material. Species such as Dromaeosaurus albertensis, Richardoestesia gilmorei, and Saurornitholestes langstoni are known from skeletal remains that have been recovered exclusively from the Dinosaur Park Formation (Campanian). It is therefore likely that teeth from different formations widely disparate in age or geographic position are not referable to these species. Tooth taxa without any associated skeletal material, such as Paronychodon lacustris and Richardoestesia isosceles, have also been identified from multiple localities of disparate ages throughout the Late Cretaceous. To address this problem, a dataset of measurements of 1183 small theropod teeth (the most specimen-rich theropod tooth dataset ever constructed) from North America ranging in age from Santonian through Maastrichtian were analyzed using multivariate statistical methods: canonical variate analysis, pairwise discriminant function analysis, and multivariate analysis of variance. The results indicate that teeth referred to the same taxon from different formations are often quantitatively distinct. In contrast, isolated teeth found in time equivalent formations are not quantitatively distinguishable from each other. These results support the hypothesis that small theropod taxa, like other dinosaurs in the Late Cretaceous, tend to be exclusive to discrete host formations. The methods outlined have great potential for future studies of isolated teeth worldwide, and may be the most useful non-destructive technique known of extracting the most data possible from isolated and fragmentary specimens. The ability to accurately assess species diversity and turnover through time based on isolated teeth will help illuminate

  11. Modeling discrete time-to-event data

    CERN Document Server

    Tutz, Gerhard

    2016-01-01

    This book focuses on statistical methods for the analysis of discrete failure times. Failure time analysis is one of the most important fields in statistical research, with applications affecting a wide range of disciplines, in particular, demography, econometrics, epidemiology and clinical research. Although there are a large variety of statistical methods for failure time analysis, many techniques are designed for failure times that are measured on a continuous scale. In empirical studies, however, failure times are often discrete, either because they have been measured in intervals (e.g., quarterly or yearly) or because they have been rounded or grouped. The book covers well-established methods like life-table analysis and discrete hazard regression models, but also introduces state-of-the art techniques for model evaluation, nonparametric estimation and variable selection. Throughout, the methods are illustrated by real life applications, and relationships to survival analysis in continuous time are expla...

  12. A simple ergonomic measure reduces fluoroscopy time during ERCP: A multivariate analysis.

    Science.gov (United States)

    Jowhari, Fahd; Hopman, Wilma M; Hookey, Lawrence

    2017-03-01

    Background and study aims  Endoscopic retrograde cholangiopancreatgraphy (ERCP) carries a radiation risk to patients undergoing the procedure and the team performing it. Fluoroscopy time (FT) has been shown to have a linear relationship with radiation exposure during ERCP. Recent modifications to our ERCP suite design were felt to impact fluoroscopy time and ergonomics. This multivariate analysis was therefore undertaken to investigate these effects, and to identify and validate various clinical, procedural and ergonomic factors influencing the total fluoroscopy time during ERCP. This would better assist clinicians with predicting prolonged fluoroscopic durations and to undertake relevant precautions accordingly. Patients and methods  A retrospective analysis of 299 ERCPs performed by 4 endoscopists over an 18-month period, at a single tertiary care center was conducted. All inpatients/outpatients (121 males, 178 females) undergoing ERCP for any clinical indication from January 2012 to June 2013 in the chosen ERCP suite were included in the study. Various predetermined clinical, procedural and ergonomic factors were obtained via chart review. Univariate analyses identified factors to be included in the multivariate regression model with FT as the dependent variable. Results  Bringing the endoscopy and fluoroscopy screens next to each other was associated with a significantly lesser FT than when the screens were separated further (-1.4 min, P  = 0.026). Other significant factors associated with a prolonged FT included having a prior ERCP (+ 1.4 min, P  = 0.031), and more difficult procedures (+ 4.2 min for each level of difficulty, P  < 0.001). ERCPs performed by high-volume endoscopists used lesser FT vs. low-volume endoscopists (-1.82, P = 0.015). Conclusions  Our study has identified and validated various factors that affect the total fluoroscopy time during ERCP. This is the first study to show that decreasing the distance

  13. Automated multivariate analysis of multi-sensor data submitted online: Real-time environmental monitoring.

    Science.gov (United States)

    Eide, Ingvar; Westad, Frank

    2018-01-01

    A pilot study demonstrating real-time environmental monitoring with automated multivariate analysis of multi-sensor data submitted online has been performed at the cabled LoVe Ocean Observatory located at 258 m depth 20 km off the coast of Lofoten-Vesterålen, Norway. The major purpose was efficient monitoring of many variables simultaneously and early detection of changes and time-trends in the overall response pattern before changes were evident in individual variables. The pilot study was performed with 12 sensors from May 16 to August 31, 2015. The sensors provided data for chlorophyll, turbidity, conductivity, temperature (three sensors), salinity (calculated from temperature and conductivity), biomass at three different depth intervals (5-50, 50-120, 120-250 m), and current speed measured in two directions (east and north) using two sensors covering different depths with overlap. A total of 88 variables were monitored, 78 from the two current speed sensors. The time-resolution varied, thus the data had to be aligned to a common time resolution. After alignment, the data were interpreted using principal component analysis (PCA). Initially, a calibration model was established using data from May 16 to July 31. The data on current speed from two sensors were subject to two separate PCA models and the score vectors from these two models were combined with the other 10 variables in a multi-block PCA model. The observations from August were projected on the calibration model consecutively one at a time and the result was visualized in a score plot. Automated PCA of multi-sensor data submitted online is illustrated with an attached time-lapse video covering the relative short time period used in the pilot study. Methods for statistical validation, and warning and alarm limits are described. Redundant sensors enable sensor diagnostics and quality assurance. In a future perspective, the concept may be used in integrated environmental monitoring.

  14. Automated multivariate analysis of multi-sensor data submitted online: Real-time environmental monitoring.

    Directory of Open Access Journals (Sweden)

    Ingvar Eide

    Full Text Available A pilot study demonstrating real-time environmental monitoring with automated multivariate analysis of multi-sensor data submitted online has been performed at the cabled LoVe Ocean Observatory located at 258 m depth 20 km off the coast of Lofoten-Vesterålen, Norway. The major purpose was efficient monitoring of many variables simultaneously and early detection of changes and time-trends in the overall response pattern before changes were evident in individual variables. The pilot study was performed with 12 sensors from May 16 to August 31, 2015. The sensors provided data for chlorophyll, turbidity, conductivity, temperature (three sensors, salinity (calculated from temperature and conductivity, biomass at three different depth intervals (5-50, 50-120, 120-250 m, and current speed measured in two directions (east and north using two sensors covering different depths with overlap. A total of 88 variables were monitored, 78 from the two current speed sensors. The time-resolution varied, thus the data had to be aligned to a common time resolution. After alignment, the data were interpreted using principal component analysis (PCA. Initially, a calibration model was established using data from May 16 to July 31. The data on current speed from two sensors were subject to two separate PCA models and the score vectors from these two models were combined with the other 10 variables in a multi-block PCA model. The observations from August were projected on the calibration model consecutively one at a time and the result was visualized in a score plot. Automated PCA of multi-sensor data submitted online is illustrated with an attached time-lapse video covering the relative short time period used in the pilot study. Methods for statistical validation, and warning and alarm limits are described. Redundant sensors enable sensor diagnostics and quality assurance. In a future perspective, the concept may be used in integrated environmental monitoring.

  15. Analyzing time-ordered event data with missed observations

    NARCIS (Netherlands)

    Dokter, Adriaan M.; van Loon, E. Emiel; Fokkema, Wimke; Lameris, Thomas K.; Nolet, Bart A.; van der Jeugd, Henk P.

    2017-01-01

    A common problem with observational datasets is that not all events of interest may be detected. For example, observing animals in the wild can difficult when animals move, hide, or cannot be closely approached. We consider time series of events recorded in conditions where events are occasionally

  16. Real-time synchronization of batch trajectories for on-line multivariate statistical process control using Dynamic Time Warping

    OpenAIRE

    González Martínez, Jose María; Ferrer Riquelme, Alberto José; Westerhuis, Johan A.

    2011-01-01

    This paper addresses the real-time monitoring of batch processes with multiple different local time trajectories of variables measured during the process run. For Unfold Principal Component Analysis (U-PCA)—or Unfold Partial Least Squares (U-PLS)-based on-line monitoring of batch processes, batch runs need to be synchronized, not only to have the same time length, but also such that key events happen at the same time. An adaptation from Kassidas et al.'s approach [1] will be introduced to ach...

  17. Asymptotics for the Conditional-Sum-of-Squares Estimator in Multivariate Fractional Time-Series Models

    DEFF Research Database (Denmark)

    Ørregård Nielsen, Morten

    2015-01-01

    the multivariate non-cointegrated fractional autoregressive integrated moving average (ARIMA) model. The novelty of the consistency result, in particular, is that it applies to a multivariate model and to an arbitrarily large set of admissible parameter values, for which the objective function does not converge...

  18. A Regularized Linear Dynamical System Framework for Multivariate Time Series Analysis.

    Science.gov (United States)

    Liu, Zitao; Hauskrecht, Milos

    2015-01-01

    Linear Dynamical System (LDS) is an elegant mathematical framework for modeling and learning Multivariate Time Series (MTS). However, in general, it is difficult to set the dimension of an LDS's hidden state space. A small number of hidden states may not be able to model the complexities of a MTS, while a large number of hidden states can lead to overfitting. In this paper, we study learning methods that impose various regularization penalties on the transition matrix of the LDS model and propose a regularized LDS learning framework (rLDS) which aims to (1) automatically shut down LDSs' spurious and unnecessary dimensions, and consequently, address the problem of choosing the optimal number of hidden states; (2) prevent the overfitting problem given a small amount of MTS data; and (3) support accurate MTS forecasting. To learn the regularized LDS from data we incorporate a second order cone program and a generalized gradient descent method into the Maximum a Posteriori framework and use Expectation Maximization to obtain a low-rank transition matrix of the LDS model. We propose two priors for modeling the matrix which lead to two instances of our rLDS. We show that our rLDS is able to recover well the intrinsic dimensionality of the time series dynamics and it improves the predictive performance when compared to baselines on both synthetic and real-world MTS datasets.

  19. Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Data

    Science.gov (United States)

    Hallac, David; Vare, Sagar; Boyd, Stephen; Leskovec, Jure

    2018-01-01

    Subsequence clustering of multivariate time series is a useful tool for discovering repeated patterns in temporal data. Once these patterns have been discovered, seemingly complicated datasets can be interpreted as a temporal sequence of only a small number of states, or clusters. For example, raw sensor data from a fitness-tracking application can be expressed as a timeline of a select few actions (i.e., walking, sitting, running). However, discovering these patterns is challenging because it requires simultaneous segmentation and clustering of the time series. Furthermore, interpreting the resulting clusters is difficult, especially when the data is high-dimensional. Here we propose a new method of model-based clustering, which we call Toeplitz Inverse Covariance-based Clustering (TICC). Each cluster in the TICC method is defined by a correlation network, or Markov random field (MRF), characterizing the interdependencies between different observations in a typical subsequence of that cluster. Based on this graphical representation, TICC simultaneously segments and clusters the time series data. We solve the TICC problem through alternating minimization, using a variation of the expectation maximization (EM) algorithm. We derive closed-form solutions to efficiently solve the two resulting subproblems in a scalable way, through dynamic programming and the alternating direction method of multipliers (ADMM), respectively. We validate our approach by comparing TICC to several state-of-the-art baselines in a series of synthetic experiments, and we then demonstrate on an automobile sensor dataset how TICC can be used to learn interpretable clusters in real-world scenarios. PMID:29770257

  20. Extracting a robust U.S. business cycle using a time-varying multivariate model-based bandpass filter

    NARCIS (Netherlands)

    Koopman, S.J.; Creal, D.D.

    2010-01-01

    We develop a flexible business cycle indicator that accounts for potential time variation in macroeconomic variables. The coincident economic indicator is based on a multivariate trend cycle decomposition model and is constructed from a moderate set of US macroeconomic time series. In particular, we

  1. Computing return times or return periods with rare event algorithms

    Science.gov (United States)

    Lestang, Thibault; Ragone, Francesco; Bréhier, Charles-Edouard; Herbert, Corentin; Bouchet, Freddy

    2018-04-01

    The average time between two occurrences of the same event, referred to as its return time (or return period), is a useful statistical concept for practical applications. For instance insurances or public agencies may be interested by the return time of a 10 m flood of the Seine river in Paris. However, due to their scarcity, reliably estimating return times for rare events is very difficult using either observational data or direct numerical simulations. For rare events, an estimator for return times can be built from the extrema of the observable on trajectory blocks. Here, we show that this estimator can be improved to remain accurate for return times of the order of the block size. More importantly, we show that this approach can be generalised to estimate return times from numerical algorithms specifically designed to sample rare events. So far those algorithms often compute probabilities, rather than return times. The approach we propose provides a computationally extremely efficient way to estimate numerically the return times of rare events for a dynamical system, gaining several orders of magnitude of computational costs. We illustrate the method on two kinds of observables, instantaneous and time-averaged, using two different rare event algorithms, for a simple stochastic process, the Ornstein–Uhlenbeck process. As an example of realistic applications to complex systems, we finally discuss extreme values of the drag on an object in a turbulent flow.

  2. Soil erosion under multiple time-varying rainfall events

    Science.gov (United States)

    Heng, B. C. Peter; Barry, D. Andrew; Jomaa, Seifeddine; Sander, Graham C.

    2010-05-01

    Soil erosion is a function of many factors and process interactions. An erosion event produces changes in surface soil properties such as texture and hydraulic conductivity. These changes in turn alter the erosion response to subsequent events. Laboratory-scale soil erosion studies have typically focused on single independent rainfall events with constant rainfall intensities. This study investigates the effect of multiple time-varying rainfall events on soil erosion using the EPFL erosion flume. The rainfall simulator comprises ten Veejet nozzles mounted on oscillating bars 3 m above a 6 m × 2 m flume. Spray from the nozzles is applied onto the soil surface in sweeps; rainfall intensity is thus controlled by varying the sweeping frequency. Freshly-prepared soil with a uniform slope was subjected to five rainfall events at daily intervals. In each 3-h event, rainfall intensity was ramped up linearly to a maximum of 60 mm/h and then stepped down to zero. Runoff samples were collected and analysed for particle size distribution (PSD) as well as total sediment concentration. We investigate whether there is a hysteretic relationship between sediment concentration and discharge within each event and how this relationship changes from event to event. Trends in the PSD of the eroded sediment are discussed and correlated with changes in sediment concentration. Close-up imagery of the soil surface following each event highlight changes in surface soil structure with time. This study enhances our understanding of erosion processes in the field, with corresponding implications for soil erosion modelling.

  3. Analyzing time-ordered event data with missed observations.

    Science.gov (United States)

    Dokter, Adriaan M; van Loon, E Emiel; Fokkema, Wimke; Lameris, Thomas K; Nolet, Bart A; van der Jeugd, Henk P

    2017-09-01

    A common problem with observational datasets is that not all events of interest may be detected. For example, observing animals in the wild can difficult when animals move, hide, or cannot be closely approached. We consider time series of events recorded in conditions where events are occasionally missed by observers or observational devices. These time series are not restricted to behavioral protocols, but can be any cyclic or recurring process where discrete outcomes are observed. Undetected events cause biased inferences on the process of interest, and statistical analyses are needed that can identify and correct the compromised detection processes. Missed observations in time series lead to observed time intervals between events at multiples of the true inter-event time, which conveys information on their detection probability. We derive the theoretical probability density function for observed intervals between events that includes a probability of missed detection. Methodology and software tools are provided for analysis of event data with potential observation bias and its removal. The methodology was applied to simulation data and a case study of defecation rate estimation in geese, which is commonly used to estimate their digestive throughput and energetic uptake, or to calculate goose usage of a feeding site from dropping density. Simulations indicate that at a moderate chance to miss arrival events ( p  = 0.3), uncorrected arrival intervals were biased upward by up to a factor 3, while parameter values corrected for missed observations were within 1% of their true simulated value. A field case study shows that not accounting for missed observations leads to substantial underestimates of the true defecation rate in geese, and spurious rate differences between sites, which are introduced by differences in observational conditions. These results show that the derived methodology can be used to effectively remove observational biases in time-ordered event

  4. Family Events and the Timing of Intergenerational Transfers

    Science.gov (United States)

    Leopold, Thomas; Schneider, Thorsten

    2011-01-01

    This research investigates how family events in adult children's lives influence the timing of their parents' financial transfers. We draw on retrospective data collected by the German Socio-Economic Panel Study and use event history models to study the effects of marriage, divorce and childbirth on the receipt of large gifts from parents. We find…

  5. Sensor-Generated Time Series Events: A Definition Language

    Science.gov (United States)

    Anguera, Aurea; Lara, Juan A.; Lizcano, David; Martínez, Maria Aurora; Pazos, Juan

    2012-01-01

    There are now a great many domains where information is recorded by sensors over a limited time period or on a permanent basis. This data flow leads to sequences of data known as time series. In many domains, like seismography or medicine, time series analysis focuses on particular regions of interest, known as events, whereas the remainder of the time series contains hardly any useful information. In these domains, there is a need for mechanisms to identify and locate such events. In this paper, we propose an events definition language that is general enough to be used to easily and naturally define events in time series recorded by sensors in any domain. The proposed language has been applied to the definition of time series events generated within the branch of medicine dealing with balance-related functions in human beings. A device, called posturograph, is used to study balance-related functions. The platform has four sensors that record the pressure intensity being exerted on the platform, generating four interrelated time series. As opposed to the existing ad hoc proposals, the results confirm that the proposed language is valid, that is generally applicable and accurate, for identifying the events contained in the time series.

  6. Repeated Time-to-event Analysis of Consecutive Analgesic Events in Postoperative Pain

    DEFF Research Database (Denmark)

    Juul, Rasmus Vestergaard; Rasmussen, Sten; Kreilgaard, Mads

    2015-01-01

    BACKGROUND: Reduction in consumption of opioid rescue medication is often used as an endpoint when investigating analgesic efficacy of drugs by adjunct treatment, but appropriate methods are needed to analyze analgesic consumption in time. Repeated time-to-event (RTTE) modeling is proposed as a way...... to describe analgesic consumption by analyzing the timing of consecutive analgesic events. METHODS: Retrospective data were obtained from 63 patients receiving standard analgesic treatment including morphine on request after surgery following hip fracture. Times of analgesic events up to 96 h after surgery...... were extracted from hospital medical records. Parametric RTTE analysis was performed with exponential, Weibull, or Gompertz distribution of analgesic events using NONMEM®, version 7.2 (ICON Development Solutions, USA). The potential influences of night versus day, sex, and age were investigated...

  7. Reciprocal Benefits of Mass-Univariate and Multivariate Modeling in Brain Mapping: Applications to Event-Related Functional MRI, H215O-, and FDG-PET

    Directory of Open Access Journals (Sweden)

    James R. Moeller

    2006-01-01

    Full Text Available In brain mapping studies of sensory, cognitive, and motor operations, specific waveforms of dynamic neural activity are predicted based on theoretical models of human information processing. For example in event-related functional MRI (fMRI, the general linear model (GLM is employed in mass-univariate analyses to identify the regions whose dynamic activity closely matches the expected waveforms. By comparison multivariate analyses based on PCA or ICA provide greater flexibility in detecting spatiotemporal properties of experimental data that may strongly support alternative neuroscientific explanations. We investigated conjoint multivariate and mass-univariate analyses that combine the capabilities to (1 verify activation of neural machinery we already understand and (2 discover reliable signatures of new neural machinery. We examined combinations of GLM and PCA that recover latent neural signals (waveforms and footprints with greater accuracy than either method alone. Comparative results are illustrated with analyses of real fMRI data, adding to Monte Carlo simulation support.

  8. On the quiet-time Pc 5 pulsation events (spacequakes)

    International Nuclear Information System (INIS)

    Gupta, J.C.; Niblett, E.R.

    1979-01-01

    A quiet-time Pc 5 event (designated Spacequake) of March 18, 1974, first noted on the Fort Churchill magnetogram, was studied using global data. Its amplitude was found to be largest in the northern part of the auroral zone and its period seemed to increase with latitude. The clockwise polarization of the event noted at Baker Lake and higher latitudes changed to counterclockwise at Fort Churchill in X-Y, X-Z and Y-Z planes. The resonance of a field line (L approximately 10) excited due to an instability of the Kelvin-Helmholtz type may have given rise to the observed event. It is conjectured that the cause of instability at this altitude was internal convection of the magnetosphere. Similar quiet-time events from four Canadian observatories were selected from approximately 11 years of magnetograms and their statistical analysis revealed that (i) occurrences maximised near dawn and dusk (ii) the amplitude-latitude profile peaked at Great Whale River (L approximately 6.67), (iii) periods increased with increasing geomagnetic latitudes, (iv) a large number of events occurred in January, February and March every year, and (v) frequency of occurrence increased with increasing sunspot numbers. Comparison of these results with those available in the literature from analyses of satellite data clearly indicate that quiet-time Pc 5 events (Spacequakes) originate in the outer magnetosphere. (author)

  9. Multivariable predictive control considering time delay for load-frequency control in multi-area power systems

    Directory of Open Access Journals (Sweden)

    Daniar Sabah

    2016-12-01

    Full Text Available In this paper, a multivariable model based predictive control (MPC is proposed for the solution of load frequency control (LFC in a multi-area interconnected power system. The proposed controller is designed to consider time delay, generation rate constraint and multivariable nature of the LFC system, simultaneously. A new formulation of the MPC is presented to compensate time delay. The generation rate constraint is considered by employing a constrained MPC and economic allocation of the generation is further guaranteed by an innovative modification in the predictive control objective function. The effectiveness of proposed scheme is verified through time-based simulations on the standard 39-bus test system and the responses are then compared with the proportional-integral controller. The evaluation of the results reveals that the proposed control scheme offers satisfactory performance with fast responses.

  10. Time Separation Between Events in a Sequence: a Regional Property?

    Science.gov (United States)

    Muirwood, R.; Fitzenz, D. D.

    2013-12-01

    Earthquake sequences are loosely defined as events occurring too closely in time and space to appear unrelated. Depending on the declustering method, several, all, or no event(s) after the first large event might be recognized as independent mainshocks. It can therefore be argued that a probabilistic seismic hazard assessment (PSHA, traditionally dealing with mainshocks only) might already include the ground shaking effects of such sequences. Alternatively all but the largest event could be classified as an ';aftershock' and removed from the earthquake catalog. While in PSHA the question is only whether to keep or remove the events from the catalog, for Risk Management purposes, the community response to the earthquakes, as well as insurance risk transfer mechanisms, can be profoundly affected by the actual timing of events in such a sequence. In particular the repetition of damaging earthquakes over a period of weeks to months can lead to businesses closing and families evacuating from the region (as happened in Christchurch, New Zealand in 2011). Buildings that are damaged in the first earthquake may go on to be damaged again, even while they are being repaired. Insurance also functions around a set of critical timeframes - including the definition of a single 'event loss' for reinsurance recoveries within the 192 hour ';hours clause', the 6-18 month pace at which insurance claims are settled, and the annual renewal of insurance and reinsurance contracts. We show how temporal aspects of earthquake sequences need to be taken into account within models for Risk Management, and what time separation between events are most sensitive, both in terms of the modeled disruptions to lifelines and business activity as well as in the losses to different parties (such as insureds, insurers and reinsurers). We also explore the time separation between all events and between loss causing events for a collection of sequences from across the world and we point to the need to

  11. Visualization-by-Sketching: An Artist's Interface for Creating Multivariate Time-Varying Data Visualizations.

    Science.gov (United States)

    Schroeder, David; Keefe, Daniel F

    2016-01-01

    We present Visualization-by-Sketching, a direct-manipulation user interface for designing new data visualizations. The goals are twofold: First, make the process of creating real, animated, data-driven visualizations of complex information more accessible to artists, graphic designers, and other visual experts with traditional, non-technical training. Second, support and enhance the role of human creativity in visualization design, enabling visual experimentation and workflows similar to what is possible with traditional artistic media. The approach is to conceive of visualization design as a combination of processes that are already closely linked with visual creativity: sketching, digital painting, image editing, and reacting to exemplars. Rather than studying and tweaking low-level algorithms and their parameters, designers create new visualizations by painting directly on top of a digital data canvas, sketching data glyphs, and arranging and blending together multiple layers of animated 2D graphics. This requires new algorithms and techniques to interpret painterly user input relative to data "under" the canvas, balance artistic freedom with the need to produce accurate data visualizations, and interactively explore large (e.g., terabyte-sized) multivariate datasets. Results demonstrate a variety of multivariate data visualization techniques can be rapidly recreated using the interface. More importantly, results and feedback from artists support the potential for interfaces in this style to attract new, creative users to the challenging task of designing more effective data visualizations and to help these users stay "in the creative zone" as they work.

  12. Interpretability of Multivariate Brain Maps in Linear Brain Decoding: Definition, and Heuristic Quantification in Multivariate Analysis of MEG Time-Locked Effects.

    Science.gov (United States)

    Kia, Seyed Mostafa; Vega Pons, Sandro; Weisz, Nathan; Passerini, Andrea

    2016-01-01

    Brain decoding is a popular multivariate approach for hypothesis testing in neuroimaging. Linear classifiers are widely employed in the brain decoding paradigm to discriminate among experimental conditions. Then, the derived linear weights are visualized in the form of multivariate brain maps to further study spatio-temporal patterns of underlying neural activities. It is well known that the brain maps derived from weights of linear classifiers are hard to interpret because of high correlations between predictors, low signal to noise ratios, and the high dimensionality of neuroimaging data. Therefore, improving the interpretability of brain decoding approaches is of primary interest in many neuroimaging studies. Despite extensive studies of this type, at present, there is no formal definition for interpretability of multivariate brain maps. As a consequence, there is no quantitative measure for evaluating the interpretability of different brain decoding methods. In this paper, first, we present a theoretical definition of interpretability in brain decoding; we show that the interpretability of multivariate brain maps can be decomposed into their reproducibility and representativeness. Second, as an application of the proposed definition, we exemplify a heuristic for approximating the interpretability in multivariate analysis of evoked magnetoencephalography (MEG) responses. Third, we propose to combine the approximated interpretability and the generalization performance of the brain decoding into a new multi-objective criterion for model selection. Our results, for the simulated and real MEG data, show that optimizing the hyper-parameters of the regularized linear classifier based on the proposed criterion results in more informative multivariate brain maps. More importantly, the presented definition provides the theoretical background for quantitative evaluation of interpretability, and hence, facilitates the development of more effective brain decoding algorithms

  13. Events in time: Basic analysis of Poisson data

    International Nuclear Information System (INIS)

    Engelhardt, M.E.

    1994-09-01

    The report presents basic statistical methods for analyzing Poisson data, such as the member of events in some period of time. It gives point estimates, confidence intervals, and Bayesian intervals for the rate of occurrence per unit of time. It shows how to compare subsets of the data, both graphically and by statistical tests, and how to look for trends in time. It presents a compound model when the rate of occurrence varies randomly. Examples and SAS programs are given

  14. Events in time: Basic analysis of Poisson data

    Energy Technology Data Exchange (ETDEWEB)

    Engelhardt, M.E.

    1994-09-01

    The report presents basic statistical methods for analyzing Poisson data, such as the member of events in some period of time. It gives point estimates, confidence intervals, and Bayesian intervals for the rate of occurrence per unit of time. It shows how to compare subsets of the data, both graphically and by statistical tests, and how to look for trends in time. It presents a compound model when the rate of occurrence varies randomly. Examples and SAS programs are given.

  15. Characterization of Land Transitions Patterns from Multivariate Time Series Using Seasonal Trend Analysis and Principal Component Analysis

    Directory of Open Access Journals (Sweden)

    Benoit Parmentier

    2014-12-01

    Full Text Available Characterizing biophysical changes in land change areas over large regions with short and noisy multivariate time series and multiple temporal parameters remains a challenging task. Most studies focus on detection rather than the characterization, i.e., the manner by which surface state variables are altered by the process of changes. In this study, a procedure is presented to extract and characterize simultaneous temporal changes in MODIS multivariate times series from three surface state variables the Normalized Difference Vegetation Index (NDVI, land surface temperature (LST and albedo (ALB. The analysis involves conducting a seasonal trend analysis (STA to extract three seasonal shape parameters (Amplitude 0, Amplitude 1 and Amplitude 2 and using principal component analysis (PCA to contrast trends in change and no-change areas. We illustrate the method by characterizing trends in burned and unburned pixels in Alaska over the 2001–2009 time period. Findings show consistent and meaningful extraction of temporal patterns related to fire disturbances. The first principal component (PC1 is characterized by a decrease in mean NDVI (Amplitude 0 with a concurrent increase in albedo (the mean and the annual amplitude and an increase in LST annual variability (Amplitude 1. These results provide systematic empirical evidence of surface changes associated with one type of land change, fire disturbances, and suggest that STA with PCA may be used to characterize many other types of land transitions over large landscape areas using multivariate Earth observation time series.

  16. A Deep Learning Architecture for Temporal Sleep Stage Classification Using Multivariate and Multimodal Time Series.

    Science.gov (United States)

    Chambon, Stanislas; Galtier, Mathieu N; Arnal, Pierrick J; Wainrib, Gilles; Gramfort, Alexandre

    2018-04-01

    Sleep stage classification constitutes an important preliminary exam in the diagnosis of sleep disorders. It is traditionally performed by a sleep expert who assigns to each 30 s of the signal of a sleep stage, based on the visual inspection of signals such as electroencephalograms (EEGs), electrooculograms (EOGs), electrocardiograms, and electromyograms (EMGs). We introduce here the first deep learning approach for sleep stage classification that learns end-to-end without computing spectrograms or extracting handcrafted features, that exploits all multivariate and multimodal polysomnography (PSG) signals (EEG, EMG, and EOG), and that can exploit the temporal context of each 30-s window of data. For each modality, the first layer learns linear spatial filters that exploit the array of sensors to increase the signal-to-noise ratio, and the last layer feeds the learnt representation to a softmax classifier. Our model is compared to alternative automatic approaches based on convolutional networks or decisions trees. Results obtained on 61 publicly available PSG records with up to 20 EEG channels demonstrate that our network architecture yields the state-of-the-art performance. Our study reveals a number of insights on the spatiotemporal distribution of the signal of interest: a good tradeoff for optimal classification performance measured with balanced accuracy is to use 6 EEG with 2 EOG (left and right) and 3 EMG chin channels. Also exploiting 1 min of data before and after each data segment offers the strongest improvement when a limited number of channels are available. As sleep experts, our system exploits the multivariate and multimodal nature of PSG signals in order to deliver the state-of-the-art classification performance with a small computational cost.

  17. Absolute GPS Time Event Generation and Capture for Remote Locations

    Science.gov (United States)

    HIRES Collaboration

    The HiRes experiment operates fixed location and portable lasers at remote desert locations to generate calibration events. One physics goal of HiRes is to search for unusual showers. These may appear similar to upward or horizontally pointing laser tracks used for atmospheric calibration. It is therefore necessary to remove all of these calibration events from the HiRes detector data stream in a physics blind manner. A robust and convenient "tagging" method is to generate the calibration events at precisely known times. To facilitate this tagging method we have developed the GPSY (Global Positioning System YAG) module. It uses a GPS receiver, an embedded processor and additional timing logic to generate laser triggers at arbitrary programmed times and frequencies with better than 100nS accuracy. The GPSY module has two trigger outputs (one microsecond resolution) to trigger the laser flash-lamp and Q-switch and one event capture input (25nS resolution). The GPSY module can be programmed either by a front panel menu based interface or by a host computer via an RS232 serial interface. The latter also allows for computer logging of generated and captured event times. Details of the design and the implementation of these devices will be presented. 1 Motivation Air Showers represent a small fraction, much less than a percent, of the total High Resolution Fly's Eye data sample. The bulk of the sample is calibration data. Most of this calibration data is generated by two types of systems that use lasers. One type sends light directly to the detectors via optical fibers to monitor detector gains (Girard 2001). The other sends a beam of light into the sky and the scattered light that reaches the detectors is used to monitor atmospheric effects (Wiencke 1998). It is important that these calibration events be cleanly separated from the rest of the sample both to provide a complete set of monitoring information, and more

  18. iVAR: a program for imputing missing data in multivariate time series using vector autoregressive models.

    Science.gov (United States)

    Liu, Siwei; Molenaar, Peter C M

    2014-12-01

    This article introduces iVAR, an R program for imputing missing data in multivariate time series on the basis of vector autoregressive (VAR) models. We conducted a simulation study to compare iVAR with three methods for handling missing data: listwise deletion, imputation with sample means and variances, and multiple imputation ignoring time dependency. The results showed that iVAR produces better estimates for the cross-lagged coefficients than do the other three methods. We demonstrate the use of iVAR with an empirical example of time series electrodermal activity data and discuss the advantages and limitations of the program.

  19. A real-time assessment of factors influencing medication events.

    Science.gov (United States)

    Dollarhide, Adrian W; Rutledge, Thomas; Weinger, Matthew B; Fisher, Erin Stucky; Jain, Sonia; Wolfson, Tanya; Dresselhaus, Timothy R

    2014-01-01

    Reducing medical error is critical to improving the safety and quality of healthcare. Physician stress, fatigue, and excessive workload are performance-shaping factors (PSFs) that may influence medical events (actual administration errors and near misses), but direct relationships between these factors and patient safety have not been clearly defined. This study assessed the real-time influence of emotional stress, workload, and sleep deprivation on self-reported medication events by physicians in academic hospitals. During an 18-month study period, 185 physician participants working at four university-affiliated teaching hospitals reported medication events using a confidential reporting application on handheld computers. Emotional stress scores, perceived workload, patient case volume, clinical experience, total sleep, and demographic variables were also captured via the handheld computers. Medication event reports (n = 11) were then correlated with these demographic and PSFs. Medication events were associated with 36.1% higher perceived workload (p sleep (p = .10). These results confirm the effect of factors influencing medication events, and support attention to both provider and hospital environmental characteristics for improving patient safety. © 2013 National Association for Healthcare Quality.

  20. Subsurface signatures and timing of extreme wave events along the ...

    Indian Academy of Sciences (India)

    The diagnostic event signatures include the extent and elevation of the deposits, as well as morphologic similarity ... Historical archives of the origin, timing, and impact of tsunamis, storms, and floods along the mar- gins of ... High-resolution GPR studies (by the IIT Madras group) of erosional signatures from the beach ridge.

  1. Conceptualization of Collective Behavior Events in the New York "Times."

    Science.gov (United States)

    Blake, Joseph A.; And Others

    1978-01-01

    Reports that most collective behavior events reported in the New York "Times" are described in terms of emotionality and anonymity of membership and are alleged to be violent and spontaneous, and that there are significant rank-order correlations between the reported presence of control agents, reported violence, and attributions of spontaneity.…

  2. SQL Triggers Reacting on Time Events: An Extension Proposal

    Science.gov (United States)

    Behrend, Andreas; Dorau, Christian; Manthey, Rainer

    Being able to activate triggers at timepoints reached or after time intervals elapsed has been acknowledged by many authors as a valuable functionality of a DBMS. Recently, the interest in time-based triggers has been renewed in the context of data stream monitoring. However, up till now SQL triggers react to data changes only, even though research proposals and prototypes have been supporting several other event types, in particular time-based ones, since long. We therefore propose a seamless extension of the SQL trigger concept by time-based triggers, focussing on semantic issues arising from such an extension.

  3. Time and the event: The semantics of Russian prefixes

    Directory of Open Access Journals (Sweden)

    Gillian Ramchand

    2005-03-01

    Full Text Available In this paper, I draw on data from prefixation in Russian to argue for a basic distinction between event structure and temporal struc- ture. I present a linguistic semantics of verb and argument structure interpretation on the one hand, and a formal semantic implementa- tion of 'telicity' on the other, which makes sense of the generalisations apparently common to both domains. I will claim that the temporal domain embeds the event structure domain, and that the latter con- strains the former. At the same time, the different formal primitives that operate at the levels proposed form the basis for a principled linguistic distinction between the two tiers of composition: the event structure level encodes subevental relations and predicational rela- tions within those subevents; the temporal structure level introduces a t variable explicitly and relates it to the structure built up by the event level. Whether the event structure is homogenous or not will have an impact on whether the temporal variable chosen will be 'def- inite' or 'indefinite.' This latter claim then forms the basis for a new conception of the difference between perfective and imperfective verb forms in Russian.

  4. Prediction problem for target events based on the inter-event waiting time

    Science.gov (United States)

    Shapoval, A.

    2010-11-01

    In this paper we address the problem of forecasting the target events of a time series given the distribution ξ of time gaps between target events. Strong earthquakes and stock market crashes are the two types of such events that we are focusing on. In the series of earthquakes, as McCann et al. show [W.R. Mc Cann, S.P. Nishenko, L.R. Sykes, J. Krause, Seismic gaps and plate tectonics: seismic potential for major boundaries, Pure and Applied Geophysics 117 (1979) 1082-1147], there are well-defined gaps (called seismic gaps) between strong earthquakes. On the other hand, usually there are no regular gaps in the series of stock market crashes [M. Raberto, E. Scalas, F. Mainardi, Waiting-times and returns in high-frequency financial data: an empirical study, Physica A 314 (2002) 749-755]. For the case of seismic gaps, we analytically derive an upper bound of prediction efficiency given the coefficient of variation of the distribution ξ. For the case of stock market crashes, we develop an algorithm that predicts the next crash within a certain time interval after the previous one. We show that this algorithm outperforms random prediction. The efficiency of our algorithm sets up a lower bound of efficiency for effective prediction of stock market crashes.

  5. Space-Time Characteristic Functions in Multivariate Logic and Possible Interpretation of Entanglement

    Science.gov (United States)

    Gaudeau de Gerlicz, Claude; Sechpine, Pierre; Bobola, Philippe; Antoine, Mathias

    The knowledge about hidden variables in physics, (Bohr's-Schrödinger theories) and their developments, boundaries seem more and more fuzzy at physical scales. Also some other new theories give to both time and space as much fuzziness. The classical theory, (school of Copenhagen's) and also Heisenberg and Louis de Broglie give us the idea of a dual wave and particle parts such the way we observe. Thus, the Pondichery interpretation recently developed by Cramer and al. gives to the time part this duality. According Cramer, there could be a little more to this duality, some late or advanced waves of time that have been confirmed and admitted as possible solutions with the Maxwell's equations. We developed here a possible pattern that could matched in the sequence between Space and both retarded and advanced time wave in the "Cramer handshake" in locality of the present when the observation is made everything become local.

  6. New strategy to identify radicals in a time evolving EPR data set by multivariate curve resolution-alternating least squares

    Energy Technology Data Exchange (ETDEWEB)

    Fadel, Maya Abou [LASIR CNRS UMR 8516, Université Lille 1, Sciences et Technologies, 59655 Villeneuve d' Ascq Cedex (France); Juan, Anna de [Chemometrics Group, Section of Analytical Chemistry, Universitat de Barcelona, Diagonal 645, 08028 Barcelona (Spain); Vezin, Hervé [LASIR CNRS UMR 8516, Université Lille 1, Sciences et Technologies, 59655 Villeneuve d' Ascq Cedex (France); Duponchel, Ludovic, E-mail: ludovic.duponchel@univ-lille1.fr [LASIR CNRS UMR 8516, Université Lille 1, Sciences et Technologies, 59655 Villeneuve d' Ascq Cedex (France)

    2016-12-01

    Electron paramagnetic resonance (EPR) spectroscopy is a powerful technique that is able to characterize radicals formed in kinetic reactions. However, spectral characterization of individual chemical species is often limited or even unmanageable due to the severe kinetic and spectral overlap among species in kinetic processes. Therefore, we applied, for the first time, multivariate curve resolution-alternating least squares (MCR-ALS) method to EPR time evolving data sets to model and characterize the different constituents in a kinetic reaction. Here we demonstrate the advantage of multivariate analysis in the investigation of radicals formed along the kinetic process of hydroxycoumarin in alkaline medium. Multiset analysis of several EPR-monitored kinetic experiments performed in different conditions revealed the individual paramagnetic centres as well as their kinetic profiles. The results obtained by MCR-ALS method demonstrate its prominent potential in analysis of EPR time evolved spectra. - Highlights: • A new strategy to identify radicals in a time evolving EPR data set. • Extraction of pure EPR spectral signatures and corresponding kinetic profiles. • The proposed method does not require any prior knowledge of the chemical system. • A multiset analysis in order to decrease rotational ambiguity.

  7. Real-time prediction of the occurrence of GLE events

    Science.gov (United States)

    Núñez, Marlon; Reyes-Santiago, Pedro J.; Malandraki, Olga E.

    2017-07-01

    A tool for predicting the occurrence of Ground Level Enhancement (GLE) events using the UMASEP scheme is presented. This real-time tool, called HESPERIA UMASEP-500, is based on the detection of the magnetic connection, along which protons arrive in the near-Earth environment, by estimating the lag correlation between the time derivatives of 1 min soft X-ray flux (SXR) and 1 min near-Earth proton fluxes observed by the GOES satellites. Unlike current GLE warning systems, this tool can predict GLE events before the detection by any neutron monitor (NM) station. The prediction performance measured for the period from 1986 to 2016 is presented for two consecutive periods, because of their notable difference in performance. For the 2000-2016 period, this prediction tool obtained a probability of detection (POD) of 53.8% (7 of 13 GLE events), a false alarm ratio (FAR) of 30.0%, and average warning times (AWT) of 8 min with respect to the first NM station's alert and 15 min to the GLE Alert Plus's warning. We have tested the model by replacing the GOES proton data with SOHO/EPHIN proton data, and the results are similar in terms of POD, FAR, and AWT for the same period. The paper also presents a comparison with a GLE warning system.

  8. Multivariate analysis of diagnostic parameters derived from whole-kidney and parenchymal time-activity curves

    International Nuclear Information System (INIS)

    Bergmann, H.; Mostbeck, A.; Samal, M.; Nimmon, C.C.; Staudenherz, A.; Dudczak, R.

    2002-01-01

    Aim: In a previous work, we have confirmed earlier reports that time-activity curves of renal cortex provide additional useful diagnostic information. The aim of this experiment was to support the finding quantitatively using multiple regression. Materials and Methods: In a retrospective study, we have analyzed MAG3 renal data (90 kidneys in 57 children). Whole-kidney (WK) and parenchymal (PA) time-activity curves were extracted from 20 min pre-diuretic phase using standard WK and parenchymal fuzzy ROIs. Using multiple regression analysis, peak time, mean transit time, output efficiency, and four additional indices of residual activity in WK and PA ROIs were related to the maximum elimination rate (EM) of urine after the diuretic. The kidneys were divided into four groups according to the WK peak time (WKPT): WKPT longer than 0 (all kidneys), 5, 10, and 15 min. Results: Multiple correlation coefficients between the set of WK, PA, and WK+PA curve parameters (independent variables) and the log EM (dependent variable) for each group are summarized. Conclusions: Using pre-diuretic time-activity curves, it is possible to predict diuretic response. This can be useful when interpreting dubious results. Parenchymal curves predict diuretic response better than the whole-kidney curves. With increasing WKPT the whole-kidney curves become useless, while the parenchymal curves are still useful. Using both WK and PA curves produces the best results. This demonstrates that both WK and PA curves carry independent diagnostic information. The contribution obtained from the parenchymal curves certainly worth the difficulties and time required to draw additional ROIs. However, substantial efforts have to be given to the accurate and reproducible definition of parenchymal ROIs

  9. A diary after dinner: How the time of event recording influences later accessibility of diary events.

    Science.gov (United States)

    Szőllősi, Ágnes; Keresztes, Attila; Conway, Martin A; Racsmány, Mihály

    2015-01-01

    Recording the events of a day in a diary may help improve their later accessibility. An interesting question is whether improvements in long-term accessibility will be greater if the diary is completed at the end of the day, or after a period of sleep, the following morning. We investigated this question using an internet-based diary method. On each of five days, participants (n = 109) recorded autobiographical memories for that day or for the previous day. Recording took place either in the morning or in the evening. Following a 30-day retention interval, the diary events were free recalled. We found that participants who recorded their memories in the evening before sleep had best memory performance. These results suggest that the time of reactivation and recording of recent autobiographical events has a significant effect on the later accessibility of those diary events. We discuss our results in the light of related findings that show a beneficial effect of reduced interference during sleep on memory consolidation and reconsolidation.

  10. Multivariable analysis of anesthetic factors associated with time to extubation in dogs.

    Science.gov (United States)

    Kleine, Stephanie; Hofmeister, Erik; Egan, Katrina

    2014-12-01

    The purpose of this study was to identify factors that prolong the time to extubation in dogs. Anesthetic records of 900 dogs at a university teaching hospital were searched. Multiple linear regression was used to compare independent predictors (patient demographics, anesthetic and intraoperative variables) with the dependent variable (time to extubation). Induction with propofol (P temperature (P = 0.0000), and by 0.096 minutes for every 1 minute increase in anesthetic duration (P = 0.000). Anesthetic variables, which can be manipulated by the anesthetist, include choice of premedication and induction drugs, hypothermia, and duration of anesthesia. Published by Elsevier Ltd.

  11. Time use choices and healthy body weight: A multivariate analysis of data from the American Time use Survey

    Directory of Open Access Journals (Sweden)

    Stevens Robert B

    2011-08-01

    Full Text Available Abstract Background We examine the relationship between time use choices and healthy body weight as measured by survey respondents' body mass index (BMI. Using data from the 2006 and 2007 American Time Use Surveys, we expand upon earlier research by including more detailed measures of time spent eating as well as measures of physical activity time and sedentary time. We also estimate three alternative models that relate time use to BMI. Results Our results suggest that time use and BMI are simultaneously determined. The preferred empirical model reveals evidence of an inverse relationship between time spent eating and BMI for women and men. In contrast, time spent drinking beverages while simultaneously doing other things and time spent watching television/videos are positively linked to BMI. For women only, time spent in food preparation and clean-up is inversely related to BMI while for men only, time spent sleeping is inversely related to BMI. Models that include grocery prices, opportunity costs of time, and nonwage income reveal that as these economic variables increase, BMI declines. Conclusions In this large, nationally representative data set, our analyses that correct for time use endogeneity reveal that the Americans' time use decisions have implications for their BMI. The analyses suggest that both eating time and context (i.e., while doing other tasks simultaneously matters as does time spent in food preparation, and time spent in sedentary activities. Reduced form models suggest that shifts in grocery prices, opportunity costs of time, and nonwage income may be contributing to alterations in time use patterns and food choices that have implications for BMI.

  12. Harmonic spectral components in time sequences of Markov correlated events

    Science.gov (United States)

    Mazzetti, Piero; Carbone, Anna

    2017-07-01

    The paper concerns the analysis of the conditions allowing time sequences of Markov correlated events give rise to a line power spectrum having a relevant physical interest. It is found that by specializing the Markov matrix in order to represent closed loop sequences of events with arbitrary distribution, generated in a steady physical condition, a large set of line spectra, covering all possible frequency values, is obtained. The amplitude of the spectral lines is given by a matrix equation based on a generalized Markov matrix involving the Fourier transform of the distribution functions representing the time intervals between successive events of the sequence. The paper is a complement of a previous work where a general expression for the continuous power spectrum was given. In that case the Markov matrix was left in a more general form, thus preventing the possibility of finding line spectra of physical interest. The present extension is also suggested by the interest of explaining the emergence of a broad set of waves found in the electro and magneto-encephalograms, whose frequency ranges from 0.5 to about 40Hz, in terms of the effects produced by chains of firing neurons within the complex neural network of the brain. An original model based on synchronized closed loop sequences of firing neurons is proposed, and a few numerical simulations are reported as an application of the above cited equation.

  13. Cardiorespiratory Dynamic Response to Mental Stress: A Multivariate Time-Frequency Analysis

    Directory of Open Access Journals (Sweden)

    Devy Widjaja

    2013-01-01

    out continuously in time to evaluate the dynamic response to mental stress and attention. The results show an increased heart and respiratory rate during stress and attention, compared to a resting condition. Also a fast reduction in vagal activity is noted. The partial TF analysis reveals a faster reduction of RRV power related to (3 s than unrelated to (30 s respiration, demonstrating that the autonomic response to mental stress is driven by mechanisms characterized by different temporal scales.

  14. Cardiorespiratory dynamic response to mental stress: a multivariate time-frequency analysis.

    Science.gov (United States)

    Widjaja, Devy; Orini, Michele; Vlemincx, Elke; Van Huffel, Sabine

    2013-01-01

    Mental stress is a growing problem in our society. In order to deal with this, it is important to understand the underlying stress mechanisms. In this study, we aim to determine how the cardiorespiratory interactions are affected by mental arithmetic stress and attention. We conduct cross time-frequency (TF) analyses to assess the cardiorespiratory coupling. In addition, we introduce partial TF spectra to separate variations in the RR interval series that are linearly related to respiration from RR interval variations (RRV) that are not related to respiration. The performance of partial spectra is evaluated in two simulation studies. Time-varying parameters, such as instantaneous powers and frequencies, are derived from the computed spectra. Statistical analysis is carried out continuously in time to evaluate the dynamic response to mental stress and attention. The results show an increased heart and respiratory rate during stress and attention, compared to a resting condition. Also a fast reduction in vagal activity is noted. The partial TF analysis reveals a faster reduction of RRV power related to (3 s) than unrelated to (30 s) respiration, demonstrating that the autonomic response to mental stress is driven by mechanisms characterized by different temporal scales.

  15. Marginal regression analysis of recurrent events with coarsened censoring times.

    Science.gov (United States)

    Hu, X Joan; Rosychuk, Rhonda J

    2016-12-01

    Motivated by an ongoing pediatric mental health care (PMHC) study, this article presents weakly structured methods for analyzing doubly censored recurrent event data where only coarsened information on censoring is available. The study extracted administrative records of emergency department visits from provincial health administrative databases. The available information of each individual subject is limited to a subject-specific time window determined up to concealed data. To evaluate time-dependent effect of exposures, we adapt the local linear estimation with right censored survival times under the Cox regression model with time-varying coefficients (cf. Cai and Sun, Scandinavian Journal of Statistics 2003, 30, 93-111). We establish the pointwise consistency and asymptotic normality of the regression parameter estimator, and examine its performance by simulation. The PMHC study illustrates the proposed approach throughout the article. © 2016, The International Biometric Society.

  16. Comparing and combining biomarkers as principle surrogates for time-to-event clinical endpoints.

    Science.gov (United States)

    Gabriel, Erin E; Sachs, Michael C; Gilbert, Peter B

    2015-02-10

    Principal surrogate endpoints are useful as targets for phase I and II trials. In many recent trials, multiple post-randomization biomarkers are measured. However, few statistical methods exist for comparison of or combination of biomarkers as principal surrogates, and none of these methods to our knowledge utilize time-to-event clinical endpoint information. We propose a Weibull model extension of the semi-parametric estimated maximum likelihood method that allows for the inclusion of multiple biomarkers in the same risk model as multivariate candidate principal surrogates. We propose several methods for comparing candidate principal surrogates and evaluating multivariate principal surrogates. These include the time-dependent and surrogate-dependent true and false positive fraction, the time-dependent and the integrated standardized total gain, and the cumulative distribution function of the risk difference. We illustrate the operating characteristics of our proposed methods in simulations and outline how these statistics can be used to evaluate and compare candidate principal surrogates. We use these methods to investigate candidate surrogates in the Diabetes Control and Complications Trial. Copyright © 2014 John Wiley & Sons, Ltd.

  17. Recurrent-Neural-Network-Based Multivariable Adaptive Control for a Class of Nonlinear Dynamic Systems With Time-Varying Delay.

    Science.gov (United States)

    Hwang, Chih-Lyang; Jan, Chau

    2016-02-01

    At the beginning, an approximate nonlinear autoregressive moving average (NARMA) model is employed to represent a class of multivariable nonlinear dynamic systems with time-varying delay. It is known that the disadvantages of robust control for the NARMA model are as follows: 1) suitable control parameters for larger time delay are more sensitive to achieving desirable performance; 2) it only deals with bounded uncertainty; and 3) the nominal NARMA model must be learned in advance. Due to the dynamic feature of the NARMA model, a recurrent neural network (RNN) is online applied to learn it. However, the system performance becomes deteriorated due to the poor learning of the larger variation of system vector functions. In this situation, a simple network is employed to compensate the upper bound of the residue caused by the linear parameterization of the approximation error of RNN. An e -modification learning law with a projection for weight matrix is applied to guarantee its boundedness without persistent excitation. Under suitable conditions, the semiglobally ultimately bounded tracking with the boundedness of estimated weight matrix is obtained by the proposed RNN-based multivariable adaptive control. Finally, simulations are presented to verify the effectiveness and robustness of the proposed control.

  18. Piecing together the puzzle: Improving event content coverage for real-time sub-event detection using adaptive microblog crawling.

    Directory of Open Access Journals (Sweden)

    Laurissa Tokarchuk

    Full Text Available In an age when people are predisposed to report real-world events through their social media accounts, many researchers value the benefits of mining user generated content from social media. Compared with the traditional news media, social media services, such as Twitter, can provide more complete and timely information about the real-world events. However events are often like a puzzle and in order to solve the puzzle/understand the event, we must identify all the sub-events or pieces. Existing Twitter event monitoring systems for sub-event detection and summarization currently typically analyse events based on partial data as conventional data collection methodologies are unable to collect comprehensive event data. This results in existing systems often being unable to report sub-events in real-time and often in completely missing sub-events or pieces in the broader event puzzle. This paper proposes a Sub-event detection by real-TIme Microblog monitoring (STRIM framework that leverages the temporal feature of an expanded set of news-worthy event content. In order to more comprehensively and accurately identify sub-events this framework first proposes the use of adaptive microblog crawling. Our adaptive microblog crawler is capable of increasing the coverage of events while minimizing the amount of non-relevant content. We then propose a stream division methodology that can be accomplished in real time so that the temporal features of the expanded event streams can be analysed by a burst detection algorithm. In the final steps of the framework, the content features are extracted from each divided stream and recombined to provide a final summarization of the sub-events. The proposed framework is evaluated against traditional event detection using event recall and event precision metrics. Results show that improving the quality and coverage of event contents contribute to better event detection by identifying additional valid sub-events. The

  19. Piecing together the puzzle: Improving event content coverage for real-time sub-event detection using adaptive microblog crawling.

    Science.gov (United States)

    Tokarchuk, Laurissa; Wang, Xinyue; Poslad, Stefan

    2017-01-01

    In an age when people are predisposed to report real-world events through their social media accounts, many researchers value the benefits of mining user generated content from social media. Compared with the traditional news media, social media services, such as Twitter, can provide more complete and timely information about the real-world events. However events are often like a puzzle and in order to solve the puzzle/understand the event, we must identify all the sub-events or pieces. Existing Twitter event monitoring systems for sub-event detection and summarization currently typically analyse events based on partial data as conventional data collection methodologies are unable to collect comprehensive event data. This results in existing systems often being unable to report sub-events in real-time and often in completely missing sub-events or pieces in the broader event puzzle. This paper proposes a Sub-event detection by real-TIme Microblog monitoring (STRIM) framework that leverages the temporal feature of an expanded set of news-worthy event content. In order to more comprehensively and accurately identify sub-events this framework first proposes the use of adaptive microblog crawling. Our adaptive microblog crawler is capable of increasing the coverage of events while minimizing the amount of non-relevant content. We then propose a stream division methodology that can be accomplished in real time so that the temporal features of the expanded event streams can be analysed by a burst detection algorithm. In the final steps of the framework, the content features are extracted from each divided stream and recombined to provide a final summarization of the sub-events. The proposed framework is evaluated against traditional event detection using event recall and event precision metrics. Results show that improving the quality and coverage of event contents contribute to better event detection by identifying additional valid sub-events. The novel combination of

  20. Detecting and characterising ramp events in wind power time series

    International Nuclear Information System (INIS)

    Gallego, Cristóbal; Cuerva, Álvaro; Costa, Alexandre

    2014-01-01

    In order to implement accurate models for wind power ramp forecasting, ramps need to be previously characterised. This issue has been typically addressed by performing binary ramp/non-ramp classifications based on ad-hoc assessed thresholds. However, recent works question this approach. This paper presents the ramp function, an innovative wavelet- based tool which detects and characterises ramp events in wind power time series. The underlying idea is to assess a continuous index related to the ramp intensity at each time step, which is obtained by considering large power output gradients evaluated under different time scales (up to typical ramp durations). The ramp function overcomes some of the drawbacks shown by the aforementioned binary classification and permits forecasters to easily reveal specific features of the ramp behaviour observed at a wind farm. As an example, the daily profile of the ramp-up and ramp-down intensities are obtained for the case of a wind farm located in Spain

  1. Multivariable nonlinear analysis of foreign exchange rates

    Science.gov (United States)

    Suzuki, Tomoya; Ikeguchi, Tohru; Suzuki, Masuo

    2003-05-01

    We analyze the multivariable time series of foreign exchange rates. These are price movements that have often been analyzed, and dealing time intervals and spreads between bid and ask prices. Considering dealing time intervals as event timing such as neurons’ firings, we use raster plots (RPs) and peri-stimulus time histograms (PSTHs) which are popular methods in the field of neurophysiology. Introducing special processings to obtaining RPs and PSTHs time histograms for analyzing exchange rates time series, we discover that there exists dynamical interaction among three variables. We also find that adopting multivariables leads to improvements of prediction accuracy.

  2. Real-time monitoring of a coffee roasting process with near infrared spectroscopy using multivariate statistical analysis: A feasibility study.

    Science.gov (United States)

    Catelani, Tiago A; Santos, João Rodrigo; Páscoa, Ricardo N M J; Pezza, Leonardo; Pezza, Helena R; Lopes, João A

    2018-03-01

    This work proposes the use of near infrared (NIR) spectroscopy in diffuse reflectance mode and multivariate statistical process control (MSPC) based on principal component analysis (PCA) for real-time monitoring of the coffee roasting process. The main objective was the development of a MSPC methodology able to early detect disturbances to the roasting process resourcing to real-time acquisition of NIR spectra. A total of fifteen roasting batches were defined according to an experimental design to develop the MSPC models. This methodology was tested on a set of five batches where disturbances of different nature were imposed to simulate real faulty situations. Some of these batches were used to optimize the model while the remaining was used to test the methodology. A modelling strategy based on a time sliding window provided the best results in terms of distinguishing batches with and without disturbances, resourcing to typical MSPC charts: Hotelling's T 2 and squared predicted error statistics. A PCA model encompassing a time window of four minutes with three principal components was able to efficiently detect all disturbances assayed. NIR spectroscopy combined with the MSPC approach proved to be an adequate auxiliary tool for coffee roasters to detect faults in a conventional roasting process in real-time. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. Real-time risk assessment of operational events

    International Nuclear Information System (INIS)

    Perryman, L.J.; Foster, N.A.S.; Nicholls, D.R.; Grobbelaar, J.F.

    1996-01-01

    Probabilistic risk assessment (PRA) has always been fundamental to the licensing process of Koeberg nuclear power station. Furthermore, over the past 8 years PRA has assisted in many areas of operation. One of these areas is the real-time assessment of abnormal operating events. Over the years, considerable experience has been gained in using PRA to improve plant safety and performance. This paper presents some of the insights obtained in using PRA in such a dynamic role and demonstrates that, by developing and using the plant-specific 'living' PRA, considerable safety and financial gains can be obtained. These insights specifically concern the prerequisites before optimal use of a plant-specific 'living' PRA can be made. Finally, examples are presented of occurrences when PRA was used to improve plant safety and performance. These examples serve to demonstrate the advantages that can be obtained if sufficient resources are placed at the disposal of the PRA team. (orig.)

  4. Timing System Solution for MedAustron; Real-time Event and Data Distribution Network

    CERN Document Server

    Štefanič, R; Dedič, J; Gutleber, J; Moser, R

    2011-01-01

    MedAustron is an ion beam research and therapy centre under construction in Wiener Neustadt, Austria. The facility features a synchrotron particle accelerator for light ions. The timing system for this class of accelerators has been developed in close collaboration between MedAustron and Cosylab. Mitigating economical and technological risks, we have chosen a proven, widely used Micro Research Finland (MRF) timing equipment and redesigned its FPGA firmware, extending its high-logic services above transport layer, as required by machine specifics. We obtained a generic real-time broadcast network for coordinating actions of a compact, pulse-to-pulse modulation based particle accelerator. High-level services include support for virtual accelerators and a rich selection of event response mechanisms. The system uses a combination of a real-time link for downstream events and a non-real-time link for upstream messaging and non time-critical communication. It comes with National Instruments LabVI...

