Evaluating Perceived Probability of Threat-Relevant Outcomes and Temporal Orientation in Flying Phobia

PubMed Central

Mavromoustakos, Elena; Clark, Gavin I.; Rock, Adam J.

2016-01-01

Probability bias regarding threat-relevant outcomes has been demonstrated across anxiety disorders but has not been investigated in flying phobia. Individual temporal orientation (time perspective) may be hypothesised to influence estimates of negative outcomes occurring. The present study investigated whether probability bias could be demonstrated in flying phobia and whether probability estimates of negative flying events was predicted by time perspective. Sixty flying phobic and fifty-five non-flying-phobic adults were recruited to complete an online questionnaire. Participants completed the Flight Anxiety Scale, Probability Scale (measuring perceived probability of flying-negative events, general-negative and general positive events) and the Past-Negative, Future and Present-Hedonistic subscales of the Zimbardo Time Perspective Inventory (variables argued to predict mental travel forward and backward in time). The flying phobic group estimated the probability of flying negative and general negative events occurring as significantly higher than non-flying phobics. Past-Negative scores (positively) and Present-Hedonistic scores (negatively) predicted probability estimates of flying negative events. The Future Orientation subscale did not significantly predict probability estimates. This study is the first to demonstrate probability bias for threat-relevant outcomes in flying phobia. Results suggest that time perspective may influence perceived probability of threat-relevant outcomes but the nature of this relationship remains to be determined. PMID:27557054

"Flash" dance: how speed modulates percieved duration in dancers and non-dancers.

PubMed

Sgouramani, Helena; Vatakis, Argiro

2014-03-01

Speed has been proposed as a modulating factor on duration estimation. However, the different measurement methodologies and experimental designs used have led to inconsistent results across studies, and, thus, the issue of how speed modulates time estimation remains unresolved. Additionally, no studies have looked into the role of expertise on spatiotemporal tasks (tasks requiring high temporal and spatial acuity; e.g., dancing) and susceptibility to modulations of speed in timing judgments. In the present study, therefore, using naturalistic, dynamic dance stimuli, we aimed at defining the role of speed and the interaction of speed and experience on time estimation. We presented videos of a dancer performing identical ballet steps in fast and slow versions, while controlling for the number of changes present. Professional dancers and non-dancers performed duration judgments through a production and a reproduction task. Analysis revealed a significantly larger underestimation of fast videos as compared to slow ones during reproduction. The exact opposite result was true for the production task. Dancers were significantly less variable in their time estimations as compared to non-dancers. Speed and experience, therefore, affect the participants' estimates of time. Results are discussed in association to the theoretical framework of current models by focusing on the role of attention. © 2013 Elsevier B.V. All rights reserved.

Solutions for the diurnally forced advection-diffusion equation to estimate bulk fluid velocity and diffusivity in streambeds from temperature time series

Treesearch

Charles H. Luce; Daniele Tonina; Frank Gariglio; Ralph Applebee

2013-01-01

Work over the last decade has documented methods for estimating fluxes between streams and streambeds from time series of temperature at two depths in the streambed. We present substantial extension to the existing theory and practice of using temperature time series to estimate streambed water fluxes and thermal properties, including (1) a new explicit analytical...

Estimating spatial travel times using automatic vehicle identification data

DOT National Transportation Integrated Search

2001-01-01

Prepared ca. 2001. The paper describes an algorithm that was developed for estimating reliable and accurate average roadway link travel times using Automatic Vehicle Identification (AVI) data. The algorithm presented is unique in two aspects. First, ...

Fossils matter: improved estimates of divergence times in Pinus reveal older diversification.

PubMed

Saladin, Bianca; Leslie, Andrew B; Wüest, Rafael O; Litsios, Glenn; Conti, Elena; Salamin, Nicolas; Zimmermann, Niklaus E

2017-04-04

The taxonomy of pines (genus Pinus) is widely accepted and a robust gene tree based on entire plastome sequences exists. However, there is a large discrepancy in estimated divergence times of major pine clades among existing studies, mainly due to differences in fossil placement and dating methods used. We currently lack a dated molecular phylogeny that makes use of the rich pine fossil record, and this study is the first to estimate the divergence dates of pines based on a large number of fossils (21) evenly distributed across all major clades, in combination with applying both node and tip dating methods. We present a range of molecular phylogenetic trees of Pinus generated within a Bayesian framework. We find the origin of crown Pinus is likely up to 30 Myr older (Early Cretaceous) than inferred in most previous studies (Late Cretaceous) and propose generally older divergence times for major clades within Pinus than previously thought. Our age estimates vary significantly between the different dating approaches, but the results generally agree on older divergence times. We present a revised list of 21 fossils that are suitable to use in dating or comparative analyses of pines. Reliable estimates of divergence times in pines are essential if we are to link diversification processes and functional adaptation of this genus to geological events or to changing climates. In addition to older divergence times in Pinus, our results also indicate that node age estimates in pines depend on dating approaches and the specific fossil sets used, reflecting inherent differences in various dating approaches. The sets of dated phylogenetic trees of pines presented here provide a way to account for uncertainties in age estimations when applying comparative phylogenetic methods.

