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Sample records for multivariate event time

  1. A new multivariate time series data analysis technique: Automated detection of flux transfer events using Cluster data

    NASA Astrophysics Data System (ADS)

    Karimabadi, H.; Sipes, T. B.; Wang, Y.; Lavraud, B.; Roberts, A.

    2009-06-01

    A new data mining technique called MineTool-TS is introduced which captures the time-lapse information in multivariate time series data through extraction of global features and metafeatures. This technique is developed into a JAVA-based data mining software which automates all the steps in the model building to make it more accessible to nonexperts. As its first application in space sciences, MineTool-TS is used to develop a model for automated detection of flux transfer events (FTEs) at Earth's magnetopause in the Cluster spacecraft time series data. The model classifies a given time series into one of three categories of non-FTE, magnetosheath FTE, or magnetospheric FTE. One important feature of MineTool-TS is the ability to explore the importance of each variable or combination of variables as indicators of FTEs. FTEs have traditionally been identified on the basis of their magnetic field signatures, but here we find that some plasma variables can also be effective indicators of FTEs. For example, the perpendicular ion temperature yields a model accuracy of ˜93%, while a model based solely on the normal magnetic field BN yields an accuracy of ˜95%. This opens up the possibility of searching for more unusual FTEs that may, for example, have no clear BN signature and create a more comprehensive and less biased list of FTEs for statistical studies. We also find that models using GSM coordinates yield comparable accuracy to those using boundary normal coordinates. This is useful since there are regions where magnetopause models are not accurate. Another surprising result is the finding that the algorithm can largely detect FTEs, and even distinguish between magnetosheath and magnetospheric FTEs, solely on the basis of models built from single parameters, something that experts may not do so straightforwardly on the basis of short time series intervals. The most accurate models use a combination of plasma and magnetic field variables and achieve a very high

  2. Multivariate Time Series Similarity Searching

    PubMed Central

    Wang, Jimin; Zhu, Yuelong; Li, Shijin; Wan, Dingsheng; Zhang, Pengcheng

    2014-01-01

    Multivariate time series (MTS) datasets are very common in various financial, multimedia, and hydrological fields. In this paper, a dimension-combination method is proposed to search similar sequences for MTS. Firstly, the similarity of single-dimension series is calculated; then the overall similarity of the MTS is obtained by synthesizing each of the single-dimension similarity based on weighted BORDA voting method. The dimension-combination method could use the existing similarity searching method. Several experiments, which used the classification accuracy as a measure, were performed on six datasets from the UCI KDD Archive to validate the method. The results show the advantage of the approach compared to the traditional similarity measures, such as Euclidean distance (ED), cynamic time warping (DTW), point distribution (PD), PCA similarity factor (SPCA), and extended Frobenius norm (Eros), for MTS datasets in some ways. Our experiments also demonstrate that no measure can fit all datasets, and the proposed measure is a choice for similarity searches. PMID:24895665

  3. Multivariate time series similarity searching.

    PubMed

    Wang, Jimin; Zhu, Yuelong; Li, Shijin; Wan, Dingsheng; Zhang, Pengcheng

    2014-01-01

    Multivariate time series (MTS) datasets are very common in various financial, multimedia, and hydrological fields. In this paper, a dimension-combination method is proposed to search similar sequences for MTS. Firstly, the similarity of single-dimension series is calculated; then the overall similarity of the MTS is obtained by synthesizing each of the single-dimension similarity based on weighted BORDA voting method. The dimension-combination method could use the existing similarity searching method. Several experiments, which used the classification accuracy as a measure, were performed on six datasets from the UCI KDD Archive to validate the method. The results show the advantage of the approach compared to the traditional similarity measures, such as Euclidean distance (ED), cynamic time warping (DTW), point distribution (PD), PCA similarity factor (SPCA), and extended Frobenius norm (Eros), for MTS datasets in some ways. Our experiments also demonstrate that no measure can fit all datasets, and the proposed measure is a choice for similarity searches. PMID:24895665

  4. Multivariate cluster analysis of forest fire events in Portugal

    NASA Astrophysics Data System (ADS)

    Tonini, Marj; Pereira, Mario; Vega Orozco, Carmen; Parente, Joana

    2015-04-01

    Portugal is one of the major fire-prone European countries, mainly due to its favourable climatic, topographic and vegetation conditions. Compared to the other Mediterranean countries, the number of events registered here from 1980 up to nowadays is the highest one; likewise, with respect to the burnt area, Portugal is the third most affected country. Portuguese mapped burnt areas are available from the website of the Institute for the Conservation of Nature and Forests (ICNF). This official geodatabase is the result of satellite measurements starting from the year 1990. The spatial information, delivered in shapefile format, provides a detailed description of the shape and the size of area burnt by each fire, while the date/time information relate to the ignition fire is restricted to the year of occurrence. In terms of a statistical formalism wildfires can be associated to a stochastic point process, where events are analysed as a set of geographical coordinates corresponding, for example, to the centroid of each burnt area. The spatio/temporal pattern of stochastic point processes, including the cluster analysis, is a basic procedure to discover predisposing factorsas well as for prevention and forecasting purposes. These kinds of studies are primarily focused on investigating the spatial cluster behaviour of environmental data sequences and/or mapping their distribution at different times. To include both the two dimensions (space and time) a comprehensive spatio-temporal analysis is needful. In the present study authors attempt to verify if, in the case of wildfires in Portugal, space and time act independently or if, conversely, neighbouring events are also closer in time. We present an application of the spatio-temporal K-function to a long dataset (1990-2012) of mapped burnt areas. Moreover, the multivariate K-function allowed checking for an eventual different distribution between small and large fires. The final objective is to elaborate a 3D

  5. Network structure of multivariate time series

    NASA Astrophysics Data System (ADS)

    Lacasa, Lucas; Nicosia, Vincenzo; Latora, Vito

    2015-10-01

    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.

  6. Network structure of multivariate time series.

    PubMed

    Lacasa, Lucas; Nicosia, Vincenzo; Latora, Vito

    2015-01-01

    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. PMID:26487040

  7. Network structure of multivariate time series

    PubMed Central

    Lacasa, Lucas; Nicosia, Vincenzo; Latora, Vito

    2015-01-01

    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. PMID:26487040

  8. Multivariate Statistical Modelling of Drought and Heat Wave Events

    NASA Astrophysics Data System (ADS)

    Manning, Colin; Widmann, Martin; Vrac, Mathieu; Maraun, Douglas; Bevaqua, Emanuele

    2016-04-01

    Multivariate Statistical Modelling of Drought and Heat Wave Events C. Manning1,2, M. Widmann1, M. Vrac2, D. Maraun3, E. Bevaqua2,3 1. School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, UK 2. Laboratoire des Sciences du Climat et de l'Environnement, (LSCE-IPSL), Centre d'Etudes de Saclay, Gif-sur-Yvette, France 3. Wegener Center for Climate and Global Change, University of Graz, Brandhofgasse 5, 8010 Graz, Austria Compound extreme events are a combination of two or more contributing events which in themselves may not be extreme but through their joint occurrence produce an extreme impact. Compound events are noted in the latest IPCC report as an important type of extreme event that have been given little attention so far. As part of the CE:LLO project (Compound Events: muLtivariate statisticaL mOdelling) we are developing a multivariate statistical model to gain an understanding of the dependence structure of certain compound events. One focus of this project is on the interaction between drought and heat wave events. Soil moisture has both a local and non-local effect on the occurrence of heat waves where it strongly controls the latent heat flux affecting the transfer of sensible heat to the atmosphere. These processes can create a feedback whereby a heat wave maybe amplified or suppressed by the soil moisture preconditioning, and vice versa, the heat wave may in turn have an effect on soil conditions. An aim of this project is to capture this dependence in order to correctly describe the joint probabilities of these conditions and the resulting probability of their compound impact. We will show an application of Pair Copula Constructions (PCCs) to study the aforementioned compound event. PCCs allow in theory for the formulation of multivariate dependence structures in any dimension where the PCC is a decomposition of a multivariate distribution into a product of bivariate components modelled using copulas. A

  9. Time varying, multivariate volume data reduction

    SciTech Connect

    Ahrens, James P; Fout, Nathaniel; Ma, Kwan - Liu

    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

  10. Visual Data Mining of Large, Multivariate Space-Time Data

    NASA Astrophysics Data System (ADS)

    Cook, D.

    2001-12-01

    Interest in understanding global climate change is generating monitoring efforts that yield a huge amount of multivariate space-time data. While analytical methods for univariate space-time data may be mature and substantial, methods for multivariate space-time data analysis are still in their infancy. The urgency of understanding climate change on a global scale begs for input from data analysts, and to work effectively they need new tools to explore multivariate aspects of climate. This talk describes interactive and dynamic visual tools for mining information from multivariate space-time data. Methods for small amounts of data will be discussed, followed by approaches to scaling up methods for large quantities of data. We focus on the ``multiple views'' approach for viewing multivariate data, and how these extend to include space-time contextual information. We also will describe dynamic graphics methods such as tours in the space-time context. Data mining is the current terminology for exploratory analyses of data, typically associated with large databases. Exploratory analysis has a goal of finding anomalies, quirks and deviations from a trend, and basically extracting unexpected information from data. It oft-times emphasizes model-free methods, although model-based approaches are also integral components to the analysis process. Visual data mining concentrates on the use of visual tools in the exploratory process. As such it often involves highly interactive and dynamic graphics environments which facilitate quick queries and visual responses. Visual methods are especially important in exploratory analysis because they provide an interface for using the human eye to digest complex information. A good plot can convey far more information than a numerical summary. Visual tools enhance the chances of discovering the unexpected, and detecting the anomalous events.

  11. Segmentation of biological multivariate time-series data

    NASA Astrophysics Data System (ADS)

    Omranian, Nooshin; Mueller-Roeber, Bernd; Nikoloski, Zoran

    2015-03-01

    Time-series data from multicomponent systems capture the dynamics of the ongoing processes and reflect the interactions between the components. The progression of processes in such systems usually involves check-points and events at which the relationships between the components are altered in response to stimuli. Detecting these events together with the implicated components can help understand the temporal aspects of complex biological systems. Here we propose a regularized regression-based approach for identifying breakpoints and corresponding segments from multivariate time-series data. In combination with techniques from clustering, the approach also allows estimating the significance of the determined breakpoints as well as the key components implicated in the emergence of the breakpoints. Comparative analysis with the existing alternatives demonstrates the power of the approach to identify biologically meaningful breakpoints in diverse time-resolved transcriptomics data sets from the yeast Saccharomyces cerevisiae and the diatom Thalassiosira pseudonana.

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

    ERIC Educational Resources Information Center

    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…

  13. Interpretable Early Classification of Multivariate Time Series

    ERIC Educational Resources Information Center

    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,…

  14. Assessment of Critical Events Corridors through Multivariate Cascading Outages Analysis

    SciTech Connect

    Makarov, Yuri V.; Samaan, Nader A.; Diao, Ruisheng; Kumbale, Murali; Chen, Yousu; Singh, Ruchi; Green, Irina; Morgan, Mark P.

    2011-10-17

    Massive blackouts of electrical power systems in North America over the past decade has focused increasing attention upon ways to identify and simulate network events that may potentially lead to widespread network collapse. This paper summarizes a method to simulate power-system vulnerability to cascading failures to a supplied set of initiating events synonymously termed as Extreme Events. The implemented simulation method is currently confined to simulating steady state power-system response to a set of extreme events. The outlined method of simulation is meant to augment and provide a new insight into bulk power transmission network planning that at present remains mainly confined to maintaining power system security for single and double component outages under a number of projected future network operating conditions. Although one of the aims of this paper is to demonstrate the feasibility of simulating network vulnerability to cascading outages, a more important goal has been to determine vulnerable parts of the network that may potentially be strengthened in practice so as to mitigate system susceptibility to cascading failures. This paper proposes to demonstrate a systematic approach to analyze extreme events and identify vulnerable system elements that may be contributing to cascading outages. The hypothesis of critical events corridors is proposed to represent repeating sequential outages that can occur in the system for multiple initiating events. The new concept helps to identify system reinforcements that planners could engineer in order to 'break' the critical events sequences and therefore lessen the likelihood of cascading outages. This hypothesis has been successfully validated with a California power system model.

  15. [Anomaly Detection of Multivariate Time Series Based on Riemannian Manifolds].

    PubMed

    Xu, Yonghong; Hou, Xiaoying; Li Shuting; Cui, Jie

    2015-06-01

    Multivariate time series problems widely exist in production and life in the society. Anomaly detection has provided people with a lot of valuable information in financial, hydrological, meteorological fields, and the research areas of earthquake, video surveillance, medicine and others. In order to quickly and efficiently find exceptions in time sequence so that it can be presented in front of people in an intuitive way, we in this study combined the Riemannian manifold with statistical process control charts, based on sliding window, with a description of the covariance matrix as the time sequence, to achieve the multivariate time series of anomaly detection and its visualization. We made MA analog data flow and abnormal electrocardiogram data from MIT-BIH as experimental objects, and verified the anomaly detection method. The results showed that the method was reasonable and effective. PMID:26485975

  16. Regularly timed events amid chaos.

    PubMed

    Blakely, Jonathan N; Cooper, Roy M; Corron, Ned J

    2015-11-01

    We show rigorously that the solutions of a class of chaotic oscillators are characterized by regularly timed events in which the derivative of the solution is instantaneously zero. The perfect regularity of these events is in stark contrast with the well-known unpredictability of chaos. We explore some consequences of these regularly timed events through experiments using chaotic electronic circuits. First, we show that a feedback loop can be implemented to phase lock the regularly timed events to a periodic external signal. In this arrangement the external signal regulates the timing of the chaotic signal but does not strictly lock its phase. That is, phase slips of the chaotic oscillation persist without disturbing timing of the regular events. Second, we couple the regularly timed events of one chaotic oscillator to those of another. A state of synchronization is observed where the oscillators exhibit synchronized regular events while their chaotic amplitudes and phases evolve independently. Finally, we add additional coupling to synchronize the amplitudes, as well, however in the opposite direction illustrating the independence of the amplitudes from the regularly timed events. PMID:26651759

  17. A Method for Comparing Multivariate Time Series with Different Dimensions

    PubMed Central

    Tapinos, Avraam; Mendes, Pedro

    2013-01-01

    In many situations it is desirable to compare dynamical systems based on their behavior. Similarity of behavior often implies similarity of internal mechanisms or dependency on common extrinsic factors. While there are widely used methods for comparing univariate time series, most dynamical systems are characterized by multivariate time series. Yet, comparison of multivariate time series has been limited to cases where they share a common dimensionality. A semi-metric is a distance function that has the properties of non-negativity, symmetry and reflexivity, but not sub-additivity. Here we develop a semi-metric – SMETS – that can be used for comparing groups of time series that may have different dimensions. To demonstrate its utility, the method is applied to dynamic models of biochemical networks and to portfolios of shares. The former is an example of a case where the dependencies between system variables are known, while in the latter the system is treated (and behaves) as a black box. PMID:23393554

  18. Multivariate optimization of production systems: The time dimension

    SciTech Connect

    Ravindran, N.; Horne, R.N.

    1993-04-01

    Traditional analysis of oil and gas production systems treats individual nodes one at a time. This only calculates a feasible solution which is not necessarily optimal. Multivariate optimization is able to determine the most profitable configuration, including all variables simultaneously. The optimization can also find the optimal recovery over a period of time, rather than just at a single instant as in traditional methods. This report describes the development of multivariate optimization for situations in which the decision variables may change as a function of time. For example, instead of estimating a tubing size which is optimal over the life of the project, this approach determines a series of optimal tubing sizes which may change from year to year. Examples show that under an optimal strategy, tubing size can be changed only infrequently while still increasing profitability of a project. The methods used in this work considered the special requirements of objectives which are not smooth functions of their decision variables. The physical problems considered included artificial lift production systems.

  19. Impact of dose intensity of ponatinib on selected adverse events: Multivariate analyses from a pooled population of clinical trial patients.

    PubMed

    Dorer, David J; Knickerbocker, Ronald K; Baccarani, Michele; Cortes, Jorge E; Hochhaus, Andreas; Talpaz, Moshe; Haluska, Frank G

    2016-09-01

    Ponatinib is approved for adults with refractory chronic myeloid leukemia or Philadelphia chromosome-positive acute lymphoblastic leukemia, including those with the T315I BCR-ABL1 mutation. We pooled data from 3 clinical trials (N=671) to determine the impact of ponatinib dose intensity on the following adverse events: arterial occlusive events (cardiovascular, cerebrovascular, and peripheral vascular events), venous thromboembolic events, cardiac failure, thrombocytopenia, neutropenia, hypertension, pancreatitis, increased lipase, increased alanine aminotransferase, increased aspartate aminotransferase, rash, arthralgia, and hypertriglyceridemia. Multivariate analyses allowed adjustment for covariates potentially related to changes in dosing or an event. Logistic regression analysis identified significant associations between dose intensity and most events after adjusting for covariates. Pancreatitis, rash, and cardiac failure had the strongest associations with dose intensity (odds ratios >2). Time-to-event analyses showed significant associations between dose intensity and risk of arterial occlusive events and each subcategory. Further, these analyses suggested that a lag exists between a change in dose and the resulting change in event risk. No significant association between dose intensity and risk of venous thromboembolic events was evident. Collectively, these findings suggest a potential causal relationship between ponatinib dose and certain adverse events and support prospective investigations of approaches to lower average ponatinib dose intensity. PMID:27505637

  20. The LCLS Timing Event System

    SciTech Connect

    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.

  1. Optimal model-free prediction from multivariate time series.

    PubMed

    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. PMID:26066231

  2. Fast and Flexible Multivariate Time Series Subsequence Search

    NASA Technical Reports Server (NTRS)

    Bhaduri, Kanishka; Oza, Nikunj C.; Zhu, Qiang; Srivastava, Ashok N.

    2010-01-01

    Multivariate Time-Series (MTS) are ubiquitous, and are generated in areas as disparate as sensor recordings in aerospace systems, music and video streams, medical monitoring, and financial systems. Domain experts are often interested in searching for interesting multivariate patterns from these MTS databases which often contain several gigabytes of data. Surprisingly, research on MTS search is very limited. Most of the existing work only supports queries with the same length of data, or queries on a fixed set of variables. In this paper, we propose an efficient and flexible subsequence search framework for massive MTS databases, that, for the first time, enables querying on any subset of variables with arbitrary time delays between them. We propose two algorithms to solve this problem (1) a List Based Search (LBS) algorithm which uses sorted lists for indexing, and (2) a R*-tree Based Search (RBS) which uses Minimum Bounding Rectangles (MBR) to organize the subsequences. Both algorithms guarantee that all matching patterns within the specified thresholds will be returned (no false dismissals). The very few false alarms can be removed by a post-processing step. Since our framework is also capable of Univariate Time-Series (UTS) subsequence search, we first demonstrate the efficiency of our algorithms on several UTS datasets previously used in the literature. We follow this up with experiments using two large MTS databases from the aviation domain, each containing several millions of observations. Both these tests show that our algorithms have very high prune rates (>99%) thus needing actual disk access for only less than 1% of the observations. To the best of our knowledge, MTS subsequence search has never been attempted on datasets of the size we have used in this paper.

  3. F100 multivariable control synthesis program: Evaluation of a multivariable control using a real-time engine simulation

    NASA Technical Reports Server (NTRS)

    Szuch, J. R.; Soeder, J. F.; Seldner, K.; Cwynar, D. S.

    1977-01-01

    The design, evaluation, and testing of a practical, multivariable, linear quadratic regulator control for the F100 turbofan engine were accomplished. NASA evaluation of the multivariable control logic and implementation are covered. The evaluation utilized a real time, hybrid computer simulation of the engine. Results of the evaluation are presented, and recommendations concerning future engine testing of the control are made. Results indicated that the engine testing of the control should be conducted as planned.

  4. Optimizing Functional Network Representation of Multivariate Time Series

    NASA Astrophysics Data System (ADS)

    Zanin, Massimiliano; Sousa, Pedro; Papo, David; Bajo, Ricardo; García-Prieto, Juan; Pozo, Francisco Del; Menasalvas, Ernestina; Boccaletti, Stefano

    2012-09-01

    By combining complex network theory and data mining techniques, we provide objective criteria for optimization of the functional network representation of generic multivariate time series. In particular, we propose a method for the principled selection of the threshold value for functional network reconstruction from raw data, and for proper identification of the network's indicators that unveil the most discriminative information on the system for classification purposes. We illustrate our method by analysing networks of functional brain activity of healthy subjects, and patients suffering from Mild Cognitive Impairment, an intermediate stage between the expected cognitive decline of normal aging and the more pronounced decline of dementia. We discuss extensions of the scope of the proposed methodology to network engineering purposes, and to other data mining tasks.

  5. Optimizing Functional Network Representation of Multivariate Time Series

    PubMed Central

    Zanin, Massimiliano; Sousa, Pedro; Papo, David; Bajo, Ricardo; García-Prieto, Juan; Pozo, Francisco del; Menasalvas, Ernestina; Boccaletti, Stefano

    2012-01-01

    By combining complex network theory and data mining techniques, we provide objective criteria for optimization of the functional network representation of generic multivariate time series. In particular, we propose a method for the principled selection of the threshold value for functional network reconstruction from raw data, and for proper identification of the network's indicators that unveil the most discriminative information on the system for classification purposes. We illustrate our method by analysing networks of functional brain activity of healthy subjects, and patients suffering from Mild Cognitive Impairment, an intermediate stage between the expected cognitive decline of normal aging and the more pronounced decline of dementia. We discuss extensions of the scope of the proposed methodology to network engineering purposes, and to other data mining tasks. PMID:22953051

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

    NASA Astrophysics Data System (ADS)

    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.

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

    PubMed

    Demanuele, Charmaine; Bähner, Florian; Plichta, Michael M; Kirsch, Peter; Tost, Heike; Meyer-Lindenberg, Andreas; Durstewitz, Daniel

    2015-01-01

    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 functional magnetic resonance imaging (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 (RAM) 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

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

    PubMed Central

    Demanuele, Charmaine; Bähner, Florian; Plichta, Michael M.; Kirsch, Peter; Tost, Heike; Meyer-Lindenberg, Andreas; Durstewitz, Daniel

    2015-01-01

    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 functional magnetic resonance imaging (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 (RAM) 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

  9. Evaluating multivariate visualizations on time-varying data

    NASA Astrophysics Data System (ADS)

    Livingston, Mark A.; Decker, Jonathan W.; Ai, Zhuming

    2013-01-01

    Multivariate visualization techniques have been applied to a wide variety of visual analysis tasks and a broad range of data types and sources. Their utility has been evaluated in a modest range of simple analysis tasks. In this work, we extend our previous task to a case of time-varying data. We implemented ve visualizations of our synthetic test data: three previously evaluated techniques (Data-driven Spots, Oriented Slivers, and Attribute Blocks), one hybrid of the rst two that we call Oriented Data-driven Spots, and an implementation of Attribute Blocks that merges the temporal slices. We conducted a user study of these ve techniques. Our previous nding (with static data) was that users performed best when the density of the target (as encoded in the visualization) was either highest or had the highest ratio to non-target features. The time-varying presentations gave us a wider range of density and density gains from which to draw conclusions; we now see evidence for the density gain as the perceptual measure, rather than the absolute density.

  10. Mulstiscale Stochastic Generator of Multivariate Met-Ocean Time Series

    NASA Astrophysics Data System (ADS)

    Guanche, Yanira; Mínguez, Roberto; Méndez, Fernando J.

    2013-04-01

    The design of maritime structures requires information on sea state conditions that influence its behavior during its life cycle. In the last decades, there has been a increasing development of sea databases (buoys, reanalysis, satellite) that allow an accurate description of the marine climate and its interaction with a given structure in terms of functionality and stability. However, these databases have a limited timelength, and its appliance entails an associated uncertainty. To avoid this limitation, engineers try to sample synthetically generated time series, statistically consistent, which allow the simulation of longer time periods. The present work proposes a hybrid methodology to deal with this issue. It is based in the combination of clustering algorithms (k-means) and an autoregressive logistic regression model (logit). Since the marine climate is directly related to the atmospheric conditions at a synoptic scale, the proposed methodology takes both systems into account; generating simultaneously circulation patterns (weather types) time series and the sea state time series related. The generation of these time series can be summarized in three steps: (1) By applying the clustering technique k-means the atmospheric conditions are classified into a representative number of synoptical patterns (2) Taking into account different covariates involved (such as seasonality, interannual variability, trends or autoregressive term) the autoregressive logistic model is adjusted (3) Once the model is able to simulate weather types time series the last step is to generate multivariate hourly metocean parameters related to these weather types. This is done by an autoregressive model (ARMA) for each variable, including cross-correlation between them. To show the goodness of the proposed method the following data has been used: Sea Level Pressure (SLP) databases from NCEP-NCAR and Global Ocean Wave (GOW) reanalysis from IH Cantabria. The synthetical met-ocean hourly

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

    ERIC Educational Resources Information Center

    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…

  12. Memory for time: how people date events.

    PubMed

    Janssen, Steve M J; Chessa, Antonio G; Murre, Jaap M J

    2006-01-01

    The effect of different formats on the accuracy of dating news and the distribution of personal events was examined in four conditions. In the first, participants had to date events in the absolute time format (e.g., "July 2004"), and in the second, they had to date events in the relative time format (e.g., "3 weeks ago"). In the other conditions, they were asked to choose between the two formats. We found a small backward telescoping effect for recent news events and a large forward telescoping effect for remote events. Events dated in the absolute time format were more accurate than those dated in the relative time format. Furthermore, participants preferred to date news events with the relative time format and personal events with the absolute time format, as well as preferring to date remote events in the relative time format and recent events in the absolute time format. PMID:16686113

  13. Nonparametric Bayesian Segmentation of a Multivariate Inhomogeneous Space-Time Poisson Process.

    PubMed

    Ding, Mingtao; He, Lihan; Dunson, David; Carin, Lawrence

    2012-12-01

    A nonparametric Bayesian model is proposed for segmenting time-evolving multivariate spatial point process data. An inhomogeneous Poisson process is assumed, with a logistic stick-breaking process (LSBP) used to encourage piecewise-constant spatial Poisson intensities. The LSBP explicitly favors spatially contiguous segments, and infers the number of segments based on the observed data. The temporal dynamics of the segmentation and of the Poisson intensities are modeled with exponential correlation in time, implemented in the form of a first-order autoregressive model for uniformly sampled discrete data, and via a Gaussian process with an exponential kernel for general temporal sampling. We consider and compare two different inference techniques: a Markov chain Monte Carlo sampler, which has relatively high computational complexity; and an approximate and efficient variational Bayesian analysis. The model is demonstrated with a simulated example and a real example of space-time crime events in Cincinnati, Ohio, USA. PMID:23741284

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

    NASA Astrophysics Data System (ADS)

    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

  15. Multivariate space - time analysis of PRE-STORM precipitation

    NASA Technical Reports Server (NTRS)

    Polyak, Ilya; North, Gerald R.; Valdes, Juan B.