  5. Time to Tenure in Spanish Universities: An Event History Analysis

    Science.gov (United States)

    Sanz-Menéndez, Luis; Cruz-Castro, Laura; Alva, Kenedy

    2013-01-01

    Understanding how institutional incentives and mechanisms for assigning recognition shape access to a permanent job is important. This study, based on data from questionnaire survey responses and publications of 1,257 university science, biomedical and engineering faculty in Spain, attempts to understand the timing of getting a permanent position and the relevant factors that account for this transition, in the context of dilemmas between mobility and permanence faced by organizations. Using event history analysis, the paper looks at the time to promotion and the effects of some relevant covariates associated to academic performance, social embeddedness and mobility. We find that research productivity contributes to career acceleration, but that other variables are also significantly associated to a faster transition. Factors associated to the social elements of academic life also play a role in reducing the time from PhD graduation to tenure. However, mobility significantly increases the duration of the non-tenure stage. In contrast with previous findings, the role of sex is minor. The variations in the length of time to promotion across different scientific domains is confirmed, with faster career advancement for those in the Engineering and Technological Sciences compared with academics in the Biological and Biomedical Sciences. Results show clear effects of seniority, and rewards to loyalty, in addition to some measurements of performance and quality of the university granting the PhD, as key elements speeding up career advancement. Findings suggest the existence of a system based on granting early permanent jobs to those that combine social embeddedness and team integration with some good credentials regarding past and potential future performance, rather than high levels of mobility. PMID:24116199

  6. Time to tenure in Spanish universities: an event history analysis.

    Science.gov (United States)

    Sanz-Menéndez, Luis; Cruz-Castro, Laura; Alva, Kenedy

    2013-01-01

    Understanding how institutional incentives and mechanisms for assigning recognition shape access to a permanent job is important. This study, based on data from questionnaire survey responses and publications of 1,257 university science, biomedical and engineering faculty in Spain, attempts to understand the timing of getting a permanent position and the relevant factors that account for this transition, in the context of dilemmas between mobility and permanence faced by organizations. Using event history analysis, the paper looks at the time to promotion and the effects of some relevant covariates associated to academic performance, social embeddedness and mobility. We find that research productivity contributes to career acceleration, but that other variables are also significantly associated to a faster transition. Factors associated to the social elements of academic life also play a role in reducing the time from PhD graduation to tenure. However, mobility significantly increases the duration of the non-tenure stage. In contrast with previous findings, the role of sex is minor. The variations in the length of time to promotion across different scientific domains is confirmed, with faster career advancement for those in the Engineering and Technological Sciences compared with academics in the Biological and Biomedical Sciences. Results show clear effects of seniority, and rewards to loyalty, in addition to some measurements of performance and quality of the university granting the PhD, as key elements speeding up career advancement. Findings suggest the existence of a system based on granting early permanent jobs to those that combine social embeddedness and team integration with some good credentials regarding past and potential future performance, rather than high levels of mobility.

  7. Time to tenure in Spanish universities: an event history analysis.

    Directory of Open Access Journals (Sweden)

    Luis Sanz-Menéndez

    Full Text Available Understanding how institutional incentives and mechanisms for assigning recognition shape access to a permanent job is important. This study, based on data from questionnaire survey responses and publications of 1,257 university science, biomedical and engineering faculty in Spain, attempts to understand the timing of getting a permanent position and the relevant factors that account for this transition, in the context of dilemmas between mobility and permanence faced by organizations. Using event history analysis, the paper looks at the time to promotion and the effects of some relevant covariates associated to academic performance, social embeddedness and mobility. We find that research productivity contributes to career acceleration, but that other variables are also significantly associated to a faster transition. Factors associated to the social elements of academic life also play a role in reducing the time from PhD graduation to tenure. However, mobility significantly increases the duration of the non-tenure stage. In contrast with previous findings, the role of sex is minor. The variations in the length of time to promotion across different scientific domains is confirmed, with faster career advancement for those in the Engineering and Technological Sciences compared with academics in the Biological and Biomedical Sciences. Results show clear effects of seniority, and rewards to loyalty, in addition to some measurements of performance and quality of the university granting the PhD, as key elements speeding up career advancement. Findings suggest the existence of a system based on granting early permanent jobs to those that combine social embeddedness and team integration with some good credentials regarding past and potential future performance, rather than high levels of mobility.

  8. Predictive modeling in Clostridium acetobutylicum fermentations employing Raman spectroscopy and multivariate data analysis for real-time culture monitoring

    Science.gov (United States)

    Zu, Theresah N. K.; Liu, Sanchao; Germane, Katherine L.; Servinsky, Matthew D.; Gerlach, Elliot S.; Mackie, David M.; Sund, Christian J.

    2016-05-01

    The coupling of optical fibers with Raman instrumentation has proven to be effective for real-time monitoring of chemical reactions and fermentations when combined with multivariate statistical data analysis. Raman spectroscopy is relatively fast, with little interference from the water peak present in fermentation media. Medical research has explored this technique for analysis of mammalian cultures for potential diagnosis of some cancers. Other organisms studied via this route include Escherichia coli, Saccharomyces cerevisiae, and some Bacillus sp., though very little work has been performed on Clostridium acetobutylicum cultures. C. acetobutylicum is a gram-positive anaerobic bacterium, which is highly sought after due to its ability to use a broad spectrum of substrates and produce useful byproducts through the well-known Acetone-Butanol-Ethanol (ABE) fermentation. In this work, real-time Raman data was acquired from C. acetobutylicum cultures grown on glucose. Samples were collected concurrently for comparative off-line product analysis. Partial-least squares (PLS) models were built both for agitated cultures and for static cultures from both datasets. Media components and metabolites monitored include glucose, butyric acid, acetic acid, and butanol. Models were cross-validated with independent datasets. Experiments with agitation were more favorable for modeling with goodness of fit (QY) values of 0.99 and goodness of prediction (Q2Y) values of 0.98. Static experiments did not model as well as agitated experiments. Raman results showed the static experiments were chaotic, especially during and shortly after manual sampling.

  9. Neural network real time event selection for the DIRAC experiment

    CERN Document Server

    Kokkas, P; Tauscher, Ludwig; Vlachos, S

    2001-01-01

    The neural network first level trigger for the DIRAC experiment at CERN is presented. Both the neural network algorithm used and its actual hardware implementation are described. The system uses the fast plastic scintillator information of the DIRAC spectrometer. In 210 ns it selects events with two particles having low relative momentum. Such events are selected with an efficiency of more than 0.94. The corresponding rate reduction for background events is a factor of 2.5. (10 refs).

  10. Inferring Weighted Directed Association Networks from Multivariate Time Series with the Small-Shuffle Symbolic Transfer Entropy Spectrum Method

    Directory of Open Access Journals (Sweden)

    Yanzhu Hu

    2016-09-01

    Full Text Available Complex network methodology is very useful for complex system exploration. However, the relationships among variables in complex systems are usually not clear. Therefore, inferring association networks among variables from their observed data has been a popular research topic. We propose a method, named small-shuffle symbolic transfer entropy spectrum (SSSTES, for inferring association networks from multivariate time series. The method can solve four problems for inferring association networks, i.e., strong correlation identification, correlation quantification, direction identification and temporal relation identification. The method can be divided into four layers. The first layer is the so-called data layer. Data input and processing are the things to do in this layer. In the second layer, we symbolize the model data, original data and shuffled data, from the previous layer and calculate circularly transfer entropy with different time lags for each pair of time series variables. Thirdly, we compose transfer entropy spectrums for pairwise time series with the previous layer’s output, a list of transfer entropy matrix. We also identify the correlation level between variables in this layer. In the last layer, we build a weighted adjacency matrix, the value of each entry representing the correlation level between pairwise variables, and then get the weighted directed association network. Three sets of numerical simulated data from a linear system, a nonlinear system and a coupled Rossler system are used to show how the proposed approach works. Finally, we apply SSSTES to a real industrial system and get a better result than with two other methods.

  11. Robust multivariate analysis

    CERN Document Server

    J Olive, David

    2017-01-01

    This text presents methods that are robust to the assumption of a multivariate normal distribution or methods that are robust to certain types of outliers. Instead of using exact theory based on the multivariate normal distribution, the simpler and more applicable large sample theory is given.  The text develops among the first practical robust regression and robust multivariate location and dispersion estimators backed by theory.   The robust techniques  are illustrated for methods such as principal component analysis, canonical correlation analysis, and factor analysis.  A simple way to bootstrap confidence regions is also provided. Much of the research on robust multivariate analysis in this book is being published for the first time. The text is suitable for a first course in Multivariate Statistical Analysis or a first course in Robust Statistics. This graduate text is also useful for people who are familiar with the traditional multivariate topics, but want to know more about handling data sets with...

  12. A comparison of multivariate and univariate time series approaches to modelling and forecasting emergency department demand in Western Australia.

    Science.gov (United States)

    Aboagye-Sarfo, Patrick; Mai, Qun; Sanfilippo, Frank M; Preen, David B; Stewart, Louise M; Fatovich, Daniel M

    2015-10-01

    To develop multivariate vector-ARMA (VARMA) forecast models for predicting emergency department (ED) demand in Western Australia (WA) and compare them to the benchmark univariate autoregressive moving average (ARMA) and Winters' models. Seven-year monthly WA state-wide public hospital ED presentation data from 2006/07 to 2012/13 were modelled. Graphical and VARMA modelling methods were used for descriptive analysis and model fitting. The VARMA models were compared to the benchmark univariate ARMA and Winters' models to determine their accuracy to predict ED demand. The best models were evaluated by using error correction methods for accuracy. Descriptive analysis of all the dependent variables showed an increasing pattern of ED use with seasonal trends over time. The VARMA models provided a more precise and accurate forecast with smaller confidence intervals and better measures of accuracy in predicting ED demand in WA than the ARMA and Winters' method. VARMA models are a reliable forecasting method to predict ED demand for strategic planning and resource allocation. While the ARMA models are a closely competing alternative, they under-estimated future ED demand. Copyright © 2015 Elsevier Inc. All rights reserved.

  13. Timing system solution for MedAustron; Real-time event and data distribution network

    International Nuclear Information System (INIS)

    Stefanic, R.; Tavcar, R.; Dedic, J.; Gutleber, J.; Moser, R.

    2012-01-01

    MedAustron is an ion beam research and therapy centre under construction in Wiener Neustadt, Austria. The facility features a synchrotron particle accelerator for light ions. The timing system for this class of accelerators has been developed in close collaboration between MedAustron and Cosylab. Mitigating economical and technological risks, we have chosen a proven, widely used Micro Research Finland (MRF) timing equipment and redesigned its FPGA firmware, extending its high-logic services above transport layer, as required by machine specifics. We obtained a generic real-time broadcast network for coordinating actions of a compact, pulse-to-pulse modulation based particle accelerator. High-level services include support for virtual accelerators and a rich selection of event response mechanisms. The system uses a combination of a real-time link for downstream events and a non-real-time link for upstream messaging and non time-critical communication. It comes with National Instruments LabVIEW-based software support, ready to be integrated into PXIe based front-end controllers. This article explains the high level logic services provided by the real-time link, describes the non-real-time interfaces and presents the software configuration mechanisms. (authors)

  14. Event processing for business organizing the real-time enterprise

    CERN Document Server

    Luckham, David C

    2011-01-01

    Find out how Events Processing (EP) works and how it can workfor you Business Event Processing: An Introduction and StrategyGuide thoroughly describes what EP is, how to use it, and howit relates to other popular information technology architecturessuch as Service Oriented Architecture. Explains how sense and response architectures are being appliedwith tremendous results to businesses throughout the world andshows businesses how they can get started implementing EPShows how to choose business event processing technology tosuit your specific business needs and how to keep costs of adoptingit

  15. Nonstochastic Analysis of Manufacturing Systems Using Timed-Event Graphs

    DEFF Research Database (Denmark)

    Hulgaard, Henrik; Amon, Tod

    1996-01-01

    Using automated methods to analyze the temporal behavior ofmanufacturing systems has proven to be essential and quite beneficial.Popular methodologies include Queueing networks, Markov chains,simulation techniques, and discrete event systems (such as Petrinets). These methodologies are primarily...

  16. Dividing time: Concurrent timing of auditory and visual events by young and elderly adults

    OpenAIRE

    McAuley, J. Devin; Miller, Jonathan P.; Wang, Mo; Pang, Kevin C. H.

    2010-01-01

    This article examines age differences in individual’s ability to produce the durations of learned auditory and visual target events either in isolation (focused attention) or concurrently (divided attention). Young adults produced learned target durations equally well in focused and divided attention conditions. Older adults in contrast showed an age-related increase in timing variability in divided attention conditions that tended to be more pronounced for visual targets than for auditory ta...

  17. Forecasting with quantitative methods the impact of special events in time series

    OpenAIRE

    Nikolopoulos, Konstantinos

    2010-01-01

    Abstract Quantitative methods are very successful for producing baseline forecasts of time series; however these models fail to forecast neither the timing nor the impact of special events such as promotions or strikes. In most of the cases the timing of such events is not known so they are usually referred as shocks (economics) or special events (forecasting). Sometimes the timing of such events is known a priori (i.e. a future promotion); but even then the impact of the forthcom...

  18. Dividing time: concurrent timing of auditory and visual events by young and elderly adults.

    Science.gov (United States)

    McAuley, J Devin; Miller, Jonathan P; Wang, Mo; Pang, Kevin C H

    2010-07-01

    This article examines age differences in individual's ability to produce the durations of learned auditory and visual target events either in isolation (focused attention) or concurrently (divided attention). Young adults produced learned target durations equally well in focused and divided attention conditions. Older adults, in contrast, showed an age-related increase in timing variability in divided attention conditions that tended to be more pronounced for visual targets than for auditory targets. Age-related impairments were associated with a decrease in working memory span; moreover, the relationship between working memory and timing performance was largest for visual targets in divided attention conditions.

  19. Handling time misalignment and rank deficiency in liquid chromatography by multivariate curve resolution: Quantitation of five biogenic amines in fish.

    Science.gov (United States)

    Pinto, Licarion; Díaz Nieto, César Horacio; Zón, María Alicia; Fernández, Héctor; de Araujo, Mario Cesar Ugulino

    2016-01-01

    Biogenic amines (BAs) are used for identifying spoilage in food. The most common are tryptamine (TRY), 2-phenylethylamine (PHE), putrescine (PUT), cadaverine (CAD) and histamine (HIS). Due to lack of chromophores, chemical derivatization with dansyl was employed to analyze these BAs using high performance liquid chromatography with a diode array detector (HPLC-DAD). However, the derivatization reaction occurs with any primary or secondary amine, leading to co-elution of analytes and interferents with identical spectral profiles, and thus causing rank deficiency. When the spectral profile is the same and peak misalignment is present on the chromatographic runs, it is not possible to handle the data only with Multivariate Curve Resolution and Alternative Least Square (MCR-ALS), by augmenting the time, or the spectral mode. A way to circumvent this drawback is to receive information from another detector that leads to a selective profile for the analyte. To overcome both problems, (tri-linearity break in time, and spectral mode), this paper proposes a new analytical methodology for fast quantitation of these BAs in fish with HPLC-DAD by using the icoshift algorithm for temporal misalignment correction before MCR-ALS spectral mode augmented treatment. Limits of detection, relative errors of prediction (REP) and average recoveries, ranging from 0.14 to 0.50 µg mL(-1), 3.5-8.8% and 88.08%-99.68%, respectively. These are outstanding results obtained, reaching quantification limits for the five BAs much lower than those established by the Food and Agriculture Organization of the United Nations and World Health Organization (FAO/WHO), and the European Food Safety Authority (EFSA), all without any pre-concentration steps. The concentrations of BAs in fish samples ranged from 7.82 to 29.41 µg g(-1), 8.68-25.95 µg g(-1), 4.76-28.54 µg g(-1), 5.18-39.95 µg g(-1) and 1.45-52.62 µg g(-1) for TRY, PHE, PUT, CAD, and HIS, respectively. In addition, the proposed method spends

  20. Rainfall timing and runoff: The influence of the criterion for rain event separation

    OpenAIRE

    Molina-Sanchis, Isabel; Lázaro, Roberto; Arnau-Rosalén, Eva; Calvo-Cases, Adolfo

    2016-01-01

    Rain is not uniform in time and space in semiarid areas and its distribution is very important for the runoff process. Hydrological studies usually divide rainfall into events. However, defining rain events is complicated, and rain characteristics vary depending on how the events are delimited. Choosing a minimum inter-event time (MIT) is a commonly used criterion. Our hypothesis is that there will be an optimal MIT that explains the maximum part of the variance of the runoff, with time to ru...

  1. Handling time misalignment and rank deficiency in liquid chromatography by multivariate curve resolution: Quantitation of five biogenic amines in fish

    International Nuclear Information System (INIS)

    Pinto, Licarion; Díaz Nieto, César Horacio; Zón, María Alicia; Fernández, Héctor; Ugulino de Araujo, Mario Cesar

    2016-01-01

    Biogenic amines (BAs) are used for identifying spoilage in food. The most common are tryptamine (TRY), 2-phenylethylamine (PHE), putrescine (PUT), cadaverine (CAD) and histamine (HIS). Due to lack of chromophores, chemical derivatization with dansyl was employed to analyze these BAs using high performance liquid chromatography with a diode array detector (HPLC-DAD). However, the derivatization reaction occurs with any primary or secondary amine, leading to co-elution of analytes and interferents with identical spectral profiles, and thus causing rank deficiency. When the spectral profile is the same and peak misalignment is present on the chromatographic runs, it is not possible to handle the data only with Multivariate Curve Resolution and Alternative Least Square (MCR-ALS), by augmenting the time, or the spectral mode. A way to circumvent this drawback is to receive information from another detector that leads to a selective profile for the analyte. To overcome both problems, (tri-linearity break in time, and spectral mode), this paper proposes a new analytical methodology for fast quantitation of these BAs in fish with HPLC-DAD by using the icoshift algorithm for temporal misalignment correction before MCR-ALS spectral mode augmented treatment. Limits of detection, relative errors of prediction (REP) and average recoveries, ranging from 0.14 to 0.50 µg mL"−"1, 3.5–8.8% and 88.08%–99.68%, respectively. These are outstanding results obtained, reaching quantification limits for the five BAs much lower than those established by the Food and Agriculture Organization of the United Nations and World Health Organization (FAO/WHO), and the European Food Safety Authority (EFSA), all without any pre-concentration steps. The concentrations of BAs in fish samples ranged from 7.82 to 29.41 µg g"−"1, 8.68–25.95 µg g"−"1, 4.76–28.54 µg g"−"1, 5.18–39.95 µg g"−"1 and 1.45–52.62 µg g"−"1 for TRY, PHE, PUT, CAD, and HIS, respectively. In

  2. Handling time misalignment and rank deficiency in liquid chromatography by multivariate curve resolution: Quantitation of five biogenic amines in fish

    Energy Technology Data Exchange (ETDEWEB)

    Pinto, Licarion [Laboratório de Automação e Instrumentação em Química Analítica e Quimiometria (LAQA), Universidade Federal da Paraíba, CCEN, Departamento de Química, Caixa Postal 5093, CEP 58051-970, João Pessoa, PB (Brazil); Díaz Nieto, César Horacio; Zón, María Alicia; Fernández, Héctor [Departamento de Química, Facultad de Ciencias Exactas, Físico-Químicas y Naturales, Universidad Nacional de Río Cuarto, 5800, Río Cuarto (Argentina); Ugulino de Araujo, Mario Cesar, E-mail: laqa@quimica.ufpb.br [Laboratório de Automação e Instrumentação em Química Analítica e Quimiometria (LAQA), Universidade Federal da Paraíba, CCEN, Departamento de Química, Caixa Postal 5093, CEP 58051-970, João Pessoa, PB (Brazil)

    2016-01-01

    Biogenic amines (BAs) are used for identifying spoilage in food. The most common are tryptamine (TRY), 2-phenylethylamine (PHE), putrescine (PUT), cadaverine (CAD) and histamine (HIS). Due to lack of chromophores, chemical derivatization with dansyl was employed to analyze these BAs using high performance liquid chromatography with a diode array detector (HPLC-DAD). However, the derivatization reaction occurs with any primary or secondary amine, leading to co-elution of analytes and interferents with identical spectral profiles, and thus causing rank deficiency. When the spectral profile is the same and peak misalignment is present on the chromatographic runs, it is not possible to handle the data only with Multivariate Curve Resolution and Alternative Least Square (MCR-ALS), by augmenting the time, or the spectral mode. A way to circumvent this drawback is to receive information from another detector that leads to a selective profile for the analyte. To overcome both problems, (tri-linearity break in time, and spectral mode), this paper proposes a new analytical methodology for fast quantitation of these BAs in fish with HPLC-DAD by using the icoshift algorithm for temporal misalignment correction before MCR-ALS spectral mode augmented treatment. Limits of detection, relative errors of prediction (REP) and average recoveries, ranging from 0.14 to 0.50 µg mL{sup −1}, 3.5–8.8% and 88.08%–99.68%, respectively. These are outstanding results obtained, reaching quantification limits for the five BAs much lower than those established by the Food and Agriculture Organization of the United Nations and World Health Organization (FAO/WHO), and the European Food Safety Authority (EFSA), all without any pre-concentration steps. The concentrations of BAs in fish samples ranged from 7.82 to 29.41 µg g{sup −1}, 8.68–25.95 µg g{sup −1}, 4.76–28.54 µg g{sup −1}, 5.18–39.95 µg g{sup −1} and 1.45–52.62 µg g{sup −1} for TRY, PHE, PUT, CAD, and

  3. Methods of Multivariate Analysis

    CERN Document Server

    Rencher, Alvin C

    2012-01-01

    Praise for the Second Edition "This book is a systematic, well-written, well-organized text on multivariate analysis packed with intuition and insight . . . There is much practical wisdom in this book that is hard to find elsewhere."-IIE Transactions Filled with new and timely content, Methods of Multivariate Analysis, Third Edition provides examples and exercises based on more than sixty real data sets from a wide variety of scientific fields. It takes a "methods" approach to the subject, placing an emphasis on how students and practitioners can employ multivariate analysis in real-life sit

  4. Efficient algorithms for approximate time separation of events

    Indian Academy of Sciences (India)

    R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

    in the verification and analysis of asynchronous and concurrent systems. ...... Gunawardena J 1994 Timing analysis of digital circuits and the theory of min-max ... Williams T E 1994 Performance of iterative computation in self-timed rings.

  5. Multivariable Real-Time Control of Viscosity Curve for a Continuous Production Process of a Non-Newtonian Fluid

    Directory of Open Access Journals (Sweden)

    Roberto Mei

    2018-01-01

    Full Text Available The application of a multivariable predictive controller to the mixing process for the production of a non-Newtonian fluid is discussed in this work. A data-driven model has been developed to describe the dynamic behaviour of the rheological properties of the fluid as a function of the operating conditions using experimental data collected in a pilot plant. The developed model provides a realistic process representation and it is used to test and verify the multivariable controller, which has been designed to maintain viscosity curves of the non-Newtonian fluid within a given region of the viscosity-vs-shear rate plane in presence of process disturbances occurring in the mixing process.

  6. Classification of chilli sauces: Multivariate pattern recognition using selected GCMS retention time peaks of chilli sauces samples

    International Nuclear Information System (INIS)

    Low, Kah Hin; Sharifuddin Mohd Zain; Mohd Radzi Abas

    2008-01-01

    As a preliminary work on the possibility of separating classes of chili sauces based on taste or customer preferences, organic compounds from different kinds of chili sauces of various brands were separated and analyzed by gas chromatography/ mass spectrometry (GC/ MS). It was found that these organic compounds do form a basis for separation of different types of sauces. The similarity and dissimilarity of chromatograms due to the organic composition of the chili sauces were explored by multivariate pattern recognition techniques based on cluster analysis (CA) and principal component analysis (PCA). Both CA and PCA results exhibit four linearly separable classes, namely general sauces, hot sauces, sauces with benzoic acid and sauces with garlic. It was concluded that by using chosen retention peaks in the chromatograms of various sauce samples as multivariate features, CA and PCA can be successfully used to reveal the natural clusters existing in chili sauces according to their organic composition. (author)

  7. Application of combined multivariate techniques for the description of time-resolved powder X-ray diffraction data

    Czech Academy of Sciences Publication Activity Database

    Taris, A.; Grosso, M.; Brundu, M.; Guida, V.; Viani, Alberto

    2017-01-01

    Roč. 50, č. 2 (2017), s. 451-461 ISSN 1600-5767 R&D Projects: GA MŠk(CZ) LO1219 Keywords : in situ X-ray powder diffraction * amorphous content * chemically bonded ceramic s * statistical total correlation spectroscopy * multivariate curve resolution Subject RIV: JJ - Other Materials OBOR OECD: Materials engineering Impact factor: 2.495, year: 2016 http://journals.iucr.org/j/issues/2017/02/00/ap5006/index.html

  8. Geological Time, Biological Events and the Learning Transfer Problem

    Science.gov (United States)

    Johnson, Claudia C.; Middendorf, Joan; Rehrey, George; Dalkilic, Mehmet M.; Cassidy, Keely

    2014-01-01

    Comprehension of geologic time does not come easily, especially for students who are studying the earth sciences for the first time. This project investigated the potential success of two teaching interventions that were designed to help non-science majors enrolled in an introductory geology class gain a richer conceptual understanding of the…

  9. Event timing in high purity germanium coaxial detectors

    International Nuclear Information System (INIS)

    El-Ibiary, M.Y.

    1979-08-01

    The timing of gamma ray radiation in systems using high purity coaxial germanium detectors is analyzed and compared to that of systems using Ge(Li) detectors. The analysis takes into account the effect of the residual impurities on the electric field distribution, and hence on the rate of rise of the electrical pulses delivered to the timing module. Conditions under which the electric field distribution could lead to an improvement in timing performance, are identified. The results of the analysis confirm the experimental results published elsewhere and when compared with those for Ge(Li) detectors, which usually operate under conditions of charge carrier velocity saturation, confirm that high purity germanium detectors need not have inferior timing characteristics. A chart is given to provide a quantitative basis on which the trade off between the radius of the detector and its time resolution may be made

  10. The Effect of the Great Moderation on the U.S. Business Cycle in a Time-varying Multivariate Trend-cycle Model

    OpenAIRE

    Drew Creal; Siem Jan Koopman; Eric Zivot

    2008-01-01

    In this paper we investigate whether the dynamic properties of the U.S. business cycle have changed in the last fifty years. For this purpose we develop a flexible business cycle indicator that is constructed from a moderate set of macroeconomic time series. The coincident economic indicator is based on a multivariate trend-cycle decomposition model that accounts for time variation in macroeconomic volatility, known as the great moderation. In particular, we consider an unobserved components ...

  11. Real-time complex event processing for cloud resources

    Science.gov (United States)

    Adam, M.; Cordeiro, C.; Field, L.; Giordano, D.; Magnoni, L.

    2017-10-01

    The ongoing integration of clouds into the WLCG raises the need for detailed health and performance monitoring of the virtual resources in order to prevent problems of degraded service and interruptions due to undetected failures. When working in scale, the existing monitoring diversity can lead to a metric overflow whereby the operators need to manually collect and correlate data from several monitoring tools and frameworks, resulting in tens of different metrics to be constantly interpreted and analyzed per virtual machine. In this paper we present an ESPER based standalone application which is able to process complex monitoring events coming from various sources and automatically interpret data in order to issue alarms upon the resources’ statuses, without interfering with the actual resources and data sources. We will describe how this application has been used with both commercial and non-commercial cloud activities, allowing the operators to quickly be alarmed and react to misbehaving VMs and LHC experiments’ workflows. We will present the pattern analysis mechanisms being used, as well as the surrounding Elastic and REST API interfaces where the alarms are collected and served to users.

  12. Optical timing receiver for the NASA Spaceborne Ranging System. Part II: high precision event-timing digitizer

    Energy Technology Data Exchange (ETDEWEB)

    Leskovar, Branko; Turko, Bojan

    1978-08-01

    Position-resolution capabilities of the NASA Spaceborne Laser Ranging System are essentially determined by the timeresolution capabilities of its optical timing receiver. The optical timing receiver consists of a fast photoelectric device; (e.g., photomultiplier or an avalanche photodiode detector), a timing discriminator, a high-precision event-timing digitizer, and a signal-processing system. The time-resolution capabilities of the receiver are determined by the photoelectron time spread of the photoelectric device, the time walk and resolution characteristics of the timing discriminator, and the resolution of the event-timing digitizer. It is thus necessary to evaluate available fast photoelectronic devices with respect to the time-resolution capabilities, and to develop a very low time walk timing discriminator and a high-resolution event-timing digitizer to be used in the high-resolution spaceborne laser ranging system receiver. This part of the report describes the development of a high precision event-timing digitizer. The event-timing digitizer is basically a combination of a very accurate high resolution real time digital clock and an interval timer. The timing digitizer is a high resolution multiple stop clock, counting the time up to 131 days in 19.5 ps increments.

  13. Real-time monitoring of clinical processes using complex event processing and transition systems.

    Science.gov (United States)

    Meinecke, Sebastian

    2014-01-01

    Dependencies between tasks in clinical processes are often complex and error-prone. Our aim is to describe a new approach for the automatic derivation of clinical events identified via the behaviour of IT systems using Complex Event Processing. Furthermore we map these events on transition systems to monitor crucial clinical processes in real-time for preventing and detecting erroneous situations.

  14. Causality and associative holography of time-and-space domain events

    International Nuclear Information System (INIS)

    Rebane, Aleksander

    2014-01-01

    We consider reference-free associative recall of time-and-space domain holograms of arbitrary non-stationary optical object amplitudes or events. We show that if the probe fragment correlates with the recorded event either in space or in time coordinates or in both, then the hologram faithfully reproduces those missing parts (sub-events) that occur simultaneously or later in time with respect to the probe fragment. However, if a missing sub-event occurred before the fragment used as associative probe, then the hologram will not play this information back due to the time arrow imposed by causality. (paper)

  15. Timing of Childhood Events and Early-Adult Household Formation.

    Science.gov (United States)

    Hill, Martha S.; And Others

    1996-01-01

    Identified a number of risk factors contributing to early household formation. Found that for girls, factors included mother's educational level and birth order; for boys, parental divorce at any stage of childhood. Risk factors common to boys and girls were age of mother at time of child's birth and race. (HTH)

  16. love in a time of scarcity: an event- hermeneutical interpretation

    African Journals Online (AJOL)

    But love is a risk: it may happen, but it need not. ..... This issue incorporates perhaps the strongest perplexity of all: how can we think of a ... Dalferth identifies three types of hermeneutics in theology, based on the .... abroad, living a rebellious life. ..... shortage of food, money or time, you magnify the behaviour that is causing.

  17. Determination of P – wave arrival time of acoustic events

    Directory of Open Access Journals (Sweden)

    Matěj Petružálek

    2010-10-01

    Full Text Available The new approach to the P-wave arrival time determination based on acoustic emission data from loading experiments is tested.The algorithm used in this paper is built on the STA/LTA function computed by a convolution that speeds up the computation processvery much. The picking process makes use of shifting of temporary onset until certain conditions are fulfill and as a main decisioncriterion on the threshold exceeding of the STA/LTA derivation function is used. The P-wave onset time is determined in a selectedinterval that corresponds to the theoretical propagation of elastic wave in the rock sample. Results obtained by our algorithm werecorrelated with data acquired manually and a high order statistic software as well.

  18. Multivariate statistical process control (MSPC) using Raman spectroscopy for in-line culture cell monitoring considering time-varying batches synchronized with correlation optimized warping (COW).

    Science.gov (United States)

    Liu, Ya-Juan; André, Silvère; Saint Cristau, Lydia; Lagresle, Sylvain; Hannas, Zahia; Calvosa, Éric; Devos, Olivier; Duponchel, Ludovic

    2017-02-01

    Multivariate statistical process control (MSPC) is increasingly popular as the challenge provided by large multivariate datasets from analytical instruments such as Raman spectroscopy for the monitoring of complex cell cultures in the biopharmaceutical industry. However, Raman spectroscopy for in-line monitoring often produces unsynchronized data sets, resulting in time-varying batches. Moreover, unsynchronized data sets are common for cell culture monitoring because spectroscopic measurements are generally recorded in an alternate way, with more than one optical probe parallelly connecting to the same spectrometer. Synchronized batches are prerequisite for the application of multivariate analysis such as multi-way principal component analysis (MPCA) for the MSPC monitoring. Correlation optimized warping (COW) is a popular method for data alignment with satisfactory performance; however, it has never been applied to synchronize acquisition time of spectroscopic datasets in MSPC application before. In this paper we propose, for the first time, to use the method of COW to synchronize batches with varying durations analyzed with Raman spectroscopy. In a second step, we developed MPCA models at different time intervals based on the normal operation condition (NOC) batches synchronized by COW. New batches are finally projected considering the corresponding MPCA model. We monitored the evolution of the batches using two multivariate control charts based on Hotelling's T 2 and Q. As illustrated with results, the MSPC model was able to identify abnormal operation condition including contaminated batches which is of prime importance in cell culture monitoring We proved that Raman-based MSPC monitoring can be used to diagnose batches deviating from the normal condition, with higher efficacy than traditional diagnosis, which would save time and money in the biopharmaceutical industry. Copyright © 2016 Elsevier B.V. All rights reserved.

  19. A new approach in space-time analysis of multivariate hydrological data: Application to Brazil's Nordeste region rainfall

    Science.gov (United States)

    Sicard, Emeline; Sabatier, Robert; Niel, HéLèNe; Cadier, Eric

    2002-12-01

    The objective of this paper is to implement an original method for spatial and multivariate data, combining a method of three-way array analysis (STATIS) with geostatistical tools. The variables of interest are the monthly amounts of rainfall in the Nordeste region of Brazil, recorded from 1937 to 1975. The principle of the technique is the calculation of a linear combination of the initial variables, containing a large part of the initial variability and taking into account the spatial dependencies. It is a promising method that is able to analyze triple variability: spatial, seasonal, and interannual. In our case, the first component obtained discriminates a group of rain gauges, corresponding approximately to the Agreste, from all the others. The monthly variables of July and August strongly influence this separation. Furthermore, an annual study brings out the stability of the spatial structure of components calculated for each year.

  20. Detecting relationships between the interannual variability in climate records and ecological time series using a multivariate statistical approach - four case studies for the North Sea region

    Energy Technology Data Exchange (ETDEWEB)

    Heyen, H. [GKSS-Forschungszentrum Geesthacht GmbH (Germany). Inst. fuer Gewaesserphysik

    1998-12-31

    A multivariate statistical approach is presented that allows a systematic search for relationships between the interannual variability in climate records and ecological time series. Statistical models are built between climatological predictor fields and the variables of interest. Relationships are sought on different temporal scales and for different seasons and time lags. The possibilities and limitations of this approach are discussed in four case studies dealing with salinity in the German Bight, abundance of zooplankton at Helgoland Roads, macrofauna communities off Norderney and the arrival of migratory birds on Helgoland. (orig.) [Deutsch] Ein statistisches, multivariates Modell wird vorgestellt, das eine systematische Suche nach potentiellen Zusammenhaengen zwischen Variabilitaet in Klima- und oekologischen Zeitserien erlaubt. Anhand von vier Anwendungsbeispielen wird der Klimaeinfluss auf den Salzgehalt in der Deutschen Bucht, Zooplankton vor Helgoland, Makrofauna vor Norderney, und die Ankunft von Zugvoegeln auf Helgoland untersucht. (orig.)

  1. fixedTimeEvents: An R package for the distribution of distances between discrete events in fixed time

    Directory of Open Access Journals (Sweden)

    Kristian Hovde Liland

    2016-01-01

    Full Text Available When a series of Bernoulli trials occur within a fixed time frame or limited space, it is often interesting to assess if the successful outcomes have occurred completely at random, or if they tend to group together. One example, in genetics, is detecting grouping of genes within a genome. Approximations of the distribution of successes are possible, but they become inaccurate for small sample sizes. In this article, we describe the exact distribution of time between random, non-overlapping successes in discrete time of fixed length. A complete description of the probability mass function, the cumulative distribution function, mean, variance and recurrence relation is included. We propose an associated test for the over-representation of short distances and illustrate the methodology through relevant examples. The theory is implemented in an R package including probability mass, cumulative distribution, quantile function, random number generator, simulation functions, and functions for testing.

  2. Simulation of unexpected events in using controlled working time

    International Nuclear Information System (INIS)

    Ruzicka, F.; Kindler, E.

    1987-01-01

    The RHYTHMS data base is described for random and rhythmic processes, constructed using the SIMULA programming language. An example is shown of its application in the simulation of accidents in discharging radioactive wastes from a bituminization line in a nuclear power plant. The radioactive waste is embedded in bitumen and shipped in unsealed drums. Normal operation envisages such processing of a certain number of drums during one shift. However, an accident can happen whose elimination takes a certain time. The possibility is also considered of personnel exposure and the necessity of replacing the exposed personnel. The selection of the correct solution is then given by the capability of removing all drums and by the determination of the number of work teams that have to be employed for the removal. Object-oriented programming was applied in the solution of the base. (J.B.). 3 refs

  3. Integrating Continuous-Time and Discrete-Event Concepts in Process Modelling, Simulation and Control

    NARCIS (Netherlands)

    Beek, van D.A.; Gordijn, S.H.F.; Rooda, J.E.; Ertas, A.

    1995-01-01

    Currently, modelling of systems in the process industry requires the use of different specification languages for the specification of the discrete-event and continuous-time subsystems. In this way, models are restricted to individual subsystems of either a continuous-time or discrete-event nature.

  4. Estimating the Probability of a Rare Event Over a Finite Time Horizon

    NARCIS (Netherlands)

    de Boer, Pieter-Tjerk; L'Ecuyer, Pierre; Rubino, Gerardo; Tuffin, Bruno

    2007-01-01

    We study an approximation for the zero-variance change of measure to estimate the probability of a rare event in a continuous-time Markov chain. The rare event occurs when the chain reaches a given set of states before some fixed time limit. The jump rates of the chain are expressed as functions of

  5. Boosting joint models for longitudinal and time-to-event data

    DEFF Research Database (Denmark)

    Waldmann, Elisabeth; Taylor-Robinson, David; Klein, Nadja

    2017-01-01

    Joint models for longitudinal and time-to-event data have gained a lot of attention in the last few years as they are a helpful technique clinical studies where longitudinal outcomes are recorded alongside event times. Those two processes are often linked and the two outcomes should thus be model...

  6. Joint Models for Longitudinal and Time-to-Event Data With Applications in R

    CERN Document Server

    Rizopoulos, Dimitris

    2012-01-01

    In longitudinal studies it is often of interest to investigate how a marker that is repeatedly measured in time is associated with a time to an event of interest, e.g., prostate cancer studies where longitudinal PSA level measurements are collected in conjunction with the time-to-recurrence. Joint Models for Longitudinal and Time-to-Event Data: With Applications in R provides a full treatment of random effects joint models for longitudinal and time-to-event outcomes that can be utilized to analyze such data. The content is primarily explanatory, focusing on applications of joint modeling, but

  7. Events

    Directory of Open Access Journals (Sweden)

    Igor V. Karyakin

    2016-02-01

    Full Text Available The 9th ARRCN Symposium 2015 was held during 21st–25th October 2015 at the Novotel Hotel, Chumphon, Thailand, one of the most favored travel destinations in Asia. The 10th ARRCN Symposium 2017 will be held during October 2017 in the Davao, Philippines. International Symposium on the Montagu's Harrier (Circus pygargus «The Montagu's Harrier in Europe. Status. Threats. Protection», organized by the environmental organization «Landesbund für Vogelschutz in Bayern e.V.» (LBV was held on November 20-22, 2015 in Germany. The location of this event was the city of Wurzburg in Bavaria.

  8. Leveraging Long-term Seismic Catalogs for Automated Real-time Event Classification

    Science.gov (United States)

    Linville, L.; Draelos, T.; Pankow, K. L.; Young, C. J.; Alvarez, S.

    2017-12-01

    We investigate the use of labeled event types available through reviewed seismic catalogs to produce automated event labels on new incoming data from the crustal region spanned by the cataloged events. Using events cataloged by the University of Utah Seismograph Stations between October, 2012 and June, 2017, we calculate the spectrogram for a time window that spans the duration of each event as seen on individual stations, resulting in 110k event spectrograms (50% local earthquakes examples, 50% quarry blasts examples). Using 80% of the randomized example events ( 90k), a classifier is trained to distinguish between local earthquakes and quarry blasts. We explore variations of deep learning classifiers, incorporating elements of convolutional and recurrent neural networks. Using a single-layer Long Short Term Memory recurrent neural network, we achieve 92% accuracy on the classification task on the remaining 20K test examples. Leveraging the decisions from a group of stations that detected the same event by using the median of all classifications in the group increases the model accuracy to 96%. Additional data with equivalent processing from 500 more recently cataloged events (July, 2017), achieves the same accuracy as our test data on both single-station examples and multi-station medians, suggesting that the model can maintain accurate and stable classification rates on real-time automated events local to the University of Utah Seismograph Stations, with potentially minimal levels of re-training through time.

  9. Modal Identification of a Time-Invariant 6-Storey Model Test RC-Frame from Free Decay Tests using Multi-Variate Models

    DEFF Research Database (Denmark)

    Skjærbæk, P. S.; Nielsen, Søren R. K.; Kirkegaard, Poul Henning

    1997-01-01

    in the comparison. The data investigated are sampled from a laboratory model of a plane 6-storey, 2-bay RC-frame. The laboratory model is excited at the top storey where two different types of excitation where considered. In the first case the structure was excited in the first mode and in the second case......The scope of the paper is to apply multi-variate time-domain models for identification of eginfrequencies and mode shapes of a time- invariant model test Reinforced Concrete (RC) frame from measured decays. The frequencies and mode shapes of interest are the two lowest ones since they are normally...

  10. Modal Identification of a Time-Invariant 6-Storey Model Test RC-Frame from Free Decay Tests using Multi-Variate Models

    DEFF Research Database (Denmark)

    Skjærbæk, P. S.; Nielsen, Søren R. K.; Kirkegaard, Poul Henning

    in the comparison. The data investigated are sampled from a laboratory model of a plane 6-storey, 2-bay RC-frame. The laboratory model is excited at the top storey where two different types of excitation where considered. In the first case the structure was excited in the first mode and in the second case......The scope of the paper is to apply multi-variate time-domain models for identification of eginfrequencies and mode shapes of a time- invariant model test Reinforced Concrete (RC) frame from measured decays. The frequencies and mode shapes of interest are the two lowest ones since they are normally...

  11. Multiscale Characterization of PM2.5 in Southern Taiwan based on Noise-assisted Multivariate Empirical Mode Decomposition and Time-dependent Intrinsic Correlation

    Science.gov (United States)

    Hsiao, Y. R.; Tsai, C.

    2017-12-01

    As the WHO Air Quality Guideline indicates, ambient air pollution exposes world populations under threat of fatal symptoms (e.g. heart disease, lung cancer, asthma etc.), raising concerns of air pollution sources and relative factors. This study presents a novel approach to investigating the multiscale variations of PM2.5 in southern Taiwan over the past decade, with four meteorological influencing factors (Temperature, relative humidity, precipitation and wind speed),based on Noise-assisted Multivariate Empirical Mode Decomposition(NAMEMD) algorithm, Hilbert Spectral Analysis(HSA) and Time-dependent Intrinsic Correlation(TDIC) method. NAMEMD algorithm is a fully data-driven approach designed for nonlinear and nonstationary multivariate signals, and is performed to decompose multivariate signals into a collection of channels of Intrinsic Mode Functions (IMFs). TDIC method is an EMD-based method using a set of sliding window sizes to quantify localized correlation coefficients for multiscale signals. With the alignment property and quasi-dyadic filter bank of NAMEMD algorithm, one is able to produce same number of IMFs for all variables and estimates the cross correlation in a more accurate way. The performance of spectral representation of NAMEMD-HSA method is compared with Complementary Empirical Mode Decomposition/ Hilbert Spectral Analysis (CEEMD-HSA) and Wavelet Analysis. The nature of NAMAMD-based TDICC analysis is then compared with CEEMD-based TDIC analysis and the traditional correlation analysis.

  12. Monitoring Natural Events Globally in Near Real-Time Using NASA's Open Web Services and Tools

    Science.gov (United States)

    Boller, Ryan A.; Ward, Kevin Alan; Murphy, Kevin J.

    2015-01-01

    Since 1960, NASA has been making global measurements of the Earth from a multitude of space-based missions, many of which can be useful for monitoring natural events. In recent years, these measurements have been made available in near real-time, making it possible to use them to also aid in managing the response to natural events. We present the challenges and ongoing solutions to using NASA satellite data for monitoring and managing these events.

  13. Seizure-Onset Mapping Based on Time-Variant Multivariate Functional Connectivity Analysis of High-Dimensional Intracranial EEG: A Kalman Filter Approach.

    Science.gov (United States)

    Lie, Octavian V; van Mierlo, Pieter

    2017-01-01

    The visual interpretation of intracranial EEG (iEEG) is the standard method used in complex epilepsy surgery cases to map the regions of seizure onset targeted for resection. Still, visual iEEG analysis is labor-intensive and biased due to interpreter dependency. Multivariate parametric functional connectivity measures using adaptive autoregressive (AR) modeling of the iEEG signals based on the Kalman filter algorithm have been used successfully to localize the electrographic seizure onsets. Due to their high computational cost, these methods have been applied to a limited number of iEEG time-series (Kalman filter implementations, a well-known multivariate adaptive AR model (Arnold et al. 1998) and a simplified, computationally efficient derivation of it, for their potential application to connectivity analysis of high-dimensional (up to 192 channels) iEEG data. When used on simulated seizures together with a multivariate connectivity estimator, the partial directed coherence, the two AR models were compared for their ability to reconstitute the designed seizure signal connections from noisy data. Next, focal seizures from iEEG recordings (73-113 channels) in three patients rendered seizure-free after surgery were mapped with the outdegree, a graph-theory index of outward directed connectivity. Simulation results indicated high levels of mapping accuracy for the two models in the presence of low-to-moderate noise cross-correlation. Accordingly, both AR models correctly mapped the real seizure onset to the resection volume. This study supports the possibility of conducting fully data-driven multivariate connectivity estimations on high-dimensional iEEG datasets using the Kalman filter approach.

  14. Cognitive load and task condition in event- and time-based prospective memory: an experimental investigation.

    Science.gov (United States)

    Khan, Azizuddin; Sharma, Narendra K; Dixit, Shikha

    2008-09-01

    Prospective memory is memory for the realization of delayed intention. Researchers distinguish 2 kinds of prospective memory: event- and time-based (G. O. Einstein & M. A. McDaniel, 1990). Taking that distinction into account, the present authors explored participants' comparative performance under event- and time-based tasks. In an experimental study of 80 participants, the authors investigated the roles of cognitive load and task condition in prospective memory. Cognitive load (low vs. high) and task condition (event- vs. time-based task) were the independent variables. Accuracy in prospective memory was the dependent variable. Results showed significant differential effects under event- and time-based tasks. However, the effect of cognitive load was more detrimental in time-based prospective memory. Results also revealed that time monitoring is critical in successful performance of time estimation and so in time-based prospective memory. Similarly, participants' better performance on the event-based prospective memory task showed that they acted on the basis of environment cues. Event-based prospective memory was environmentally cued; time-based prospective memory required self-initiation.

  15. Towards RTOS support for mixed time-triggered and event-triggered task sets

    NARCIS (Netherlands)

    Heuvel, van den M.M.H.P.; Bril, R.J.; Lukkien, J.J.; Isovic, D.; Sankar Ramachandran, G.

    2012-01-01

    Many embedded systems have complex timing constraints and, at the same time, have flexibility requirements which prohibit offline planning of the entire system. To support a mixture of time-triggered and event-triggered tasks, some industrial systems deploy a real-time operating system (RTOS) with a

  16. A time-dependent event tree technique for modelling recovery operations

    International Nuclear Information System (INIS)

    Kohut, P.; Fitzpatrick, R.

    1991-01-01

    The development of a simplified time dependent event tree methodology is presented. The technique is especially applicable to describe recovery operations in nuclear reactor accident scenarios initiated by support system failures. The event tree logic is constructed using time dependent top events combined with a damage function that contains information about the final state time behavior of the reactor core. Both the failure and the success states may be utilized for the analysis. The method is illustrated by modeling the loss of service water function with special emphasis on the RCP [reactor coolant pump] seal LOCA [loss of coolant accident] scenario. 5 refs., 2 figs., 2 tabs

  17. Predictive event modelling in multicenter clinical trials with waiting time to response.

    Science.gov (United States)

    Anisimov, Vladimir V

    2011-01-01

    A new analytic statistical technique for predictive event modeling in ongoing multicenter clinical trials with waiting time to response is developed. It allows for the predictive mean and predictive bounds for the number of events to be constructed over time, accounting for the newly recruited patients and patients already at risk in the trial, and for different recruitment scenarios. For modeling patient recruitment, an advanced Poisson-gamma model is used, which accounts for the variation in recruitment over time, the variation in recruitment rates between different centers and the opening or closing of some centers in the future. A few models for event appearance allowing for 'recurrence', 'death' and 'lost-to-follow-up' events and using finite Markov chains in continuous time are considered. To predict the number of future events over time for an ongoing trial at some interim time, the parameters of the recruitment and event models are estimated using current data and then the predictive recruitment rates in each center are adjusted using individual data and Bayesian re-estimation. For a typical scenario (continue to recruit during some time interval, then stop recruitment and wait until a particular number of events happens), the closed-form expressions for the predictive mean and predictive bounds of the number of events at any future time point are derived under the assumptions of Markovian behavior of the event progression. The technique is efficiently applied to modeling different scenarios for some ongoing oncology trials. Case studies are considered. Copyright © 2011 John Wiley & Sons, Ltd.

  18. A novel way to detect correlations on multi-time scales, with temporal evolution and for multi-variables

    Science.gov (United States)

    Yuan, Naiming; Xoplaki, Elena; Zhu, Congwen; Luterbacher, Juerg

    2016-06-01

    In this paper, two new methods, Temporal evolution of Detrended Cross-Correlation Analysis (TDCCA) and Temporal evolution of Detrended Partial-Cross-Correlation Analysis (TDPCCA), are proposed by generalizing DCCA and DPCCA. Applying TDCCA/TDPCCA, it is possible to study correlations on multi-time scales and over different periods. To illustrate their properties, we used two climatological examples: i) Global Sea Level (GSL) versus North Atlantic Oscillation (NAO); and ii) Summer Rainfall over Yangtze River (SRYR) versus previous winter Pacific Decadal Oscillation (PDO). We find significant correlations between GSL and NAO on time scales of 60 to 140 years, but the correlations are non-significant between 1865-1875. As for SRYR and PDO, significant correlations are found on time scales of 30 to 35 years, but the correlations are more pronounced during the recent 30 years. By combining TDCCA/TDPCCA and DCCA/DPCCA, we proposed a new correlation-detection system, which compared to traditional methods, can objectively show how two time series are related (on which time scale, during which time period). These are important not only for diagnosis of complex system, but also for better designs of prediction models. Therefore, the new methods offer new opportunities for applications in natural sciences, such as ecology, economy, sociology and other research fields.

  19. Multivariate Analyses and Classification of Inertial Sensor Data to Identify Aging Effects on the Timed-Up-and-Go Test

    NARCIS (Netherlands)

    Vervoort, Danique; Vuillerme, Nicolas; Kosse, Nienke; Hortobágyi, Tibor; Lamoth, Claudine J C

    2016-01-01

    Many tests can crudely quantify age-related mobility decrease but instrumented versions of mobility tests could increase their specificity and sensitivity. The Timed-up-and-Go (TUG) test includes several elements that people use in daily life. The test has different transition phases: rise from a

  20. Adaptive Event-Triggered Control Based on Heuristic Dynamic Programming for Nonlinear Discrete-Time Systems.

    Science.gov (United States)

    Dong, Lu; Zhong, Xiangnan; Sun, Changyin; He, Haibo

    2017-07-01

    This paper presents the design of a novel adaptive event-triggered control method based on the heuristic dynamic programming (HDP) technique for nonlinear discrete-time systems with unknown system dynamics. In the proposed method, the control law is only updated when the event-triggered condition is violated. Compared with the periodic updates in the traditional adaptive dynamic programming (ADP) control, the proposed method can reduce the computation and transmission cost. An actor-critic framework is used to learn the optimal event-triggered control law and the value function. Furthermore, a model network is designed to estimate the system state vector. The main contribution of this paper is to design a new trigger threshold for discrete-time systems. A detailed Lyapunov stability analysis shows that our proposed event-triggered controller can asymptotically stabilize the discrete-time systems. Finally, we test our method on two different discrete-time systems, and the simulation results are included.

  1. Prediction of gas chromatography/electron capture detector retention times of chlorinated pesticides, herbicides, and organohalides by multivariate chemometrics methods

    International Nuclear Information System (INIS)

    Ghasemi, Jahanbakhsh; Asadpour, Saeid; Abdolmaleki, Azizeh

    2007-01-01

    A quantitative structure-retention relationship (QSRR) study, has been carried out on the gas chromatograph/electron capture detector (GC/ECD) system retention times (t R s) of 38 diverse chlorinated pesticides, herbicides, and organohalides by using molecular structural descriptors. Modeling of retention times of these compounds as a function of the theoretically derived descriptors was established by multiple linear regression (MLR) and partial least squares (PLS) regression. The stepwise regression using SPSS was used for the selection of the variables that resulted in the best-fitted models. Appropriate models with low standard errors and high correlation coefficients were obtained. Three types of molecular descriptors including electronic, steric and thermodynamic were used to develop a quantitative relationship between the retention times and structural properties. MLR and PLS analysis has been carried out to derive the best QSRR models. After variables selection, MLR and PLS methods used with leave-one-out cross validation for building the regression models. The predictive quality of the QSRR models were tested for an external prediction set of 12 compounds randomly chosen from 38 compounds. The PLS regression method was used to model the structure-retention relationships, more accurately. However, the results surprisingly showed more or less the same quality for MLR and PLS modeling according to squared regression coefficients R 2 which were 0.951 and 0.948 for MLR and PLS, respectively

  2. Towards Real-Time Detection of Gait Events on Different Terrains Using Time-Frequency Analysis and Peak Heuristics Algorithm.

    Science.gov (United States)

    Zhou, Hui; Ji, Ning; Samuel, Oluwarotimi Williams; Cao, Yafei; Zhao, Zheyi; Chen, Shixiong; Li, Guanglin

    2016-10-01

    Real-time detection of gait events can be applied as a reliable input to control drop foot correction devices and lower-limb prostheses. Among the different sensors used to acquire the signals associated with walking for gait event detection, the accelerometer is considered as a preferable sensor due to its convenience of use, small size, low cost, reliability, and low power consumption. Based on the acceleration signals, different algorithms have been proposed to detect toe off (TO) and heel strike (HS) gait events in previous studies. While these algorithms could achieve a relatively reasonable performance in gait event detection, they suffer from limitations such as poor real-time performance and are less reliable in the cases of up stair and down stair terrains. In this study, a new algorithm is proposed to detect the gait events on three walking terrains in real-time based on the analysis of acceleration jerk signals with a time-frequency method to obtain gait parameters, and then the determination of the peaks of jerk signals using peak heuristics. The performance of the newly proposed algorithm was evaluated with eight healthy subjects when they were walking on level ground, up stairs, and down stairs. Our experimental results showed that the mean F1 scores of the proposed algorithm were above 0.98 for HS event detection and 0.95 for TO event detection on the three terrains. This indicates that the current algorithm would be robust and accurate for gait event detection on different terrains. Findings from the current study suggest that the proposed method may be a preferable option in some applications such as drop foot correction devices and leg prostheses.

  3. WAITING TIME DISTRIBUTION OF SOLAR ENERGETIC PARTICLE EVENTS MODELED WITH A NON-STATIONARY POISSON PROCESS

    International Nuclear Information System (INIS)

    Li, C.; Su, W.; Fang, C.; Zhong, S. J.; Wang, L.

    2014-01-01

    We present a study of the waiting time distributions (WTDs) of solar energetic particle (SEP) events observed with the spacecraft WIND and GOES. The WTDs of both solar electron events (SEEs) and solar proton events (SPEs) display a power-law tail of ∼Δt –γ . The SEEs display a broken power-law WTD. The power-law index is γ 1 = 0.99 for the short waiting times (<70 hr) and γ 2 = 1.92 for large waiting times (>100 hr). The break of the WTD of SEEs is probably due to the modulation of the corotating interaction regions. The power-law index, γ ∼ 1.82, is derived for the WTD of the SPEs which is consistent with the WTD of type II radio bursts, indicating a close relationship between the shock wave and the production of energetic protons. The WTDs of SEP events can be modeled with a non-stationary Poisson process, which was proposed to understand the waiting time statistics of solar flares. We generalize the method and find that, if the SEP event rate λ = 1/Δt varies as the time distribution of event rate f(λ) = Aλ –α exp (– βλ), the time-dependent Poisson distribution can produce a power-law tail WTD of ∼Δt α –3 , where 0 ≤ α < 2

  4. Containment closure time following the loss of shutdown cooling event of YGN Units 3 and 4

    International Nuclear Information System (INIS)

    Seul, Kwang Won; Bang, Young Seok; Kim, Hho Jung

    1999-01-01

    The YGN Units 3 and 4 plant conditions during shutdown operation were reviewed to identify the possible event scenarios following the loss of shutdown cooling (SDC) event. For the five cases of typical reactor coolant system (RCS) configurations under the worst event sequence, such as unavailable secondary cooling and no RCS inventory makeup, the thermal hydraulic analyses were performed using the RELAP5/MOS3.2 code to investigate the plant behavior following the event. The thermal hydraulic analyses include the estimation of time to boil, time to core uncovery, and time to core heat up to determine the containment closure time to prevent the uncontrolled release of fission products to atmosphere. The result indicates that the containment closure is recommended to be achieved within 42 minutes after the loss of SDC for the steam generator (SG) inlet plenum manway open case or the large cold leg open case under the worst event sequence. The containment closure time is significantly dependent on the elevation and size of the opening and the SG secondary water level condition. It is also found that the containment closure needs to be initiated before the boiling time to ensure the survivability of the workers in the containment. These results will provide using information to operators to cope with the loss of SDC event. (Author). 15 refs., 3 tabs., 7 figs

  5. Limited preemptive scheduling of mixed time-triggered and event-triggered tasks

    NARCIS (Netherlands)

    Heuvel, van den M.M.H.P.; Bril, R.J.; Zhang, X.; Abdullah, S.M.J.; Isovic, D.

    2013-01-01

    Many embedded systems have complex timing constraints and, at the same time, have flexibility requirements which prohibit offline planning of the entire system. To support a mixture of time-triggered and event-triggered tasks, some industrial systems deploy a table-driven dispatcher for

  6. Time to Wound Healing and Major Adverse Limb Events in Patients with Critical Limb Ischemia Treated with Endovascular Revascularization.

    Science.gov (United States)

    Reed, Grant W; Salehi, Negar; Giglou, Pejman R; Kafa, Rami; Malik, Umair; Maier, Michael; Shishehbor, Mehdi H

    2016-10-01

    There are few studies that quantify the impact of time to wound healing on outcomes after endovascular revascularization of critical limb ischemia (CLI). In this retrospective study, 179 patients with CLI and tissue loss were assessed for adverse events after endovascular therapy. Associations between time to wound healing and outcomes were determined via Cox proportional hazards analysis. The long-term probability of events was assessed with Kaplan-Meier analysis. The primary end point was major adverse limb events (MALE-major amputation, surgical endarterectomy, or bypass). Secondary end points were major amputation, need for repeat endovascular therapy, and mortality. After multivariable adjustment for time-dependent wound healing, age, renal function, diabetes, and Rutherford class, independent predictors of MALE included the presence of an unhealed wound (hazard ratio [HR], 5.2; 95% confidence interval (CI), 2.3-11.8; P wounds compared with healed wounds (log-rank P wounds healed within 4 months had a lower probability of MALE than patients who did not heal by 4 months (log-rank, P = 0.04). Unhealed wounds were also independently associated with major amputation (HR, 9.0; 95% CI, 2.6-31.1; P = 0.0004), and patients whose wounds healed by 3 months had less major amputation (log-rank, P = 0.04). Unhealed wounds were independently associated with increased risk of mortality (HR, 42.7; 95% CI, 5.7-319.0; P = 0.002) but not repeat revascularization. Unhealed wounds are an independent risk factor for MALE, major amputation, and mortality after endovascular treatment of CLI. Wound healing within 3 months is associated with less risk of major amputation, and within 4 months less risk of MALE. A focus should be on achieving wound healing as fast as possible in this population. Copyright © 2016 Elsevier Inc. All rights reserved.

  7. Improving linear accelerator service response with a real- time electronic event reporting system.

    Science.gov (United States)

    Hoisak, Jeremy D P; Pawlicki, Todd; Kim, Gwe-Ya; Fletcher, Richard; Moore, Kevin L

    2014-09-08

    To track linear accelerator performance issues, an online event recording system was developed in-house for use by therapists and physicists to log the details of technical problems arising on our institution's four linear accelerators. In use since October 2010, the system was designed so that all clinical physicists would receive email notification when an event was logged. Starting in October 2012, we initiated a pilot project in collaboration with our linear accelerator vendor to explore a new model of service and support, in which event notifications were also sent electronically directly to dedicated engineers at the vendor's technical help desk, who then initiated a response to technical issues. Previously, technical issues were reported by telephone to the vendor's call center, which then disseminated information and coordinated a response with the Technical Support help desk and local service engineers. The purpose of this work was to investigate the improvements to clinical operations resulting from this new service model. The new and old service models were quantitatively compared by reviewing event logs and the oncology information system database in the nine months prior to and after initiation of the project. Here, we focus on events that resulted in an inoperative linear accelerator ("down" machine). Machine downtime, vendor response time, treatment cancellations, and event resolution were evaluated and compared over two equivalent time periods. In 389 clinical days, there were 119 machine-down events: 59 events before and 60 after introduction of the new model. In the new model, median time to service response decreased from 45 to 8 min, service engineer dispatch time decreased 44%, downtime per event decreased from 45 to 20 min, and treatment cancellations decreased 68%. The decreased vendor response time and reduced number of on-site visits by a service engineer resulted in decreased downtime and decreased patient treatment cancellations.