Cross Time-Frequency Analysis for Combining Information of Several Sources: Application to Estimation of Spontaneous Respiratory Rate from Photoplethysmography

PubMed Central

Peláez-Coca, M. D.; Orini, M.; Lázaro, J.; Bailón, R.; Gil, E.

2013-01-01

A methodology that combines information from several nonstationary biological signals is presented. This methodology is based on time-frequency coherence, that quantifies the similarity of two signals in the time-frequency domain. A cross time-frequency analysis method, based on quadratic time-frequency distribution, has been used for combining information of several nonstationary biomedical signals. In order to evaluate this methodology, the respiratory rate from the photoplethysmographic (PPG) signal is estimated. The respiration provokes simultaneous changes in the pulse interval, amplitude, and width of the PPG signal. This suggests that the combination of information from these sources will improve the accuracy of the estimation of the respiratory rate. Another target of this paper is to implement an algorithm which provides a robust estimation. Therefore, respiratory rate was estimated only in those intervals where the features extracted from the PPG signals are linearly coupled. In 38 spontaneous breathing subjects, among which 7 were characterized by a respiratory rate lower than 0.15 Hz, this methodology provided accurate estimates, with the median error {0.00; 0.98} mHz ({0.00; 0.31}%) and the interquartile range error {4.88; 6.59} mHz ({1.60; 1.92}%). The estimation error of the presented methodology was largely lower than the estimation error obtained without combining different PPG features related to respiration. PMID:24363777

Estimates of residence time and related variations in quality of ground water beneath Submarine Base Bangor and vicinity, Kitsap County, Washington

USGS Publications Warehouse

Cox, S.E.

2003-01-01

Estimates of residence time of ground water beneath Submarine Base Bangor and vicinity ranged from less than 50 to 4,550 years before present, based on analysis of the environmental tracers tritium, chlorofluorocarbons (CFCs), and carbon-14 (14C), in 33 ground-water samples collected from wells tapping the ground-water system. The concentrations of multiple environmental tracers tritium, CFCs, and 14C were used to classify ground water as modern (recharged after 1953), pre-modern (recharged prior to 1953), or indeterminate. Estimates of the residence time of pre-modern ground water were based on evaluation of 14C of dissolved inorganic carbon present in ground water using geochemical mass-transfer modeling to account for the interactions of the carbon in ground water with carbon of the aquifer sediments. Ground-water samples were obtained from two extensive aquifers and from permeable interbeds within the thick confining unit separating the sampled aquifers. Estimates of ground-water residence time for all ground-water samples from the shallow aquifer were less than 45 years and were classified as modern. Estimates of the residence time of ground water in the permeable interbeds within the confining unit ranged from modern to 4,200 years and varied spatially. Near the recharge area, residence times in the permeable interbeds typically were less than 800 years, whereas near the discharge area residence times were in excess of several thousand years. In the deeper aquifers, estimates of ground-water residence times typically were several thousand years but ranged from modern to 4,550 years. These estimates of ground-water residence time based on 14C were often larger than estimates of ground-water residence time developed by particle-tracking analysis using a ground-water flow model. There were large uncertainties?on the order of 1,000-2,000 years?in the estimates based on 14C. Modern ground-water tracers found in some samples from large-capacity production wells screened in the deeper aquifer may be the result of preferential ground-water pathways or induced downward flow caused by pumping stress. Spatial variations in water quality were used to develop a conceptual model of chemical evolution of ground water. Stable isotope ratios of deuterium and oxygen-18 in the 33 ground-water samples were similar, indicating similar climatic conditions and source of precipitation recharge for all of the sampled ground water. Oxidation of organic matter and mineral dissolution increased the concentrations of dissolved inorganic carbon and common ions in downgradient ground waters. However, the largest concentrations were not found near areas of ground-water discharge, but at intermediate locations where organic carbon concentrations were greatest. Dissolved methane, derived from microbial methanogenesis, was present in some ground waters. Methanogenesis resulted in substantial alteration of the carbon isotopic composition of ground water. The NETPATH geochemical model code was used to model mass-transfers of carbon affecting the 14C estimate of ground-water residence time. Carbon sources in ground water include dispersed particulate organic matter present in the confining unit separating the two aquifers and methane present in some ground water. Carbonate minerals were not observed in the lithologic material of the ground-water system but may be present, because they have been found in the bedrock of stream drainages that contribute sediment to the study area.