    1994-01-01

    This paper presents the methodologies and results of the multivariate modeling and two-dimensional spectral and correlation analysis of PRE-STORM rainfall gauge data. Estimated parameters of the models for the specific spatial averages clearly indicate the eastward and southeastward wave propagation of rainfall fluctuations. A relationship between the coefficients of the diffusion equation and the parameters of the stochastic model of rainfall fluctuations is derived that leads directly to the exclusive use of rainfall data to estimate advection speed (about 12 m/s) as well as other coefficients of the diffusion equation of the corresponding fields. The statistical methodology developed here can be used for confirmation of physical models by comparison of the corresponding second-moment statistics of the observed and simulated data, for generating multiple samples of any size, for solving the inverse problem of the hydrodynamic equations, and for application in some other areas of meteorological and climatological data analysis and modeling.

  16. When univariate model-free time series prediction is better than multivariate

    NASA Astrophysics Data System (ADS)

    Chayama, Masayoshi; Hirata, Yoshito

    2016-07-01

    The delay coordinate method is known to be a practically useful technique for reconstructing the states of an observed system. While this method is theoretically supported by Takens' embedding theorem concerning observations of a scalar time series, we can extend the method to include a multivariate time series. It is often assumed that a better prediction can be obtained using a multivariate time series than by using a scalar time series. However, multivariate time series contains various types of information, and it may be difficult to extract information that is useful for predicting the states. Thus, univariate prediction may sometimes be superior to multivariate prediction. Here, we compare univariate model-free time series predictions with multivariate ones, and demonstrate that univariate model-free prediction is better than multivariate one when the prediction steps are small, while multivariate prediction performs better when the prediction steps become larger. We show the validity of the former finding by using artificial datasets generated from the Lorenz 96 models and a real solar irradiance dataset. The results indicate that it is possible to determine which method is the best choice by considering how far into the future we want to predict.

  17. Scaling analysis of multi-variate intermittent time series

    NASA Astrophysics Data System (ADS)

    Kitt, Robert; Kalda, Jaan

    2005-08-01

    The scaling properties of the time series of asset prices and trading volumes of stock markets are analysed. It is shown that similar to the asset prices, the trading volume data obey multi-scaling length-distribution of low-variability periods. In the case of asset prices, such scaling behaviour can be used for risk forecasts: the probability of observing next day a large price movement is (super-universally) inversely proportional to the length of the ongoing low-variability period. Finally, a method is devised for a multi-factor scaling analysis. We apply the simplest, two-factor model to equity index and trading volume time series.

  18. A multi-variance analysis in the time domain

    NASA Technical Reports Server (NTRS)

    Walter, Todd

    1993-01-01

    Recently a new technique for characterizing the noise processes affecting oscillators was introduced. This technique minimizes the difference between the estimates of several different variances and their values as predicted by the standard power law model of noise. The method outlined makes two significant advancements: it uses exclusively time domain variances so that deterministic parameters such as linear frequency drift may be estimated, and it correctly fits the estimates using the chi-square distribution. These changes permit a more accurate fitting at long time intervals where there is the least information. This technique was applied to both simulated and real data with excellent results.

  19. It's T time: A study on the return period of multivariate problems

    NASA Astrophysics Data System (ADS)

    Michailidi, Eleni Maria; Balistrocchi, Matteo; Bacchi, Baldassare

    2016-04-01

    variables: hydrograph's peak flow, volume and shape. Consequently, a multivariate framework is needed for a more realistic view of the matter at hand. In recent years, the application of copula functions has facilitated overcoming the inadequacies of multivariate distributions as the problem is handled from two non-interwinding aspects: the dependence structure of the pair of variables and the marginal distributions. The main objective of this study is to investigate whether it is possible to find, in a multivariate space, a region where all the multivariate events produce 'risk' lower or greater than a fixed mean inter-occurrence of failures of one time every T-years. Preliminary results seem to confirm that it is impossible to obtain uniqueness in the definition.

  20. Decoupling in linear time-varying multivariable systems

    NASA Technical Reports Server (NTRS)

    Sankaran, V.

    1973-01-01

    The necessary and sufficient conditions for the decoupling of an m-input, m-output, linear time varying dynamical system by state variable feedback is described. The class of feedback matrices which decouple the system are illustrated. Systems which do not satisfy these results are described and systems with disturbances are considered. Some examples are illustrated to clarify the results.

  1. A wireless time synchronized event control system

    NASA Astrophysics Data System (ADS)

    Klug, Robert; Williams, Jonathan; Scheffel, Peter

    2014-05-01

    McQ has developed a wireless, time-synchronized, event control system to control, monitor, and record events with precise timing over large test sites for applications such as high speed rocket sled payload testing. Events of interest may include firing rocket motors and launch sleds, initiating flares, ejecting bombs, ejecting seats, triggering high speed cameras, measuring sled velocity, and triggering events based on a velocity window or other criteria. The system consists of Event Controllers, a Launch Controller, and a wireless network. The Event Controllers can be easily deployed at areas of interest within the test site and maintain sub-microsecond timing accuracy for monitoring sensors, electronically triggering other equipment and events, and providing timing signals to other test equipment. Recorded data and status information is reported over the wireless network to a server and user interface. Over the wireless network, the user interface configures the system based on a user specified mission plan and provides real time command, control, and monitoring of the devices and data. An overview of the system, its features, performance, and potential uses is presented.

  2. Event Discovery in Astronomical Time Series

    NASA Astrophysics Data System (ADS)

    Preston, D.; Protopapas, P.; Brodley, C.

    2009-09-01

    The discovery of events in astronomical time series data is a non-trival problem. Existing methods address the problem by requiring a fixed-sized sliding window which, given the varying lengths of events and sampling rates, could overlook important events. In this work, we develop probability models for finding the significance of an arbitrary-sized sliding window, and use these probabilities to find areas of significance. In addition, we present our analyses of major surveys archived at the Time Series Center, part of the Initiative in Innovative Computing at Harvard University. We applied our method to the time series data in order to discover events such as microlensing or any non-periodic events in the MACHO, OGLE and TAOS surveys. The analysis shows that the method is an effective tool for filtering out nearly 99% of noisy and uninteresting time series from a large set of data, but still provides full recovery of all known variable events (microlensing, blue star events, supernovae etc.). Furthermore, due to its efficiency, this method can be performed on-the-fly and will be used to analyze upcoming surveys, such as Pan-STARRS.

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

    ERIC Educational Resources Information Center

    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…

  4. Asymmetric Time Evolution and Indistinguishable Events

    SciTech Connect

    Bryant, P. W.

    2010-11-25

    With a time asymmetric theory, in which quantum mechanical time evolution is given by a semigroup of operators rather than by a group, the states of open systems are represented by density operators exhibiting a branching behavior. To treat the indistinguishably of the members of experimental ensembles, we hypothesize that environmental interference occurs during events that are themselves fundamentally indistinguishable.

  5. Discrete Events as Units of Perceived Time

    ERIC Educational Resources Information Center

    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…

  6. Learning a Mahalanobis Distance-Based Dynamic Time Warping Measure for Multivariate Time Series Classification.

    PubMed

    Mei, Jiangyuan; Liu, Meizhu; Wang, Yuan-Fang; Gao, Huijun

    2016-06-01

    Multivariate time series (MTS) datasets broadly exist in numerous fields, including health care, multimedia, finance, and biometrics. How to classify MTS accurately has become a hot research topic since it is an important element in many computer vision and pattern recognition applications. In this paper, we propose a Mahalanobis distance-based dynamic time warping (DTW) measure for MTS classification. The Mahalanobis distance builds an accurate relationship between each variable and its corresponding category. It is utilized to calculate the local distance between vectors in MTS. Then we use DTW to align those MTS which are out of synchronization or with different lengths. After that, how to learn an accurate Mahalanobis distance function becomes another key problem. This paper establishes a LogDet divergence-based metric learning with triplet constraint model which can learn Mahalanobis matrix with high precision and robustness. Furthermore, the proposed method is applied on nine MTS datasets selected from the University of California, Irvine machine learning repository and Robert T. Olszewski's homepage, and the results demonstrate the improved performance of the proposed approach. PMID:25966490

  7. Reinforcement genetic approach to coefficient estimation for multivariable nonlinear discrete-time dynamical systems

    NASA Astrophysics Data System (ADS)

    Chang, Wei-Der; Yan, Jun-Juh

    2006-10-01

    In this paper, we propose a novel genetic algorithm (GA) with a multi-crossover fashion to estimate the associated coefficients for a class of nonlinear discrete-time multivariable dynamical systems. Unlike the traditional crossover method of using two chromosomes, the proposed method uses three chromosomes to achieve a crossover. According to the adjusting direction by crossing three chromosomes, more excellent offspring can be produced. To solve the identification problem of multivariable nonlinear discrete-time systems, each of estimated system coefficients represents a gene, and a collection of genes is referred to as a chromosome in the view of GA. The chromosomes in the population are then evolved using the proposed multi-crossover method. An illustrative example of multivariable nonlinear systems is given to demonstrate the effectiveness, as compared with the traditional crossover method, of the proposed method.

  8. Multivariable Model for Time to First Treatment in Patients With Chronic Lymphocytic Leukemia

    PubMed Central

    Wierda, William G.; O'Brien, Susan; Wang, Xuemei; Faderl, Stefan; Ferrajoli, Alessandra; Do, Kim-Anh; Garcia-Manero, Guillermo; Cortes, Jorge; Thomas, Deborah; Koller, Charles A.; Burger, Jan A.; Lerner, Susan; Schlette, Ellen; Abruzzo, Lynne; Kantarjian, Hagop M.; Keating, Michael J.

    2011-01-01

    Purpose The clinical course for patients with chronic lymphocytic leukemia (CLL) is diverse; some patients have indolent disease, never needing treatment, whereas others have aggressive disease requiring early treatment. We continue to use criteria for active disease to initiate therapy. Multivariable analysis was performed to identify prognostic factors independently associated with time to first treatment for patients with CLL. Patients and Methods Traditional laboratory, clinical prognostic, and newer prognostic factors such as fluorescent in situ hybridization (FISH), IGHV mutation status, and ZAP-70 expression evaluated at first patient visit to MD Anderson Cancer Center were correlated by multivariable analysis with time to first treatment. This multivariable model was used to develop a nomogram—a weighted tool to calculate 2- and 4-year probability of treatment and estimate median time to first treatment. Results There were 930 previously untreated patients who had traditional and new prognostic factors evaluated; they did not have active CLL requiring initiation of treatment within 3 months of first visit and were observed for time to first treatment. The following were independently associated with shorter time to first treatment: three involved lymph node sites, increased size of cervical lymph nodes, presence of 17p deletion or 11q deletion by FISH, increased serum lactate dehydrogenase, and unmutated IGHV mutation status. Conclusion We developed a multivariable model that incorporates traditional and newer prognostic factors to identify patients at high risk for progression to treatment. This model may be useful to identify patients for early interventional trials. PMID:21969505

  9. Arbitrary eigenvalue assignments for linear time-varying multivariable control systems

    NASA Technical Reports Server (NTRS)

    Nguyen, Charles C.

    1987-01-01

    The problem of eigenvalue assignments for a class of linear time-varying multivariable systems is considered. Using matrix operators and canonical transformations, it is shown that a time-varying system that is 'lexicography-fixedly controllable' can be made via state feedback to be equivalent to a time-invariant system whose eigenvalues are arbitrarily assignable. A simple algorithm for the design of the state feedback is provided.

  10. Copula based flexible modeling of associations between clustered event times.

    PubMed

    Geerdens, Candida; Claeskens, Gerda; Janssen, Paul

    2016-07-01

    Multivariate survival data are characterized by the presence of correlation between event times within the same cluster. First, we build multi-dimensional copulas with flexible and possibly symmetric dependence structures for such data. In particular, clustered right-censored survival data are modeled using mixtures of max-infinitely divisible bivariate copulas. Second, these copulas are fit by a likelihood approach where the vast amount of copula derivatives present in the likelihood is approximated by finite differences. Third, we formulate conditions for clustered right-censored survival data under which an information criterion for model selection is either weakly consistent or consistent. Several of the familiar selection criteria are included. A set of four-dimensional data on time-to-mastitis is used to demonstrate the developed methodology. PMID:26210669

  11. Extracting tidal frequencies using multivariate harmonic analysis of sea level height time series

    NASA Astrophysics Data System (ADS)

    Amiri-Simkooei, A. R.; Zaminpardaz, S.; Sharifi, M. A.

    2014-10-01

    This contribution is seen as a first attempt to extract the tidal frequencies using a multivariate spectral analysis method applied to multiple time series of tide-gauge records. The existing methods are either physics-based in which the ephemeris of Moon, Sun and other planets are used, or are observation-based in which univariate analysis methods—Fourier and wavelet for instance—are applied to tidal observations. The existence of many long tide-gauge records around the world allows one to use tidal observations and extract the main tidal constituents for which efficient multivariate methods are to be developed. This contribution applies the multivariate least-squares harmonic estimation (LS-HE) to the tidal time series of the UK tide-gauge stations. The first 413 harmonics of the tidal constituents and their nonlinear components are provided using the multivariate LS-HE. A few observations of the research are highlighted: (1) the multivariate analysis takes information of multiple time series into account in an optimal least- squares sense, and thus the tidal frequencies have higher detection power compared to the univariate analysis. (2) Dominant tidal frequencies range from the long-term signals to the sixth-diurnal species interval. Higher frequencies have negligible effects. (3) The most important tidal constituents (the first 50 frequencies) ordered from their amplitudes range from 212 cm (M2) to 1 cm (OQ2) for the data set considered. There are signals in this list that are not available in the 145 main tidal frequencies of the literature. (4) Tide predictions using different lists of tidal frequencies on five different data sets around the world are compared. The prediction results using the first significant 50 constituents provided promising results on these locations of the world.

  12. Multivariate time series modeling of short-term system scale irrigation demand

    NASA Astrophysics Data System (ADS)

    Perera, Kushan C.; Western, Andrew W.; George, Biju; Nawarathna, Bandara

    2015-12-01

    Travel time limits the ability of irrigation system operators to react to short-term irrigation demand fluctuations that result from variations in weather, including very hot periods and rainfall events, as well as the various other pressures and opportunities that farmers face. Short-term system-wide irrigation demand forecasts can assist in system operation. Here we developed a multivariate time series (ARMAX) model to forecast irrigation demands with respect to aggregated service points flows (IDCGi, ASP) and off take regulator flows (IDCGi, OTR) based across 5 command areas, which included area covered under four irrigation channels and the study area. These command area specific ARMAX models forecast 1-5 days ahead daily IDCGi, ASP and IDCGi, OTR using the real time flow data recorded at the service points and the uppermost regulators and observed meteorological data collected from automatic weather stations. The model efficiency and the predictive performance were quantified using the root mean squared error (RMSE), Nash-Sutcliffe model efficiency coefficient (NSE), anomaly correlation coefficient (ACC) and mean square skill score (MSSS). During the evaluation period, NSE for IDCGi, ASP and IDCGi, OTR across 5 command areas were ranged 0.98-0.78. These models were capable of generating skillful forecasts (MSSS ⩾ 0.5 and ACC ⩾ 0.6) of IDCGi, ASP and IDCGi, OTR for all 5 lead days and IDCGi, ASP and IDCGi, OTR forecasts were better than using the long term monthly mean irrigation demand. Overall these predictive performance from the ARMAX time series models were higher than almost all the previous studies we are aware. Further, IDCGi, ASP and IDCGi, OTR forecasts have improved the operators' ability to react for near future irrigation demand fluctuations as the developed ARMAX time series models were self-adaptive to reflect the short-term changes in the irrigation demand with respect to various pressures and opportunities that farmers' face, such as

  13. A discrete-time Multiple Event Process Survival Mixture (MEPSUM) model.

    PubMed

    Dean, Danielle O; Bauer, Daniel J; Shanahan, Michael J

    2014-06-01

    Traditional survival analysis was developed to investigate the occurrence and timing of a single event, but researchers have recently begun to ask questions about the order and timing of multiple events. A multiple event process survival mixture model is developed here to analyze nonrepeatable events measured in discrete-time that may occur at the same point in time. Building on both traditional univariate survival analysis and univariate survival mixture analysis, the model approximates the underlying multivariate distribution of hazard functions via a discrete-point finite mixture in which the mixing components represent prototypical patterns of event occurrence. The model is applied in an empirical analysis concerning transitions to adulthood, where the events under study include parenthood, marriage, beginning full-time work, and obtaining a college degree. Promising opportunities, as well as possible limitations of the model and future directions for research, are discussed. PMID:24079930

  14. Multivariate spatial analysis of a heavy rain event in a densely populated delta city

    NASA Astrophysics Data System (ADS)

    Gaitan, Santiago; ten Veldhuis, Marie-claire; Bruni, Guenda; van de Giesen, Nick

    2014-05-01

    Delta cities account for half of the world's population and host key infrastructure and services for the global economic growth. Due to the characteristic geography of delta areas, these cities face high vulnerability to extreme weather and pluvial flooding risks, that are expected to increase as climate change drives heavier rain events. Besides, delta cities are subjected to fast urban densification processes that progressively make them more vulnerable to pluvial flooding. Delta cities need to be adapted to better cope with this threat. The mechanism leading to damage after heavy rains is not completely understood. For instance, current research has shown that rain intensities and volumes can only partially explain the occurrence and localization of rain-related insurance claims (Spekkers et al., 2013). The goal of this paper is to provide further insights into spatial characteristics of the urban environment that can significantly be linked to pluvial-related flooding impacts. To that end, a study-case has been selected: on October 12 to 14 2013, a heavy rain event triggered pluvial floods in Rotterdam, a densely populated city which is undergoing multiple climate adaptation efforts and is located in the Meuse river Delta. While the average yearly precipitation in this city is around 800 mm, local rain gauge measurements ranged from aprox. 60 to 130 mm just during these three days. More than 600 citizens' telephonic complaints reported impacts related to rainfall. The registry of those complaints, which comprises around 300 calls made to the municipality and another 300 to the fire brigade, was made available for research. Other accessible information about this city includes a series of rainfall measurements with up to 1 min time-step at 7 different locations around the city, ground-based radar rainfall data (1 Km^2 spatial resolution and 5 min time-step), a digital elevation model (50 cm of horizontal resolution), a model of overland-flow paths, cadastral

  15. Applying the multivariate time-rescaling theorem to neural population models

    PubMed Central

    Gerhard, Felipe; Haslinger, Robert; Pipa, Gordon

    2011-01-01

    Statistical models of neural activity are integral to modern neuroscience. Recently, interest has grown in modeling the spiking activity of populations of simultaneously recorded neurons to study the effects of correlations and functional connectivity on neural information processing. However any statistical model must be validated by an appropriate goodness-of-fit test. Kolmogorov-Smirnov tests based upon the time-rescaling theorem have proven to be useful for evaluating point-process-based statistical models of single-neuron spike trains. Here we discuss the extension of the time-rescaling theorem to the multivariate (neural population) case. We show that even in the presence of strong correlations between spike trains, models which neglect couplings between neurons can be erroneously passed by the univariate time-rescaling test. We present the multivariate version of the time-rescaling theorem, and provide a practical step-by-step procedure for applying it towards testing the sufficiency of neural population models. Using several simple analytically tractable models and also more complex simulated and real data sets, we demonstrate that important features of the population activity can only be detected using the multivariate extension of the test. PMID:21395436

  16. Genetic basis of adult migration timing in anadromous steelhead discovered through multivariate association testing.

    PubMed

    Hess, Jon E; Zendt, Joseph S; Matala, Amanda R; Narum, Shawn R

    2016-05-11

    Migration traits are presumed to be complex and to involve interaction among multiple genes. We used both univariate analyses and a multivariate random forest (RF) machine learning algorithm to conduct association mapping of 15 239 single nucleotide polymorphisms (SNPs) for adult migration-timing phenotype in steelhead (Oncorhynchus mykiss). Our study focused on a model natural population of steelhead that exhibits two distinct migration-timing life histories with high levels of admixture in nature. Neutral divergence was limited between fish exhibiting summer- and winter-run migration owing to high levels of interbreeding, but a univariate mixed linear model found three SNPs from a major effect gene to be significantly associated with migration timing (p < 0.000005) that explained 46% of trait variation. Alignment to the annotated Salmo salar genome provided evidence that all three SNPs localize within a 46 kb region overlapping GREB1-like (an oestrogen target gene) on chromosome Ssa03. Additionally, multivariate analyses with RF identified that these three SNPs plus 15 additional SNPs explained up to 60% of trait variation. These candidate SNPs may provide the ability to predict adult migration timing of steelhead to facilitate conservation management of this species, and this study demonstrates the benefit of multivariate analyses for association studies. PMID:27170720

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

    NASA Astrophysics Data System (ADS)

    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

  18. Supporting the Process of Exploring and Interpreting Space–Time Multivariate Patterns: The Visual Inquiry Toolkit

    PubMed Central

    Chen, Jin; MacEachren, Alan M.; Guo, Diansheng

    2009-01-01

    While many data sets carry geographic and temporal references, our ability to analyze these datasets lags behind our ability to collect them because of the challenges posed by both data complexity and tool scalability issues. This study develops a visual analytics approach that leverages human expertise with visual, computational, and cartographic methods to support the application of visual analytics to relatively large spatio-temporal, multivariate data sets. We develop and apply a variety of methods for data clustering, pattern searching, information visualization, and synthesis. By combining both human and machine strengths, this approach has a better chance to discover novel, relevant, and potentially useful information that is difficult to detect by any of the methods used in isolation. We demonstrate the effectiveness of the approach by applying the Visual Inquiry Toolkit we developed to analyze a data set containing geographically referenced, time-varying and multivariate data for U.S. technology industries. PMID:19960096

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

    NASA Astrophysics Data System (ADS)

    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.

  20. A Visualization System for Space-Time and Multivariate Patterns (VIS-STAMP)

    PubMed Central

    Guo, Diansheng; Chen, Jin; MacEachren, Alan M.; Liao, Ke

    2011-01-01

    The research reported here integrates computational, visual, and cartographic methods to develop a geovisual analytic approach for exploring and understanding spatio-temporal and multivariate patterns. The developed methodology and tools can help analysts investigate complex patterns across multivariate, spatial, and temporal dimensions via clustering, sorting, and visualization. Specifically, the approach involves a self-organizing map, a parallel coordinate plot, several forms of reorderable matrices (including several ordering methods), a geographic small multiple display, and a 2-dimensional cartographic color design method. The coupling among these methods leverages their independent strengths and facilitates a visual exploration of patterns that are difficult to discover otherwise. The visualization system we developed supports overview of complex patterns and, through a variety of interactions, enables users to focus on specific patterns and examine detailed views. We demonstrate the system with an application to the IEEE InfoVis 2005 Contest data set, which contains time-varying, geographically referenced, and multivariate data for technology companies in the US. PMID:17073369

  1. A multivariate based event detection method and performance comparison with two baseline methods.

    PubMed

    Liu, Shuming; Smith, Kate; Che, Han

    2015-09-01

    Early warning systems have been widely deployed to protect water systems from accidental and intentional contamination events. Conventional detection algorithms are often criticized for having high false positive rates and low true positive rates. This mainly stems from the inability of these methods to determine whether variation in sensor measurements is caused by equipment noise or the presence of contamination. This paper presents a new detection method that identifies the existence of contamination by comparing Euclidean distances of correlation indicators, which are derived from the correlation coefficients of multiple water quality sensors. The performance of the proposed method was evaluated using data from a contaminant injection experiment and compared with two baseline detection methods. The results show that the proposed method can differentiate between fluctuations caused by equipment noise and those due to the presence of contamination. It yielded higher possibility of detection and a lower false alarm rate than the two baseline methods. With optimized parameter values, the proposed method can correctly detect 95% of all contamination events with a 2% false alarm rate. PMID:25996758

  2. A pairwise likelihood-based approach for changepoint detection in multivariate time series models

    PubMed Central

    Ma, Ting Fung; Yau, Chun Yip

    2016-01-01

    This paper develops a composite likelihood-based approach for multiple changepoint estimation in multivariate time series. We derive a criterion based on pairwise likelihood and minimum description length for estimating the number and locations of changepoints and for performing model selection in each segment. The number and locations of the changepoints can be consistently estimated under mild conditions and the computation can be conducted efficiently with a pruned dynamic programming algorithm. Simulation studies and real data examples demonstrate the statistical and computational efficiency of the proposed method. PMID:27279666

  3. Multivariable time series prediction for the icing process on overhead power transmission line.

    PubMed

    Li, Peng; Zhao, Na; Zhou, Donghua; Cao, Min; Li, Jingjie; Shi, Xinling

    2014-01-01

    The design of monitoring and predictive alarm systems is necessary for successful overhead power transmission line icing. Given the characteristics of complexity, nonlinearity, and fitfulness in the line icing process, a model based on a multivariable time series is presented here to predict the icing load of a transmission line. In this model, the time effects of micrometeorology parameters for the icing process have been analyzed. The phase-space reconstruction theory and machine learning method were then applied to establish the prediction model, which fully utilized the history of multivariable time series data in local monitoring systems to represent the mapping relationship between icing load and micrometeorology factors. Relevant to the characteristic of fitfulness in line icing, the simulations were carried out during the same icing process or different process to test the model's prediction precision and robustness. According to the simulation results for the Tao-Luo-Xiong Transmission Line, this model demonstrates a good accuracy of prediction in different process, if the prediction length is less than two hours, and would be helpful for power grid departments when deciding to take action in advance to address potential icing disasters. PMID:25136653

  4. Multivariable Time Series Prediction for the Icing Process on Overhead Power Transmission Line

    PubMed Central

    Li, Peng; Zhao, Na; Zhou, Donghua; Cao, Min; Li, Jingjie; Shi, Xinling

    2014-01-01

    The design of monitoring and predictive alarm systems is necessary for successful overhead power transmission line icing. Given the characteristics of complexity, nonlinearity, and fitfulness in the line icing process, a model based on a multivariable time series is presented here to predict the icing load of a transmission line. In this model, the time effects of micrometeorology parameters for the icing process have been analyzed. The phase-space reconstruction theory and machine learning method were then applied to establish the prediction model, which fully utilized the history of multivariable time series data in local monitoring systems to represent the mapping relationship between icing load and micrometeorology factors. Relevant to the characteristic of fitfulness in line icing, the simulations were carried out during the same icing process or different process to test the model's prediction precision and robustness. According to the simulation results for the Tao-Luo-Xiong Transmission Line, this model demonstrates a good accuracy of prediction in different process, if the prediction length is less than two hours, and would be helpful for power grid departments when deciding to take action in advance to address potential icing disasters. PMID:25136653

  5. A Multivariate Statistical Approach based on a Dynamic Moving Storms (DMS) Generator for Estimating the Frequency of Extreme Storm Events

    NASA Astrophysics Data System (ADS)

    Fang, N. Z.; Gao, S.