  8. Full-waveform detection of non-impulsive seismic events based on time-reversal methods

    Science.gov (United States)

    Solano, Ericka Alinne; Hjörleifsdóttir, Vala; Liu, Qinya

    2017-12-01

    We present a full-waveform detection method for non-impulsive seismic events, based on time-reversal principles. We use the strain Green's tensor as a matched filter, correlating it with continuous observed seismograms, to detect non-impulsive seismic events. We show that this is mathematically equivalent to an adjoint method for detecting earthquakes. We define the detection function, a scalar valued function, which depends on the stacked correlations for a group of stations. Event detections are given by the times at which the amplitude of the detection function exceeds a given value relative to the noise level. The method can make use of the whole seismic waveform or any combination of time-windows with different filters. It is expected to have an advantage compared to traditional detection methods for events that do not produce energetic and impulsive P waves, for example glacial events, landslides, volcanic events and transform-fault earthquakes for events which velocity structure along the path is relatively well known. Furthermore, the method has advantages over empirical Greens functions template matching methods, as it does not depend on records from previously detected events, and therefore is not limited to events occurring in similar regions and with similar focal mechanisms as these events. The method is not specific to any particular way of calculating the synthetic seismograms, and therefore complicated structural models can be used. This is particularly beneficial for intermediate size events that are registered on regional networks, for which the effect of lateral structure on the waveforms can be significant. To demonstrate the feasibility of the method, we apply it to two different areas located along the mid-oceanic ridge system west of Mexico where non-impulsive events have been reported. The first study area is between Clipperton and Siqueiros transform faults (9°N), during the time of two earthquake swarms, occurring in March 2012 and May

  9. Effect of a data buffer on the recorded distribution of time intervals for random events

    Energy Technology Data Exchange (ETDEWEB)

    Barton, J C [Polytechnic of North London (UK)

    1976-03-15

    The use of a data buffer enables the distribution of the time intervals between events to be studied for times less than the recording system dead-time but the usual negative exponential distribution for random events has to be modified. The theory for this effect is developed for an n-stage buffer followed by an asynchronous recorder. Results are evaluated for the values of n from 1 to 5. In the language of queueing theory the system studied is of type M/D/1/n+1, i.e. with constant service time and a finite number of places.

  10. Multivariate Analyses and Classification of Inertial Sensor Data to Identify Aging Effects on the Timed-Up-and-Go Test.

    Directory of Open Access Journals (Sweden)

    Danique Vervoort

    Full Text Available Many tests can crudely quantify age-related mobility decrease but instrumented versions of mobility tests could increase their specificity and sensitivity. The Timed-up-and-Go (TUG test includes several elements that people use in daily life. The test has different transition phases: rise from a chair, walk, 180° turn, walk back, turn, and sit-down on a chair. For this reason the TUG is an often used test to evaluate in a standardized way possible decline in balance and walking ability due to age and or pathology. Using inertial sensors, qualitative information about the performance of the sub-phases can provide more specific information about a decline in balance and walking ability. The first aim of our study was to identify variables extracted from the instrumented timed-up-and-go (iTUG that most effectively distinguished performance differences across age (age 18-75. Second, we determined the discriminative ability of those identified variables to classify a younger (age 18-45 and older age group (age 46-75. From healthy adults (n = 59, trunk accelerations and angular velocities were recorded during iTUG performance. iTUG phases were detected with wavelet-analysis. Using a Partial Least Square (PLS model, from the 72-iTUG variables calculated across phases, those that explained most of the covariance between variables and age were extracted. Subsequently, a PLS-discriminant analysis (DA assessed classification power of the identified iTUG variables to discriminate the age groups. 27 variables, related to turning, walking and the stand-to-sit movement explained 71% of the variation in age. The PLS-DA with these 27 variables showed a sensitivity and specificity of 90% and 85%. Based on this model, the iTUG can accurately distinguish young and older adults. Such data can serve as a reference for pathological aging with respect to a widely used mobility test. Mobility tests like the TUG supplemented with smart technology could be used in

  11. Events

    Directory of Open Access Journals (Sweden)

    Igor V. Karyakin

    2015-12-01

    Full Text Available In April 2015 a charity program “PROTECTED AREAS – LIFE SAVER” was launched for reserved areas and national parks in Russia and CIS countries. The project “Eagles of Russia” received the support of the Russian Geographical Society for the second time.  In 2015 in the Republic of Tatarstan 67 special protection forest areas (SPFA will be allotted in 17 administrative districts. Where there will be 41 areas for the protection of the Imperial Eagle (Aquila heliaca, 23 – for the White-Tailed Eagle (Haliaeetus albicilla and 3 – for the Greater Spotted Eagle (Aquila clanga. XIV International Ornithological Conference of Northern Eurasia was held in August 18–24, 2015 in Almaty, Kazakhstan, on the basis of Kazakh National University named after Al-Farabi (KNU. V International readings from Buturlin, dedicated to the memory of Sergei Buturlin a famous Russian ornithologist, were held in September 22–24,2015 inUlyanovsk. In 29–30 October 2015, the Interregional Conference “Raptor Research and Conservation. Legislative Issue” was held in Elista. The status of steppe eagle (Aquila nipalensis in the European Red List and IUCN Red List has changed. SochiNational Park, Southern Federal University, Menzbir Ornithological Society and the Working Group on birds of prey and owls of Northern Eurasia are planning to hold regular VII International Conference on research and conservation of raptors in North Eurasia inSochion the basis of theSochiNational Park. Excerpts from the Resolution Adopted at the XIV International Ornithological Conference ofNorth Eurasia. Date held: 18–22 August, 2015. Excerpts from the Resolution Adopted at the Interregional Conference “Raptor Research and Conservation. Legislative Issue”. Date held: 29–30 October, 2015.

  12. A Scalable GVT Estimation Algorithm for PDES: Using Lower Bound of Event-Bulk-Time

    Directory of Open Access Journals (Sweden)

    Yong Peng

    2015-01-01

    Full Text Available Global Virtual Time computation of Parallel Discrete Event Simulation is crucial for conducting fossil collection and detecting the termination of simulation. The triggering condition of GVT computation in typical approaches is generally based on the wall-clock time or logical time intervals. However, the GVT value depends on the timestamps of events rather than the wall-clock time or logical time intervals. Therefore, it is difficult for the existing approaches to select appropriate time intervals to compute the GVT value. In this study, we propose a scalable GVT estimation algorithm based on Lower Bound of Event-Bulk-Time, which triggers the computation of the GVT value according to the number of processed events. In order to calculate the number of transient messages, our algorithm employs Event-Bulk to record the messages sent and received by Logical Processes. To eliminate the performance bottleneck, we adopt an overlapping computation approach to distribute the workload of GVT computation to all worker-threads. We compare our algorithm with the fast asynchronous GVT algorithm using PHOLD benchmark on the shared memory machine. Experimental results indicate that our algorithm has a light overhead and shows higher speedup and accuracy of GVT computation than the fast asynchronous GVT algorithm.

  13. Model Checking Multivariate State Rewards

    DEFF Research Database (Denmark)

    Nielsen, Bo Friis; Nielson, Flemming; Nielson, Hanne Riis

    2010-01-01

    We consider continuous stochastic logics with state rewards that are interpreted over continuous time Markov chains. We show how results from multivariate phase type distributions can be used to obtain higher-order moments for multivariate state rewards (including covariance). We also generalise...

  14. Electrophysiological correlates of strategic monitoring in event-based and time-based prospective memory.

    Directory of Open Access Journals (Sweden)

    Giorgia Cona

    Full Text Available Prospective memory (PM is the ability to remember to accomplish an action when a particular event occurs (i.e., event-based PM, or at a specific time (i.e., time-based PM while performing an ongoing activity. Strategic Monitoring is one of the basic cognitive functions supporting PM tasks, and involves two mechanisms: a retrieval mode, which consists of maintaining active the intention in memory; and target checking, engaged for verifying the presence of the PM cue in the environment. The present study is aimed at providing the first evidence of event-related potentials (ERPs associated with time-based PM, and at examining differences and commonalities in the ERPs related to Strategic Monitoring mechanisms between event- and time-based PM tasks.The addition of an event-based or a time-based PM task to an ongoing activity led to a similar sustained positive modulation of the ERPs in the ongoing trials, mainly expressed over prefrontal and frontal regions. This modulation might index the retrieval mode mechanism, similarly engaged in the two PM tasks. On the other hand, two further ERP modulations were shown specifically in an event-based PM task. An increased positivity was shown at 400-600 ms post-stimulus over occipital and parietal regions, and might be related to target checking. Moreover, an early modulation at 130-180 ms post-stimulus seems to reflect the recruitment of attentional resources for being ready to respond to the event-based PM cue. This latter modulation suggests the existence of a third mechanism specific for the event-based PM; that is, the "readiness mode".

  15. On Event/Time Triggered and Distributed Analysis of a WSN System for Event Detection, Using Fuzzy Logic

    Directory of Open Access Journals (Sweden)

    Sofia Maria Dima

    2016-01-01

    Full Text Available Event detection in realistic WSN environments is a critical research domain, while the environmental monitoring comprises one of its most pronounced applications. Although efforts related to the environmental applications have been presented in the current literature, there is a significant lack of investigation on the performance of such systems, when applied in wireless environments. Aiming at addressing this shortage, in this paper an advanced multimodal approach is followed based on fuzzy logic. The proposed fuzzy inference system (FIS is implemented on TelosB motes and evaluates the probability of fire detection while aiming towards power conservation. Additionally to a straightforward centralized approach, a distributed implementation of the above FIS is also proposed, aiming towards network congestion reduction while optimally distributing the energy consumption among network nodes so as to maximize network lifetime. Moreover this work proposes an event based execution of the aforementioned FIS aiming to further reduce the computational as well as the communication cost, compared to a periodical time triggered FIS execution. As a final contribution, performance metrics acquired from all the proposed FIS implementation techniques are thoroughly compared and analyzed with respect to critical network conditions aiming to offer realistic evaluation and thus objective conclusions’ extraction.

  16. Time distributions of solar energetic particle events: Are SEPEs really random?

    Science.gov (United States)

    Jiggens, P. T. A.; Gabriel, S. B.

    2009-10-01

    Solar energetic particle events (SEPEs) can exhibit flux increases of several orders of magnitude over background levels and have always been considered to be random in nature in statistical models with no dependence of any one event on the occurrence of previous events. We examine whether this assumption of randomness in time is correct. Engineering modeling of SEPEs is important to enable reliable and efficient design of both Earth-orbiting and interplanetary spacecraft and future manned missions to Mars and the Moon. All existing engineering models assume that the frequency of SEPEs follows a Poisson process. We present analysis of the event waiting times using alternative distributions described by Lévy and time-dependent Poisson processes and compared these with the usual Poisson distribution. The results show significant deviation from a Poisson process and indicate that the underlying physical processes might be more closely related to a Lévy-type process, suggesting that there is some inherent “memory” in the system. Inherent Poisson assumptions of stationarity and event independence are investigated, and it appears that they do not hold and can be dependent upon the event definition used. SEPEs appear to have some memory indicating that events are not completely random with activity levels varying even during solar active periods and are characterized by clusters of events. This could have significant ramifications for engineering models of the SEP environment, and it is recommended that current statistical engineering models of the SEP environment should be modified to incorporate long-term event dependency and short-term system memory.

  17. The role of musical training in emergent and event-based timing

    Directory of Open Access Journals (Sweden)

    Lawrence eBaer

    2013-05-01

    Full Text Available Musical performance is thought to rely predominantly on event-based timing involving a clock-like neural process and an explicit internal representation of the time interval. Some aspects of musical performance may rely on emergent timing, which is established through the optimization of movement kinematics, and can be maintained without reference to any explicit representation of the time interval. We predicted that musical training would have its largest effect on event-based timing, supporting the dissociability of these timing processes and the dominance of event-based timing in musical performance. We compared 22 musicians and 17 non-musicians on the prototypical event-based timing task of finger tapping and on the typically emergently timed task of circle drawing. For each task, participants first responded in synchrony with a metronome (Paced and then responded at the same rate without the metronome (Unpaced. Analyses of the Unpaced phase revealed that non-musicians were more variable in their inter-response intervals for finger tapping compared to circle drawing. Musicians did not differ between the two tasks. Between groups, non-musicians were more variable than musicians for tapping but not for drawing. We were able to show that the differences were due to less timer variability in musicians on the tapping task. Correlational analyses of movement jerk and inter-response interval variability revealed a negative association for tapping and a positive association for drawing in non-musicians only. These results suggest that musical training affects temporal variability in tapping but not drawing. Additionally, musicians and non-musicians may be employing different movement strategies to maintain accurate timing in the two tasks. These findings add to our understanding of how musical training affects timing and support the dissociability of event-based and emergent timing modes.

  18. The showerfront time-structure of ''anomalous muon'' events associated with Hercules X-1

    International Nuclear Information System (INIS)

    Alexandreas, D.E.; Allen, R.C.; Biller, S.D.; Dion, G.M.; Lu, X-Q.; Vishwanath, P.R.; Yodh, G.B.; Berley, D.; Chang, C.Y.; Dingus, B.L.; Dion, C.; Goodman, J.A.; Gupta, S.K.; Haines, T.J.; Kwok, P.W.; Stark, M.J.; Burman, R.L.; Hoffman, C.M.; Lloyd-Evans, J.; Nagle, D.E.; Potter, M.E.; Sandberg, V.D.; Zhang, W.P.; Cady, D.R.; Ellsworth, R.W.; Krakauer, D.A.; Talaga, R.L.

    1990-01-01

    The 11 ''in-phase'' source events from the 1986 muon-rich bursts associated with Hercules X-1 (previously reported by this group) have been studied for indications of further anomalous behavior. The most significant effect observed resulted from an analysis of the showerfront time-structures of these events. This analysis was then applied a priori to the rest of the source day, where an additional ∼9 signal events are expected to remain. The same effect was observed at a chance probability level of ∼0.1%. 1 ref., 7 figs

  19. Probabilistic tsunami hazard assessment considering time-lag of seismic event on Nankai trough

    International Nuclear Information System (INIS)

    Sugino, Hideharu; Sakagami, Masaharu; Ebisawa, Katsumi; Korenaga, Mariko

    2011-01-01

    In the area in front of Nankai trough, tsunami wave height may increase if tsunamis attacking from some wave sources overlap because of time-lag of seismic event on Nankai trough. To evaluation tsunami risk of the important facilities located in front of Nankai trough, we proposed the probabilistic tsunami hazard assessment considering uncertainty on time-lag of seismic event on Nankai trough and we evaluated the influence that the time-lag gave to tsunami hazard at the some representative points. (author)

  20. Time-to-event analysis of mastitis at first-lactation in Valle del Belice ewes

    NARCIS (Netherlands)

    Portolano, B.; Firlocchiaro, R.; Kaam, van J.B.C.H.M.; Riggio, V.; Maizon, D.O.

    2007-01-01

    A time-to-event study for mastitis at first-lactation in Valle del Belice ewes was conducted, using survival analysis with an animal model. The goals were to evaluate the effect of lambing season and level of milk production on the time from lambing to the day when a ewe experienced a test-day with

  1. Determination of the event collision time with the ALICE detector at the LHC

    NARCIS (Netherlands)

    Adam, J.; Adamová, D.; Aggarwal, M. M.; Aglieri Rinella, G.; Agnello, M.; Agrawal, N.; Ahammed, Z.; Ahmad, S.; Ahn, S. U.; Aiola, S.; Akindinov, A.; Alam, S. N.; Albuquerque, D. S. D.; Aleksandrov, D.; Alessandro, B.; Alexandre, D.; Alfaro Molina, R.; Alici, A.; Alkin, A.; Alme, J.; Alt, T.; Altinpinar, S.; Altsybeev, I.; Alves Garcia Prado, C.; Janssen, M M; Andrei, C.; Andrews, H. A.; Andronic, A.; Anguelov, V.; Anson, C. D.; Antičić, T.; Antinori, F.; Antonioli, P.; Anwar, R.; Aphecetche, L.; Appelshäuser, H.; Arcelli, S.; Arnaldi, R.; Arnold, O. W.; Arsene, I. C.; Arslandok, M.; Audurier, B.; Augustinus, A.; Averbeck, R.; Azmi, M. D.; Badalà, A.; Baek, Y. W.; Bagnasco, S.; Bailhache, R.; Bala, R.; Balasubramanian, S.; Baldisseri, A.; Baral, R. C.; Barbano, A. M.; Barbera, R.; Barile, F.; Barnaföldi, G. G.; Barnby, L. S.; Barret, V.; Bartalini, P.; Barth, K.; Bartke, J.; Bartsch, E.; Basile, M.; Bastid, N.; Basu, S.; Bathen, B.; Batigne, G.; Batista Camejo, A.; Batyunya, B.; Batzing, P. C.; Bearden, I. G.; Beck, H.; Bedda, C.; Behera, N. K.; Belikov, I.; Bellini, F.; Bello Martinez, H.; Bellwied, R.; Beltran, L. G. E.; Belyaev, V.; Bencedi, G.; Beole, S.; Bercuci, A.; Berdnikov, Y.; Berenyi, D.; Bertens, R. A.; Berzano, D.; Betev, L.; Bhasin, A.; Bhat, I. R.; Bhati, A. K.; Bhattacharjee, B.; Bhom, J.; Bianchi, L.; Bianchi, N.; Bianchin, C.; Bielčík, J.; Bielčíková, J.; Bilandzic, A.; Biro, G.; Biswas, R.; Biswas, S.; Bjelogrlic, S.; Blair, J. T.; Blau, D.; Blume, C.; Bock, F.; Bogdanov, A.; Boldizsár, L.; Bombara, M.; Bonora, M.; Book, J.; Borel, H.; Borissov, A.; Borri, M.; Botta, E.; Bourjau, C.; Braun-Munzinger, P.; Bregant, M.; Broker, T. A.; Browning, T. A.; Broz, M.; Brucken, E. J.; Bruna, E.; Bruno, G. E.; Budnikov, D.; Buesching, H.; Bufalino, S.; Buhler, P.; Iga Buitron, S. A.; Buncic, P.; Busch, O.; Buthelezi, Z.; Butt, J. B.; Buxton, J. T.; Cabala, J.; Caffarri, D.; Caines, H.; Caliva, A.; Calvo Villar, E.; Camerini, P.; Carena, F.; Carena, W.; Carnesecchi, F.; Castillo Castellanos, J.; Castro, A. J.; Casula, E. A R; Ceballos Sanchez, C.; Cepila, J.; Cerello, P.; Cerkala, J.; Chang, B.; Chapeland, S.; Chartier, M.; Charvet, J. L.; Chattopadhyay, S.; Chattopadhyay, S.; Chauvin, A.; Chelnokov, V.; Cherney, M.; Cheshkov, C.; Cheynis, B.; Chibante Barroso, V.; Chinellato, D. D.; Cho, Sukhee; Chochula, P.; Choi, K.; Chojnacki, M.; Choudhury, S.; Christakoglou, P.; Christensen, C. H.; Christiansen, P.; Chujo, T.; Chung, S. U.; Cicalo, C.; Cifarelli, L.; Cindolo, F.; Cleymans, J.; Colamaria, F.; Colella, D.; Collu, A.; Colocci, M.; Conesa Balbastre, G.; Conesa del Valle, Z.; Connors, M. E.; Contreras, J. G.; Cormier, T. M.; Corrales Morales, Y.; Cortés Maldonado, I.; Cortese, P.; Cosentino, M. R.; Costa, F.; Crkovská, J.; Crochet, P.; Cruz Albino, R.; Cuautle, E.; Cunqueiro, L.; Dahms, T.; Dainese, A.; Danisch, M. C.; Danu, A.; Das, D.; Das, I.; Das, S.; Dash, A.; Dash, S.; Dasgupta, S. S.; De Caro, A.; De Cataldo, G.; De Conti, C.; De Cuveland, J.; De Falco, A.; De Gruttola, D.; De Marco, N.; De Pasquale, S.; De Souza, R. Derradi; Deisting, A.; Deloff, A.; Deplano, C.; Dhankher, P.; Di Bari, D.; Di Mauro, A.; Di Nezza, P.; Di Ruzza, B.; Diaz Corchero, M. A.; Dietel, T.; Dillenseger, P.; Divià, R.; Djuvsland, O.; Dobrin, A.; Domenicis Gimenez, D.; Dönigus, B.; Dordic, O.; Drozhzhova, T.; Dubey, A. K.; Dubla, A.; Ducroux, L.; Duggal, A. K.; Dupieux, P.; Ehlers, R. J.; Elia, D.; Endress, E.; Engel, H.; Epple, E.; Erazmus, B.; Erhardt, F.; Espagnon, B.; Esumi, S.; Eulisse, G.; Eum, J.; Evans, D.; Evdokimov, S.; Eyyubova, G.; Fabbietti, L.; Fabris, D.; Faivre, J.; Fantoni, A.; Fasel, M.; Feldkamp, L.; Feliciello, A.; Feofilov, G.; Ferencei, J.; Fernández Téllez, A.; Ferreiro, E. G.; Ferretti, A.; Festanti, A.; Feuillard, V. J. G.; Figiel, J.; Figueredo, M. A S; Filchagin, S.; Finogeev, D.; Fionda, F. M.; Fiore, E. M.; Floris, M.; Foertsch, S.; Foka, P.; Fokin, S.; Fragiacomo, E.; Francescon, A.; De Francisco, A.; Frankenfeld, U.; Fronze, G. G.; Fuchs, U.; Furget, C.; Furs, A.; Fusco Girard, M.; Gaardhøje, J. J.; Gagliardi, M.; Gago, A. M.; Gajdosova, K.; Gallio, M.; Galvan, C. D.; Gangadharan, D. R.; Ganoti, P.; Gao, C.; Garabatos, C.; Garcia-Solis, E.; Garg, K.; Garg, P.; Gargiulo, C.; Gasik, P.; Gauger, E. F.; Gay Ducati, M. B.; Germain, M.; Ghosh, P.; Ghosh, S. K.; Gianotti, P.; Giubellino, P.; Giubilato, P.; Gladysz-Dziadus, E.; Glässel, P.; Goméz Coral, D. M.; Gomez Ramirez, A.; Gonzalez, A. S.; Gonzalez, V; González-Zamora, P.; Gorbunov, S.; Görlich, L.; Gotovac, S.; Grabski, V.; Graczykowski, L. K.; Graham, K. L.; Greiner, L. C.; Grelli, A.; Grigoras, C.; Grigoriev, V.; Grigoryan, A.; Grigoryan, S.; Grion, N.; Gronefeld, J. M.; Grosse-Oetringhaus, J. F.; Grosso, R.; Gruber, L.; Guber, F.; Guernane, R.; Guerzoni, B.; Gulbrandsen, K.; Gunji, T.; Gupta, A.; Gupta, R.; Guzman, I. B.; Haake, R.; Hadjidakis, C.; Hamagaki, H.; Hamar, G.; Hamon, J. C.; Harris, J. W.; Harton, A.; Hatzifotiadou, D.; Hayashi, S.; Heckel, S. T.; Hellbär, E.; Helstrup, H.; Herghelegiu, A.; Herrera Corral, G.; Herrmann, F.; Hess, B. A.; Hetland, K. F.; Hillemanns, H.; Hippolyte, B.; Hladky, J.; Horak, D.; Hosokawa, R.; Hristov, P.; Hughes, C.W.; Humanic, T. J.; Hussain, N.; Hussain, T.; Hutter, D.; Hwang, D. S.; Ilkaev, R.; Inaba, M.; Ippolitov, M.; Irfan, M.; Isakov, V.; Islam, M. S.; Ivanov, M.; Ivanov, V.; Izucheev, V.; Jacak, B.; Jacazio, N.; Jacobs, P. M.; Jadhav, M. B.; Jadlovska, S.; Jadlovsky, J.; Jahnke, C.; Jakubowska, M. J.; Janik, M. A.; Jayarathna, P. H S Y; Jena, C.; Jena, S.; Jimenez Bustamante, R. T.; Jones, P. G.; Jusko, A.; Kalinak, P.; Kalweit, A.; Kang, J. H.; Kaplin, V.; Kar, S.; Karasu Uysal, A.; Karavichev, O.; Karavicheva, T.; Karayan, L.; Karpechev, E.; Kebschull, U.; Keidel, R.; Keijdener, D. L.D.; Keil, M.; Mohisin Khan, M.; Khan, P.M.; Khan, Shfaqat A.; Khanzadeev, A.; Kharlov, Y.; Khatun, A.; Khuntia, A.; Kileng, B.; Kim, D. W.; Kim, D. J.; Kim, D.-S.; Kim, H.; Kim, J. S.; Kim, J.; Kim, M.; Kim, M.; Kim, S.; Kim, T.; Kirsch, S.; Kisel, I.; Kiselev, S.; Kisiel, A.; Kiss, G.; Klay, J. L.; Klein, C; Klein, J.; Klein-Bösing, C.; Klewin, S.; Kluge, A.; Knichel, M. L.; Knospe, A. G.; Kobdaj, C.; Kofarago, M.; Kollegger, T.; Kolojvari, A.; Kondratiev, V.; Kondratyeva, N.; Kondratyuk, E.; Konevskikh, A.; Kopcik, M.; Kour, M.; Kouzinopoulos, C.; Kovalenko, O.; Kovalenko, V.; Kowalski, M.L.; Koyithatta Meethaleveedu, G.; Králik, I.; Kravčáková, A.; Krivda, M.; Krizek, F.; Kryshen, E.; Krzewicki, M.; Kubera, A. M.; Kučera, V.; Kuhn, C.; Kuijer, P. G.; Kumar, A.; Kumar, J.; Kumar, L.; Kumar, S.; Kundu, Seema; Kurashvili, P.; Kurepin, A.; Kurepin, A. B.; Kuryakin, A.; Kushpil, S.; Kweon, M. J.; Kwon, Y.; La Pointe, S. L.; La Rocca, P.; Lagana Fernandes, C.; Lakomov, I.; Langoy, R.; Lapidus, K.; Lara, C.; Lardeux, A.; Lattuca, A.; Laudi, E.; Lazaridis, L.; Lea, R.; Leardini, L.; Lee, S.; Lehas, F.; Strunz-Lehner, Christine; Lehrbach, J.; Lemmon, R. C.; Lenti, V.; Leogrande, E.; León Monzón, I.; Lévai, P.; Li, S.; Li, X.; Lien, J.; Lietava, R.; Lindal, S.; Lindenstruth, V.; Lippmann, C.; Lisa, M. A.; Ljunggren, H. M.; Llope, W. J.; Lodato, D. F.; Loenne, P. I.; Loginov, V.; Loizides, C.; Lopez, X.; López Torres, E.; Lowe, A.; Luettig, P.; Lunardon, M.; Luparello, G.; Lupi, M.; Lutz, T. H.; Maevskaya, A.; Mager, M.; Mahajan, S.; Mahmood, S. M.; Maire, A.; Majka, R. D.; Malaev, M.; Maldonado Cervantes, I.; Malinina, L.; Mal’Kevich, D.; Malzacher, P.; Mamonov, A.; Manko, V.; Manso, F.; Manzari, V.; Mao, Y.; Marchisone, M.; Mareš, J.; Margagliotti, G. V.; Margotti, A.; Margutti, J.; Marín, Alicia; Markert, C.; Marquard, M.; Martin, N. A.; Martinengo, P.; Martínez, Isabel M.; Martínez García, G.; Martinez Pedreira, M.; Mas, A.; Masciocchi, S.; Masera, M.; Masoni, A.; Mastroserio, A.; Matyja, A.; mayer, C.; Mazer, J.; Mazzilli, M.; Mazzoni, M. A.; Meddi, F.; Melikyan, Y.; Menchaca-Rocha, A.; Meninno, E.; Mercado Pérez, J.; Meres, M.; Mhlanga, S.; Miake, Y.; Mieskolainen, M. M.; Mikhaylov, K.; Milano, L.; Milosevic, J.; Mischke, A.; Mishra, A. N.; Mishra, T.; Miśkowiec, D.; Mitra, J.; Mitu, C. M.; Mohammadi, N.; Mohanty, B.; Molnar, L.; Montes, E.; Moreira De Godoy, D. A.; Moreno, L. A. P.; Moretto, S.; Morreale, A.; Morsch, A.; Muccifora, V.; Mudnic, E.; Mühlheim, D.; Muhuri, S.; Mukherjee, M.; Mulligan, J. D.; Munhoz, M. G.; Münning, K.; Munzer, R. H.; Murakami, H.; Murray, S.; Musa, L.; Musinsky, J.; Myers, C. J.; Naik, B.; Nair, Rajiv; Nandi, B. K.; Nania, R.; Nappi, E.; Naru, M. U.; Natal Da Luz, H.; Nattrass, C.; Navarro, S. R.; Nayak, K.; Nayak, R.; Nayak, T. K.; Nazarenko, S.; Nedosekin, A.; Negrao De Oliveira, R. A.; Nellen, L.; Ng, F.; Nicassio, M.; Niculescu, M.; Niedziela, J.; Nielsen, B. S.; Nikolaev, S.; Nikulin, S.; Nikulin, V.; Noferini, F.; Nomokonov, P.; Nooren, G.; Noris, J. C. C.; Norman, J.; Nyanin, A.; Nystrand, J.; Oeschler, H.; Oh, S.; Ohlson, A.; Okubo, T.; Olah, L.; Oleniacz, J.; Oliveira Da Silva, A. C.; Oliver, M. H.; Onderwaater, J.; Oppedisano, C.; Orava, R.; Oravec, M.; Ortiz Velasquez, A.; Oskarsson, A.; Otwinowski, J.; Oyama, K.; Ozdemir, M.; Pachmayer, Y.; Pacik, V.; Pagano, D.; Pagano, P.; Paić, G.; Pal, S. K.; Palni, P.; Pan, J.; Pandey, A. K.; Papikyan, V.; Pappalardo, G. S.; Pareek, P.; Park, J.; Park, J.-W.; Parmar, S.; Passfeld, A.; Paticchio, V.; Patra, R. N.; Paul, B.; Pei, H.; Peitzmann, T.; Peng, X.; Pereira Da Costa, H.; Peresunko, D.; Perez Lezama, E.; Peskov, V.; Pestov, Y.; Petráček, V.; Petrov, V.; Petrovici, M.; Petta, C.; Piano, S.; Pikna, M.; Pillot, P.; Pimentel, L. O. D. L.; Pinazza, O.; Pinsky, L.; Piyarathna, D. B.; Płoskoń, M.; Planinic, M.; Pluta, J.; Pochybova, S.; Podesta-Lerma, P. L M; Poghosyan, M. G.; Polichtchouk, B.; Poljak, N.; Poonsawat, W.; Pop, A.; Poppenborg, H.; Porteboeuf-Houssais, S.; Porter, J.; Pospisil, J.; Pozdniakov, V.; Prasad, S. K.; Preghenella, R.; Prino, F.; Pruneau, C. A.; Pshenichnov, I.; Puccio, M.; Puddu, G.; Pujahari, P.; Punin, V.; Putschke, J.; Qvigstad, H.; Rachevski, A.; Raha, S.; Rajput, S.; Rak, J.; Rakotozafindrabe, A.; Ramello, L.; Rami, F.; Rana, D. B.; Raniwala, R.; Raniwala, S.; Räsänen, S.; Rascanu, B. T.; Rathee, D.; Ratza, V.; Ravasenga, I.; Read, K. F.; Redlich, K.; Rehman, A.; Reichelt, P.; Reidt, F.; Ren, X.; Renfordt, R.; Reolon, A. R.; Reshetin, A.; Reygers, K.; Riabov, V.; Ricci, R. A.; Richert, T.; Richter, M.; Riedler, P.; Riegler, W.; Riggi, F.; Ristea, C.; Rodríguez Cahuantzi, M.; Røed, K.; Rogochaya, E.; Rohr, D.; Röhrich, D.; Ronchetti, F.; Ronflette, L.; Rosnet, P.; Rossi, A.; Roukoutakis, F.; Roy, A.; Roy, C.; Roy, P.; Rubio Montero, A. J.; Rui, R.; Russo, R.; Ryabinkin, E.; Ryabov, Y.; Rybicki, A.; Saarinen, S.; Sadhu, S.; Sadovsky, S.; Šafařík, K.; Sahlmuller, B.; Sahoo, B.; Sahoo, P.; Sahoo, R.; Sahoo, S.; Sahu, P. K.; Saini, J.; Sakai, S.; Saleh, M. A.; Salzwedel, J.; Sambyal, S.; Samsonov, V.; Sandoval, A.; Sano, M.; Sarkar, D.; Sarkar, N.; Sarma, P.; Sas, M. H.P.; Scapparone, E.; Scarlassara, F.; Scharenberg, R. P.; Schiaua, C.; Schicker, R.; Schmidt, C.; Schmidt, H. R.; Schmidt, M.; Schukraft, J.; Schutz, Y.; Schwarz, K.; Schweda, K.; Scioli, G.; Scomparin, E.; Scott, R.; Šefčík, M.; Seger, J. E.; Sekiguchi, Y.; Sekihata, D.; Selyuzhenkov, I.; Senosi, K.; Senyukov, S.; Serradilla, E.; Sett, P.; Sevcenco, A.; Shabanov, A.; Shabetai, A.; Shadura, O.; Shahoyan, R.; Shangaraev, A.; Sharma, A.; Sharma, A.; Sharma, M.; Sharma, M.; Sharma, N.; Sheikh, A. I.; Shigaki, K.; Shou, Q. Y.; Shtejer, K.; Sibiriak, Y.; Siddhanta, S.; Sielewicz, K. M.; Siemiarczuk, T.; Silvermyr, D.; Silvestre, C.; Simatovic, G.; Simonetti, G.; Singaraju, R.; Singh, R; Singhal, V.; Sinha, T.; Sitar, B.; Sitta, M.; Skaali, T. B.; Slupecki, M.; Smirnov, N.; Snellings, R. J.M.; Snellman, T. W.; Song, J.; Song, M.; Song, Z.; Soramel, F.; Sorensen, S.; Sozzi, F.; Spiriti, E.; Sputowska, I.; Srivastava, B. K.; Stachel, J.; Stan, I.; Stankus, P.; Stenlund, E.; Steyn, G.; Stiller, J. H.; Stocco, D.; Strmen, P.; Suaide, A. A P; Sugitate, T.; Suire, C.; Suleymanov, M.; Suljic, M.; Sultanov, R.; Šumbera, M.; Sumowidagdo, S.; Suzuki, K.; Swain, S.; Szabo, A.; Szarka, I.; Szczepankiewicz, A.; Szymanski, M.; Tabassam, U.; Takahashi, J.; Tambave, G. J.; Tanaka, N.; Tarhini, M.; Tariq, M.; Tarzila, M. G.; Tauro, A.; Tejeda Muñoz, G.; Telesca, A.; Terasaki, K.; Terrevoli, C.; Teyssier, B.; Thakur, D.; Thomas, D.; Tieulent, R.; Tikhonov, A.; Timmins, A. R.; Toia, A.; tripathy, S.; Trogolo, S.; Trombetta, G.; Trubnikov, V.; Trzaska, W. H.; Tsuji, T.; Tumkin, A.; Turrisi, R.; Tveter, T. S.; Ullaland, K.; Umaka, E. N.; Uras, A.; Usai, G. L.; Utrobicic, A.; Vala, M.; Van Der Maarel, J.; Van Hoorne, J. W.; van Leeuwen, M.; Vanat, T.; Vande Vyvre, P.; Varga, D.; Vargas, A.; Vargyas, M.; Varma, R.; Vasileiou, M.; Vasiliev, A.; Vauthier, A.; Vázquez Doce, O.; Vechernin, V.; Veen, A. M.; Velure, A.; Vercellin, E.; Vergara Limón, S.; Vernet, R.; Vértesi, R.; Vickovic, L.; Vigolo, S.; Viinikainen, J.; Vilakazi, Z.; Villalobos Baillie, O.; Villatoro Tello, A.; Vinogradov, A.; Vinogradov, L.; Virgili, T.; Vislavicius, V.; Vodopyanov, A.; Völkl, M. A.; Voloshin, K.; Voloshin, S. A.; Volpe, G.; Haller, B.; Vorobyev, I.; Voscek, D.; Vranic, D.; Vrláková, J.; Wagner, B.; Wagner, J.; Wang, H.; Wang, M.; Watanabe, D.; Watanabe, Y.; Weber, M.; Weber, S. G.; Weiser, D. F.; Wessels, J. P.; Westerhoff, U.; Whitehead, A. M.; Wiechula, J.; Wikne, J.; Wilk, G.; Wilkinson, J.; Willems, G. A.; Williams, M. C S; Windelband, B.; Winn, M.; Witt, W. E.; Yalcin, S.; Yang, P.; Yano, S.; Yin, Z.; Yokoyama, H.; Yoo, I. K.; Yoon, J. H.; Yurchenko, V.; Zaccolo, V.; Zaman, A.; Zampolli, C.; Zanoli, H. J. C.; Zaporozhets, S.; Zardoshti, N.; Zarochentsev, A.; Závada, P.; Zaviyalov, N.; Zbroszczyk, H.; Zhalov, M.; Zhang, H.; Zhang, X.; Zhang, Y.; Zhang, C.; Zhang, Z.; Zhao, C.; Zhigareva, N.; Zhou, D.; Zhou, Y.; Zhou, Z.; Zhu, H.; Zhu, J.; Zichichi, A.; Zimmermann, A.; Zimmermann, M. B.; Zinovjev, G.; Zmeskal, J.

    2017-01-01

    Particle identification is an important feature of the ALICE detector at the LHC. In particular, for particle identification via the time-of-flight technique, the precise determination of the event collision time represents an important ingredient of the quality of the measurement. In this paper,

  2. Multi-variable X-band radar observation and tracking of ash plume from Mt. Etna volcano on November 23, 2013 event

    Science.gov (United States)

    Montopoli, Mario; Vulpiani, Gianfranco; Riccci, Matteo; Corradini, Stefano; Merucci, Luca; Marzano, Frank S.

    2015-04-01

    Ground based weather radar observations of volcanic ash clouds are gaining momentum after recent works which demonstrated their potential use either as stand alone tool or in combination with satellite retrievals. From an operational standpoint, radar data have been mainly exploited to derive the height of ash plume and its temporal-spatial development, taking into account the radar limitation of detecting coarse ash particles (from approximately 20 microns to 10 millimeters and above in terms of particle's radius). More sophisticated radar retrievals can include airborne ash concentration, ash fall rate and out-flux rate. Marzano et al. developed several volcanic ash radar retrieval (VARR) schemes, even though their practical use is still subject to a robust validation activity. The latter is made particularly difficult due to the lack of field campaigns with multiple observations and the scarce repetition of volcanic events. The radar variable, often used to infer the physical features of actual ash clouds, is the radar reflectivity named ZHH. It is related to ash particle size distribution and it shows a nice power law relationship with ash concentration. This makes ZHH largely used in radar-volcanology studies. However, weather radars are often able to detect Doppler frequency shifts and, more and more, they have a polarization-diversity capability. The former means that wind speed spectrum of the ash cloud is potentially inferable, whereas the latter implies that variables other than ZHH are available. Theoretically, these additional radar variables are linked to the degree of eccentricity of ash particles, their orientation and density as well as the presence of strong turbulence effects. Thus, the opportunity to refine the ash radar estimates so far developed can benefit from the thorough analysis of radar Doppler and polarization diversity. In this work we show a detailed analysis of Doppler shifts and polarization variables measured by the X band radar

  3. From sensation to perception: Using multivariate classification of visual illusions to identify neural correlates of conscious awareness in space and time.

    Science.gov (United States)

    Hogendoorn, Hinze

    2015-01-01

    An important goal of cognitive neuroscience is understanding the neural underpinnings of conscious awareness. Although the low-level processing of sensory input is well understood in most modalities, it remains a challenge to understand how the brain translates such input into conscious awareness. Here, I argue that the application of multivariate pattern classification techniques to neuroimaging data acquired while observers experience perceptual illusions provides a unique way to dissociate sensory mechanisms from mechanisms underlying conscious awareness. Using this approach, it is possible to directly compare patterns of neural activity that correspond to the contents of awareness, independent from changes in sensory input, and to track these neural representations over time at high temporal resolution. I highlight five recent studies using this approach, and provide practical considerations and limitations for future implementations.

  4. Multiple imputation for multivariate data with missing and below-threshold measurements: time-series concentrations of pollutants in the Arctic.

    Science.gov (United States)

    Hopke, P K; Liu, C; Rubin, D B

    2001-03-01

    Many chemical and environmental data sets are complicated by the existence of fully missing values or censored values known to lie below detection thresholds. For example, week-long samples of airborne particulate matter were obtained at Alert, NWT, Canada, between 1980 and 1991, where some of the concentrations of 24 particulate constituents were coarsened in the sense of being either fully missing or below detection limits. To facilitate scientific analysis, it is appealing to create complete data by filling in missing values so that standard complete-data methods can be applied. We briefly review commonly used strategies for handling missing values and focus on the multiple-imputation approach, which generally leads to valid inferences when faced with missing data. Three statistical models are developed for multiply imputing the missing values of airborne particulate matter. We expect that these models are useful for creating multiple imputations in a variety of incomplete multivariate time series data sets.

  5. Estimating the effect of a rare time-dependent treatment on the recurrent event rate.

    Science.gov (United States)

    Smith, Abigail R; Zhu, Danting; Goodrich, Nathan P; Merion, Robert M; Schaubel, Douglas E

    2018-05-30

    In many observational studies, the objective is to estimate the effect of treatment or state-change on the recurrent event rate. If treatment is assigned after the start of follow-up, traditional methods (eg, adjustment for baseline-only covariates or fully conditional adjustment for time-dependent covariates) may give biased results. We propose a two-stage modeling approach using the method of sequential stratification to accurately estimate the effect of a time-dependent treatment on the recurrent event rate. At the first stage, we estimate the pretreatment recurrent event trajectory using a proportional rates model censored at the time of treatment. Prognostic scores are estimated from the linear predictor of this model and used to match treated patients to as yet untreated controls based on prognostic score at the time of treatment for the index patient. The final model is stratified on matched sets and compares the posttreatment recurrent event rate to the recurrent event rate of the matched controls. We demonstrate through simulation that bias due to dependent censoring is negligible, provided the treatment frequency is low, and we investigate a threshold at which correction for dependent censoring is needed. The method is applied to liver transplant (LT), where we estimate the effect of development of post-LT End Stage Renal Disease (ESRD) on rate of days hospitalized. Copyright © 2018 John Wiley & Sons, Ltd.

  6. Predictive value of night-time heart rate for cardiovascular events in hypertension. The ABP-International study.

    Science.gov (United States)

    Palatini, Paolo; Reboldi, Gianpaolo; Beilin, Lawrence J; Eguchi, Kazuo; Imai, Yutaka; Kario, Kazuomi; Ohkubo, Takayoshi; Pierdomenico, Sante D; Saladini, Francesca; Schwartz, Joseph E; Wing, Lindon; Verdecchia, Paolo

    2013-09-30

    Data from prospective cohort studies regarding the association between ambulatory heart rate (HR) and cardiovascular events (CVE) are conflicting. To investigate whether ambulatory HR predicts CVE in hypertension, we performed 24-hour ambulatory blood pressure and HR monitoring in 7600 hypertensive patients aged 52 ± 16 years from Italy, U.S.A., Japan, and Australia, included in the 'ABP-International' registry. All were untreated at baseline examination. Standardized hazard ratios for ambulatory HRs were computed, stratifying for cohort, and adjusting for age, gender, blood pressure, smoking, diabetes, serum total cholesterol and serum creatinine. During a median follow-up of 5.0 years there were 639 fatal and nonfatal CVE. In a multivariable Cox model, night-time HR predicted fatal combined with nonfatal CVE more closely than 24h HR (p=0.007 and =0.03, respectively). Daytime HR and the night:day HR ratio were not associated with CVE (p=0.07 and =0.18, respectively). The hazard ratio of the fatal combined with nonfatal CVE for a 10-beats/min increment of the night-time HR was 1.13 (95% CI, 1.04-1.22). This relationship remained significant when subjects taking beta-blockers during the follow-up (hazard ratio, 1.15; 95% CI, 1.05-1.25) or subjects who had an event within 5 years after enrollment (hazard ratio, 1.23; 95% CI, 1.05-1.45) were excluded from analysis. At variance with previous data obtained from general populations, ambulatory HR added to the risk stratification for fatal combined with nonfatal CVE in the hypertensive patients from the ABP-International study. Night-time HR was a better predictor of CVE than daytime HR. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  7. A Comparison of Pseudo-Maximum Likelihood and Asymptotically Distribution-Free Dynamic Factor Analysis Parameter Estimation in Fitting Covariance-Structure Models to Block-Toeplitz Representing Single-Subject Multivariate Time-Series

    NARCIS (Netherlands)

    Molenaar, P.C.M.; Nesselroade, J.R.

    1998-01-01

    The study of intraindividual variability pervades empirical inquiry in virtually all subdisciplines of psychology. The statistical analysis of multivariate time-series data - a central product of intraindividual investigations - requires special modeling techniques. The dynamic factor model (DFM),

  8. Distributed Event-Triggered Control of Multiagent Systems with Time-Varying Topology

    Directory of Open Access Journals (Sweden)

    Jingwei Ma

    2014-01-01

    Full Text Available This paper studies the consensus of first-order discrete-time multiagent systems, where the interaction topology is time-varying. The event-triggered control is used to update the control input of each agent, and the event-triggering condition is designed based on the combination of the relative states of each agent to its neighbors. By applying the common Lyapunov function method, a sufficient condition for consensus, which is expressed as a group of linear matrix inequalities, is obtained and the feasibility of these linear matrix inequalities is further analyzed. Simulation examples are provided to explain the effectiveness of the theoretical results.

  9. Real time event selection and flash analog-to-digital converters

    International Nuclear Information System (INIS)

    Imori, Masatosi

    1983-01-01

    In high-energy particle experiments, high-speed analog logic is employed to select events on a real-time basis. Flash analog-to-digital converters replace the high-speed analog logic with digital logic. The digital logic gives great flexibility to the scheme for real-time event selection. This paper proposes the use of flash A/D converters for the logic used to obtain the total sum of the energy deposited in individual counters in a shower detector. (author)

  10. Markov chains and semi-Markov models in time-to-event analysis.

    Science.gov (United States)

    Abner, Erin L; Charnigo, Richard J; Kryscio, Richard J

    2013-10-25

    A variety of statistical methods are available to investigators for analysis of time-to-event data, often referred to as survival analysis. Kaplan-Meier estimation and Cox proportional hazards regression are commonly employed tools but are not appropriate for all studies, particularly in the presence of competing risks and when multiple or recurrent outcomes are of interest. Markov chain models can accommodate censored data, competing risks (informative censoring), multiple outcomes, recurrent outcomes, frailty, and non-constant survival probabilities. Markov chain models, though often overlooked by investigators in time-to-event analysis, have long been used in clinical studies and have widespread application in other fields.

  11. Zero Time of Transitory Nuclear Events Derived by Parent-Daughter Systems

    International Nuclear Information System (INIS)

    Nir-El, Y.

    2014-01-01

    The detection and identification of a nuclear event that results in the dissemination of radioactive products into the environment can be realized by dating the age of the event. In order to correct observed activities for the decay since the occurrence of the event, the age must be known to a high level of confidence. Previous papers. described the method to date the age of a nuclear event by measuring the activity of two fission products, which constitute the clock in this application. Within the proficiency test programme for radionuclide laboratories supporting the CTBT, a simulated gamma spectrum with the characteristics of an atmospheric test of a Chinese thermonuclear device, was used to determine the zero time by calculating the theoretical peak area ratio of 95Nb/95Zr. Their approach used only the main gamma lines at 766 and 757 keV and assigned the same detection efficiency to both these close lines. Their methodology of calculating the uncertainty of zero time is subject to comments because it takes the sum of two components (nuclide ratio and activity ratio as function of time) in quadrature. In another paper, the activity of 95Nb as a function of time was presented without any development or expression for the zero time. Analytical equations for zero time and the associated uncertainty calculations were derived in a recent paper using a measured activity ratio of two nuclides and illustrating the procedure by data from the Chinese test. The evaluation of the zero time uncertainty was performed by a very large set of very complicated analytical equations. The present paper aims at developing a procedure to determine the zero time and its uncertainty in a transitory nuclear event by treating a parent-daughter system of 3 nuclides, where one daughter feeds the other one, in addition to its direct feeding by the decay of the parent

  12. Potential Biases in the Estimation of the Delay Time in Multivariate Time Series: An application to Climate Data and Functional Networks

    Science.gov (United States)

    Martin, E.; Davidsen, J.; Complexity Science Group

    2011-12-01

    Measuring cross-correlations is of vital importance to science in general and is a key ingredient in functional networks, which are being widely applied to geophysical systems. A functional network is a collection of nodes (e.g. global positions), and two nodes are connected by a link if their joint behaviour satisfies some criteria. In most cases each node is associated with a time series, and a link is created between two nodes if their time series have a cross-correlation that is deemed significant. However, the spatial distance between nodes and the resolution of the time series, Δ t, can mean that it is unphysical for a signal to propagate from one node to another within a time Δ t. One way to account for this is to measure the cross-correlation at a number of different time lags and use the time delay for which it is a maximum. Here we show that this method is biased for a large class of time series that are common to geophysical systems, namely long-range correlated time series. These are time series which show persistence, for example, a warm day is more likely to be followed by another warm day than a cold one. If one randomly generates two series which each have long-range correlations, the naive assumption is that the maximum cross-correlation between them is equally likely to be found at every time lag. However, the cross-correlation between the series is more likely to be a maximum at the largest and smallest (in this work we allow time lags to be negative) time lags measured. This is a systematic effect which can, and should, be corrected for when judging if a correlation is significant. Whereas the traditional null model is that each time lag is equally likely to give the maximum cross-correlation, our work provides a more correct null model for this class of systems. We apply this to climate data, as well as go on to discuss other potential issues when measuring cross-correlations in this context.

  13. Illustration of compositional variations over time of Chinese porcelain glazes combining micro-X-ray Fluorescence spectrometry, multivariate data analysis and Seger formulas

    International Nuclear Information System (INIS)

    Van Pevenage, J.; Verhaeven, E.; Vekemans, B.; Lauwers, D.; Herremans, D.; De Clercq, W.; Vincze, L.; Moens, L.; Vandenabeele, P.

    2015-01-01

    In this research, the transparent glaze layers of Chinese porcelain samples were investigated. Depending on the production period, these samples can be divided into two groups: the samples of group A dating from the Kangxi period (1661–1722), and the samples of group B produced under emperor Qianlong (1735–1795). Due to the specific sample preparation method and the small spot size of the X-ray beam, investigation of the transparent glaze layers is enabled. Despite the many existing research papers about glaze investigations of ceramics and/or porcelain ware, this research reveals new insights into the glaze composition and structure of Chinese porcelain samples. In this paper it is demonstrated, using micro-X-ray Fluorescence (μ-XRF) spectrometry, multivariate data analysis and statistical analysis (Hotelling's T-Square test) that the transparent glaze layers of the samples of groups A and B are significantly different (95% confidence level). Calculation of the Seger formulas, enabled classification of the glazes. Combining all the information, the difference in composition of the Chinese porcelain glazes of the Kangxi period and the Qianlong period can be demonstrated. - Highlights: • Fully described methodology for the analysis of silicate glazes of Chinese porcelain samples • The combination of a semi-quantitative analysis of silicate glazes, multi-variate data and statistical analysis. • The use of Seger formula to understand better the composition of the glazes. • New insights into the glaze composition and structure of Chinese porcelain glazes of different time periods

  14. Unbiased metabolite profiling by liquid chromatography-quadrupole time-of-flight mass spectrometry and multivariate data analysis for herbal authentication: classification of seven Lonicera species flower buds.

    Science.gov (United States)

    Gao, Wen; Yang, Hua; Qi, Lian-Wen; Liu, E-Hu; Ren, Mei-Ting; Yan, Yu-Ting; Chen, Jun; Li, Ping

    2012-07-06

    Plant-based medicines become increasingly popular over the world. Authentication of herbal raw materials is important to ensure their safety and efficacy. Some herbs belonging to closely related species but differing in medicinal properties are difficult to be identified because of similar morphological and microscopic characteristics. Chromatographic fingerprinting is an alternative method to distinguish them. Existing approaches do not allow a comprehensive analysis for herbal authentication. We have now developed a strategy consisting of (1) full metabolic profiling of herbal medicines by rapid resolution liquid chromatography (RRLC) combined with quadrupole time-of-flight mass spectrometry (QTOF MS), (2) global analysis of non-targeted compounds by molecular feature extraction algorithm, (3) multivariate statistical analysis for classification and prediction, and (4) marker compounds characterization. This approach has provided a fast and unbiased comparative multivariate analysis of the metabolite composition of 33-batch samples covering seven Lonicera species. Individual metabolic profiles are performed at the level of molecular fragments without prior structural assignment. In the entire set, the obtained classifier for seven Lonicera species flower buds showed good prediction performance and a total of 82 statistically different components were rapidly obtained by the strategy. The elemental compositions of discriminative metabolites were characterized by the accurate mass measurement of the pseudomolecular ions and their chemical types were assigned by the MS/MS spectra. The high-resolution, comprehensive and unbiased strategy for metabolite data analysis presented here is powerful and opens the new direction of authentication in herbal analysis. Copyright © 2012 Elsevier B.V. All rights reserved.

  15. Illustration of compositional variations over time of Chinese porcelain glazes combining micro-X-ray Fluorescence spectrometry, multivariate data analysis and Seger formulas

    Energy Technology Data Exchange (ETDEWEB)

    Van Pevenage, J., E-mail: Raman@UGent.be [Department of Analytical Chemistry, Raman Spectroscopy Research Group, Ghent University, Krijgslaan 281, S12, B-9000 Ghent (Belgium); Verhaeven, E. [Department of Conservation and Restoration, University College Antwerp, Blindestraat 9, B-2000 Antwerp (Belgium); Vekemans, B. [Department of Analytical Chemistry, Ghent University, Krijgslaan 281, S12, B-9000 Ghent (Belgium); Lauwers, D., E-mail: Raman@UGent.be [Department of Analytical Chemistry, Raman Spectroscopy Research Group, Ghent University, Krijgslaan 281, S12, B-9000 Ghent (Belgium); Herremans, D.; De Clercq, W. [Department of Archaeology, Ghent University, Sint-Pietersnieuwstraat 35, B-9000 Ghent (Belgium); Vincze, L. [Department of Analytical Chemistry, Ghent University, Krijgslaan 281, S12, B-9000 Ghent (Belgium); Moens, L., E-mail: Raman@UGent.be [Department of Analytical Chemistry, Raman Spectroscopy Research Group, Ghent University, Krijgslaan 281, S12, B-9000 Ghent (Belgium); Vandenabeele, P. [Department of Archaeology, Ghent University, Sint-Pietersnieuwstraat 35, B-9000 Ghent (Belgium)

    2015-01-01

    In this research, the transparent glaze layers of Chinese porcelain samples were investigated. Depending on the production period, these samples can be divided into two groups: the samples of group A dating from the Kangxi period (1661–1722), and the samples of group B produced under emperor Qianlong (1735–1795). Due to the specific sample preparation method and the small spot size of the X-ray beam, investigation of the transparent glaze layers is enabled. Despite the many existing research papers about glaze investigations of ceramics and/or porcelain ware, this research reveals new insights into the glaze composition and structure of Chinese porcelain samples. In this paper it is demonstrated, using micro-X-ray Fluorescence (μ-XRF) spectrometry, multivariate data analysis and statistical analysis (Hotelling's T-Square test) that the transparent glaze layers of the samples of groups A and B are significantly different (95% confidence level). Calculation of the Seger formulas, enabled classification of the glazes. Combining all the information, the difference in composition of the Chinese porcelain glazes of the Kangxi period and the Qianlong period can be demonstrated. - Highlights: • Fully described methodology for the analysis of silicate glazes of Chinese porcelain samples • The combination of a semi-quantitative analysis of silicate glazes, multi-variate data and statistical analysis. • The use of Seger formula to understand better the composition of the glazes. • New insights into the glaze composition and structure of Chinese porcelain glazes of different time periods.

  16. Automated reasoning with dynamic event trees: a real-time, knowledge-based decision aide

    International Nuclear Information System (INIS)

    Touchton, R.A.; Gunter, A.D.; Subramanyan, N.

    1988-01-01

    The models and data contained in a probabilistic risk assessment (PRA) Event Sequence Analysis represent a wealth of information that can be used for dynamic calculation of event sequence likelihood. In this paper we report a new and unique computerization methodology which utilizes these data. This sub-system (referred to as PREDICTOR) has been developed and tested as part of a larger system. PREDICTOR performs a real-time (re)calculation of the estimated likelihood of core-melt as a function of plant status. This methodology uses object-oriented programming techniques from the artificial intelligence discipline that enable one to codify event tree and fault tree logic models and associated probabilities developed in a PRA study. Existence of off-normal conditions is reported to PREDICTOR, which then updates the relevant failure probabilities throughout the event tree and fault tree models by dynamically replacing the off-the-shelf (or prior) probabilities with new probabilities based on the current situation. The new event probabilities are immediately propagated through the models (using 'demons') and an updated core-melt probability is calculated. Along the way, the dominant non-success path of each event tree is determined and highlighted. (author)

  17. Testing the timing of radiocarbon-dated events between proxy archives

    NARCIS (Netherlands)

    Christen, J. A.; Mauquoy, D.; van der Plicht, J.; Bennett, K. D.; Blaauw, Maarten

    For interpreting past changes on a regional or global scale, the timings of proxy-inferred events are usually aligned with data from other locations. However, too often chronological uncertainties are ignored in proxy diagrams and multisite comparisons, making it possible for researchers to fall

  18. Work, family, and happiness : essays on interdependencies within families, life events, and time allocation decisions

    NARCIS (Netherlands)

    Pouwels, B.

    2011-01-01

    In this thesis we investigate how today’s work and family life influence people’s happiness – or the lack thereof. We contribute to the research agenda by focusing on three underexplored issues in the literature, namely i) interdependencies within families, ii) life events, and iii) time allocation

  19. Individual Change and the Timing and Onset of Important Life Events: Methods, Models, and Assumptions

    Science.gov (United States)

    Grimm, Kevin; Marcoulides, Katerina

    2016-01-01

    Researchers are often interested in studying how the timing of a specific event affects concurrent and future development. When faced with such research questions there are multiple statistical models to consider and those models are the focus of this paper as well as their theoretical underpinnings and assumptions regarding the nature of the…

  20. The influence of pubertal timing and stressful life events on depression and delinquency among Chinese adolescents.

    Science.gov (United States)

    Chen, Jie; Yu, Jing; Wu, Yun; Zhang, Jianxin

    2015-06-01

    This study aimed to investigate the influences of pubertal timing and stressful life events on Chinese adolescents' depression and delinquency. Sex differences in these influences were also examined. A large sample with 4,228 participants aged 12-15 years (53% girls) was recruited in Beijing, China. Participants' pubertal development, stressful life events, depressive symptoms, and delinquency were measured using self-reported questionnaires. Both early maturing girls and boys displayed more delinquency than their same-sex on-time and late maturing peers. Early maturing girls displayed more depressive symptoms than on-time and late maturing girls, but boys in the three maturation groups showed similar levels of depressive symptoms. The interactive effects between early pubertal timing and stressful life events were significant in predicting depression and delinquency, particularly for girls. Early pubertal maturation is an important risk factor for Chinese adolescents' depression and delinquency. Stressful life events intensified the detrimental effects of early pubertal maturation on adolescents' depression and delinquency, particularly for girls. © 2015 The Institute of Psychology, Chinese Academy of Sciences and Wiley Publishing Asia Pty Ltd.

  1. Work, family, and happiness : essays on interdependencies within families, life events, and time allocation decisions

    OpenAIRE

    Pouwels, B.

    2011-01-01

    In this thesis we investigate how today’s work and family life influence people’s happiness – or the lack thereof. We contribute to the research agenda by focusing on three underexplored issues in the literature, namely i) interdependencies within families, ii) life events, and iii) time allocation decisions. Using data of the Dutch Time Competition Survey 2003 and the German Socio-Economic Panel 1984 – 2005 (GSOEP), this thesis shows that the happiness of partners in marital relationships is...

  2. On the timing properties of germanium detectors: The centroid diagrams of prompt photopeaks and Compton events

    International Nuclear Information System (INIS)

    Penev, I.; Andrejtscheff, W.; Protochristov, Ch.; Zhelev, Zh.

    1987-01-01

    In the applications of the generalized centroid shift method with germanium detectors, the energy dependence of the time centroids of prompt photopeaks (zero-time line) and of Compton background events reveal a peculiar behavior crossing each other at about 100 keV. The effect is plausibly explained as associated with the ratio of γ-quanta causing the photoeffect and Compton scattering, respectively, at the boundaries of the detector. (orig.)

  3. FACT. Multivariate extraction of muon ring images

    Energy Technology Data Exchange (ETDEWEB)

    Noethe, Maximilian; Temme, Fabian; Buss, Jens [Experimentelle Physik 5b, TU Dortmund, Dortmund (Germany); Collaboration: FACT-Collaboration

    2016-07-01

    In ground-based gamma-ray astronomy, muon ring images are an important event class for instrument calibration and monitoring of its properties. In this talk, a multivariate approach will be presented, that is well suited for real time extraction of muons from data streams of Imaging Atmospheric Cherenkov Telescopes (IACT). FACT, the First G-APD Cherenkov Telescope is located on the Canary Island of La Palma and is the first IACT to use Silicon Photomultipliers for detecting the Cherenkov photons of extensive air showers. In case of FACT, the extracted muon events are used to calculate the time resolution of the camera. In addition, the effect of the mirror alignment in May 2014 on properties of detected muons is investigated. Muon candidates are identified with a random forest classification algorithm. The performance of the classifier is evaluated for different sets of image parameters in order to compare the gain in performance with the computational costs of their calculation.