Application of independent component analysis for speech-music separation using an efficient score function estimation

NASA Astrophysics Data System (ADS)

Pishravian, Arash; Aghabozorgi Sahaf, Masoud Reza

2012-12-01

In this paper speech-music separation using Blind Source Separation is discussed. The separating algorithm is based on the mutual information minimization where the natural gradient algorithm is used for minimization. In order to do that, score function estimation from observation signals (combination of speech and music) samples is needed. The accuracy and the speed of the mentioned estimation will affect on the quality of the separated signals and the processing time of the algorithm. The score function estimation in the presented algorithm is based on Gaussian mixture based kernel density estimation method. The experimental results of the presented algorithm on the speech-music separation and comparing to the separating algorithm which is based on the Minimum Mean Square Error estimator, indicate that it can cause better performance and less processing time

An Estimation Method of Waiting Time for Health Service at Hospital by Using a Portable RFID and Robust Estimation

NASA Astrophysics Data System (ADS)

Ishigaki, Tsukasa; Yamamoto, Yoshinobu; Nakamura, Yoshiyuki; Akamatsu, Motoyuki

Patients that have an health service by doctor have to wait long time at many hospitals. The long waiting time is the worst factor of patient's dissatisfaction for hospital service according to questionnaire for patients. The present paper describes an estimation method of the waiting time for each patient without an electronic medical chart system. The method applies a portable RFID system to data acquisition and robust estimation of probability distribution of the health service and test time by doctor for high-accurate waiting time estimation. We carried out an health service of data acquisition at a real hospital and verified the efficiency of the proposed method. The proposed system widely can be used as data acquisition system in various fields such as marketing service, entertainment or human behavior measurement.

On-Board Real-Time State and Fault Identification for Rovers

NASA Technical Reports Server (NTRS)

Washington, Richard

2000-01-01

For extended autonomous operation, rovers must identify potential faults to determine whether its execution needs to be halted or not. At the same time, rovers present particular challenges for state estimation techniques: they are subject to environmental influences that affect senior readings during normal and anomalous operation, and the sensors fluctuate rapidly both because of noise and because of the dynamics of the rover's interaction with its environment. This paper presents MAKSI, an on-board method for state estimation and fault diagnosis that is particularly appropriate for rovers. The method is based on a combination of continuous state estimation, wing Kalman filters, and discrete state estimation, wing a Markov-model representation.

Modeling environmental noise exceedances using non-homogeneous Poisson processes.

PubMed

Guarnaccia, Claudio; Quartieri, Joseph; Barrios, Juan M; Rodrigues, Eliane R

2014-10-01

In this work a non-homogeneous Poisson model is considered to study noise exposure. The Poisson process, counting the number of times that a sound level surpasses a threshold, is used to estimate the probability that a population is exposed to high levels of noise a certain number of times in a given time interval. The rate function of the Poisson process is assumed to be of a Weibull type. The presented model is applied to community noise data from Messina, Sicily (Italy). Four sets of data are used to estimate the parameters involved in the model. After the estimation and tuning are made, a way of estimating the probability that an environmental noise threshold is exceeded a certain number of times in a given time interval is presented. This estimation can be very useful in the study of noise exposure of a population and also to predict, given the current behavior of the data, the probability of occurrence of high levels of noise in the near future. One of the most important features of the model is that it implicitly takes into account different noise sources, which need to be treated separately when using usual models.

An improved method for nonlinear parameter estimation: a case study of the Rössler model

NASA Astrophysics Data System (ADS)

He, Wen-Ping; Wang, Liu; Jiang, Yun-Di; Wan, Shi-Quan

2016-08-01

Parameter estimation is an important research topic in nonlinear dynamics. Based on the evolutionary algorithm (EA), Wang et al. (2014) present a new scheme for nonlinear parameter estimation and numerical tests indicate that the estimation precision is satisfactory. However, the convergence rate of the EA is relatively slow when multiple unknown parameters in a multidimensional dynamical system are estimated simultaneously. To solve this problem, an improved method for parameter estimation of nonlinear dynamical equations is provided in the present paper. The main idea of the improved scheme is to use all of the known time series for all of the components in some dynamical equations to estimate the parameters in single component one by one, instead of estimating all of the parameters in all of the components simultaneously. Thus, we can estimate all of the parameters stage by stage. The performance of the improved method was tested using a classic chaotic system—Rössler model. The numerical tests show that the amended parameter estimation scheme can greatly improve the searching efficiency and that there is a significant increase in the convergence rate of the EA, particularly for multiparameter estimation in multidimensional dynamical equations. Moreover, the results indicate that the accuracy of parameter estimation and the CPU time consumed by the presented method have no obvious dependence on the sample size.