    2015-12-01

    Challenges of fully considering the complexity among spatially and temporally varied rainfall always exist in flood frequency analysis. Conventional approaches that simplify the complexity of spatiotemporal interactions generally undermine their impacts on flood risks. A previously developed stochastic storm generator called Dynamic Moving Storms (DMS) aims to address the highly-dependent nature of precipitation field: spatial variability, temporal variability, and movement of the storm. The authors utilize a multivariate statistical approach based on DMS to estimate the occurrence probability or frequency of extreme storm events. Fifteen years of radar rainfall data is used to generate a large number of synthetic storms as basis for statistical assessment. Two parametric retrieval algorithms are developed to recognize rain cells and track storm motions respectively. The resulted parameters are then used to establish probability density functions (PDFs), which are fitted to parametric distribution functions for further Monte Carlo simulations. Consequently, over 1,000,000 synthetic storms are generated based on twelve retrieved parameters for integrated risk assessment and ensemble forecasts. Furthermore, PDFs for parameters are used to calculate joint probabilities based on 2-dimensional Archimedean-Copula functions to determine the occurrence probabilities of extreme events. The approach is validated on the Upper Trinity River watershed and the generated results are compared with those from traditional rainfall frequency studies (i.e. Intensity-Duration-Frequency curves, and Areal Reduction Factors).

  6. Uniform approach to linear and nonlinear interrelation patterns in multivariate time series

    NASA Astrophysics Data System (ADS)

    Rummel, Christian; Abela, Eugenio; Müller, Markus; Hauf, Martinus; Scheidegger, Olivier; Wiest, Roland; Schindler, Kaspar

    2011-06-01

    Currently, a variety of linear and nonlinear measures is in use to investigate spatiotemporal interrelation patterns of multivariate time series. Whereas the former are by definition insensitive to nonlinear effects, the latter detect both nonlinear and linear interrelation. In the present contribution we employ a uniform surrogate-based approach, which is capable of disentangling interrelations that significantly exceed random effects and interrelations that significantly exceed linear correlation. The bivariate version of the proposed framework is explored using a simple model allowing for separate tuning of coupling and nonlinearity of interrelation. To demonstrate applicability of the approach to multivariate real-world time series we investigate resting state functional magnetic resonance imaging (rsfMRI) data of two healthy subjects as well as intracranial electroencephalograms (iEEG) of two epilepsy patients with focal onset seizures. The main findings are that for our rsfMRI data interrelations can be described by linear cross-correlation. Rejection of the null hypothesis of linear iEEG interrelation occurs predominantly for epileptogenic tissue as well as during epileptic seizures.

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

    PubMed

    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. PMID:25190632

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

    USGS Publications Warehouse

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

    2013-01-01

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

  9. Multi-variate models are essential for understanding vertebrate diversification in deep time

    PubMed Central

    Benson, Roger B. J.; Mannion, Philip D.

    2012-01-01

    Statistical models are helping palaeontologists to elucidate the history of biodiversity. Sampling standardization has been extensively applied to remedy the effects of uneven sampling in large datasets of fossil invertebrates. However, many vertebrate datasets are smaller, and the issue of uneven sampling has commonly been ignored, or approached using pairwise comparisons with a numerical proxy for sampling effort. Although most authors find a strong correlation between palaeodiversity and sampling proxies, weak correlation is recorded in some datasets. This has led several authors to conclude that uneven sampling does not influence our view of vertebrate macroevolution. We demonstrate that multi-variate regression models incorporating a model of underlying biological diversification, as well as a sampling proxy, fit observed sauropodomorph dinosaur palaeodiversity best. This bivariate model is a better fit than separate univariate models, and illustrates that observed palaeodiversity is a composite pattern, representing a biological signal overprinted by variation in sampling effort. Multi-variate models and other approaches that consider sampling as an essential component of palaeodiversity are central to gaining a more complete understanding of deep time vertebrate diversification. PMID:21697163

  10. Determining mixed linear-nonlinear coupled differential equations from multivariate discrete time series sequences

    NASA Astrophysics Data System (ADS)

    Irving, A. D.; Dewson, T.

    1997-02-01

    A new method is described for extracting mixed linear-nonlinear coupled differential equations from multivariate discrete time series data. It is assumed in the present work that the solution of the coupled ordinary differential equations can be represented as a multivariate Volterra functional expansion. A tractable hierarchy of moment equations is generated by operating on a suitably truncated Volterra functional expansion. The hierarchy facilitates the calculation of the coefficients of the coupled differential equations. In order to demonstrate the method's ability to accurately estimate the coefficients of the governing differential equations, it is applied to data derived from the numerical solution of the Lorenz equations with additive noise. The method is then used to construct a dynamic global mid- and high-magnetic latitude ionospheric model where nonlinear phenomena such as period doubling and quenching occur. It is shown that the estimated inhomogeneous coupled second-order differential equation model for the ionospheric foF2 peak plasma density can accurately forecast the future behaviour of a set of ionosonde stations which encompass the earth. Finally, the method is used to forecast the future behaviour of a portfolio of Japanese common stock prices. The hierarchy method can be used to characterise the observed behaviour of a wide class of coupled linear and mixed linear-nonlinear phenomena.

  11. Reconstructing causal pathways and optimal prediction from multivariate time series using the Tigramite package

    NASA Astrophysics Data System (ADS)

    Runge, Jakob

    2016-04-01

    Causal reconstruction techniques from multivariate time series have become a popular approach to analyze interactions in complex systems such as the Earth. These approaches allow to exclude effects of common drivers and indirect influences. Practical applications are, however, especially challenging if nonlinear interactions are taken into account and for typically strongly autocorrelated climate time series. Here we discuss a new reconstruction approach with accompanying software package (Tigramite) and focus on two applications: (1) Information or perturbation transfer along causal pathways. This method allows to detect and quantify which intermediate nodes are important mediators of an interaction mechanism and is illustrated to disentangle pathways of atmospheric flow over Europe and for the ENSO - Indian Monsoon interaction mechanism. (2) A nonlinear model-free prediction technique that efficiently utilizes causal drivers and can be shown to yield information-theoretically optimal predictors avoiding over-fitting. The performance of this framework is illustrated on a climatological index of El Nino Southern Oscillation. References: Runge, J. (2015). Quantifying information transfer and mediation along causal pathways in complex systems. Phys. Rev. E, 92(6), 062829. doi:10.1103/PhysRevE.92.062829 Runge, J., Donner, R. V., & Kurths, J. (2015). Optimal model-free prediction from multivariate time series. Phys. Rev. E, 91(5), 052909. doi:10.1103/PhysRevE.91.052909 Runge, J., Petoukhov, V., Donges, J. F., Hlinka, J., Jajcay, N., Vejmelka, M., … Kurths, J. (2015). Identifying causal gateways and mediators in complex spatio-temporal systems. Nature Communications, 6, 8502. doi:10.1038/ncomms9502

  12. Time-varying nonstationary multivariate risk analysis using a dynamic Bayesian copula

    NASA Astrophysics Data System (ADS)

    Sarhadi, Ali; Burn, Donald H.; Concepción Ausín, María.; Wiper, Michael P.

    2016-03-01

    A time-varying risk analysis is proposed for an adaptive design framework in nonstationary conditions arising from climate change. A Bayesian, dynamic conditional copula is developed for modeling the time-varying dependence structure between mixed continuous and discrete multiattributes of multidimensional hydrometeorological phenomena. Joint Bayesian inference is carried out to fit the marginals and copula in an illustrative example using an adaptive, Gibbs Markov Chain Monte Carlo (MCMC) sampler. Posterior mean estimates and credible intervals are provided for the model parameters and the Deviance Information Criterion (DIC) is used to select the model that best captures different forms of nonstationarity over time. This study also introduces a fully Bayesian, time-varying joint return period for multivariate time-dependent risk analysis in nonstationary environments. The results demonstrate that the nature and the risk of extreme-climate multidimensional processes are changed over time under the impact of climate change, and accordingly the long-term decision making strategies should be updated based on the anomalies of the nonstationary environment.

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

    PubMed Central

    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

  14. Nonparametric estimation of the survival function for ordered multivariate failure time data: A comparative study.

    PubMed

    Meira-Machado, Luís; Sestelo, Marta; Gonçalves, Andreia

    2016-05-01

    In longitudinal studies of disease, patients may experience several events through a follow-up period. In these studies, the sequentially ordered events are often of interest and lead to problems that have received much attention recently. Issues of interest include the estimation of bivariate survival, marginal distributions, and the conditional distribution of gap times. In this work, we consider the estimation of the survival function conditional to a previous event. Different nonparametric approaches will be considered for estimating these quantities, all based on the Kaplan-Meier estimator of the survival function. We explore the finite sample behavior of the estimators through simulations. The different methods proposed in this article are applied to a dataset from a German Breast Cancer Study. The methods are used to obtain predictors for the conditional survival probabilities as well as to study the influence of recurrence in overall survival. PMID:26455826

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

    PubMed Central

    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. PMID:25905027

  16. Circuit for measuring time differences among events

    DOEpatents

    Romrell, Delwin M.

    1977-01-01

    An electronic circuit has a plurality of input terminals. Application of a first input signal to any one of the terminals initiates a timing sequence. Later inputs to the same terminal are ignored but a later input to any other terminal of the plurality generates a signal which can be used to measure the time difference between the later input and the first input signal. Also, such time differences may be measured between the first input signal and an input signal to any other terminal of the plurality or the circuit may be reset at any time by an external reset signal.

  17. Bicomponent Trend Maps: A Multivariate Approach to Visualizing Geographic Time Series

    PubMed Central

    Schroeder, Jonathan P.

    2012-01-01

    The most straightforward approaches to temporal mapping cannot effectively illustrate all potentially significant aspects of spatio-temporal patterns across many regions and times. This paper introduces an alternative approach, bicomponent trend mapping, which employs a combination of principal component analysis and bivariate choropleth mapping to illustrate two distinct dimensions of long-term trend variations. The approach also employs a bicomponent trend matrix, a graphic that illustrates an array of typical trend types corresponding to different combinations of scores on two principal components. This matrix is useful not only as a legend for bicomponent trend maps but also as a general means of visualizing principal components. To demonstrate and assess the new approach, the paper focuses on the task of illustrating population trends from 1950 to 2000 in census tracts throughout major U.S. urban cores. In a single static display, bicomponent trend mapping is not able to depict as wide a variety of trend properties as some other multivariate mapping approaches, but it can make relationships among trend classes easier to interpret, and it offers some unique flexibility in classification that could be particularly useful in an interactive data exploration environment. PMID:23504193

  18. Young Children's Memory for the Times of Personal Past Events

    PubMed Central

    Pathman, Thanujeni; Larkina, Marina; Burch, Melissa; Bauer, Patricia J.

    2012-01-01

    Remembering the temporal information associated with personal past events is critical for autobiographical memory, yet we know relatively little about the development of this capacity. In the present research, we investigated temporal memory for naturally occurring personal events in 4-, 6-, and 8-year-old children. Parents recorded unique events in which their children participated during a 4-month period. At test, children made relative recency judgments and estimated the time of each event using conventional time-scales (time of day, day of week, month of year, and season). Children also were asked to provide justifications for their time-scale judgments. Six- and 8-year-olds, but not 4-year-olds, accurately judged the order of two distinct events. There were age-related improvements in children's estimation of the time of events using conventional time-scales. Older children provided more justifications for their time-scale judgments compared to younger children. Relations between correct responding on the time-scale judgments and provision of meaningful justifications suggest that children may use that information to reconstruct the times associated with past events. The findings can be used to chart a developmental trajectory of performance in temporal memory for personal past events, and have implications for our understanding of autobiographical memory development. PMID:23687467

  19. Detection of flood events in hydrological discharge time series

    NASA Astrophysics Data System (ADS)

    Seibert, S. P.; Ehret, U.

    2012-04-01

    The shortcomings of mean-squared-error (MSE) based distance metrics are well known (Beran 1999, Schaeffli & Gupta 2007) and the development of novel distance metrics (Pappenberger & Beven 2004, Ehret & Zehe 2011) and multi-criteria-approaches enjoy increasing popularity (Reusser 2009, Gupta et al. 2009). Nevertheless, the hydrological community still lacks metrics which identify and thus, allow signature based evaluations of hydrological discharge time series. Signature based information/evaluations are required wherever specific time series features, such as flood events, are of special concern. Calculation of event based runoff coefficients or precise knowledge on flood event characteristics (like onset or duration of rising limp or the volume of falling limp, etc.) are possible applications. The same applies for flood forecasting/simulation models. Directly comparing simulated and observed flood event features may reveal thorough insights into model dynamics. Compared to continuous space-and-time-aggregated distance metrics, event based evaluations may provide answers like the distributions of event characteristics or the percentage of the events which were actually reproduced by a hydrological model. It also may help to provide information on the simulation accuracy of small, medium and/or large events in terms of timing and magnitude. However, the number of approaches which expose time series features is small and their usage is limited to very specific questions (Merz & Blöschl 2009, Norbiato et al. 2009). We believe this is due to the following reasons: i) a generally accepted definition of the signature of interest is missing or difficult to obtain (in our case: what makes a flood event a flood event?) and/or ii) it is difficult to translate such a definition into a equation or (graphical) procedure which exposes the feature of interest in the discharge time series. We reviewed approaches which detect event starts and/or ends in hydrological discharge time

  20. ETARA - EVENT TIME AVAILABILITY, RELIABILITY ANALYSIS

    NASA Technical Reports Server (NTRS)

    Viterna, L. A.

    1994-01-01

    The ETARA system was written to evaluate the performance of the Space Station Freedom Electrical Power System, but the methodology and software can be modified to simulate any system that can be represented by a block diagram. ETARA is an interactive, menu-driven reliability, availability, and maintainability (RAM) simulation program. Given a Reliability Block Diagram representation of a system, the program simulates the behavior of the system over a specified period of time using Monte Carlo methods to generate block failure and repair times as a function of exponential and/or Weibull distributions. ETARA can calculate availability parameters such as equivalent availability, state availability (percentage of time at a particular output state capability), continuous state duration and number of state occurrences. The program can simulate initial spares allotment and spares replenishment for a resupply cycle. The number of block failures are tabulated both individually and by block type. ETARA also records total downtime, repair time, and time waiting for spares. Maintenance man-hours per year and system reliability, with or without repair, at or above a particular output capability can also be calculated. The key to using ETARA is the development of a reliability or availability block diagram. The block diagram is a logical graphical illustration depicting the block configuration necessary for a function to be successfully accomplished. Each block can represent a component, a subsystem, or a system. The function attributed to each block is considered for modeling purposes to be either available or unavailable; there are no degraded modes of block performance. A block does not have to represent physically connected hardware in the actual system to be connected in the block diagram. The block needs only to have a role in contributing to an available system function. ETARA can model the RAM characteristics of systems represented by multilayered, nesting block diagrams

  1. Balance characteristics of multivariate background error covariance for rainy and dry seasons and their impact on precipitation forecasts of two rainfall events

    NASA Astrophysics Data System (ADS)

    Chen, Yaodeng; Xia, Xue; Min, Jinzhong; Huang, Xiang-Yu; Rizvi, Syed R. H.

    2016-02-01

    Atmospheric moisture content or humidity is an important analysis variable of any meteorological data assimilation system. The humidity analysis can be univariate, using humidity background (normally short-range numerical forecasts) and humidity observations. However, more and more data assimilation systems are multivariate, analyzing humidity together with wind, temperature and pressure. Background error covariances, with unbalanced velocity potential and humidity in the multivariate formulation, are generated from weather research and forecasting model forecasts, collected over a summer rainy season and a winter dry season. The unbalanced velocity potential and humidity related correlations are shown to be significantly larger, indicating more important roles unbalanced velocity potential and humidity play, in the rainy season than that in the dry season. Three cycling data assimilation experiments of two rainfall events in the middle and lower reaches of the Yangtze River are carried out. The experiments differ in the formulation of the background error covariances. Results indicate that only including unbalanced velocity potential in the multivariate background error covariance improves wind analyses, but has little impact on temperature and humidity analyses. In contrast, further including humidity in the multivariate background error covariance although has a slight negative effect on wind analyses and a neutral effect on temperature analyses, but significantly improves humidity analyses, leading to precipitation forecasts more consistent with China Hourly Merged Precipitation Analysis.

  2. Dynamic Modelling and Statistical Analysis of Event Times

    PubMed Central

    Peña, Edsel A.

    2006-01-01

    This review article provides an overview of recent work in the modelling and analysis of recurrent events arising in engineering, reliability, public health, biomedical, and other areas. Recurrent event modelling possesses unique facets making it different and more difficult to handle than single event settings. For instance, the impact of an increasing number of event occurrences needs to be taken into account, the effects of covariates should be considered, potential association among the inter-event times within a unit cannot be ignored, and the effects of performed interventions after each event occurrence need to be factored in. A recent general class of models for recurrent events which simultaneously accommodates these aspects is described. Statistical inference methods for this class of models are presented and illustrated through applications to real data sets. Some existing open research problems are described. PMID:17906740

  3. Nuclear event zero-time calculation and uncertainty evaluation.

    PubMed

    Pan, Pujing; Ungar, R Kurt

    2012-04-01

    It is important to know the initial time, or zero-time, of a nuclear event such as a nuclear weapon's test, a nuclear power plant accident or a nuclear terrorist attack (e.g. with an improvised nuclear device, IND). Together with relevant meteorological information, the calculated zero-time is used to help locate the origin of a nuclear event. The zero-time of a nuclear event can be derived from measured activity ratios of two nuclides. The calculated zero-time of a nuclear event would not be complete without an appropriately evaluated uncertainty term. In this paper, analytical equations for zero-time and the associated uncertainty calculations are derived using a measured activity ratio of two nuclides. Application of the derived equations is illustrated in a realistic example using data from the last Chinese thermonuclear test in 1980. PMID:22305002

  4. Family Events and the Timing of Intergenerational Transfers

    ERIC Educational Resources Information Center

    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

    PubMed Central

    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. Real-time measurements, rare events and photon economics

    NASA Astrophysics Data System (ADS)

    Jalali, B.; Solli, D. R.; Goda, K.; Tsia, K.; Ropers, C.

    2010-07-01

    Rogue events otherwise known as outliers and black swans are singular, rare, events that carry dramatic impact. They appear in seemingly unconnected systems in the form of oceanic rogue waves, stock market crashes, evolution, and communication systems. Attempts to understand the underlying dynamics of such complex systems that lead to spectacular and often cataclysmic outcomes have been frustrated by the scarcity of events, resulting in insufficient statistical data, and by the inability to perform experiments under controlled conditions. Extreme rare events also occur in ultrafast physical sciences where it is possible to collect large data sets, even for rare events, in a short time period. The knowledge gained from observing rare events in ultrafast systems may provide valuable insight into extreme value phenomena that occur over a much slower timescale and that have a closer connection with human experience. One solution is a real-time ultrafast instrument that is capable of capturing singular and randomly occurring non-repetitive events. The time stretch technology developed during the past 13 years is providing a powerful tool box for reaching this goal. This paper reviews this technology and discusses its use in capturing rogue events in electronic signals, spectroscopy, and imaging. We show an example in nonlinear optics where it was possible to capture rare and random solitons whose unusual statistical distribution resemble those observed in financial markets. The ability to observe the true spectrum of each event in real time has led to important insight in understanding the underlying process, which in turn has made it possible to control soliton generation leading to improvement in the coherence of supercontinuum light. We also show a new class of fast imagers which are being considered for early detection of cancer because of their potential ability to detect rare diseased cells (so called rogue cells) in a large population of healthy cells.

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

    PubMed

    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. PMID:26529734

  8. Moving Events in Time: Time-Referent Hand-Arm Movements Influence Perceived Temporal Distance to Past Events

    ERIC Educational Resources Information Center

    Blom, Stephanie S. A. H.; Semin, Gun R.

    2013-01-01

    We examine and find support for the hypothesis that time-referent hand-arm movements influence temporal judgments. In line with the concept of "left is associated with earlier times, and right is associated with later times," we show that performing left (right) hand-arm movements while thinking about a past event increases (decreases) the…

  9. Effects of alcohol intake on time-based event expectations.

    PubMed

    Kunchulia, Marina; Thomaschke, Roland

    2016-04-01

    Previous evidence suggests that alcohol affects various forms of temporal cognition. However, there are presently no studies investigating whether and how alcohol affects on time-based event expectations. Here, we investigated the effects of alcohol on time-based event expectations. Seventeen healthy volunteers, aged between 19 and 36 years, participated. We employed a variable foreperiod paradigm with temporally predictable events, mimicking a computer game. Error rate and reaction time were analyzed in placebo (0 g/kg), low dose (0.2 g/kg) and high dose (0.6 g/kg) conditions. We found that alcohol intake did not eliminate, but substantially reduced, the formation of time-based expectancy. This effect was stronger for high doses, than for low doses, of alcohol. As a result of our studies, we have evidence that alcohol intake impairs time-based event expectations. The mechanism by which the level of alcohol impairs time-based event expectations needs to be clarified by future research. PMID:26680768

  10. Asynchronous visual event-based time-to-contact.

    PubMed

    Clady, Xavier; Clercq, Charles; Ieng, Sio-Hoi; Houseini, Fouzhan; Randazzo, Marco; Natale, Lorenzo; Bartolozzi, Chiara; Benosman, Ryad

    2014-01-01

    Reliable and fast sensing of the environment is a fundamental requirement for autonomous mobile robotic platforms. Unfortunately, the frame-based acquisition paradigm at the basis of main stream artificial perceptive systems is limited by low temporal dynamics and redundant data flow, leading to high computational costs. Hence, conventional sensing and relative computation are obviously incompatible with the design of high speed sensor-based reactive control for mobile applications, that pose strict limits on energy consumption and computational load. This paper introduces a fast obstacle avoidance method based on the output of an asynchronous event-based time encoded imaging sensor. The proposed method relies on an event-based Time To Contact (TTC) computation based on visual event-based motion flows. The approach is event-based in the sense that every incoming event adds to the computation process thus allowing fast avoidance responses. The method is validated indoor on a mobile robot, comparing the event-based TTC with a laser range finder TTC, showing that event-based sensing offers new perspectives for mobile robotics sensing. PMID:24570652

  11. Asynchronous visual event-based time-to-contact

    PubMed Central

    Clady, Xavier; Clercq, Charles; Ieng, Sio-Hoi; Houseini, Fouzhan; Randazzo, Marco; Natale, Lorenzo; Bartolozzi, Chiara; Benosman, Ryad

    2014-01-01

    Reliable and fast sensing of the environment is a fundamental requirement for autonomous mobile robotic platforms. Unfortunately, the frame-based acquisition paradigm at the basis of main stream artificial perceptive systems is limited by low temporal dynamics and redundant data flow, leading to high computational costs. Hence, conventional sensing and relative computation are obviously incompatible with the design of high speed sensor-based reactive control for mobile applications, that pose strict limits on energy consumption and computational load. This paper introduces a fast obstacle avoidance method based on the output of an asynchronous event-based time encoded imaging sensor. The proposed method relies on an event-based Time To Contact (TTC) computation based on visual event-based motion flows. The approach is event-based in the sense that every incoming event adds to the computation process thus allowing fast avoidance responses. The method is validated indoor on a mobile robot, comparing the event-based TTC with a laser range finder TTC, showing that event-based sensing offers new perspectives for mobile robotics sensing. PMID:24570652

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

    NASA Astrophysics Data System (ADS)

    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

  13. Identifying Multiple Periodicities in Sparse Photon Event Time Series

    NASA Astrophysics Data System (ADS)

    Koen, Chris

    2016-04-01

    The data considered are event times (e.g. photon arrival times, or the occurrence of sharp pulses). The source is multiperiodic, or the data could be multiperiodic because several unresolved sources contribute to the time series. Most events may be unobserved, either because the source is intermittent, or because some events are below the detection limit. The data may also be contaminated by spurious pulses. The problem considered is the determination of the periods in the data. A two-step procedure is proposed: in the first, a likely period is identified; in the second, events associated with this periodicity are removed from the time series. The steps are repeated until the remaining events do not exhibit any periodicity. A number of period-finding methods from the literature are reviewed, and a new maximum likelihood statistic is also introduced. It is shown that the latter is competitive compared to other techniques. The proposed methodology is tested on simulated data. Observations of two rotating radio transients are discussed, but contrary to claims in the literature, no evidence for multiperiodicity could be found.