  4. Visual exploration of movement and event data with interactive time masks

    Directory of Open Access Journals (Sweden)

    Natalia Andrienko

    2017-03-01

    Full Text Available We introduce the concept of time mask, which is a type of temporal filter suitable for selection of multiple disjoint time intervals in which some query conditions fulfil. Such a filter can be applied to time-referenced objects, such as events and trajectories, for selecting those objects or segments of trajectories that fit in one of the selected time intervals. The selected subsets of objects or segments are dynamically summarized in various ways, and the summaries are represented visually on maps and/or other displays to enable exploration. The time mask filtering can be especially helpful in analysis of disparate data (e.g., event records, positions of moving objects, and time series of measurements, which may come from different sources. To detect relationships between such data, the analyst may set query conditions on the basis of one dataset and investigate the subsets of objects and values in the other datasets that co-occurred in time with these conditions. We describe the desired features of an interactive tool for time mask filtering and present a possible implementation of such a tool. By example of analysing two real world data collections related to aviation and maritime traffic, we show the way of using time masks in combination with other types of filters and demonstrate the utility of the time mask filtering. Keywords: Data visualization, Interactive visualization, Interaction technique

  5. Convolutional neural networks applied to neutrino events in a liquid argon time projection chamber

    International Nuclear Information System (INIS)

    Acciarri, R.; Adams, C.; An, R.; Asaadi, J.; Auger, M.

    2017-01-01

    Here, we present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identification or event detection on simulated neutrino interactions. Lastly, we also address technical issues that arise when applying this technique to data from a large LArTPC at or near ground level.

  6. Thermal ambience of expanding event horizon in Minkowski space-time

    International Nuclear Information System (INIS)

    Gerlach, U.H.

    1983-01-01

    It is shown that in flat space-time the thermal ambience of accelerated observers is not associated exclusively with flat event horizons, but arises also with (observer-dependent) event horizons that are light cones. The quanta of this ambience are characterized by a generalized frequency which identifies the representation of the Lorentz group. Global and local model detectors capable of responding to quanta of any given generalized frequency are exhibited. The discussion of the thermal ambience is implemented in terms of a partial-wave analysis using a set of harmonics on the hyperboloid x 2 +y 2 +z 2 -t 2 = 1

  7. Convolutional neural networks applied to neutrino events in a liquid argon time projection chamber

    Energy Technology Data Exchange (ETDEWEB)

    Acciarri, R.; Adams, C.; An, R.; Asaadi, J.; Auger, M.; Bagby, L.; Baller, B.; Barr, G.; Bass, M.; Bay, F.; Bishai, M.; Blake, A.; Bolton, T.; Bugel, L.; Camilleri, L.; Caratelli, D.; Carls, B.; Fernandez, R. Castillo; Cavanna, F.; Chen, H.; Church, E.; Cianci, D.; Collin, G. H.; Conrad, J. M.; Convery, M.; Crespo-Anad?n, J. I.; Del Tutto, M.; Devitt, D.; Dytman, S.; Eberly, B.; Ereditato, A.; Sanchez, L. Escudero; Esquivel, J.; Fleming, B. T.; Foreman, W.; Furmanski, A. P.; Garvey, G. T.; Genty, V.; Goeldi, D.; Gollapinni, S.; Graf, N.; Gramellini, E.; Greenlee, H.; Grosso, R.; Guenette, R.; Hackenburg, A.; Hamilton, P.; Hen, O.; Hewes, J.; Hill, C.; Ho, J.; Horton-Smith, G.; James, C.; de Vries, J. Jan; Jen, C. -M.; Jiang, L.; Johnson, R. A.; Jones, B. J. P.; Joshi, J.; Jostlein, H.; Kaleko, D.; Karagiorgi, G.; Ketchum, W.; Kirby, B.; Kirby, M.; Kobilarcik, T.; Kreslo, I.; Laube, A.; Li, Y.; Lister, A.; Littlejohn, B. R.; Lockwitz, S.; Lorca, D.; Louis, W. C.; Luethi, M.; Lundberg, B.; Luo, X.; Marchionni, A.; Mariani, C.; Marshall, J.; Caicedo, D. A. Martinez; Meddage, V.; Miceli, T.; Mills, G. B.; Moon, J.; Mooney, M.; Moore, C. D.; Mousseau, J.; Murrells, R.; Naples, D.; Nienaber, P.; Nowak, J.; Palamara, O.; Paolone, V.; Papavassiliou, V.; Pate, S. F.; Pavlovic, Z.; Porzio, D.; Pulliam, G.; Qian, X.; Raaf, J. L.; Rafique, A.; Rochester, L.; von Rohr, C. Rudolf; Russell, B.; Schmitz, D. W.; Schukraft, A.; Seligman, W.; Shaevitz, M. H.; Sinclair, J.; Snider, E. L.; Soderberg, M.; S?ldner-Rembold, S.; Soleti, S. R.; Spentzouris, P.; Spitz, J.; St. John, J.; Strauss, T.; Szelc, A. M.; Tagg, N.; Terao, K.; Thomson, M.; Toups, M.; Tsai, Y. -T.; Tufanli, S.; Usher, T.; Van de Water, R. G.; Viren, B.; Weber, M.; Weston, J.; Wickremasinghe, D. A.; Wolbers, S.; Wongjirad, T.; Woodruff, K.; Yang, T.; Zeller, G. P.; Zennamo, J.; Zhang, C.

    2017-03-01

    We present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identification or event detection on simulated neutrino interactions. We also address technical issues that arise when applying this technique to data from a large LArTPC at or near ground level.

  8. A novel multivariate approach using science-based calibration for direct coating thickness determination in real-time NIR process monitoring.

    Science.gov (United States)

    Möltgen, C-V; Herdling, T; Reich, G

    2013-11-01

    This study demonstrates an approach, using science-based calibration (SBC), for direct coating thickness determination on heart-shaped tablets in real-time. Near-Infrared (NIR) spectra were collected during four full industrial pan coating operations. The tablets were coated with a thin hydroxypropyl methylcellulose (HPMC) film up to a film thickness of 28 μm. The application of SBC permits the calibration of the NIR spectral data without using costly determined reference values. This is due to the fact that SBC combines classical methods to estimate the coating signal and statistical methods for the noise estimation. The approach enabled the use of NIR for the measurement of the film thickness increase from around 8 to 28 μm of four independent batches in real-time. The developed model provided a spectroscopic limit of detection for the coating thickness of 0.64 ± 0.03 μm root-mean square (RMS). In the commonly used statistical methods for calibration, such as Partial Least Squares (PLS), sufficiently varying reference values are needed for calibration. For thin non-functional coatings this is a challenge because the quality of the model depends on the accuracy of the selected calibration standards. The obvious and simple approach of SBC eliminates many of the problems associated with the conventional statistical methods and offers an alternative for multivariate calibration. Copyright © 2013 Elsevier B.V. All rights reserved.

  9. The Dependence of Characteristic Times of Gradual SEP Events on Their Associated CME Properties

    Science.gov (United States)

    Pan, Z. H.; Wang, C. B.; Xue, X. H.; Wang, Y. M.

    It is generally believed that coronal mass ejections CMEs are the drivers of shocks that accelerate gradual solar energetic particles SEPs One might expect that the characteristics of the SEP intensity time profiles observed at 1 AU are determined by properties of the associated CMEs such as the radial speed and the angular width Recently Kahler statistically investigated the characteristic times of gradual SEP events observed from 1998-2002 and their associated coronal mass ejection properties Astrophys J 628 1014--1022 2005 Three characteristic times of gradual SEP events are determined as functions of solar source longitude 1 T 0 the time from associated CME launch to SEP onset at 1 AU 2 T R the rise time from SEP onset to the time when the SEP intensity is a factor of 2 below peak intensity and 3 T D the duration over which the SEP intensity is within a factor of 2 of the peak intensity However in his study the CME speeds and angular widths are directly taken from the LASCO CME catalog In this study we analyze the radial speeds and the angular widths of CMEs by an ice-cream cone model and re-investigate their correlationships with the characteristic times of the corresponding SEP events We find T R and T D are significantly correlated with radial speed for SEP events in the best-connected longitude range and there is no correlation between T 0 and CME radial speed and angular width which is consistent with Kahler s results On the other hand it s found that T R and T D are also have

  10. Lessons Learned from Real-Time, Event-Based Internet Science Communications

    Science.gov (United States)

    Phillips, T.; Myszka, E.; Gallagher, D. L.; Adams, M. L.; Koczor, R. J.; Whitaker, Ann F. (Technical Monitor)

    2001-01-01

    For the last several years the Science Directorate at Marshall Space Flight Center has carried out a diverse program of Internet-based science communication. The Directorate's Science Roundtable includes active researchers, NASA public relations, educators, and administrators. The Science@NASA award-winning family of Web sites features science, mathematics, and space news. The program includes extended stories about NASA science, a curriculum resource for teachers tied to national education standards, on-line activities for students, and webcasts of real-time events. The focus of sharing science activities in real-time has been to involve and excite students and the public about science. Events have involved meteor showers, solar eclipses, natural very low frequency radio emissions, and amateur balloon flights. In some cases, broadcasts accommodate active feedback and questions from Internet participants. Through these projects a pattern has emerged in the level of interest or popularity with the public. The pattern differentiates projects that include science from those that do not, All real-time, event-based Internet activities have captured public interest at a level not achieved through science stories or educator resource material exclusively. The worst event-based activity attracted more interest than the best written science story. One truly rewarding lesson learned through these projects is that the public recognizes the importance and excitement of being part of scientific discovery. Flying a camera to 100,000 feet altitude isn't as interesting to the public as searching for viable life-forms at these oxygen-poor altitudes. The details of these real-time, event-based projects and lessons learned will be discussed.

  11. Emerging Media Crisis Value Model: A Comparison of Relevant, Timely Message Strategies for Emergency Events

    Directory of Open Access Journals (Sweden)

    Sabrina Page

    2013-01-01

    Full Text Available Communication during an emergency or crisis event is essential for emergency responders, the community involved, and those watching on television as well as receiving information via social media from family members, friends or other community members. The evolution of communication during an emergency/crisis event now includes utilizing social media. To better understand this evolution the Emerging Media Crisis Value Model (EMCVM is used in comparing two emergency events; Hurricane Irene (2011, a natural disaster, and the theater shooting in Aurora, Colorado (2012, a man-made crisis. The EMCVM provides a foundation for future studies focusing on the use of social media, emergency responders at the local, state and national levels are better prepared to educate a community thus, counteracting public uncertainty, fear, while providing timely, accurate information.

  12. Non-fragile ?-? control for discrete-time stochastic nonlinear systems under event-triggered protocols

    Science.gov (United States)

    Sun, Ying; Ding, Derui; Zhang, Sunjie; Wei, Guoliang; Liu, Hongjian

    2018-07-01

    In this paper, the non-fragile ?-? control problem is investigated for a class of discrete-time stochastic nonlinear systems under event-triggered communication protocols, which determine whether the measurement output should be transmitted to the controller or not. The main purpose of the addressed problem is to design an event-based output feedback controller subject to gain variations guaranteeing the prescribed disturbance attenuation level described by the ?-? performance index. By utilizing the Lyapunov stability theory combined with S-procedure, a sufficient condition is established to guarantee both the exponential mean-square stability and the ?-? performance for the closed-loop system. In addition, with the help of the orthogonal decomposition, the desired controller parameter is obtained in terms of the solution to certain linear matrix inequalities. Finally, a simulation example is exploited to demonstrate the effectiveness of the proposed event-based controller design scheme.

  13. Statistical Property and Model for the Inter-Event Time of Terrorism Attacks

    Science.gov (United States)

    Zhu, Jun-Fang; Han, Xiao-Pu; Wang, Bing-Hong

    2010-06-01

    The inter-event time of terrorism attack events is investigated by empirical data and model analysis. Empirical evidence shows that it follows a scale-free property. In order to understand the dynamic mechanism of such a statistical feature, an opinion dynamic model with a memory effect is proposed on a two-dimensional lattice network. The model mainly highlights the role of individual social conformity and self-affirmation psychology. An attack event occurs when the order parameter indicating the strength of public opposition opinion is smaller than a critical value. Ultimately, the model can reproduce the same statistical property as the empirical data and gives a good understanding for the possible dynamic mechanism of terrorism attacks.

  14. Triggerless Readout with Time and Amplitude Reconstruction of Event Based on Deconvolution Algorithm

    International Nuclear Information System (INIS)

    Kulis, S.; Idzik, M.

    2011-01-01

    In future linear colliders like CLIC, where the period between the bunch crossings is in a sub-nanoseconds range ( 500 ps), an appropriate detection technique with triggerless signal processing is needed. In this work we discuss a technique, based on deconvolution algorithm, suitable for time and amplitude reconstruction of an event. In the implemented method the output of a relatively slow shaper (many bunch crossing periods) is sampled and digitalised in an ADC and then the deconvolution procedure is applied to digital data. The time of an event can be found with a precision of few percent of sampling time. The signal to noise ratio is only slightly decreased after passing through the deconvolution filter. The performed theoretical and Monte Carlo studies are confirmed by the results of preliminary measurements obtained with the dedicated system comprising of radiation source, silicon sensor, front-end electronics, ADC and further digital processing implemented on a PC computer. (author)

  15. Event Based Simulator for Parallel Computing over the Wide Area Network for Real Time Visualization

    Science.gov (United States)

    Sundararajan, Elankovan; Harwood, Aaron; Kotagiri, Ramamohanarao; Satria Prabuwono, Anton

    As the computational requirement of applications in computational science continues to grow tremendously, the use of computational resources distributed across the Wide Area Network (WAN) becomes advantageous. However, not all applications can be executed over the WAN due to communication overhead that can drastically slowdown the computation. In this paper, we introduce an event based simulator to investigate the performance of parallel algorithms executed over the WAN. The event based simulator known as SIMPAR (SIMulator for PARallel computation), simulates the actual computations and communications involved in parallel computation over the WAN using time stamps. Visualization of real time applications require steady stream of processed data flow for visualization purposes. Hence, SIMPAR may prove to be a valuable tool to investigate types of applications and computing resource requirements to provide uninterrupted flow of processed data for real time visualization purposes. The results obtained from the simulation show concurrence with the expected performance using the L-BSP model.

  16. Real-time decision support in the face of emerging natural hazard events

    DEFF Research Database (Denmark)

    Anders, Annett

    and losses. Motivated by these factors, the present thesis aims at developing a framework for the decision support system for real-time decision making in emerging natural hazard events. The thesis also demonstrates the implementation of the developed framework to illustrate its use and advantages...... turbines, agricultural facilities and offshore platforms. Operators of these facilities are often required to make decisions regarding the continued operations of their facilities in extreme storm events. These decisions, which in the present thesis are called real-time decisions, are often made by a small...... number of people in extremely stressful situations, ad-hoc relying on personal experiences of decision makers. On the other hand, recent advancements of information technology potentially make it possible for decision makers to access various types of information in real-time. Remarkable examples...

  17. A sequential threshold cure model for genetic analysis of time-to-event data

    DEFF Research Database (Denmark)

    Ødegård, J; Madsen, Per; Labouriau, Rodrigo S.

    2011-01-01

    In analysis of time-to-event data, classical survival models ignore the presence of potential nonsusceptible (cured) individuals, which, if present, will invalidate the inference procedures. Existence of nonsusceptible individuals is particularly relevant under challenge testing with specific...... pathogens, which is a common procedure in aquaculture breeding schemes. A cure model is a survival model accounting for a fraction of nonsusceptible individuals in the population. This study proposes a mixed cure model for time-to-event data, measured as sequential binary records. In a simulation study...... survival data were generated through 2 underlying traits: susceptibility and endurance (risk of dying per time-unit), associated with 2 sets of underlying liabilities. Despite considerable phenotypic confounding, the proposed model was largely able to distinguish the 2 traits. Furthermore, if selection...

  18. APNEA list mode data acquisition and real-time event processing

    Energy Technology Data Exchange (ETDEWEB)

    Hogle, R.A.; Miller, P. [GE Corporate Research & Development Center, Schenectady, NY (United States); Bramblett, R.L. [Lockheed Martin Specialty Components, Largo, FL (United States)

    1997-11-01

    The LMSC Active Passive Neutron Examinations and Assay (APNEA) Data Logger is a VME-based data acquisition system using commercial-off-the-shelf hardware with the application-specific software. It receives TTL inputs from eighty-eight {sup 3}He detector tubes and eight timing signals. Two data sets are generated concurrently for each acquisition session: (1) List Mode recording of all detector and timing signals, timestamped to 3 microsecond resolution; (2) Event Accumulations generated in real-time by counting events into short (tens of microseconds) and long (seconds) time bins following repetitive triggers. List Mode data sets can be post-processed to: (1) determine the optimum time bins for TRU assay of waste drums, (2) analyze a given data set in several ways to match different assay requirements and conditions and (3) confirm assay results by examining details of the raw data. Data Logger events are processed and timestamped by an array of 15 TMS320C40 DSPs and delivered to an embedded controller (PowerPC604) for interim disk storage. Three acquisition modes, corresponding to different trigger sources are provided. A standard network interface to a remote host system (Windows NT or SunOS) provides for system control, status, and transfer of previously acquired data. 6 figs.

  19. A log-Weibull spatial scan statistic for time to event data.

    Science.gov (United States)

    Usman, Iram; Rosychuk, Rhonda J

    2018-06-13

    Spatial scan statistics have been used for the identification of geographic clusters of elevated numbers of cases of a condition such as disease outbreaks. These statistics accompanied by the appropriate distribution can also identify geographic areas with either longer or shorter time to events. Other authors have proposed the spatial scan statistics based on the exponential and Weibull distributions. We propose the log-Weibull as an alternative distribution for the spatial scan statistic for time to events data and compare and contrast the log-Weibull and Weibull distributions through simulation studies. The effect of type I differential censoring and power have been investigated through simulated data. Methods are also illustrated on time to specialist visit data for discharged patients presenting to emergency departments for atrial fibrillation and flutter in Alberta during 2010-2011. We found northern regions of Alberta had longer times to specialist visit than other areas. We proposed the spatial scan statistic for the log-Weibull distribution as a new approach for detecting spatial clusters for time to event data. The simulation studies suggest that the test performs well for log-Weibull data.

  20. Relative timing of last glacial maximum and late-glacial events in the central tropical Andes

    Science.gov (United States)

    Bromley, Gordon R. M.; Schaefer, Joerg M.; Winckler, Gisela; Hall, Brenda L.; Todd, Claire E.; Rademaker, Kurt M.

    2009-11-01

    Whether or not tropical climate fluctuated in synchrony with global events during the Late Pleistocene is a key problem in climate research. However, the timing of past climate changes in the tropics remains controversial, with a number of recent studies reporting that tropical ice age climate is out of phase with global events. Here, we present geomorphic evidence and an in-situ cosmogenic 3He surface-exposure chronology from Nevado Coropuna, southern Peru, showing that glaciers underwent at least two significant advances during the Late Pleistocene prior to Holocene warming. Comparison of our glacial-geomorphic map at Nevado Coropuna to mid-latitude reconstructions yields a striking similarity between Last Glacial Maximum (LGM) and Late-Glacial sequences in tropical and temperate regions. Exposure ages constraining the maximum and end of the older advance at Nevado Coropuna range between 24.5 and 25.3 ka, and between 16.7 and 21.1 ka, respectively, depending on the cosmogenic production rate scaling model used. Similarly, the mean age of the younger event ranges from 10 to 13 ka. This implies that (1) the LGM and the onset of deglaciation in southern Peru occurred no earlier than at higher latitudes and (2) that a significant Late-Glacial event occurred, most likely prior to the Holocene, coherent with the glacial record from mid and high latitudes. The time elapsed between the end of the LGM and the Late-Glacial event at Nevado Coropuna is independent of scaling model and matches the period between the LGM termination and Late-Glacial reversal in classic mid-latitude records, suggesting that these events in both tropical and temperate regions were in phase.

  1. The fungal and acritarch events as time markers for the latest Permian mass extinction: An update

    Directory of Open Access Journals (Sweden)

    Michael R. Rampino

    2018-01-01

    Full Text Available The latest Permian extinction (252 Myr ago was the most severe in the geologic record. On land, widespread Late Permian gymnosperm/seed-fern dominated forests appear to have suffered rapid and almost complete destruction, as evidenced by increased soil erosion and changes in fluvial style in deforested areas, signs of wildfires, replacement of trees by lower plants, and almost complete loss of peat-forming and fire-susceptible vegetation. Permian–Triassic boundary strata at many sites show two widespread palynological events in the wake of the forest destruction: The fungal event, evidenced by a thin zone with >95% fungal cells (Reduviasporonites and woody debris, found in terrestrial and marine sediments, and the acritarch event, marked by the sudden flood of unusual phytoplankton in the marine realm. These two events represent the global temporary explosive spread of stress-tolerant and opportunistic organisms on land and in the sea just after the latest Permian disaster. They represent unique events, and thus they can provide a time marker in correlating latest Permian marine and terrestrial sequences.

  2. Multivariate spectral-analysis of movement-related EEG data

    International Nuclear Information System (INIS)

    Andrew, C. M.

    1997-01-01

    The univariate method of event-related desynchronization (ERD) analysis, which quantifies the temporal evolution of power within specific frequency bands from electroencephalographic (EEG) data recorded during a task or event, is extended to an event related multivariate spectral analysis method. With this method, time courses of cross-spectra, phase spectra, coherence spectra, band-averaged coherence values (event-related coherence, ERCoh), partial power spectra and partial coherence spectra are estimated from an ensemble of multivariate event-related EEG trials. This provides a means of investigating relationships between EEG signals recorded over different scalp areas during the performance of a task or the occurrence of an event. The multivariate spectral analysis method is applied to EEG data recorded during three different movement-related studies involving discrete right index finger movements. The first study investigates the impact of the EEG derivation type on the temporal evolution of interhemispheric coherence between activity recorded at electrodes overlying the left and right sensorimotor hand areas during cued finger movement. The question results whether changes in coherence necessarily reflect changes in functional coupling of the cortical structures underlying the recording electrodes. The method is applied to data recorded during voluntary finger movement and a hypothesis, based on an existing global/local model of neocortical dynamics, is formulated to explain the coherence results. The third study applies partial spectral analysis too, and investigates phase relationships of, movement-related data recorded from a full head montage, thereby providing further results strengthening the global/local hypothesis. (author)

  3. Description of the signal and background event mixing as implemented in the Marlin processor OverlayTiming

    CERN Document Server

    Schade, P

    2011-01-01

    This note documents OverlayTiming, a processor in the Marlin software frame- work. OverlayTiming can model the timing structure of a linear collider bunch train and offers the possibility to merge simulated physics events with beam-beam background events. In addition, a realistic structure of the detector readout can be imitated by defining readout time windows for each subdetector.

  4. Potential of turbidity monitoring for real time control of pollutant discharge in sewers during rainfall events.

    Science.gov (United States)

    Lacour, C; Joannis, C; Gromaire, M-C; Chebbo, G

    2009-01-01

    Turbidity sensors can be used to continuously monitor the evolution of pollutant mass discharge. For two sites within the Paris combined sewer system, continuous turbidity, conductivity and flow data were recorded at one-minute time intervals over a one-year period. This paper is intended to highlight the variability in turbidity dynamics during wet weather. For each storm event, turbidity response aspects were analysed through different classifications. The correlation between classification and common parameters, such as the antecedent dry weather period, total event volume per impervious hectare and both the mean and maximum hydraulic flow for each event, was also studied. Moreover, the dynamics of flow and turbidity signals were compared at the event scale. No simple relation between turbidity responses, hydraulic flow dynamics and the chosen parameters was derived from this effort. Knowledge of turbidity dynamics could therefore potentially improve wet weather management, especially when using pollution-based real-time control (P-RTC) since turbidity contains information not included in hydraulic flow dynamics and not readily predictable from such dynamics.

  5. Chemometric and multivariate statistical analysis of time-of-flight secondary ion mass spectrometry spectra from complex Cu-Fe sulfides.

    Science.gov (United States)

    Kalegowda, Yogesh; Harmer, Sarah L

    2012-03-20

    Time-of-flight secondary ion mass spectrometry (TOF-SIMS) spectra of mineral samples are complex, comprised of large mass ranges and many peaks. Consequently, characterization and classification analysis of these systems is challenging. In this study, different chemometric and statistical data evaluation methods, based on monolayer sensitive TOF-SIMS data, have been tested for the characterization and classification of copper-iron sulfide minerals (chalcopyrite, chalcocite, bornite, and pyrite) at different flotation pulp conditions (feed, conditioned feed, and Eh modified). The complex mass spectral data sets were analyzed using the following chemometric and statistical techniques: principal component analysis (PCA); principal component-discriminant functional analysis (PC-DFA); soft independent modeling of class analogy (SIMCA); and k-Nearest Neighbor (k-NN) classification. PCA was found to be an important first step in multivariate analysis, providing insight into both the relative grouping of samples and the elemental/molecular basis for those groupings. For samples exposed to oxidative conditions (at Eh ~430 mV), each technique (PCA, PC-DFA, SIMCA, and k-NN) was found to produce excellent classification. For samples at reductive conditions (at Eh ~ -200 mV SHE), k-NN and SIMCA produced the most accurate classification. Phase identification of particles that contain the same elements but a different crystal structure in a mixed multimetal mineral system has been achieved.

  6. Event History Analysis in Quantitative Genetics

    DEFF Research Database (Denmark)

    Maia, Rafael Pimentel

    Event history analysis is a clas of statistical methods specially designed to analyze time-to-event characteristics, e.g. the time until death. The aim of the thesis was to present adequate multivariate versions of mixed survival models that properly represent the genetic aspects related to a given...

  7. Continuous-time random walks with reset events. Historical background and new perspectives

    Science.gov (United States)

    Montero, Miquel; Masó-Puigdellosas, Axel; Villarroel, Javier

    2017-09-01

    In this paper, we consider a stochastic process that may experience random reset events which relocate the system to its starting position. We focus our attention on a one-dimensional, monotonic continuous-time random walk with a constant drift: the process moves in a fixed direction between the reset events, either by the effect of the random jumps, or by the action of a deterministic bias. However, the orientation of its motion is randomly determined after each restart. As a result of these alternating dynamics, interesting properties do emerge. General formulas for the propagator as well as for two extreme statistics, the survival probability and the mean first-passage time, are also derived. The rigor of these analytical results is verified by numerical estimations, for particular but illuminating examples.

  8. Narrative of the annotated Space–Time Cube – revisiting a historical event

    DEFF Research Database (Denmark)

    Kraak, Menno-Jan; Kveladze, Irma

    2017-01-01

    The Space–Time Cube (STC) is a suitable representation to display multiple characteristics of movement data and will especially reveal temporal patterns in the data. By adding annotations to the cube’s paths and stations, the narrative of the display is enhanced. To illustrate the STC’s storytell......The Space–Time Cube (STC) is a suitable representation to display multiple characteristics of movement data and will especially reveal temporal patterns in the data. By adding annotations to the cube’s paths and stations, the narrative of the display is enhanced. To illustrate the STC......’s storytelling capabilities, a historical event, Napoleon’s crossing of the Berezina River during his Russian campaign in 1812 is presented and linked to an event in 2012 when the authors made a similar trip. Also, a set of different visual queries and their results are presented, emphasizing the STC...... as an alternative addition to a more extended visualization environment....

  9. Potential of turbidity monitoring for real time control of pollutant discharge in sewers during rainfall events

    OpenAIRE

    LACOUR, Céline; JOANNIS, Claude; GROMAIRE, MC; CHEBBO, Ghassan

    2009-01-01

    Turbidity sensors can be used to continuously monitor the evolution of pollutant mass discharge. For two sites within the Paris combined sewer system, continuous turbidity, conductivity and flow data were recorded at one-minute time intervals over a one-year period. This paper is intended to highlight the variability in turbidity dynamics during wet weather. For each storm event, turbidity response aspects were analysed through different classifications. The correlation between classification...

  10. Building a Catalog of Time-Dependent Inversions for Cascadia ETS Events

    Science.gov (United States)

    Bartlow, N. M.; Williams, C. A.; Wallace, L. M.

    2017-12-01

    Episodic Tremor and Slip (ETS), composed of periodically occurring slow slip events accompanied by tectonic tremor, have been recognized in Cascadia since 1999. While the tremor has been continuously and automatically monitored for a few years (Wech et al., SRL, 2010; pnsn.org/tremor), the geodetically-derived slip has not been systematically monitored in the same way. Instead, numerous time-dependent and static inversions of the geodetic data have been performed for individual ETS events, with many events going unstudied. Careful study of, and monitoring of, ETS is important both to advance the scientific understanding of fault mechanics and to improve earthquake hazard forecasting in Cascadia. Here we present the results of initial efforts to standardize geodetic inversions of slow slip during Cascadia ETS. We use the Network Inversion Filter (NIF, Segall and Matthews,1997; McGuire and Segall, 2003; Miyazaki et al.,2006), applied evenly to an extended time period, to detect and catalog slow slip transients. Bartlow et al., 2014, conducted a similar study for the Hikurangi subduction zone, covering a 2.5 year period. Additionally, we generate Green's functions using the PyLith finite element code (Aagaard et al., 2013) to allow consideration of elastic property variations derived from a Cascadia-wide seismic velocity model (Stephenson, USGS pub., 2007). These Green's functions are then integrated to provide Green's functions compatible with the Network Inversion Filter. The use of heterogeneous elastic Green's functions allows for a more accurate estimation of slip amplitudes, both during individual ETS events and averaged over multiple events. This is useful for constraining the total slip budget in Cascadia, including whether ETS takes up the entire plate motion on the deeper extent of the plate interface where it occurs. The recent study of Williams and Wallace, GRL, 2015 demonstrated that the use heterogeneous elastic Green's Functions in inversions can make a

  11. Quantifying and estimating the predictive accuracy for censored time-to-event data with competing risks.

    Science.gov (United States)

    Wu, Cai; Li, Liang

    2018-05-15

    This paper focuses on quantifying and estimating the predictive accuracy of prognostic models for time-to-event outcomes with competing events. We consider the time-dependent discrimination and calibration metrics, including the receiver operating characteristics curve and the Brier score, in the context of competing risks. To address censoring, we propose a unified nonparametric estimation framework for both discrimination and calibration measures, by weighting the censored subjects with the conditional probability of the event of interest given the observed data. The proposed method can be extended to time-dependent predictive accuracy metrics constructed from a general class of loss functions. We apply the methodology to a data set from the African American Study of Kidney Disease and Hypertension to evaluate the predictive accuracy of a prognostic risk score in predicting end-stage renal disease, accounting for the competing risk of pre-end-stage renal disease death, and evaluate its numerical performance in extensive simulation studies. Copyright © 2018 John Wiley & Sons, Ltd.

  12. Joint two-part Tobit models for longitudinal and time-to-event data.

    Science.gov (United States)

    Dagne, Getachew A

    2017-11-20

    In this article, we show how Tobit models can address problems of identifying characteristics of subjects having left-censored outcomes in the context of developing a method for jointly analyzing time-to-event and longitudinal data. There are some methods for handling these types of data separately, but they may not be appropriate when time to event is dependent on the longitudinal outcome, and a substantial portion of values are reported to be below the limits of detection. An alternative approach is to develop a joint model for the time-to-event outcome and a two-part longitudinal outcome, linking them through random effects. This proposed approach is implemented to assess the association between the risk of decline of CD4/CD8 ratio and rates of change in viral load, along with discriminating between patients who are potentially progressors to AIDS from patients who do not. We develop a fully Bayesian approach for fitting joint two-part Tobit models and illustrate the proposed methods on simulated and real data from an AIDS clinical study. Copyright © 2017 John Wiley & Sons, Ltd.

  13. Determination of the event collision time with the ALICE detector at the LHC

    CERN Document Server

    Adam, Jaroslav; Aggarwal, Madan Mohan; Aglieri Rinella, Gianluca; Agnello, Michelangelo; Agrawal, Neelima; Ahammed, Zubayer; Ahmad, Shakeel; Ahn, Sang Un; Aiola, Salvatore; Akindinov, Alexander; Alam, Sk Noor; Silva De Albuquerque, Danilo; Aleksandrov, Dmitry; Alessandro, Bruno; Alexandre, Didier; Alfaro Molina, Jose Ruben; Alici, Andrea; Alkin, Anton; Alme, Johan; Alt, Torsten; Altinpinar, Sedat; Altsybeev, Igor; Alves Garcia Prado, Caio; An, Mangmang; Andrei, Cristian; Andrews, Harry Arthur; Andronic, Anton; Anguelov, Venelin; Anson, Christopher Daniel; Anticic, Tome; Antinori, Federico; Antonioli, Pietro; Anwar, Rafay; Aphecetche, Laurent Bernard; Appelshaeuser, Harald; Arcelli, Silvia; Arnaldi, Roberta; Arnold, Oliver Werner; Arsene, Ionut Cristian; Arslandok, Mesut; Audurier, Benjamin; Augustinus, Andre; Averbeck, Ralf Peter; Azmi, Mohd Danish; Badala, Angela; Baek, Yong Wook; Bagnasco, Stefano; Bailhache, Raphaelle Marie; Bala, Renu; Balasubramanian, Supraja; Baldisseri, Alberto; Baral, Rama Chandra; Barbano, Anastasia Maria; Barbera, Roberto; Barile, Francesco; Barnafoldi, Gergely Gabor; Barnby, Lee Stuart; Ramillien Barret, Valerie; Bartalini, Paolo; Barth, Klaus; Bartke, Jerzy Gustaw; Bartsch, Esther; Basile, Maurizio; Bastid, Nicole; Basu, Sumit; Bathen, Bastian; Batigne, Guillaume; Batista Camejo, Arianna; Batyunya, Boris; Batzing, Paul Christoph; Bearden, Ian Gardner; Beck, Hans; Bedda, Cristina; Behera, Nirbhay Kumar; Belikov, Iouri; Bellini, Francesca; Bello Martinez, Hector; Bellwied, Rene; Espinoza Beltran, Lucina Gabriela; Belyaev, Vladimir; Bencedi, Gyula; Beole, Stefania; Bercuci, Alexandru; Berdnikov, Yaroslav; Berenyi, Daniel; Bertens, Redmer Alexander; Berzano, Dario; Betev, Latchezar; Bhasin, Anju; Bhat, Inayat Rasool; Bhati, Ashok Kumar; Bhattacharjee, Buddhadeb; Bhom, Jihyun; Bianchi, Livio; Bianchi, Nicola; Bianchin, Chiara; Bielcik, Jaroslav; Bielcikova, Jana; Bilandzic, Ante; Biro, Gabor; Biswas, Rathijit; Biswas, Saikat; Bjelogrlic, Sandro; Blair, Justin Thomas; Blau, Dmitry; Blume, Christoph; Bock, Friederike; Bogdanov, Alexey; Boldizsar, Laszlo; Bombara, Marek; Bonora, Matthias; Book, Julian Heinz; Borel, Herve; Borissov, Alexander; Borri, Marcello; Botta, Elena; Bourjau, Christian; Braun-munzinger, Peter; Bregant, Marco; Broker, Theo Alexander; Browning, Tyler Allen; Broz, Michal; Brucken, Erik Jens; Bruna, Elena; Bruno, Giuseppe Eugenio; Budnikov, Dmitry; Buesching, Henner; Bufalino, Stefania; Buhler, Paul; Iga Buitron, Sergio Arturo; Buncic, Predrag; Busch, Oliver; Buthelezi, Edith Zinhle; Bashir Butt, Jamila; Buxton, Jesse Thomas; Cabala, Jan; Caffarri, Davide; Caines, Helen Louise; Caliva, Alberto; Calvo Villar, Ernesto; Camerini, Paolo; Carena, Francesco; Carena, Wisla; Carnesecchi, Francesca; Castillo Castellanos, Javier Ernesto; Castro, Andrew John; Casula, Ester Anna Rita; Ceballos Sanchez, Cesar; Cepila, Jan; Cerello, Piergiorgio; Cerkala, Jakub; Chang, Beomsu; Chapeland, Sylvain; Chartier, Marielle; Charvet, Jean-luc Fernand; Chattopadhyay, Subhasis; Chattopadhyay, Sukalyan; Chauvin, Alex; Chelnokov, Volodymyr; Cherney, Michael Gerard; Cheshkov, Cvetan Valeriev; Cheynis, Brigitte; Chibante Barroso, Vasco Miguel; Dobrigkeit Chinellato, David; Cho, Soyeon; Chochula, Peter; Choi, Kyungeon; Chojnacki, Marek; Choudhury, Subikash; Christakoglou, Panagiotis; Christensen, Christian Holm; Christiansen, Peter; Chujo, Tatsuya; Chung, Suh-urk; Cicalo, Corrado; Cifarelli, Luisa; Cindolo, Federico; Cleymans, Jean Willy Andre; Colamaria, Fabio Filippo; Colella, Domenico; Collu, Alberto; Colocci, Manuel; Conesa Balbastre, Gustavo; Conesa Del Valle, Zaida; Connors, Megan Elizabeth; Contreras Nuno, Jesus Guillermo; Cormier, Thomas Michael; Corrales Morales, Yasser; Cortes Maldonado, Ismael; Cortese, Pietro; Cosentino, Mauro Rogerio; Costa, Filippo; Crkovska, Jana; Crochet, Philippe; Cruz Albino, Rigoberto; Cuautle Flores, Eleazar; Cunqueiro Mendez, Leticia; Dahms, Torsten; Dainese, Andrea; Danisch, Meike Charlotte; Danu, Andrea; Das, Debasish; Das, Indranil; Das, Supriya; Dash, Ajay Kumar; Dash, Sadhana; De, Sudipan; De Caro, Annalisa; De Cataldo, Giacinto; De Conti, Camila; De Cuveland, Jan; De Falco, Alessandro; De Gruttola, Daniele; De Marco, Nora; De Pasquale, Salvatore; Derradi De Souza, Rafael; Deisting, Alexander; Deloff, Andrzej; Deplano, Caterina; Dhankher, Preeti; Di Bari, Domenico; Di Mauro, Antonio; Di Nezza, Pasquale; Di Ruzza, Benedetto; Diaz Corchero, Miguel Angel; Dietel, Thomas; Dillenseger, Pascal; Divia, Roberto; Djuvsland, Oeystein; Dobrin, Alexandru Florin; Domenicis Gimenez, Diogenes; Donigus, Benjamin; Dordic, Olja; Drozhzhova, Tatiana; Dubey, Anand Kumar; Dubla, Andrea; Ducroux, Laurent; Duggal, Ashpreet Kaur; Dupieux, Pascal; Ehlers Iii, Raymond James; Elia, Domenico; Endress, Eric; Engel, Heiko; Epple, Eliane; Erazmus, Barbara Ewa; Erhardt, Filip; Espagnon, Bruno; Esumi, Shinichi; Eulisse, Giulio; Eum, Jongsik; Evans, David; Evdokimov, Sergey; Eyyubova, Gyulnara; Fabbietti, Laura; Fabris, Daniela; Faivre, Julien; Fantoni, Alessandra; Fasel, Markus; Feldkamp, Linus; Feliciello, Alessandro; Feofilov, Grigorii; Ferencei, Jozef; Fernandez Tellez, Arturo; Gonzalez Ferreiro, Elena; Ferretti, Alessandro; Festanti, Andrea; Feuillard, Victor Jose Gaston; Figiel, Jan; Araujo Silva Figueredo, Marcel; Filchagin, Sergey; Finogeev, Dmitry; Fionda, Fiorella; Fiore, Enrichetta Maria; Floris, Michele; Foertsch, Siegfried Valentin; Foka, Panagiota; Fokin, Sergey; Fragiacomo, Enrico; Francescon, Andrea; Francisco, Audrey; Frankenfeld, Ulrich Michael; Fronze, Gabriele Gaetano; Fuchs, Ulrich; Furget, Christophe; Furs, Artur; Fusco Girard, Mario; Gaardhoeje, Jens Joergen; Gagliardi, Martino; Gago Medina, Alberto Martin; Gajdosova, Katarina; Gallio, Mauro; Duarte Galvan, Carlos; Gangadharan, Dhevan Raja; Ganoti, Paraskevi; Gao, Chaosong; Garabatos Cuadrado, Jose; Garcia-solis, Edmundo Javier; Garg, Kunal; Garg, Prakhar; Gargiulo, Corrado; Gasik, Piotr Jan; Gauger, Erin Frances; De Leone Gay, Maria Beatriz; Germain, Marie; Ghosh, Premomoy; Ghosh, Sanjay Kumar; Gianotti, Paola; Giubellino, Paolo; Giubilato, Piero; Gladysz-dziadus, Ewa; Glassel, Peter; Gomez Coral, Diego Mauricio; Gomez Ramirez, Andres; Sanchez Gonzalez, Andres; Gonzalez, Victor; Gonzalez Zamora, Pedro; Gorbunov, Sergey; Gorlich, Lidia Maria; Gotovac, Sven; Grabski, Varlen; Graczykowski, Lukasz Kamil; Graham, Katie Leanne; Greiner, Leo Clifford; Grelli, Alessandro; Grigoras, Costin; Grigoryev, Vladislav; Grigoryan, Ara; Grigoryan, Smbat; Grion, Nevio; Gronefeld, Julius Maximilian; Grosse-oetringhaus, Jan Fiete; Grosso, Raffaele; Gruber, Lukas; Guber, Fedor; Guernane, Rachid; Guerzoni, Barbara; Gulbrandsen, Kristjan Herlache; Gunji, Taku; Gupta, Anik; Gupta, Ramni; Bautista Guzman, Irais; Haake, Rudiger; Hadjidakis, Cynthia Marie; Hamagaki, Hideki; Hamar, Gergoe; Hamon, Julien Charles; Harris, John William; Harton, Austin Vincent; Hatzifotiadou, Despina; Hayashi, Shinichi; Heckel, Stefan Thomas; Hellbar, Ernst; Helstrup, Haavard; Herghelegiu, Andrei Ionut; Herrera Corral, Gerardo Antonio; Herrmann, Florian; Hess, Benjamin Andreas; Hetland, Kristin Fanebust; Hillemanns, Hartmut; Hippolyte, Boris; Hladky, Jan; Horak, David; Hosokawa, Ritsuya; Hristov, Peter Zahariev; Hughes, Charles; Humanic, Thomas; Hussain, Nur; Hussain, Tahir; Hutter, Dirk; Hwang, Dae Sung; Ilkaev, Radiy; Inaba, Motoi; Ippolitov, Mikhail; Irfan, Muhammad; Isakov, Vladimir; Islam, Md Samsul; Ivanov, Marian; Ivanov, Vladimir; Izucheev, Vladimir; Jacak, Barbara; Jacazio, Nicolo; Jacobs, Peter Martin; Jadhav, Manoj Bhanudas; Jadlovska, Slavka; Jadlovsky, Jan; Jahnke, Cristiane; Jakubowska, Monika Joanna; Janik, Malgorzata Anna; Pahula Hewage, Sandun; Jena, Chitrasen; Jena, Satyajit; Jimenez Bustamante, Raul Tonatiuh; Jones, Peter Graham; Jusko, Anton; Kalinak, Peter; Kalweit, Alexander Philipp; Kang, Ju Hwan; Kaplin, Vladimir; Kar, Somnath; Karasu Uysal, Ayben; Karavichev, Oleg; Karavicheva, Tatiana; Karayan, Lilit; Karpechev, Evgeny; Kebschull, Udo Wolfgang; Keidel, Ralf; Keijdener, Darius Laurens; Keil, Markus; Khan, Mohammed Mohisin; Khan, Palash; Khan, Shuaib Ahmad; Khanzadeev, Alexei; Kharlov, Yury; Khatun, Anisa; Khuntia, Arvind; Kileng, Bjarte; Kim, Do Won; Kim, Dong Jo; Kim, Daehyeok; Kim, Hyeonjoong; Kim, Jinsook; Kim, Jiyoung; Kim, Minjung; Kim, Minwoo; Kim, Se Yong; Kim, Taesoo; Kirsch, Stefan; Kisel, Ivan; Kiselev, Sergey; Kisiel, Adam Ryszard; Kiss, Gabor; Klay, Jennifer Lynn; Klein, Carsten; Klein, Jochen; Klein-boesing, Christian; Klewin, Sebastian; Kluge, Alexander; Knichel, Michael Linus; Knospe, Anders Garritt; Kobdaj, Chinorat; Kofarago, Monika; Kollegger, Thorsten; Kolozhvari, Anatoly; Kondratev, Valerii; Kondratyeva, Natalia; Kondratyuk, Evgeny; Konevskikh, Artem; Kopcik, Michal; Kour, Mandeep; Kouzinopoulos, Charalampos; Kovalenko, Oleksandr; Kovalenko, Vladimir; Kowalski, Marek; Koyithatta Meethaleveedu, Greeshma; Kralik, Ivan; Kravcakova, Adela; Krivda, Marian; Krizek, Filip; Kryshen, Evgeny; Krzewicki, Mikolaj; Kubera, Andrew Michael; Kucera, Vit; Kuhn, Christian Claude; Kuijer, Paulus Gerardus; Kumar, Ajay; Kumar, Jitendra; Kumar, Lokesh; Kumar, Shyam; Kundu, Sourav; Kurashvili, Podist; Kurepin, Alexander; Kurepin, Alexey; Kuryakin, Alexey; Kushpil, Svetlana; Kweon, Min Jung; Kwon, Youngil; La Pointe, Sarah Louise; La Rocca, Paola; Lagana Fernandes, Caio; Lakomov, Igor; Langoy, Rune; Lapidus, Kirill; Lara Martinez, Camilo Ernesto; Lardeux, Antoine Xavier; Lattuca, Alessandra; Laudi, Elisa; Lazaridis, Lazaros; Lea, Ramona; Leardini, Lucia; Lee, Seongjoo; Lehas, Fatiha; Lehner, Sebastian; Lehrbach, Johannes; Lemmon, Roy Crawford; Lenti, Vito; Leogrande, Emilia; Leon Monzon, Ildefonso; Levai, Peter; Li, Shuang; Li, Xiaomei; Lien, Jorgen Andre; Lietava, Roman; Lindal, Svein; Lindenstruth, Volker; Lippmann, Christian; Lisa, Michael Annan; Ljunggren, Hans Martin; Llope, William; Lodato, Davide Francesco; Lonne, Per-ivar; Loginov, Vitaly; Loizides, Constantinos; Lopez, Xavier Bernard; Lopez Torres, Ernesto; Lowe, Andrew John; Luettig, Philipp Johannes; Lunardon, Marcello; Luparello, Grazia; Lupi, Matteo; Lutz, Tyler Harrison; Maevskaya, Alla; Mager, Magnus; Mahajan, Sanjay; Mahmood, Sohail Musa; Maire, Antonin; Majka, Richard Daniel; Malaev, Mikhail; Maldonado Cervantes, Ivonne Alicia; Malinina, Liudmila; Mal'kevich, Dmitry; Malzacher, Peter; Mamonov, Alexander; Manko, Vladislav; Manso, Franck; Manzari, Vito; Mao, Yaxian; Marchisone, Massimiliano; Mares, Jiri; Margagliotti, Giacomo Vito; Margotti, Anselmo; Margutti, Jacopo; Marin, Ana Maria; Markert, Christina; Marquard, Marco; Martin, Nicole Alice; Martinengo, Paolo; Martinez Hernandez, Mario Ivan; Martinez-garcia, Gines; Martinez Pedreira, Miguel; Mas, Alexis Jean-michel; Masciocchi, Silvia; Masera, Massimo; Masoni, Alberto; Mastroserio, Annalisa; Matyja, Adam Tomasz; Mayer, Christoph; Mazer, Joel Anthony; Mazzilli, Marianna; Mazzoni, Alessandra Maria; Meddi, Franco; Melikyan, Yuri; Menchaca-rocha, Arturo Alejandro; Meninno, Elisa; Mercado-perez, Jorge; Meres, Michal; Mhlanga, Sibaliso; Miake, Yasuo; Mieskolainen, Matti Mikael; Mikhaylov, Konstantin; Milano, Leonardo; Milosevic, Jovan; Mischke, Andre; Mishra, Aditya Nath; Mishra, Tribeni; Miskowiec, Dariusz Czeslaw; Mitra, Jubin; Mitu, Ciprian Mihai; Mohammadi, Naghmeh; Mohanty, Bedangadas; Molnar, Levente; Montes Prado, Esther; Moreira De Godoy, Denise Aparecida; Perez Moreno, Luis Alberto; Moretto, Sandra; Morreale, Astrid; Morsch, Andreas; Muccifora, Valeria; Mudnic, Eugen; Muhlheim, Daniel Michael; Muhuri, Sanjib; Mukherjee, Maitreyee; Mulligan, James Declan; Gameiro Munhoz, Marcelo; Munning, Konstantin; Munzer, Robert Helmut; Murakami, Hikari; Murray, Sean; Musa, Luciano; Musinsky, Jan; Myers, Corey James; Naik, Bharati; Nair, Rahul; Nandi, Basanta Kumar; Nania, Rosario; Nappi, Eugenio; Naru, Muhammad Umair; Ferreira Natal Da Luz, Pedro Hugo; Nattrass, Christine; Rosado Navarro, Sebastian; Nayak, Kishora; Nayak, Ranjit; Nayak, Tapan Kumar; Nazarenko, Sergey; Nedosekin, Alexander; Negrao De Oliveira, Renato Aparecido; Nellen, Lukas; Ng, Fabian; Nicassio, Maria; Niculescu, Mihai; Niedziela, Jeremi; Nielsen, Borge Svane; Nikolaev, Sergey; Nikulin, Sergey; Nikulin, Vladimir; Noferini, Francesco; Nomokonov, Petr; Nooren, Gerardus; Cabanillas Noris, Juan Carlos; Norman, Jaime; Nyanin, Alexander; Nystrand, Joakim Ingemar; Oeschler, Helmut Oskar; Oh, Saehanseul; Ohlson, Alice Elisabeth; Okubo, Tsubasa; Olah, Laszlo; Oleniacz, Janusz; Oliveira Da Silva, Antonio Carlos; Oliver, Michael Henry; Onderwaater, Jacobus; Oppedisano, Chiara; Orava, Risto; Oravec, Matej; Ortiz Velasquez, Antonio; Oskarsson, Anders Nils Erik; Otwinowski, Jacek Tomasz; Oyama, Ken; Ozdemir, Mahmut; Pachmayer, Yvonne Chiara; Pacik, Vojtech; Pagano, Davide; Pagano, Paola; Paic, Guy; Pal, Susanta Kumar; Palni, Prabhakar; Pan, Jinjin; Pandey, Ashutosh Kumar; Papikyan, Vardanush; Pappalardo, Giuseppe; Pareek, Pooja; Park, Jonghan; Park, Woojin; Parmar, Sonia; Passfeld, Annika; Paticchio, Vincenzo; Patra, Rajendra Nath; Paul, Biswarup; Pei, Hua; Peitzmann, Thomas; Peng, Xinye; Pereira Da Costa, Hugo Denis Antonio; Peresunko, Dmitry Yurevich; Perez Lezama, Edgar; Peskov, Vladimir; Pestov, Yury; Petracek, Vojtech; Petrov, Viacheslav; Petrovici, Mihai; Petta, Catia; Piano, Stefano; Pikna, Miroslav; Pillot, Philippe; Ozelin De Lima Pimentel, Lais; Pinazza, Ombretta; Pinsky, Lawrence; Piyarathna, Danthasinghe; Ploskon, Mateusz Andrzej; Planinic, Mirko; Pluta, Jan Marian; Pochybova, Sona; Podesta Lerma, Pedro Luis Manuel; Poghosyan, Martin; Polishchuk, Boris; Poljak, Nikola; Poonsawat, Wanchaloem; Pop, Amalia; Poppenborg, Hendrik; Porteboeuf, Sarah Julie; Porter, R Jefferson; Pospisil, Jan; Pozdniakov, Valeriy; Prasad, Sidharth Kumar; Preghenella, Roberto; Prino, Francesco; Pruneau, Claude Andre; Pshenichnov, Igor; Puccio, Maximiliano; Puddu, Giovanna; Pujahari, Prabhat Ranjan; Punin, Valery; Putschke, Jorn Henning; Qvigstad, Henrik; Rachevski, Alexandre; Raha, Sibaji; Rajput, Sonia; Rak, Jan; Rakotozafindrabe, Andry Malala; Ramello, Luciano; Rami, Fouad; Rana, Dhan Bahadur; Raniwala, Rashmi; Raniwala, Sudhir; Rasanen, Sami Sakari; Rascanu, Bogdan Theodor; Rathee, Deepika; Ratza, Viktor; Ravasenga, Ivan; Read, Kenneth Francis; Redlich, Krzysztof; Rehman, Attiq Ur; Reichelt, Patrick Simon; Reidt, Felix; Ren, Xiaowen; Renfordt, Rainer Arno Ernst; Reolon, Anna Rita; Reshetin, Andrey; Reygers, Klaus Johannes; Riabov, Viktor; Ricci, Renato Angelo; Richert, Tuva Ora Herenui; Richter, Matthias Rudolph; Riedler, Petra; Riegler, Werner; Riggi, Francesco; Ristea, Catalin-lucian; Rodriguez Cahuantzi, Mario; Roeed, Ketil; Rogochaya, Elena; Rohr, David Michael; Roehrich, Dieter; Ronchetti, Federico; Ronflette, Lucile; Rosnet, Philippe; Rossi, Andrea; Roukoutakis, Filimon; Roy, Ankhi; Roy, Christelle Sophie; Roy, Pradip Kumar; Rubio Montero, Antonio Juan; Rui, Rinaldo; Russo, Riccardo; Ryabinkin, Evgeny; Ryabov, Yury; Rybicki, Andrzej; Saarinen, Sampo; Sadhu, Samrangy; Sadovskiy, Sergey; Safarik, Karel; Sahlmuller, Baldo; Sahoo, Baidyanath; Sahoo, Pragati; Sahoo, Raghunath; Sahoo, Sarita; Sahu, Pradip Kumar; Saini, Jogender; Sakai, Shingo; Saleh, Mohammad Ahmad; Salzwedel, Jai Samuel Nielsen; Sambyal, Sanjeev Singh; Samsonov, Vladimir; Sandoval, Andres; Sano, Masato; Sarkar, Debojit; Sarkar, Nachiketa; Sarma, Pranjal; Sas, Mike Henry Petrus; Scapparone, Eugenio; Scarlassara, Fernando; Scharenberg, Rolf Paul; Schiaua, Claudiu Cornel; Schicker, Rainer Martin; Schmidt, Christian Joachim; Schmidt, Hans Rudolf; Schmidt, Martin; Schukraft, Jurgen; Schutz, Yves Roland; Schwarz, Kilian Eberhard; Schweda, Kai Oliver; Scioli, Gilda; Scomparin, Enrico; Scott, Rebecca Michelle; Sefcik, Michal; Seger, Janet Elizabeth; Sekiguchi, Yuko; Sekihata, Daiki; Selyuzhenkov, Ilya; Senosi, Kgotlaesele; Senyukov, Serhiy; Serradilla Rodriguez, Eulogio; Sett, Priyanka; Sevcenco, Adrian; Shabanov, Arseniy; Shabetai, Alexandre; Shadura, Oksana; Shahoyan, Ruben; Shangaraev, Artem; Sharma, Ankita; Sharma, Anjali; Sharma, Mona; Sharma, Monika; Sharma, Natasha; Sheikh, Ashik Ikbal; Shigaki, Kenta; Shou, Qiye; Shtejer Diaz, Katherin; Sibiryak, Yury; Siddhanta, Sabyasachi; Sielewicz, Krzysztof Marek; Siemiarczuk, Teodor; Silvermyr, David Olle Rickard; Silvestre, Catherine Micaela; Simatovic, Goran; Simonetti, Giuseppe; Singaraju, Rama Narayana; Singh, Ranbir; Singhal, Vikas; Sarkar - Sinha, Tinku; Sitar, Branislav; Sitta, Mario; Skaali, Bernhard; Slupecki, Maciej; Smirnov, Nikolai; Snellings, Raimond; Snellman, Tomas Wilhelm; Song, Jihye; Song, Myunggeun; Song, Zixuan; Soramel, Francesca; Sorensen, Soren Pontoppidan; Sozzi, Federica; Spiriti, Eleuterio; Sputowska, Iwona Anna; Srivastava, Brijesh Kumar; Stachel, Johanna; Stan, Ionel; Stankus, Paul; Stenlund, Evert Anders; Steyn, Gideon Francois; Stiller, Johannes Hendrik; Stocco, Diego; Strmen, Peter; Alarcon Do Passo Suaide, Alexandre; Sugitate, Toru; Suire, Christophe Pierre; Suleymanov, Mais Kazim Oglu; Suljic, Miljenko; Sultanov, Rishat; Sumbera, Michal; Sumowidagdo, Suharyo; Suzuki, Ken; Swain, Sagarika; Szabo, Alexander; Szarka, Imrich; Szczepankiewicz, Adam; Szymanski, Maciej Pawel; Tabassam, Uzma; Takahashi, Jun; Tambave, Ganesh Jagannath; Tanaka, Naoto; Tarhini, Mohamad; Tariq, Mohammad; Tarzila, Madalina-gabriela; Tauro, Arturo; Tejeda Munoz, Guillermo; Telesca, Adriana; Terasaki, Kohei; Terrevoli, Cristina; Teyssier, Boris; Thakur, Dhananjaya; Thomas, Deepa; Tieulent, Raphael Noel; Tikhonov, Anatoly; Timmins, Anthony Robert; Toia, Alberica; Tripathy, Sushanta; Trogolo, Stefano; Trombetta, Giuseppe; Trubnikov, Victor; Trzaska, Wladyslaw Henryk; Tsuji, Tomoya; Tumkin, Alexandr; Turrisi, Rosario; Tveter, Trine Spedstad; Ullaland, Kjetil; Umaka, Ejiro Naomi; Uras, Antonio; Usai, Gianluca; Utrobicic, Antonija; Vala, Martin; Van Der Maarel, Jasper; Van Hoorne, Jacobus Willem; Van Leeuwen, Marco; Vanat, Tomas; Vande Vyvre, Pierre; Varga, Dezso; Diozcora Vargas Trevino, Aurora; Vargyas, Marton; Varma, Raghava; Vasileiou, Maria; Vasiliev, Andrey; Vauthier, Astrid; Vazquez Doce, Oton; Vechernin, Vladimir; Veen, Annelies Marianne; Velure, Arild; Vercellin, Ermanno; Vergara Limon, Sergio; Vernet, Renaud; Vertesi, Robert; Vickovic, Linda; Vigolo, Sonia; Viinikainen, Jussi Samuli; Vilakazi, Zabulon; Villalobos Baillie, Orlando; Villatoro Tello, Abraham; Vinogradov, Alexander; Vinogradov, Leonid; Virgili, Tiziano; Vislavicius, Vytautas; Vodopyanov, Alexander; Volkl, Martin Andreas; Voloshin, Kirill; Voloshin, Sergey; Volpe, Giacomo; Von Haller, Barthelemy; Vorobyev, Ivan; Voscek, Dominik; Vranic, Danilo; Vrlakova, Janka; Wagner, Boris; Wagner, Jan; Wang, Hongkai; Wang, Mengliang; Watanabe, Daisuke; Watanabe, Yosuke; Weber, Michael; Weber, Steffen Georg; Weiser, Dennis Franz; Wessels, Johannes Peter; Westerhoff, Uwe; Whitehead, Andile Mothegi; Wiechula, Jens; Wikne, Jon; Wilk, Grzegorz Andrzej; Wilkinson, Jeremy John; Willems, Guido Alexander; Williams, Crispin; Windelband, Bernd Stefan; Winn, Michael Andreas; Witt, William Edward; Yalcin, Serpil; Yang, Ping; Yano, Satoshi; Yin, Zhongbao; Yokoyama, Hiroki; Yoo, In-kwon; Yoon, Jin Hee; Yurchenko, Volodymyr; Zaccolo, Valentina; Zaman, Ali; Zampolli, Chiara; Correia Zanoli, Henrique Jose; Zaporozhets, Sergey; Zardoshti, Nima; Zarochentsev, Andrey; Zavada, Petr; Zavyalov, Nikolay; Zbroszczyk, Hanna Paulina; Zhalov, Mikhail; Zhang, Haitao; Zhang, Xiaoming; Zhang, Yonghong; Chunhui, Zhang; Zhang, Zuman; Zhao, Chengxin; Zhigareva, Natalia; Zhou, Daicui; Zhou, You; Zhou, Zhuo; Zhu, Hongsheng; Zhu, Jianhui; Zichichi, Antonino; Zimmermann, Alice; Zimmermann, Markus Bernhard; Zinovjev, Gennady; Zmeskal, Johann

    2017-02-24

    Particle identification is an important feature of the ALICE detector at the LHC. In particular, for particle identification via the time-of-flight technique, the precise determination of the event collision time represents an important ingredient of the quality of the measurement. In this paper, the different methods used for such a measurement in ALICE by means of the T0 and the TOF detectors are reviewed. Efficiencies, resolution and the improvement of the particle identification separation power of the methods used are presented for the different LHC colliding systems (pp , p-Pb and Pb-Pb) during the first period of data taking of LHC (Run 1).

  14. Delay-time distribution of core-collapse supernovae with late events resulting from binary interaction

    Science.gov (United States)

    Zapartas, E.; de Mink, S. E.; Izzard, R. G.; Yoon, S.-C.; Badenes, C.; Götberg, Y.; de Koter, A.; Neijssel, C. J.; Renzo, M.; Schootemeijer, A.; Shrotriya, T. S.