Parameters estimation using the first passage times method in a jump-diffusion model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Khaldi, K., E-mail: kkhaldi@umbb.dz; LIMOSE Laboratory, Boumerdes University, 35000; Meddahi, S., E-mail: samia.meddahi@gmail.com

2016-06-02

The main purposes of this paper are two contributions: (1) it presents a new method, which is the first passage time (FPT method) generalized for all passage times (GPT method), in order to estimate the parameters of stochastic Jump-Diffusion process. (2) it compares in a time series model, share price of gold, the empirical results of the estimation and forecasts obtained with the GPT method and those obtained by the moments method and the FPT method applied to the Merton Jump-Diffusion (MJD) model.

Use of the superpopulation approach to estimate breeding population size: An example in asynchronously breeding birds

USGS Publications Warehouse

Williams, K.A.; Frederick, P.C.; Nichols, J.D.

2011-01-01

Many populations of animals are fluid in both space and time, making estimation of numbers difficult. Much attention has been devoted to estimation of bias in detection of animals that are present at the time of survey. However, an equally important problem is estimation of population size when all animals are not present on all survey occasions. Here, we showcase use of the superpopulation approach to capture-recapture modeling for estimating populations where group membership is asynchronous, and where considerable overlap in group membership among sampling occasions may occur. We estimate total population size of long-legged wading bird (Great Egret and White Ibis) breeding colonies from aerial observations of individually identifiable nests at various times in the nesting season. Initiation and termination of nests were analogous to entry and departure from a population. Estimates using the superpopulation approach were 47-382% larger than peak aerial counts of the same colonies. Our results indicate that the use of the superpopulation approach to model nesting asynchrony provides a considerably less biased and more efficient estimate of nesting activity than traditional methods. We suggest that this approach may also be used to derive population estimates in a variety of situations where group membership is fluid. ?? 2011 by the Ecological Society of America.

Control system estimation and design for aerospace vehicles with time delay

NASA Technical Reports Server (NTRS)

Allgaier, G. R.; Williams, T. L.

1972-01-01

The problems of estimation and control of discrete, linear, time-varying systems are considered. Previous solutions to these problems involved either approximate techniques, open-loop control solutions, or results which required excessive computation. The estimation problem is solved by two different methods, both of which yield the identical algorithm for determining the optimal filter. The partitioned results achieve a substantial reduction in computation time and storage requirements over the expanded solution, however. The results reduce to the Kalman filter when no delays are present in the system. The control problem is also solved by two different methods, both of which yield identical algorithms for determining the optimal control gains. The stochastic control is shown to be identical to the deterministic control, thus extending the separation principle to time delay systems. The results obtained reduce to the familiar optimal control solution when no time delays are present in the system.

Effect of Display Factors on Chinese Reading Times, Comprehension Scores and Preferences

ERIC Educational Resources Information Center

Chan, A.H.S.; Lee, P.S.K.

2005-01-01

This paper presents the results of research on elemental standard reading time estimates for traditional Chinese characters on computer displays and explores the factors that may affect the time estimates. Seventy-two native Chinese readers, aged 19 to 24, were asked to read 16 simple passages and then answer four multiple-choice questions.…

Training specificity and transfer in time and distance estimation.

PubMed

Healy, Alice F; Tack, Lindsay Anderson; Schneider, Vivian I; Barshi, Immanuel

2015-07-01

Learning is often specific to the conditions of training, making it important to identify which aspects of the testing environment are crucial to be matched in the training environment. In the present study, we examined training specificity in time and distance estimation tasks that differed only in the focus of processing (FOP). External spatial cues were provided for the distance estimation task and for the time estimation task in one condition, but not in another. The presence of a concurrent alphabet secondary task was manipulated during training and testing in all estimation conditions in Experiment 1. For distance as well as for time estimation in both conditions, training of the primary estimation task was found to be specific to the presence of the secondary task. In Experiments 2 and 3, we examined transfer between one estimation task and another, with no secondary task in either case. When all conditions were equal aside from the FOP instructions, including the presence of external spatial cues, Experiment 2 showed "transfer" between tasks, suggesting that training might not be specific to the FOP. When the external spatial cues were removed from the time estimation task, Experiment 3 showed no transfer between time and distance estimations, suggesting that external task cues influenced the procedures used in the estimation tasks.

Maximum likelihood estimation of signal-to-noise ratio and combiner weight

NASA Technical Reports Server (NTRS)

Kalson, S.; Dolinar, S. J.