  14. Identifying multiple periodicities in sparse photon event time series

    NASA Astrophysics Data System (ADS)

    Koen, Chris

    2016-07-01

    The data considered are event times (e.g. photon arrival times, or the occurrence of sharp pulses). The source is multiperiodic, or the data could be multiperiodic because several unresolved sources contribute to the time series. Most events may be unobserved, either because the source is intermittent, or because some events are below the detection limit. The data may also be contaminated by spurious pulses. The problem considered is the determination of the periods in the data. A two-step procedure is proposed: in the first, a likely period is identified; in the second, events associated with this periodicity are removed from the time series. The steps are repeated until the remaining events do not exhibit any periodicity. A number of period-finding methods from the literature are reviewed, and a new maximum likelihood statistic is also introduced. It is shown that the latter is competitive compared to other techniques. The proposed methodology is tested on simulated data. Observations of two rotating radio transients are discussed, but contrary to claims in the literature, no evidence for multiperiodicity could be found.

  15. Statistical issues in the analysis of adverse events in time-to-event data.

    PubMed

    Allignol, Arthur; Beyersmann, Jan; Schmoor, Claudia

    2016-07-01

    The aim of this work is to shed some light on common issues in the statistical analysis of adverse events (AEs) in clinical trials, when the main outcome is a time-to-event endpoint. To begin, we show that AEs are always subject to competing risks. That is, the occurrence of a certain AE may be precluded by occurrence of the main time-to-event outcome or by occurrence of another (fatal) AE. This has raised concerns on 'informative' censoring. We show that, in general, neither simple proportions nor Kaplan-Meier estimates of AE occurrence should be used, but common survival techniques for hazards that censor the competing event are still valid, but incomplete analyses. They must be complemented by an analogous analysis of the competing event for inference on the cumulative AE probability. The commonly used incidence rate (or incidence density) is a valid estimator of the AE hazard assuming it to be time constant. An estimator of the cumulative AE probability can be derived if the incidence rate of AE is combined with an estimator of the competing hazard. We discuss less restrictive analyses using non-parametric and semi-parametric approaches. We first consider time-to-first-AE analyses and then briefly discuss how they can be extended to the analysis of recurrent AEs. We will give a practical presentation with illustration of the methods by a simple example. Copyright © 2016 John Wiley & Sons, Ltd. PMID:26929180

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

    PubMed

    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 < .05), 38.6% higher inpatient caseloads (p < .01), and 55.9% higher emotional stress scores (p < .01). There was a trend for reported events to also be associated with less 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. PMID:23551380

  17. Events in time: Basic analysis of Poisson data

    SciTech Connect

    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.

  18. Deconstructing events: The neural bases for space, time, and causality

    PubMed Central

    Kranjec, Alexander; Cardillo, Eileen R.; Lehet, Matthew; Chatterjee, Anjan

    2013-01-01

    Space, time, and causality provide a natural structure for organizing our experience. These abstract categories allow us to think relationally in the most basic sense; understanding simple events require one to represent the spatial relations among objects, the relative durations of actions or movements, and links between causes and effects. The present fMRI study investigates the extent to which the brain distinguishes between these fundamental conceptual domains. Participants performed a one-back task with three conditions of interest (SPACE, TIME and CAUSALITY). Each condition required comparing relations between events in a simple verbal narrative. Depending on the condition, participants were instructed to either attend to the spatial, temporal, or causal characteristics of events, but between participants, each particular event relation appeared in all three conditions. Contrasts compared neural activity during each condition against the remaining two and revealed how thinking about events is deconstructed neurally. Space trials recruited neural areas traditionally associated with visuospatial processing, primarily bilateral frontal and occipitoparietal networks. Causality trials activated areas previously found to underlie causal thinking and thematic role assignment, such as left medial frontal, and left middle temporal gyri, respectively. Causality trials also produced activations in SMA, caudate, and cerebellum; cortical and subcortical regions associated with the perception of time at different timescales. The TIME contrast however, produced no significant effects. This pattern, indicating negative results for TIME trials, but positive effects for CAUSALITY trials in areas important for time perception, motivated additional overlap analyses to further probe relations between domains. The results of these analyses suggest a closer correspondence between time and causality than between time and space. PMID:21861674

  19. Estimating time-varying effects for overdispersed recurrent events data with treatment switching

    PubMed Central

    CHEN, QINGXIA; ZENG, DONGLIN; IBRAHIM, JOSEPH G.; AKACHA, MOUNA; SCHMIDLI, HEINZ

    2014-01-01

    Summary In the analysis of multivariate event times, frailty models assuming time-independent regression coefficients are often considered, mainly due to their mathematical convenience. In practice, regression coefficients are often time dependent and the temporal effects are of clinical interest. Motivated by a phase III clinical trial in multiple sclerosis, we develop a semiparametric frailty modelling approach to estimate time-varying effects for overdispersed recurrent events data with treatment switching. The proposed model incorporates the treatment switching time in the time-varying coefficients. Theoretical properties of the proposed model are established and an efficient expectation-maximization algorithm is derived to obtain the maximum likelihood estimates. Simulation studies evaluate the numerical performance of the proposed model under various temporal treatment effect curves. The ideas in this paper can also be used for time-varying coefficient frailty models without treatment switching as well as for alternative models when the proportional hazard assumption is violated. A multiple sclerosis dataset is analysed to illustrate our methodology. PMID:24465031

  20. Comparing and Combining Biomarkers as Principle Surrogates for Time-to-Event Clinical Endpoints

    PubMed Central

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

    2016-01-01

    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 of Huang and Gilbert [1] 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. PMID:25352131

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

    NASA Astrophysics Data System (ADS)

    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

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

    ERIC Educational Resources Information Center

    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.…

  3. Reading Times and the Detection of Event Shift Processing

    ERIC Educational Resources Information Center

    Radvansky, Gabriel A.; Copeland, David E.

    2010-01-01

    When people read narratives, they often need to update their situation models as the described events change. Previous research has shown little to no increases in reading times for spatial shifts but consistent increases for temporal shifts. On this basis, researchers have suggested that spatial updating does not regularly occur, whereas temporal…

  4. Off-Time Events and Life Quality of Older Adults.

    ERIC Educational Resources Information Center

    Goodhart, Darlene; Zautra, Alex

    Many previous studies have found that daily life events influence community residents' perceived quality of life, which refers to the relative goodness of life as evaluated subjectively. A subsample population of 539 older residents, aged 55 and over, were interviewed in their homes. A 60-item scale was devised to measure the effects of "off-time"…

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

    NASA Astrophysics Data System (ADS)

    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.

  6. Established time series measure occurrence and frequency of episodic events.

    NASA Astrophysics Data System (ADS)

    Pebody, Corinne; Lampitt, Richard

    2015-04-01

    Established time series measure occurrence and frequency of episodic events. Episodic flux events occur in open oceans. Time series making measurements over significant time scales are one of the few methods that can capture these events and compare their impact with 'normal' flux. Seemingly rare events may be significant on local scales, but without the ability to measure the extent of flux on spatial and temporal scales and combine with the frequency of occurrence, it is difficult to constrain their impact. The Porcupine Abyssal Plain Sustained Observatory (PAP-SO) in the Northeast Atlantic (49 °N 16 °W, 5000m water depth) has measured particle flux since 1989 and zooplankton swimmers since 2000. Sediment traps at 3000m and 100 metres above bottom, collect material year round and we have identified close links between zooplankton and particle flux. Some of these larger animals, for example Diacria trispinosa, make a significant contribution to carbon flux through episodic flux events. D. trispinosa is a euthecosome mollusc which occurs in the Northeast Atlantic, though the PAP-SO is towards the northern limit of its distribution. Pteropods are comprised of aragonite shell, containing soft body parts excepting the muscular foot which extends beyond the mouth of the living animal. Pteropods, both live-on-entry animals and the empty shells are found year round in the 3000m trap. Generally the abundance varies with particle flux, but within that general pattern there are episodic events where significant numbers of these animals containing both organic and inorganic carbon are captured at depth and therefore could be defined as contributing to export flux. Whether the pulse of animals is as a result of the life cycle of D. trispinosa or the effects of the physics of the water column is unclear, but the complexity of the PAP-SO enables us not only to collect these animals but to examine them in parallel to the biogeochemical and physical elements measured by the

  7. The Time of Our Lives: Life Span Development of Timing and Event Tracking

    ERIC Educational Resources Information Center

    McAuley, J. Devin; Jones, Mari Riess; Holub, Shayla; Johnston, Heather M.; Miller, Nathaniel S.

    2006-01-01

    Life span developmental profiles were constructed for 305 participants (ages 4-95) for a battery of paced and unpaced perceptual-motor timing tasks that included synchronize-continue tapping at a wide range of target event rates. Two life span hypotheses, derived from an entrainment theory of timing and event tracking, were tested. A preferred…

  8. Initial Time Dependence of Abundances in Solar Energetic Particle Events

    NASA Technical Reports Server (NTRS)

    Reames, Donald V.; Ny, C. K.; Tylka, A. J.

    1999-01-01

    We compare the initial behavior of Fe/O and He/H abundance ratios and their relationship to the evolution of the proton energy spectra in "small" and "large" gradual solar energetic particle (SEP) events. The results are qualitatively consistent with the behavior predicted by the theory of Ng et al. (1999a, b). He/H ratios that initially rise with time are a signature of scattering by non-Kolmogorov Alfven wave spectra generated by intense beams of shock-accelerated protons streaming outward in large gradual SEP events.

  9. The rotating spot method of timing subjective events.

    PubMed

    Pockett, Susan; Miller, Arden

    2007-06-01

    The rotating spot method of timing subjective events involves the subject's watching a rotating spot on a computer and reporting the position of the spot at the instant when the subjective event of interest occurs. We conducted an experiment to investigate factors that may impact on the results produced by this method, using the subject's perception of when they made a simple finger movement as the subjective event to be timed. Seven aspects of the rotating spot method were investigated, using a factorial experiment. Four of these aspects altered the physical characteristics of the computer generated spot or clock face and the remaining three altered the instructions given to the participant. We found compelling evidence that one factor, whether the subject was instructed to report the instant when the finger movement was initiated or the instant when it was completed, resulted in a systematic shift in the response. Evidence that three other factors affect the observed variability in the response was also found. In addition, we observed that there are substantial systematic differences in the responses made by different subjects. We discuss the implications of our findings and make recommendations about the optimal way of conducting future experiments using the rotating spot method. Our overall conclusion is that our results strongly validate the rotating spot method of timing at least the studied variety of subjective event. PMID:17049882

  10. Four Simultaneous Component Models for the Analysis of Multivariate Time Series from More Than One Subject To Model Intraindividual and Interindividual Differences.

    ERIC Educational Resources Information Center

    Timmerman, Marieke E.; Kiers, Henk A. L.

    2003-01-01

    Discusses a class of four simultaneous component models for the explanatory analysis of multivariate time series collected from more than one subject simultaneously. Shows how the models can be ordered hierarchically and illustrates their use through an empirical example. (SLD)

  11. Encoding of event timing in the phase of neural oscillations.

    PubMed

    Kösem, Anne; Gramfort, Alexandre; van Wassenhove, Virginie

    2014-05-15

    Time perception is a critical component of conscious experience. To be in synchrony with the environment, the brain must deal not only with differences in the speed of light and sound but also with its computational and neural transmission delays. Here, we asked whether the brain could actively compensate for temporal delays by changing its processing time. Specifically, can changes in neural timing or in the phase of neural oscillation index perceived timing? For this, a lag-adaptation paradigm was used to manipulate participants' perceived audiovisual (AV) simultaneity of events while they were recorded with magnetoencephalography (MEG). Desynchronized AV stimuli were presented rhythmically to elicit a robust 1 Hz frequency-tagging of auditory and visual cortical responses. As participants' perception of AV simultaneity shifted, systematic changes in the phase of entrained neural oscillations were observed. This suggests that neural entrainment is not a passive response and that the entrained neural oscillation shifts in time. Crucially, our results indicate that shifts in neural timing in auditory cortices linearly map participants' perceived AV simultaneity. To our knowledge, these results provide the first mechanistic evidence for active neural compensation in the encoding of sensory event timing in support of the emergence of time awareness. PMID:24531044

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

    NASA Astrophysics Data System (ADS)

    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.

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

    NASA Astrophysics Data System (ADS)

    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.

  14. Life Events and Depressive Symptoms in African American Adolescents: Do Ecological Domains and Timing of Life Events Matter?

    ERIC Educational Resources Information Center

    Sanchez, Yadira M.; Lambert, Sharon F.; Ialongo, Nicholas S.

    2012-01-01

    Considerable research has documented associations between adverse life events and internalizing symptoms in adolescents, but much of this research has focused on the number of events experienced, with less attention to the ecological context or timing of events. This study examined life events in three ecological domains relevant to adolescents…

  15. Time-quefrency analysis of overlapping similar microseismic events

    NASA Astrophysics Data System (ADS)

    Nagano, Koji

    2016-05-01

    In this paper, I describe a new technique to determine the interval between P-waves in similar, overlapping microseismic events. The similar microseismic events that occur with overlapping waveforms are called `proximate microseismic doublets' herein. Proximate microseismic doublets had been discarded in previous studies because we had not noticed their usefulness. Analysis of similar events can show relative locations of sources between them. Analysis of proximate microseismic doublets can provide more precise relative source locations because variation in the velocity structure has little influence on their relative travel times. It is necessary to measure the interval between the P-waves in the proximate microseismic doublets to determine their relative source locations. A `proximate microseismic doublet' is a pair of microseismic events in which the second event arrives before the attenuation of the first event. Cepstrum analysis can provide the interval even though the second event overlaps the first event. However, a cepstrum of a proximate microseismic doublet generally has two peaks, one representing the interval between the arrivals of the two P-waves, and the other representing the interval between the arrivals of the two S-waves. It is therefore difficult to determine the peak that represents the P-wave interval from the cepstrum alone. I used window functions in cepstrum analysis to isolate the first and second P-waves and to suppress the second S-wave. I change the length of the window function and calculate the cepstrum for each window length. The result is represented in a three-dimensional contour plot of length-quefrency-cepstrum data. The contour plot allows me to identify the cepstrum peak that represents the P-wave interval. The precise quefrency can be determined from a two-dimensional quefrency-cepstrum graph, provided that the length of the window is appropriately chosen. I have used both synthetic and field data to demonstrate that this

  16. An introduction to real-time graphical techniques for analyzing multivariate data

    NASA Astrophysics Data System (ADS)

    Friedman, Jerome H.; McDonald, John Alan; Stuetzle, Werner

    1987-08-01

    Orion I is a graphics system used to study applications of computer graphics - especially interactive motion graphics - in statistics. Orion I is the newest of a family of "Prim" systems, whose most striking common feature is the use of real-time motion graphics to display three dimensional scatterplots. Orion I differs from earlier Prim systems through the use of modern and relatively inexpensive raster graphics and microprocessor technology. It also delivers more computing power to its user; Orion I can perform more sophisticated real-time computations than were possible on previous such systems. We demonstrate some of Orion I's capabilities in our film: "Exploring data with Orion I".

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

    PubMed

    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. PMID:26088958

  18. Real-Time Multimission Event Notification System for Mars Relay

    NASA Technical Reports Server (NTRS)

    Wallick, Michael N.; Allard, Daniel A.; Gladden, Roy E.; Wang, Paul; Hy, Franklin H.

    2013-01-01

    As the Mars Relay Network is in constant flux (missions and teams going through their daily workflow), it is imperative that users are aware of such state changes. For example, a change by an orbiter team can affect operations on a lander team. This software provides an ambient view of the real-time status of the Mars network. The Mars Relay Operations Service (MaROS) comprises a number of tools to coordinate, plan, and visualize various aspects of the Mars Relay Network. As part of MaROS, a feature set was developed that operates on several levels of the software architecture. These levels include a Web-based user interface, a back-end "ReSTlet" built in Java, and databases that store the data as it is received from the network. The result is a real-time event notification and management system, so mission teams can track and act upon events on a moment-by-moment basis. This software retrieves events from MaROS and displays them to the end user. Updates happen in real time, i.e., messages are pushed to the user while logged into the system, and queued when the user is not online for later viewing. The software does not do away with the email notifications, but augments them with in-line notifications. Further, this software expands the events that can generate a notification, and allows user-generated notifications. Existing software sends a smaller subset of mission-generated notifications via email. A common complaint of users was that the system-generated e-mails often "get lost" with other e-mail that comes in. This software allows for an expanded set (including user-generated) of notifications displayed in-line of the program. By separating notifications, this can improve a user's workflow.

  19. Putting Predictive Models to Use: Scoring of Unseen Streaming Data using a Multivariate Time Series Classification Tool

    NASA Astrophysics Data System (ADS)

    Sipes, T.; Karimabadi, H.; Imber, S. M.; Slavin, J. A.; Pothier, N. M.; Coeli, R.

    2013-12-01

    Advances in data collection and data storage technologies have made the assembly of multivariate time series data more common. Data analysis and extraction of knowledge from such massive and complex datasets encountered in space physics today present a major obstacle to fully utilizing our vast data repositories and to scientific progress. In the previous years we introduced a time series classification tool MineTool-TS [Karimabadi et al, 2009] and its extension to simulation and streaming data [Sipes& Karimabadi, 2012, 2013]. In this work we demonstrate the applicability and real world utility of the predictive models created using the tool to scoring and labeling of a large dataset of unseen, streaming data. Predictive models that are created are based on the assumption that the training data used to create them is a true representative of the population. Multivariate time series datasets are also characterized by large amounts of variability and potential background noise. Moreover, there are multiple issues being raised by the streaming nature of the data. In this work we illustrate how we dealt with these challenges and demonstrate the results in a study of flux ropes in the plasma sheet. We have used an iterative process of building a predictive model using the original labeled training set, tested it on a week worth of streaming data, had the results checked by a scientific expert in the domain, and fed the results and the labels back into the training set, creating a large training set and using it to produce the final model. This final model was then put to use to predict a very large, unseen, six month period of streaming data. In this work we present the results of our machine learning approach to automatically detect flux ropes in spacecraft data.

  20. Classification of broiler breast filets according to deboning time using near infrared spectroscopy and multivariate analysis

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Chicken breast filets were deboned and NIR spectra were collected after 2, 4, and 24 hours. The deboning was performed on pairs of filets to minimize differences due only to the meat and not the deboning time (i.e. right at 2 hours, left at 24; right at 2, left at 4; right at 4, left at 24 hrs). The...

  1. MULTIVARIATE STATISTICAL MODELS FOR EFFECTS OF PM AND COPOLLUTANTS IN A DAILY TIME SERIES EPIDEMIOLOGY STUDY

    EPA Science Inventory

    Most analyses of daily time series epidemiology data relate mortality or morbidity counts to PM and other air pollutants by means of single-outcome regression models using multiple predictors, without taking into account the complex statistical structure of the predictor variable...

  2. Active movement restores veridical event-timing after tactile adaptation.

    PubMed

    Tomassini, Alice; Gori, Monica; Burr, David; Sandini, Giulio; Morrone, Maria Concetta

    2012-10-01

    Growing evidence suggests that time in the subsecond range is tightly linked to sensory processing. Event-time can be distorted by sensory adaptation, and many temporal illusions can accompany action execution. In this study, we show that adaptation to tactile motion causes a strong contraction of the apparent duration of tactile stimuli. However, when subjects make a voluntary motor act before judging the duration, it annuls the adaptation-induced temporal distortion, reestablishing veridical event-time. The movement needs to be performed actively by the subject: passive movement of similar magnitude and dynamics has no effect on adaptation, showing that it is the motor commands themselves, rather than reafferent signals from body movement, which reset the adaptation for tactile duration. No other concomitant perceptual changes were reported (such as apparent speed or enhanced temporal discrimination), ruling out a generalized effect of body movement on somatosensory processing. We suggest that active movement resets timing mechanisms in preparation for the new scenario that the movement will cause, eliminating inappropriate biases in perceived time. Our brain seems to utilize the intention-to-move signals to retune its perceptual machinery appropriately, to prepare to extract new temporal information. PMID:22832572

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

    PubMed Central

    Orini, Michele; 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. PMID:24386006

  4. A rank test for bivariate time-to-event outcomes when one event is a surrogate.

    PubMed

    Shaw, Pamela A; Fay, Michael P

    2016-08-30

    In many clinical settings, improving patient survival is of interest but a practical surrogate, such as time to disease progression, is instead used as a clinical trial's primary endpoint. A time-to-first endpoint (e.g., death or disease progression) is commonly analyzed but may not be adequate to summarize patient outcomes if a subsequent event contains important additional information. We consider a surrogate outcome very generally as one correlated with the true endpoint of interest. Settings of interest include those where the surrogate indicates a beneficial outcome so that the usual time-to-first endpoint of death or surrogate event is nonsensical. We present a new two-sample test for bivariate, interval-censored time-to-event data, where one endpoint is a surrogate for the second, less frequently observed endpoint of true interest. This test examines whether patient groups have equal clinical severity. If the true endpoint rarely occurs, the proposed test acts like a weighted logrank test on the surrogate; if it occurs for most individuals, then our test acts like a weighted logrank test on the true endpoint. If the surrogate is a useful statistical surrogate, our test can have better power than tests based on the surrogate that naively handles the true endpoint. In settings where the surrogate is not valid (treatment affects the surrogate but not the true endpoint), our test incorporates the information regarding the lack of treatment effect from the observed true endpoints and hence is expected to have a dampened treatment effect compared with tests based on the surrogate alone. Published 2016. This article is a U.S. Government work and is in the public domain in the USA. PMID:27059817

  5. Time course of salinity adaptation in a strongly euryhaline estuarine teleost, fundulus heteroclitus: A multivariable approach

    USGS Publications Warehouse

    Marshall, W.S.; Emberley, T.R.; Singer, T.D.; Bryson, S.E.; McCormick, S.D.

    1999-01-01

    Freshwater-adapted killifish (Fundulus heteroclitus) were transferred directly from soft fresh water to full-strength sea water for periods of 1h, 3h, 8h and 1, 2, 7, 14 and 30 days. Controls were transferred to fresh water for 24 h. Measured variables included: blood [Na+], osmolality, glucose and cortisol levels, basal and stimulated rates of ion transport and permeability of in vitro opercular epithelium, gill Na+/K+-ATPase and citrate synthase activity and chloride cell ultrastructure. These data were compared with previously published killifish cystic fibrosis transmembrane conductance regulator (kfCFTR) expression in the gills measured over a similar time course. Plasma cortisol levels peaked at 1 h, coincident with a rise in plasma [Na+]. At 8 h after transfer to sea water, a time at which previous work has shown kfCFTR expression to be elevated, blood osmolality and [Na+] were high, and cortisol levels and opercular membrane short-circuit current (I(SC); a measure of Cl- secretion rate) were low. The 24h group, which showed the highest level of kfCFTR expression, had the highest plasma [Na+] and osmolality, elevated plasma cortisol levels, significantly lower opercular membrane resistance, an increased opercular membrane ion secretion rate and collapsed tubule inclusions in mitochondria-rich cells, but no change in gill Na+/K+-ATPase and citrate synthase activity or plasma glucose levels. Apparently, killifish have a rapid (<1h) cortisol response to salinity coupled to subsequent (8-48 h) expression of kfCFTR anion channel proteins in existing mitochondria-rich cells that convert transport from ion uptake to ion secretion.

  6. Predicting analysis time in events-driven clinical trials using accumulating time-to-event surrogate information.

    PubMed

    Wang, Jianming; Ke, Chunlei; Yu, Zhinuan; Fu, Lei; Dornseif, Bruce

    2016-05-01

    For clinical trials with time-to-event endpoints, predicting the accrual of the events of interest with precision is critical in determining the timing of interim and final analyses. For example, overall survival (OS) is often chosen as the primary efficacy endpoint in oncology studies, with planned interim and final analyses at a pre-specified number of deaths. Often, correlated surrogate information, such as time-to-progression (TTP) and progression-free survival, are also collected as secondary efficacy endpoints. It would be appealing to borrow strength from the surrogate information to improve the precision of the analysis time prediction. Currently available methods in the literature for predicting analysis timings do not consider utilizing the surrogate information. In this article, using OS and TTP as an example, a general parametric model for OS and TTP is proposed, with the assumption that disease progression could change the course of the overall survival. Progression-free survival, related both to OS and TTP, will be handled separately, as it can be derived from OS and TTP. The authors seek to develop a prediction procedure using a Bayesian method and provide detailed implementation strategies under certain assumptions. Simulations are performed to evaluate the performance of the proposed method. An application to a real study is also provided. Copyright © 2015 John Wiley & Sons, Ltd. PMID:26689725

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

    NASA Astrophysics Data System (ADS)

    Gallego, Cristóbal; Cuerva, Álvaro; Costa, Alexandre

    2014-12-01

    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.

  8. Empirical reconstruction of storm-time steady magnetospheric convection events

    NASA Astrophysics Data System (ADS)

    Stephens, G. K.; Sitnov, M. I.; Kissinger, J.; Tsyganenko, N. A.; McPherron, R. L.; Korth, H.; Anderson, B. J.

    2013-12-01

    We investigate the storm-scale morphology of the magnetospheric magnetic field as well as underlying distributions of electric currents, equatorial plasma pressure and entropy for four Steady Magnetospheric Convection (SMC) events that occurred during the May 2000 and October 2011 magnetic storms. The analysis is made using the empirical geomagnetic field model TS07D, in which the structure of equatorial currents is not predefined and it is dictated by data. The model also combines the strengths of statistical and event-oriented approaches in mining data for the reconstruction of the magnetic field. The formation of a near-Earth minimum of the equatorial magnetic field in the midnight sector is inferred from data without ad hoc assumptions of a special current system postulated in earlier empirical reconstructions. In addition, a new SMC class is discovered where the minimum equatorial field is substantially larger and located closer to Earth. The magnetic field tailward of the minimum is also much larger, and the corresponding region of accumulated magnetic flux may occupy a very short tail region. The equatorial current and plasma pressure are found to be strongly enhanced far beyond geosynchronous orbit and in a broad local time interval covering the whole nightside region. This picture is consistent with independent recent statistical studies of the SMC pressure distributions, global MHD and kinetic RCM-E simulations. Distributions of the flux tube volume and entropy inferred from data reveal different mechanisms of the magnetotail convection crisis resolution for two classes of SMC events.