    2017-05-01

    Most massive stars, the progenitors of core-collapse supernovae, are in close binary systems and may interact with their companion through mass transfer or merging. We undertake a population synthesis study to compute the delay-time distribution of core-collapse supernovae, that is, the supernova rate versus time following a starburst, taking into account binary interactions. We test the systematic robustness of our results by running various simulations to account for the uncertainties in our standard assumptions. We find that a significant fraction, %, of core-collapse supernovae are "late", that is, they occur 50-200 Myr after birth, when all massive single stars have already exploded. These late events originate predominantly from binary systems with at least one, or, in most cases, with both stars initially being of intermediate mass (4-8 M⊙). The main evolutionary channels that contribute often involve either the merging of the initially more massive primary star with its companion or the engulfment of the remaining core of the primary by the expanding secondary that has accreted mass at an earlier evolutionary stage. Also, the total number of core-collapse supernovae increases by % because of binarity for the same initial stellar mass. The high rate implies that we should have already observed such late core-collapse supernovae, but have not recognized them as such. We argue that φ Persei is a likely progenitor and that eccentric neutron star - white dwarf systems are likely descendants. Late events can help explain the discrepancy in the delay-time distributions derived from supernova remnants in the Magellanic Clouds and extragalactic type Ia events, lowering the contribution of prompt Ia events. We discuss ways to test these predictions and speculate on the implications for supernova feedback in simulations of galaxy evolution.

  15. Inter-Event Time Definition Setting Procedure for Urban Drainage Systems

    Directory of Open Access Journals (Sweden)

    Jingul Joo

    2013-12-01

    Full Text Available Traditional inter-event time definition (IETD estimate methodologies generally take into account only rainfall characteristics and not drainage basin characteristics. Therefore, they may not succeed in providing an appropriate value of IETD for any sort of application to the design of urban drainage system devices. To overcome this limitation, this study presents a method of IETD determination that considers basin characteristics. The suggested definition of IETD is the time period from the end of a rainfall event to the end of a direct runoff. The suggested method can identify the independent events that are suitable for the statistical analysis of the recorded rainfall. Using the suggested IETD, the IETD of the Joong-Rang drainage system was determined and the area-IETD relation curve was drawn. The resulting regression curve can be used to determinate the IETD of ungauged urban drainage systems, with areas ranging between 40 and 4400 ha. Using the regression curve, the IETDs and time distribution of the design rainfall for four drainage systems in Korea were determined and rainfall-runoff simulations were performed with the Storm Water Management Model (SWMM. The results were compared with those from Huff's method which assumed a six-hour IETD. The peak flow rates obtained by the suggested method were 11%~15% greater than those obtained by Huff’s method. The suggested IETD determination method can identify independent events that are suitable for the statistical analysis of the recorded rainfall aimed at the design of urban drainage system devices.

  16. Event processing time prediction at the CMS experiment of the Large Hadron Collider

    International Nuclear Information System (INIS)

    Cury, Samir; Gutsche, Oliver; Kcira, Dorian

    2014-01-01

    The physics event reconstruction is one of the biggest challenges for the computing of the LHC experiments. Among the different tasks that computing systems of the CMS experiment performs, the reconstruction takes most of the available CPU resources. The reconstruction time of single collisions varies according to event complexity. Measurements were done in order to determine this correlation quantitatively, creating means to predict it based on the data-taking conditions of the input samples. Currently the data processing system splits tasks in groups with the same number of collisions and does not account for variations in the processing time. These variations can be large and can lead to a considerable increase in the time it takes for CMS workflows to finish. The goal of this study was to use estimates on processing time to more efficiently split the workflow into jobs. By considering the CPU time needed for each job the spread of the job-length distribution in a workflow is reduced.

  17. Multivariate Generalized Multiscale Entropy Analysis

    Directory of Open Access Journals (Sweden)

    Anne Humeau-Heurtier

    2016-11-01

    Full Text Available Multiscale entropy (MSE was introduced in the 2000s to quantify systems’ complexity. MSE relies on (i a coarse-graining procedure to derive a set of time series representing the system dynamics on different time scales; (ii the computation of the sample entropy for each coarse-grained time series. A refined composite MSE (rcMSE—based on the same steps as MSE—also exists. Compared to MSE, rcMSE increases the accuracy of entropy estimation and reduces the probability of inducing undefined entropy for short time series. The multivariate versions of MSE (MMSE and rcMSE (MrcMSE have also been introduced. In the coarse-graining step used in MSE, rcMSE, MMSE, and MrcMSE, the mean value is used to derive representations of the original data at different resolutions. A generalization of MSE was recently published, using the computation of different moments in the coarse-graining procedure. However, so far, this generalization only exists for univariate signals. We therefore herein propose an extension of this generalized MSE to multivariate data. The multivariate generalized algorithms of MMSE and MrcMSE presented herein (MGMSE and MGrcMSE, respectively are first analyzed through the processing of synthetic signals. We reveal that MGrcMSE shows better performance than MGMSE for short multivariate data. We then study the performance of MGrcMSE on two sets of short multivariate electroencephalograms (EEG available in the public domain. We report that MGrcMSE may show better performance than MrcMSE in distinguishing different types of multivariate EEG data. MGrcMSE could therefore supplement MMSE or MrcMSE in the processing of multivariate datasets.

  18. Different frontal involvement in ALS and PLS revealed by Stroop event-related potentials and reaction times

    Directory of Open Access Journals (Sweden)

    Ninfa eAmato

    2013-12-01

    Full Text Available BACKGROUND: A growing body of evidence suggests a link between cognitive and pathological changes in amyotrophic lateral sclerosis (ALS and in frontotemporal lobar dementia (FTLD. Cognitive deficits have been investigated much less extensively in primary lateral sclerosis (PLS than in ALS. OBJECTIVE: to investigate bioelectrical activity to Stroop test, assessing frontal function, in ALS, PLS and control groups. METHODS: 32 non-demented ALS patients, 10 non-demented PLS patients and 27 healthy subjects were included. Twenty-nine electroencephalography (EEG channels with binaural reference were recorded during covert Stroop task performance, involving mental discrimination of the stimuli and not vocal or motor response. Group effects on event related potentials (ERPs latency were analyzed using statistical multivariate analysis. Topographic analysis was performed using low resolution brain electromagnetic tomography (LORETA. RESULTS: ALS patients committed more errors in the execution of the task but they were not slower, whereas PLS patients did not show reduced accuracy, despite a slowing of reaction times (RTs. The main ERP components were delayed in ALS, but not in PLS, compared with controls. Moreover, RTs speed but not ERP latency correlated with clinical scores. ALS had decreased frontotemporal activity in the P2, P3 and N4 time windows compared to controls. CONCLUSION: These findings suggest a different pattern of psychophysiological involvement in ALS compared with PLS. The former is increasingly recognized to be a multisystems disorder, with a spectrum of executive and behavioural impairments reflecting frontotemporal dysfunction. The latter seems to mainly involve the motor system, with largely spared cognitive functions. Moreover, our results suggest that the covert version of the Stroop task used in the present study, may be useful to assess cognitive state in the very advanced stage of the disease, when other cognitive tasks are not

  19. Modeling associations between latent event processes governing time series of pulsing hormones.

    Science.gov (United States)

    Liu, Huayu; Carlson, Nichole E; Grunwald, Gary K; Polotsky, Alex J

    2017-10-31

    This work is motivated by a desire to quantify relationships between two time series of pulsing hormone concentrations. The locations of pulses are not directly observed and may be considered latent event processes. The latent event processes of pulsing hormones are often associated. It is this joint relationship we model. Current approaches to jointly modeling pulsing hormone data generally assume that a pulse in one hormone is coupled with a pulse in another hormone (one-to-one association). However, pulse coupling is often imperfect. Existing joint models are not flexible enough for imperfect systems. In this article, we develop a more flexible class of pulse association models that incorporate parameters quantifying imperfect pulse associations. We propose a novel use of the Cox process model as a model of how pulse events co-occur in time. We embed the Cox process model into a hormone concentration model. Hormone concentration is the observed data. Spatial birth and death Markov chain Monte Carlo is used for estimation. Simulations show the joint model works well for quantifying both perfect and imperfect associations and offers estimation improvements over single hormone analyses. We apply this model to luteinizing hormone (LH) and follicle stimulating hormone (FSH), two reproductive hormones. Use of our joint model results in an ability to investigate novel hypotheses regarding associations between LH and FSH secretion in obese and non-obese women. © 2017, The International Biometric Society.

  20. Event-Triggered Faults Tolerant Control for Stochastic Systems with Time Delays

    Directory of Open Access Journals (Sweden)

    Ling Huang

    2016-01-01

    Full Text Available This paper is concerned with the state-feedback controller design for stochastic networked control systems (NCSs with random actuator failures and transmission delays. Firstly, an event-triggered scheme is introduced to optimize the performance of the stochastic NCSs. Secondly, stochastic NCSs under event-triggered scheme are modeled as stochastic time-delay systems. Thirdly, some less conservative delay-dependent stability criteria in terms of linear matrix inequalities for the codesign of both the controller gain and the trigger parameters are obtained by using delay-decomposition technique and convex combination approach. Finally, a numerical example is provided to show the less sampled data transmission and less conservatism of the proposed theory.

  1. Towards real-time regional earthquake simulation I: real-time moment tensor monitoring (RMT) for regional events in Taiwan

    Science.gov (United States)

    Lee, Shiann-Jong; Liang, Wen-Tzong; Cheng, Hui-Wen; Tu, Feng-Shan; Ma, Kuo-Fong; Tsuruoka, Hiroshi; Kawakatsu, Hitoshi; Huang, Bor-Shouh; Liu, Chun-Chi

    2014-01-01

    We have developed a real-time moment tensor monitoring system (RMT) which takes advantage of a grid-based moment tensor inversion technique and real-time broad-band seismic recordings to automatically monitor earthquake activities in the vicinity of Taiwan. The centroid moment tensor (CMT) inversion technique and a grid search scheme are applied to obtain the information of earthquake source parameters, including the event origin time, hypocentral location, moment magnitude and focal mechanism. All of these source parameters can be determined simultaneously within 117 s after the occurrence of an earthquake. The monitoring area involves the entire Taiwan Island and the offshore region, which covers the area of 119.3°E to 123.0°E and 21.0°N to 26.0°N, with a depth from 6 to 136 km. A 3-D grid system is implemented in the monitoring area with a uniform horizontal interval of 0.1° and a vertical interval of 10 km. The inversion procedure is based on a 1-D Green's function database calculated by the frequency-wavenumber (fk) method. We compare our results with the Central Weather Bureau (CWB) catalogue data for earthquakes occurred between 2010 and 2012. The average differences between event origin time and hypocentral location are less than 2 s and 10 km, respectively. The focal mechanisms determined by RMT are also comparable with the Broadband Array in Taiwan for Seismology (BATS) CMT solutions. These results indicate that the RMT system is realizable and efficient to monitor local seismic activities. In addition, the time needed to obtain all the point source parameters is reduced substantially compared to routine earthquake reports. By connecting RMT with a real-time online earthquake simulation (ROS) system, all the source parameters will be forwarded to the ROS to make the real-time earthquake simulation feasible. The RMT has operated offline (2010-2011) and online (since January 2012 to present) at the Institute of Earth Sciences (IES), Academia Sinica

  2. Multivariate analysis with LISREL

    CERN Document Server

    Jöreskog, Karl G; Y Wallentin, Fan

    2016-01-01

    This book traces the theory and methodology of multivariate statistical analysis and shows how it can be conducted in practice using the LISREL computer program. It presents not only the typical uses of LISREL, such as confirmatory factor analysis and structural equation models, but also several other multivariate analysis topics, including regression (univariate, multivariate, censored, logistic, and probit), generalized linear models, multilevel analysis, and principal component analysis. It provides numerous examples from several disciplines and discusses and interprets the results, illustrated with sections of output from the LISREL program, in the context of the example. The book is intended for masters and PhD students and researchers in the social, behavioral, economic and many other sciences who require a basic understanding of multivariate statistical theory and methods for their analysis of multivariate data. It can also be used as a textbook on various topics of multivariate statistical analysis.

  3. Time-Frequency Data Reduction for Event Related Potentials: Combining Principal Component Analysis and Matching Pursuit

    Directory of Open Access Journals (Sweden)

    Selin Aviyente

    2010-01-01

    Full Text Available Joint time-frequency representations offer a rich representation of event related potentials (ERPs that cannot be obtained through individual time or frequency domain analysis. This representation, however, comes at the expense of increased data volume and the difficulty of interpreting the resulting representations. Therefore, methods that can reduce the large amount of time-frequency data to experimentally relevant components are essential. In this paper, we present a method that reduces the large volume of ERP time-frequency data into a few significant time-frequency parameters. The proposed method is based on applying the widely used matching pursuit (MP approach, with a Gabor dictionary, to principal components extracted from the time-frequency domain. The proposed PCA-Gabor decomposition is compared with other time-frequency data reduction methods such as the time-frequency PCA approach alone and standard matching pursuit methods using a Gabor dictionary for both simulated and biological data. The results show that the proposed PCA-Gabor approach performs better than either the PCA alone or the standard MP data reduction methods, by using the smallest amount of ERP data variance to produce the strongest statistical separation between experimental conditions.

  4. Measures of dependence for multivariate Lévy distributions

    Science.gov (United States)

    Boland, J.; Hurd, T. R.; Pivato, M.; Seco, L.

    2001-02-01

    Recent statistical analysis of a number of financial databases is summarized. Increasing agreement is found that logarithmic equity returns show a certain type of asymptotic behavior of the largest events, namely that the probability density functions have power law tails with an exponent α≈3.0. This behavior does not vary much over different stock exchanges or over time, despite large variations in trading environments. The present paper proposes a class of multivariate distributions which generalizes the observed qualities of univariate time series. A new consequence of the proposed class is the "spectral measure" which completely characterizes the multivariate dependences of the extreme tails of the distribution. This measure on the unit sphere in M-dimensions, in principle completely general, can be determined empirically by looking at extreme events. If it can be observed and determined, it will prove to be of importance for scenario generation in portfolio risk management.

  5. Measurement of the time dependence of B0-B0(bar) oscillations using inclusive dilepton events

    Energy Technology Data Exchange (ETDEWEB)

    Barrera, Barbara

    2000-10-16

    A preliminary study of time dependence of B{sup 0}{bar B}{sup 0} oscillations using dilepton events is presented. The flavor of the B meson is determined by the charge sign of the lepton. To separate signal leptons from cascade and fake leptons we have used a method which combines several discriminating variables in a neural network. The time evolution of the oscillations is studied by reconstructing the time difference between the decays of the B mesons produced by the {Upsilon}(4S) decay. With an integrated luminosity of 7.7 fb{sup -1} collected on resonance by BABAR at the PEP-II asymmetric B Factory, we measure the difference in mass of the neutral B eigenstates, {Delta}m{sub B{sup 0}}, to be (0.507 {+-} 0.015 {+-} 0.022) x 10{sup 12} {Dirac_h} s{sup -1}.

  6. A mathematical approach for evaluating Markov models in continuous time without discrete-event simulation.

    Science.gov (United States)

    van Rosmalen, Joost; Toy, Mehlika; O'Mahony, James F

    2013-08-01

    Markov models are a simple and powerful tool for analyzing the health and economic effects of health care interventions. These models are usually evaluated in discrete time using cohort analysis. The use of discrete time assumes that changes in health states occur only at the end of a cycle period. Discrete-time Markov models only approximate the process of disease progression, as clinical events typically occur in continuous time. The approximation can yield biased cost-effectiveness estimates for Markov models with long cycle periods and if no half-cycle correction is made. The purpose of this article is to present an overview of methods for evaluating Markov models in continuous time. These methods use mathematical results from stochastic process theory and control theory. The methods are illustrated using an applied example on the cost-effectiveness of antiviral therapy for chronic hepatitis B. The main result is a mathematical solution for the expected time spent in each state in a continuous-time Markov model. It is shown how this solution can account for age-dependent transition rates and discounting of costs and health effects, and how the concept of tunnel states can be used to account for transition rates that depend on the time spent in a state. The applied example shows that the continuous-time model yields more accurate results than the discrete-time model but does not require much computation time and is easily implemented. In conclusion, continuous-time Markov models are a feasible alternative to cohort analysis and can offer several theoretical and practical advantages.

  7. Temporal event structure and timing in schizophrenia: preserved binding in a longer "now".

    Science.gov (United States)

    Martin, Brice; Giersch, Anne; Huron, Caroline; van Wassenhove, Virginie

    2013-01-01

    Patients with schizophrenia experience a loss of temporal continuity or subjective fragmentation along the temporal dimension. Here, we develop the hypothesis that impaired temporal awareness results from a perturbed structuring of events in time-i.e., canonical neural dynamics. To address this, 26 patients and their matched controls took part in two psychophysical studies using desynchronized audiovisual speech. Two tasks were used and compared: first, an identification task testing for multisensory binding impairments in which participants reported what they heard while looking at a speaker's face; in a second task, we tested the perceived simultaneity of the same audiovisual speech stimuli. In both tasks, we used McGurk fusion and combination that are classic ecologically valid multisensory illusions. First, and contrary to previous reports, our results show that patients do not significantly differ from controls in their rate of illusory reports. Second, the illusory reports of patients in the identification task were more sensitive to audiovisual speech desynchronies than those of controls. Third, and surprisingly, patients considered audiovisual speech to be synchronized for longer delays than controls. As such, the temporal tolerance profile observed in a temporal judgement task was less of a predictor for sensory binding in schizophrenia than for that obtained in controls. We interpret our results as an impairment of temporal event structuring in schizophrenia which does not specifically affect sensory binding operations but rather, the explicit access to timing information associated here with audiovisual speech processing. Our findings are discussed in the context of curent neurophysiological frameworks for the binding and the structuring of sensory events in time. Copyright © 2012 Elsevier Ltd. All rights reserved.

  8. Quantifying the predictive accuracy of time-to-event models in the presence of competing risks.

    Science.gov (United States)

    Schoop, Rotraut; Beyersmann, Jan; Schumacher, Martin; Binder, Harald

    2011-02-01

    Prognostic models for time-to-event data play a prominent role in therapy assignment, risk stratification and inter-hospital quality assurance. The assessment of their prognostic value is vital not only for responsible resource allocation, but also for their widespread acceptance. The additional presence of competing risks to the event of interest requires proper handling not only on the model building side, but also during assessment. Research into methods for the evaluation of the prognostic potential of models accounting for competing risks is still needed, as most proposed methods measure either their discrimination or calibration, but do not examine both simultaneously. We adapt the prediction error proposal of Graf et al. (Statistics in Medicine 1999, 18, 2529–2545) and Gerds and Schumacher (Biometrical Journal 2006, 48, 1029–1040) to handle models with competing risks, i.e. more than one possible event type, and introduce a consistent estimator. A simulation study investigating the behaviour of the estimator in small sample size situations and for different levels of censoring together with a real data application follows.

  9. Time-to-event methodology improved statistical evaluation in register-based health services research.

    Science.gov (United States)

    Bluhmki, Tobias; Bramlage, Peter; Volk, Michael; Kaltheuner, Matthias; Danne, Thomas; Rathmann, Wolfgang; Beyersmann, Jan

    2017-02-01

    Complex longitudinal sampling and the observational structure of patient registers in health services research are associated with methodological challenges regarding data management and statistical evaluation. We exemplify common pitfalls and want to stimulate discussions on the design, development, and deployment of future longitudinal patient registers and register-based studies. For illustrative purposes, we use data from the prospective, observational, German DIabetes Versorgungs-Evaluation register. One aim was to explore predictors for the initiation of a basal insulin supported therapy in patients with type 2 diabetes initially prescribed to glucose-lowering drugs alone. Major challenges are missing mortality information, time-dependent outcomes, delayed study entries, different follow-up times, and competing events. We show that time-to-event methodology is a valuable tool for improved statistical evaluation of register data and should be preferred to simple case-control approaches. Patient registers provide rich data sources for health services research. Analyses are accompanied with the trade-off between data availability, clinical plausibility, and statistical feasibility. Cox' proportional hazards model allows for the evaluation of the outcome-specific hazards, but prediction of outcome probabilities is compromised by missing mortality information. Copyright © 2016 Elsevier Inc. All rights reserved.

  10. Event timing in associative learning: from biochemical reaction dynamics to behavioural observations.

    Directory of Open Access Journals (Sweden)

    Ayse Yarali

    Full Text Available Associative learning relies on event timing. Fruit flies for example, once trained with an odour that precedes electric shock, subsequently avoid this odour (punishment learning; if, on the other hand the odour follows the shock during training, it is approached later on (relief learning. During training, an odour-induced Ca(++ signal and a shock-induced dopaminergic signal converge in the Kenyon cells, synergistically activating a Ca(++-calmodulin-sensitive adenylate cyclase, which likely leads to the synaptic plasticity underlying the conditioned avoidance of the odour. In Aplysia, the effect of serotonin on the corresponding adenylate cyclase is bi-directionally modulated by Ca(++, depending on the relative timing of the two inputs. Using a computational approach, we quantitatively explore this biochemical property of the adenylate cyclase and show that it can generate the effect of event timing on associative learning. We overcome the shortage of behavioural data in Aplysia and biochemical data in Drosophila by combining findings from both systems.

  11. Integrated survival analysis using an event-time approach in a Bayesian framework.

    Science.gov (United States)

    Walsh, Daniel P; Dreitz, Victoria J; Heisey, Dennis M

    2015-02-01

    Event-time or continuous-time statistical approaches have been applied throughout the biostatistical literature and have led to numerous scientific advances. However, these techniques have traditionally relied on knowing failure times. This has limited application of these analyses, particularly, within the ecological field where fates of marked animals may be unknown. To address these limitations, we developed an integrated approach within a Bayesian framework to estimate hazard rates in the face of unknown fates. We combine failure/survival times from individuals whose fates are known and times of which are interval-censored with information from those whose fates are unknown, and model the process of detecting animals with unknown fates. This provides the foundation for our integrated model and permits necessary parameter estimation. We provide the Bayesian model, its derivation, and use simulation techniques to investigate the properties and performance of our approach under several scenarios. Lastly, we apply our estimation technique using a piece-wise constant hazard function to investigate the effects of year, age, chick size and sex, sex of the tending adult, and nesting habitat on mortality hazard rates of the endangered mountain plover (Charadrius montanus) chicks. Traditional models were inappropriate for this analysis because fates of some individual chicks were unknown due to failed radio transmitters. Simulations revealed biases of posterior mean estimates were minimal (≤ 4.95%), and posterior distributions behaved as expected with RMSE of the estimates decreasing as sample sizes, detection probability, and survival increased. We determined mortality hazard rates for plover chicks were highest at birth weights and/or whose nest was within agricultural habitats. Based on its performance, our approach greatly expands the range of problems for which event-time analyses can be used by eliminating the need for having completely known fate data.

  12. Integrated survival analysis using an event-time approach in a Bayesian framework

    Science.gov (United States)

    Walsh, Daniel P.; Dreitz, VJ; Heisey, Dennis M.

    2015-01-01

    Event-time or continuous-time statistical approaches have been applied throughout the biostatistical literature and have led to numerous scientific advances. However, these techniques have traditionally relied on knowing failure times. This has limited application of these analyses, particularly, within the ecological field where fates of marked animals may be unknown. To address these limitations, we developed an integrated approach within a Bayesian framework to estimate hazard rates in the face of unknown fates. We combine failure/survival times from individuals whose fates are known and times of which are interval-censored with information from those whose fates are unknown, and model the process of detecting animals with unknown fates. This provides the foundation for our integrated model and permits necessary parameter estimation. We provide the Bayesian model, its derivation, and use simulation techniques to investigate the properties and performance of our approach under several scenarios. Lastly, we apply our estimation technique using a piece-wise constant hazard function to investigate the effects of year, age, chick size and sex, sex of the tending adult, and nesting habitat on mortality hazard rates of the endangered mountain plover (Charadrius montanus) chicks. Traditional models were inappropriate for this analysis because fates of some individual chicks were unknown due to failed radio transmitters. Simulations revealed biases of posterior mean estimates were minimal (≤ 4.95%), and posterior distributions behaved as expected with RMSE of the estimates decreasing as sample sizes, detection probability, and survival increased. We determined mortality hazard rates for plover chicks were highest at birth weights and/or whose nest was within agricultural habitats. Based on its performance, our approach greatly expands the range of problems for which event-time analyses can be used by eliminating the need for having completely known fate data.

  13. Advances and Challenges in Space-time Modelling of Natural Events

    CERN Document Server

    Porcu, Emilio; Schlather, Martin

    2012-01-01

    This book arises as the natural continuation of the International Spring School "Advances and Challenges in Space-Time modelling of Natural Events," which took place in Toledo (Spain) in March 2010. This Spring School above all focused on young researchers (Master students, PhD students and post-doctoral researchers) in academics, extra-university research and the industry who are interested in learning about recent developments, new methods and applications in spatial statistics and related areas, and in exchanging ideas and findings with colleagues.

  14. Phase II Trials for Heterogeneous Patient Populations with a Time-to-Event Endpoint.

    Science.gov (United States)

    Jung, Sin-Ho

    2017-07-01

    In this paper, we consider a single-arm phase II trial with a time-to-event end-point. We assume that the study population has multiple subpopulations with different prognosis, but the study treatment is expected to be similarly efficacious across the subpopulations. We review a stratified one-sample log-rank test and present its sample size calculation method under some practical design settings. Our sample size method requires specification of the prevalence of subpopulations. We observe that the power of the resulting sample size is not very sensitive to misspecification of the prevalence.

  15. Clinical usefulness and feasibility of time-frequency analysis of chemosensory event-related potentials.

    Science.gov (United States)

    Huart, C; Rombaux, Ph; Hummel, T; Mouraux, A

    2013-09-01

    The clinical usefulness of olfactory event-related brain potentials (OERPs) to assess olfactory function is limited by the relatively low signal-to-noise ratio of the responses identified using conventional time-domain averaging. Recently, it was shown that time-frequency analysis of the obtained EEG signals can markedly improve the signal-to-noise ratio of OERPs in healthy controls, because it enhances both phase-locked and non phase-locked EEG responses. The aim of the present study was to investigate the clinical usefulness of this approach and evaluate its feasibility in a clinical setting. We retrospectively analysed EEG recordings obtained from 45 patients (15 anosmic, 15 hyposmic and 15 normos- mic). The responses to olfactory stimulation were analysed using conventional time-domain analysis and joint time-frequency analysis. The ability of the two methods to discriminate between anosmic, hyposmic and normosmic patients was assessed using a Receiver Operating Characteristic analysis. The discrimination performance of OERPs identified using conventional time-domain averaging was poor. In contrast, the discrimination performance of the EEG response identified in the time-frequency domain was relatively high. Furthermore, we found a significant correlation between the magnitude of this response and the psychophysical olfactory score. Time-frequency analysis of the EEG responses to olfactory stimulation could be used as an effective and reliable diagnostic tool for the objective clinical evaluation of olfactory function in patients.

  16. Implementation of Tree and Butterfly Barriers with Optimistic Time Management Algorithms for Discrete Event Simulation

    Science.gov (United States)

    Rizvi, Syed S.; Shah, Dipali; Riasat, Aasia

    The Time Wrap algorithm [3] offers a run time recovery mechanism that deals with the causality errors. These run time recovery mechanisms consists of rollback, anti-message, and Global Virtual Time (GVT) techniques. For rollback, there is a need to compute GVT which is used in discrete-event simulation to reclaim the memory, commit the output, detect the termination, and handle the errors. However, the computation of GVT requires dealing with transient message problem and the simultaneous reporting problem. These problems can be dealt in an efficient manner by the Samadi's algorithm [8] which works fine in the presence of causality errors. However, the performance of both Time Wrap and Samadi's algorithms depends on the latency involve in GVT computation. Both algorithms give poor latency for large simulation systems especially in the presence of causality errors. To improve the latency and reduce the processor ideal time, we implement tree and butterflies barriers with the optimistic algorithm. Our analysis shows that the use of synchronous barriers such as tree and butterfly with the optimistic algorithm not only minimizes the GVT latency but also minimizes the processor idle time.

  17. Event Detection Intelligent Camera: Demonstration of flexible, real-time data taking and processing

    Energy Technology Data Exchange (ETDEWEB)

    Szabolics, Tamás, E-mail: szabolics.tamas@wigner.mta.hu; Cseh, Gábor; Kocsis, Gábor; Szepesi, Tamás; Zoletnik, Sándor

    2015-10-15

    Highlights: • We present EDICAM's operation principles description. • Firmware tests results. • Software test results. • Further developments. - Abstract: An innovative fast camera (EDICAM – Event Detection Intelligent CAMera) was developed by MTA Wigner RCP in the last few years. This new concept was designed for intelligent event driven processing to be able to detect predefined events and track objects in the plasma. The camera provides a moderate frame rate of 400 Hz at full frame resolution (1280 × 1024), and readout of smaller region of interests can be done in the 1–140 kHz range even during exposure of the full image. One of the most important advantages of this hardware is a 10 Gbit/s optical link which ensures very fast communication and data transfer between the PC and the camera, enabling two level of processing: primitive algorithms in the camera hardware and high-level processing in the PC. This camera hardware has successfully proven to be able to monitoring the plasma in several fusion devices for example at ASDEX Upgrade, KSTAR and COMPASS with the first version of firmware. A new firmware and software package is under development. It allows to detect predefined events in real time and therefore the camera is capable to change its own operation or to give warnings e.g. to the safety system of the experiment. The EDICAM system can handle a huge amount of data (up to TBs) with high data rate (950 MB/s) and will be used as the central element of the 10 camera overview video diagnostic system of Wendenstein 7-X (W7-X) stellarator. This paper presents key elements of the newly developed built-in intelligence stressing the revolutionary new features and the results of the test of the different software elements.

  18. Multi-channel control circuit for real-time control of events in Aditya tokamak

    Energy Technology Data Exchange (ETDEWEB)

    Edappala, Praveenlal, E-mail: praveen@ipr.res.in; Shah, Minsha; Rajpal, Rachana; Tanna, R.L.; Ghosh, Joydeep; Chattopadhyay, P.K.; Jha, R.

    2016-11-15

    Highlights: • Low cost microcontroller based control circuit. • The control hardware can be programmed/configured very easily for different applications. • Microcontroller programming is done in assembly language so that precise timing can be achieved with micro seconds resolution. • Successful implementation of this circuit in noisy tokamak environment. • Efficient noise and burst elimination. • Can be integrated in to the other subsystems. • Low cost solution for implementing feedback control in small and medium size tokamaks and other experiments requiring feedback control. - Abstract: Tokamak plasma is prone to many random events having potential for causing severe damages to the machine, such as disruptions, production and elimination of high-energy runaway electrons etc. These events can be mitigated by obtaining pre-cursor signal leading to these events and then taking proper measures just before their onset to avoid their happenings, like disruptions can be mitigated by massive gas injection or putting a bias voltage on an electrode placed inside the plasma, the runaways can be mitigated by gas injection and by applying specific magnetic fields. Hence for real time control of these events, the pre-cursors should be electronically recorded and the mitigation techniques should be initiated by sending triggers to their individual operational systems. To implement these methodologies of real-time controlling of events in Aditya Tokamak, a low cost multi-channel Micro-Controller based timing circuit is designed and developed in-house. This circuit first compares the precursor signals fed into it with the pre-set values and gives a trigger output whenever the signals overshoot the pre-set values. The circuit readies itself for operation along with start of the tokamak discharge and waits up to an initial pre-determined delay and then initiates a trigger at the time of overshooting of precursor signal. The circuit is fully integrated and assembled in

  19. Exploring the relationship between analgesic event rate and pain intensity in kidney stone surgery: A Repeated Time to Event Pilot Study

    DEFF Research Database (Denmark)

    Juul, Rasmus Vestergaard; Pedersen, Katja Venborg; Christrup, Lona Louring

    III-60 Rasmus Juul Exploring the relationship between analgesic event rate and pain intensity in kidney stone surgery: A Repeated Time to Event Pilot Study RV Juul(1), KV Pedersen(2, 4), LL Christrup(1), AE Olesen(1, 3), AM Drewes(3), PJS Osther(4), TM Lund(1) 1) Department of Drug Design...... a relationship with pain intensity has not yet been established. The aim of this pilot study was to discuss how best to investigate the relationship between RTTE hazard of analgesic events and pain intensity in postoperative pain. Methods: Data was available from 44 patients undergoing kidney stone surgery......). Gompertz and exponential distribution models were evaluated. Post-hoc linear mixed effect modelling was performed between estimated RTTE hazard and observed NRS using the lme4 package in R (3). Results: A Gompertz distribution model adequately described data, with a baseline event rate of 0.64h-1 (RSE 25...

  20. The past, present, and future of the U.S. electric power sector: Examining regulatory changes using multivariate time series approaches

    Science.gov (United States)

    Binder, Kyle Edwin

    The U.S. energy sector has undergone continuous change in the regulatory, technological, and market environments. These developments show no signs of slowing. Accordingly, it is imperative that energy market regulators and participants develop a strong comprehension of market dynamics and the potential implications of their actions. This dissertation contributes to a better understanding of the past, present, and future of U.S. energy market dynamics and interactions with policy. Advancements in multivariate time series analysis are employed in three related studies of the electric power sector. Overall, results suggest that regulatory changes have had and will continue to have important implications for the electric power sector. The sector, however, has exhibited adaptability to past regulatory changes and is projected to remain resilient in the future. Tests for constancy of the long run parameters in a vector error correction model are applied to determine whether relationships among coal inventories in the electric power sector, input prices, output prices, and opportunity costs have remained constant over the past 38 years. Two periods of instability are found, the first following railroad deregulation in the U.S. and the second corresponding to a number of major regulatory changes in the electric power and natural gas sectors. Relationships among Renewable Energy Credit prices, electricity prices, and natural gas prices are estimated using a vector error correction model. Results suggest that Renewable Energy Credit prices do not completely behave as previously theorized in the literature. Potential reasons for the divergence between theory and empirical evidence are the relative immaturity of current markets and continuous institutional intervention. Potential impacts of future CO2 emissions reductions under the Clean Power Plan on economic and energy sector activity are estimated. Conditional forecasts based on an outlined path for CO2 emissions are

  1. Twitter data analysis: temporal and term frequency analysis with real-time event

    Science.gov (United States)

    Yadav, Garima; Joshi, Mansi; Sasikala, R.

    2017-11-01

    From the past few years, World Wide Web (www) has become a prominent and huge source for user generated content and opinionative data. Among various social media, Twitter gained popularity as it offers a fast and effective way of sharing users’ perspective towards various critical and other issues in different domain. As the data is hugely generated on cloud, it has opened doors for the researchers in the field of data science and analysis. There are various domains such as ‘Political’ domain, ‘Entertainment’ domain and ‘Business’ domain. Also there are various APIs that Twitter provides for developers 1) Search API, focus on the old tweets 2) Rest API, focuses on user details and allow to collect the user profile, friends and followers 3) Streaming API, which collects details like tweets, hashtags, geo locations. In our work we are accessing Streaming API in order to fetch real-time tweets for the dynamic happening event. For this we are focusing on ‘Entertainment’ domain especially ‘Sports’ as IPL-T20 is currently the trending on-going event. We are collecting these numerous amounts of tweets and storing them in MongoDB database where the tweets are stored in JSON document format. On this document we are performing time-series analysis and term frequency analysis using different techniques such as filtering, information extraction for text-mining that fulfils our objective of finding interesting moments for temporal data in the event and finding the ranking among the players or the teams based on popularity which helps people in understanding key influencers on the social media platform.

  2. Perceiving control over aversive and fearful events can alter how we experience those events: an investigation of time perception in spider-fearful individuals

    Directory of Open Access Journals (Sweden)

    Simona eBuetti

    2012-09-01

    Full Text Available We used a time perception task to study the effects of the subjective experience of control on emotion and cognitive processing. This task is uniquely sensitive to the emotionality of the stimuli: high-arousing negative stimuli are perceived as lasting longer than high-arousing positive events, while the opposite pattern is observed for low-arousing stimuli. We evaluated the temporal distortions of emotionally-charged events in non-anxious (Experiments 1 and 5 and spider-fearful individuals (Experiments 2-4. Participants were shown images of varying durations between 400 and 1600 ms and were asked to report if the perceived duration of the image seemed closer to a short (400 ms or to a long (1600 ms standard duration. Our results replicate previous findings showing that the emotional content of the image modulated the perceived duration of that image. More importantly, we studied whether giving participants the illusion that they have some control over the emotional content of the images could eliminate this temporal distortion. Results confirmed this hypothesis, even though our participant population was composed of highly-reactive emotional individuals (spider fearful facing fear-related images (spiders. Further, we also showed that under conditions of little-to-no control, spider-fearful individuals perceive temporal distortions in a distinct manner from non-anxious participants: the duration of events was entirely determined by the valence of the events, rather than by the typical valence x arousal interaction. That is, spider-fearful participants perceived negative events as lasting longer than positive events, regardless of their level of arousal. Finally, we also showed that under conditions of cognitive dissonance, control can eliminate temporal distortions of low arousal events, but not of high-arousing events, providing an important boundary condition to the otherwise positive effects of control on time estimation.

  3. NASA Climate Days: Promoting Climate Literacy One Ambassador and One Event at a Time

    Science.gov (United States)

    Weir, H. M.; Lewis, P. M.; Chambers, L. H.; Millham, R. A.; Richardson, A.

    2012-12-01

    presentations from the training, along with downloadable Climate Day Kit materials. Utilizing informal educators from museums, aquariums, libraries and other similar venues allow the hard-to-understand, sometimes-controversial, topic of climate change to be presented to the public in tailored events that suit an individual community's needs. Included in the process of scheduling and executing these climate events, the Ambassadors participate in virtual conferences to discuss progress, to ensure proper evaluation and to allow ample time for questions from the trainers and scientists. This ensures an accurate stream of information from the scientist to the public in a fashion that can be understood and digested by the layperson, helping them to make better-informed decisions about societal issues related to global climate change. Through a series of local Climate Day events, it is hoped that the public will have the opportunity to have first hand experience with the topic of climate change, leaving with a better understanding of its scientific basis. Outcome: This paper will summarize the various methods and strategies used in the Climate Day training events. A discussion of methods that work and those that do not for informal education will help provide a better understanding of the challenges faced in educating the public on such a controversial and hard-to-understand topic.

  4. Timing of Mississippi Valley-type mineralization: Relation to Appalachian orogenic events

    Energy Technology Data Exchange (ETDEWEB)

    Kesler, S.E.; van der Pluijm, B.A. (Univ. of Michigan, Ann Arbor (USA))

    1990-11-01

    Although Mississippi Valley-type deposits in Lower Ordovician carbonate rocks of the Appalachian orogen are commonly interpreted to have been precipitated by basinal brines, the timing of brine migration remains poorly known. Late Paleozoic K-Ar isotopic ages on authigenic K-feldspar, which is widespread in Appalachian carbonate rocks, as well as evidence of paleomagnetic overprints of similar age, have focused attention on the possibility that these Mississippi Valley-type deposits formed as a result of late Paleozoic deformation. Geologic and geochemical similarities among most of these deposits, from Georgia to Newfoundland, including unusually high sphalerite/galena ratios, isotopically heavy sulfur, and relatively nonradiogenic lead, suggest that they are coeval. Sphalerite sand that parallels host-rock layering in many of the deposits indicates that mineralization occurred before regional deformation. Although the late Paleozoic age of deformation in the southern Appalachians provides little constraint on the age of Mississippi Valley-type mineralization, deformation of these deposits in the Newfoundland Appalachians is early to middle Paleozoic in age. Thus, if Ordovician-hosted, Appalachian Mississippi Valley-type deposits are coeval, they must have formed by middle Paleozoic time and cannot be the product of a late Paleozoic fluid-expulsion event. This hypothesis has important implications for basin evolution, fluid events, and remagnetization in the Appalachians.

  5. Surrogate marker analysis in cancer clinical trials through time-to-event mediation techniques.

    Science.gov (United States)

    Vandenberghe, Sjouke; Duchateau, Luc; Slaets, Leen; Bogaerts, Jan; Vansteelandt, Stijn

    2017-01-01

    The meta-analytic approach is the gold standard for validation of surrogate markers, but has the drawback of requiring data from several trials. We refine modern mediation analysis techniques for time-to-event endpoints and apply them to investigate whether pathological complete response can be used as a surrogate marker for disease-free survival in the EORTC 10994/BIG 1-00 randomised phase 3 trial in which locally advanced breast cancer patients were randomised to either taxane or anthracycline based neoadjuvant chemotherapy. In the mediation analysis, the treatment effect is decomposed into an indirect effect via pathological complete response and the remaining direct effect. It shows that only 4.2% of the treatment effect on disease-free survival after five years is mediated by the treatment effect on pathological complete response. There is thus no evidence from our analysis that pathological complete response is a valuable surrogate marker to evaluate the effect of taxane versus anthracycline based chemotherapies on progression free survival of locally advanced breast cancer patients. The proposed analysis strategy is broadly applicable to mediation analyses of time-to-event endpoints, is easy to apply and outperforms existing strategies in terms of precision as well as robustness against model misspecification.

  6. R and D on a Fast LXe TPC with real-time event reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Dussoni, S., E-mail: simeone.dussoni@pi.infn.it [INFN Sezione di Pisa, Largo B. Pontecorvo 3, 56127 Pisa (Italy); Baldini, A. [INFN Sezione di Pisa, Largo B. Pontecorvo 3, 56127 Pisa (Italy); Galli, L. [INFN Sezione di Pisa, Largo B. Pontecorvo 3, 56127 Pisa (Italy); Paul Scherrer Institute PSI, CH-5232 Villigen (Switzerland); Cerri, C.; Grassi, M. [INFN Sezione di Pisa, Largo B. Pontecorvo 3, 56127 Pisa (Italy); Papa, A. [Paul Scherrer Institute PSI, CH-5232 Villigen (Switzerland); Signorelli, G. [INFN Sezione di Pisa, Largo B. Pontecorvo 3, 56127 Pisa (Italy)

    2013-12-21

    The FOXFIRE project (Feasibility Of a Xenon detector with Front-end for Ionization Real-time Extraction) aims at the realization of a Liquid Xenon TPC optimized for high rate particle physics experiments, in particular in the field of rare event searches, with particles in the 10–100 MeV energy range. Liquid Xenon has several attractive properties to be exploited resulting in superior time and energy resolution, by using the scintillation light readout with suitable photo-detectors. A novel approach with a complementary TPC readout scheme can improve the space resolution to a level of a few hundred microns. We are studying both the feasibility of a light readout with higher granularity by means of Silicon PhotoMultipliers optimized for the Xenon emission spectrum as well as on an innovative micro-fabricated device capable of charge multiplication in liquid phase. The detector will be equipped with a readout electronics capable of online reconstruction of events, allowing the detector to sustain a high rate of interactions.

  7. Development of time dependent safety analysis code for plasma anomaly events in fusion reactors

    International Nuclear Information System (INIS)

    Honda, Takuro; Okazaki, Takashi; Bartels, H.W.; Uckan, N.A.; Seki, Yasushi.

    1997-01-01

    A safety analysis code SAFALY has been developed to analyze plasma anomaly events in fusion reactors, e.g., a loss of plasma control. The code is a hybrid code comprising a zero-dimensional plasma dynamics and a one-dimensional thermal analysis of in-vessel components. The code evaluates the time evolution of plasma parameters and temperature distributions of in-vessel components. As the plasma-safety interface model, we proposed a robust plasma physics model taking into account updated data for safety assessment. For example, physics safety guidelines for beta limit, density limit and H-L mode confinement transition threshold power, etc. are provided in the model. The model of the in-vessel components are divided into twenty temperature regions in the poloidal direction taking account of radiative heat transfer between each surface of each region. This code can also describe the coolant behavior under hydraulic accidents with the results by hydraulics code and treat vaporization (sublimation) from plasma facing components (PFCs). Furthermore, the code includes the model of impurity transport form PFCs by using a transport probability and a time delay. Quantitative analysis based on the model is possible for a scenario of plasma passive shutdown. We examined the possibility of the code as a safety analysis code for plasma anomaly events in fusion reactors and had a prospect that it would contribute to the safety analysis of the International Thermonuclear Experimental Reactor (ITER). (author)

  8. Replica analysis of overfitting in regression models for time-to-event data

    Science.gov (United States)

    Coolen, A. C. C.; Barrett, J. E.; Paga, P.; Perez-Vicente, C. J.

    2017-09-01

    Overfitting, which happens when the number of parameters in a model is too large compared to the number of data points available for determining these parameters, is a serious and growing problem in survival analysis. While modern medicine presents us with data of unprecedented dimensionality, these data cannot yet be used effectively for clinical outcome prediction. Standard error measures in maximum likelihood regression, such as p-values and z-scores, are blind to overfitting, and even for Cox’s proportional hazards model (the main tool of medical statisticians), one finds in literature only rules of thumb on the number of samples required to avoid overfitting. In this paper we present a mathematical theory of overfitting in regression models for time-to-event data, which aims to increase our quantitative understanding of the problem and provide practical tools with which to correct regression outcomes for the impact of overfitting. It is based on the replica method, a statistical mechanical technique for the analysis of heterogeneous many-variable systems that has been used successfully for several decades in physics, biology, and computer science, but not yet in medical statistics. We develop the theory initially for arbitrary regression models for time-to-event data, and verify its predictions in detail for the popular Cox model.

  9. Big Data Toolsets to Pharmacometrics: Application of Machine Learning for Time-to-Event Analysis.

    Science.gov (United States)

    Gong, Xiajing; Hu, Meng; Zhao, Liang

    2018-05-01

    Additional value can be potentially created by applying big data tools to address pharmacometric problems. The performances of machine learning (ML) methods and the Cox regression model were evaluated based on simulated time-to-event data synthesized under various preset scenarios, i.e., with linear vs. nonlinear and dependent vs. independent predictors in the proportional hazard function, or with high-dimensional data featured by a large number of predictor variables. Our results showed that ML-based methods outperformed the Cox model in prediction performance as assessed by concordance index and in identifying the preset influential variables for high-dimensional data. The prediction performances of ML-based methods are also less sensitive to data size and censoring rates than the Cox regression model. In conclusion, ML-based methods provide a powerful tool for time-to-event analysis, with a built-in capacity for high-dimensional data and better performance when the predictor variables assume nonlinear relationships in the hazard function. © 2018 The Authors. Clinical and Translational Science published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

  10. Discrete events simulation of a route with traffic lights through automated control in real time

    Directory of Open Access Journals (Sweden)

    Rodrigo César Teixeira Baptista

    2013-03-01

    Full Text Available This paper presents the integration and communication in real-time of a discrete event simulation model with an automatic control system. The simulation model of an intersection with roads having traffic lights was built in the Arena environment. The integration and communication have been made via network, and the control system was operated by a programmable logic controller. Scenarios were simulated for the free, regular and congested traffic situations. The results showed the average number of vehicles that entered in the system and that were retained and also the total average time of the crossing of the vehicles on the road. In general, the model allowed evaluating the behavior of the traffic in each of the ways and the commands from the controller to activation and deactivation of the traffic lights.

  11. Post-event human decision errors: operator action tree/time reliability correlation

    Energy Technology Data Exchange (ETDEWEB)

    Hall, R E; Fragola, J; Wreathall, J

    1982-11-01

    This report documents an interim framework for the quantification of the probability of errors of decision on the part of nuclear power plant operators after the initiation of an accident. The framework can easily be incorporated into an event tree/fault tree analysis. The method presented consists of a structure called the operator action tree and a time reliability correlation which assumes the time available for making a decision to be the dominating factor in situations requiring cognitive human response. This limited approach decreases the magnitude and complexity of the decision modeling task. Specifically, in the past, some human performance models have attempted prediction by trying to emulate sequences of human actions, or by identifying and modeling the information processing approach applicable to the task. The model developed here is directed at describing the statistical performance of a representative group of hypothetical individuals responding to generalized situations.

  12. Post-event human decision errors: operator action tree/time reliability correlation

    International Nuclear Information System (INIS)

    Hall, R.E.; Fragola, J.; Wreathall, J.

    1982-11-01

    This report documents an interim framework for the quantification of the probability of errors of decision on the part of nuclear power plant operators after the initiation of an accident. The framework can easily be incorporated into an event tree/fault tree analysis. The method presented consists of a structure called the operator action tree and a time reliability correlation which assumes the time available for making a decision to be the dominating factor in situations requiring cognitive human response. This limited approach decreases the magnitude and complexity of the decision modeling task. Specifically, in the past, some human performance models have attempted prediction by trying to emulate sequences of human actions, or by identifying and modeling the information processing approach applicable to the task. The model developed here is directed at describing the statistical performance of a representative group of hypothetical individuals responding to generalized situations

  13. TMVA(Toolkit for Multivariate Analysis) new architectures design and implementation.

    CERN Document Server

    Zapata Mesa, Omar Andres

    2016-01-01

    Toolkit for Multivariate Analysis(TMVA) is a package in ROOT for machine learning algorithms for classification and regression of the events in the detectors. In TMVA, we are developing new high level algorithms to perform multivariate analysis as cross validation, hyper parameter optimization, variable importance etc... Almost all the algorithms are expensive and designed to process a huge amount of data. It is very important to implement the new technologies on parallel computing to reduce the processing times.

  14. Modeling time-to-event (survival) data using classification tree analysis.

    Science.gov (United States)

    Linden, Ariel; Yarnold, Paul R

    2017-12-01

    Time to the occurrence of an event is often studied in health research. Survival analysis differs from other designs in that follow-up times for individuals who do not experience the event by the end of the study (called censored) are accounted for in the analysis. Cox regression is the standard method for analysing censored data, but the assumptions required of these models are easily violated. In this paper, we introduce classification tree analysis (CTA) as a flexible alternative for modelling censored data. Classification tree analysis is a "decision-tree"-like classification model that provides parsimonious, transparent (ie, easy to visually display and interpret) decision rules that maximize predictive accuracy, derives exact P values via permutation tests, and evaluates model cross-generalizability. Using empirical data, we identify all statistically valid, reproducible, longitudinally consistent, and cross-generalizable CTA survival models and then compare their predictive accuracy to estimates derived via Cox regression and an unadjusted naïve model. Model performance is assessed using integrated Brier scores and a comparison between estimated survival curves. The Cox regression model best predicts average incidence of the outcome over time, whereas CTA survival models best predict either relatively high, or low, incidence of the outcome over time. Classification tree analysis survival models offer many advantages over Cox regression, such as explicit maximization of predictive accuracy, parsimony, statistical robustness, and transparency. Therefore, researchers interested in accurate prognoses and clear decision rules should consider developing models using the CTA-survival framework. © 2017 John Wiley & Sons, Ltd.

  15. Area-specific information processing in prefrontal cortex during a probabilistic inference task: a multivariate fMRI BOLD time series analysis.

    Directory of Open Access Journals (Sweden)

    Charmaine Demanuele

    Full Text Available Discriminating spatiotemporal stages of information processing involved in complex cognitive processes remains a challenge for neuroscience. This is especially so in prefrontal cortex whose subregions, such as the dorsolateral prefrontal (DLPFC, anterior cingulate (ACC and orbitofrontal (OFC cortices are known to have differentiable roles in cognition. Yet it is much less clear how these subregions contribute to different cognitive processes required by a given task. To investigate this, we use functional MRI data recorded from a group of healthy adults during a "Jumping to Conclusions" probabilistic reasoning task.We used a novel approach combining multivariate test statistics with bootstrap-based procedures to discriminate between different task stages reflected in the fMRI blood oxygenation level dependent signal pattern and to unravel differences in task-related information encoded by these regions. Furthermore, we implemented a new feature extraction algorithm that selects voxels from any set of brain regions that are jointly maximally predictive about specific task stages.Using both the multivariate statistics approach and the algorithm that searches for maximally informative voxels we show that during the Jumping to Conclusions task, the DLPFC and ACC contribute more to the decision making phase comprising the accumulation of evidence and probabilistic reasoning, while the OFC is more involved in choice evaluation and uncertainty feedback. Moreover, we show that in presumably non-task-related regions (temporal cortices all information there was about task processing could be extracted from just one voxel (indicating the unspecific nature of that information, while for prefrontal areas a wider multivariate pattern of activity was maximally informative.We present a new approach to reveal the different roles of brain regions during the processing of one task from multivariate activity patterns measured by fMRI. This method can be a valuable

  16. Type and Timing of Negative Life Events Are Associated with Adolescent Depression

    Directory of Open Access Journals (Sweden)

    Saori Nishikawa

    2018-02-01

    Full Text Available Previous studies have demonstrated an association between negative life events (NLEs in childhood and resilience/posttraumatic growth (PTG with regard to the pathogenesis of major depressive disorder. We hypothesized that the type and timing of NLEs interact to influence mental health in the general youth population. Therefore, the present study aimed to examine the effects of NLE timing and intensity on current depressive symptoms, and to determine the direct and indirect effects of NLEs/resilience on PTG and depression among non-clinical adolescents. Data were collected from 1,038 high-school students across seven high schools in Fukui, Japan, during their freshman and sophomore years (648 boys and 390 girls, mean age = 15.71, SD = 0.524. Respondents completed a set of questionnaires designed to evaluate the type and timing of NLEs, depressive and traumatic symptoms, and PTG. Cluster analysis was used to divide participants into three groups based on outcomes: “cluster 1” (n = 631, for whom depressive scores were significantly lower than other two subgroups (p < 0.05, for both; “cluster 2” (n = 52, for whom levels of current and past perceived stress associated with NLEs were significantly higher than those of the other two subgroups (p < 0.05, for both; “cluster 3” (n = 374, for whom perceived stress at the time of NLE was significantly higher than that of participants in the cluster 1 (p < 0.05 group, but not the cluster 2 group. Our findings indicated that exposure to NLEs at a younger age resulted in stronger negative outcomes and that NLE timing and intensity were associated with PTG and current symptoms of depression. Furthermore, path analysis demonstrated that associations between perceived stress at the time of NLEs were direct and indirect predictors of current depression via PTG and that posttraumatic stress symptom and PTG mediate the association between NLEs/trait-resiliency and current

  17. Applied multivariate statistics with R

    CERN Document Server

    Zelterman, Daniel

    2015-01-01

    This book brings the power of multivariate statistics to graduate-level practitioners, making these analytical methods accessible without lengthy mathematical derivations. Using the open source, shareware program R, Professor Zelterman demonstrates the process and outcomes for a wide array of multivariate statistical applications. Chapters cover graphical displays, linear algebra, univariate, bivariate and multivariate normal distributions, factor methods, linear regression, discrimination and classification, clustering, time series models, and additional methods. Zelterman uses practical examples from diverse disciplines to welcome readers from a variety of academic specialties. Those with backgrounds in statistics will learn new methods while they review more familiar topics. Chapters include exercises, real data sets, and R implementations. The data are interesting, real-world topics, particularly from health and biology-related contexts. As an example of the approach, the text examines a sample from the B...

  18. Serial Spike Time Correlations Affect Probability Distribution of Joint Spike Events.

    Science.gov (United States)

    Shahi, Mina; van Vreeswijk, Carl; Pipa, Gordon

    2016-01-01

    Detecting the existence of temporally coordinated spiking activity, and its role in information processing in the cortex, has remained a major challenge for neuroscience research. Different methods and approaches have been suggested to test whether the observed synchronized events are significantly different from those expected by chance. To analyze the simultaneous spike trains for precise spike correlation, these methods typically model the spike trains as a Poisson process implying that the generation of each spike is independent of all the other spikes. However, studies have shown that neural spike trains exhibit dependence among spike sequences, such as the absolute and relative refractory periods which govern the spike probability of the oncoming action potential based on the time of the last spike, or the bursting behavior, which is characterized by short epochs of rapid action potentials, followed by longer episodes of silence. Here we investigate non-renewal processes with the inter-spike interval distribution model that incorporates spike-history dependence of individual neurons. For that, we use the Monte Carlo method to estimate the full shape of the coincidence count distribution and to generate false positives for coincidence detection. The results show that compared to the distributions based on homogeneous Poisson processes, and also non-Poisson processes, the width of the distribution of joint spike events changes. Non-renewal processes can lead to both heavy tailed or narrow coincidence distribution. We conclude that small differences in the exact autostructure of the point process can cause large differences in the width of a coincidence distribution. Therefore, manipulations of the autostructure for the estimation of significance of joint spike events seem to be inadequate.

  19. Memory for time and place contributes to enhanced confidence in memories for emotional events

    Science.gov (United States)

    Rimmele, Ulrike; Davachi, Lila; Phelps, Elizabeth A.

    2012-01-01

    Emotion strengthens the subjective sense of remembering. However, these confidently remembered emotional memories have not been found be more accurate for some types of contextual details. We investigated whether the subjective sense of recollecting negative stimuli is coupled with enhanced memory accuracy for three specific types of central contextual details using the remember/know paradigm and confidence ratings. Our results indicate that the subjective sense of remembering is indeed coupled with better recollection of spatial location and temporal context. In contrast, we found a double-dissociation between the subjective sense of remembering and memory accuracy for colored dots placed in the conceptual center of negative and neutral scenes. These findings show that the enhanced subjective recollective experience for negative stimuli reliably indicates objective recollection for spatial location and temporal context, but not for other types of details, whereas for neutral stimuli, the subjective sense of remembering is coupled with all the types of details assessed. Translating this finding to flashbulb memories, we found that, over time, more participants correctly remembered the location where they learned about the terrorist attacks on 9/11 than any other canonical feature. Likewise participants’ confidence was higher in their memory for location vs. other canonical features. These findings indicate that the strong recollective experience of a negative event corresponds to an accurate memory for some kinds of contextual details, but not other kinds. This discrepancy provides further evidence that the subjective sense of remembering negative events is driven by a different mechanism than the subjective sense of remembering neutral events. PMID:22642353

  20. Unchanged Levels of Soluble CD14 and IL-6 Over Time Predict Serious Non-AIDS Events in HIV-1-Infected People

    Science.gov (United States)

    Sunil, Meena; Nigalye, Maitreyee; Somasunderam, Anoma; Martinez, Maria Laura; Yu, Xiaoying; Arduino, Roberto C.; Bell, Tanvir K.

    2016-01-01

    Abstract HIV-1-infected persons have increased risk of serious non-AIDS events (SNAEs) despite suppressive antiretroviral therapy. Increased circulating levels of soluble CD14 (sCD14), soluble CD163 (sCD163), and interleukin-6 (IL-6) at a single time point have been associated with SNAEs. However, whether changes in these biomarker levels predict SNAEs in HIV-1-infected persons is unknown. We hypothesized that greater decreases in inflammatory biomarkers would be associated with fewer SNAEs. We identified 39 patients with SNAEs, including major cardiovascular events, end stage renal disease, decompensated cirrhosis, non-AIDS-defining malignancies, and death of unknown cause, and age- and sex-matched HIV-1-infected controls. sCD14, sCD163, and IL-6 were measured at study enrollment (T1) and proximal to the event (T2) or equivalent duration in matched controls. Over ∼34 months, unchanged rather than decreasing levels of sCD14 and IL-6 predicted SNAEs. Older age and current illicit substance abuse, but not HCV coinfection, were associated with SNAEs. In a multivariate analysis, older age, illicit substance use, and unchanged IL-6 levels remained significantly associated with SNAEs. Thus, the trajectories of sCD14 and IL-6 levels predict SNAEs. Interventions to decrease illicit substance use may decrease the risk of SNAEs in HIV-1-infected persons. PMID:27344921

  1. Joint modelling of repeated measurement and time-to-event data: an introductory tutorial.

    Science.gov (United States)

    Asar, Özgür; Ritchie, James; Kalra, Philip A; Diggle, Peter J

    2015-02-01

    The term 'joint modelling' is used in the statistical literature to refer to methods for simultaneously analysing longitudinal measurement outcomes, also called repeated measurement data, and time-to-event outcomes, also called survival data. A typical example from nephrology is a study in which the data from each participant consist of repeated estimated glomerular filtration rate (eGFR) measurements and time to initiation of renal replacement therapy (RRT). Joint models typically combine linear mixed effects models for repeated measurements and Cox models for censored survival outcomes. Our aim in this paper is to present an introductory tutorial on joint modelling methods, with a case study in nephrology. We describe the development of the joint modelling framework and compare the results with those obtained by the more widely used approaches of conducting separate analyses of the repeated measurements and survival times based on a linear mixed effects model and a Cox model, respectively. Our case study concerns a data set from the Chronic Renal Insufficiency Standards Implementation Study (CRISIS). We also provide details of our open-source software implementation to allow others to replicate and/or modify our analysis. The results for the conventional linear mixed effects model and the longitudinal component of the joint models were found to be similar. However, there were considerable differences between the results for the Cox model with time-varying covariate and the time-to-event component of the joint model. For example, the relationship between kidney function as measured by eGFR and the hazard for initiation of RRT was significantly underestimated by the Cox model that treats eGFR as a time-varying covariate, because the Cox model does not take measurement error in eGFR into account. Joint models should be preferred for simultaneous analyses of repeated measurement and survival data, especially when the former is measured with error and the association

  2. Sensitivity Analysis of Per-Protocol Time-to-Event Treatment Efficacy in Randomized Clinical Trials

    Science.gov (United States)

    Gilbert, Peter B.; Shepherd, Bryan E.; Hudgens, Michael G.