1986-01-01

An algorithm for estimating signal to noise ratio and combiner weight parameters for a discrete time series is presented. The algorithm is based upon the joint maximum likelihood estimate of the signal and noise power. The discrete-time series are the sufficient statistics obtained after matched filtering of a biphase modulated signal in additive white Gaussian noise, before maximum likelihood decoding is performed.

Integrating field plots, lidar, and landsat time series to provide temporally consistent annual estimates of biomass from 1990 to present

Treesearch

Warren B. Cohen; Hans-Erik Andersen; Sean P. Healey; Gretchen G. Moisen; Todd A. Schroeder; Christopher W. Woodall; Grant M. Domke; Zhiqiang Yang; Robert E. Kennedy; Stephen V. Stehman; Curtis Woodcock; Jim Vogelmann; Zhe Zhu; Chengquan Huang

2015-01-01

We are developing a system that provides temporally consistent biomass estimates for national greenhouse gas inventory reporting to the United Nations Framework Convention on Climate Change. Our model-assisted estimation framework relies on remote sensing to scale from plot measurements to lidar strip samples, to Landsat time series-based maps. As a demonstration, new...

Time synchronization of a frequency-hopped MFSK communication system

NASA Technical Reports Server (NTRS)

Simon, M. K.; Polydoros, A.; Huth, G. K.

1981-01-01

In a frequency-hopped (FH) multiple-frequency-shift-keyed (MFSK) communication system, frequency hopping causes the necessary frequency transitions for time synchronization estimation rather than the data sequence as in the conventional (nonfrequency-hopped) system. Making use of this observation, this paper presents a fine synchronization (i.e., time errors of less than a hop duration) technique for estimation of FH timing. The performance degradation due to imperfect FH time synchronization is found in terms of the effect on bit error probability as a function of full-band or partial-band noise jamming levels and of the number of hops used in the FH timing estimate.

A matlab framework for estimation of NLME models using stochastic differential equations: applications for estimation of insulin secretion rates.

PubMed

Mortensen, Stig B; Klim, Søren; Dammann, Bernd; Kristensen, Niels R; Madsen, Henrik; Overgaard, Rune V

2007-10-01

The non-linear mixed-effects model based on stochastic differential equations (SDEs) provides an attractive residual error model, that is able to handle serially correlated residuals typically arising from structural mis-specification of the true underlying model. The use of SDEs also opens up for new tools for model development and easily allows for tracking of unknown inputs and parameters over time. An algorithm for maximum likelihood estimation of the model has earlier been proposed, and the present paper presents the first general implementation of this algorithm. The implementation is done in Matlab and also demonstrates the use of parallel computing for improved estimation times. The use of the implementation is illustrated by two examples of application which focus on the ability of the model to estimate unknown inputs facilitated by the extension to SDEs. The first application is a deconvolution-type estimation of the insulin secretion rate based on a linear two-compartment model for C-peptide measurements. In the second application the model is extended to also give an estimate of the time varying liver extraction based on both C-peptide and insulin measurements.

Time concurrency/phase-time synchronization in digital communications networks

NASA Technical Reports Server (NTRS)

Kihara, Masami; Imaoka, Atsushi

1990-01-01

Digital communications networks have the intrinsic capability of time synchronization which makes it possible for networks to supply time signals to some applications and services. A practical estimation method for the time concurrency on terrestrial networks is presented. By using this method, time concurrency capability of the Nippon Telegraph and Telephone Corporation (NTT) digital communications network is estimated to be better than 300 ns rms at an advanced level, and 20 ns rms at final level.

Estimation of time averages from irregularly spaced observations - With application to coastal zone color scanner estimates of chlorophyll concentration

NASA Technical Reports Server (NTRS)

Chelton, Dudley B.; Schlax, Michael G.

1991-01-01

The sampling error of an arbitrary linear estimate of a time-averaged quantity constructed from a time series of irregularly spaced observations at a fixed located is quantified through a formalism. The method is applied to satellite observations of chlorophyll from the coastal zone color scanner. The two specific linear estimates under consideration are the composite average formed from the simple average of all observations within the averaging period and the optimal estimate formed by minimizing the mean squared error of the temporal average based on all the observations in the time series. The resulting suboptimal estimates are shown to be more accurate than composite averages. Suboptimal estimates are also found to be nearly as accurate as optimal estimates using the correct signal and measurement error variances and correlation functions for realistic ranges of these parameters, which makes it a viable practical alternative to the composite average method generally employed at present.