  9. Marking of Fluid Timed Events Graphs with Multipliers for a desired cycle time

    NASA Astrophysics Data System (ADS)

    Hamaci, S.; Labadi, K.

    2009-03-01

    We study fluid analogues of a subclass of petri nets, called Fluid Timed Event Graphs with Multipliers, which are a time extension of weighted T-Systems studied in the Petri Net literature. These event graphs can be studied in the algebraic structure called (min, +) algebra. In this paper we deal with the problem of allocating an initial marking in a Fluid Timed Event Graphs with Multipliers for a desired cycle time. for that, to calculate the marking of some places, we proceed by linearization of the mathematical model reflecting the behavior of a FGETM in order to obtain a model (min, +) linear. From the latter, we determine the marking which satisfiers the desired cycle time .

  10. What controls the local time extent of flux transfer events?

    NASA Astrophysics Data System (ADS)

    Milan, S. E.; Imber, S. M.; Carter, J. A.; Walach, M.-T.; Hubert, B.

    2016-02-01

    Flux transfer events (FTEs) are the manifestation of bursty and/or patchy magnetic reconnection at the magnetopause. We compare two sequences of the ionospheric signatures of flux transfer events observed in global auroral imagery and coherent ionospheric radar measurements. Both sequences were observed during very similar seasonal and interplanetary magnetic field (IMF) conditions, though with differing solar wind speed. A key observation is that the signatures differed considerably in their local time extent. The two periods are 26 August 1998, when the IMF had components BZ≈-10 nT and BY≈9 nT and the solar wind speed was VX≈650 km s-1, and 31 August 2005, IMF BZ≈-7 nT, BY≈17 nT, and VX≈380 km s-1. In the first case, the reconnection rate was estimated to be near 160 kV, and the FTE signatures extended across at least 7 h of magnetic local time (MLT) of the dayside polar cap boundary. In the second, a reconnection rate close to 80 kV was estimated, and the FTEs had a MLT extent of roughly 2 h. We discuss the ramifications of these differences for solar wind-magnetosphere coupling.

  11. Intelligent fuzzy controller for event-driven real time systems

    NASA Technical Reports Server (NTRS)

    Grantner, Janos; Patyra, Marek; Stachowicz, Marian S.

    1992-01-01

    Most of the known linguistic models are essentially static, that is, time is not a parameter in describing the behavior of the object's model. In this paper we show a model for synchronous finite state machines based on fuzzy logic. Such finite state machines can be used to build both event-driven, time-varying, rule-based systems and the control unit section of a fuzzy logic computer. The architecture of a pipelined intelligent fuzzy controller is presented, and the linguistic model is represented by an overall fuzzy relation stored in a single rule memory. A VLSI integrated circuit implementation of the fuzzy controller is suggested. At a clock rate of 30 MHz, the controller can perform 3 MFLIPS on multi-dimensional fuzzy data.

  12. An update on multivariate return periods in hydrology

    NASA Astrophysics Data System (ADS)

    Gräler, Benedikt; Petroselli, Andrea; Grimaldi, Salvatore; De Baets, Bernard; Verhoest, Niko

    2016-05-01

    Many hydrological studies are devoted to the identification of events that are expected to occur on average within a certain time span. While this topic is well established in the univariate case, recent advances focus on a multivariate characterization of events based on copulas. Following a previous study, we show how the definition of the survival Kendall return period fits into the set of multivariate return periods.Moreover, we preliminary investigate the ability of the multivariate return period definitions to select maximal events from a time series. Starting from a rich simulated data set, we show how similar the selection of events from a data set is. It can be deduced from the study and theoretically underpinned that the strength of correlation in the sample influences the differences between the selection of maximal events.

  13. Detection of intermittent events in atmospheric time series

    NASA Astrophysics Data System (ADS)

    Paradisi, P.; Cesari, R.; Palatella, L.; Contini, D.; Donateo, A.

    2009-04-01

    The modeling approach in atmospheric sciences is based on the assumption that local fluxes of mass, momentum, heat, etc... can be described as linear functions of the local gradient of some intensive property (concentration, flow strain, temperature,...). This is essentially associated with Gaussian statistics and short range (exponential) correlations. However, the atmosphere is a complex dynamical system displaying a wide range of spatial and temporal scales. A global description of the atmospheric dynamics should include a great number of degrees of freedom, strongly interacting on several temporal and spatial scales, thus generating long range (power-law) correlations and non-Gaussian distribution of fluctuations (Lévy flights, Lévy walks, Continuous Time Random Walks) [1]. This is typically associated with anomalous diffusion and scaling, non-trivial memory features and correlation decays and, especially, with the emergence of flux-gradient relationships that are non-linear and/or non-local in time and/or space. Actually, the local flux-gradient relationship is greatly preferred due to a more clear physical meaning, allowing to perform direct comparisons with experimental data, and, especially, to smaller computational costs in numerical models. In particular, the linearity of this relationship allows to define a transport coefficient (e.g., turbulent diffusivity) and the modeling effort is usually focused on this coefficient. However, the validity of the local (and linear) flux-gradient model is strongly dependent on the range of spatial and temporal scales represented by the model and, consequently, by the sub-grid processes included in the flux-gradient relationship. In this work, in order to check the validity of local and linear flux-gradient relationships, an approach based on the concept of renewal critical events [2] is introduced. In fact, in renewal theory [2], the dynamical origin of anomalous behaviour and non-local flux-gradient relation is

  14. UNCERTAINTY IN PHASE ARRIVAL TIME PICKS FOR REGIONAL SEISMIC EVENTS: AN EXPERIMENTAL DESIGN

    SciTech Connect

    A. VELASCO; ET AL

    2001-02-01

    The detection and timing of seismic arrivals play a critical role in the ability to locate seismic events, especially at low magnitude. Errors can occur with the determination of the timing of the arrivals, whether these errors are made by automated processing or by an analyst. One of the major obstacles encountered in properly estimating travel-time picking error is the lack of a clear and comprehensive discussion of all of the factors that influence phase picks. This report discusses possible factors that need to be modeled to properly study phase arrival time picking errors. We have developed a multivariate statistical model, experimental design, and analysis strategy that can be used in this study. We have embedded a general form of the International Data Center(IDC)/U.S. National Data Center (USNDC) phase pick measurement error model into our statistical model. We can use this statistical model to optimally calibrate a picking error model to regional data. A follow-on report will present the results of this analysis plan applied to an implementation of an experiment/data-gathering task.

  15. Event coincidence analysis for quantifying statistical interrelationships between event time series. On the role of flood events as triggers of epidemic outbreaks

    NASA Astrophysics Data System (ADS)

    Donges, J. F.; Schleussner, C.-F.; Siegmund, J. F.; Donner, R. V.

    2016-05-01

    Studying event time series is a powerful approach for analyzing the dynamics of complex dynamical systems in many fields of science. In this paper, we describe the method of event coincidence analysis to provide a framework for quantifying the strength, directionality and time lag of statistical interrelationships between event series. Event coincidence analysis allows to formulate and test null hypotheses on the origin of the observed interrelationships including tests based on Poisson processes or, more generally, stochastic point processes with a prescribed inter-event time distribution and other higher-order properties. Applying the framework to country-level observational data yields evidence that flood events have acted as triggers of epidemic outbreaks globally since the 1950s. Facing projected future changes in the statistics of climatic extreme events, statistical techniques such as event coincidence analysis will be relevant for investigating the impacts of anthropogenic climate change on human societies and ecosystems worldwide.

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

    NASA Astrophysics Data System (ADS)

    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.

  17. Relative timing of deglacial climate events in Antarctica and Greenland.

    PubMed

    Morgan, Vin; Delmotte, Marc; van Ommen, Tas; Jouzel, Jean; Chappellaz, Jérôme; Woon, Suenor; Masson-Delmotte, Valérie; Raynaud, Dominique

    2002-09-13

    The last deglaciation was marked by large, hemispheric, millennial-scale climate variations: the Bølling-Allerød and Younger Dryas periods in the north, and the Antarctic Cold Reversal in the south. A chronology from the high-accumulation Law Dome East Antarctic ice core constrains the relative timing of these two events and provides strong evidence that the cooling at the start of the Antarctic Cold Reversal did not follow the abrupt warming during the northern Bølling transition around 14,500 years ago. This result suggests that southern changes are not a direct response to abrupt changes in North Atlantic thermohaline circulation, as is assumed in the conventional picture of a hemispheric temperature seesaw. PMID:12228715

  18. Detecting Rare Events in the Time-Domain

    SciTech Connect

    Rest, A; Garg, A

    2008-10-31

    One of the biggest challenges in current and future time-domain surveys is to extract the objects of interest from the immense data stream. There are two aspects to achieving this goal: detecting variable sources and classifying them. Difference imaging provides an elegant technique for identifying new transients or changes in source brightness. Much progress has been made in recent years toward refining the process. We discuss a selection of pitfalls that can afflict an automated difference imagine pipeline and describe some solutions. After identifying true astrophysical variables, we are faced with the challenge of classifying them. For rare events, such as supernovae and microlensing, this challenge is magnified because we must balance having selection criteria that select for the largest number of objects of interest against a high contamination rate. We discuss considerations and techniques for developing classification schemes.

  19. Simplifying Facility and Event Scheduling: Saving Time and Money.

    ERIC Educational Resources Information Center

    Raasch, Kevin

    2003-01-01

    Describes a product called the Event Management System (EMS), a computer software program to manage facility and event scheduling. Provides example of the school district and university uses of EMS. Describes steps in selecting a scheduling-management system. (PKP)

  20. Time in Language: Event Duration in Language Comprehension

    ERIC Educational Resources Information Center

    Coll-Florit, Marta; Gennari, Silvia P.

    2011-01-01

    This work investigates how we process and represent event duration in on-line language comprehension. Specifically, it examines how events of different duration are processed and what type of knowledge underlies their representations. Studies 1-4 examined verbs and phrases in different contexts. They showed that durative events took longer to…

  1. Dynamic ultrasound imaging—A multivariate approach for the analysis and comparison of time-dependent musculoskeletal movements

    PubMed Central

    2012-01-01

    Background Muscle functions are generally assumed to affect a wide variety of conditions and activities, including pain, ischemic and neurological disorders, exercise and injury. It is therefore very desirable to obtain more information on musculoskeletal contributions to and activity during clinical processes such as the treatment of muscle injuries, post-surgery evaluations, and the monitoring of progressive degeneration in neuromuscular disorders. The spatial image resolution achievable with ultrasound systems has improved tremendously in the last few years and it is nowadays possible to study skeletal muscles in real-time during activity. However, ultrasound imaging has an inherent problem that makes it difficult to compare different measurement series or image sequences from two or more subjects. Due to physiological differences between different subjects, the ultrasound sequences will be visually different – partly because of variation in probe placement and partly because of the difficulty of perfectly reproducing any given movement. Methods Ultrasound images of the biceps and calf of a single subject were transformed to achieve congruence and then efficiently compressed and stacked to facilitate analysis using a multivariate method known as O2PLS. O2PLS identifies related and unrelated variation in and between two sets of data such that different phases of the studied movements can be analysed. The methodology was used to study the dynamics of the Achilles tendon and the calf and also the Biceps brachii and upper arm. The movements of these parts of the body are both of interest in clinical orthopaedic research. Results This study extends the novel method of multivariate analysis of congruent images (MACI) to facilitate comparisons between two series of ultrasound images. This increases its potential range of medical applications and its utility for detecting, visualising and quantifying the dynamics and functions of skeletal muscle. Conclusions The most

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

    PubMed

    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

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

    PubMed Central

    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

  4. Validation of cross-sectional time series and multivariate adaptive regression splines models for the prediction of energy expenditure in children and adolescents using doubly labeled water

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Accurate, nonintrusive, and inexpensive techniques are needed to measure energy expenditure (EE) in free-living populations. Our primary aim in this study was to validate cross-sectional time series (CSTS) and multivariate adaptive regression splines (MARS) models based on observable participant cha...

  5. Real-time interpretation of novel events across childhood

    PubMed Central

    Borovsky, Arielle; Sweeney, Kim; Elman, Jeffrey L.; Fernald, Anne

    2014-01-01

    Despite extensive evidence that adults and children rapidly integrate world knowledge to generate expectancies for upcoming language, little work has explored how this knowledge is initially acquired and used. We explore this question in 3- to 10-year-old children and adults by measuring the degree to which sentences depicting recently learned connections between agents, actions and objects lead to anticipatory eye-movements to the objects. Combinatory information in sentences about agent and action elicited anticipatory eye-movements to the Target object in adults and older children. Our findings suggest that adults and school-aged children can quickly activate information about recently exposed novel event relationships in real-time language processing. However, there were important developmental differences in the use of this knowledge. Adults and school-aged children used the sentential agent and action to predict the sentence final theme, while preschool children’s fixations reflected a simple association to the currently spoken item. We consider several reasons for this developmental difference and possible extensions of this paradigm. PMID:24976677

  6. Dead-time correction for time-of-flight secondary-ion mass spectral images: a critical issue in multivariate image analysis.

    PubMed

    Tyler, Bonnie J; Peterson, Richard E

    2013-01-01

    Dead-time effects result in a non-linear detector response in the common time-of-flight secondary-ion mass spectrometry instruments. This can result in image artifacts that can often be misinterpreted. Although the Poisson correction procedure has been shown to effectively eliminate this non-linearity in spectra, applying the correction to images presents difficulties because the low number of counts per pixel can create large statistical errors. The efficacy of three approaches to dead-time correction in images has been explored. These approaches include: pixel binning, image segmentation and a binomial statistical correction. When few pixels are fully saturated, all three approaches work satisfactorily. When a large number of pixels are fully saturated, the statistical approach fails to remove the dead-time artifacts revealed by multivariate analysis. Pixel binning is accurate at higher levels of saturation so long as the bin size is much smaller than the feature size. The segmentation approach works well independent of feature size or the number of fully saturated pixels but requires an accurate segmentation algorithm. It is recommended that images be collected under conditions that minimize the number of fully saturated pixels. When this is impractical and small features are present in the image, segmentation can provide an accurate way to correct for the detector saturation effect. PMID:24707067

  7. Time-Lapse Photography in Recording Classroom Events.

    ERIC Educational Resources Information Center

    Walker, Rob; Adelman, Clem

    An observational recording system was devised to record and to replay the stream of classroom events--nonverbal events, as well as verbal. Although videotape recording/closed circuit television has been used in similar systems, the one here used selected 35mm. stills made from 16mm. film. The stills were then synchronized with tape recordings and…

  8. Young Children's Memory for the Times of Personal Past Events

    ERIC Educational Resources Information Center

    Pathman, Thanujeni; Larkina, Marina; Burch, Melissa M.; Bauer, Patricia J.

    2013-01-01

    Remembering the temporal information associated with personal past events is critical for autobiographical memory, yet we know relatively little about the development of this capacity. In the present research, we investigated temporal memory for naturally occurring personal events in 4-, 6-, and 8-year-old children. Parents recorded unique events…

  9. Modality transition-based network from multivariate time series for characterizing horizontal oil-water flow patterns

    NASA Astrophysics Data System (ADS)

    Ding, Mei-Shuang; Jin, Ning-De; Gao, Zhong-Ke

    2015-11-01

    The simultaneous flow of oil and water through a horizontal pipe is a common occurrence during petroleum industrial processes. Characterizing the flow behavior underlying horizontal oil-water flows is a challenging problem of significant importance. In order to solve this problem, we carry out experiment to measure multivariate signals from different flow patterns and then propose a novel modality transition-based network to analyze the multivariate signals. The results suggest that the local betweenness centrality and weighted shortest path of the constructed network can characterize the transitions of flow conditions and further allow quantitatively distinguishing and uncovering the dynamic flow behavior underlying different horizontal oil-water flow patterns.

  10. A new pseudodeterministic multivariate receptor model for individual source apportionment using highly time-resolved ambient concentration measurements

    NASA Astrophysics Data System (ADS)

    Park, Seung Shik; Pancras, J. Patrick; Ondov, John; Poor, Noreen

    2005-04-01

    A new multivariate pseudodeterministic receptor model (PDRM), combining mass balance and Gaussian plume dispersion equations, was developed to exploit highly time-resolved ambient measurements of SO2 and particulate pollutants influencing air quality at a site in Sydney, Florida, during the Tampa Bay Regional Aerosol Chemistry Experiment (BRACE) in May 2002. The PDRM explicitly exploits knowledge of the number and locations of major stationary sources, source and transport wind directions, stack gas emission parameters, and meteorological plume dispersion parameters during sample collections to constrain solutions for individual sources. Model outputs include average emission rates and time-resolved ambient concentrations for each of the measured species and time-resolved meteorological dispersion factors for each of the sources. The model was applied to ambient Federal Reference Method SO2 and 30-min elemental measurements during an 8.5-hour period when winds swept a 70° sector containing six large stationary sources. Agreement between predicted and observed ambient SO2 concentrations was extraordinarily good: The correlation coefficient (R2) was 0.97, their ratio was 1.00 ± 0.18, and predicted SO2 emission rates for each of four large utility sources lie within 8% of their average continuous emission monitor values. Mean fractional bias, normalized mean square error, and the fractions of the predictions within a factor of 2 of the observed values are -2.7, 0.9, and 94%, respectively. For elemental markers of coal-fired (As and Se) and oil-fired (Ni) power plant emissions the average ratio of predicted and observed concentrations was 1.02 ± 0.18 for As, 0.96 ± 0.17 for Se, and 0.99 ± 0.41 for Ni, indicating that the six sources located in the wind sector between approximately 200° and 260° well accounted for background-corrected concentrations measured at the sampling site. Model results were relatively insensitive to the choice of upper bound used to

  11. Quantifying causal coupling strength: A lag-specific measure for multivariate time series related to transfer entropy

    NASA Astrophysics Data System (ADS)

    Runge, Jakob; Heitzig, Jobst; Marwan, Norbert; Kurths, Jürgen

    2012-12-01

    While it is an important problem to identify the existence of causal associations between two components of a multivariate time series, a topic addressed in Runge, Heitzig, Petoukhov, and Kurths [Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.108.258701 108, 258701 (2012)], it is even more important to assess the strength of their association in a meaningful way. In the present article we focus on the problem of defining a meaningful coupling strength using information-theoretic measures and demonstrate the shortcomings of the well-known mutual information and transfer entropy. Instead, we propose a certain time-delayed conditional mutual information, the momentary information transfer (MIT), as a lag-specific measure of association that is general, causal, reflects a well interpretable notion of coupling strength, and is practically computable. Rooted in information theory, MIT is general in that it does not assume a certain model class underlying the process that generates the time series. As discussed in a previous paper [Runge, Heitzig, Petoukhov, and Kurths, Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.108.258701 108, 258701 (2012)], the general framework of graphical models makes MIT causal in that it gives a nonzero value only to lagged components that are not independent conditional on the remaining process. Further, graphical models admit a low-dimensional formulation of conditions, which is important for a reliable estimation of conditional mutual information and, thus, makes MIT practically computable. MIT is based on the fundamental concept of source entropy, which we utilize to yield a notion of coupling strength that is, compared to mutual information and transfer entropy, well interpretable in that, for many cases, it solely depends on the interaction of the two components at a certain lag. In particular, MIT is, thus, in many cases able to exclude the misleading influence of autodependency within a process in an information-theoretic way

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

    PubMed

    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

  13. Large Time Projection Chambers for Rare Event Detection

    SciTech Connect

    Heffner, M

    2009-11-03

    The Time Projection Chamber (TPC) concept [add ref to TPC section] has been applied to many projects outside of particle physics and the accelerator based experiments where it was initially developed. TPCs in non-accelerator particle physics experiments are principally focused on rare event detection (e.g. neutrino and darkmater experiments) and the physics of these experiments can place dramatically different constraints on the TPC design (only extensions to the traditional TPCs are discussed here). The drift gas, or liquid, is usually the target or matter under observation and due to very low signal rates a TPC with the largest active mass is desired. The large mass complicates particle tracking of short and sometimes very low energy particles. Other special design issues include, efficient light collection, background rejection, internal triggering and optimal energy resolution. Backgrounds from gamma-rays and neutrons are significant design issues in the construction of these TPCs. They are generally placed deep underground to shield from cosmogenic particles and surrounded with shielding to reduce radiation from the local surroundings. The construction materials have to be carefully screened for radiopurity as they are in close contact with the active mass and can be a signification source of background events. The TPC excels in reducing this internal background because the mass inside the fieldcage forms one monolithic volume from which fiducial cuts can be made ex post facto to isolate quiet drift mass, and can be circulated and purified to a very high level. Self shielding in these large mass systems can be significant and the effect improves with density. The liquid phase TPC can obtain a high density at low pressure which results in very good self-shielding and compact installation with a lightweight containment. The down sides are the need for cryogenics, slower charge drift, tracks shorter than the typical electron diffusion, lower energy resolution (e

  14. Estimation of Maximum Likelihood of the Unextendable Dead Time Period in a Flow of Physical Events

    NASA Astrophysics Data System (ADS)

    Gortsev, A. M.; Solov'ev, A. A.

    2016-03-01

    A flow of physical events (photons, electrons, etc.) is studied. One of the mathematical models of such flows is the MAP-flow of events. The flow circulates under conditions of the unextendable dead time period, when the dead time period is unknown. The dead time period is estimated by the method of maximum likelihood from observations of arrival instants of events.

  15. Real-time detection of traffic events using smart cameras

    NASA Astrophysics Data System (ADS)

    Macesic, M.; Jelaca, V.; Niño-Castaneda, J. O.; Prodanovic, N.; Panic, M.; Pizurica, A.; Crnojevic, V.; Philips, W.

    2012-01-01

    With rapid increase of number of vehicles on roads it is necessary to maintain close monitoring of traffic. For this purpose many surveillance cameras are placed along roads and on crossroads, creating a huge communication load between the cameras and the monitoring center. Therefore, the data needs to be processed on site and transferred to the monitoring centers in form of metadata or as a set of selected images. For this purpose it is necessary to detect events of interest already on the camera side, which implies using smart cameras as visual sensors. In this paper we propose a method for tracking of vehicles and analysis of vehicle trajectories to detect different traffic events. Kalman filtering is used for tracking, combining foreground and optical flow measurements. Obtained vehicle trajectories are used to detect different traffic events. Every new trajectory is compared with collection of normal routes and clustered accordingly. If the observed trajectory differs from all normal routes more than a predefined threshold, it is marked as abnormal and the alarm is raised. The system was developed and tested on Texas Instruments OMAP platform. Testing was done on four different locations, two locations in the city and two locations on the open road.

  16. Time Scales of Solar Energetic Particle Events and Speeds of Source CMEs

    NASA Astrophysics Data System (ADS)

    Kahler, S.

    2004-05-01

    Solar Energetic Particle (SEP) events are characterized primarily by their peak intensities or fluences. Event temporal characteristics and their associations with solar phenomena are less frequently considered. We measure the times to SEP event onsets, rise times and event durations of E = 20 MeV solar proton events observed with the NASA/GSFC Epact instrument on the Wind spacecraft. The approximately 140 SEP events, observed from 1998 through 2002, were accompanied by associated coronal mass ejections (CMEs) observed with the Lasco coronagraph on the SOHO spacecraft. The timing characteristics of the SEP events are compared with the speeds and widths of the associated CMEs to determine whether any of the characteristics of the SEP intensity-time profiles can be related to CME properties. The longitude dependence of the temporal profiles is considered separately to determine the geometric extents of the shocks producing the SEP events at 1 AU.

  17. A Simple Computer Interface To Time Relatively Slow Physical Events.

    ERIC Educational Resources Information Center

    Ocaya, R. O.

    2000-01-01

    Describes a simple computer interface that can be used to make reliable time measurements, such as when timing the swings of a pendulum. Presents a sample experiment involving a form of pendulum known as the compound pendulum. (Author/YDS)

  18. Applications to Real World Time Series Event detection, multimodality and non-stationarity: Ordinal patterns, a tool to rule them all?

    NASA Astrophysics Data System (ADS)

    Arroyo, D.; Chamorro, P.; Amigó, J. M.; Rodríguez, F. B.; Varona, P.

    2013-06-01

    In this work, we apply ordinal analysis of time series to the characterisation of neuronal activity. Automatic event detection is performed by means of the so-called permutation entropy, along with the quantification of the relative cardinality of forbidden patterns. In addition, multivariate time series are characterised using the joint permutation entropy. In order to illustrate the suitability of the ordinal analysis for characterising neurophysiological data, we have compared the measures based on ordinal patterns of time series to the tools typically used in the context of neurophysiology.

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

    ERIC Educational Resources Information Center

    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…

  20. Multivariate normality

    NASA Technical Reports Server (NTRS)

    Crutcher, H. L.; Falls, L. W.

    1976-01-01

    Sets of experimentally determined or routinely observed data provide information about the past, present and, hopefully, future sets of similarly produced data. An infinite set of statistical models exists which may be used to describe the data sets. The normal distribution is one model. If it serves at all, it serves well. If a data set, or a transformation of the set, representative of a larger population can be described by the normal distribution, then valid statistical inferences can be drawn. There are several tests which may be applied to a data set to determine whether the univariate normal model adequately describes the set. The chi-square test based on Pearson's work in the late nineteenth and early twentieth centuries is often used. Like all tests, it has some weaknesses which are discussed in elementary texts. Extension of the chi-square test to the multivariate normal model is provided. Tables and graphs permit easier application of the test in the higher dimensions. Several examples, using recorded data, illustrate the procedures. Tests of maximum absolute differences, mean sum of squares of residuals, runs and changes of sign are included in these tests. Dimensions one through five with selected sample sizes 11 to 101 are used to illustrate the statistical tests developed.

  1. Reporting of Life Events Over Time: Methodological Issues in a Longitudinal Sample of Women

    ERIC Educational Resources Information Center

    Pachana, Nancy A.; Brilleman, Sam L.; Dobson, Annette J.

    2011-01-01

    The number of life events reported by study participants is sensitive to the method of data collection and time intervals under consideration. Individual characteristics also influence reporting; respondents with poor mental health report more life events. Much current research on life events is cross-sectional. Data from a longitudinal study of…

  2. Travel time classification of extreme solar events: Two families and an outlier

    NASA Astrophysics Data System (ADS)

    Freed, A. J.; Russell, C. T.