    2013-01-01

    Summary Assessing per-protocol treatment effcacy on a time-to-event endpoint is a common objective of randomized clinical trials. The typical analysis uses the same method employed for the intention-to-treat analysis (e.g., standard survival analysis) applied to the subgroup meeting protocol adherence criteria. However, due to potential post-randomization selection bias, this analysis may mislead about treatment efficacy. Moreover, while there is extensive literature on methods for assessing causal treatment effects in compliers, these methods do not apply to a common class of trials where a) the primary objective compares survival curves, b) it is inconceivable to assign participants to be adherent and event-free before adherence is measured, and c) the exclusion restriction assumption fails to hold. HIV vaccine efficacy trials including the recent RV144 trial exemplify this class, because many primary endpoints (e.g., HIV infections) occur before adherence is measured, and nonadherent subjects who receive some of the planned immunizations may be partially protected. Therefore, we develop methods for assessing per-protocol treatment efficacy for this problem class, considering three causal estimands of interest. Because these estimands are not identifiable from the observable data, we develop nonparametric bounds and semiparametric sensitivity analysis methods that yield estimated ignorance and uncertainty intervals. The methods are applied to RV144. PMID:24187408

  3. Spectral analysis of time series of events: effect of respiration on heart rate in neonates

    International Nuclear Information System (INIS)

    Van Drongelen, Wim; Williams, Amber L; Lasky, Robert E

    2009-01-01

    Certain types of biomedical processes such as the heart rate generator can be considered as signals that are sampled by the occurring events, i.e. QRS complexes. This sampling property generates problems for the evaluation of spectral parameters of such signals. First, the irregular occurrence of heart beats creates an unevenly sampled data set which must either be pre-processed (e.g. by using trace binning or interpolation) prior to spectral analysis, or analyzed with specialized methods (e.g. Lomb's algorithm). Second, the average occurrence of events determines the Nyquist limit for the sampled time series. Here we evaluate different types of spectral analysis of recordings of neonatal heart rate. Coupling between respiration and heart rate and the detection of heart rate itself are emphasized. We examine both standard and data adaptive frequency bands of heart rate signals generated by models of coupled oscillators and recorded data sets from neonates. We find that an important spectral artifact occurs due to a mirror effect around the Nyquist limit of half the average heart rate. Further we conclude that the presence of respiratory coupling can only be detected under low noise conditions and if a data-adaptive respiratory band is used

  4. Continuous multivariate exponential extension

    International Nuclear Information System (INIS)

    Block, H.W.

    1975-01-01

    The Freund-Weinman multivariate exponential extension is generalized to the case of nonidentically distributed marginal distributions. A fatal shock model is given for the resulting distribution. Results in the bivariate case and the concept of constant multivariate hazard rate lead to a continuous distribution related to the multivariate exponential distribution (MVE) of Marshall and Olkin. This distribution is shown to be a special case of the extended Freund-Weinman distribution. A generalization of the bivariate model of Proschan and Sullo leads to a distribution which contains both the extended Freund-Weinman distribution and the MVE

  5. Aesthetic appreciation: event-related field and time-frequency analyses.

    Science.gov (United States)

    Munar, Enric; Nadal, Marcos; Castellanos, Nazareth P; Flexas, Albert; Maestú, Fernando; Mirasso, Claudio; Cela-Conde, Camilo J

    2011-01-01

    Improvements in neuroimaging methods have afforded significant advances in our knowledge of the cognitive and neural foundations of aesthetic appreciation. We used magnetoencephalography (MEG) to register brain activity while participants decided about the beauty of visual stimuli. The data were analyzed with event-related field (ERF) and Time-Frequency (TF) procedures. ERFs revealed no significant differences between brain activity related with stimuli rated as "beautiful" and "not beautiful." TF analysis showed clear differences between both conditions 400 ms after stimulus onset. Oscillatory power was greater for stimuli rated as "beautiful" than those regarded as "not beautiful" in the four frequency bands (theta, alpha, beta, and gamma). These results are interpreted in the frame of synchronization studies.

  6. A power filter for the detection of burst events based on time-frequency spectrum estimation

    International Nuclear Information System (INIS)

    Guidi, G M; Cuoco, E; Vicere, A

    2004-01-01

    We propose as a statistic for the detection of bursts in a gravitational wave interferometer the 'energy' of the events estimated with a time-dependent calculation of the spectrum. This statistic has an asymptotic Gaussian distribution with known statistical moments, which makes it possible to perform a uniformly most powerful test (McDonough R N and Whalen A D 1995 Detection of Signals in Noise (New York: Academic)) on the energy mean. We estimate the receiver operating characteristic (ROC, from the same book) of this statistic for different levels of the signal-to-noise ratio in the specific case of a simulated noise having the spectral density expected for Virgo, using test signals taken from a library of possible waveforms emitted during the collapse of the core of type II supernovae

  7. Detecting Forest Disturbance Events from MODIS and Landsat Time Series for the Conterminous United States

    Science.gov (United States)

    Zhang, G.; Ganguly, S.; Saatchi, S. S.; Hagen, S. C.; Harris, N.; Yu, Y.; Nemani, R. R.

    2013-12-01

    Spatial and temporal patterns of forest disturbance and regrowth processes are key for understanding aboveground terrestrial vegetation biomass and carbon stocks at regional-to-continental scales. The NASA Carbon Monitoring System (CMS) program seeks key input datasets, especially information related to impacts due to natural/man-made disturbances in forested landscapes of Conterminous U.S. (CONUS), that would reduce uncertainties in current carbon stock estimation and emission models. This study provides a end-to-end forest disturbance detection framework based on pixel time series analysis from MODIS (Moderate Resolution Imaging Spectroradiometer) and Landsat surface spectral reflectance data. We applied the BFAST (Breaks for Additive Seasonal and Trend) algorithm to the Normalized Difference Vegetation Index (NDVI) data for the time period from 2000 to 2011. A harmonic seasonal model was implemented in BFAST to decompose the time series to seasonal and interannual trend components in order to detect abrupt changes in magnitude and direction of these components. To apply the BFAST for whole CONUS, we built a parallel computing setup for processing massive time-series data using the high performance computing facility of the NASA Earth Exchange (NEX). In the implementation process, we extracted the dominant deforestation events from the magnitude of abrupt changes in both seasonal and interannual components, and estimated dates for corresponding deforestation events. We estimated the recovery rate for deforested regions through regression models developed between NDVI values and time since disturbance for all pixels. A similar implementation of the BFAST algorithm was performed over selected Landsat scenes (all Landsat cloud free data was used to generate NDVI from atmospherically corrected spectral reflectances) to demonstrate the spatial coherence in retrieval layers between MODIS and Landsat. In future, the application of this largely parallel disturbance

  8. Likelihood estimators for multivariate extremes

    KAUST Repository

    Huser, Raphaë l; Davison, Anthony C.; Genton, Marc G.

    2015-01-01

    The main approach to inference for multivariate extremes consists in approximating the joint upper tail of the observations by a parametric family arising in the limit for extreme events. The latter may be expressed in terms of componentwise maxima, high threshold exceedances or point processes, yielding different but related asymptotic characterizations and estimators. The present paper clarifies the connections between the main likelihood estimators, and assesses their practical performance. We investigate their ability to estimate the extremal dependence structure and to predict future extremes, using exact calculations and simulation, in the case of the logistic model.

  9. Likelihood estimators for multivariate extremes

    KAUST Repository

    Huser, Raphaël

    2015-11-17

    The main approach to inference for multivariate extremes consists in approximating the joint upper tail of the observations by a parametric family arising in the limit for extreme events. The latter may be expressed in terms of componentwise maxima, high threshold exceedances or point processes, yielding different but related asymptotic characterizations and estimators. The present paper clarifies the connections between the main likelihood estimators, and assesses their practical performance. We investigate their ability to estimate the extremal dependence structure and to predict future extremes, using exact calculations and simulation, in the case of the logistic model.

  10. Disambiguating past events: Accurate source memory for time and context depends on different retrieval processes.

    Science.gov (United States)

    Persson, Bjorn M; Ainge, James A; O'Connor, Akira R

    2016-07-01

    Current animal models of episodic memory are usually based on demonstrating integrated memory for what happened, where it happened, and when an event took place. These models aim to capture the testable features of the definition of human episodic memory which stresses the temporal component of the memory as a unique piece of source information that allows us to disambiguate one memory from another. Recently though, it has been suggested that a more accurate model of human episodic memory would include contextual rather than temporal source information, as humans' memory for time is relatively poor. Here, two experiments were carried out investigating human memory for temporal and contextual source information, along with the underlying dual process retrieval processes, using an immersive virtual environment paired with a 'Remember-Know' memory task. Experiment 1 (n=28) showed that contextual information could only be retrieved accurately using recollection, while temporal information could be retrieved using either recollection or familiarity. Experiment 2 (n=24), which used a more difficult task, resulting in reduced item recognition rates and therefore less potential for contamination by ceiling effects, replicated the pattern of results from Experiment 1. Dual process theory predicts that it should only be possible to retrieve source context from an event using recollection, and our results are consistent with this prediction. That temporal information can be retrieved using familiarity alone suggests that it may be incorrect to view temporal context as analogous to other typically used source contexts. This latter finding supports the alternative proposal that time since presentation may simply be reflected in the strength of memory trace at retrieval - a measure ideally suited to trace strength interrogation using familiarity, as is typically conceptualised within the dual process framework. Copyright © 2016 Elsevier Inc. All rights reserved.

  11. Multivariate GARCH models

    DEFF Research Database (Denmark)

    Silvennoinen, Annastiina; Teräsvirta, Timo

    This article contains a review of multivariate GARCH models. Most common GARCH models are presented and their properties considered. This also includes nonparametric and semiparametric models. Existing specification and misspecification tests are discussed. Finally, there is an empirical example...

  12. BAYESIAN TECHNIQUES FOR COMPARING TIME-DEPENDENT GRMHD SIMULATIONS TO VARIABLE EVENT HORIZON TELESCOPE OBSERVATIONS

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Junhan; Marrone, Daniel P.; Chan, Chi-Kwan; Medeiros, Lia; Özel, Feryal; Psaltis, Dimitrios, E-mail: junhankim@email.arizona.edu [Department of Astronomy and Steward Observatory, University of Arizona, 933 N. Cherry Avenue, Tucson, AZ 85721 (United States)

    2016-12-01

    The Event Horizon Telescope (EHT) is a millimeter-wavelength, very-long-baseline interferometry (VLBI) experiment that is capable of observing black holes with horizon-scale resolution. Early observations have revealed variable horizon-scale emission in the Galactic Center black hole, Sagittarius A* (Sgr A*). Comparing such observations to time-dependent general relativistic magnetohydrodynamic (GRMHD) simulations requires statistical tools that explicitly consider the variability in both the data and the models. We develop here a Bayesian method to compare time-resolved simulation images to variable VLBI data, in order to infer model parameters and perform model comparisons. We use mock EHT data based on GRMHD simulations to explore the robustness of this Bayesian method and contrast it to approaches that do not consider the effects of variability. We find that time-independent models lead to offset values of the inferred parameters with artificially reduced uncertainties. Moreover, neglecting the variability in the data and the models often leads to erroneous model selections. We finally apply our method to the early EHT data on Sgr A*.

  13. A discrete event simulation model for evaluating time delays in a pipeline network

    Energy Technology Data Exchange (ETDEWEB)

    Spricigo, Deisi; Muggiati, Filipe V.; Lueders, Ricardo; Neves Junior, Flavio [Federal University of Technology of Parana (UTFPR), Curitiba, PR (Brazil)

    2009-07-01

    Currently in the oil industry the logistic chain stands out as a strong candidate to obtain highest profit, since recent studies have pointed out to a cost reduction by adoption of better policies for distribution of oil derivatives, particularly those where pipelines are used to transport products. Although there are models to represent transfers of oil derivatives in pipelines, they are quite complex and computationally burden. In this paper, we are interested on models that are less detailed in terms of fluid dynamics but provide more information about operational decisions in a pipeline network. We propose a discrete event simulation model in ARENA that allows simulating a pipeline network based on average historical data. Time delays for transferring different products can be evaluated through different routes. It is considered that transport operations follow a historical behavior and average time delays can thus be estimated within certain bounds. Due to its stochastic nature, time quantities are characterized by average and dispersion measures. This allows comparing different operational scenarios for product transportation. Simulation results are compared to data obtained from a real world pipeline network and different scenarios of production and demand are analyzed. (author)

  14. The influence of hydrologic residence time on lake carbon cycling dynamics following extreme precipitation events

    Science.gov (United States)

    Jacob A. Zwart; Stephen D. Sebestyen; Christopher T. Solomon; Stuart E. Jones

    2016-01-01

    The frequency and magnitude of extreme events are expected to increase in the future, yet little is known about effects of such events on ecosystem structure and function. We examined how extreme precipitation events affect exports of terrestrial dissolved organic carbon (t-DOC) from watersheds to lakes as well as in-lake heterotrophy in three north-temperate lakes....

  15. wayGoo recommender system: personalized recommendations for events scheduling, based on static and real-time information

    Science.gov (United States)

    Thanos, Konstantinos-Georgios; Thomopoulos, Stelios C. A.

    2016-05-01

    wayGoo is a fully functional application whose main functionalities include content geolocation, event scheduling, and indoor navigation. However, significant information about events do not reach users' attention, either because of the size of this information or because some information comes from real - time data sources. The purpose of this work is to facilitate event management operations by prioritizing the presented events, based on users' interests using both, static and real - time data. Through the wayGoo interface, users select conceptual topics that are interesting for them. These topics constitute a browsing behavior vector which is used for learning users' interests implicitly, without being intrusive. Then, the system estimates user preferences and return an events list sorted from the most preferred one to the least. User preferences are modeled via a Naïve Bayesian Network which consists of: a) the `decision' random variable corresponding to users' decision on attending an event, b) the `distance' random variable, modeled by a linear regression that estimates the probability that the distance between a user and each event destination is not discouraging, ` the seat availability' random variable, modeled by a linear regression, which estimates the probability that the seat availability is encouraging d) and the `relevance' random variable, modeled by a clustering - based collaborative filtering, which determines the relevance of each event users' interests. Finally, experimental results show that the proposed system contribute essentially to assisting users in browsing and selecting events to attend.

  16. Statistical methods for the time-to-event analysis of individual participant data from multiple epidemiological studies

    DEFF Research Database (Denmark)

    Thompson, Simon; Kaptoge, Stephen; White, Ian

    2010-01-01

    Meta-analysis of individual participant time-to-event data from multiple prospective epidemiological studies enables detailed investigation of exposure-risk relationships, but involves a number of analytical challenges....

  17. Modeling a typical winter-time dust event over the Arabian Peninsula and the Red Sea

    Directory of Open Access Journals (Sweden)

    S. Kalenderski

    2013-02-01

    Full Text Available We used WRF-Chem, a regional meteorological model coupled with an aerosol-chemistry component, to simulate various aspects of the dust phenomena over the Arabian Peninsula and Red Sea during a typical winter-time dust event that occurred in January 2009. The model predicted that the total amount of emitted dust was 18.3 Tg for the entire dust outburst period and that the two maximum daily rates were ~2.4 Tg day−1 and ~1.5 Tg day−1, corresponding to two periods with the highest aerosol optical depth that were well captured by ground- and satellite-based observations. The model predicted that the dust plume was thick, extensive, and mixed in a deep boundary layer at an altitude of 3–4 km. Its spatial distribution was modeled to be consistent with typical spatial patterns of dust emissions. We utilized MODIS-Aqua and Solar Village AERONET measurements of the aerosol optical depth (AOD to evaluate the radiative impact of aerosols. Our results clearly indicated that the presence of dust particles in the atmosphere caused a significant reduction in the amount of solar radiation reaching the surface during the dust event. We also found that dust aerosols have significant impact on the energy and nutrient balances of the Red Sea. Our results showed that the simulated cooling under the dust plume reached 100 W m−2, which could have profound effects on both the sea surface temperature and circulation. Further analysis of dust generation and its spatial and temporal variability is extremely important for future projections and for better understanding of the climate and ecological history of the Red Sea.

  18. Modeling a typical winter-time dust event over the Arabian Peninsula and the Red Sea

    KAUST Repository

    Kalenderski, Stoitchko

    2013-02-20

    We used WRF-Chem, a regional meteorological model coupled with an aerosol-chemistry component, to simulate various aspects of the dust phenomena over the Arabian Peninsula and Red Sea during a typical winter-time dust event that occurred in January 2009. The model predicted that the total amount of emitted dust was 18.3 Tg for the entire dust outburst period and that the two maximum daily rates were ?2.4 Tg day-1 and ?1.5 Tg day-1, corresponding to two periods with the highest aerosol optical depth that were well captured by ground-and satellite-based observations. The model predicted that the dust plume was thick, extensive, and mixed in a deep boundary layer at an altitude of 3-4 km. Its spatial distribution was modeled to be consistent with typical spatial patterns of dust emissions. We utilized MODIS-Aqua and Solar Village AERONET measurements of the aerosol optical depth (AOD) to evaluate the radiative impact of aerosols. Our results clearly indicated that the presence of dust particles in the atmosphere caused a significant reduction in the amount of solar radiation reaching the surface during the dust event. We also found that dust aerosols have significant impact on the energy and nutrient balances of the Red Sea. Our results showed that the simulated cooling under the dust plume reached 100 W m-2, which could have profound effects on both the sea surface temperature and circulation. Further analysis of dust generation and its spatial and temporal variability is extremely important for future projections and for better understanding of the climate and ecological history of the Red Sea.

  19. Mapping the Recent US Hurricanes Triggered Flood Events in Near Real Time

    Science.gov (United States)

    Shen, X.; Lazin, R.; Anagnostou, E. N.; Wanik, D. W.; Brakenridge, G. R.

    2017-12-01

    Synthetic Aperture Radar (SAR) observations is the only reliable remote sensing data source to map flood inundation during severe weather events. Unfortunately, since state-of-art data processing algorithms cannot meet the automation and quality standard of a near-real-time (NRT) system, quality controlled inundation mapping by SAR currently depends heavily on manual processing, which limits our capability to quickly issue flood inundation maps at global scale. Specifically, most SAR-based inundation mapping algorithms are not fully automated, while those that are automated exhibit severe over- and/or under-detection errors that limit their potential. These detection errors are primarily caused by the strong overlap among the SAR backscattering probability density functions (PDF) of different land cover types. In this study, we tested a newly developed NRT SAR-based inundation mapping system, named Radar Produced Inundation Diary (RAPID), using Sentinel-1 dual polarized SAR data over recent flood events caused by Hurricanes Harvey, Irma, and Maria (2017). The system consists of 1) self-optimized multi-threshold classification, 2) over-detection removal using land-cover information and change detection, 3) under-detection compensation, and 4) machine-learning based correction. Algorithm details are introduced in another poster, H53J-1603. Good agreements were obtained by comparing the result from RAPID with visual interpretation of SAR images and manual processing from Dartmouth Flood Observatory (DFO) (See Figure 1). Specifically, the over- and under-detections that is typically noted in automated methods is significantly reduced to negligible levels. This performance indicates that RAPID can address the automation and accuracy issues of current state-of-art algorithms and has the potential to apply operationally on a number of satellite SAR missions, such as SWOT, ALOS, Sentinel etc. RAPID data can support many applications such as rapid assessment of damage

  20. Assessment of realistic nowcasting lead-times based on predictability analysis of Mediterranean Heavy Precipitation Events

    Science.gov (United States)

    Bech, Joan; Berenguer, Marc

    2014-05-01

    Operational quantitative precipitation forecasts (QPF) are provided routinely by weather services or hydrological authorities, particularly those responsible for densely populated regions of small catchments, such as those typically found in Mediterranean areas prone to flash-floods. Specific rainfall values are used as thresholds for issuing warning levels considering different time frameworks (mid-range, short-range, 24h, 1h, etc.), for example 100 mm in 24h or 60 mm in 1h. There is a clear need to determine how feasible is a specific rainfall value for a given lead-time, in particular for very short range forecasts or nowcasts typically obtained from weather radar observations (Pierce et al 2012). In this study we assess which specific nowcast lead-times can be provided for a number of heavy precipitation events (HPE) that affected Catalonia (NE Spain). The nowcasting system we employed generates QPFs through the extrapolation of rainfall fields observed with weather radar following a Lagrangian approach developed and tested successfully in previous studies (Berenguer et al. 2005, 2011).Then QPFs up to 3h are compared with two quality controlled observational data sets: weather radar quantitative precipitation estimates (QPE) and raingauge data. Several high-impact weather HPE were selected including the 7 September 2005 Llobregat Delta river tornado outbreak (Bech et al. 2007) or the 2 November 2008 supercell tornadic thunderstorms (Bech et al. 2011) both producing, among other effects, local flash floods. In these two events there were torrential rainfall rates (30' amounts exceeding 38.2 and 12.3 mm respectively) and 24h accumulation values above 100 mm. A number of verification scores are used to characterize the evolution of precipitation forecast quality with time, which typically presents a decreasing trend but showing an strong dependence on the selected rainfall threshold and integration period. For example considering correlation factors, 30

  1. New SHRIMP zircon results from Broken Hill: towards robust stratigraphic and event timing

    International Nuclear Information System (INIS)

    Page, R.W.; Stevens, B.P.J.

    1999-01-01

    Full text: Zircon U-Pb SHRIMP geochronology is a powerful means of elucidating geological ages, providing that it is integrated with unequivocal field constraints, and providing that the fundamental assumptions which are behind any isotopic dating methods are geologically validated. In an attempt to better quantify the timing of Broken Hill's complex history and to reduce some current uncertainties, we report initial results from a new U-Pb SHRIMP investigation. This program was planned within the background of our own disparate stratigraphic and structural approaches to Broken Hill geology, and with objectives to (a) benchmark our new age results with those of previous workers as well as our own previous work in the Broken Hill Group, (b) evaluate and test the evidence for reported Archaean basement terrain, (c) date stratigraphic units in the upper parts of the Willyama Supergroup, (d) better constrain the timing of deformational events. Our U-Pb SHRIMP work on zircons from layered paragneisses in the Redan Geophysical Zone near Farmcote was catalysed by Nutman and Ehlers' (1998a) preferred interpretation that these 'strondhjemitic' gneisses represent an original ∼2650 Ma protolith. Our work finds zircon provenance age signatures typical of almost all ca. 1700 Ma metasediments, whether in the Broken Hill Block or other Australian Palaeoproterozoic settings. This therefore suggests that the rocks are not Archaean basement, but are part of a Thackaringa Group package possibly deposited about 1705-1710 Ma ago. New SHRIMP work on the Alma Gneiss provides a magmatic age of 1704±3 Ma, and a minimum stratigraphic age for host Thackaringa Group. This result is within error of our ages for other granitoids (1703±3 Ma, 1704±3 Ma) in the same stratigraphic position near Farmcote. As the Thackaringa Group is no more than 1000-1500 metres thick and includes 1710-1700 Ma detrital zircons, pan of the Alma Gneiss intrusion may well have been shallowly intruded, and akin to

  2. Event- and time-triggered remembering: the impact of attention deficit hyperactivity disorder on prospective memory performance in children.

    Science.gov (United States)

    Talbot, Karley-Dale S; Kerns, Kimberly A

    2014-11-01

    The current study examined prospective memory (PM, both time-based and event-based) and time estimation (TR, a time reproduction task) in children with and without attention deficit hyperactivity disorder (ADHD). This study also investigated the influence of task performance and TR on time-based PM in children with ADHD relative to controls. A sample of 69 children, aged 8 to 13 years, completed the CyberCruiser-II time-based PM task, a TR task, and the Super Little Fisherman event-based PM task. PM performance was compared with children's TR abilities, parental reports of daily prospective memory disturbances (Prospective and Retrospective Memory Questionnaire for Children, PRMQC), and ADHD symptomatology (Conner's rating scales). Children with ADHD scored more poorly on event-based PM, time-based PM, and TR; interestingly, TR did not appear related to performance on time-based PM. In addition, it was found that PRMQC scores and ADHD symptom severity were related to performance on the time-based PM task but not to performance on the event-based PM task. These results provide some limited support for theories that propose a distinction between event-based PM and time-based PM. Copyright © 2014 Elsevier Inc. All rights reserved.

  3. Energy time dispersion of a new class of magnetospheric ion events observed near the Earth's bow shock

    Directory of Open Access Journals (Sweden)

    G. C. Anagnostopoulos

    2000-01-01

    Full Text Available We have analyzed high time resolution (\\geq6 s data during the onset and the decay phase of several energetic (\\geq35 keV ion events observed near the Earth's bow shock by the CCE/AMPTE and IMP-7/8 spacecraft, during times of intense substorm/geomagnetic activity. We found that forward energy dispersion at the onset of events (earlier increase of middle energy ions and/or a delayed fall of the middle energy ion fluxes at the end of events are often evident in high time resolution data. The energy spectra at the onset and the decay of this kind of events show a characteristic hump at middle (50-120 keV energies and the angular distributions display either anisotropic or broad forms. The time scale of energy dispersion in the ion events examined was found to range from several seconds to \\sim1 h depending on the ion energies compared and on the rate of variation of the Interplanetary Magnetic Field (IMF direction. Several canditate processes are discussed to explain the observations and it is suggested that a rigidity dependent transport process of magnetospheric particles within the magnetosheath is most probably responsible for the detection of this new type of near bow shock magnetospheric ion events. The new class of ion events was observed within both the magnetosheath and the upstream region.Key words. Interplanetary physics (energetic particles; planetary bow shocks

  4. Time compression of soil erosion by the effect of largest daily event. A regional analysis of USLE database.

    Science.gov (United States)

    Gonzalez-Hidalgo, J. C.; Batalla, R.; Cerda, A.; de Luis, M.

    2009-04-01

    When Thornes and Brunsden wrote in 1977 "How often one hears the researcher (and no less the undergraduate) complain that after weeks of observation "nothing happened" only to learn that, the day after his departure, a flood caused unprecedent erosion and channel changes!" (Thornes and Brunsden, 1977, p. 57), they focussed on two different problems in geomorphological research: the effects of extreme events and the temporal compression of geomorphological processes. The time compression is one of the main characteristic of erosion processes. It means that an important amount of the total soil eroded is produced in very short temporal intervals, i.e. few events mostly related to extreme events. From magnitude-frequency analysis we know that few events, not necessarily extreme by magnitude, produce high amount of geomorphological work. Last but not least, extreme isolated events are a classical issue in geomorphology by their specific effects, and they are receiving permanent attention, increased at present because of scenarios of global change. Notwithstanding, the time compression of geomorphological processes could be focused not only on the analysis of extreme events and the traditional magnitude-frequency approach, but on new complementary approach based on the effects of largest events. The classical approach define extreme event as a rare event (identified by its magnitude and quantified by some deviation from central value), while we define largest events by the rank, whatever their magnitude. In a previous research on time compression of soil erosion, using USLE soil erosion database (Gonzalez-Hidalgo et al., EGU 2007), we described a relationship between the total amount of daily erosive events recorded by plot and the percentage contribution to total soil erosion of n-largest aggregated daily events. Now we offer a further refined analysis comparing different agricultural regions in USA. To do that we have analyzed data from 594 erosion plots from USLE

  5. A distributed real-time system for event-driven control and dynamic data acquisition on a fusion plasma experiment

    International Nuclear Information System (INIS)

    Sousa, J.; Combo, A.; Batista, A.; Correia, M.; Trotman, D.; Waterhouse, J.; Varandas, C.A.F.

    2000-01-01

    A distributed real-time trigger and timing system, designed in a tree-type topology and implemented in VME and CAMAC versions, has been developed for a magnetic confinement fusion experiment. It provides sub-microsecond time latencies for the transport of small data objects allowing event-driven discharge control with failure counteraction, dynamic pre-trigger sampling and event recording as well as accurate simultaneous triggers and synchronism on all nodes with acceptable optimality and predictability of timeliness. This paper describes the technical characteristics of the hardware components (central unit composed by one or more reflector crates, event and synchronism reflector cards, event and pulse node module, fan-out and fan-in modules) as well as software for both tests and integration on a global data acquisition system. The results of laboratory operation for several configurations and the overall performance of the system are presented and analysed

  6. Real-time detection and classification of anomalous events in streaming data

    Science.gov (United States)

    Ferragut, Erik M.; Goodall, John R.; Iannacone, Michael D.; Laska, Jason A.; Harrison, Lane T.

    2016-04-19

    A system is described for receiving a stream of events and scoring the events based on anomalousness and maliciousness (or other classification). The events can be displayed to a user in user-defined groupings in an animated fashion. The system can include a plurality of anomaly detectors that together implement an algorithm to identify low probability events and detect atypical traffic patterns. The atypical traffic patterns can then be classified as being of interest or not. In one particular example, in a network environment, the classification can be whether the network traffic is malicious or not.

  7. Effects of solar proton events on dayglow observed by the TIMED/SABER satellite

    Science.gov (United States)

    Gao, Hong; Xu, Jiyao; Smith, Anne K.; Chen, Guang-Ming

    2017-07-01

    The effect of solar proton events on the daytime O2 and OH airglows and ozone and atomic oxygen concentrations in the mesosphere is studied using data from the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER). Five events occurred in September 2005, December 2006, March 2012, May 2013, and June 2015 that satisfy two criteria: the maximum proton fluxes are larger than 1000 pfu, and daytime data in the high latitude region are available from SABER. The event in December 2006 is studied in detail, and the effects of all five events are compared in brief. The results indicate that all four parameters in the mesosphere decrease during the events. During the event in 2006, the maximum depletions of O2 and OH dayglow emission rates and ozone and atomic oxygen volume mixing ratios at 70 km are respectively 31.6%, 37.0%, 42.4%, and 38.9%. The effect of the solar proton event changes with latitude, longitude, and altitude. The depletions due to the stronger events are larger on average than those due to the weaker events. The depletions of both dayglow emission rates are weaker than those of ozone and atomic oxygen. The responses of O2 and OH nightglow emissions around their peak altitudes to the SPEs are not as strong and regular as those for dayglow in the mesosphere.

  8. Multivariate refined composite multiscale entropy analysis

    International Nuclear Information System (INIS)

    Humeau-Heurtier, Anne

    2016-01-01

    Multiscale entropy (MSE) has become a prevailing method to quantify signals complexity. MSE relies on sample entropy. However, MSE may yield imprecise complexity estimation at large scales, because sample entropy does not give precise estimation of entropy when short signals are processed. A refined composite multiscale entropy (RCMSE) has therefore recently been proposed. Nevertheless, RCMSE is for univariate signals only. The simultaneous analysis of multi-channel (multivariate) data often over-performs studies based on univariate signals. We therefore introduce an extension of RCMSE to multivariate data. Applications of multivariate RCMSE to simulated processes reveal its better performances over the standard multivariate MSE. - Highlights: • Multiscale entropy quantifies data complexity but may be inaccurate at large scale. • A refined composite multiscale entropy (RCMSE) has therefore recently been proposed. • Nevertheless, RCMSE is adapted to univariate time series only. • We herein introduce an extension of RCMSE to multivariate data. • It shows better performances than the standard multivariate multiscale entropy.

  9. Exercise electrocardiogram in middle-aged and older leisure time sportsmen: 100 exercise tests would be enough to identify one silent myocardial ischemia at risk for cardiac event.

    Science.gov (United States)

    Hupin, David; Edouard, Pascal; Oriol, Mathieu; Laukkanen, Jari; Abraham, Pierre; Doutreleau, Stéphane; Guy, Jean-Michel; Carré, François; Barthélémy, Jean-Claude; Roche, Frédéric; Chatard, Jean-Claude

    2018-04-15

    The importance of exercise electrocardiogram (ECG) has been controversial in the prevention of cardiac events among sportsmen. The aim of this study was to determine the frequency of silent myocardial ischemia (SMI) from an exercise ECG and its relationship with induced coronary angiographic assessment and potentially preventable cardiac events. This prospective cohort study included leisure time asymptomatic sportsmen over 35years old, referred from 2011 to 2014 in the Sports Medicine Unit of the University Hospital of Saint-Etienne. Of the cohort of 1500 sportsmen (1205 men; mean age 50.7±9.4years; physical activity level 32.8±26.8MET-h/week), 951 (63%) had at least one cardiovascular disease (CVD) risk factor. Family history, medical examination and standard resting 12-lead were collected. A total of 163 exercise ECGs (10.9%) were defined as positive, most of them due to SMI (n=129, 8.6%). SMI was an indication for coronary angiography in 23 cases, leading to 17 documented SMIs (1.1%), including 11 significant stenoses requiring revascularization. In multivariate logistic regression analysis, a high risk of CVD (OR=2.65 [CI 95%: 1.33-5.27], p=0.005) and an age >50years (OR=2.71 [CI 95%: 1.65-4.44], p<0.0001) were independently associated with confirmed SMI. The association of positive exercise ECG with significant coronary stenosis was stronger among sportsmen with CVD risk factors and older than 50years. Screening by exercise ECG can lower the risk of cardiac events in middle-aged and older sportsmen. One hundred tests would be enough to detect one silent myocardial ischemia at risk for cardiac event. Copyright © 2017 Elsevier B.V. All rights reserved.

  10. Multivariate Birkhoff interpolation

    CERN Document Server

    Lorentz, Rudolph A

    1992-01-01

    The subject of this book is Lagrange, Hermite and Birkhoff (lacunary Hermite) interpolation by multivariate algebraic polynomials. It unifies and extends a new algorithmic approach to this subject which was introduced and developed by G.G. Lorentz and the author. One particularly interesting feature of this algorithmic approach is that it obviates the necessity of finding a formula for the Vandermonde determinant of a multivariate interpolation in order to determine its regularity (which formulas are practically unknown anyways) by determining the regularity through simple geometric manipulations in the Euclidean space. Although interpolation is a classical problem, it is surprising how little is known about its basic properties in the multivariate case. The book therefore starts by exploring its fundamental properties and its limitations. The main part of the book is devoted to a complete and detailed elaboration of the new technique. A chapter with an extensive selection of finite elements follows as well a...

  11. Applied multivariate statistical analysis

    CERN Document Server

    Härdle, Wolfgang Karl

    2015-01-01

    Focusing on high-dimensional applications, this 4th edition presents the tools and concepts used in multivariate data analysis in a style that is also accessible for non-mathematicians and practitioners.  It surveys the basic principles and emphasizes both exploratory and inferential statistics; a new chapter on Variable Selection (Lasso, SCAD and Elastic Net) has also been added.  All chapters include practical exercises that highlight applications in different multivariate data analysis fields: in quantitative financial studies, where the joint dynamics of assets are observed; in medicine, where recorded observations of subjects in different locations form the basis for reliable diagnoses and medication; and in quantitative marketing, where consumers’ preferences are collected in order to construct models of consumer behavior.  All of these examples involve high to ultra-high dimensions and represent a number of major fields in big data analysis. The fourth edition of this book on Applied Multivariate ...

  12. Non-equilibrium effects of core-cooling and time-dependent internal heating on mantle flush events

    Directory of Open Access Journals (Sweden)

    D. A. Yuen

    1995-01-01

    Full Text Available We have examined the non-equilibrium effects of core-cooling and time-dependent internal-heating on the thermal evolution of the Earth's mantle and on mantle flush events caused by the two major phase transitions. Both two- and three-dimensional models have been employed. The mantle viscosity responds to the secular cooling through changes in the averaged temperature field. A viscosity which decreases algebraically with the average temperature has been considered. The time-dependent internal-heating is prescribed to decrease exponentially with a single decay time. We have studied the thermal histories with initial Rayleigh numbers between 2 x 107 and 108 . Flush events, driven by the non-equilibrium forcings, are much more dramatic than those produced by the equilibrium boundary conditions and constant internal heating. Multiple flush events are found under non-equilibrium conditions in which there is very little internal heating or very fast decay rates of internal-heating. Otherwise, the flush events take place in a relatively continuous fashion. Prior to massive flush events small-scale percolative structures appear in the 3D temperature fields. Time-dependent signatures, such as the surface heat flux, also exhibits high frequency oscillatory patterns prior to massive flush events. These two observations suggest that the flush event may be a self-organized critical phenomenon. The Nusselt number as a function of the time-varying Ra does not follow the Nusselt vs. Rayleigh number power-law relationship based on equilibrium (constant temperature boundary conditions. Instead Nu(t may vary non-monotonically with time because of the mantle flush events. Convective processes in the mantle operate quite differently under non-equilibrium conditions from its behaviour under the usual equilibrium situations.

  13. Correlation Analyses Between the Characteristic Times of Gradual Solar Energetic Particle Events and the Properties of Associated Coronal Mass Ejections

    Science.gov (United States)

    Pan, Z. H.; Wang, C. B.; Wang, Yuming; Xue, X. H.

    2011-06-01

    It is generally believed that gradual solar energetic particles (SEPs) are accelerated by shocks associated with coronal mass ejections (CMEs). Using an ice-cream cone model, the radial speed and angular width of 95 CMEs associated with SEP events during 1998 - 2002 are calculated from SOHO/LASCO observations. Then, we investigate the relationships between the kinematic properties of these CMEs and the characteristic times of the intensity-time profile of their accompanied SEP events observed at 1 AU. These characteristic times of SEP are i) the onset time from the accompanying CME eruption at the Sun to the SEP arrival at 1 AU, ii) the rise time from the SEP onset to the time when the SEP intensity is one-half of peak intensity, and iii) the duration over which the SEP intensity is within a factor of two of the peak intensity. It is found that the onset time has neither significant correlation with the radial speed nor with the angular width of the accompanying CME. For events that are poorly connected to the Earth, the SEP rise time and duration have no significant correlation with the radial speed and angular width of the associated CMEs. However, for events that are magnetically well connected to the Earth, the SEP rise time and duration have significantly positive correlations with the radial speed and angular width of the associated CMEs. This indicates that a CME event with wider angular width and higher speed may more easily drive a strong and wide shock near to the Earth-connected interplanetary magnetic field lines, may trap and accelerate particles for a longer time, and may lead to longer rise time and duration of the ensuing SEP event.

  14. Multivariate multiscale entropy of financial markets

    Science.gov (United States)

    Lu, Yunfan; Wang, Jun

    2017-11-01

    In current process of quantifying the dynamical properties of the complex phenomena in financial market system, the multivariate financial time series are widely concerned. In this work, considering the shortcomings and limitations of univariate multiscale entropy in analyzing the multivariate time series, the multivariate multiscale sample entropy (MMSE), which can evaluate the complexity in multiple data channels over different timescales, is applied to quantify the complexity of financial markets. Its effectiveness and advantages have been detected with numerical simulations with two well-known synthetic noise signals. For the first time, the complexity of four generated trivariate return series for each stock trading hour in China stock markets is quantified thanks to the interdisciplinary application of this method. We find that the complexity of trivariate return series in each hour show a significant decreasing trend with the stock trading time progressing. Further, the shuffled multivariate return series and the absolute multivariate return series are also analyzed. As another new attempt, quantifying the complexity of global stock markets (Asia, Europe and America) is carried out by analyzing the multivariate returns from them. Finally we utilize the multivariate multiscale entropy to assess the relative complexity of normalized multivariate return volatility series with different degrees.

  15. The time course of implicit processing of erotic pictures: an event-related potential study.

    Science.gov (United States)

    Feng, Chunliang; Wang, Lili; Wang, Naiyi; Gu, Ruolei; Luo, Yue-Jia

    2012-12-13

    The current study investigated the time course of the implicit processing of erotic stimuli using event-related potentials (ERPs). ERPs elicited by erotic pictures were compared with those by three other types of pictures: non-erotic positive, negative, and neutral pictures. We observed that erotic pictures evoked enhanced neural responses compared with other pictures at both early (P2/N2) and late (P3/positive slow wave) temporal stages. These results suggested that erotic pictures selectively captured individuals' attention at early stages and evoked deeper processing at late stages. More importantly, the amplitudes of P2, N2, and P3 only discriminated between erotic and non-erotic (i.e., positive, neutral, and negative) pictures. That is, no difference was revealed among non-erotic pictures, although these pictures differed in both valence and arousal. Thus, our results suggest that the erotic picture processing is beyond the valence and arousal. Copyright © 2012 Elsevier B.V. All rights reserved.

  16. Timely event-related synchronization fading and phase de-locking and their defects in migraine.

    Science.gov (United States)

    Yum, Myung-Kul; Moon, Jin-Hwa; Kang, Joong Koo; Kwon, Oh-Young; Park, Ki-Jong; Shon, Young-Min; Lee, Il Keun; Jung, Ki-Young

    2014-07-01

    To investigate the characteristics of event-related synchronization (ERS) fading and phase de-locking of alpha waves during passive auditory stimulation (PAS) in the migraine patients. The subjects were 16 adult women with migraine and 16 normal controls. Electroencephalographic (EEG) data obtained during PAS with standard (SS) and deviant stimuli (DS) were used. Alpha ERS fading, the phase locking index (PLI) and de-locking index (DLI) were evaluated from the 10 Hz complex Morlet wavelet components at 100 ms (t100) and 300 ms (t300) after PAS. At t100, significant ERS was found with SS and DS in the migraineurs and controls (P=0.000). At t300 in the controls, ERS faded to zero for DS while in the migraineurs there was no fading for DS. In both groups the PLI for SS and DS was significantly reduced, i.e. de-locked, at t300 compared to t100 (P=0.000). In the migraineurs, the DLI for DS was significantly lower than in the controls (P=0.003). The alpha ERS fading and phase de-locking are defective in migraineurs during passive auditory cognitive processing. The defects in timely alpha ERS fading and in de-locking may play a role in the different attention processing in migraine patients. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  17. Survival analysis using S analysis of time-to-event data

    CERN Document Server

    Tableman, Mara

    2003-01-01

    Survival Analysis Using S: Analysis of Time-to-Event Data is designed as a text for a one-semester or one-quarter course in survival analysis for upper-level or graduate students in statistics, biostatistics, and epidemiology. Prerequisites are a standard pre-calculus first course in probability and statistics, and a course in applied linear regression models. No prior knowledge of S or R is assumed. A wide choice of exercises is included, some intended for more advanced students with a first course in mathematical statistics. The authors emphasize parametric log-linear models, while also detailing nonparametric procedures along with model building and data diagnostics. Medical and public health researchers will find the discussion of cut point analysis with bootstrap validation, competing risks and the cumulative incidence estimator, and the analysis of left-truncated and right-censored data invaluable. The bootstrap procedure checks robustness of cut point analysis and determines cut point(s). In a chapter ...

  18. Relating derived relations as a model of analogical reasoning: reaction times and event-related potentials.

    Science.gov (United States)

    Barnes-Holmes, Dermot; Regan, Donal; Barnes-Holmes, Yvonne; Commins, Sean; Walsh, Derek; Stewart, Ian; Smeets, Paul M; Whelan, Robert; Dymond, Simon

    2005-11-01

    The current study aimed to test a Relational Frame Theory (RFT) model of analogical reasoning based on the relating of derived same and derived difference relations. Experiment 1 recorded reaction time measures of similar-similar (e.g., "apple is to orange as dog is to cat") versus different-different (e.g., "he is to his brother as chalk is to cheese") derived relational responding, in both speed-contingent and speed-noncontingent conditions. Experiment 2 examined the event-related potentials (ERPs) associated with these two response patterns. Both experiments showed similar-similar responding to be significantly faster than different-different responding. Experiment 2 revealed significant differences between the waveforms of the two response patterns in the left-hemispheric prefrontal regions; different-different waveforms were significantly more negative than similar-similar waveforms. The behavioral and neurophysiological data support the RFT prediction that, all things being equal, similar-similar responding is relationally "simpler" than, and functionally distinct from, different-different analogical responding. The ERP data were fully consistent with findings in the neurocognitive literature on analogy. These findings strengthen the validity of the RFT model of analogical reasoning and supplement the behavior-analytic approach to analogy based on the relating of derived relations.

  19. Life events during surgical residency have different effects on women and men over time.

    Science.gov (United States)

    Chen, Michelle M; Yeo, Heather L; Roman, Sanziana A; Bell, Richard H; Sosa, Julie A

    2013-08-01

    Women represent half of medical school graduates in the United States. Our aim was to characterize the effects of marriage and childbirth on the experiences of surgery residents. This was a prospective, longitudinal study of categorical general surgery residents between 2008 and 2010. Outcomes included changes in faculty and peer relationships, work-life balance, financial security, and career goals over time. We included 4,028 residents. Compared with men, women in postgraduate years (PGYs) 1 through 5 were less likely to be married (28.2% to 47.3% vs 49.6% to 67.6%) or have children (4.6% to 18.0% vs 19.0% to 45.8%) (P < .001). Women who married during PGY1 to PGY3 became worried about performing in front of senior residents (P = .005); men who married were more likely to be happy at work (P = .005). Women who had a first child during PGY1 to PGY3 were more likely to feel overwhelmed (P = .008) and worry about financial security (P = .03) than other women. Men who had a child were more likely to feel supported by faculty (P = .004), but they experienced more family strain (P = .008) compared to childless men. Marriage and childbirth are associated with divergent changes in career experiences for women and men. Women lag behind their male peers in these life events from start to finish of residency. Copyright © 2013 Mosby, Inc. All rights reserved.

  20. Human active X-specific DNA methylation events showing stability across time and tissues

    Science.gov (United States)

    Joo, Jihoon Eric; Novakovic, Boris; Cruickshank, Mark; Doyle, Lex W; Craig, Jeffrey M; Saffery, Richard

    2014-01-01

    The phenomenon of X chromosome inactivation in female mammals is well characterised and remains the archetypal example of dosage compensation via monoallelic expression. The temporal series of events that culminates in inactive X-specific gene silencing by DNA methylation has revealed a ‘patchwork' of gene inactivation along the chromosome, with approximately 15% of genes escaping. Such genes are therefore potentially subject to sex-specific imbalance between males and females. Aside from XIST, the non-coding RNA on the X chromosome destined to be inactivated, very little is known about the extent of loci that may be selectively silenced on the active X chromosome (Xa). Using longitudinal array-based DNA methylation profiling of two human tissues, we have identified specific and widespread active X-specific DNA methylation showing stability over time and across tissues of disparate origin. Our panel of X-chromosome loci subject to methylation on Xa reflects a potentially novel mechanism for controlling female-specific X inactivation and sex-specific dimorphisms in humans. Further work is needed to investigate these phenomena. PMID:24713664

  1. Nuclear event time histories and computed site transfer functions for locations in the Los Angeles region

    Science.gov (United States)

    Rogers, A.M.; Covington, P.A.; Park, R.B.; Borcherdt, R.D.; Perkins, D.M.

    1980-01-01

    This report presents a collection of Nevada Test Site (NTS) nuclear explosion recordings obtained at sites in the greater Los Angeles, Calif., region. The report includes ground velocity time histories, as well as, derived site transfer functions. These data have been collected as part of a study to evaluate the validity of using low-level ground motions to predict the frequency-dependent response of a site during an earthquake. For this study 19 nuclear events were recorded at 98 separate locations. Some of these sites have recorded more than one of the nuclear explosions, and, consequently, there are a total of 159, three-component station records. The location of all the recording sites are shown in figures 1–5, the station coordinates and abbreviations are given in table 1. The station addresses are listed in table 2, and the nuclear explosions that were recorded are listed in table 3. The recording sites were chosen on the basis of three criteria: (1) that the underlying geological conditions were representative of conditions over significant areas of the region, (2) that the site was the location of a strong-motion recording of the 1971 San Fernando earthquake, or (3) that more complete geographical coverage was required in that location.

  2. Evolution of Storm-time Subauroral Electric Fields: RCM Event Simulations

    Science.gov (United States)

    Sazykin, S.; Spiro, R. W.; Wolf, R. A.; Toffoletto, F.; Baker, J.; Ruohoniemi, J. M.

    2012-12-01

    Subauroral polarization streams (SAPS) are regions of strongly-enhanced westward ExB plasma drift (poleward-directed electric fields) located just equatorward of the evening auroral oval. Several recently -installed HF (coherent scatter) radars in the SuperDARN chain at mid-latitudes present a novel opportunity for obtaining two-dimensional maps of ionospheric ExB flows at F-region altitudes that span several hours of the evening and nighttime subauroral ionosphere. These new and exciting observations of SAPS provide an opportunity and a challenge to coupled magnetosphere-ionosphere models. In this paper, we use the Rice Convection Model (RCM) to simulate several events where SAPS were observed by the mid-latitude SuperDARN chain. RCM frequently predicts the occurrence of SAPS in the subauroral evening MLT sector; the mechanism is essentially current closure on the dusk side where downward Birkeland currents (associated with the ion plasma sheet inner edge) map to a region of reduced ionospheric conductance just equatorward of the diffuse auroral precipitation (associated with the electron plasma sheet inner edge). We present detailed comparisons of model-computed ionospheric convection patterns with observations, with two goals in mind: (1) to analyze to what extent the observed appearance and time evolution of SAPS structures are driven by time variations of the cross polar cap potential drop (or, equivalently, the z-component of the interplanetary magnetic field), and (2) to evaluate the ability of the model to reproduce the spatial extent and magnitude of SAPS structures.

  3. Real-time observations of stressful events in the operating room

    Directory of Open Access Journals (Sweden)

    AlNassar Sami

    2012-01-01

    Full Text Available Aim: To identify and quantify factors causing stress in the operating room (OR and evaluate the relationship between these factors and surgeons′ stress level. Methods: This is a prospective observational study from 32 elective surgical procedures conducted in the OR of King Khalid University Hospital, Riyadh, Saudi Arabia. Before each operation, each surgeon was asked of stressors. Two interns observed 16 surgeries each, separately. The interns watched and took notes during the entire surgical procedure. During each operation, the observer recorded anxiety-inducing activities and events that occurred in real time by means of a checklist of 8 potential stressors: technical, patient problems, teamwork problems, time and management issues, distractions and interruptions, equipment problems, personal problems, and teaching. After each operation, surgeons were asked to answer the validated State-Trait Anxiety Inventory questionnaire and self-report on their stress level from the 8 sources using a scale of 1-8 (1: stress free, 8: extremely stressful. The observer also recorded perceived stress levels experienced by the surgeons during the operation. Results: One hundred ten stressors were identified. Technical problems most frequently caused stress (16.4% and personal issues the least often (6.4%. Frequently encountered stressors (teaching and distractions/interruptions caused less stress to the surgeons. Technical factors, teamwork, and equipment problems occurred frequently and were also a major contributor to OR stress. All patients were discharged in good health and within 1 week of surgery. Conclusion: Certain stressful factors do occur among surgeons in the OR and can increase the potential for errors. Further research is required to determine the impact of stress on performance and the outcome of surgery.

  4. Incidence and Timing of Thromboembolic Events in Patients With Ovarian Cancer Undergoing Neoadjuvant Chemotherapy.

    Science.gov (United States)

    Greco, Patricia S; Bazzi, Ali A; McLean, Karen; Reynolds, R Kevin; Spencer, Ryan J; Johnston, Carolyn M; Liu, J Rebecca; Uppal, Shitanshu

    2017-06-01

    To identify the incidence and timing of venous thromboembolism as well as any associated risk factors in patients with ovarian, fallopian tube, or primary peritoneal cancer undergoing neoadjuvant chemotherapy. We conducted a retrospective cohort study of patients diagnosed with ovarian, fallopian tube, and primary peritoneal cancer and receiving neoadjuvant chemotherapy from January 2009 to May 2014 at a single academic institution. The timing and number of venous thromboembolic events for the entire cohort were categorized as follows: presenting symptom, during neoadjuvant chemotherapy treatment, after debulking surgery, and during adjuvant chemotherapy. Of the 125 total patients with ovarian cancer undergoing neoadjuvant chemotherapy, 13 of 125 patients (10.4%, 95% confidence interval [CI] 6.1-17.2%) had a venous thromboembolism as a presenting symptom and were excluded from further analysis. Of the 112 total patients at risk, 30 (26.8%, 95% CI 19.3-35.9%) experienced a venous thromboembolism. Based on the phase of care, 13 (11.6%, 95% CI 6.8-19.1%) experienced a venous thromboembolism during neoadjuvant chemotherapy, six (5.4%, 95% CI 2.4-11.5%) developed a postoperative venous thromboembolism, and 11 (9.9%, 95% CI 5.5-17%) developed a venous thromboembolism during adjuvant chemotherapy. Two of the four patients with clear cell histology developed a venous thromboembolism in this cohort. Overall new diagnosis of venous thromboembolism was associated with one fourth of the patients undergoing neoadjuvant chemotherapy for ovarian cancer with nearly half of these diagnosed during chemotherapy cycles before interval debulking surgery. Efforts to reduce venous thromboembolism so far have largely focused on the postoperative period. Additional attention to venous thromboembolic prophylaxis during chemotherapy (neoadjuvant and adjuvant) in this patient population is warranted in an effort to decrease the rates of venous thromboembolism.

  5. Guidelines for time-to-event end-point definitions in trials for pancreatic cancer. Results of the DATECAN initiative (Definition for the Assessment of Time-to-event End-points in CANcer trials).

    Science.gov (United States)

    Bonnetain, Franck; Bonsing, Bert; Conroy, Thierry; Dousseau, Adelaide; Glimelius, Bengt; Haustermans, Karin; Lacaine, François; Van Laethem, Jean Luc; Aparicio, Thomas; Aust, Daniela; Bassi, Claudio; Berger, Virginie; Chamorey, Emmanuel; Chibaudel, Benoist; Dahan, Laeticia; De Gramont, Aimery; Delpero, Jean Robert; Dervenis, Christos; Ducreux, Michel; Gal, Jocelyn; Gerber, Erich; Ghaneh, Paula; Hammel, Pascal; Hendlisz, Alain; Jooste, Valérie; Labianca, Roberto; Latouche, Aurelien; Lutz, Manfred; Macarulla, Teresa; Malka, David; Mauer, Muriel; Mitry, Emmanuel; Neoptolemos, John; Pessaux, Patrick; Sauvanet, Alain; Tabernero, Josep; Taieb, Julien; van Tienhoven, Geertjan; Gourgou-Bourgade, Sophie; Bellera, Carine; Mathoulin-Pélissier, Simone; Collette, Laurence

    2014-11-01

    Using potential surrogate end-points for overall survival (OS) such as Disease-Free- (DFS) or Progression-Free Survival (PFS) is increasingly common in randomised controlled trials (RCTs). However, end-points are too often imprecisely defined which largely contributes to a lack of homogeneity across trials, hampering comparison between them. The aim of the DATECAN (Definition for the Assessment of Time-to-event End-points in CANcer trials)-Pancreas project is to provide guidelines for standardised definition of time-to-event end-points in RCTs for pancreatic cancer. Time-to-event end-points currently used were identified from a literature review of pancreatic RCT trials (2006-2009). Academic research groups were contacted for participation in order to select clinicians and methodologists to participate in the pilot and scoring groups (>30 experts). A consensus was built after 2 rounds of the modified Delphi formal consensus approach with the Rand scoring methodology (range: 1-9). For pancreatic cancer, 14 time to event end-points and 25 distinct event types applied to two settings (detectable disease and/or no detectable disease) were considered relevant and included in the questionnaire sent to 52 selected experts. Thirty experts answered both scoring rounds. A total of 204 events distributed over the 14 end-points were scored. After the first round, consensus was reached for 25 items; after the second consensus was reached for 156 items; and after the face-to-face meeting for 203 items. The formal consensus approach reached the elaboration of guidelines for standardised definitions of time-to-event end-points allowing cross-comparison of RCTs in pancreatic cancer. Copyright © 2014 Elsevier Ltd. All rights reserved.

  6. Analyzing multivariate survival data using composite likelihood and flexible parametric modeling of the hazard functions

    DEFF Research Database (Denmark)

    Nielsen, Jan; Parner, Erik

    2010-01-01

    In this paper, we model multivariate time-to-event data by composite likelihood of pairwise frailty likelihoods and marginal hazards using natural cubic splines. Both right- and interval-censored data are considered. The suggested approach is applied on two types of family studies using the gamma...

  7. A MULTIVARIATE WEIBULL DISTRIBUTION

    Directory of Open Access Journals (Sweden)

    Cheng Lee

    2010-07-01

    Full Text Available A multivariate survival function of Weibull Distribution is developed by expanding the theorem by Lu and Bhattacharyya. From the survival function, the probability density function, the cumulative probability function, the determinant of the Jacobian Matrix, and the general moment are derived.

  8. Multivariate realised kernels

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole; Hansen, Peter Reinhard; Lunde, Asger

    We propose a multivariate realised kernel to estimate the ex-post covariation of log-prices. We show this new consistent estimator is guaranteed to be positive semi-definite and is robust to measurement noise of certain types and can also handle non-synchronous trading. It is the first estimator...

  9. Multivariate data analysis

    DEFF Research Database (Denmark)

    Hansen, Michael Adsetts Edberg

    Interest in statistical methodology is increasing so rapidly in the astronomical community that accessible introductory material in this area is long overdue. This book fills the gap by providing a presentation of the most useful techniques in multivariate statistics. A wide-ranging annotated set...

  10. Multivariate pattern dependence.

    Directory of Open Access Journals (Sweden)

    Stefano Anzellotti

    2017-11-01

    Full Text Available When we perform a cognitive task, multiple brain regions are engaged. Understanding how these regions interact is a fundamental step to uncover the neural bases of behavior. Most research on the interactions between brain regions has focused on the univariate responses in the regions. However, fine grained patterns of response encode important information, as shown by multivariate pattern analysis. In the present article, we introduce and apply multivariate pattern dependence (MVPD: a technique to study the statistical dependence between brain regions in humans in terms of the multivariate relations between their patterns of responses. MVPD characterizes the responses in each brain region as trajectories in region-specific multidimensional spaces, and models the multivariate relationship between these trajectories. We applied MVPD to the posterior superior temporal sulcus (pSTS and to the fusiform face area (FFA, using a searchlight approach to reveal interactions between these seed regions and the rest of the brain. Across two different experiments, MVPD identified significant statistical dependence not detected by standard functional connectivity. Additionally, MVPD outperformed univariate connectivity in its ability to explain independent variance in the responses of individual voxels. In the end, MVPD uncovered different connectivity profiles associated with different representational subspaces of FFA: the first principal component of FFA shows differential connectivity with occipital and parietal regions implicated in the processing of low-level properties of faces, while the second and third components show differential connectivity with anterior temporal regions implicated in the processing of invariant representations of face identity.

  11. Resolving the Timing of Events Around the Cretaceous-Paleogene Boundary

    Science.gov (United States)

    Sprain, Courtney Jean

    Despite decades of study, the exact cause of the Cretaceous-Paleogene boundary (KPB) mass extinction remains contentious. Hypothesized scenarios center around two main environmental perturbations: voluminous (>10 6 km3) volcanic eruptions from the Deccan Traps in modern-day India, and the large impact recorded by the Chicxulub crater. The impact hypothesis has gained broad support, bolstered by the discoveries of iridium anomalies, shocked quartz, and spherules at the KPB worldwide, which are contemporaneous with the Chicxulub impact structure. However, evidence for protracted extinctions, particularly in non-marine settings, and paleoenvironmental change associated with climatic swings before the KPB, challenge the notion that the impact was the sole cause of the KPB mass extinction. Despite forty years of study, the relative importance of each of these events is unclear, and one key inhibitor is insufficient resolution of existing geochronology. In this dissertation, I present work developing a high-precision global chronologic framework for the KPB that outlines the temporal sequence of biotic changes (both within the terrestrial and marine realms), climatic changes, and proposed perturbations (i.e. impact, volcanic eruptions) using 40Ar/39Ar geochronology and paleomagnetism. This work is focused on two major areas of study: 1) refining the timing and tempo of terrestrial ecosystem change around the KPB, and 2) calibrating the geomagnetic polarity timescale, and particularly the timing and duration of magnetic polarity chron C29r (the KPB falls about halfway into C29r). First I develop a high-precision chronostratigraphic framework for fluvial sediments within the Hell Creek region, in NE Montana, which is one of the best-studied terrestrial KPB sections worldwide. For this work I dated 15 tephra deposits with +/- 30 ka precision using 40Ar/ 39Ar geochronology, ranging in time from 300 ka before the KPB to 1 Ma after. By tying these results to paleontological

  12. Illustration of compositional variations over time of Chinese porcelain glazes combining micro-X-ray Fluorescence spectrometry, multivariate data analysis and Seger formulas

    Science.gov (United States)

    Van Pevenage, J.; Verhaeven, E.; Vekemans, B.; Lauwers, D.; Herremans, D.; De Clercq, W.; Vincze, L.; Moens, L.; Vandenabeele, P.

    2015-01-01

    In this research, the transparent glaze layers of Chinese porcelain samples were investigated. Depending on the production period, these samples can be divided into two groups: the samples of group A dating from the Kangxi period (1661-1722), and the samples of group B produced under emperor Qianlong (1735-1795). Due to the specific sample preparation method and the small spot size of the X-ray beam, investigation of the transparent glaze layers is enabled. Despite the many existing research papers about glaze investigations of ceramics and/or porcelain ware, this research reveals new insights into the glaze composition and structure of Chinese porcelain samples. In this paper it is demonstrated, using micro-X-ray Fluorescence (μ-XRF) spectrometry, multivariate data analysis and statistical analysis (Hotelling's T-Square test) that the transparent glaze layers of the samples of groups A and B are significantly different (95% confidence level). Calculation of the Seger formulas, enabled classification of the glazes. Combining all the information, the difference in composition of the Chinese porcelain glazes of the Kangxi period and the Qianlong period can be demonstrated.

  13. Development of Time Projection Chambers with Micromegas for Rare Event Searches

    CERN Document Server

    Tomas, Alfredo; Villar, J A

    The Rare Event Searches is a heterogeneous field from the point of view of their physical motivations: double betha neutrinoless decay experiments, direct detection of WIMPs as well as axions and other WISPs (candidates for the DM, but also motivated by other questions from Particle Physics). The field is rather defined by the requirements of these experiments, essentially a very sensitive detector with low background which is usually operated in underground laboratories. The availability of a rich description of the event registered by the detector is a powerful tool for the discrimination of the signal from the background. The topological description of the interaction that can be delivered by a gaseous TPC is a useful source of information about the event. The generic requirements for a gaseous TPC that is intended for rare event searches are very good imaging capabilities, high gain and efficiency, stability and reliability and radio-purity, which could imply working with particular gases, in absence of q...

  14. The effect of time constraints and running phases on combined event pistol shooting performance.

    Science.gov (United States)

    Dadswell, Clare; Payton, Carl; Holmes, Paul; Burden, Adrian

    2016-01-01

    The combined event is a crucial aspect of the modern pentathlon competition, but little is known about how shooting performance changes through the event. This study aimed to identify (i) how performance-related variables changed within each shooting series and (ii) how performance-related variables changed between each shooting series. Seventeen modern pentathletes completed combined event trials. An optoelectronic shooting system recorded score and pistol movement, and force platforms recorded centre of pressure movement 1 s prior to every shot. Heart rate and blood lactate values were recorded throughout the event. Whilst heart rate and blood lactate significantly increased between series (P  0.05). Thus, combined event shooting performance following each running phase appears similar to shooting performance following only 20 m of running. This finding has potential implications for the way in which modern pentathletes train for combined event shooting, and highlights the need for modern pentathletes to establish new methods with which to enhance shooting accuracy.