Near real-time estimation of the seismic source parameters in a compressed domain

NASA Astrophysics Data System (ADS)

Rodriguez, Ismael A. Vera

Seismic events can be characterized by its origin time, location and moment tensor. Fast estimations of these source parameters are important in areas of geophysics like earthquake seismology, and the monitoring of seismic activity produced by volcanoes, mining operations and hydraulic injections in geothermal and oil and gas reservoirs. Most available monitoring systems estimate the source parameters in a sequential procedure: first determining origin time and location (e.g., epicentre, hypocentre or centroid of the stress glut density), and then using this information to initialize the evaluation of the moment tensor. A more efficient estimation of the source parameters requires a concurrent evaluation of the three variables. The main objective of the present thesis is to address the simultaneous estimation of origin time, location and moment tensor of seismic events. The proposed method displays the benefits of being: 1) automatic, 2) continuous and, depending on the scale of application, 3) of providing results in real-time or near real-time. The inversion algorithm is based on theoretical results from sparse representation theory and compressive sensing. The feasibility of implementation is determined through the analysis of synthetic and real data examples. The numerical experiments focus on the microseismic monitoring of hydraulic fractures in oil and gas wells, however, an example using real earthquake data is also presented for validation. The thesis is complemented with a resolvability analysis of the moment tensor. The analysis targets common monitoring geometries employed in hydraulic fracturing in oil wells. Additionally, it is presented an application of sparse representation theory for the denoising of one-component and three-component microseismicity records, and an algorithm for improved automatic time-picking using non-linear inversion constraints.

A method for the estimation of the significance of cross-correlations in unevenly sampled red-noise time series

NASA Astrophysics Data System (ADS)

Max-Moerbeck, W.; Richards, J. L.; Hovatta, T.; Pavlidou, V.; Pearson, T. J.; Readhead, A. C. S.

2014-11-01

We present a practical implementation of a Monte Carlo method to estimate the significance of cross-correlations in unevenly sampled time series of data, whose statistical properties are modelled with a simple power-law power spectral density. This implementation builds on published methods; we introduce a number of improvements in the normalization of the cross-correlation function estimate and a bootstrap method for estimating the significance of the cross-correlations. A closely related matter is the estimation of a model for the light curves, which is critical for the significance estimates. We present a graphical and quantitative demonstration that uses simulations to show how common it is to get high cross-correlations for unrelated light curves with steep power spectral densities. This demonstration highlights the dangers of interpreting them as signs of a physical connection. We show that by using interpolation and the Hanning sampling window function we are able to reduce the effects of red-noise leakage and to recover steep simple power-law power spectral densities. We also introduce the use of a Neyman construction for the estimation of the errors in the power-law index of the power spectral density. This method provides a consistent way to estimate the significance of cross-correlations in unevenly sampled time series of data.

Accuracy and Precision of USNO GPS Carrier-Phase Time Transfer

DTIC Science & Technology

2010-01-01

values. Comparison measures used include estimates obtained from two-way satellite time/frequency transfer ( TWSTFT ), and GPS-based estimates obtained...the IGS are used as a benchmark in the computation. Frequency values have a few times 10 -15 fractional frequency uncertainty. TWSTFT values confirm...obtained from two-way satellite time/frequency transfer ( TWSTFT ), BIPM Circular T, and the International GNSS Service (IGS). At present, it is known that

Mapping the Origins of Time: Scalar Errors in Infant Time Estimation

ERIC Educational Resources Information Center

Addyman, Caspar; Rocha, Sinead; Mareschal, Denis

2014-01-01

Time is central to any understanding of the world. In adults, estimation errors grow linearly with the length of the interval, much faster than would be expected of a clock-like mechanism. Here we present the first direct demonstration that this is also true in human infants. Using an eye-tracking paradigm, we examined 4-, 6-, 10-, and…

Bounded Linear Stability Analysis - A Time Delay Margin Estimation Approach for Adaptive Control

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.; Ishihara, Abraham K.; Krishnakumar, Kalmanje Srinlvas; Bakhtiari-Nejad, Maryam

2009-01-01

This paper presents a method for estimating time delay margin for model-reference adaptive control of systems with almost linear structured uncertainty. The bounded linear stability analysis method seeks to represent the conventional model-reference adaptive law by a locally bounded linear approximation within a small time window using the comparison lemma. The locally bounded linear approximation of the combined adaptive system is cast in a form of an input-time-delay differential equation over a small time window. The time delay margin of this system represents a local stability measure and is computed analytically by a matrix measure method, which provides a simple analytical technique for estimating an upper bound of time delay margin. Based on simulation results for a scalar model-reference adaptive control system, both the bounded linear stability method and the matrix measure method are seen to provide a reasonably accurate and yet not too conservative time delay margin estimation.

A novel approach to estimation of the time to biomarker threshold: applications to HIV.