    2014-10-01

    Extreme solar events are of great interest because of the extensive damage that could be experienced by technological systems such as electrical transformers during such periods. In studying geophysical phenomena, it is helpful to have a quantitative measure of event strength so that similar events can be intercompared. Such a measure also allows the calculation of the occurrence rates of events with varying strength. We use historical fast travel time solar events to develop a measure of strength based on the Sun-Earth trip time. We find that these fast events can be grouped into two distinct families with one even faster outlier. That outlier is not the Carrington event of 1859 but the extremely intense solar particle event of August 1972.

  3. Parent–offspring similarity in the timing of developmental events: an origin of heterochrony?

    PubMed Central

    Tills, Oliver; Rundle, Simon D.; Spicer, John I.

    2013-01-01

    Understanding the link between ontogeny (development) and phylogeny (evolution) remains a key aim of biology. Heterochrony, the altered timing of developmental events between ancestors and descendants, could be such a link although the processes responsible for producing heterochrony, widely viewed as an interspecific phenomenon, are still unclear. However, intraspecific variation in developmental event timing, if heritable, could provide the raw material from which heterochronies originate. To date, however, heritable developmental event timing has not been demonstrated, although recent work did suggest a genetic basis for intraspecific differences in event timing in the embryonic development of the pond snail, Radix balthica. Consequently, here we used high-resolution (temporal and spatial) imaging of the entire embryonic development of R. balthica to perform a parent–offspring comparison of the timing of twelve, physiological and morphological developmental events. Between-parent differences in the timing of all events were good predictors of such timing differences between their offspring, and heritability was demonstrated for two of these events (foot attachment and crawling). Such heritable intraspecific variation in developmental event timing could be the raw material for speciation events, providing a fundamental link between ontogeny and phylogeny, via heterochrony. PMID:23966639

  4. Intermittent control of unstable multivariate systems.

    PubMed

    Loram, I; Gawthrop, P; Gollee, H

    2015-08-01

    A sensorimotor architecture inspired from biological, vertebrate control should (i) explain the interface between high dimensional sensory analysis, low dimensional goals and high dimensional motor mechanisms and (ii) provide both stability and flexibility. Our interest concerns whether single-input-single-output intermittent control (SISO_IC) generalized to multivariable intermittent control (MIC) can meet these requirements.We base MIC on the continuous-time observer-predictorstate-feedback architecture. MIC uses event detection. A system matched hold (SMH), using the underlying continuoustime optimal control design, generates multivariate open-loop control signals between samples of the predicted state. Combined, this serial process provides a single-channel of control with optimised sensor fusion and motor synergies. Quadratic programming provides constrained, optimised equilibrium control design to handle unphysical configurations, redundancy and provides minimum, necessary reduction of open loop instability through optimised joint impedance. In this multivariate form, dimensionality is linked to goals rather than neuromuscular or sensory degrees of freedom. The biological and engineering rationale for intermittent rather than continuous multivariate control, is that the generalised hold sustains open loop predictive control while the open loop interval provides time within the feedback loop for online centralised, state dependent optimisation and selection. PMID:26736539

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

    ERIC Educational Resources Information Center

    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)

  6. Pipeline Implementation of Real Time Event Cross Correlation for Nuclear Treaty Monitoring

    NASA Astrophysics Data System (ADS)

    Junek, W. N.; Wehlen, J. A., III

    2014-12-01

    The United States National Data Center (US NDC) is responsible for monitoring international compliance to nuclear test ban treaties. This mission is performed through real time acquisition, processing, and evaluation of data acquired by a global network of seismic, hydroacoustic, and infrasonic sensors. Automatic and human reviewed event solutions are stored in a data warehouse which contains over 15 years of alphanumeric information and waveform data. A significant effort is underway to employ the data warehouse in real time processing to improve the quality of automatic event solutions, reduce analyst burden, and supply decision makers with information regarding relevant historic events. To this end, the US NDC processing pipeline has been modified to automatically recognize events built in the past. Event similarity information and the most relevant historic solution are passed to the human analyst to assist their evaluation of automatically formed events. This is achieved through real time cross correlation of selected seismograms from automatically formed events against those stored in the data warehouse. Historic events used in correlation analysis are selected based on a set of user defined parameters, which are tuned to maintain pipeline timeliness requirements. Software architecture and database infrastructure were modified using a multithreaded design for increased processing speed, database connection pools for parallel queries, and Oracle spatial indexing to enhance query efficiency. This functionality allows the human analyst to spend more time studying anomalous events and less time rebuilding routine events.

  7. Real-Time GPS Network Monitors Bayou Corne Sinkhole Event

    NASA Astrophysics Data System (ADS)

    Kent, Joshua D.; Dunaway, Larry

    2013-10-01

    In August 2012 a sinkhole developed in the swampy marshland near the rural community of Bayou Corne in Assumption Parish (i.e., county), Louisiana. The area was evacuated, and some residents have still not been able to return. The sinkhole—which now measures about 450 meters wide and is continuing to grow—is being monitored by multiple systems, including four rapid-response GPS continuously operating reference stations (CORS) called CORS911. The real-time data provided by this system are used by scientists and decision makers to help ensure public safety.

  8. Developmental and Cognitive Perspectives on Humans' Sense of the Times of Past and Future Events

    ERIC Educational Resources Information Center

    Friedman, W.J.

    2005-01-01

    Mental time travel in human adults includes a sense of when past events occurred and future events are expected to occur. Studies with adults and children reveal that a number of distinct psychological processes contribute to a temporally differentiated sense of the past and future. Adults possess representations of multiple time patterns, and…

  9. The Roles of Prior Experience and the Timing of Misinformation Presentation on Young Children's Event Memories

    ERIC Educational Resources Information Center

    Roberts, Kim P.; Powell, Martine B.

    2007-01-01

    The current study addressed how the timing of interviews affected children's memories of unique and repeated events. Five- to six-year-olds (N = 125) participated in activities 1 or 4 times and were misinformed either 3 or 21 days after the only or last event. Although single-experience children were subsequently less accurate in the 21- versus…

  10. Qualitative and event-specific real-time PCR detection methods for Bt brinjal event EE-1.

    PubMed

    Randhawa, Gurinder Jit; Sharma, Ruchi; Singh, Monika

    2012-01-01

    Bt brinjal event EE-1 with cry1Ac gene, expressing insecticidal protein against fruit and shoot borer, is the first genetically modified food crop in the pipeline for commercialization in India. Qualitative polymerase chain reaction (PCR) along with event-specific conventional as well as real-time PCR methods to characterize the event EE-1 is reported. A multiplex (pentaplex) PCR system simultaneously amplifying cry1Ac transgene, Cauliflower Mosaic Virus (CaMV) 35S promoter, nopaline synthase (nos) terminator, aminoglycoside adenyltransferase (aadA) marker gene, and a taxon-specific beta-fructosidase gene in event EE-1 has been developed. Furthermore, construct-specific PCR, targeting the approximate 1.8 kb region of inserted gene construct comprising the region of CaMV 35S promoter and cry1Ac gene has also been developed. The LOD of developed EE-1 specific conventional PCR assay is 0.01%. The method performance of the reported real-time PCR assay was consistent with the acceptance criteria of Codex Alimentarius Commission ALINORM 10/33/23, with the LOD and LOQ values of 0.05%. The developed detection methods would not only facilitate effective regulatory compliance for identification of genetic traits, risk assessment, management, and postrelease monitoring, but also address consumer concerns and resolution of legal disputes. PMID:23451391

  11. Time sequence of events leading to chromosomal aberration formation

    SciTech Connect

    Moore, R.C. ); Bender, M.A. )

    1993-01-01

    Investigations have been carried out which have measured the influence of the repair polymerases on the yield of different types of chromosomal aberrations. The studies were mainly concerned with the effect of inhibiting the polymerases on the yield of aberrations. The polymerases fill in single strand regions, and the fact that their inhibition affects the yield of aberrations suggests that single strand lesions are influential in aberration formation. The results indicate that: (1) There are two actions of polymerases in clastogenesis. One is in their involvement in a G2 repair system, in which the pair of chromatids is concerned, and which does not yield aberrations unless the inhibition is still operating when the cells enter mitosis. The second also operates in G1 and S, and is such that when repair is inhibited, further damage accrues. (2) The second action is affected by inhibiting polymerase but operates even when the repair enzymes are active. (3) The production of chromosomal exchanges involves a series of reactions, some of which are reversible. (4) The time span over which the reactions occur is much longer than has been envisaged previously (e.g., most of a cell cycle). 29 refs., 1 fig.

  12. Time sequence of events leading to chromosomal aberration formation

    SciTech Connect

    Moore, R.C. ); Bender, M.A. )

    1993-01-01

    Investigations have been carried out on the influence of the repair polymerases on the yield of different types of chromosomal aberrations. The studies were mainly concerned with the effect of inhibiting the polymerases on the yield of aberrations. The polymerases fill in single-strand regions, and the fact that their inhibition affects the yield of aberrations suggests that single-strand lesions are influential in aberration formation. The results indicate that there are two actions of polymerases in clastogenesis. One is in their involvement in a G[sub 2] repair system, in which either of the two chromatids is concerned, and which does not yield aberrations unless the inhibition is still operating when the cells enter mitosis. The second is such that when repair is inhibited, further damage accrues. The second action is affected by inhibiting polymerase repair, but also operates even when the repair enzymes are active. The production of chromosomal exchanges involves a series of reactions, some of which are reversible. The time span over which the reactions occur is much longer than has been envisaged previously.

  13. Time sequence of events leading to chromosomal aberration formation

    SciTech Connect

    Moore, R.C.; Bender, M.A.

    1993-05-01

    Investigations have been carried out on the influence of the repair polymerases on the yield of different types of chromosomal aberrations. The studies were mainly concerned with the effect of inhibiting the polymerases on the yield of aberrations. The polymerases fill in single-strand regions, and the fact that their inhibition affects the yield of aberrations suggests that single-strand lesions are influential in aberration formation. The results indicate that there are two actions of polymerases in clastogenesis. One is in their involvement in a G{sub 2} repair system, in which either of the two chromatids is concerned, and which does not yield aberrations unless the inhibition is still operating when the cells enter mitosis. The second is such that when repair is inhibited, further damage accrues. The second action is affected by inhibiting polymerase repair, but also operates even when the repair enzymes are active. The production of chromosomal exchanges involves a series of reactions, some of which are reversible. The time span over which the reactions occur is much longer than has been envisaged previously.

  14. Cognitive tasks in information analysis: Use of event dwell time to characterize component activities

    SciTech Connect

    Sanquist, Thomas F.; Greitzer, Frank L.; Slavich, Antoinette L.; Littlefield, Rik J.; Littlefield, Janis S.; Cowley, Paula J.

    2004-09-28

    Technology-based enhancement of information analysis requires a detailed understanding of the cognitive tasks involved in the process. The information search and report production tasks of the information analysis process were investigated through evaluation of time-stamped workstation data gathered with custom software. Model tasks simulated the search and production activities, and a sample of actual analyst data were also evaluated. Task event durations were calculated on the basis of millisecond-level time stamps, and distributions were plotted for analysis. The data indicate that task event time shows a cyclic pattern of variation, with shorter event durations (< 2 sec) reflecting information search and filtering, and longer event durations (> 10 sec) reflecting information evaluation. Application of cognitive principles to the interpretation of task event time data provides a basis for developing “cognitive signatures” of complex activities, and can facilitate the development of technology aids for information intensive tasks.

  15. Time, space, and events in language and cognition: a comparative view.

    PubMed

    Sinha, Chris; Gärdenfors, Peter

    2014-10-01

    We propose an event-based account of the cognitive and linguistic representation of time and temporal relations. Human beings differ from nonhuman animals in entertaining and communicating elaborate detached (as opposed to cued) event representations and temporal relational schemas. We distinguish deictically based (D-time) from sequentially based (S-time) representations, identifying these with the philosophical categories of A-series and B-series time. On the basis of cross-linguistic data, we claim that all cultures employ both D-time and S-time representations. We outline a cognitive model of event structure, emphasizing that this does not entail an explicit, separate representation of a time dimension. We propose that the notion of an event-independent, metric "time as such" is not universal, but a cultural and historical construction based on cognitive technologies for measuring time intervals. We critically examine claims that time is universally conceptualized in terms of spatial metaphors, and hypothesize that systematic space-time metaphor is only found in languages and cultures that have constructed the notion of time as a separate dimension. We emphasize the importance of distinguishing what is universal from what is variable in cultural and linguistic representations of time, and speculate on the general implications of an event-based understanding of time. PMID:25098724

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

    NASA Technical Reports Server (NTRS)

    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.

  17. Conditions for Recurrence of a Flow of Physical Events with Unextendable Dead Time Period

    NASA Astrophysics Data System (ADS)

    Nezhel'skaya, L. A.

    2016-04-01

    A flow of physical events (photons, electrons, etc.) is studied. One of the mathematical models of such flows is the modulated MAP flow of events circulating under conditions of unextendable dead time period. The explicit form of the probability density of interarrival interval of the flow is presented together with the explicit form of the joint probability density of two adjacent intervals in the observed flow. The conditions for recurrence of the observable flow of events are presented.

  18. Orbital chronology for the Cenomanian-Turonian Oceanic Anoxic Event 2 and the timing of the "Plenus Cold Event"

    NASA Astrophysics Data System (ADS)

    Voigt, Silke; Erbacher, Jochen; Pälike, Heiko; Westerhold, Thomas

    2015-04-01

    The Cenomanian-Turonian OAE 2 is reflected by one of the most extreme carbon cycle perturbations in Earth's history possibly triggered by massive volcanic CO2 degassing during the emplacement of large igneous provinces (LIPs). Severe climatic, oceanographic and biotic feedbacks are reported from different depositional settings. The nature of these changes as well as their spatial and temporal dimension is still not well understood to date. The main difficulty to integrate different observations in different locations is the insufficient resolution of available timescales and stratigraphies. Although new radiometric ages exists for the stratotype section at Pueblo and regional orbital age models are developed from shelf settings from both sides of the Atlantic Ocean, their correlation to the open ocean is not unequivocal. Here, we present a cyclostratigraphic correlation based on time series analyses of relative changes in XRF-element concentrations derived from two sites, the oceanic ODP-Site 1261 (Demerara Rise, tropical Western Atlantic) and a mid-latitude shelf-sea locality exposed in the Wunstorf Core (Germany). Both successions expose distinct sedimentary cycles as well as a brief period of intermittent surface-water cooling and bottom water oxygenation ("Plenus Cold Event" in western Europe) during the early OAE 2 which is considered as synchronous event by several authors. The estimated overall duration of OAE 2 is about 5 and 4.5 short eccentricity cycles for both Site 1261 and Wunstorf. For correlation purposes the independently derived floating orbital time scales of Site 1261 and Wunstorf are tied to each other using the first prominent increase of the δ13C anomaly, a characteristic feature of all OAE 2 successions. Sedimentary cycles, interpreted as short eccentricity cycles during OAE 2, are correlated between the two different depositional settings. Based on this correlation the cooling pulses recorded in the tropical Atlantic and the European mid

  19. Real-Time Forecasting Of Streamflow And Water Loss/Gain In A River System By Using A Robust Multivariate Bayesian Regression Model

    NASA Astrophysics Data System (ADS)

    Ticlavilca, A. M.; McKee, M.; Walker, W.

    2009-12-01

    This research presents a model that simultaneously forecasts streamflow one and two days ahead, and water loss/gain in a river reach between two reservoirs one day ahead and for the next two days. The reservoir operator can take into account these real-time predictions and decide whether to increase/decrease the releases from the upstream reservoir in order to compensate the water loss/gain and manage the streamflow entering the downstream reservoir efficiently. The model inputs are the past daily data of climate (maximum and minimum temperature), streamflow, reservoir releases, water loss/gain in the river, and irrigation canal diversions. The model is developed in the form of a multivariate relevance vector machine (MVRVM) that is based on a multivariate Bayesian regression approach. Based on this Bayesian approach, a predictive confidence interval is obtained from the model that captures the uncertainty of both the model and the data. The model is applied to the river system located in the Lower Sevier River Basin near Delta, Utah. The results show that the model learns the input-output patterns with good accuracy. A bootstrap analysis is used to guarantee robustness of the estimated model parameters. Test results demonstrate good performance of predictions and statistics that indicate robust model generalization abilities.

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

    NASA Astrophysics Data System (ADS)

    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.

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

    PubMed

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

    2016-01-01

    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. PMID:27293028

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

    PubMed Central

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

    2016-01-01

    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. PMID:27293028

  3. A discrete time event-history approach to informative drop-out in mixed latent Markov models with covariates.

    PubMed

    Bartolucci, Francesco; Farcomeni, Alessio

    2015-03-01

    Mixed latent Markov (MLM) models represent an important tool of analysis of longitudinal data when response variables are affected by time-fixed and time-varying unobserved heterogeneity, in which the latter is accounted for by a hidden Markov chain. In order to avoid bias when using a model of this type in the presence of informative drop-out, we propose an event-history (EH) extension of the latent Markov approach that may be used with multivariate longitudinal data, in which one or more outcomes of a different nature are observed at each time occasion. The EH component of the resulting model is referred to the interval-censored drop-out, and bias in MLM modeling is avoided by correlated random effects, included in the different model components, which follow common latent distributions. In order to perform maximum likelihood estimation of the proposed model by the expectation-maximization algorithm, we extend the usual forward-backward recursions of Baum and Welch. The algorithm has the same complexity as the one adopted in cases of non-informative drop-out. We illustrate the proposed approach through simulations and an application based on data coming from a medical study about primary biliary cirrhosis in which there are two outcomes of interest, one continuous and the other binary. PMID:25227970

  4. Schizophrenia Spectrum Disorders Show Reduced Specificity and Less Positive Events in Mental Time Travel.

    PubMed

    Chen, Xing-Jie; Liu, Lu-Lu; Cui, Ji-Fang; Wang, Ya; Chen, An-Tao; Li, Feng-Hua; Wang, Wei-Hong; Zheng, Han-Feng; Gan, Ming-Yuan; Li, Chun-Qiu; Shum, David H K; Chan, Raymond C K

    2016-01-01

    Mental time travel refers to the ability to recall past events and to imagine possible future events. Schizophrenia (SCZ) patients have problems in remembering specific personal experiences in the past and imagining what will happen in the future. This study aimed to examine episodic past and future thinking in SCZ spectrum disorders including SCZ patients and individuals with schizotypal personality disorder (SPD) proneness who are at risk for developing SCZ. Thirty-two SCZ patients, 30 SPD proneness individuals, and 33 healthy controls participated in the study. The Sentence Completion for Events from the Past Test (SCEPT) and the Sentence Completion for Events in the Future Test were used to measure past and future thinking abilities. Results showed that SCZ patients showed significantly reduced specificity in recalling past and imagining future events, they generated less proportion of specific and extended events compared to healthy controls. SPD proneness individuals only generated less extended events compared to healthy controls. The reduced specificity was mainly manifested in imagining future events. Both SCZ patients and SPD proneness individuals generated less positive events than controls. These results suggest that mental time travel impairments in SCZ spectrum disorders and have implications for understanding their cognitive and emotional deficits. PMID:27507958

  5. Schizophrenia Spectrum Disorders Show Reduced Specificity and Less Positive Events in Mental Time Travel

    PubMed Central

    Chen, Xing-jie; Liu, Lu-lu; Cui, Ji-fang; Wang, Ya; Chen, An-tao; Li, Feng-hua; Wang, Wei-hong; Zheng, Han-feng; Gan, Ming-yuan; Li, Chun-qiu; Shum, David H. K.; Chan, Raymond C. K.

    2016-01-01

    Mental time travel refers to the ability to recall past events and to imagine possible future events. Schizophrenia (SCZ) patients have problems in remembering specific personal experiences in the past and imagining what will happen in the future. This study aimed to examine episodic past and future thinking in SCZ spectrum disorders including SCZ patients and individuals with schizotypal personality disorder (SPD) proneness who are at risk for developing SCZ. Thirty-two SCZ patients, 30 SPD proneness individuals, and 33 healthy controls participated in the study. The Sentence Completion for Events from the Past Test (SCEPT) and the Sentence Completion for Events in the Future Test were used to measure past and future thinking abilities. Results showed that SCZ patients showed significantly reduced specificity in recalling past and imagining future events, they generated less proportion of specific and extended events compared to healthy controls. SPD proneness individuals only generated less extended events compared to healthy controls. The reduced specificity was mainly manifested in imagining future events. Both SCZ patients and SPD proneness individuals generated less positive events than controls. These results suggest that mental time travel impairments in SCZ spectrum disorders and have implications for understanding their cognitive and emotional deficits. PMID:27507958

  6. Fisher's theorems for multivariable, time- and space-dependent systems, with applications in population genetics and chemical kinetics

    PubMed Central

    Vlad, Marcel O.; Szedlacsek, Stefan E.; Pourmand, Nader; Cavalli-Sforza, L. Luca; Oefner, Peter; Ross, John

    2005-01-01

    We study different physical, chemical, or biological processes involving replication, transformation, and disappearance processes, as well as transport processes, and assume that the time and space dependence of the species densities are known. We derive two types of Fisher equations. The first type relates the average value of the time derivative of the relative time-specific rates of growth of the different species to the variance of the relative, time-specific rates of growth. A second type relates the average value of the gradient or the divergence of the relative, space-specific rates of growth to the space correlation matrix of the relative, space-specific rates of growth. These Fisher equations are exact results, which are independent of the detailed kinetics of the process: they are valid whether the evolution equations are linear or nonlinear, local or nonlocal in space and/or time and can be applied for the study of a large class of physical, chemical, and biological systems described in terms of time- and/or space-dependent density fields. We examine the implications of our generalized Fisher relations in population genetics, biochemistry, and chemical kinetics (reaction–diffusion systems). We show that there is a connection between the enhanced (hydrodynamic) transport of mutations induced by population growth and space-specific rate vectors: the velocity of enhanced transport is proportional to the product of the diffusion coefficient of the species and the space rate vector; this relation is similar to a fluctuation–dissipation relation in statistical mechanics. PMID:15994224

  7. Penalised logistic regression and dynamic prediction for discrete-time recurrent event data.

    PubMed

    Elgmati, Entisar; Fiaccone, Rosemeire L; Henderson, R; Matthews, John N S

    2015-10-01

    We consider methods for the analysis of discrete-time recurrent event data, when interest is mainly in prediction. The Aalen additive model provides an extremely simple and effective method for the determination of covariate effects for this type of data, especially in the presence of time-varying effects and time varying covariates, including dynamic summaries of prior event history. The method is weakened for predictive purposes by the presence of negative estimates. The obvious alternative of a standard logistic regression analysis at each time point can have problems of stability when event frequency is low and maximum likelihood estimation is used. The Firth penalised likelihood approach is stable but in removing bias in regression coefficients it introduces bias into predicted event probabilities. We propose an alterative modified penalised likelihood, intermediate between Firth and no penalty, as a pragmatic compromise between stability and bias. Illustration on two data sets is provided. PMID:25626559

  8. Forecasting dose-time profiles of solar particle events using a dosimetry-based forecasting methodology

    NASA Astrophysics Data System (ADS)

    Neal, John Stuart

    2001-10-01

    A dosimetery-based Bayesian methodology for forecasting astronaut radiation doses in deep space due to radiologically significant solar particle event proton fluences is developed. Three non-linear sigmoidal growth curves (Gompertz, Weibull, logistic) are used with hierarchical, non-linear, regression models to forecast solar particle event dose-time profiles from doses obtained early in the development of the event. Since there are no detailed measurements of dose versus time for actual events, surrogate dose data are provided by calculational methods. Proton fluence data are used as input to the deterministic, coupled neutron-proton space radiation computer code, BRYNTRN, for transporting protons and their reaction products (protons, neutrons, 2H, 3H, 3He, and 4He) through aluminum shielding material and water. Calculated doses and dose rates for ten historical solar particle events are used as the input data by grouping similar historical solar particle events, using asymptotic dose and maximum dose rate as the grouping criteria. These historical data are then used to lend strength to predictions of dose and dose rate-time profiles for new solar particle events. Bayesian inference techniques are used to make parameter estimates and predictive forecasts. Markov Chain Monte Carlo (MCMC) methods are used to sample from the posterior distributions. Hierarchical, non-linear regression models provide useful predictions of asymptotic dose and dose-time profiles for the November 8, 2000 and August 12, 1989 solar particle events. Predicted dose rate-time profiles are adequate for the November 8, 2000 solar particle event. Predictions of dose rate-time profiles for the August 12, 1989 solar particle event suffer due to a more complex dose rate-time profile. Forecasts provide a valuable tool to space operations planners when making recommendations concerning operations in which radiological exposure might jeopardize personal safety or mission completion. This work

  9. 0.5 billion events per second time correlated single photon counting using CMOS SPAD arrays.

    PubMed

    Krstajić, Nikola; Poland, Simon; Levitt, James; Walker, Richard; Erdogan, Ahmet; Ameer-Beg, Simon; Henderson, Robert K

    2015-09-15

    We present a digital architecture for fast acquisition of time correlated single photon counting (TCSPC) events from a 32×32 complementary metal oxide semiconductor (CMOS) single photon avalanche detector (SPAD) array (Megaframe) to the computer memory. Custom firmware was written to transmit event codes from 1024-TCSPC-enabled pixels for fast transfer of TCSPC events. Our 1024-channel TCSPC system is capable of acquiring up to 0.5×10(9) TCSPC events per second with 16 histogram bins spanning a 14 ns width. Other options include 320×10(6) TCSPC events per second with 256 histogram bins spanning either a 14 or 56 ns time window. We present a wide-field fluorescence microscopy setup demonstrating fast fluorescence lifetime data acquisition. To the best of our knowledge, this is the fastest direct TCSPC transfer from a single photon counting device to the computer to date. PMID:26371922

  10. Real-time, time-frequency mapping of event-related cortical activation

    NASA Astrophysics Data System (ADS)

    Cheung, Connie; Chang, Edward F.