  15. Real-time distributed fiber optic sensor for security systems: Performance, event classification and nuisance mitigation

    Science.gov (United States)

    Mahmoud, Seedahmed S.; Visagathilagar, Yuvaraja; Katsifolis, Jim

    2012-09-01

    The success of any perimeter intrusion detection system depends on three important performance parameters: the probability of detection (POD), the nuisance alarm rate (NAR), and the false alarm rate (FAR). The most fundamental parameter, POD, is normally related to a number of factors such as the event of interest, the sensitivity of the sensor, the installation quality of the system, and the reliability of the sensing equipment. The suppression of nuisance alarms without degrading sensitivity in fiber optic intrusion detection systems is key to maintaining acceptable performance. Signal processing algorithms that maintain the POD and eliminate nuisance alarms are crucial for achieving this. In this paper, a robust event classification system using supervised neural networks together with a level crossings (LCs) based feature extraction algorithm is presented for the detection and recognition of intrusion and non-intrusion events in a fence-based fiber-optic intrusion detection system. A level crossings algorithm is also used with a dynamic threshold to suppress torrential rain-induced nuisance alarms in a fence system. Results show that rain-induced nuisance alarms can be suppressed for rainfall rates in excess of 100 mm/hr with the simultaneous detection of intrusion events. The use of a level crossing based detection and novel classification algorithm is also presented for a buried pipeline fiber optic intrusion detection system for the suppression of nuisance events and discrimination of intrusion events. The sensor employed for both types of systems is a distributed bidirectional fiber-optic Mach-Zehnder (MZ) interferometer.

  16. Future versus present: time perspective and pupillary response in a relatedness judgment task investigating temporal event knowledge.

    Science.gov (United States)

    Nowack, Kati; Milfont, Taciano L; van der Meer, Elke

    2013-02-01

    Mental representations of events contain many components such as typical agents, instruments, objects as well as a temporal dimension that is directed towards the future. While the role of temporal orientation (chronological, reverse) in event knowledge has been demonstrated by numerous studies, little is known about the influence of time perspective (present or future) as source of individual differences affecting event knowledge. The present study combined behavioral data with task-evoked pupil dilation to examine the impact of time perspective on cognitive resource allocation. In a relatedness judgment task, everyday events like raining were paired with an object feature like wet. Chronological items were processed more easily than reverse items regardless of time perspective. When more automatic processes were applied, greater scores on future time perspective were associated with lower error rates for chronological items. This suggests that a match between a strong focus on future consequences and items with a temporal orientation directed toward the future serves to enhance responding accuracy. Indexed by pupillary data, future-oriented participants invested more cognitive resources while outperforming present-oriented participants in reaction times across all conditions. This result was supported by a principal component analysis on the pupil data, which demonstrated the same impact of time perspective on the factor associated with more general aspects of cognitive effort. These findings suggest that future time perspective may be linked to a more general cognitive performance characteristic that improves overall task performance. Copyright © 2012 Elsevier B.V. All rights reserved.

  17. Cooperative Control of Mobile Sensor Networks for Environmental Monitoring: An Event-Triggered Finite-Time Control Scheme.

    Science.gov (United States)

    Lu, Qiang; Han, Qing-Long; Zhang, Botao; Liu, Dongliang; Liu, Shirong

    2017-12-01

    This paper deals with the problem of environmental monitoring by developing an event-triggered finite-time control scheme for mobile sensor networks. The proposed control scheme can be executed by each sensor node independently and consists of two parts: one part is a finite-time consensus algorithm while the other part is an event-triggered rule. The consensus algorithm is employed to enable the positions and velocities of sensor nodes to quickly track the position and velocity of a virtual leader in finite time. The event-triggered rule is used to reduce the updating frequency of controllers in order to save the computational resources of sensor nodes. Some stability conditions are derived for mobile sensor networks with the proposed control scheme under both a fixed communication topology and a switching communication topology. Finally, simulation results illustrate the effectiveness of the proposed control scheme for the problem of environmental monitoring.

  18. Multivariate wavelet frames

    CERN Document Server

    Skopina, Maria; Protasov, Vladimir

    2016-01-01

    This book presents a systematic study of multivariate wavelet frames with matrix dilation, in particular, orthogonal and bi-orthogonal bases, which are a special case of frames. Further, it provides algorithmic methods for the construction of dual and tight wavelet frames with a desirable approximation order, namely compactly supported wavelet frames, which are commonly required by engineers. It particularly focuses on methods of constructing them. Wavelet bases and frames are actively used in numerous applications such as audio and graphic signal processing, compression and transmission of information. They are especially useful in image recovery from incomplete observed data due to the redundancy of frame systems. The construction of multivariate wavelet frames, especially bases, with desirable properties remains a challenging problem as although a general scheme of construction is well known, its practical implementation in the multidimensional setting is difficult. Another important feature of wavelet is ...

  19. Multivariate calculus and geometry

    CERN Document Server

    Dineen, Seán

    2014-01-01

    Multivariate calculus can be understood best by combining geometric insight, intuitive arguments, detailed explanations and mathematical reasoning. This textbook has successfully followed this programme. It additionally provides a solid description of the basic concepts, via familiar examples, which are then tested in technically demanding situations. In this new edition the introductory chapter and two of the chapters on the geometry of surfaces have been revised. Some exercises have been replaced and others provided with expanded solutions. Familiarity with partial derivatives and a course in linear algebra are essential prerequisites for readers of this book. Multivariate Calculus and Geometry is aimed primarily at higher level undergraduates in the mathematical sciences. The inclusion of many practical examples involving problems of several variables will appeal to mathematics, science and engineering students.

  20. Intelligent multivariate process supervision

    International Nuclear Information System (INIS)

    Visuri, Pertti.

    1986-01-01

    This thesis addresses the difficulties encountered in managing large amounts of data in supervisory control of complex systems. Some previous alarm and disturbance analysis concepts are reviewed and a method for improving the supervision of complex systems is presented. The method, called multivariate supervision, is based on adding low level intelligence to the process control system. By using several measured variables linked together by means of deductive logic, the system can take into account the overall state of the supervised system. Thus, it can present to the operators fewer messages with higher information content than the conventional control systems which are based on independent processing of each variable. In addition, the multivariate method contains a special information presentation concept for improving the man-machine interface. (author)

  1. Multivariate rational data fitting

    Science.gov (United States)

    Cuyt, Annie; Verdonk, Brigitte

    1992-12-01

    Sections 1 and 2 discuss the advantages of an object-oriented implementation combined with higher floating-point arithmetic, of the algorithms available for multivariate data fitting using rational functions. Section 1 will in particular explain what we mean by "higher arithmetic". Section 2 will concentrate on the concepts of "object orientation". In sections 3 and 4 we shall describe the generality of the data structure that can be dealt with: due to some new results virtually every data set is acceptable right now, with possible coalescence of coordinates or points. In order to solve the multivariate rational interpolation problem the data sets are fed to different algorithms depending on the structure of the interpolation points in then-variate space.

  2. Real time imaging of live cell ATP leaking or release events by chemiluminescence microscopy

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Yun [Iowa State Univ., Ames, IA (United States)

    2008-12-18

    The purpose of this research was to expand the chemiluminescence microscopy applications in live bacterial/mammalian cell imaging and to improve the detection sensitivity for ATP leaking or release events. We first demonstrated that chemiluminescence (CL) imaging can be used to interrogate single bacterial cells. While using a luminometer allows detecting ATP from cell lysate extracted from at least 10 bacterial cells, all previous cell CL detection never reached this sensitivity of single bacteria level. We approached this goal with a different strategy from before: instead of breaking bacterial cell membrane and trying to capture the transiently diluted ATP with the firefly luciferase CL assay, we introduced the firefly luciferase enzyme into bacteria using the modern genetic techniques and placed the CL reaction substrate D-luciferin outside the cells. By damaging the cell membrane with various antibacterial drugs including antibiotics such as Penicillins and bacteriophages, the D-luciferin molecules diffused inside the cell and initiated the reaction that produces CL light. As firefly luciferases are large protein molecules which are retained within the cells before the total rupture and intracellular ATP concentration is high at the millmolar level, the CL reaction of firefly luciferase, ATP and D-luciferin can be kept for a relatively long time within the cells acting as a reaction container to generate enough photons for detection by the extremely sensitive intensified charge coupled device (ICCD) camera. The result was inspiring as various single bacterium lysis and leakage events were monitored with 10-s temporal resolution movies. We also found a new way of enhancing diffusion D-luciferin into cells by dehydrating the bacteria. Then we started with this novel single bacterial CL imaging technique, and applied it for quantifying gene expression levels from individual bacterial cells. Previous published result in single cell gene expression quantification

  3. Real Time Robot Soccer Game Event Detection Using Finite State Machines with Multiple Fuzzy Logic Probability Evaluators

    Directory of Open Access Journals (Sweden)

    Elmer P. Dadios

    2009-01-01

    Full Text Available This paper presents a new algorithm for real time event detection using Finite State Machines with multiple Fuzzy Logic Probability Evaluators (FLPEs. A machine referee for a robot soccer game is developed and is used as the platform to test the proposed algorithm. A novel technique to detect collisions and other events in microrobot soccer game under inaccurate and insufficient information is presented. The robots' collision is used to determine goalkeeper charging and goal score events which are crucial for the machine referee's decisions. The Main State Machine (MSM handles the schedule of event activation. The FLPE calculates the probabilities of the true occurrence of the events. Final decisions about the occurrences of events are evaluated and compared through threshold crisp probability values. The outputs of FLPEs can be combined to calculate the probability of an event composed of subevents. Using multiple fuzzy logic system, the FLPE utilizes minimal number of rules and can be tuned individually. Experimental results show the accuracy and robustness of the proposed algorithm.

  4. Transient multivariable sensor evaluation

    Energy Technology Data Exchange (ETDEWEB)

    Vilim, Richard B.; Heifetz, Alexander

    2017-02-21

    A method and system for performing transient multivariable sensor evaluation. The method and system includes a computer system for identifying a model form, providing training measurement data, generating a basis vector, monitoring system data from sensor, loading the system data in a non-transient memory, performing an estimation to provide desired data and comparing the system data to the desired data and outputting an alarm for a defective sensor.

  5. Interaction between Gender and Skill on Competitive State Anxiety Using the Time-to-Event Paradigm: What Roles Do Intensity, Direction, and Frequency Dimensions Play?

    Directory of Open Access Journals (Sweden)

    John E. Hagan

    2017-05-01

    Full Text Available Background and purpose: The functional understanding and examination of competitive anxiety responses as temporal events that unfold as time-to-competition moves closer has emerged as a topical research area within the domains of sport psychology. However, little is known from an inclusive and interaction oriented perspective. Using the multidimensional anxiety theory as a framework, the present study examined the temporal patterning of competitive anxiety, focusing on the dimensions of intensity, direction, and frequency of intrusions in athletes across gender and skill level.Methods: Elite and semi-elite table tennis athletes from the Ghanaian league (N = 90 completed a modified version of Competitive State Anxiety Inventory-2 (CSAI-2 with the inclusion of the directional and frequency of intrusion scales at three temporal phases (7 days, 2 days, and 1 h prior to a competitive fixture.Results: Multivariate Analyses of Variance repeated measures with follow-up analyses revealed significant interactions for between-subjects factors on all anxiety dimensions (intensity, direction, and frequency. Notably, elite (international female athletes were less cognitively anxious, showed more facilitative interpretation toward somatic anxiety symptoms and experienced less frequency of somatic anxiety symptoms than their male counterparts. However, both elite groups displayed appreciable level of self-confidence. For time-to-event effects, both cognitive and somatic anxiety intensity fluctuated whereas self-confidence showed a steady rise as competition neared. Somatic anxiety debilitative interpretation slightly improved 1 h before competition whereas cognitive anxiety frequencies also increased progressively during the entire preparatory phase.Conclusion: Findings suggest a more dynamic image of elite athletes’ pre-competitive anxiety responses than suggested by former studies, potentially influenced by cultural differences. The use of psychological

  6. Preferential processing of tactile events under conditions of divided attention: Effects of divided attention on reaction time

    OpenAIRE

    Hanson, James V. M.; Whitaker, David; Heron, James

    2009-01-01

    Differences in transduction and transmission latencies of visual, auditory and tactile events cause corresponding differences in simple reaction time. As reaction time is usually measured in unimodal blocks, it is unclear whether such latency differences also apply when observers monitor multiple sensory channels. We investigate this by comparing reaction time when attention is focussed on a single modality, and when attention is divided between multiple modalities. Results show that tactile ...

  7. A time-varying subjective quality model for mobile streaming videos with stalling events

    Science.gov (United States)

    Ghadiyaram, Deepti; Pan, Janice; Bovik, Alan C.

    2015-09-01

    Over-the-top mobile video streaming is invariably influenced by volatile network conditions which cause playback interruptions (stalling events), thereby impairing users' quality of experience (QoE). Developing models that can accurately predict users' QoE could enable the more efficient design of quality-control protocols for video streaming networks that reduce network operational costs while still delivering high-quality video content to the customers. Existing objective models that predict QoE are based on global video features, such as the number of stall events and their lengths, and are trained and validated on a small pool of ad hoc video datasets, most of which are not publicly available. The model we propose in this work goes beyond previous models as it also accounts for the fundamental effect that a viewer's recent level of satisfaction or dissatisfaction has on their overall viewing experience. In other words, the proposed model accounts for and adapts to the recency, or hysteresis effect caused by a stall event in addition to accounting for the lengths, frequency of occurrence, and the positions of stall events - factors that interact in a complex way to affect a user's QoE. On the recently introduced LIVE-Avvasi Mobile Video Database, which consists of 180 distorted videos of varied content that are afflicted solely with over 25 unique realistic stalling events, we trained and validated our model to accurately predict the QoE, attaining standout QoE prediction performance.

  8. Multivariate meta-analysis: Potential and promise

    Science.gov (United States)

    Jackson, Dan; Riley, Richard; White, Ian R

    2011-01-01

    The multivariate random effects model is a generalization of the standard univariate model. Multivariate meta-analysis is becoming more commonly used and the techniques and related computer software, although continually under development, are now in place. In order to raise awareness of the multivariate methods, and discuss their advantages and disadvantages, we organized a one day ‘Multivariate meta-analysis’ event at the Royal Statistical Society. In addition to disseminating the most recent developments, we also received an abundance of comments, concerns, insights, critiques and encouragement. This article provides a balanced account of the day's discourse. By giving others the opportunity to respond to our assessment, we hope to ensure that the various view points and opinions are aired before multivariate meta-analysis simply becomes another widely used de facto method without any proper consideration of it by the medical statistics community. We describe the areas of application that multivariate meta-analysis has found, the methods available, the difficulties typically encountered and the arguments for and against the multivariate methods, using four representative but contrasting examples. We conclude that the multivariate methods can be useful, and in particular can provide estimates with better statistical properties, but also that these benefits come at the price of making more assumptions which do not result in better inference in every case. Although there is evidence that multivariate meta-analysis has considerable potential, it must be even more carefully applied than its univariate counterpart in practice. Copyright © 2011 John Wiley & Sons, Ltd. PMID:21268052

  9. Timing of the brain events underlying access to consciousness during the attentional blink.

    Science.gov (United States)

    Sergent, Claire; Baillet, Sylvain; Dehaene, Stanislas

    2005-10-01

    In the phenomenon of attentional blink, identical visual stimuli are sometimes fully perceived and sometimes not detected at all. This phenomenon thus provides an optimal situation to study the fate of stimuli not consciously perceived and the differences between conscious and nonconscious processing. We correlated behavioral visibility ratings and recordings of event-related potentials to study the temporal dynamics of access to consciousness. Intact early potentials (P1 and N1) were evoked by unseen words, suggesting that these brain events are not the primary correlates of conscious perception. However, we observed a rapid divergence around 270 ms, after which several brain events were evoked solely by seen words. Thus, we suggest that the transition toward access to consciousness relates to the optional triggering of a late wave of activation that spreads through a distributed network of cortical association areas.

  10. Time to foster a rational approach to preventing cardiovascular morbid events.

    Science.gov (United States)

    Cohn, Jay N; Duprez, Daniel A

    2008-07-29

    Efforts to prevent atherosclerotic morbid events have focused primarily on risk factor prevention and intervention. These approaches, based on the statistical association of risk factors with events, have dominated clinical practice in the last generation. Because the cardiovascular abnormalities eventuating in morbid events are detectable in the arteries and heart before the development of symptomatic disease, recent efforts have focused on identifying the presence of these abnormalities as a more sensitive and specific guide to the need for therapy. Advances in noninvasive techniques for studying the vasculature and the left ventricle now provide the opportunity to use early disease rather than risk factors as the tool for clinical decision making. A disease scoring system has been developed using 10 tests of vascular and cardiac function and structure. More extensive data to confirm the sensitivity and specificity of this scoring system and to demonstrate its utility in tracking the response to therapy are needed to justify widespread application in clinical practice.

  11. Climate Central World Weather Attribution (WWA) project: Real-time extreme weather event attribution analysis

    Science.gov (United States)

    Haustein, Karsten; Otto, Friederike; Uhe, Peter; Allen, Myles; Cullen, Heidi

    2015-04-01

    Extreme weather detection and attribution analysis has emerged as a core theme in climate science over the last decade or so. By using a combination of observational data and climate models it is possible to identify the role of climate change in certain types of extreme weather events such as sea level rise and its contribution to storm surges, extreme heat events and droughts or heavy rainfall and flood events. These analyses are usually carried out after an extreme event has occurred when reanalysis and observational data become available. The Climate Central WWA project will exploit the increasing forecast skill of seasonal forecast prediction systems such as the UK MetOffice GloSea5 (Global seasonal forecasting system) ensemble forecasting method. This way, the current weather can be fed into climate models to simulate large ensembles of possible weather scenarios before an event has fully emerged yet. This effort runs along parallel and intersecting tracks of science and communications that involve research, message development and testing, staged socialization of attribution science with key audiences, and dissemination. The method we employ uses a very large ensemble of simulations of regional climate models to run two different analyses: one to represent the current climate as it was observed, and one to represent the same events in the world that might have been without human-induced climate change. For the weather "as observed" experiment, the atmospheric model uses observed sea surface temperature (SST) data from GloSea5 (currently) and present-day atmospheric gas concentrations to simulate weather events that are possible given the observed climate conditions. The weather in the "world that might have been" experiments is obtained by removing the anthropogenic forcing from the observed SSTs, thereby simulating a counterfactual world without human activity. The anthropogenic forcing is obtained by comparing the CMIP5 historical and natural simulations

  12. MOBBED: a computational data infrastructure for handling large collections of event-rich time series datasets in MATLAB.

    Science.gov (United States)

    Cockfield, Jeremy; Su, Kyungmin; Robbins, Kay A

    2013-01-01

    Experiments to monitor human brain activity during active behavior record a variety of modalities (e.g., EEG, eye tracking, motion capture, respiration monitoring) and capture a complex environmental context leading to large, event-rich time series datasets. The considerable variability of responses within and among subjects in more realistic behavioral scenarios requires experiments to assess many more subjects over longer periods of time. This explosion of data requires better computational infrastructure to more systematically explore and process these collections. MOBBED is a lightweight, easy-to-use, extensible toolkit that allows users to incorporate a computational database into their normal MATLAB workflow. Although capable of storing quite general types of annotated data, MOBBED is particularly oriented to multichannel time series such as EEG that have event streams overlaid with sensor data. MOBBED directly supports access to individual events, data frames, and time-stamped feature vectors, allowing users to ask questions such as what types of events or features co-occur under various experimental conditions. A database provides several advantages not available to users who process one dataset at a time from the local file system. In addition to archiving primary data in a central place to save space and avoid inconsistencies, such a database allows users to manage, search, and retrieve events across multiple datasets without reading the entire dataset. The database also provides infrastructure for handling more complex event patterns that include environmental and contextual conditions. The database can also be used as a cache for expensive intermediate results that are reused in such activities as cross-validation of machine learning algorithms. MOBBED is implemented over PostgreSQL, a widely used open source database, and is freely available under the GNU general public license at http://visual.cs.utsa.edu/mobbed. Source and issue reports for MOBBED

  13. Multivariate Analysis of the Effect of Source of Supply and Carrier on Processing and Shipping Times for Issue Priority Group One Requisitions

    National Research Council Canada - National Science Library

    Sagara, Gavan M

    2008-01-01

    This thesis investigates the effects of source of supply and carrier on the delivery times of high-priority requisitions to primary destinations of Navy, Military Sealift Command, USMC ground forces, and select U.S...

  14. Quantification of risk considering external events on the change of allowed outage time and the preventive maintenance during power operation

    Energy Technology Data Exchange (ETDEWEB)

    Kang, D. J.; Kim, K. Y.; Yang, J. E

    2001-03-01

    In this study, for the major safety systems of Ulchin Units 3/4, we quantify the risk on the change of AOT and the PM during power operation to identify the effects on the results of external events PSA when nuclear power plant changes such as allowed outage time are requested. The systems for which the risks on the change of allowed outage time are quantified are High Pressure Safety Injection System (HPSIS), Containment Spray System (CSS), and Emergency Diesel Generator (EDG). The systems for which the risks on the PM during power operation are Low Pressure Safety Injection System (LPSIS), CSS, EDG, Essential Service Water System (ESWS). Following conclusions can be obtained through this study: 1)The increase of core damage frequency ({delta}CDF) on the change of AOT and the conditional core damage probability (CCDP) on the on-line PM of each system are differently quantified according to the cases of considering only internal events or only external events. . 2)It is expected that the quantification of risk including internal and external events is advantageous for the licensee of NPP if the regulatory acceptance criteria for the technical specification changes are relatively set up. However, it is expected to be disadvantageous for the licensee if the acceptance criteria are absolutely set up. 3)It is expected that the conduction on the quantification of only a fire event is sufficient when the quantification of external events PSA model is required for the plant changes of Korea Standard NPPs. 4)It is expected that the quantification of the increase of core damage frequency and the incremental conditional core damage probability on technical specification changes are not needed if the quantification results of those considering only internal events are below regulatory acceptance criteria and the external events PSA results are not greatly affected by the system availability. However, it is expected that the quantification of risk considering external events

  15. Quantification of risk considering external events on the change of allowed outage time and the preventive maintenance during power operation

    International Nuclear Information System (INIS)

    Kang, D. J.; Kim, K. Y.; Yang, J. E.

    2001-03-01

    In this study, for the major safety systems of Ulchin Units 3/4, we quantify the risk on the change of AOT and the PM during power operation to identify the effects on the results of external events PSA when nuclear power plant changes such as allowed outage time are requested. The systems for which the risks on the change of allowed outage time are quantified are High Pressure Safety Injection System (HPSIS), Containment Spray System (CSS), and Emergency Diesel Generator (EDG). The systems for which the risks on the PM during power operation are Low Pressure Safety Injection System (LPSIS), CSS, EDG, Essential Service Water System (ESWS). Following conclusions can be obtained through this study: 1)The increase of core damage frequency (ΔCDF) on the change of AOT and the conditional core damage probability (CCDP) on the on-line PM of each system are differently quantified according to the cases of considering only internal events or only external events. . 2)It is expected that the quantification of risk including internal and external events is advantageous for the licensee of NPP if the regulatory acceptance criteria for the technical specification changes are relatively set up. However, it is expected to be disadvantageous for the licensee if the acceptance criteria are absolutely set up. 3)It is expected that the conduction on the quantification of only a fire event is sufficient when the quantification of external events PSA model is required for the plant changes of Korea Standard NPPs. 4)It is expected that the quantification of the increase of core damage frequency and the incremental conditional core damage probability on technical specification changes are not needed if the quantification results of those considering only internal events are below regulatory acceptance criteria and the external events PSA results are not greatly affected by the system availability. However, it is expected that the quantification of risk considering external events on

  16. Multivariate Max-Stable Spatial Processes

    KAUST Repository

    Genton, Marc G.

    2014-01-06

    Analysis of spatial extremes is currently based on univariate processes. Max-stable processes allow the spatial dependence of extremes to be modelled and explicitly quantified, they are therefore widely adopted in applications. For a better understanding of extreme events of real processes, such as environmental phenomena, it may be useful to study several spatial variables simultaneously. To this end, we extend some theoretical results and applications of max-stable processes to the multivariate setting to analyze extreme events of several variables observed across space. In particular, we study the maxima of independent replicates of multivariate processes, both in the Gaussian and Student-t cases. Then, we define a Poisson process construction in the multivariate setting and introduce multivariate versions of the Smith Gaussian extremevalue, the Schlather extremal-Gaussian and extremal-t, and the BrownResnick models. Inferential aspects of those models based on composite likelihoods are developed. We present results of various Monte Carlo simulations and of an application to a dataset of summer daily temperature maxima and minima in Oklahoma, U.S.A., highlighting the utility of working with multivariate models in contrast to the univariate case. Based on joint work with Simone Padoan and Huiyan Sang.

  17. Multivariate Max-Stable Spatial Processes

    KAUST Repository

    Genton, Marc G.

    2014-01-01

    Analysis of spatial extremes is currently based on univariate processes. Max-stable processes allow the spatial dependence of extremes to be modelled and explicitly quantified, they are therefore widely adopted in applications. For a better understanding of extreme events of real processes, such as environmental phenomena, it may be useful to study several spatial variables simultaneously. To this end, we extend some theoretical results and applications of max-stable processes to the multivariate setting to analyze extreme events of several variables observed across space. In particular, we study the maxima of independent replicates of multivariate processes, both in the Gaussian and Student-t cases. Then, we define a Poisson process construction in the multivariate setting and introduce multivariate versions of the Smith Gaussian extremevalue, the Schlather extremal-Gaussian and extremal-t, and the BrownResnick models. Inferential aspects of those models based on composite likelihoods are developed. We present results of various Monte Carlo simulations and of an application to a dataset of summer daily temperature maxima and minima in Oklahoma, U.S.A., highlighting the utility of working with multivariate models in contrast to the univariate case. Based on joint work with Simone Padoan and Huiyan Sang.

  18. Gaia16aye binary microlensing event is rising for the 5th time

    Science.gov (United States)

    Wyrzykowski, L.; Mroz, P.; Rybicki, K.; Altavilla, G.; Bakis, V.; Bendjoya, P.; Birenbaum, G.; Blagorodnova, N.; Blanco-Cuaresma, S.; Bonanos, A.; Bozza, V.; Britavskiy, N.; Burgaz, U.; Butterley, T.; Capuozzo, P.; Carrasco, J. M.; Chruslinska, M.; Damljanovic, G.; Dapergolas, T.; Dennefeld, M.; Dhillon, V. S.; Dominik, M.; Esenoglu, H.; Fossey, S.; Gomboc, A.; Hallokoun, N.; Hamanowicz, A.; Hardy, L. K.; Hudec, R.; Khamitov, I.; Klencki, J.; Kolaczkowski, Z.; Kolb, U.; Leonini, S.; Leto, G.; Lewis, F.; Liakos, A.; Littlefair, S. P.; Maoz, D.; Maund, J. R.; Mikolajczyk, P.; Palaversa, L.; Pawlak, M.; Penny, M.; Piascik, A.; Reig, P.; Rhodes, L.; Russell, D.; Sanchez, R. Z.; Shappee, B.; Shvartzvald, Y.; Sitek, M.; Sniegowska, M.; Sokolovsky, K.; Steele, I.; Street, R.; Tomasella, L.; Trascinelli, L.; Wiersema, K.; Wilson, R. W.; Zharkov, I.; Zola, S.; Zubareva, A.

    2017-05-01

    Gaia16aye, nicknamed Ayers Rock (19:40:01.13 +30:07:53.4, J2000) was detected in August 2016 and continue on-going, becoming the longest microlensing event found in the Galactic Disk (ATEL #9376, #9507).

  19. Precipitation-snowmelt timing and snowmelt augmentation of large peak flow events, western Cascades, Oregon

    Science.gov (United States)

    Keith Jennings; Julia A. Jones

    2015-01-01

    This study tested multiple hydrologic mechanisms to explain snowpack dynamics in extreme rain-on-snow floods, which occur widely in the temperate and polar regions. We examined 26, 10 day large storm events over the period 1992–2012 in the H.J. Andrews Experimental Forest in western Oregon, using statistical analyses (regression, ANOVA, and wavelet coherence) of hourly...

  20. Sample Size Estimation for Negative Binomial Regression Comparing Rates of Recurrent Events with Unequal Follow-Up Time.

    Science.gov (United States)

    Tang, Yongqiang

    2015-01-01

    A sample size formula is derived for negative binomial regression for the analysis of recurrent events, in which subjects can have unequal follow-up time. We obtain sharp lower and upper bounds on the required size, which is easy to compute. The upper bound is generally only slightly larger than the required size, and hence can be used to approximate the sample size. The lower and upper size bounds can be decomposed into two terms. The first term relies on the mean number of events in each group, and the second term depends on two factors that measure, respectively, the extent of between-subject variability in event rates, and follow-up time. Simulation studies are conducted to assess the performance of the proposed method. An application of our formulae to a multiple sclerosis trial is provided.

  1. Long-Term Memory: A Natural Mechanism for the Clustering of Extreme Events and Anomalous Residual Times in Climate Records

    Science.gov (United States)

    Bunde, Armin; Eichner, Jan F.; Kantelhardt, Jan W.; Havlin, Shlomo

    2005-01-01

    We study the statistics of the return intervals between extreme events above a certain threshold in long-term persistent records. We find that the long-term memory leads (i)to a stretched exponential distribution of the return intervals, (ii)to a pronounced clustering of extreme events, and (iii)to an anomalous behavior of the mean residual time to the next event that depends on the history and increases with the elapsed time in a counterintuitive way. We present an analytical scaling approach and demonstrate that all these features can be seen in long climate records. The phenomena should also occur in heartbeat records, Internet traffic, and stock market volatility and have to be taken into account for an efficient risk evaluation.

  2. Control Multivariable por Desacoplo

    Directory of Open Access Journals (Sweden)

    Fernando Morilla

    2013-01-01

    Full Text Available Resumen: La interacción entre variables es una característica inherente de los procesos multivariables, que dificulta su operación y el diseño de sus sistemas de control. Bajo el paradigma de Control por desacoplo se agrupan un conjunto de metodologías, que tradicionalmente han estado orientadas a eliminar o reducir la interacción, y que recientemente algunos investigadores han reorientado con objetivos de solucionar un problema tan complejo como es el control multivariable. Parte del material descrito en este artículo es bien conocido en el campo del control de procesos, pero la mayor parte de él son resultados de varios años de investigación de los autores en los que han primado la generalización del problema, la búsqueda de soluciones de fácil implementación y la combinación de bloques elementales de control PID. Esta conjunción de intereses provoca que no siempre se pueda conseguir un desacoplo perfecto, pero que sí se pueda conseguir una considerable reducción de la interacción en el nivel básico de la pirámide de control, en beneficio de otros sistemas de control que ocupan niveles jerárquicos superiores. El artículo resume todos los aspectos básicos del Control por desacoplo y su aplicación a dos procesos representativos: una planta experimental de cuatro tanques acoplados y un modelo 4×4 de un sistema experimental de calefacción, ventilación y aire acondicionado. Abstract: The interaction between variables is inherent in multivariable processes and this fact may complicate their operation and control system design. Under the paradigm of decoupling control, several methodologies that traditionally have been addressed to cancel or reduce the interactions are gathered. Recently, this approach has been reoriented by several researchers with the aim to solve such a complex problem as the multivariable control. Parts of the material in this work are well known in the process control field; however, most of them are

  3. Introduction to multivariate discrimination

    Science.gov (United States)

    Kégl, Balázs

    2013-07-01

    Multivariate discrimination or classification is one of the best-studied problem in machine learning, with a plethora of well-tested and well-performing algorithms. There are also several good general textbooks [1-9] on the subject written to an average engineering, computer science, or statistics graduate student; most of them are also accessible for an average physics student with some background on computer science and statistics. Hence, instead of writing a generic introduction, we concentrate here on relating the subject to a practitioner experimental physicist. After a short introduction on the basic setup (Section 1) we delve into the practical issues of complexity regularization, model selection, and hyperparameter optimization (Section 2), since it is this step that makes high-complexity non-parametric fitting so different from low-dimensional parametric fitting. To emphasize that this issue is not restricted to classification, we illustrate the concept on a low-dimensional but non-parametric regression example (Section 2.1). Section 3 describes the common algorithmic-statistical formal framework that unifies the main families of multivariate classification algorithms. We explain here the large-margin principle that partly explains why these algorithms work. Section 4 is devoted to the description of the three main (families of) classification algorithms, neural networks, the support vector machine, and AdaBoost. We do not go into the algorithmic details; the goal is to give an overview on the form of the functions these methods learn and on the objective functions they optimize. Besides their technical description, we also make an attempt to put these algorithm into a socio-historical context. We then briefly describe some rather heterogeneous applications to illustrate the pattern recognition pipeline and to show how widespread the use of these methods is (Section 5). We conclude the chapter with three essentially open research problems that are either

  4. Introduction to multivariate discrimination

    International Nuclear Information System (INIS)

    Kegl, B.

    2013-01-01

    Multivariate discrimination or classification is one of the best-studied problem in machine learning, with a plethora of well-tested and well-performing algorithms. There are also several good general textbooks [1-9] on the subject written to an average engineering, computer science, or statistics graduate student; most of them are also accessible for an average physics student with some background on computer science and statistics. Hence, instead of writing a generic introduction, we concentrate here on relating the subject to a practitioner experimental physicist. After a short introduction on the basic setup (Section 1) we delve into the practical issues of complexity regularization, model selection, and hyper-parameter optimization (Section 2), since it is this step that makes high-complexity non-parametric fitting so different from low-dimensional parametric fitting. To emphasize that this issue is not restricted to classification, we illustrate the concept on a low-dimensional but non-parametric regression example (Section 2.1). Section 3 describes the common algorithmic-statistical formal framework that unifies the main families of multivariate classification algorithms. We explain here the large-margin principle that partly explains why these algorithms work. Section 4 is devoted to the description of the three main (families of) classification algorithms, neural networks, the support vector machine, and AdaBoost. We do not go into the algorithmic details; the goal is to give an overview on the form of the functions these methods learn and on the objective functions they optimize. Besides their technical description, we also make an attempt to put these algorithm into a socio-historical context. We then briefly describe some rather heterogeneous applications to illustrate the pattern recognition pipeline and to show how widespread the use of these methods is (Section 5). We conclude the chapter with three essentially open research problems that are either

  5. Multivariate realised kernels

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole Eiler; Hansen, Peter Reinhard; Lunde, Asger

    2011-01-01

    We propose a multivariate realised kernel to estimate the ex-post covariation of log-prices. We show this new consistent estimator is guaranteed to be positive semi-definite and is robust to measurement error of certain types and can also handle non-synchronous trading. It is the first estimator...... which has these three properties which are all essential for empirical work in this area. We derive the large sample asymptotics of this estimator and assess its accuracy using a Monte Carlo study. We implement the estimator on some US equity data, comparing our results to previous work which has used...

  6. Pattern recognition based on time-frequency analysis and convolutional neural networks for vibrational events in φ-OTDR

    Science.gov (United States)

    Xu, Chengjin; Guan, Junjun; Bao, Ming; Lu, Jiangang; Ye, Wei

    2018-01-01

    Based on vibration signals detected by a phase-sensitive optical time-domain reflectometer distributed optical fiber sensing system, this paper presents an implement of time-frequency analysis and convolutional neural network (CNN), used to classify different types of vibrational events. First, spectral subtraction and the short-time Fourier transform are used to enhance time-frequency features of vibration signals and transform different types of vibration signals into spectrograms, which are input to the CNN for automatic feature extraction and classification. Finally, by replacing the soft-max layer in the CNN with a multiclass support vector machine, the performance of the classifier is enhanced. Experiments show that after using this method to process 4000 vibration signal samples generated by four different vibration events, namely, digging, walking, vehicles passing, and damaging, the recognition rates of vibration events are over 90%. The experimental results prove that this method can automatically make an effective feature selection and greatly improve the classification accuracy of vibrational events in distributed optical fiber sensing systems.

  7. Identifying deliberate attempts to fake memory impairment through the combined use of reaction time and event-related potential measures

    NARCIS (Netherlands)

    van Hooff, Johanna C.; Sargeant, Elizabeth; Foster, Jonathan K.; Schmand, Ben A.

    2009-01-01

    The central aim of this study was to evaluate the value of reaction time (RT) measures and event-related potentials (ERPs) for the assessment of simulated memory impairment. In two identical experiments (N = 24), healthy volunteers carried out an adapted version of the Amsterdam Short-Term Memory

  8. Distinct and shared cognitive functions mediate event- and time-based prospective memory impairment in normal ageing

    Science.gov (United States)

    Gonneaud, Julie; Kalpouzos, Grégoria; Bon, Laetitia; Viader, Fausto; Eustache, Francis; Desgranges, Béatrice

    2011-01-01

    Prospective memory (PM) is the ability to remember to perform an action at a specific point in the future. Regarded as multidimensional, PM involves several cognitive functions that are known to be impaired in normal aging. In the present study, we set out to investigate the cognitive correlates of PM impairment in normal aging. Manipulating cognitive load, we assessed event- and time-based PM, as well as several cognitive functions, including executive functions, working memory and retrospective episodic memory, in healthy subjects covering the entire adulthood. We found that normal aging was characterized by PM decline in all conditions and that event-based PM was more sensitive to the effects of aging than time-based PM. Whatever the conditions, PM was linked to inhibition and processing speed. However, while event-based PM was mainly mediated by binding and retrospective memory processes, time-based PM was mainly related to inhibition. The only distinction between high- and low-load PM cognitive correlates lays in an additional, but marginal, correlation between updating and the high-load PM condition. The association of distinct cognitive functions, as well as shared mechanisms with event- and time-based PM confirms that each type of PM relies on a different set of processes. PMID:21678154

  9. Identification of the timing-of-events model with multiple competing exit risks from single-spell data

    DEFF Research Database (Denmark)

    Drepper, Bettina; Effraimidis, G.

    2016-01-01

    The identification result of the timing-of-events model (Abbring and Van den Berg, 2003b) is extended to a model with several competing exit risk equations. This extension allows e.g. to simultaneously identify the different effects a benefit sanction has on the rate of finding work and leaving t...

  10. Survival analysis with covariates in combination with multinomial analysis to parametrize time to event for multi-state models

    NARCIS (Netherlands)

    Feenstra, T.L.; Postmus, D.; Quik, E.H.; Langendijk, H.; Krabbe, P.F.M.

    Objectives: Recent ISPOR Good practice guidelines as well as literature encourage to use a single distribution rather than the latent failure approach to model time to event for patient level simulation models with multiple competing outcomes. Aim was to apply the preferred method of a single

  11. Do changes in the frequency, magnitude and timing of extreme climatic events threaten the population viability of coastal birds?

    NARCIS (Netherlands)

    van de Pol, Martijn; Ens, Bruno J.; Heg, Dik; Brouwer, Lyanne; Krol, Johan; Maier, Martin; Exo, Klaus-Michael; Oosterbeek, Kees; Lok, Tamar; Eising, Corine M.; Koffijberg, Kees

    P>1. Climate change encompasses changes in both the means and the extremes of climatic variables, but the population consequences of the latter are intrinsically difficult to study. 2. We investigated whether the frequency, magnitude and timing of rare but catastrophic flooding events have changed

  12. Survival analysis with covariates in combination with multinomial analysis to parametrize time to event for multi-state models

    NARCIS (Netherlands)

    Feenstra, T.L.; Postmus, D.; Quik, E.H.; Langendijk, H.; Krabbe, P.F.M.

    2013-01-01

    Objectives: Recent ISPOR Good practice guidelines as well as literature encourage to use a single distribution rather than the latent failure approach to model time to event for patient level simulation models with multiple competing outcomes. Aim was to apply the preferred method of a single

  13. DETECT: a MATLAB toolbox for event detection and identification in time series, with applications to artifact detection in EEG signals.

    Science.gov (United States)

    Lawhern, Vernon; Hairston, W David; Robbins, Kay

    2013-01-01

    Recent advances in sensor and recording technology have allowed scientists to acquire very large time-series datasets. Researchers often analyze these datasets in the context of events, which are intervals of time where the properties of the signal change relative to a baseline signal. We have developed DETECT, a MATLAB toolbox for detecting event time intervals in long, multi-channel time series. Our primary goal is to produce a toolbox that is simple for researchers to use, allowing them to quickly train a model on multiple classes of events, assess the accuracy of the model, and determine how closely the results agree with their own manual identification of events without requiring extensive programming knowledge or machine learning experience. As an illustration, we discuss application of the DETECT toolbox for detecting signal artifacts found in continuous multi-channel EEG recordings and show the functionality of the tools found in the toolbox. We also discuss the application of DETECT for identifying irregular heartbeat waveforms found in electrocardiogram (ECG) data as an additional illustration.

  14. DETECT: a MATLAB toolbox for event detection and identification in time series, with applications to artifact detection in EEG signals.

    Directory of Open Access Journals (Sweden)

    Vernon Lawhern

    Full Text Available Recent advances in sensor and recording technology have allowed scientists to acquire very large time-series datasets. Researchers often analyze these datasets in the context of events, which are intervals of time where the properties of the signal change relative to a baseline signal. We have developed DETECT, a MATLAB toolbox for detecting event time intervals in long, multi-channel time series. Our primary goal is to produce a toolbox that is simple for researchers to use, allowing them to quickly train a model on multiple classes of events, assess the accuracy of the model, and determine how closely the results agree with their own manual identification of events without requiring extensive programming knowledge or machine learning experience. As an illustration, we discuss application of the DETECT toolbox for detecting signal artifacts found in continuous multi-channel EEG recordings and show the functionality of the tools found in the toolbox. We also discuss the application of DETECT for identifying irregular heartbeat waveforms found in electrocardiogram (ECG data as an additional illustration.

  15. Improved multivariate polynomial factoring algorithm

    International Nuclear Information System (INIS)

    Wang, P.S.

    1978-01-01

    A new algorithm for factoring multivariate polynomials over the integers based on an algorithm by Wang and Rothschild is described. The new algorithm has improved strategies for dealing with the known problems of the original algorithm, namely, the leading coefficient problem, the bad-zero problem and the occurrence of extraneous factors. It has an algorithm for correctly predetermining leading coefficients of the factors. A new and efficient p-adic algorithm named EEZ is described. Bascially it is a linearly convergent variable-by-variable parallel construction. The improved algorithm is generally faster and requires less store then the original algorithm. Machine examples with comparative timing are included

  16. Event-based state estimation for a class of complex networks with time-varying delays: A comparison principle approach

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Wenbing [Department of Mathematics, Yangzhou University, Yangzhou 225002 (China); Wang, Zidong [Department of Computer Science, Brunel University London, Uxbridge, Middlesex, UB8 3PH (United Kingdom); Liu, Yurong, E-mail: yrliu@yzu.edu.cn [Department of Mathematics, Yangzhou University, Yangzhou 225002 (China); Communication Systems and Networks (CSN) Research Group, Faculty of Engineering, King Abdulaziz University, Jeddah 21589 (Saudi Arabia); Ding, Derui [Shanghai Key Lab of Modern Optical System, Department of Control Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093 (China); Alsaadi, Fuad E. [Communication Systems and Networks (CSN) Research Group, Faculty of Engineering, King Abdulaziz University, Jeddah 21589 (Saudi Arabia)

    2017-01-05

    The paper is concerned with the state estimation problem for a class of time-delayed complex networks with event-triggering communication protocol. A novel event generator function, which is dependent not only on the measurement output but also on a predefined positive constant, is proposed with hope to reduce the communication burden. A new concept of exponentially ultimate boundedness is provided to quantify the estimation performance. By means of the comparison principle, some sufficient conditions are obtained to guarantee that the estimation error is exponentially ultimately bounded, and then the estimator gains are obtained in terms of the solution of certain matrix inequalities. Furthermore, a rigorous proof is proposed to show that the designed triggering condition is free of the Zeno behavior. Finally, a numerical example is given to illustrate the effectiveness of the proposed event-based estimator. - Highlights: • An event-triggered estimator is designed for complex networks with time-varying delays. • A novel event generator function is proposed to reduce the communication burden. • The comparison principle is utilized to derive the sufficient conditions. • The designed triggering condition is shown to be free of the Zeno behavior.

  17. A Robust Real Time Direction-of-Arrival Estimation Method for Sequential Movement Events of Vehicles.

    Science.gov (United States)

    Liu, Huawei; Li, Baoqing; Yuan, Xiaobing; Zhou, Qianwei; Huang, Jingchang

    2018-03-27

    Parameters estimation of sequential movement events of vehicles is facing the challenges of noise interferences and the demands of portable implementation. In this paper, we propose a robust direction-of-arrival (DOA) estimation method for the sequential movement events of vehicles based on a small Micro-Electro-Mechanical System (MEMS) microphone array system. Inspired by the incoherent signal-subspace method (ISM), the method that is proposed in this work employs multiple sub-bands, which are selected from the wideband signals with high magnitude-squared coherence to track moving vehicles in the presence of wind noise. The field test results demonstrate that the proposed method has a better performance in emulating the DOA of a moving vehicle even in the case of severe wind interference than the narrowband multiple signal classification (MUSIC) method, the sub-band DOA estimation method, and the classical two-sided correlation transformation (TCT) method.

  18. Disambiguating past events: accurate source memory for time and context depends on different retrieval processes

    OpenAIRE

    Persson, Bjorn Martin; Ainge, James Alexander; O'Connor, Akira Robert

    2016-01-01

    Participant payment was provided by the School of Psychology and Neuroscience ResPay scheme. Current animal models of episodic memory are usually based on demonstrating integrated memory for what happened, where it happened, and when an event took place. These models aim to capture the testable features of the definition of human episodic memory which stresses the temporal component of the memory as a unique piece of source information that allows us to disambiguate one memory from another...

  19. Tethered to the EHR: Primary Care Physician Workload Assessment Using EHR Event Log Data and Time-Motion Observations.

    Science.gov (United States)

    Arndt, Brian G; Beasley, John W; Watkinson, Michelle D; Temte, Jonathan L; Tuan, Wen-Jan; Sinsky, Christine A; Gilchrist, Valerie J

    2017-09-01

    Primary care physicians spend nearly 2 hours on electronic health record (EHR) tasks per hour of direct patient care. Demand for non-face-to-face care, such as communication through a patient portal and administrative tasks, is increasing and contributing to burnout. The goal of this study was to assess time allocated by primary care physicians within the EHR as indicated by EHR user-event log data, both during clinic hours (defined as 8:00 am to 6:00 pm Monday through Friday) and outside clinic hours. We conducted a retrospective cohort study of 142 family medicine physicians in a single system in southern Wisconsin. All Epic (Epic Systems Corporation) EHR interactions were captured from "event logging" records over a 3-year period for both direct patient care and non-face-to-face activities, and were validated by direct observation. EHR events were assigned to 1 of 15 EHR task categories and allocated to either during or after clinic hours. Clinicians spent 355 minutes (5.9 hours) of an 11.4-hour workday in the EHR per weekday per 1.0 clinical full-time equivalent: 269 minutes (4.5 hours) during clinic hours and 86 minutes (1.4 hours) after clinic hours. Clerical and administrative tasks including documentation, order entry, billing and coding, and system security accounted for nearly one-half of the total EHR time (157 minutes, 44.2%). Inbox management accounted for another 85 minutes (23.7%). Primary care physicians spend more than one-half of their workday, nearly 6 hours, interacting with the EHR during and after clinic hours. EHR event logs can identify areas of EHR-related work that could be delegated, thus reducing workload, improving professional satisfaction, and decreasing burnout. Direct time-motion observations validated EHR-event log data as a reliable source of information regarding clinician time allocation. © 2017 Annals of Family Medicine, Inc.

  20. Nutrient losses from manure and fertilizer applications as impacted by time to first runoff event

    International Nuclear Information System (INIS)

    Smith, D.R.; Owens, P.R.; Leytem, A.B.; Warnemuende, E.A.

    2007-01-01

    Nutrient losses to surface waters following fertilization contribute to eutrophication. This study was conducted to compare the impacts of fertilization with inorganic fertilizer, swine (Sus scrofa domesticus) manure or poultry (Gallus domesticus) litter on runoff water quality, and how the duration between application and the first runoff event affects resulting water quality. Fertilizers were applied at 35 kg P ha -1 , and the duration between application and the first runoff event varied between 1 and 29 days. Swine manure was the greatest risk to water quality 1 day after fertilization due to elevated phosphorus (8.4 mg P L -1 ) and ammonium (10.3 mg NH 4 -N L -1 ) concentrations; however, this risk decreased rapidly. Phosphorus concentrations were 2.6 mg L -1 29 days after fertilization with inorganic fertilizer. This research demonstrates that manures might be more environmentally sustainable than inorganic fertilizers, provided runoff events do not occur soon after application. - Fertilization with manures results in lower nutrient runoff than inorganic fertilizers, especially if at least one week passes between fertilization and runoff

  1. Multivariate statistical methods a first course

    CERN Document Server

    Marcoulides, George A

    2014-01-01

    Multivariate statistics refer to an assortment of statistical methods that have been developed to handle situations in which multiple variables or measures are involved. Any analysis of more than two variables or measures can loosely be considered a multivariate statistical analysis. An introductory text for students learning multivariate statistical methods for the first time, this book keeps mathematical details to a minimum while conveying the basic principles. One of the principal strategies used throughout the book--in addition to the presentation of actual data analyses--is poin

  2. Hour glass half full or half empty? Future time perspective and preoccupation with negative events across the life span.

    Science.gov (United States)

    Strough, JoNell; Bruine de Bruin, Wändi; Parker, Andrew M; Lemaster, Philip; Pichayayothin, Nipat; Delaney, Rebecca

    2016-09-01

    According to socioemotional selectivity theory, older adults' emotional well-being stems from having a limited future time perspective that motivates them to maximize well-being in the "here and now." Presumably, then, older adults' time horizons are associated with emotional competencies that boost positive affect and dampen negative affect, but little research has addressed this. Using a U.S. adult life-span sample (N = 3,933; 18-93 years), we found that a 2-factor model of future time perspective (future opportunities; limited time) fit the data better than a 1-factor model. Through middle age, people perceived the life-span hourglass as half full-they focused more on future opportunities than limited time. Around Age 60, the balance changed to increasingly perceiving the life-span hourglass as half empty-they focused less on future opportunities and more on limited time, even after accounting for perceived health, self-reported decision-making ability, and retirement status. At all ages, women's time horizons focused more on future opportunities compared with men's, and men's focused more on limited time. Focusing on future opportunities was associated with reporting less preoccupation with negative events, whereas focusing on limited time was associated with reporting more preoccupation. Older adults reported less preoccupation with negative events, and this association was stronger after controlling for their perceptions of limited time and fewer future opportunities, suggesting that other pathways may explain older adults' reports of their ability to disengage from negative events. Insights gained and questions raised by measuring future time perspective as 2 dimensions are discussed. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  3. Protocol of the Definition for the Assessment of Time-to-event Endpoints in CANcer trials (DATECAN) project: formal consensus method for the development of guidelines for standardised time-to-event endpoints' definitions in cancer clinical trials.

    Science.gov (United States)

    Bellera, Carine A; Pulido, Marina; Gourgou, Sophie; Collette, Laurence; Doussau, Adélaïde; Kramar, Andrew; Dabakuyo, Tienhan Sandrine; Ouali, Monia; Auperin, Anne; Filleron, Thomas; Fortpied, Catherine; Le Tourneau, Christophe; Paoletti, Xavier; Mauer, Murielle; Mathoulin-Pélissier, Simone; Bonnetain, Franck

    2013-03-01

    In randomised phase III cancer clinical trials, the most objectively defined and only validated time-to-event endpoint is overall survival (OS). The appearance of new types of treatments and the multiplication of lines of treatment have resulted in the use of surrogate endpoints for overall survival such as progression-free survival (PFS), or time-to-treatment failure. Their development is strongly influenced by the necessity of reducing clinical trial duration, cost and number of patients. However, while these endpoints are frequently used, they are often poorly defined and definitions can differ between trials which may limit their use as primary endpoints. Moreover, this variability of definitions can impact on the trial's results by affecting estimation of treatments' effects. The aim of the Definition for the Assessment of Time-to-event Endpoints in CANcer trials (DATECAN) project is to provide recommendations for standardised definitions of time-to-event endpoints in randomised cancer clinical trials. We will use a formal consensus methodology based on experts' opinions which will be obtained in a systematic manner. Definitions will be independently developed for several cancer sites, including pancreatic, breast, head and neck and colon cancer, as well as sarcomas and gastrointestinal stromal tumours (GISTs). The DATECAN project should lead to the elaboration of recommendations that can then be used as guidelines by researchers participating in clinical trials. This process should lead to a standardisation of the definitions of commonly used time-to-event endpoints, enabling appropriate comparisons of future trials' results. Copyright © 2012 Elsevier Ltd. All rights reserved.

  4. Hierarchy of temporal responses of multivariate self-excited epidemic processes

    Science.gov (United States)

    Saichev, Alexander; Maillart, Thomas; Sornette, Didier

    2013-04-01

    Many natural and social systems are characterized by bursty dynamics, for which past events trigger future activity. These systems can be modelled by so-called self-excited Hawkes conditional Poisson processes. It is generally assumed that all events have similar triggering abilities. However, some systems exhibit heterogeneity and clusters with possibly different intra- and inter-triggering, which can be accounted for by generalization into the "multivariate" self-excited Hawkes conditional Poisson processes. We develop the general formalism of the multivariate moment generating function for the cumulative number of first-generation and of all generation events triggered by a given mother event (the "shock") as a function of the current time t. This corresponds to studying the response function of the process. A variety of different systems have been analyzed. In particular, for systems in which triggering between events of different types proceeds through a one-dimension directed or symmetric chain of influence in type space, we report a novel hierarchy of intermediate asymptotic power law decays ˜ 1/ t 1-( m+1) θ of the rate of triggered events as a function of the distance m of the events to the initial shock in the type space, where 0 < θ < 1 for the relevant long-memory processes characterizing many natural and social systems. The richness of the generated time dynamics comes from the cascades of intermediate events of possibly different kinds, unfolding via random changes of types genealogy.

  5. Event-Based Impulsive Control of Continuous-Time Dynamic Systems and Its Application to Synchronization of Memristive Neural Networks.

    Science.gov (United States)

    Zhu, Wei; Wang, Dandan; Liu, Lu; Feng, Gang

    2017-08-18

    This paper investigates exponential stabilization of continuous-time dynamic systems (CDSs) via event-based impulsive control (EIC) approaches, where the impulsive instants are determined by certain state-dependent triggering condition. The global exponential stability criteria via EIC are derived for nonlinear and linear CDSs, respectively. It is also shown that there is no Zeno-behavior for the concerned closed loop control system. In addition, the developed event-based impulsive scheme is applied to the synchronization problem of master and slave memristive neural networks. Furthermore, a self-triggered impulsive control scheme is developed to avoid continuous communication between the master system and slave system. Finally, two numerical simulation examples are presented to illustrate the effectiveness of the proposed event-based impulsive controllers.

  6. How Repeated Time To Event (RTTE) modelling of opioid requests after surgery may improve future post-operative pain management

    DEFF Research Database (Denmark)

    Juul, Rasmus Vestergaard; Rasmussen, Sten; Kreilgaard, Mads

    at Orthopaedic Department, Aalborg University Hospital, Denmark during the period May-Dec 2012. Morphine administration times (estimated precision: ±5mins), formulations and doses were extracted from medical journals in the hospitalization period or until 96 hours after surgery. RTTE modelling was performed......Title: How Repeated Time To Event (RTTE) modelling of opioid requests after surgery may improve future post-operative pain management Author: Rasmus Vestergaard Juul (1) Sten Rasmussen (2) Mads Kreilgaard (1) Ulrika S. H. Simonsson (3) Lona Louring Christrup (1) Trine Meldgaard Lund (1) Institution...... of surgery specific, drug concentration related, population specific and/or time-varying covariates of opioid requests and pain events. Conclusions: A framework has been developed based on RTTE modelling that may help improve future pain management by 1) Identification of surgery specific patterns in pain...

  7. Vaccine adverse event monitoring systems across the European Union countries: time for unifying efforts.

    LENUS (Irish Health Repository)

    Zanoni, Giovanna

    2009-05-26

    A survey conducted among 26 European Countries within the Vaccine European New Integrated Collaboration Effort (VENICE) project assessed the status of organization in prevention and management of adverse events following immunization (AEFI) and level of interconnection, with the aim at individuating points of strength and weakness. The emerging picture is for a strong political commitment to control AEFIs in Member States (MS), but with consistent heterogeneity in procedures, regulations and capacity of systems to collect, analyze and use data, although with great potentialities. Suggestions are posed by authors to promote actions for unifying strategies and policies among MS.

  8. Real-time identification of residential appliance events based on power monitoring

    Science.gov (United States)

    Yang, Zhao; Zhu, Zhicheng; Wei, Zhiqiang; Yin, Bo; Wang, Xiuwei

    2018-03-01

    Energy monitoring for specific home appliances has been regarded as the pre-requisite for reducing residential energy consumption. To enhance the accuracy of identifying operation status of household appliances and to keep pace with the development of smart power grid, this paper puts forward the integration of electric current and power data on the basis of existing algorithm. If average power difference of several adjacent cycles varies from the baseline and goes beyond the pre-assigned threshold value, the event will be flagged. Based on MATLAB platform and domestic appliances simulations, the results of tested data and verified algorithm indicate that the power method has accomplished desired results of appliance identification.

  9. Multivariate generalized linear mixed models using R

    CERN Document Server

    Berridge, Damon Mark

    2011-01-01

    Multivariate Generalized Linear Mixed Models Using R presents robust and methodologically sound models for analyzing large and complex data sets, enabling readers to answer increasingly complex research questions. The book applies the principles of modeling to longitudinal data from panel and related studies via the Sabre software package in R. A Unified Framework for a Broad Class of Models The authors first discuss members of the family of generalized linear models, gradually adding complexity to the modeling framework by incorporating random effects. After reviewing the generalized linear model notation, they illustrate a range of random effects models, including three-level, multivariate, endpoint, event history, and state dependence models. They estimate the multivariate generalized linear mixed models (MGLMMs) using either standard or adaptive Gaussian quadrature. The authors also compare two-level fixed and random effects linear models. The appendices contain additional information on quadrature, model...

  10. Multivariable calculus with applications

    CERN Document Server

    Lax, Peter D

    2017-01-01

    This text in multivariable calculus fosters comprehension through meaningful explanations. Written with students in mathematics, the physical sciences, and engineering in mind, it extends concepts from single variable calculus such as derivative, integral, and important theorems to partial derivatives, multiple integrals, Stokes’ and divergence theorems. Students with a background in single variable calculus are guided through a variety of problem solving techniques and practice problems. Examples from the physical sciences are utilized to highlight the essential relationship between calculus and modern science. The symbiotic relationship between science and mathematics is shown by deriving and discussing several conservation laws, and vector calculus is utilized to describe a number of physical theories via partial differential equations. Students will learn that mathematics is the language that enables scientific ideas to be precisely formulated and that science is a source for the development of mathemat...

  11. Multivariate Statistical Process Control

    DEFF Research Database (Denmark)

    Kulahci, Murat

    2013-01-01

    As sensor and computer technology continues to improve, it becomes a normal occurrence that we confront with high dimensional data sets. As in many areas of industrial statistics, this brings forth various challenges in statistical process control (SPC) and monitoring for which the aim...... is to identify “out-of-control” state of a process using control charts in order to reduce the excessive variation caused by so-called assignable causes. In practice, the most common method of monitoring multivariate data is through a statistic akin to the Hotelling’s T2. For high dimensional data with excessive...... amount of cross correlation, practitioners are often recommended to use latent structures methods such as Principal Component Analysis to summarize the data in only a few linear combinations of the original variables that capture most of the variation in the data. Applications of these control charts...

  12. Screening of oil sources by using comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry and multivariate statistical analysis.

    Science.gov (United States)

    Zhang, Wanfeng; Zhu, Shukui; He, Sheng; Wang, Yanxin

    2015-02-06

    Using comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC×GC/TOFMS), volatile and semi-volatile organic compounds in crude oil samples from different reservoirs or regions were analyzed for the development of a molecular fingerprint database. Based on the GC×GC/TOFMS fingerprints of crude oils, principal component analysis (PCA) and cluster analysis were used to distinguish the oil sources and find biomarkers. As a supervised technique, the geological characteristics of crude oils, including thermal maturity, sedimentary environment etc., are assigned to the principal components. The results show that tri-aromatic steroid (TAS) series are the suitable marker compounds in crude oils for the oil screening, and the relative abundances of individual TAS compounds have excellent correlation with oil sources. In order to correct the effects of some other external factors except oil sources, the variables were defined as the content ratio of some target compounds and 13 parameters were proposed for the screening of oil sources. With the developed model, the crude oils were easily discriminated, and the result is in good agreement with the practical geological setting. Copyright © 2014 Elsevier B.V. All rights reserved.

  13. Direct analysis in real time mass spectrometry and multivariate data analysis: a novel approach to rapid identification of analytical markers for quality control of traditional Chinese medicine preparation.