PubMed

Reddy, Tarylee; Molenberghs, Geert; Njagi, Edmund Njeru; Aerts, Marc

2016-11-01

In longitudinal studies of biomarkers, an outcome of interest is the time at which a biomarker reaches a particular threshold. The CD4 count is a widely used marker of human immunodeficiency virus progression. Because of the inherent variability of this marker, a single CD4 count below a relevant threshold should be interpreted with caution. Several studies have applied persistence criteria, designating the outcome as the time to the occurrence of two consecutive measurements less than the threshold. In this paper, we propose a method to estimate the time to attainment of two consecutive CD4 counts less than a meaningful threshold, which takes into account the patient-specific trajectory and measurement error. An expression for the expected time to threshold is presented, which is a function of the fixed effects, random effects and residual variance. We present an application to human immunodeficiency virus-positive individuals from a seroprevalent cohort in Durban, South Africa. Two thresholds are examined, and 95% bootstrap confidence intervals are presented for the estimated time to threshold. Sensitivity analysis revealed that results are robust to truncation of the series and variation in the number of visits considered for most patients. Caution should be exercised when interpreting the estimated times for patients who exhibit very slow rates of decline and patients who have less than three measurements. We also discuss the relevance of the methodology to the study of other diseases and present such applications. We demonstrate that the method proposed is computationally efficient and offers more flexibility than existing frameworks. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

A time-lapse photography method for monitoring salmon (Oncorhynchus spp.) passage and abundance in streams

PubMed Central

Leacock, William B.; Eby, Lisa A.; Stanford, Jack A.

2016-01-01

Accurately estimating population sizes is often a critical component of fisheries research and management. Although there is a growing appreciation of the importance of small-scale salmon population dynamics to the stability of salmon stock-complexes, our understanding of these populations is constrained by a lack of efficient and cost-effective monitoring tools for streams. Weirs are expensive, labor intensive, and can disrupt natural fish movements. While conventional video systems avoid some of these shortcomings, they are expensive and require excessive amounts of labor to review footage for data collection. Here, we present a novel method for quantifying salmon in small streams (<15 m wide, <1 m deep) that uses both time-lapse photography and video in a model-based double sampling scheme. This method produces an escapement estimate nearly as accurate as a video-only approach, but with substantially less labor, money, and effort. It requires servicing only every 14 days, detects salmon 24 h/day, is inexpensive, and produces escapement estimates with confidence intervals. In addition to escapement estimation, we present a method for estimating in-stream salmon abundance across time, data needed by researchers interested in predator--prey interactions or nutrient subsidies. We combined daily salmon passage estimates with stream specific estimates of daily mortality developed using previously published data. To demonstrate proof of concept for these methods, we present results from two streams in southwest Kodiak Island, Alaska in which high densities of sockeye salmon spawn. PMID:27326378

Estimating equations estimates of trends

USGS Publications Warehouse

Link, W.A.; Sauer, J.R.

1994-01-01

The North American Breeding Bird Survey monitors changes in bird populations through time using annual counts at fixed survey sites. The usual method of estimating trends has been to use the logarithm of the counts in a regression analysis. It is contended that this procedure is reasonably satisfactory for more abundant species, but produces biased estimates for less abundant species. An alternative estimation procedure based on estimating equations is presented.

Summary of methods for calculating dynamic lateral stability and response and for estimating aerodynamic stability derivatives

NASA Technical Reports Server (NTRS)

Campbell, John P; Mckinney, Marion O

1952-01-01

A summary of methods for making dynamic lateral stability and response calculations and for estimating the aerodynamic stability derivatives required for use in these calculations is presented. The processes of performing calculations of the time histories of lateral motions, of the period and damping of these motions, and of the lateral stability boundaries are presented as a series of simple straightforward steps. Existing methods for estimating the stability derivatives are summarized and, in some cases, simple new empirical formulas are presented. Detailed estimation methods are presented for low-subsonic-speed conditions but only a brief discussion and a list of references are given for transonic and supersonic speed conditions.

Economic productivity by age and sex: 2007 estimates for the United States.

PubMed

Grosse, Scott D; Krueger, Kurt V; Mvundura, Mercy

2009-07-01

Human capital estimates of labor productivity are often used to estimate the economic impact of diseases and injuries that cause incapacitation or death. Estimates of average hourly, annual, and lifetime economic productivity, both market and household, were calculated in 2007 US dollars for 5-year age groups for men, women, and both sexes in the United States. Data from the American Time Use Survey were used to estimate hours of paid work and household services and hourly and annual earnings and household productivity. Present values of discounted lifetime earnings were calculated for each age group using the 2004 US life tables and a discount rate of 3% per year and assuming future productivity growth of 1% per year. The estimates of hours and productivity were calculated using the time diaries of 72,922 persons included in the American Time Use Survey for the years 2003 to 2007. The present value of lifetime productivity is approximately $1.2 million in 2007 dollars for children under 5 years of age. For adults in their 20s and 30s, it is approximately $1.6 million and then it declines with increasing age. Productivity estimates are higher for males than for females, more for market productivity than for total productivity. Changes in hours of paid employment and household services can affect economic productivity by age and sex. This is the first publication to include estimates of household services based on contemporary time use data for the US population.