    2012-08-01

    Functional mapping of eloquent cortex is a common and necessary component of neurosurgical operative planning. Current electrical stimulation-based techniques are inefficient, can evoke seizures and are prone to false-negative results. Here, we present a novel cortical mapping system that extracts event-related neural activity from passive electrocorticographic recordings to quickly and accurately localize sensory and motor cortices using the precise temporal properties of spectral alteration. This procedure generates a robust functional motor and sensory cortical map in seconds, and usually with less than five to ten trial events. Our algorithm demonstrates high concordance with results derived using independent electrical cortical stimulation mapping.

  11. A multivariate time-frequency method to characterize the influence of respiration over heart period and arterial pressure

    NASA Astrophysics Data System (ADS)

    Orini, Michele; Bailón, Raquel; Laguna, Pablo; Mainardi, Luca T.; Barbieri, Riccardo

    2012-12-01

    Respiratory activity introduces oscillations both in arterial pressure and heart period, through mechanical and autonomic mechanisms. Respiration, arterial pressure, and heart period are, generally, non-stationary processes and the interactions between them are dynamic. In this study we present a methodology to robustly estimate the time course of cross spectral indices to characterize dynamic interactions between respiratory oscillations of heart period and blood pressure, as well as their interactions with respiratory activity. Time-frequency distributions belonging to Cohen's class are used to estimate time-frequency (TF) representations of coherence, partial coherence and phase difference. The characterization is based on the estimation of the time course of cross spectral indices estimated in specific TF regions around the respiratory frequency. We used this methodology to describe the interactions between respiration, heart period variability (HPV) and systolic arterial pressure variability (SAPV) during tilt table test with both spontaneous and controlled respiratory patterns. The effect of selective autonomic blockade was also studied. Results suggest the presence of common underling mechanisms of regulation between cardiovascular signals, whose interactions are time-varying. SAPV changes followed respiratory flow both in supine and standing positions and even after selective autonomic blockade. During head-up tilt, phase differences between respiration and SAPV increased. Phase differences between respiration and HPV were comparable to those between respiration and SAPV during supine position, and significantly increased during standing. As a result, respiratory oscillations in SAPV preceded respiratory oscillations in HPV during standing. Partial coherence was the most sensitive index to orthostatic stress. Phase difference estimates were consistent among spontaneous and controlled breathing patterns, whereas coherence was higher in spontaneous breathing

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

    SciTech Connect

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

    2014-09-10

    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 {sup –γ}. The SEEs display a broken power-law WTD. The power-law index is γ{sub 1} = 0.99 for the short waiting times (<70 hr) and γ{sub 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{sup –α}exp (– βλ), the time-dependent Poisson distribution can produce a power-law tail WTD of ∼Δt {sup α} {sup –3}, where 0 ≤ α < 2.

  13. Spatial Cueing in Time-Space Synesthetes: An Event-Related Brain Potential Study

    ERIC Educational Resources Information Center

    Teuscher, Ursina; Brang, David; Ramachandran, Vilayanur S.; Coulson, Seana

    2010-01-01

    Some people report that they consistently and involuntarily associate time events, such as months of the year, with specific spatial locations; a condition referred to as time-space synesthesia. The present study investigated the manner in which such synesthetic time-space associations affect visuo-spatial attention via an endogenous cuing…

  14. Early Event-Related Potentials Correlate with Inspection Time and Intelligence.

    ERIC Educational Resources Information Center

    Caryl, P. G.

    1994-01-01

    Vertex event-related potentials (ERPs) were obtained from undergraduates performing an inspection time task together with measures of inspection time (n=35) and mental ability (n=28). Techniques that reveal changes over time in the relationship between ERP measures and psychometric indices were presented. (SLD)

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

    PubMed

    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. PMID:11252602

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

    PubMed

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

    2014-01-01

    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. PMID

  17. Near Optimal Event-Triggered Control of Nonlinear Discrete-Time Systems Using Neurodynamic Programming.

    PubMed

    Sahoo, Avimanyu; Xu, Hao; Jagannathan, Sarangapani

    2016-09-01

    This paper presents an event-triggered near optimal control of uncertain nonlinear discrete-time systems. Event-driven neurodynamic programming (NDP) is utilized to design the control policy. A neural network (NN)-based identifier, with event-based state and input vectors, is utilized to learn the system dynamics. An actor-critic framework is used to learn the cost function and the optimal control input. The NN weights of the identifier, the critic, and the actor NNs are tuned aperiodically once every triggered instant. An adaptive event-trigger condition to decide the trigger instants is derived. Thus, a suitable number of events are generated to ensure a desired accuracy of approximation. A near optimal performance is achieved without using value and/or policy iterations. A detailed analysis of nontrivial inter-event times with an explicit formula to show the reduction in computation is also derived. The Lyapunov technique is used in conjunction with the event-trigger condition to guarantee the ultimate boundedness of the closed-loop system. The simulation results are included to verify the performance of the controller. The net result is the development of event-driven NDP. PMID:26285220

  18. Negative Emotional Events that People Ruminate about Feel Closer in Time

    PubMed Central

    Siedlecka, Ewa; Capper, Miriam M.; Denson, Thomas F.

    2015-01-01

    Rumination is intrusive, perseverative cognition. We suggest that one psychological consequence of ruminating about negative emotional events is that the events feel as though they happened metaphorically “just yesterday”. Results from three studies showed that ruminating about real world anger provocations, guilt-inducing events, and sad times in the last year made these past events feel as though they happened more recently. The relationship between rumination and reduced temporal psychological distance persisted even when controlling for when the event occurred and the emotional intensity of the event. Moreover, angry rumination was correlated with enhanced approach motivation, which mediated the rumination-distance relationship. The relationship between guilty rumination and distance was mediated by enhanced vividness. Construal level and taking a 3rd person perspective contributed to the sense of distance when participants were prompted to think about less emotionally charged situations. A meta-analysis of the data showed that the relationship between rumination and reduced distance was significant and twice as large as the same relationship for neutral events. These findings have implications for understanding the role of emotional rumination on memory processes in clinical populations and people prone to rumination. This research suggests that rumination may be a critical mechanism that keeps negative events close in the heart, mind, and time. PMID:25714395

  19. Inter event times of fluid induced earthquakes suggest their Poisson nature

    NASA Astrophysics Data System (ADS)

    Langenbruch, C.; Dinske, C.; Shapiro, S. A.

    2011-11-01

    We analyze the inter event time distribution of fluid-injection-induced earthquakes for six catalogs collected at geothermal injection sites at Soultz-sous-Forêts and Basel. We find that the distribution of waiting times during phases of constant seismicity rate coincides with the exponential distribution of the homogeneous Poisson process (HPP). We analyze the waiting times for the complete event catalogs and find that, as for naturally occurring earthquakes, injection induced earthquakes are distributed according to a non homogeneous Poisson process in time. Moreover, the process of event occurrence in the injection volume domain is a HPP. These results indicate that fluid-injection-induced earthquakes are directly triggered by the loading induced by the fluid injection. We also consider the spatial distance between events and perform a nearest neighbor analysis in the time-space-magnitude domain. Our analysis including a comparison to a synthetic catalog created according to the ETAS model reveals no signs of causal relationships between events. Therefore, coupling effects between events are very weak. The Poisson model seems to be a very good approximation of fluid induced seismicity.

  20. Case-based damage assessment of storm events in near real-time

    NASA Astrophysics Data System (ADS)

    Möhrle, Stella; Mühr, Bernhard

    2015-04-01

    Damage assessment in times of crisis is complex due to a highly dynamic environment and uncertainty in respect of available information. In order to assess the extent of a disaster in near real-time, historic events and their consequences may facilitate first estimations. Events of the past, which are in the same category or which have similar frame conditions like imminent or just occurring storms, might give preliminary information about possible damages. The challenge here is to identify useful historic events based on little information regarding the current event. This work investigates the potential of drawing conclusions about a current event based on similar historic disasters, exemplarily for storm events in Germany. Predicted wind speed and area affected can be used for roughly classifying a storm event. For this purpose, a grid of equidistant points can be used to split up the area of Germany. In combination with predicted wind speed at these points and the predicted number of points affected, respectively, a storm can be categorized in a fast manner. In contrast to investigate only data taken by the observation network, the grid approach is more objective, since stations are not equally distributed. Based on model data, the determined storm class provides one key factor for identifying similar historic events. Further aspects, such as region or specific event characteristics, complete knowledge about the potential storm scale and result in a similarity function, which automatically identifies useful events from the past. This work presents a case-based approach to estimate damages in the event of an extreme storm event in Germany. The focus in on the similarity function, which is based on model storm classes, particularly wind speed and area affected. In order to determine possible damages more precisely, event specific characteristics and region will be included. In the frame of determining similar storm events, neighboring storm classes will be

  1. Characterization of poly(L-lysine)-graft-poly(ethylene glycol) assembled monolayers on niobium pentoxide substrates using time-of-flight secondary ion mass spectrometry and multivariate analysis.

    PubMed

    Wagner, M S; Pasche, S; Castner, D G; Textor, M

    2004-03-01

    Control of protein adsorption onto solid surfaces is a critical area of biomaterials and biosensors research. Application of high performance surface analysis techniques to these problems can improve the rational design and understanding of coatings that control protein adsorption. We have used static time-of-flight secondary ion mass spectrometry (TOF-SIMS) to investigate several poly(L-lysine)-graft-poly(ethylene glycol) (PLL-g-PEG) adlayers adsorbed electrostatically onto negatively charged niobium pentoxide (Nb(2)O(5)) substrates. By varying the PEG graft ratio (i.e., the number of lysine monomers per grafted PEG chain) and the molecular weights of the PLL and PEG polymers, the amount of protein adsorption can be tailored between 1 and 300 ng/cm(2). Detailed multivariate analysis using principal component analysis (PCA) of the positive and negative ion TOF-SIMS spectra showed changes in the outermost surface of the polymer films that were related to the density and molecular weight of the PEG chains on the surface. However, no significant differences were noted due to PLL molecular weight, despite observed differences in the serum adsorption characteristics for adlayers of PLL-g-PEG polymers with different PLL molecular weights. From the PCA results, multivariate peak intensity ratios were developed that correlated with the thickness of the adlayer and the enrichment of the PEG chains and the methoxy terminus of the PEG chains at the outermost surface of the adlayer. Furthermore, partial least squares regression was used to correlate the TOF-SIMS spectra with the amount of protein adsorption, resulting in a predictive model for determining the amount of protein adsorption on the basis of the TOF-SIMS spectra. The accuracy of the prediction of the amount of serum adsorption depended on the molecular weight of the PLL and PEG polymers and the PEG graft ratio. The combination of multivariate analysis and static TOF-SIMS provides detailed information on the surface

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

    PubMed Central

    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 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 clinical

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

    PubMed

    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 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 clinical practice

  4. A LORETA study of mental time travel: similar and distinct electrophysiological correlates of re-experiencing past events and pre-experiencing future events.

    PubMed

    Lavallee, Christina F; Persinger, Michael A

    2010-12-01

    Previous studies exploring mental time travel paradigms with functional neuroimaging techniques have uncovered both common and distinct neural correlates of re-experiencing past events or pre-experiencing future events. A gap in the mental time travel literature exists, as paradigms have not explored the affective component of re-experiencing past episodic events; this study explored this sparsely researched area. The present study employed standardized low resolution electromagnetic tomography (sLORETA) to identify electrophysiological correlates of re-experience affect-laden and non-affective past events, as well as pre-experiencing a future anticipated event. Our results confirm previous research and are also novel in that we illustrate common and distinct electrophysiological correlates of re-experiencing affective episodic events. Furthermore, research from this experiment yields results outlining a pattern of activation in the frontal and temporal regions is correlated with the time frame of past or future events subjects imagined. PMID:20598583

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

    NASA Astrophysics Data System (ADS)

    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.

  6. Classification and Space-Time Analysis of Precipitation Events in Manizales, Caldas, Colombia.

    NASA Astrophysics Data System (ADS)

    Suarez Hincapie, J. N.; Vélez, J.; Romo Melo, L.; Chang, P.

    2015-12-01

    Manizales is a mid-mountain Andean city located near the Nevado del Ruiz volcano in west-central Colombia, this location exposes it to earthquakes, floods, landslides and volcanic eruptions. It is located in the intertropical convergence zone (ITCZ) and presents a climate with a bimodal rainfall regime (Cortés, 2010). Its mean annual rainfall is 2000 mm, one may observe precipitation 70% of the days over a year. This rain which favors the formation of large masses of clouds and the presence of macroclimatic phenomenon as "El Niño South Oscillation", has historically caused great impacts in the region (Vélez et al, 2012). For example the geographical location coupled with rain events results in a high risk of landslides in the city. Manizales has a hydrometeorological network of 40 stations that measure and transmit data of up to eight climate variables. Some of these stations keep 10 years of historical data. However, until now this information has not been used for space-time classification of precipitation events, nor has the meteorological variables that influence them been thoroughly researched. The purpose of this study was to classify historical events of rain in an urban area of Manizales and investigate patterns of atmospheric behavior that influence or trigger such events. Classification of events was performed by calculating the "n" index of the heavy rainfall, describing the behavior of precipitation as a function of time throughout the event (Monjo, 2009). The analysis of meteorological variables was performed using statistical quantification over variable time periods before each event. The proposed classification allowed for an analysis of the evolution of rainfall events. Specially, it helped to look for the influence of different meteorological variables triggering rainfall events in hazardous areas as the city of Manizales.

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

    PubMed Central

    Baer, L. H.; Thibodeau, J. L. N.; Gralnick, T. M.; Li, K. Z. H.; Penhune, V. B.

    2013-01-01

    Introduction: 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. Materials and Methods: 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). Results: 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. Discussion: 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. PMID:23717275

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

    SciTech Connect

    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. (Los Alamos National Lab.,

    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 {approximately}9 signal events are expected to remain. The same effect was observed at a chance probability level of {approximately}0.1%. 1 ref., 7 figs.

  9. Timing of the most recent surface rupture event on the Ohariu Fault near Paraparaumu, New Zealand

    USGS Publications Warehouse

    Litchfield, N.; Van Dissen, R.; Langridge, Rob; Heron, D.; Prentice, C.

    2004-01-01

    Thirteen radiocarbon ages from three trenches across the Ohariu Fault tightly constrain the timing of the most recent surface rupture event at Muaupoko Stream valley, c. 2 km east of Paraparaumu, to between 930 and 1050 cal. yr BP. This age overlaps with previously published ages of the most recent event on the Ohariu Fault and together they further constrain the event to 1000-1050 cal. yr BP. Two trenches provide loose constraints on the maximum recurrence interval at 3-7000 yr. Tephra, most probably the Kawakawa Tephra, was found within alluvial fan deposits in two of the trenches. ?? The Royal Society of New Zealand 2004.

  10. AXS and SOM: A new statistical approach for treating within-subject, time-varying, multivariate data collected using the AXS Test Battery

    NASA Astrophysics Data System (ADS)

    Lauter, Judith L.; Ninness, Chris

    2003-10-01

    The Auditory Cross-Section (AXS) Test Battery [J. L. Lauter, Behav. Res. Methods Instrum. Comput. 32, 180-190 (2000)], described in presentations to ASA in 2002 and 2003, is designed to document dynamic relations linking the cortex, brainstem, and body periphery (whether physics, physiology, or behavior) on an individually-specific basis. Data collections using the battery typically employ a within-subject, time-varying, multivariate design, yet conventional group statistics do not provide satisfactory means of treating such data. We have recently developed an approach based on Kohonens (2001) Self-Organizing Maps (SOM) algorithm, which categorizes time-varying profiles across variables, either within- or between-subjects. The treatment entails three steps: (1) z-score transformation of all raw data; (2) employing the SOM to sort the time-varying profiles into groups; and (3) deriving an estimate of the bounds for the Bayes error rate. Our three-step procedure will be briefly described and illustrated with data from a recent study combining otoacoustic emissions, auditory brainstem responses, and cortical qEEG.

  11. A Time-Reversed Reciprocal Method for Detecting High-frequency events in Civil Structures

    NASA Astrophysics Data System (ADS)

    Kohler, M. D.; Heaton, T. H.

    2007-12-01

    A new method that uses the properties of wave propagation reciprocity and time-reversed reciprocal Green's functions is presented for identifying high-frequency events that occur within engineered structures. Wave propagation properties of a seismic source in an elastic medium are directly applicable to structural waveform data. The number of structures with dense seismic networks embedded in them is increasing, making it possible to develop new approaches to identifying failure events such as fracturing welds that take advantage of the large number of recordings. The event identification method is based on the hypothesis that a database can be compiled of pre-event, source-receiver Green's functions using experimental sources. For buildings it is assumed that the source-time excitation is a delta function, proportional to the displacement produced at the receiver site. In theory, if all the Green's functions for a structure are known for a complete set of potential failure event locations, forward modeling can be used to compute a range of displacements to identify the correct Green's functions, locations, and source times from the suite of displacements that recorded actual events. The method is applied to a 17-story, steel, moment-frame building using experimentally applied impulse-force hammer sources. The building has an embedded, 72-channel, accelerometer array that is continuously recorded by 24-bit data loggers at 100 and 500 sps. The focus of this particular application is the identification of brittle- fractured welds of beam-column connections.

  12. Multivariate postprocessing techniques for probabilistic hydrological forecasting

    NASA Astrophysics Data System (ADS)

    Hemri, S.; Lisniak, D.; Klein, B.

    2015-09-01

    Hydrologic ensemble forecasts driven by atmospheric ensemble prediction systems need statistical postprocessing in order to account for systematic errors in terms of both location and spread. Runoff is an inherently multivariate process with typical events lasting from hours in case of floods to weeks or even months in case of droughts. This calls for multivariate postprocessing techniques that yield well-calibrated forecasts in univariate terms and ensure a realistic temporal dependence structure at the same time. To this end, the univariate ensemble model output statistics (EMOS) postprocessing method is combined with two different copula approaches that ensure multivariate calibration throughout the entire forecast horizon. The domain of this study covers three subcatchments of the river Rhine that represent different sizes and hydrological regimes: the Upper Rhine up to the gauge Maxau, the river Moselle up to the gauge Trier, and the river Lahn up to the gauge Kalkofen. In this study, the two approaches to model the temporal dependence structure are ensemble copula coupling (ECC), which preserves the dependence structure of the raw ensemble, and a Gaussian copula approach (GCA), which estimates the temporal correlations from training observations. The results indicate that both methods are suitable for modeling the temporal dependencies of probabilistic hydrologic forecasts.

  13. Multivariate respiratory motion prediction

    NASA Astrophysics Data System (ADS)

    Dürichen, R.; Wissel, T.; Ernst, F.; Schlaefer, A.; Schweikard, A.

    2014-10-01

    In extracranial robotic radiotherapy, tumour motion is compensated by tracking external and internal surrogates. To compensate system specific time delays, time series prediction of the external optical surrogates is used. We investigate whether the prediction accuracy can be increased by expanding the current clinical setup by an accelerometer, a strain belt and a flow sensor. Four previously published prediction algorithms are adapted to multivariate inputs—normalized least mean squares (nLMS), wavelet-based least mean squares (wLMS), support vector regression (SVR) and relevance vector machines (RVM)—and evaluated for three different prediction horizons. The measurement involves 18 subjects and consists of two phases, focusing on long term trends (M1) and breathing artefacts (M2). To select the most relevant and least redundant sensors, a sequential forward selection (SFS) method is proposed. Using a multivariate setting, the results show that the clinically used nLMS algorithm is susceptible to large outliers. In the case of irregular breathing (M2), the mean root mean square error (RMSE) of a univariate nLMS algorithm is 0.66 mm and can be decreased to 0.46 mm by a multivariate RVM model (best algorithm on average). To investigate the full potential of this approach, the optimal sensor combination was also estimated on the complete test set. The results indicate that a further decrease in RMSE is possible for RVM (to 0.42 mm). This motivates further research about sensor selection methods. Besides the optical surrogates, the sensors most frequently selected by the algorithms are the accelerometer and the strain belt. These sensors could be easily integrated in the current clinical setup and would allow a more precise motion compensation.

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

    NASA Astrophysics Data System (ADS)

    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

  15. Measures of dependence for multivariate Lévy distributions

    NASA Astrophysics Data System (ADS)

    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.

  16. Model for the evolution of the time profile in optimistic parallel discrete event simulations

    NASA Astrophysics Data System (ADS)

    Ziganurova, L.; Novotny, M. A.; Shchur, L. N.

    2016-02-01

    We investigate synchronisation aspects of an optimistic algorithm for parallel discrete event simulations (PDES). We present a model for the time evolution in optimistic PDES. This model evaluates the local virtual time profile of the processing elements. We argue that the evolution of the time profile is reminiscent of the surface profile in the directed percolation problem and in unrestricted surface growth. We present results of the simulation of the model and emphasise predictive features of our approach.

  17. Non-linear time series analysis of precipitation events using regional climate networks for Germany

    NASA Astrophysics Data System (ADS)

    Rheinwalt, Aljoscha; Boers, Niklas; Marwan, Norbert; Kurths, Jürgen; Hoffmann, Peter; Gerstengarbe, Friedrich-Wilhelm; Werner, Peter

    2016-02-01

    Synchronous occurrences of heavy rainfall events and the study of their relation in time and space are of large socio-economical relevance, for instance for the agricultural and insurance sectors, but also for the general well-being of the population. In this study, the spatial synchronization structure is analyzed as a regional climate network constructed from precipitation event series. The similarity between event series is determined by the number of synchronous occurrences. We propose a novel standardization of this number that results in synchronization scores which are not biased by the number of events in the respective time series. Additionally, we introduce a new version of the network measure directionality that measures the spatial directionality of weighted links by also taking account of the effects of the spatial embedding of the network. This measure provides an estimate of heavy precipitation isochrones by pointing out directions along which rainfall events synchronize. We propose a climatological interpretation of this measure in terms of propagating fronts or event traces and confirm it for Germany by comparing our results to known atmospheric circulation patterns.

  18. Flexible algorithm for real-time convolution supporting dynamic event-related fMRI

    NASA Astrophysics Data System (ADS)

    Eaton, Brent L.; Frank, Randall J.; Bolinger, Lizann; Grabowski, Thomas J.

    2002-04-01

    An efficient algorithm for generation of the task reference function has been developed that allows real-time statistical analysis of fMRI data, within the framework of the general linear model, for experiments with event-related stimulus designs. By leveraging time-stamped data collection in the Input/Output time-aWare Architecture (I/OWA), we detect the onset time of a stimulus as it is delivered to a subject. A dynamically updated list of detected stimulus event times is maintained in shared memory as a data stream and delivered as input to a real-time convolution algorithm. As each image is acquired from the MR scanner, the time-stamp of its acquisition is delivered via a second dynamically updated stream to the convolution algorithm, where a running convolution of the events with an estimated hemodynamic response function is computed at the image acquisition time and written to a third stream in memory. Output is interpreted as the activation reference function and treated as the covariate of interest in the I/OWA implementation of the general linear model. Statistical parametric maps are computed and displayed to the I/OWA user interface in less than the time between successive image acquisitions.

  19. Event- and time-dependent decline of outcome information in the primate prefrontal cortex

    PubMed Central

    Marcos, Encarni; Tsujimoto, Satoshi; Genovesio, Aldo

    2016-01-01

    The prefrontal cortex (PF) is involved in outcome-based flexible adaptation in a dynamically changing environment. The outcome signal dissipates gradually over time, but the temporal dynamics of this dissipation remains unknown. To examine this issue, we analyzed the outcome-related activity of PF neurons in 2 monkeys in a distance discrimination task. The initial prestimulus period of this task varied in duration, allowing us to dissociate the effects of time and event on the decline in previous outcome-related activity —previous correct versus previous error. We observed 2 types of decline in previous outcome representation: PF neurons that ceased to encode the previous outcome as time passed (time-dependent) and neurons that maintained their signal but it decreased rapidly after the occurrence of a new external event (event-dependent). Although the time-dependent dynamics explained the decline in a greater proportion of neurons, the event-dependent decline was also observed in a significant population of neurons. PMID:27162060

  20. Disentangling the effect of event-based cues on children's time-based prospective memory performance.

    PubMed

    Redshaw, Jonathan; Henry, Julie D; Suddendorf, Thomas

    2016-10-01

    Previous time-based prospective memory research, both with children and with other groups, has measured the ability to perform an action with the arrival of a time-dependent yet still event-based cue (e.g., the occurrence of a specific clock pattern) while also engaged in an ongoing activity. Here we introduce a novel means of operationalizing time-based prospective memory and assess children's growing capacities when the availability of an event-based cue is varied. Preschoolers aged 3, 4, and 5years (N=72) were required to ring a bell when a familiar 1-min sand timer had completed a cycle under four conditions. In a 2×2 within-participants design, the timer was either visible or hidden and was either presented in the context of a single task or embedded within a dual picture-naming task. Children were more likely to ring the bell before 2min had elapsed in the visible-timer and single-task conditions, with performance improving with age across all conditions. These results suggest a divergence in the development of time-based prospective memory in the presence versus absence of event-based cues, and they also suggest that performance on typical time-based tasks may be partly driven by event-based prospective memory. PMID:27295204

  1. Ants Can Expect the Time of an Event on Basis of Previous Experiences

    PubMed Central

    Cammaerts, Roger

    2016-01-01

    Working on three ant species of the genus Myrmica, M. ruginodis, M. rubra, and M. sabuleti, we showed that foragers can expect the subsequent time at which food will be available on the basis of the previous times at which food was present. The ants acquired this expectative ability right after having experienced two time shifts of food delivery. Moreover, the ants' learning score appeared to be a logarithmic function of time (i.e., of the number of training days). This ability to expect subsequent times at which an event will occur may be an advantageous ethological trait. PMID:27403457

  2. Ants Can Expect the Time of an Event on Basis of Previous Experiences.

    PubMed

    Cammaerts, Marie-Claire; Cammaerts, Roger

    2016-01-01

    Working on three ant species of the genus Myrmica, M. ruginodis, M. rubra, and M. sabuleti, we showed that foragers can expect the subsequent time at which food will be available on the basis of the previous times at which food was present. The ants acquired this expectative ability right after having experienced two time shifts of food delivery. Moreover, the ants' learning score appeared to be a logarithmic function of time (i.e., of the number of training days). This ability to expect subsequent times at which an event will occur may be an advantageous ethological trait. PMID:27403457

  3. Life events and change in leisure time physical activity: a systematic review.

    PubMed

    Engberg, Elina; Alen, Markku; Kukkonen-Harjula, Katriina; Peltonen, Juha E; Tikkanen, Heikki O; Pekkarinen, Heikki

    2012-05-01

    The global epidemic of chronic non-communicable diseases is closely related to changes in lifestyle, including decreasing leisure time physical activity (PA). Physical inactivity is a major public health challenge. To respond to that challenge, it is essential to know which personal and environmental factors affect PA behaviour. Certain life events may be one contributing factor, by creating emotional distress and disrupting a person's daily routine. The aim was to examine the literature concerning the effects of life events on changes in PA. A systematic literature search was performed on studies that assessed at least one major change in life circumstances and a change in PA. To be included, studies had to assess PA at two timepoints at least (before and after the event). Diseases as life events were excluded from this review. Thirty-four articles met the inclusion criteria. The studies examined the following life-change events: transition to university; change in employment status; marital transitions and changes in relationships; pregnancy/having a child; experiencing harassment at work, violence or disaster; and moving into an institution. The studies reviewed showed statistically significant changes in leisure PA associated with certain life events. In men and women, transition to university, having a child, remarriage and mass urban disaster decreased PA levels, while retirement increased PA. In young women, beginning work, changing work conditions, changing from being single to cohabiting, getting married, pregnancy, divorce/separation and reduced income decreased PA. In contrast, starting a new personal relationship, returning to study and harassment at work increased PA. In middle-aged women, changing work conditions, reduced income, personal achievement and death of a spouse/partner increased PA, while experiencing violence and a family member being arrested or jailed decreased PA. In older women, moving into an institution and interpersonal loss

  4. Profiling and multivariate statistical analysis of Panax ginseng based on ultra-high-performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry.