    Science.gov (United States)

    Zeng, Shanshan; Wang, Lu; Chen, Teng; Wang, Yuefei; Mo, Huanbiao; Qu, Haibin

    2012-07-06

    The paper presents a novel strategy to identify analytical markers of traditional Chinese medicine preparation (TCMP) rapidly via direct analysis in real time mass spectrometry (DART-MS). A commonly used TCMP, Danshen injection, was employed as a model. The optimal analysis conditions were achieved by measuring the contribution of various experimental parameters to the mass spectra. Salvianolic acids and saccharides were simultaneously determined within a single 1-min DART-MS run. Furthermore, spectra of Danshen injections supplied by five manufacturers were processed with principal component analysis (PCA). Obvious clustering was observed in the PCA score plot, and candidate markers were recognized from the contribution plots of PCA. The suitability of potential markers was then confirmed by contrasting with the results of traditional analysis methods. Using this strategy, fructose, glucose, sucrose, protocatechuic aldehyde and salvianolic acid A were rapidly identified as the markers of Danshen injections. The combination of DART-MS with PCA provides a reliable approach to the identification of analytical markers for quality control of TCMP. Copyright © 2012 Elsevier B.V. All rights reserved.

  14. Real-time monitoring of process parameters in rice wine fermentation by a portable spectral analytical system combined with multivariate analysis.

    Science.gov (United States)

    Ouyang, Qin; Zhao, Jiewen; Pan, Wenxiu; Chen, Quansheng

    2016-01-01

    A portable and low-cost spectral analytical system was developed and used to monitor real-time process parameters, i.e. total sugar content (TSC), alcohol content (AC) and pH during rice wine fermentation. Various partial least square (PLS) algorithms were implemented to construct models. The performance of a model was evaluated by the correlation coefficient (Rp) and the root mean square error (RMSEP) in the prediction set. Among the models used, the synergy interval PLS (Si-PLS) was found to be superior. The optimal performance by the Si-PLS model for the TSC was Rp = 0.8694, RMSEP = 0.438; the AC was Rp = 0.8097, RMSEP = 0.617; and the pH was Rp = 0.9039, RMSEP = 0.0805. The stability and reliability of the system, as well as the optimal models, were verified using coefficients of variation, most of which were found to be less than 5%. The results suggest this portable system is a promising tool that could be used as an alternative method for rapid monitoring of process parameters during rice wine fermentation. Copyright © 2015 Elsevier Ltd. All rights reserved.

  15. OpenNFT: An open-source Python/Matlab framework for real-time fMRI neurofeedback training based on activity, connectivity and multivariate pattern analysis.

    Science.gov (United States)

    Koush, Yury; Ashburner, John; Prilepin, Evgeny; Sladky, Ronald; Zeidman, Peter; Bibikov, Sergei; Scharnowski, Frank; Nikonorov, Artem; De Ville, Dimitri Van

    2017-08-01

    Neurofeedback based on real-time functional magnetic resonance imaging (rt-fMRI) is a novel and rapidly developing research field. It allows for training of voluntary control over localized brain activity and connectivity and has demonstrated promising clinical applications. Because of the rapid technical developments of MRI techniques and the availability of high-performance computing, new methodological advances in rt-fMRI neurofeedback become possible. Here we outline the core components of a novel open-source neurofeedback framework, termed Open NeuroFeedback Training (OpenNFT), which efficiently integrates these new developments. This framework is implemented using Python and Matlab source code to allow for diverse functionality, high modularity, and rapid extendibility of the software depending on the user's needs. In addition, it provides an easy interface to the functionality of Statistical Parametric Mapping (SPM) that is also open-source and one of the most widely used fMRI data analysis software. We demonstrate the functionality of our new framework by describing case studies that include neurofeedback protocols based on brain activity levels, effective connectivity models, and pattern classification approaches. This open-source initiative provides a suitable framework to actively engage in the development of novel neurofeedback approaches, so that local methodological developments can be easily made accessible to a wider range of users. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  16. Multi-state model for studying an intermediate event using time-dependent covariates: application to breast cancer.

    Science.gov (United States)

    Meier-Hirmer, Carolina; Schumacher, Martin

    2013-06-20

    The aim of this article is to propose several methods that allow to investigate how and whether the shape of the hazard ratio after an intermediate event depends on the waiting time to occurrence of this event and/or the sojourn time in this state. A simple multi-state model, the illness-death model, is used as a framework to investigate the occurrence of this intermediate event. Several approaches are shown and their advantages and disadvantages are discussed. All these approaches are based on Cox regression. As different time-scales are used, these models go beyond Markov models. Different estimation methods for the transition hazards are presented. Additionally, time-varying covariates are included into the model using an approach based on fractional polynomials. The different methods of this article are then applied to a dataset consisting of four studies conducted by the German Breast Cancer Study Group (GBSG). The occurrence of the first isolated locoregional recurrence (ILRR) is studied. The results contribute to the debate on the role of the ILRR with respect to the course of the breast cancer disease and the resulting prognosis. We have investigated different modelling strategies for the transition hazard after ILRR or in general after an intermediate event. Including time-dependent structures altered the resulting hazard functions considerably and it was shown that this time-dependent structure has to be taken into account in the case of our breast cancer dataset. The results indicate that an early recurrence increases the risk of death. A late ILRR increases the hazard function much less and after the successful removal of the second tumour the risk of death is almost the same as before the recurrence. With respect to distant disease, the appearance of the ILRR only slightly increases the risk of death if the recurrence was treated successfully. It is important to realize that there are several modelling strategies for the intermediate event and that

  17. Impact of Azithromycin on Pregnancy Prolongation in Women at Risk of Preterm Labor: A Time-to-Event Analysis.

    Science.gov (United States)

    Goyer, Isabelle; Ferland, Gabrielle; Ruo, Ni; Morin, Caroline; Brochet, Marie-Sophie; Morin, Lucie; Ferreira, Ema

    2016-09-13

    Since 2006, the empiric use of azithromycin in women at risk of premature birth has become prevalent in our institution without any evidence of its efficacy. Although antibiotics can prolong pregnancy in preterm prolonged rupture of membranes, no published data are available for women with intact membranes. To describe the purpose of adding azithromycin to the usual treatments (cerclage, tocolysis, rest, etc.) to prolong pregnancy in women with intact membranes who are at risk of or already in preterm labour. A retrospective observational cohort study was done at a Mother-Child University Hospital Centre. Patients admitted to obstetric ward who received azithromycin between January 1 st , 2006 and August 1 st , 2010 were included. A total of 127 exposed women were matched to 127 controls through medical records and pharmacy software. A time-to-event analysis was done to compare gestational age at the time of the recorded composite event (delivery, or rupture of membranes, or second intervention to prolong pregnancy). To compare proportions of composite event at different time points, χ 2 tests were used. Patients who received azithromycin had a more severe condition at presentation. Once adjusted for confounding factors, prolongation of pregnancy (HR =1.049; CI 95%: 0.774-1.421 [p=0.758]) and gestational age at the event (HR=1.200; CI 95%: 0.894-1.609 [p=0.225]) did not differ between the groups. The proportions of women with an event ≥7 days post-diagnosis or ≥37 gestational weeks were similar. Azithromycin was added to medical therapy in a more at-risk population and no clear benefit was measured.

  18. Evaluation of Frequency and Restoration time for Loss of Offsite Power events based on domestic operation experience

    International Nuclear Information System (INIS)

    Park, Jin-Hee; Han, Sang-Hoon; Lee, Ho Joong

    2006-01-01

    It is recognized that the availability of AC power to nuclear power plants is essential for safe operation and shutdown and accident recovery of commercial nuclear power plants (NPPs). Unavailability of AC power can be a important adverse impact on a plant's ability to recover accident sequences and maintain safe shutdown. The probabilistic safety assessment (PSA or PRA) performed for Korea NPPs also indicated that a loss of offsite power (LOOP) event and a station blackout (SBO) event can be a important contributors to total risk at nuclear power plant, contributing from 30% to 70% of the total risk at some NPPs in Korea. But, up to now, the LOOP and subsequent restoration time are important inputs to plant probabilistic risk assessment have relied upon foreign data. Therefore, in this paper, the actual LOOP events that have occurred from 1978 to 2004 at commercial nuclear power plants in Korea are collected. A statistical analysis for LOOP frequency and restoration time are performed to apply NPPs's specific and realistic risk model in Korea. Additionally, an engineering analysis is also performed to obtain the insights about the LOOP events

  19. Hand-wrist and cervical vertebral maturation indicators: how can these events be used to time Class II treatments?

    Science.gov (United States)

    Grave, Keith; Townsend, Grant

    2003-11-01

    Ossification events in the hand and wrist and in the cervical vertebrae have been shown to occur at specific times before, during and after the adolescent growth spurt, but there is still debate about the applicability of these findings to the clinical management of Class II cases. The aim of this study was to relate, on an individual basis, cervical vertebral maturation stages and hand-wrist ossification events to the timing of peak statural and mandibular growth in a group of indigenous Australians. Velocity curves for stature and mandibular growth were constructed for 47 boys and 27 girls, and maturation events were then plotted on the curves. For the majority of children, peak velocity in mandibular growth coincided with peak velocity in stature. Particular combinations of hand-wrist and cervical maturation events occurred consistently before, during or after the adolescent growth spurt. Our findings are consistent with those for North American children and we believe that assessment by orthodontists of a combination of hand-wrist and cervical vertebral maturation stages will enhance prediction of the adolescent growth spurt, thereby contributing to a positive, purposeful and more confident approach to the management of Class II cases.

  20. Complex analyses on clinical information systems using restricted natural language querying to resolve time-event dependencies.

    Science.gov (United States)

    Safari, Leila; Patrick, Jon D

    2018-06-01

    This paper reports on a generic framework to provide clinicians with the ability to conduct complex analyses on elaborate research topics using cascaded queries to resolve internal time-event dependencies in the research questions, as an extension to the proposed Clinical Data Analytics Language (CliniDAL). A cascaded query model is proposed to resolve internal time-event dependencies in the queries which can have up to five levels of criteria starting with a query to define subjects to be admitted into a study, followed by a query to define the time span of the experiment. Three more cascaded queries can be required to define control groups, control variables and output variables which all together simulate a real scientific experiment. According to the complexity of the research questions, the cascaded query model has the flexibility of merging some lower level queries for simple research questions or adding a nested query to each level to compose more complex queries. Three different scenarios (one of them contains two studies) are described and used for evaluation of the proposed solution. CliniDAL's complex analyses solution enables answering complex queries with time-event dependencies at most in a few hours which manually would take many days. An evaluation of results of the research studies based on the comparison between CliniDAL and SQL solutions reveals high usability and efficiency of CliniDAL's solution. Copyright © 2018 Elsevier Inc. All rights reserved.

  1. Event- and Time-Driven Techniques Using Parallel CPU-GPU Co-processing for Spiking Neural Networks.

    Science.gov (United States)

    Naveros, Francisco; Garrido, Jesus A; Carrillo, Richard R; Ros, Eduardo; Luque, Niceto R

    2017-01-01

    Modeling and simulating the neural structures which make up our central neural system is instrumental for deciphering the computational neural cues beneath. Higher levels of biological plausibility usually impose higher levels of complexity in mathematical modeling, from neural to behavioral levels. This paper focuses on overcoming the simulation problems (accuracy and performance) derived from using higher levels of mathematical complexity at a neural level. This study proposes different techniques for simulating neural models that hold incremental levels of mathematical complexity: leaky integrate-and-fire (LIF), adaptive exponential integrate-and-fire (AdEx), and Hodgkin-Huxley (HH) neural models (ranged from low to high neural complexity). The studied techniques are classified into two main families depending on how the neural-model dynamic evaluation is computed: the event-driven or the time-driven families. Whilst event-driven techniques pre-compile and store the neural dynamics within look-up tables, time-driven techniques compute the neural dynamics iteratively during the simulation time. We propose two modifications for the event-driven family: a look-up table recombination to better cope with the incremental neural complexity together with a better handling of the synchronous input activity. Regarding the time-driven family, we propose a modification in computing the neural dynamics: the bi-fixed-step integration method. This method automatically adjusts the simulation step size to better cope with the stiffness of the neural model dynamics running in CPU platforms. One version of this method is also implemented for hybrid CPU-GPU platforms. Finally, we analyze how the performance and accuracy of these modifications evolve with increasing levels of neural complexity. We also demonstrate how the proposed modifications which constitute the main contribution of this study systematically outperform the traditional event- and time-driven techniques under

  2. Performance of joint modelling of time-to-event data with time-dependent predictors: an assessment based on transition to psychosis data

    Directory of Open Access Journals (Sweden)

    Hok Pan Yuen

    2016-10-01

    Full Text Available Joint modelling has emerged to be a potential tool to analyse data with a time-to-event outcome and longitudinal measurements collected over a series of time points. Joint modelling involves the simultaneous modelling of the two components, namely the time-to-event component and the longitudinal component. The main challenges of joint modelling are the mathematical and computational complexity. Recent advances in joint modelling have seen the emergence of several software packages which have implemented some of the computational requirements to run joint models. These packages have opened the door for more routine use of joint modelling. Through simulations and real data based on transition to psychosis research, we compared joint model analysis of time-to-event outcome with the conventional Cox regression analysis. We also compared a number of packages for fitting joint models. Our results suggest that joint modelling do have advantages over conventional analysis despite its potential complexity. Our results also suggest that the results of analyses may depend on how the methodology is implemented.

  3. Memory for emotional events: The role of time of testing and type of test

    Directory of Open Access Journals (Sweden)

    Priscila Goergen Brust

    2012-03-01

    Full Text Available The impact of emotion on memory performance is widely debated in the scientific literature. In the present paper, the relation between emotion and memory was addressed in three experiments using the Slideshow Procedure. In the first experiment, 128 participants’ memory was tested for one of two versions of the Procedure (arousal or neutral through free recall. In the second experiment, 75 participants were asked to recall the information of the arousal version immediately after or one week after watching it. In the third experiment, 75 participants watched the arousal version and answered either a free recall or a recognition test one week after. The results suggested that memory for arousal events is better when tested immediately after the stimuli using free recall.

  4. Reducing uncertainty in Climate Response Time Scale by Bayesian Analysis of the 8.2 ka event

    Science.gov (United States)

    Lorenz, A.; Held, H.; Bauer, E.; Schneider von Deimling, T.

    2009-04-01

    We analyze the possibility of uncertainty reduction in Climate Response Time Scale by utilizing Greenland ice-core data that contain the 8.2 ka event within a Bayesian model-data intercomparison with the Earth system model of intermediate complexity, CLIMBER-2.3. Within a stochastic version of the model it has been possible to mimic the 8.2 ka event within a plausible experimental setting and with relatively good accuracy considering the timing of the event in comparison to other modeling exercises [1]. The simulation of the centennial cold event is effectively determined by the oceanic cooling rate which depends largely on the ocean diffusivity described by diffusion coefficients of relatively wide uncertainty ranges. The idea now is to discriminate between the different values of diffusivities according to their likelihood to rightly represent the duration of the 8.2 ka event and thus to exploit the paleo data to constrain uncertainty in model parameters in analogue to [2]. Implementing this inverse Bayesian Analysis with this model the technical difficulty arises to establish the related likelihood numerically in addition to the uncertain model parameters: While mainstream uncertainty analyses can assume a quasi-Gaussian shape of likelihood, with weather fluctuating around a long term mean, the 8.2 ka event as a highly nonlinear effect precludes such an a priori assumption. As a result of this study [3] the Bayesian Analysis showed a reduction of uncertainty in vertical ocean diffusivity parameters of factor 2 compared to prior knowledge. This learning effect on the model parameters is propagated to other model outputs of interest; e.g. the inverse ocean heat capacity, which is important for the dominant time scale of climate response to anthropogenic forcing which, in combination with climate sensitivity, strongly influences the climate systems reaction for the near- and medium-term future. 1 References [1] E. Bauer, A. Ganopolski, M. Montoya: Simulation of the

  5. Estimation of train dwell time at short stops based on track occupation event data

    NARCIS (Netherlands)

    Li, D.; Daamen, W.; Goverde, R.M.P.

    2015-01-01

    Train dwell time is one of the most unpredictable components of railway operations mainly due to the varying volumes of alighting and boarding passengers. For reliable estimations of train running times and route conflicts on main lines it is however necessary to obtain accurate estimations of dwell

  6. Non-linear time series extreme events and integer value problems

    CERN Document Server

    Turkman, Kamil Feridun; Zea Bermudez, Patrícia

    2014-01-01

    This book offers a useful combination of probabilistic and statistical tools for analyzing nonlinear time series. Key features of the book include a study of the extremal behavior of nonlinear time series and a comprehensive list of nonlinear models that address different aspects of nonlinearity. Several inferential methods, including quasi likelihood methods, sequential Markov Chain Monte Carlo Methods and particle filters, are also included so as to provide an overall view of the available tools for parameter estimation for nonlinear models. A chapter on integer time series models based on several thinning operations, which brings together all recent advances made in this area, is also included. Readers should have attended a prior course on linear time series, and a good grasp of simulation-based inferential methods is recommended. This book offers a valuable resource for second-year graduate students and researchers in statistics and other scientific areas who need a basic understanding of nonlinear time ...

  7. An Exponential Tilt Mixture Model for Time-to-Event Data to Evaluate Treatment Effect Heterogeneity in Randomized Clinical Trials.

    Science.gov (United States)

    Wang, Chi; Tan, Zhiqiang; Louis, Thomas A

    2014-01-01

    Evaluating the effect of a treatment on a time-to-event outcome is the focus of many randomized clinical trials. It is often observed that the treatment effect is heterogeneous, where only a subgroup of the patients may respond to the treatment due to some unknown mechanism such as genetic polymorphism. In this paper, we propose a semiparametric exponential tilt mixture model to estimate the proportion of patients who respond to the treatment and to assess the treatment effect. Our model is a natural extension of parametric mixture models to a semiparametric setting with a time-to-event outcome. We propose a nonparametric maximum likelihood estimation approach for inference and establish related asymptotic properties. Our method is illustrated by a randomized clinical trial on biodegradable polymer-delivered chemotherapy for malignant gliomas patients.

  8. Multivariate analysis techniques

    Energy Technology Data Exchange (ETDEWEB)

    Bendavid, Josh [European Organization for Nuclear Research (CERN), Geneva (Switzerland); Fisher, Wade C. [Michigan State Univ., East Lansing, MI (United States); Junk, Thomas R. [Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)

    2016-01-01

    The end products of experimental data analysis are designed to be simple and easy to understand: hypothesis tests and measurements of parameters. But, the experimental data themselves are voluminous and complex. Furthermore, in modern collider experiments, many petabytes of data must be processed in search of rare new processes which occur together with much more copious background processes that are of less interest to the task at hand. The systematic uncertainties on the background may be larger than the expected signal in many cases. The statistical power of an analysis and its sensitivity to systematic uncertainty can therefore usually both be improved by separating signal events from background events with higher efficiency and purity.

  9. Multivariate statistical methods a primer

    CERN Document Server

    Manly, Bryan FJ

    2004-01-01

    THE MATERIAL OF MULTIVARIATE ANALYSISExamples of Multivariate DataPreview of Multivariate MethodsThe Multivariate Normal DistributionComputer ProgramsGraphical MethodsChapter SummaryReferencesMATRIX ALGEBRAThe Need for Matrix AlgebraMatrices and VectorsOperations on MatricesMatrix InversionQuadratic FormsEigenvalues and EigenvectorsVectors of Means and Covariance MatricesFurther Reading Chapter SummaryReferencesDISPLAYING MULTIVARIATE DATAThe Problem of Displaying Many Variables in Two DimensionsPlotting index VariablesThe Draftsman's PlotThe Representation of Individual Data P:ointsProfiles o

  10. Series distance – an intuitive metric to quantify hydrograph similarity in terms of occurrence, amplitude and timing of hydrological events

    Directory of Open Access Journals (Sweden)

    U. Ehret

    2011-03-01

    Full Text Available Applying metrics to quantify the similarity or dissimilarity of hydrographs is a central task in hydrological modelling, used both in model calibration and the evaluation of simulations or forecasts. Motivated by the shortcomings of standard objective metrics such as the Root Mean Square Error (RMSE or the Mean Absolute Peak Time Error (MAPTE and the advantages of visual inspection as a powerful tool for simultaneous, case-specific and multi-criteria (yet subjective evaluation, we propose a new objective metric termed Series Distance, which is in close accordance with visual evaluation. The Series Distance quantifies the similarity of two hydrographs neither in a time-aggregated nor in a point-by-point manner, but on the scale of hydrological events. It consists of three parts, namely a Threat Score which evaluates overall agreement of event occurrence, and the overall distance of matching observed and simulated events with respect to amplitude and timing. The novelty of the latter two is the way in which matching point pairs on the observed and simulated hydrographs are identified: not by equality in time (as is the case with the RMSE, but by the same relative position in matching segments (rise or recession of the event, indicating the same underlying hydrological process. Thus, amplitude and timing errors are calculated simultaneously but separately, from point pairs that also match visually, considering complete events rather than only individual points (as is the case with MAPTE. Relative weights can freely be assigned to each component of the Series Distance, which allows (subjective customization of the metric to various fields of application, but in a traceable way. Each of the three components of the Series Distance can be used in an aggregated or non-aggregated way, which makes the Series Distance a suitable tool for differentiated, process-based model diagnostics.

    After discussing the applicability of established time series

  11. Effect of weather and time on trauma events determined using emergency medical service registry data.

    Science.gov (United States)

    Lin, Li-Wei; Lin, Hsiao-Yu; Hsu, Chien-Yeh; Rau, Hsiao-Hsien; Chen, Ping-Ling

    2015-09-01

    Trauma admissions are associated with weather and temporal factors; however, previous study results regarding these factors are contradictory. We hypothesised that weather and temporal factors have different effects on specific trauma events in an emergency medical service (EMS) system. EMS data from January 1, 2009, to December 31, 2010, were obtained from the fire department of Taipei City and associated with the local weather data. EMS trauma events were categorised into total trauma, traffic accidents (TAs), motorbike accidents (MBAs), and falls. Hourly data on trauma patients were analysed using the zero-inflated Poisson model. The hourly incidence of total trauma increased with the magnitude of precipitation (incidence rate ratio [IRR]=1.06, 1.09, and 1.11 in light, moderate, and heavy rain, respectively), and this effect was more prominent in fall patients than in patients with other injuries (IRR=1.07, 1.21, and 1.32). However, the hourly incidence of TAs and MBAs was associated only with light rain (IRR=1.11 and 1.06, respectively). An hour of sunshine exposure was associated with an increase in the hourly incidence of all groups, and higher temperatures were associated with an increased hourly incidence of total trauma, TAs, and MBAs, but not falls. The hourly incidence of falls increased only in late fall and winter. Compared with the hourly incidence between 3 am and 7 am, the hourly incidence of all groups plateaued between 7 am and 11 pm and declined from 11 pm to 3 am. During the plateau period, 2 peaks in the incidence of TAs (IRR=5.03 and 5.07, respectively) and MBAs (IRR=5.81 and 5.51, respectively) were observed during 7-11 am and 3-7 pm. The hourly incidence of total trauma, TAs, and MBAs plateaued during workdays, peaked on Fridays, declined on Saturdays, and troughed on Sundays. The incidence of falls increased only on Mondays (IRR=1.09). Weather and temporal factors had different impacts on the incidence of traffic-related accidents and falls

  12. Considerations for analysis of time-to-event outcomes measured with error: Bias and correction with SIMEX.

    Science.gov (United States)

    Oh, Eric J; Shepherd, Bryan E; Lumley, Thomas; Shaw, Pamela A

    2018-04-15

    For time-to-event outcomes, a rich literature exists on the bias introduced by covariate measurement error in regression models, such as the Cox model, and methods of analysis to address this bias. By comparison, less attention has been given to understanding the impact or addressing errors in the failure time outcome. For many diseases, the timing of an event of interest (such as progression-free survival or time to AIDS progression) can be difficult to assess or reliant on self-report and therefore prone to measurement error. For linear models, it is well known that random errors in the outcome variable do not bias regression estimates. With nonlinear models, however, even random error or misclassification can introduce bias into estimated parameters. We compare the performance of 2 common regression models, the Cox and Weibull models, in the setting of measurement error in the failure time outcome. We introduce an extension of the SIMEX method to correct for bias in hazard ratio estimates from the Cox model and discuss other analysis options to address measurement error in the response. A formula to estimate the bias induced into the hazard ratio by classical measurement error in the event time for a log-linear survival model is presented. Detailed numerical studies are presented to examine the performance of the proposed SIMEX method under varying levels and parametric forms of the error in the outcome. We further illustrate the method with observational data on HIV outcomes from the Vanderbilt Comprehensive Care Clinic. Copyright © 2017 John Wiley & Sons, Ltd.

  13. Time-to-event analysis as a framework for quantifying fish passage performance: Chapter 9.1

    Science.gov (United States)

    Castro-Santos, Theodore R.; Perry, Russell W.; Adams, Noah S.; Beeman, John W.; Eiler, John H.

    2012-01-01

    Fish passage is the result of a sequence of processes, whereby fish must approach, enter, and pass a structure. Each of these processes takes time, and fishway performance is best quantified in terms of the rates at which each process is completed. Optimal performance is achieved by maximizing the rates of approach, entry, and passage through safe and desirable routes. Sometimes, however, it is necessary to reduce rates of passage through less desirable routes in order to increase proportions passing through the preferred route. Effectiveness of operational or structural modifications for achieving either of these goals is best quantified by applying time-to-event analysis, commonly known as survival analysis methods, to telemetry data. This set of techniques allows for accurate estimation of passage rates and covariate effects on those rates. Importantly, it allows researchers to quantify rates that vary over time, as well as the effects of covariates that also vary over time. Finally, these methods are able to control for competing risks, i.e., the presence of alternate passage routes, failure to pass, or other fates that remove fish from the pool of candidates available to pass through a particular route. In this chapter, we present a model simulation of telemetered fish passing a hydroelectric dam, and provide step-by-step guidance and rationales for performing time-to-event analysis on the resulting data. We demonstrate how this approach removes bias from performance estimates that can result from using methods that focus only on proportions passing each route. Time-to-event analysis, coupled with multinomial models for measuring survival, provides a comprehensive set of techniques for quantifying fish passage, and a framework from which performance among different sites can be better understood.

  14. Complex networks from multivariate time series

    Czech Academy of Sciences Publication Activity Database

    Paluš, Milan; Hartman, David; Vejmelka, Martin

    2010-01-01

    Roč. 12, - (2010), A-14382 ISSN 1607-7962. [General Asembly of the European Geophysical Society. 02.05.2010-07.05.2010, Vienna] R&D Projects: GA AV ČR IAA300420805 Institutional research plan: CEZ:AV0Z10300504 Keywords : complex network * surface air temperature * reanalysis data * global change Subject RIV: BB - Applied Statistics, Operational Research

  15. Structural Equation Modeling of Multivariate Time Series

    Science.gov (United States)

    du Toit, Stephen H. C.; Browne, Michael W.

    2007-01-01

    The covariance structure of a vector autoregressive process with moving average residuals (VARMA) is derived. It differs from other available expressions for the covariance function of a stationary VARMA process and is compatible with current structural equation methodology. Structural equation modeling programs, such as LISREL, may therefore be…

  16. Multivariate Time Series Estimation using marima

    DEFF Research Database (Denmark)

    Spliid, Henrik

    2016-01-01

    A computer program, called marima, written in the open source language, R, has been developed. Some of marima’s facilities and ideas are presented in the following.......A computer program, called marima, written in the open source language, R, has been developed. Some of marima’s facilities and ideas are presented in the following....

  17. Vision-based Detection of Acoustic Timed Events: a Case Study on Clarinet Note Onsets

    Science.gov (United States)

    Bazzica, A.; van Gemert, J. C.; Liem, C. C. S.; Hanjalic, A.

    2017-05-01

    Acoustic events often have a visual counterpart. Knowledge of visual information can aid the understanding of complex auditory scenes, even when only a stereo mixdown is available in the audio domain, \\eg identifying which musicians are playing in large musical ensembles. In this paper, we consider a vision-based approach to note onset detection. As a case study we focus on challenging, real-world clarinetist videos and carry out preliminary experiments on a 3D convolutional neural network based on multiple streams and purposely avoiding temporal pooling. We release an audiovisual dataset with 4.5 hours of clarinetist videos together with cleaned annotations which include about 36,000 onsets and the coordinates for a number of salient points and regions of interest. By performing several training trials on our dataset, we learned that the problem is challenging. We found that the CNN model is highly sensitive to the optimization algorithm and hyper-parameters, and that treating the problem as binary classification may prevent the joint optimization of precision and recall. To encourage further research, we publicly share our dataset, annotations and all models and detail which issues we came across during our preliminary experiments.

  18. Biases in the perceived timing of perisaccadic perceptual and motor events

    DEFF Research Database (Denmark)

    Yarrow, Kielan; Whiteley, Louise Emma; Haggard, Patrick

    2006-01-01

    Subjects typically experience the temporal interval immediately following a saccade as longer than a comparable control interval. One explanation of this effect is that the brain antedates the perceptual onset of a saccade target to around the time of saccade initiation. This could explain...

  19. Mediated priming in the lexical decision task : Evidence from event-related potentials and reaction time

    NARCIS (Netherlands)

    Chwilla, DJ; Kolk, HHJ; Mulder, G

    Mediated priming (e.g., from LION to STRIPES vis TIGER) is predicted by spreading activation models hut only by some integration model. The goal of the present research was to localize mediated priming by assessing two-step priming effects on N400 and reaction times (RT). We propose that the N400

  20. Relating Derived Relations as a Model of Analogical Reasoning: Reaction Times and Event-Related Potentials

    Science.gov (United States)

    Barnes-Holmes, Dermot; Regan, Donal; Barnes-Holmes, Yvonne; Commins, Sean; Walsh, Derek; Stewart, Ian; Smeets, Paul M.; Whelan, Robert; Dymond, Simon

    2005-01-01

    The current study aimed to test a Relational Frame Theory (RFT) model of analogical reasoning based on the relating of derived same and derived difference relations. Experiment 1 recorded reaction time measures of similar-similar (e.g., "apple is to orange as dog is to cat") versus different-different (e.g., "he is to his brother as…

  1. Origins of forecast skill of weather and climate events on verifiable time scales

    CSIR Research Space (South Africa)

    Landman, WA

    2012-07-01

    Full Text Available specific location between the predictor or the predictand and their respective canonical component time series (rj and sk) Barnett, T. P., and Preisendorfer, R. W. 1987: Origins and levels of monthly and seasonal forecast skill for United States air...

  2. Ultra-high throughput real-time instruments for capturing fast signals and rare events

    Science.gov (United States)

    Buckley, Brandon Walter

    Wide-band signals play important roles in the most exciting areas of science, engineering, and medicine. To keep up with the demands of exploding internet traffic, modern data centers and communication networks are employing increasingly faster data rates. Wide-band techniques such as pulsed radar jamming and spread spectrum frequency hopping are used on the battlefield to wrestle control of the electromagnetic spectrum. Neurons communicate with each other using transient action potentials that last for only milliseconds at a time. And in the search for rare cells, biologists flow large populations of cells single file down microfluidic channels, interrogating them one-by-one, tens of thousands of times per second. Studying and enabling such high-speed phenomena pose enormous technical challenges. For one, parasitic capacitance inherent in analog electrical components limits their response time. Additionally, converting these fast analog signals to the digital domain requires enormous sampling speeds, which can lead to significant jitter and distortion. State-of-the-art imaging technologies, essential for studying biological dynamics and cells in flow, are limited in speed and sensitivity by finite charge transfer and read rates, and by the small numbers of photo-electrons accumulated in short integration times. And finally, ultra-high throughput real-time digital processing is required at the backend to analyze the streaming data. In this thesis, I discuss my work in developing real-time instruments, employing ultrafast optical techniques, which overcome some of these obstacles. In particular, I use broadband dispersive optics to slow down fast signals to speeds accessible to high-bit depth digitizers and signal processors. I also apply telecommunication multiplexing techniques to boost the speeds of confocal fluorescence microscopy. The photonic time stretcher (TiSER) uses dispersive Fourier transformation to slow down analog signals before digitization and

  3. Sub-seasonal Predictability of Heavy Precipitation Events: Implication for Real-time Flood Management in Iran

    Science.gov (United States)

    Najafi, H.; Shahbazi, A.; Zohrabi, N.; Robertson, A. W.; Mofidi, A.; Massah Bavani, A. R.

    2016-12-01

    Each year, a number of high impact weather events occur worldwide. Since any level of predictability at sub-seasonal to seasonal timescale is highly beneficial to society, international efforts is now on progress to promote reliable Ensemble Prediction Systems for monthly forecasts within the WWRP/WCRP initiative (S2S) project and North American Multi Model Ensemble (NMME). For water resources managers in the face of extreme events, not only can reliable forecasts of high impact weather events prevent catastrophic losses caused by floods but also contribute to benefits gained from hydropower generation and water markets. The aim of this paper is to analyze the predictability of recent severe weather events over Iran. Two recent heavy precipitations are considered as an illustration to examine whether S2S forecasts can be used for developing flood alert systems especially where large cascade of dams are in operation. Both events have caused major damages to cities and infrastructures. The first severe precipitation was is in the early November 2015 when heavy precipitation (more than 50 mm) occurred in 2 days. More recently, up to 300 mm of precipitation is observed within less than a week in April 2016 causing a consequent flash flood. Over some stations, the observed precipitation was even more than the total annual mean precipitation. To analyze the predictive capability, ensemble forecasts from several operational centers including (European Centre for Medium-Range Weather Forecasts (ECMWF) system, Climate Forecast System Version 2 (CFSv2) and Chinese Meteorological Center (CMA) are evaluated. It has been observed that significant changes in precipitation anomalies were likely to be predicted days in advance. The next step will be to conduct thorough analysis based on comparing multi-model outputs over the full hindcast dataset developing real-time high impact weather prediction systems.

  4. Multivariate supOU processes

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole Eiler; Stelzer, Robert

    Univariate superpositions of Ornstein-Uhlenbeck (OU) type processes, called supOU processes, provide a class of continuous time processes capable of exhibiting long memory behaviour. This paper introduces multivariate supOU processes and gives conditions for their existence and finiteness...... of moments. Moreover, the second order moment structure is explicitly calculated, and examples exhibit the possibility of long range dependence. Our supOU processes are defined via homogeneous and factorisable Lévy bases. We show that the behaviour of supOU processes is particularly nice when the mean...... reversion parameter is restricted to normal matrices and especially to strictly negative definite ones.For finite variation Lévy bases we are able to give conditions for supOU processes to have locally bounded càdlàg paths of finite variation and to show an analogue of the stochastic differential equation...

  5. Multivariate supOU processes

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole Eiler; Stelzer, Robert

    2011-01-01

    Univariate superpositions of Ornstein–Uhlenbeck-type processes (OU), called supOU processes, provide a class of continuous time processes capable of exhibiting long memory behavior. This paper introduces multivariate supOU processes and gives conditions for their existence and finiteness of moments....... Moreover, the second-order moment structure is explicitly calculated, and examples exhibit the possibility of long-range dependence. Our supOU processes are defined via homogeneous and factorizable Lévy bases. We show that the behavior of supOU processes is particularly nice when the mean reversion...... parameter is restricted to normal matrices and especially to strictly negative definite ones. For finite variation Lévy bases we are able to give conditions for supOU processes to have locally bounded càdlàg paths of finite variation and to show an analogue of the stochastic differential equation of OU...

  6. Generalized Robertson-Walker Space-Time Admitting Evolving Null Horizons Related to a Black Hole Event Horizon.

    Science.gov (United States)

    Duggal, K L

    2016-01-01

    A new technique is used to study a family of time-dependent null horizons, called " Evolving Null Horizons " (ENHs), of generalized Robertson-Walker (GRW) space-time [Formula: see text] such that the metric [Formula: see text] satisfies a kinematic condition. This work is different from our early papers on the same issue where we used (1 + n )-splitting space-time but only some special subcases of GRW space-time have this formalism. Also, in contrast to previous work, we have proved that each member of ENHs is totally umbilical in [Formula: see text]. Finally, we show that there exists an ENH which is always a null horizon evolving into a black hole event horizon and suggest some open problems.

  7. Event-sequence time series analysis in ground-based gamma-ray astronomy

    International Nuclear Information System (INIS)

    Barres de Almeida, U.; Chadwick, P.; Daniel, M.; Nolan, S.; McComb, L.

    2008-01-01

    The recent, extreme episodes of variability detected from Blazars by the leading atmospheric Cerenkov experiments motivate the development and application of specialized statistical techniques that enable the study of this rich data set to its furthest extent. The identification of the shortest variability timescales supported by the data and the actual variability structure observed in the light curves of these sources are some of the fundamental aspects being studied, that answers can bring new developments on the understanding of the physics of these objects and on the mechanisms of production of VHE gamma-rays in the Universe. Some of our efforts in studying the time variability of VHE sources involve the application of dynamic programming algorithms to the problem of detecting change-points in a Poisson sequence. In this particular paper we concentrate on the more primary issue of the applicability of counting statistics to the analysis of time-series on VHE gamma-ray astronomy.

  8. Aligning Event Logs to Task-Time Matrix Clinical Pathways in BPMN for Variance Analysis.

    Science.gov (United States)

    Yan, Hui; Van Gorp, Pieter; Kaymak, Uzay; Lu, Xudong; Ji, Lei; Chiau, Choo Chiap; Korsten, Hendrikus H M; Duan, Huilong

    2018-03-01

    Clinical pathways (CPs) are popular healthcare management tools to standardize care and ensure quality. Analyzing CP compliance levels and variances is known to be useful for training and CP redesign purposes. Flexible semantics of the business process model and notation (BPMN) language has been shown to be useful for the modeling and analysis of complex protocols. However, in practical cases one may want to exploit that CPs often have the form of task-time matrices. This paper presents a new method parsing complex BPMN models and aligning traces to the models heuristically. A case study on variance analysis is undertaken, where a CP from the practice and two large sets of patients data from an electronic medical record (EMR) database are used. The results demonstrate that automated variance analysis between BPMN task-time models and real-life EMR data are feasible, whereas that was not the case for the existing analysis techniques. We also provide meaningful insights for further improvement.

  9. Analysis of time to event outcomes in randomized controlled trials by generalized additive models.

    Directory of Open Access Journals (Sweden)

    Christos Argyropoulos

    Full Text Available Randomized Controlled Trials almost invariably utilize the hazard ratio calculated with a Cox proportional hazard model as a treatment efficacy measure. Despite the widespread adoption of HRs, these provide a limited understanding of the treatment effect and may even provide a biased estimate when the assumption of proportional hazards in the Cox model is not verified by the trial data. Additional treatment effect measures on the survival probability or the time scale may be used to supplement HRs but a framework for the simultaneous generation of these measures is lacking.By splitting follow-up time at the nodes of a Gauss Lobatto numerical quadrature rule, techniques for Poisson Generalized Additive Models (PGAM can be adopted for flexible hazard modeling. Straightforward simulation post-estimation transforms PGAM estimates for the log hazard into estimates of the survival function. These in turn were used to calculate relative and absolute risks or even differences in restricted mean survival time between treatment arms. We illustrate our approach with extensive simulations and in two trials: IPASS (in which the proportionality of hazards was violated and HEMO a long duration study conducted under evolving standards of care on a heterogeneous patient population.PGAM can generate estimates of the survival function and the hazard ratio that are essentially identical to those obtained by Kaplan Meier curve analysis and the Cox model. PGAMs can simultaneously provide multiple measures of treatment efficacy after a single data pass. Furthermore, supported unadjusted (overall treatment effect but also subgroup and adjusted analyses, while incorporating multiple time scales and accounting for non-proportional hazards in survival data.By augmenting the HR conventionally reported, PGAMs have the potential to support the inferential goals of multiple stakeholders involved in the evaluation and appraisal of clinical trial results under proportional and

  10. Near Real-Time Event Detection & Prediction Using Intelligent Software Agents

    Science.gov (United States)

    2006-03-01

    value was 0.06743. Multiple autoregressive integrated moving average ( ARIMA ) models were then build to see if the raw data, differenced data, or...slight improvement. The best adjusted r^2 value was found to be 0.1814. Successful results were not expected from linear or ARIMA -based modelling ...appear, 2005. [63] Mora-Lopez, L., Mora, J., Morales-Bueno, R., et al. Modelling time series of climatic parameters with probabilistic finite

  11. Structure and Randomness of Continuous-Time, Discrete-Event Processes

    Science.gov (United States)

    Marzen, Sarah E.; Crutchfield, James P.

    2017-10-01

    Loosely speaking, the Shannon entropy rate is used to gauge a stochastic process' intrinsic randomness; the statistical complexity gives the cost of predicting the process. We calculate, for the first time, the entropy rate and statistical complexity of stochastic processes generated by finite unifilar hidden semi-Markov models—memoryful, state-dependent versions of renewal processes. Calculating these quantities requires introducing novel mathematical objects (ɛ -machines of hidden semi-Markov processes) and new information-theoretic methods to stochastic processes.

  12. Time Series Modeling of Army Mission Command Communication Networks: An Event-Driven Analysis

    Science.gov (United States)

    2013-06-01

    Lehmann, D. R. (1984). How advertising affects sales: Meta- analysis of econometric results. Journal of Marketing Research , 21, 65-74. Barabási, A. L...317-357. Leone, R. P. (1983). Modeling sales-advertising relationships: An integrated time series- econometric approach. Journal of Marketing ... Research , 20, 291-295. McGrath, J. E., & Kravitz, D. A. (1982). Group research. Annual Review of Psychology, 33, 195- 230. Monge, P. R., & Contractor

  13. American West Tephras – Geomagnetic polarity events redefined through calibration of radio-isotopic and astronomical time

    DEFF Research Database (Denmark)

    Rivera, Tiffany; Storey, Michael

    calibration. Although this geomagnetic event is not part of the most recent geologic timescale, refined ages on short-lived excursions could hold importance to understanding time scales for the wavering nature of Earth’s magnetic field. We propose a new 40Ar/39Ar age for the Quaternary mineral dating standard......The foundation of the EARTHTIME/GTSnext initiative seeks to construct an internally consistent geologic timescale based on astronomical and radio-isotopic geochronology. American west tephras offer a prime opportunity to integrate these two independent timescales with the geomagnetic timescale....... Using an astronomically calibrated age for the monitor mineral Fish Canyon sanidine (FCs;28.201 ± 0.046 Ma, Kuiper, et al., 2008), ages of Pleistocene geomagnetic polarity events are reexamined. Of particular interest, the Quaternary mineral dating standard Alder Creek sandine (ACs) is the type locality...

  14. Time-Shift Correlation Algorithm for P300 Event Related Potential Brain-Computer Interface Implementation

    Directory of Open Access Journals (Sweden)

    Ju-Chi Liu

    2016-01-01

    Full Text Available A high efficient time-shift correlation algorithm was proposed to deal with the peak time uncertainty of P300 evoked potential for a P300-based brain-computer interface (BCI. The time-shift correlation series data were collected as the input nodes of an artificial neural network (ANN, and the classification of four LED visual stimuli was selected as the output node. Two operating modes, including fast-recognition mode (FM and accuracy-recognition mode (AM, were realized. The proposed BCI system was implemented on an embedded system for commanding an adult-size humanoid robot to evaluate the performance from investigating the ground truth trajectories of the humanoid robot. When the humanoid robot walked in a spacious area, the FM was used to control the robot with a higher information transfer rate (ITR. When the robot walked in a crowded area, the AM was used for high accuracy of recognition to reduce the risk of collision. The experimental results showed that, in 100 trials, the accuracy rate of FM was 87.8% and the average ITR was 52.73 bits/min. In addition, the accuracy rate was improved to 92% for the AM, and the average ITR decreased to 31.27 bits/min. due to strict recognition constraints.

  15. Time response of protection in event of vacuum failure based on Nude ionization gauge controller

    Science.gov (United States)

    Gao, Hui; Wang, Qiuping; Wang, Weibin; Wu, Qinglin; Chen, Wentong; Sheng, Liusi; Zhang, Yunwu

    2001-10-01

    This article describes the design and application of fast-response vacuum protection sensor module, based on the Nude ionization gauge and a homemade controller named GH07X. A simulative test indicated that the controller's response time was less than 200 μs when 1 atm air rushed into the vacuum system through a pulsed valve with 0.8 mm orifice nozzle and the emitting current of the Nude gauge was 4 mA. The experiment result showed that the response time mainly depended on the gas density as well as the electron emitting current of the Nude gauge filament. Compared with the vacuum protection sensors based on sputter ion pump and cold-cathode gauge, GH07X is faster and reliable besides, GH07X can be used as an ultrahigh-vacuum slow valve interlock controller with response time of 100 ms, which is faster than other gauge controllers. The widely used field-bus interface CAN and common serial interface RS232/RS485 are embedded in GH07X controller system.

  16. Time-Shift Correlation Algorithm for P300 Event Related Potential Brain-Computer Interface Implementation.

    Science.gov (United States)

    Liu, Ju-Chi; Chou, Hung-Chyun; Chen, Chien-Hsiu; Lin, Yi-Tseng; Kuo, Chung-Hsien

    2016-01-01

    A high efficient time-shift correlation algorithm was proposed to deal with the peak time uncertainty of P300 evoked potential for a P300-based brain-computer interface (BCI). The time-shift correlation series data were collected as the input nodes of an artificial neural network (ANN), and the classification of four LED visual stimuli was selected as the output node. Two operating modes, including fast-recognition mode (FM) and accuracy-recognition mode (AM), were realized. The proposed BCI system was implemented on an embedded system for commanding an adult-size humanoid robot to evaluate the performance from investigating the ground truth trajectories of the humanoid robot. When the humanoid robot walked in a spacious area, the FM was used to control the robot with a higher information transfer rate (ITR). When the robot walked in a crowded area, the AM was used for high accuracy of recognition to reduce the risk of collision. The experimental results showed that, in 100 trials, the accuracy rate of FM was 87.8% and the average ITR was 52.73 bits/min. In addition, the accuracy rate was improved to 92% for the AM, and the average ITR decreased to 31.27 bits/min. due to strict recognition constraints.

  17. Timing Comparisons for GLEs and High-energy Proton Events using GPS Proton Measurements

    Science.gov (United States)

    Bernstein, V.; Winter, L. M.; Carver, M.; Morley, S.

    2017-12-01

    The newly released LANL GPS particle sensor data offers a unique snapshot of access of relativistic particles into the geomagnetic field. Currently, 23 of the 31 operational GPS satellites host energetic particle detectors which can detect the arrival of high-energy solar protons associated with Ground Level Enhancements (GLEs). We compare the timing profiles of solar energetic proton detections from GPS satellites as well as from ground-based Neutron Monitors and GOES spacecraft at geostationary orbit in order to understand how high-energy protons from the Sun enter the geomagnetic field and investigate potential differences in arrival time of energetic protons at GPS satellites as a function of location. Previous studies could only use one or two spacecraft at a similar altitude to track the arrival of energetic particles. With GPS data, we can now test whether the particles arrive isotropically, as assumed, or whether there exist differences in the timing and energetics viewed by each of the individual satellites. Extensions of this work could lead to improvements in space weather forecasting that predict more localized risk estimates for space-based technology.

  18. Relating interesting quantitative time series patterns with text events and text features

    Science.gov (United States)

    Wanner, Franz; Schreck, Tobias; Jentner, Wolfgang; Sharalieva, Lyubka; Keim, Daniel A.

    2013-12-01

    In many application areas, the key to successful data analysis is the integrated analysis of heterogeneous data. One example is the financial domain, where time-dependent and highly frequent quantitative data (e.g., trading volume and price information) and textual data (e.g., economic and political news reports) need to be considered jointly. Data analysis tools need to support an integrated analysis, which allows studying the relationships between textual news documents and quantitative properties of the stock market price series. In this paper, we describe a workflow and tool that allows a flexible formation of hypotheses about text features and their combinations, which reflect quantitative phenomena observed in stock data. To support such an analysis, we combine the analysis steps of frequent quantitative and text-oriented data using an existing a-priori method. First, based on heuristics we extract interesting intervals and patterns in large time series data. The visual analysis supports the analyst in exploring parameter combinations and their results. The identified time series patterns are then input for the second analysis step, in which all identified intervals of interest are analyzed for frequent patterns co-occurring with financial news. An a-priori method supports the discovery of such sequential temporal patterns. Then, various text features like the degree of sentence nesting, noun phrase complexity, the vocabulary richness, etc. are extracted from the news to obtain meta patterns. Meta patterns are defined by a specific combination of text features which significantly differ from the text features of the remaining news data. Our approach combines a portfolio of visualization and analysis techniques, including time-, cluster- and sequence visualization and analysis functionality. We provide two case studies, showing the effectiveness of our combined quantitative and textual analysis work flow. The workflow can also be generalized to other

  19. Events at blood collection area due to nonconforming blood bags and plateletpheresis kits: need for timely corrective and preventive actions.

    Science.gov (United States)

    Verma, Anupam; Sachan, Deepti; Elhence, Priti; Pandey, Hem; Dubey, Anju

    2012-07-01

    Good blood banking practice requires that every effort should be made to detect any deviation or defect in blood bank products and to identify any potential risk to blood donor or recipient(s). We report the findings of an exercise that provide an insight into why feedback from the user side is crucial. Various events involving blood bags and plateletpheresis kits and the corresponding appropriate actions instituted for remedial measures were recorded. These scattered events were recorded for 6 months following the use of a new batch of improved blood bags with add-on features. Several events related to plateletpheresis kits from three different manufacturers were also recorded for 1 year. The affected blood bags were utilized with no untoward incident. The complaint was closed following satisfactory response from the blood bag manufacturing company that acted in a timely manner in addressing the root causes of the problems. However, corrective and preventive actions (CAPA) could not be implemented for plateletpheresis kits. The rate of undesirable events was higher with plateletpheresis kits as compared with whole blood bags (1.75% vs. 0.06%). As defects or deviations that trigger the need for CAPA can stem from numerous sources, it is important to clearly identify and document the problems and level of risk so that appropriate investigations can be instituted and remedial actions can be taken in a timely manner. This study demonstrates the usefulness of a quality initiative to collate and analyze blood product faults in conjunction with blood product manufacturers. © 2012 American Association of Blood Banks.

  20. Just-in-time learning is effective in helping first responders manage weapons of mass destruction events.

    Science.gov (United States)

    Motola, Ivette; Burns, William A; Brotons, Angel A; Withum, Kelly F; Rodriguez, Richard D; Hernandez, Salma; Rivera, Hector F; Issenberg, Saul Barry; Schulman, Carl I

    2015-10-01

    Chemical, biologic, radiologic, nuclear, and explosive (CBRNE) incidents require specialized training. The low frequency of these events leads to significant skill decay among first responders. To address skill decay and lack of experience with these high-impact events, educational modules were developed for mobile devices to provide just-in-time training to first responders en route to a CBRNE event. This study assessed the efficacy and usability of the mobile training. Ninety first responders were randomized to a control or an intervention group. All participants completed a pretest to measure knowledge of CBRNE topics. The intervention group then viewed personal protective equipment and weapons of mass destruction field management videos as an overview. Both groups were briefed on a disaster scenario (chemical nerve agent, radiologic, or explosives) requiring them to triage, assess, and manage a patient. Intervention group participants watched a mobile training video corresponding to the scenario. The control group did not receive prescenario video training. Observers rated participant performance in each scenario. After completing the scenarios, all participants answered a cognitive posttest. Those in the intervention group also answered a questionnaire on their impressions of the training. The intervention group outperformed the control group in the explosives and chemical nerve agent scenarios; the differences were statistically significant (explosives, mean of 26.32 for intervention and 22.85 for control, p just-in-time training improved first-responder knowledge of CBRNE events and is an effective tool in helping first responders manage simulated explosive and chemical agent scenarios. Therapeutic/care management study, level II.

  1. Time-to-onset and -resolution of adverse events before/after atomoxetine discontinuation in adult patients with ADHD.

    Science.gov (United States)

    Upadhyaya, Himanshu; Tanaka, Yoko; Lipsius, Sarah; Kryzhanovskaya, Ludmila A; Lane, Jeannine R; Escobar, Rodrigo; Trzepacz, Paula T; Allen, Albert J

    2015-01-01

    Adults with attention-deficit/hyperactivity disorder treated with atomoxetine were examined for time-to-onset and -resolution of common treatment-emergent adverse events (TEAEs) and male sexual dysfunction, and for changes in blood pressure (BP) and heart rate (HR) upon atomoxetine discontinuation. 12-week open-label atomoxetine (40-100 mg/day) was followed by 12-week double-blind maintenance treatment (atomoxetine 80 or 100 mg/day). Responders were then randomized to atomoxetine (n = 266) or placebo (n = 258) for 25-week randomized withdrawal. Examined were (1) median time-to-onset and -resolution of TEAEs during atomoxetine treatment, and (2) within group, visitwise mean changes for sitting HR, systolic BP, and diastolic BP for the postrandomization placebo group. Common adverse events (AEs) appeared early, within week 1 of atomoxetine treatment. Some AEs resolve relatively rapidly, whereas others have a more lingering course of resolution (including male sexual side effects); median resolution times were 3 - 53 days. BP and HR increases during atomoxetine treatment returned to baseline upon atomoxetine discontinuation. Atomoxetine is associated with common AEs, with 3- to 53-day median resolution times. ClincialTrials.gov - NCT00700427.

  2. Network Events on Multiple Space and Time Scales in Cultured Neural Networks and in a Stochastic Rate Model.

    Directory of Open Access Journals (Sweden)

    Guido Gigante

    2015-11-01

    Full Text Available Cortical networks, in-vitro as well as in-vivo, can spontaneously generate a variety of collective dynamical events such as network spikes, UP and DOWN states, global oscillations, and avalanches. Though each of them has been variously recognized in previous works as expression of the excitability of the cortical tissue and the associated nonlinear dynamics, a unified picture of the determinant factors (dynamical and architectural is desirable and not yet available. Progress has also been partially hindered by the use of a variety of statistical measures to define the network events of interest. We propose here a common probabilistic definition of network events that, applied to the firing activity of cultured neural networks, highlights the co-occurrence of network spikes, power-law distributed avalanches, and exponentially distributed 'quasi-orbits', which offer a third type of collective behavior. A rate model, including synaptic excitation and inhibition with no imposed topology, synaptic short-term depression, and finite-size noise, accounts for all these different, coexisting phenomena. We find that their emergence is largely regulated by the proximity to an oscillatory instability of the dynamics, where the non-linear excitable behavior leads to a self-amplification of activity fluctuations over a wide range of scales in space and time. In this sense, the cultured network dynamics is compatible with an excitation-inhibition balance corresponding to a slightly sub-critical regime. Finally, we propose and test a method to infer the characteristic time of the fatigue process, from the observed time course of the network's firing rate. Unlike the model, possessing a single fatigue mechanism, the cultured network appears to show multiple time scales, signalling the possible coexistence of different fatigue mechanisms.

  3. Multivariate statistics exercises and solutions

    CERN Document Server

    Härdle, Wolfgang Karl

    2015-01-01

    The authors present tools and concepts of multivariate data analysis by means of exercises and their solutions. The first part is devoted to graphical techniques. The second part deals with multivariate random variables and presents the derivation of estimators and tests for various practical situations. The last part introduces a wide variety of exercises in applied multivariate data analysis. The book demonstrates the application of simple calculus and basic multivariate methods in real life situations. It contains altogether more than 250 solved exercises which can assist a university teacher in setting up a modern multivariate analysis course. All computer-based exercises are available in the R language. All R codes and data sets may be downloaded via the quantlet download center  www.quantlet.org or via the Springer webpage. For interactive display of low-dimensional projections of a multivariate data set, we recommend GGobi.

  4. The representation of time course events in visual arts and the development of the concept of time in children: a preliminary study.

    Science.gov (United States)

    Actis-Grosso, Rossana; Zavagno, Daniele

    2008-01-01

    By means of a careful search we found several representations of dynamic contents of events that show how the depiction of the passage of time in the visual arts has evolved gradually through a series of modifications and adaptations. The general hypothesis we started to investigate is that the evolution of the representation of the time course in visual arts is mirrored in the evolution of the concept of time in children, who, according to Piaget (1946), undergo three stages in their ability to conceptualize time. Crucial for our hypothesis is Stage II, in which children become progressively able to link the different phases of an event, but vacillate between what Piaget termed 'intuitive regulations', not being able to understand all the different aspects of a given situation. We found several pictorial representations - mainly dated back to the 14th to 15th century - that seem to fit within a Stage II of children's comprehension of time. According to our hypothesis, this type of pictorial representations should be immediately understood only by those children who are at Piaget's Stage II of time conceptualization. This implies that children at Stages I and III should not be able to understand the representation of time courses in the aforementioned paintings. An experiment was run to verify the agreement between children's collocation within Piaget's three stages - as indicated by an adaptation of Piaget's original experiment - and their understanding of pictorial representations that should be considered as Stage II type of representations of time courses. Despite the small sample of children examined so far, results seem to support our hypothesis. A follow-up (Experiment 2) on the same children was also run one year later in order to verify other possible explanations. Results from the two experiments suggest that the study of the visual arts can aid our understanding of the development of the concept of time, and it can also help to distinguish between the

  5. Developing a real-time emulation of multiresolutional control architectures for complex, discrete-event systems

    Energy Technology Data Exchange (ETDEWEB)

    Davis, W.J.; Macro, J.G.; Brook, A.L. [Univ. of Illinois, Urbana, IL (United States)] [and others

    1996-12-31

    This paper first discusses an object-oriented, control architecture and then applies the architecture to produce a real-time software emulator for the Rapid Acquisition of Manufactured Parts (RAMP) flexible manufacturing system (FMS). In specifying the control architecture, the coordinated object is first defined as the primary modeling element. These coordinated objects are then integrated into a Recursive, Object-Oriented Coordination Hierarchy. A new simulation methodology, the Hierarchical Object-Oriented Programmable Logic Simulator, is then employed to model the interactions among the coordinated objects. The final step in implementing the emulator is to distribute the models of the coordinated objects over a network of computers and to synchronize their operation to a real-time clock. The paper then introduces the Hierarchical Subsystem Controller as an intelligent controller for the coordinated object. The proposed approach to intelligent control is then compared to the concept of multiresolutional semiosis that has been developed by Dr. Alex Meystel. Finally, the plans for implementing an intelligent controller for the RAMP FMS are discussed.

  6. The risk of cardiovascular events during leisure time activities at altitude.

    Science.gov (United States)

    Burtscher, Martin; Ponchia, Andrea

    2010-01-01

    Annually, more than 100 million tourists are attracted by the mountainous areas around the world. On the one hand, leisure time activities at altitude may well contribute to the well-established beneficial effects of exercise; on the other hand, these activities are also associated with a relatively high risk of death. Sudden cardiac death (SCD) is the most frequent cause of nontraumatic death in males older than 34 years at altitude during leisure time activities such as downhill skiing and hiking. Whereas prior myocardial infarction is the most important risk factor for SCD, particularly relevant in downhill skiers, the unusual physical activity during the first days at altitude and the prolonged abstinence from food and fluid intake during exercise at altitude are the most important triggers. Unaccustomed physical activity seems more likely to trigger SCD than altitude per se. The detection of subjects at risk, evidence-based therapy, and advice on adequate behavior during the altitude sojourn will help to prevent SCD and to increase the health benefits generated by mountaineering activities.

  7. Real-time definition of non-randomness in the distribution of genomic events.

    Directory of Open Access Journals (Sweden)

    Ulrich Abel

    Full Text Available Features such as mutations or structural characteristics can be non-randomly or non-uniformly distributed within a genome. So far, computer simulations were required for statistical inferences on the distribution of sequence motifs. Here, we show that these analyses are possible using an analytical, mathematical approach. For the assessment of non-randomness, our calculations only require information including genome size, number of (sampled sequence motifs and distance parameters. We have developed computer programs evaluating our analytical formulas for the real-time determination of expected values and p-values. This approach permits a flexible cluster definition that can be applied to most effectively identify non-random or non-uniform sequence motif distribution. As an example, we show the effectivity and reliability of our mathematical approach in clinical retroviral vector integration site distribution.

  8. Time scales of critical events around the Cretaceous-Paleogene boundary.

    Science.gov (United States)

    Renne, Paul R; Deino, Alan L; Hilgen, Frederik J; Kuiper, Klaudia F; Mark, Darren F; Mitchell, William S; Morgan, Leah E; Mundil, Roland; Smit, Jan

    2013-02-08

    Mass extinctions manifest in Earth's geologic record were turning points in biotic evolution. We present (40)Ar/(39)Ar data that establish synchrony between the Cretaceous-Paleogene boundary and associated mass extinctions with the Chicxulub bolide impact to within 32,000 years. Perturbation of the atmospheric carbon cycle at the boundary likely lasted less than 5000 years, exhibiting a recovery time scale two to three orders of magnitude shorter than that of the major ocean basins. Low-diversity mammalian fauna in the western Williston Basin persisted for as little as 20,000 years after the impact. The Chicxulub impact likely triggered a state shift of ecosystems already under near-critical stress.

  9. Temporal and spatial variations of travel-time residuals in central California for Novaya Zemlya events

    International Nuclear Information System (INIS)

    Robinson, R.; Iyer, H.M.

    1976-01-01

    Eight large nuclear explosions in Novaya Zemlya from October 1969 through November 1974 were used to monitor long-term variations in crustal seismic velocity near the San Andreas fault in central California. Relative P-wave travel-time residuals appear to be accurate to approximately +-0.1 sec. Of the over 100 stations used, none show clearly significant temporal variations in residual greater than this amount, corresponding to about a 4 percent change in velocity in the upper crust. Average relative residuals at individual stations show a large spatial variation of about 1.5 sec. These variations reflect both a complex crustal geology and changes in crustal thickness and provide a potentially powerful tool for studying crustal structure

  10. Hearing Shapes: Event-related Potentials Reveal the Time Course of Auditory-Visual Sensory Substitution.

    Science.gov (United States)

    Graulty, Christian; Papaioannou, Orestis; Bauer, Phoebe; Pitts