    PubMed

    Wu, Wei; Sun, Le; Zhang, Zhe; Guo, Yingying; Liu, Shuying

    2015-03-25

    An ultra-high-performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry (UHPLC-Q-TOF-MS) method was developed for the detection and structural analysis of ginsenosides in white ginseng and related processed products (red ginseng). Original neutral, malonyl, and chemically transformed ginsenosides were identified in white and red ginseng samples. The aglycone types of ginsenosides were determined by MS/MS as PPD (m/z 459), PPT (m/z 475), C-24, -25 hydrated-PPD or PPT (m/z 477 or m/z 493), and Δ20(21)-or Δ20(22)-dehydrated-PPD or PPT (m/z 441 or m/z 457). Following the structural determination, the UHPLC-Q-TOF-MS-based chemical profiling coupled with multivariate statistical analysis method was applied for global analysis of white and processed ginseng samples. The chemical markers present between the processed products red ginseng and white ginseng could be assigned. Process-mediated chemical changes were recognized as the hydrolysis of ginsenosides with large molecular weight, chemical transformations of ginsenosides, changes in malonyl-ginsenosides, and generation of 20-(R)-ginsenoside enantiomers. The relative contents of compounds classified as PPD, PPT, malonyl, and transformed ginsenosides were calculated based on peak areas in ginseng before and after processing. This study provides possibility to monitor multiple components for the quality control and global evaluation of ginseng products during processing. PMID:25590943

  5. Jointly modeling time-to-event and longitudinal data: A Bayesian approach.

    PubMed

    Huang, Yangxin; Hu, X Joan; Dagne, Getachew A

    2014-03-01

    This article explores Bayesian joint models of event times and longitudinal measures with an attempt to overcome departures from normality of the longitudinal response, measurement errors, and shortages of confidence in specifying a parametric time-to-event model. We allow the longitudinal response to have a skew distribution in the presence of measurement errors, and assume the time-to-event variable to have a nonparametric prior distribution. Posterior distributions of the parameters are attained simultaneously for inference based on Bayesian approach. An example from a recent AIDS clinical trial illustrates the methodology by jointly modeling the viral dynamics and the time to decrease in CD4/CD8 ratio in the presence of CD4 counts with measurement errors and to compare potential models with various scenarios and different distribution specifications. The analysis outcome indicates that the time-varying CD4 covariate is closely related to the first-phase viral decay rate, but the time to CD4/CD8 decrease is not highly associated with either the two viral decay rates or the CD4 changing rate over time. These findings may provide some quantitative guidance to better understand the relationship of the virological and immunological responses to antiretroviral treatments. PMID:24611039

  6. Time-Frequency Characteristics of Tsunami Magnetic Signals from Four Pacific Ocean Events

    NASA Astrophysics Data System (ADS)

    Schnepf, N. R.; Manoj, C.; An, C.; Sugioka, H.; Toh, H.

    2016-07-01

    The recent deployment of highly sensitive seafloor magnetometers coinciding with the deep solar minimum has provided excellent opportunities for observing tsunami electromagnetic signals. These fluctuating signals (periods ranging from 10-20 min) are generally found to be within ± ˜ 1 nT and coincide with the arrival of the tsunami waves. Previous studies focused on tsunami electromagnetic characteristics, as well as modeling the signal for individual events. This study instead aims to provide the time-frequency characteristics for a range of tsunami signals and a method to separate the data's noise using additional data from a remote observatory. We focus on four Pacific Ocean events of varying tsunami signal amplitude: (1) the 2011 Tohoku, Japan event (M9.0), (2) the 2010 Chile event (M8.8), (3) the 2009 Samoa event (M8.0) and, (4) the 2007 Kuril Islands event (M8.1). We find possible tsunami signals in high-pass filtered data and successfully isolate the signals from noise using a cross-wavelet analysis. The cross-wavelet analysis reveals that the longer period signals precede the stronger, shorter period signals. Our results are very encouraging for using tsunami magnetic signals in warning systems.

  7. Real-time extreme weather event attribution with forecast seasonal SSTs

    NASA Astrophysics Data System (ADS)

    Haustein, K.; Otto, F. E. L.; Uhe, P.; Schaller, N.; Allen, M. R.; Hermanson, L.; Christidis, N.; McLean, P.; Cullen, H.

    2016-06-01

    Within the last decade, extreme weather event attribution has emerged as a new field of science and garnered increasing attention from the wider scientific community and the public. Numerous methods have been put forward to determine the contribution of anthropogenic climate change to individual extreme weather events. So far nearly all such analyses were done months after an event has happened. Here we present a new method which can assess the fraction of attributable risk of a severe weather event due to an external driver in real-time. The method builds on a large ensemble of atmosphere-only general circulation model simulations forced by seasonal forecast sea surface temperatures (SSTs). Taking the England 2013/14 winter floods as an example, we demonstrate that the change in risk for heavy rainfall during the England floods due to anthropogenic climate change, is of similar magnitude using either observed or seasonal forecast SSTs. Testing the dynamic response of the model to the anomalous ocean state for January 2014, we find that observed SSTs are required to establish a discernible link between a particular SST pattern and an atmospheric response such as a shift in the jetstream in the model. For extreme events occurring under strongly anomalous SST patterns associated with known low-frequency climate modes, however, forecast SSTs can provide sufficient guidance to determine the dynamic contribution to the event.

  8. Ordering of young injection events within Saturnian SLS longitude and local time

    NASA Astrophysics Data System (ADS)

    Kennelly, T.; Leisner, J. S.; Hospodarsky, G. B.; Gurnett, D. A.

    2012-12-01

    The Saturnian SLS longitude systems are based on periodic radio emissions generated at high latitudes and relatively close to the planet. These periodicities have been observed throughout the magnetosphere in both the magnetic field and the plasma. While their presence in the outer magnetosphere has been understood, one outstanding question is how these periodicities are transmitted to the inner magnetosphere. The inner and outer magnetospheres are connected by inward-moving flux tubes, referred to as injection events, and it was postulated that they could carry the periodicities between the two regions. Early analysis of these phenomena, however, showed that there was no ordering in longitude. In this study, we reexamine this possibility by limiting our data set to the young injection events observed by the Cassini Radio and Plasma Wave Science instrument. We find that the young injection events are restricted to two local time sectors: post-noon and near-midnight. We find no structure in the post-noon sector, but the near-midnight events are strongly ordered by SLS longitude. Further, the longitudinal ordering varies with Saturnian season. Pre-equinox, the longitude system derived from the northern hemisphere's SKR emissions controls the event occurrence. Post-equinox, the events are ordered by the southern hemisphere-derived longitude system. We suggest that this may be an effect in the variations in the ionospheric conductivity or due to change in the magnetosphere's orientation relative to the solar wind.

  9. Time and again: effects of repetition and retention interval on 2 year olds' event recall.

    PubMed

    Fivush, R; Hamond, N R

    1989-04-01

    How and what very young children remember is a central question for understanding the course of memory development. In this research, we examined the effects of two factors on 2-year-old children's ability to recall novel events: repetition of the experience and time since experience. Twenty 24-month-old and twenty 28-month-old children participated in unusual laboratory play events. Half of the children returned after a 2-week delay and again after a 3-month delay (repeated experience condition); the remaining children returned only after 3 months (single experience condition). Memory was assessed by asking children to reenact the events. Recall was generally accurate, and there were no significant effects of age. All children recalled more information about the activities associated with the event than about the objects. Surprisingly, children in the repeated experience condition recalled as much about the events at the 3-month retention interval as at the 2-week retention interval. Further, children in this condition recalled more information at the 3-month retention interval than children in the single experience condition, suggesting that reexperiencing an event may guard against long-term forgetting. PMID:2703807

  10. The effect of time constraints and running phases on combined event pistol shooting performance.

    PubMed

    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), there were no accompanying changes in the time period that participants spent aiming at the target, shot score, pistol movement or centre of pressure movement (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. PMID:26375196

  11. "Anniversary Reaction": Important Events and Timing of Death in a Group of Roman Catholic Priests.

    ERIC Educational Resources Information Center

    Walker, Lee; Walker, Lawrence D.

    1990-01-01

    Compared death dates of 1,038 Roman Catholic priests with dates of Christmas, Easter, birthday, and day of ordination. Found no meaningful patterns of death around any anniversary, suggesting either no association between time of death and important anniversaries or that important event may be so extraordinary to each individuals that it is not…

  12. Intensity/time profiles of solar particle events at one astronomical unit

    NASA Technical Reports Server (NTRS)

    Shea, M. A.

    1988-01-01

    A description of the intensity-time profiles of solar proton events observed at the orbit of the earth is presented. The discussion, which includes descriptive figures, presents a general overview of the subject without the detailed mathematical description of the physical processes which usually accompany most reviews.

  13. Modeling Repeatable Events Using Discrete-Time Data: Predicting Marital Dissolution

    ERIC Educational Resources Information Center

    Teachman, Jay

    2011-01-01

    I join two methodologies by illustrating the application of multilevel modeling principles to hazard-rate models with an emphasis on procedures for discrete-time data that contain repeatable events. I demonstrate this application using data taken from the 1995 National Survey of Family Growth (NSFG) to ascertain the relationship between multiple…

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

    PubMed

    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. PMID:26261908

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

    ERIC Educational Resources Information Center

    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…

  16. Global grid of master events for waveform cross-correlation: from testing to real time processing

    NASA Astrophysics Data System (ADS)

    Bobrov, Dmitry; Rozhkov, Mikhail; Kitov, Ivan

    2014-05-01

    Seismic monitoring of the Comprehensive Nuclear-Test-Ban Treaty (CTBT) requires a globally uniform detection threshold, which is provided by geographical distribution of the Primary Seismic Network of the International Monitoring System (IMS). This detection threshold has to be as low as allowed by the entire set of real time and historical data recorded by the IMS. The International Data Centre (IDC) analyzes all relevant data in automatic processing and interactive review to issue a Reviewed Event Bulletin (REB), which includes all qualified events as obtained for the purpose of nuclear test monitoring. Since 2000, raw data, individual detections, and created events are saved in the IDC archive currently reaching tens of terabyte. In order to effectively use this archive in global monitoring we introduced the waveform cross correlation (matched filter) technique. Cross correlation between real time records at IMS stations and template waveforms is calculated for a dense (spacing of ~ 140 km) and regular grid of master events uniformly covering the globe. There are approximately 25,000 master events with 3 to 10 templates at IMS stations. In seismically active zones, we populate masters with real waveforms. For aseismic zones, we develop an extended set of synthetic templates for virtual master events. For optimal performance of cross correlation, the Principal and Independent Component Analysis are applied to the historical (from earthquakes and underground nuclear tests) and synthetic waveforms. Real waveform templates and selected PCA/ICA components are used in automatic processing for the production of a tentative cross-correlation standard event list (XSEL).

  17. Combined Use of Absolute and Differential Seismic Arrival Time Data to Improve Absolute Event Location

    NASA Astrophysics Data System (ADS)

    Myers, S.; Johannesson, G.

    2012-12-01

    Arrival time measurements based on waveform cross correlation are becoming more common as advanced signal processing methods are applied to seismic data archives and real-time data streams. Waveform correlation can precisely measure the time difference between the arrival of two phases, and differential time data can be used to constrain relative location of events. Absolute locations are needed for many applications, which generally requires the use of absolute time data. Current methods for measuring absolute time data are approximately two orders of magnitude less precise than differential time measurements. To exploit the strengths of both absolute and differential time data, we extend our multiple-event location method Bayesloc, which previously used absolute time data only, to include the use of differential time measurements that are based on waveform cross correlation. Fundamentally, Bayesloc is a formulation of the joint probability over all parameters comprising the multiple event location system. The Markov-Chain Monte Carlo method is used to sample from the joint probability distribution given arrival data sets. The differential time component of Bayesloc includes scaling a stochastic estimate of differential time measurement precision based the waveform correlation coefficient for each datum. For a regional-distance synthetic data set with absolute and differential time measurement error of 0.25 seconds and 0.01 second, respectively, epicenter location accuracy is improved from and average of 1.05 km when solely absolute time data are used to 0.28 km when absolute and differential time data are used jointly (73% improvement). The improvement in absolute location accuracy is the result of conditionally limiting absolute location probability regions based on the precise relative position with respect to neighboring events. Bayesloc estimates of data precision are found to be accurate for the synthetic test, with absolute and differential time measurement

  18. Renewal stochastic processes with correlated events: Phase transitions along time evolution

    NASA Astrophysics Data System (ADS)

    Velázquez, Jorge; Robledo, Alberto

    2011-03-01

    We consider renewal stochastic processes generated by nonindependent events from the perspective that their basic distribution and associated generating functions obey the statistical-mechanical structure of systems with interacting degrees of freedom. Based on this fact we look briefly into the less-known case of processes that display phase transitions along time. When the density distribution ψn(t) for the occurrence of the nth event at time t is considered to be a partition function, of a “microcanonical” type for n “degrees of freedom” at fixed “energy” t, one obtains a set of four partition functions of which that for the generating function variable z and Laplace transform variable ɛ, conjugate to n and t, respectively, plays a central role. These partition functions relate to each other in the customary way and in accordance to the precepts of large deviations theory, while the entropy, or Massieu potential, derived from ψn(t) satisfies an Euler relation. We illustrate this scheme first for an ordinary renewal process of events generated by a simple exponential waiting-time distribution ψ(t). Then we examine a process modeled after the so-called Hamiltonian mean-field model that is representative of agents that perform a repeated task with an associated outcome, such as an opinion poll. When a sequence of (many) events takes place in a sufficiently short time the process exhibits clustering of the outcome, but for larger times the process resembles that of independent events. The two regimes are separated by a sharp transition, technically of the second order. Finally we point out the existence of a similar scheme for random-walk processes.

  19. Analysis of inter-event times for avalanches on a conical bead pile with cohesion

    NASA Astrophysics Data System (ADS)

    Lehman, Susan; Johnson, Nathan; Tieman, Catherine; Wainwright, Elliot

    2015-03-01

    We investigate the critical behavior of a 3D conical bead pile built from uniform 3 mm steel spheres. Beads are added to the pile by dropping them onto the apex one at a time; avalanches are measured through changes in pile mass. We investigate the dynamic response of the pile by recording avalanches from the pile over tens of thousands of bead drops. We have previously shown that the avalanche size distribution follows a power law for beads dropped onto the pile apex from a low drop height. We are now tuning the critical behavior of the system by adding cohesion from a uniform magnetic field and find an increase in both size and number for very large avalanches and decreases in the mid-size avalanches. The resulting bump in the avalanche distribution moves to larger avalanche size as the cohesion in the system is increased. We compare the experimental inter-event time distribution to both the Brownian passage-time and Weibull distributions, and observe a shift from the Weibull to Brownian passage-time as we raise the threshold from measuring time between events of all sizes to time between only the largest system-spanning events. These results are both consistent with those from a mean-field model of slip avalanches in a shear system [Dahmen, Nat Phys 7, 554 (2011)].

  20. The DOE Model for Improving Seismic Event Locations Using Travel Time Corrections: Description and Demonstration

    SciTech Connect

    Hipp, J.R.; Moore, S.G.; Shepherd, E.; Young, C.J.

    1998-10-20

    The U.S. National Laboratories, under the auspices of the Department of Energy, have been tasked with improv- ing the capability of the United States National Data Center (USNDC) to monitor compliance with the Comprehen- sive Test Ban Trea~ (CTBT). One of the most important services which the USNDC must provide is to locate suspicious events, preferably as accurately as possible to help identify their origin and to insure the success of on-site inspections if they are deemed necessary. The seismic location algorithm used by the USNDC has the capability to generate accurate locations by applying geographically dependent travel time corrections, but to date, none of the means, proposed for generating and representing these corrections has proven to be entirely satisfactory. In this presentation, we detail the complete DOE model for how regional calibration travel time information gathered by the National Labs will be used to improve event locations and provide more realistic location error esti- mates. We begin with residual data and error estimates from ground truth events. Our model consists of three parts: data processing, data storage, and data retrieval. The former two are effectively one-time processes, executed in advance before the system is made operational. The last step is required every time an accurate event location is needed. Data processing involves applying non-stationary Bayesian kriging to the residwd data to densifi them, and iterating to find the optimal tessellation representation for the fast interpolation in the data retrieval task. Both the kriging and the iterative re-tessellation are slow, computationally-expensive processes but this is acceptable because they are performed off-line, before any events are to be located. In the data storage task, the densified data set is stored in a database and spatially indexed. Spatial indexing improves the access efficiency of the geographically-ori- ented data requests associated with event location

  1. gPhoton: Time-tagged GALEX photon events analysis tools

    NASA Astrophysics Data System (ADS)

    Million, Chase C.; Fleming, S. W.; Shiao, B.; Loyd, P.; Seibert, M.; Smith, M.

    2016-03-01

    Written in Python, gPhoton calibrates and sky-projects the ~1.1 trillion ultraviolet photon events detected by the microchannel plates on the Galaxy Evolution Explorer Spacecraft (GALEX), archives these events in a publicly accessible database at the Mikulski Archive for Space Telescopes (MAST), and provides tools for working with the database to extract scientific results, particularly over short time domains. The software includes a re-implementation of core functionality of the GALEX mission calibration pipeline to produce photon list files from raw spacecraft data as well as a suite of command line tools to generate calibrated light curves, images, and movies from the MAST database.

  2. Note: Gaussian mixture model for event recognition in optical time-domain reflectometry based sensing systems.

    PubMed

    Fedorov, A K; Anufriev, M N; Zhirnov, A A; Stepanov, K V; Nesterov, E T; Namiot, D E; Karasik, V E; Pnev, A B

    2016-03-01

    We propose a novel approach to the recognition of particular classes of non-conventional events in signals from phase-sensitive optical time-domain-reflectometry-based sensors. Our algorithmic solution has two main features: filtering aimed at the de-nosing of signals and a Gaussian mixture model to cluster them. We test the proposed algorithm using experimentally measured signals. The results show that two classes of events can be distinguished with the best-case recognition probability close to 0.9 at sufficient numbers of training samples. PMID:27036840

  3. Note: Gaussian mixture model for event recognition in optical time-domain reflectometry based sensing systems

    NASA Astrophysics Data System (ADS)

    Fedorov, A. K.; Anufriev, M. N.; Zhirnov, A. A.; Stepanov, K. V.; Nesterov, E. T.; Namiot, D. E.; Karasik, V. E.; Pnev, A. B.

    2016-03-01

    We propose a novel approach to the recognition of particular classes of non-conventional events in signals from phase-sensitive optical time-domain-reflectometry-based sensors. Our algorithmic solution has two main features: filtering aimed at the de-nosing of signals and a Gaussian mixture model to cluster them. We test the proposed algorithm using experimentally measured signals. The results show that two classes of events can be distinguished with the best-case recognition probability close to 0.9 at sufficient numbers of training samples.

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

    NASA Astrophysics Data System (ADS)

    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

  5. Ontology-based time information representation of vaccine adverse events in VAERS for temporal analysis

    PubMed Central

    2012-01-01

    Background The U.S. FDA/CDC Vaccine Adverse Event Reporting System (VAERS) provides a valuable data source for post-vaccination adverse event analyses. The structured data in the system has been widely used, but the information in the write-up narratives is rarely included in these kinds of analyses. In fact, the unstructured nature of the narratives makes the data embedded in them difficult to be used for any further studies. Results We developed an ontology-based approach to represent the data in the narratives in a “machine-understandable” way, so that it can be easily queried and further analyzed. Our focus is the time aspect in the data for time trending analysis. The Time Event Ontology (TEO), Ontology of Adverse Events (OAE), and Vaccine Ontology (VO) are leveraged for the semantic representation of this purpose. A VAERS case report is presented as a use case for the ontological representations. The advantages of using our ontology-based Semantic web representation and data analysis are emphasized. Conclusions We believe that representing both the structured data and the data from write-up narratives in an integrated, unified, and “machine-understandable” way can improve research for vaccine safety analyses, causality assessments, and retrospective studies. PMID:23256916

  6. Modelling the type and timing of consecutive events: application to predicting preterm birth in repeated pregnancies

    PubMed Central

    Shih, Joanna H.; Albert, Paul S.; Mendola, Pauline; Grantz, Katherine L.

    2016-01-01

    Summary Predicting the occurrence and timing of adverse pregnancy events such as preterm birth is an important analytical challenge in obstetrical practice. Developing statistical approaches that can be used to assess the risk and timing of these adverse events will provide clinicians with tools for individualized risk assessment that account for a woman’s prior pregnancy history. Often adverse pregnancy outcomes are subject to competing events; for example, interest may focus on the occurrence of pre-eclampsia-related preterm birth, where preterm birth for other reasons may serve as a competing event. We propose modelling the type and timing of adverse outcomes in repeated pregnancies. We formulate a joint model, where types of adverse outcomes across repeated pregnancies are modelled by using a polychotomous logistic regression model with random effects, and gestational ages at delivery are modelled conditionally on the types of adverse outcome. The correlation between gestational ages conditional on the adverse pregnancies is modelled by the semiparametric normal copula function. We present a two-stage estimation method and develop the asymptotic theory for the estimators proposed. The model and estimation procedure proposed are applied to the National Institute of Child Health and Human Development consecutive pregnancies study data and evaluated by simulations.

  7. Relative Time-scale for Channeling Events Within Chaotic Terrains, Margaritifer Sinus, Mars

    NASA Technical Reports Server (NTRS)

    Janke, D.

    1985-01-01

    A relative time scale for ordering channel and chaos forming events was constructed for areas within the Margaritifer Sinus region of Mars. Transection and superposition relationships of channels, chaotic terrain, and the surfaces surrounding them were used to create the relative time scale; crater density studies were not used. Channels and chaos in contact with one another were treated as systems. These systems were in turn treated both separately (in order to understand internal relationships) and as members of the suite of Martian erosional forms (in order to produce a combined, master time scale). Channeling events associated with chaotic terrain development occurred over an extended geomorphic period. The channels can be divided into three convenient groups: those that pre-date intercrater plains development post-plains, pre-chasma systems; and those associated with the development of the Vallis Marineris chasmata. No correlations with cyclic climatic changes, major geologic events in other regions on Mars, or triggering phenomena (for example, specific impact events) were found.

  8. Modelling the timing of major spring bloom events in the central Yellow Sea

    NASA Astrophysics Data System (ADS)

    Xuan, Ji-Liang; Zhou, Feng; Huang, Daji; Zhu, Xiao-Hua; Xing, Chuanxi; Fan, Xiaopeng

    2012-11-01

    Spring blooms observed in the Yellow Sea, which contribute the primary production in the local food chain, generally occur in the central part of the Yellow Sea (YS) in the early spring from March to April. In this paper, we use a 3-D physical ocean model and 1-D ecosystem model to explore the timing of the five major spring bloom events observed in the central YS in 2007. The results show that Sverdrup's critical depth model can be applied to simulate the first four spring bloom events in March and April of 2007. Under the conditions when nutrients are sufficient, the timing of the spring bloom events appears to always be controlled by physical processes and the reduction of the wind speed in particular. The magnitude of the bloom events is affected by light and temperature in the euphotic layer. The correlation between the timing of the spring bloom and the reduction of the wind speed is investigated by reversal computations and linear regression, and a critical wind speed of less than 5.7 m s-1 was determined to trigger the bloom.

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

    NASA Technical Reports Server (NTRS)

    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.

  10. Time forecast of a break-off event from a hanging glacier

    NASA Astrophysics Data System (ADS)

    Faillettaz, Jérome; Funk, Martin; Vagliasindi, Marco

    2016-06-01

    A cold hanging glacier located on the south face of the Grandes Jorasses (Mont Blanc, Italy) broke off on the 23 and 29 September 2014 with a total estimated ice volume of 105 000 m3. Thanks to accurate surface displacement measurements taken up to the final break-off, this event was successfully predicted 10 days in advance, enabling local authorities to take the necessary safety measures. The break-off event also confirmed that surface displacements experienced a power law acceleration along with superimposed log-periodic oscillations prior to the final rupture. This paper describes the methods used to achieve a satisfactory time forecast in real time and demonstrates, using a retrospective analysis, their potential for the development of early-warning systems in real time.