Estimation of octanol/water partition coefficient and aqueous solubility of environmental chemicals using molecular fingerprints and machine learning methods

EPA Science Inventory

Octanol/water partition coefficient (logP) and aqueous solubility (logS) are two important parameters in pharmacology and toxicology studies, and experimental measurements are usually time-consuming and expensive. In the present research, novel methods are presented for the estim...

Real-Time Frequency Response Estimation Using Joined-Wing SensorCraft Aeroelastic Wind-Tunnel Data

NASA Technical Reports Server (NTRS)

Grauer, Jared A; Heeg, Jennifer; Morelli, Eugene A

2012-01-01

A new method is presented for estimating frequency responses and their uncertainties from wind-tunnel data in real time. The method uses orthogonal phase-optimized multi- sine excitation inputs and a recursive Fourier transform with a least-squares estimator. The method was first demonstrated with an F-16 nonlinear flight simulation and results showed that accurate short period frequency responses were obtained within 10 seconds. The method was then applied to wind-tunnel data from a previous aeroelastic test of the Joined- Wing SensorCraft. Frequency responses describing bending strains from simultaneous control surface excitations were estimated in a time-efficient manner.

Influence of hypo- and hyperthermia on death time estimation - A simulation study.

PubMed

Muggenthaler, H; Hubig, M; Schenkl, S; Mall, G

2017-09-01

Numerous physiological and pathological mechanisms can cause elevated or lowered body core temperatures. Deviations from the physiological level of about 37°C can influence temperature based death time estimations. However, it has not been investigated by means of thermodynamics, to which extent hypo- and hyperthermia bias death time estimates. Using numerical simulation, the present study investigates the errors inherent in temperature based death time estimation in case of elevated or lowered body core temperatures before death. The most considerable errors with regard to the normothermic model occur in the first few hours post-mortem. With decreasing body core temperature and increasing post-mortem time the error diminishes and stagnates at a nearly constant level. Copyright © 2017 Elsevier B.V. All rights reserved.

The estimation error covariance matrix for the ideal state reconstructor with measurement noise

NASA Technical Reports Server (NTRS)

Polites, Michael E.

1988-01-01

A general expression is derived for the state estimation error covariance matrix for the Ideal State Reconstructor when the input measurements are corrupted by measurement noise. An example is presented which shows that the more measurements used in estimating the state at a given time, the better the estimator.

Retrospective cost-effectiveness analyses for polio vaccination in the United States.

PubMed

Thompson, Kimberly M; Tebbens, Radboud J Duintjer

2006-12-01

The history of polio vaccination in the United States spans 50 years and includes different phases of the disease, multiple vaccines, and a sustained significant commitment of resources. We estimated cost-effectiveness ratios and assessed the net benefits of polio vaccination applicable at various points in time from the societal perspective and we discounted these back to appropriate points in time. We reconstructed vaccine price data from available sources and used these to retrospectively estimate the total costs of the U.S. historical polio vaccination strategies (all costs reported in year 2002 dollars). We estimate that the United States invested approximately US dollars 35 billion (1955 net present value, discount rate of 3%) in polio vaccines between 1955 and 2005 and will invest approximately US dollars 1.4 billion (1955 net present value, or US dollars 6.3 billion in 2006 net present value) between 2006 and 2015 assuming a policy of continued use of inactivated poliovirus vaccine (IPV) for routine vaccination. The historical and future investments translate into over 1.7 billion vaccinations that prevent approximately 1.1 million cases of paralytic polio and over 160,000 deaths (1955 net present values of approximately 480,000 cases and 73,000 deaths). Due to treatment cost savings, the investment implies net benefits of approximately US dollars 180 billion (1955 net present value), even without incorporating the intangible costs of suffering and death and of averted fear. Retrospectively, the U.S. investment in polio vaccination represents a highly valuable, cost-saving public health program. Observed changes in the cost-effectiveness ratio estimates over time suggest the need for living economic models for interventions that appropriately change with time. This article also demonstrates that estimates of cost-effectiveness ratios at any single time point may fail to adequately consider the context of the investment made to date and the importance of population and other dynamics, and shows the importance of dynamic modeling.

On the estimation of intracluster correlation for time-to-event outcomes in cluster randomized trials.

PubMed

Kalia, Sumeet; Klar, Neil; Donner, Allan

2016-12-30

Cluster randomized trials (CRTs) involve the random assignment of intact social units rather than independent subjects to intervention groups. Time-to-event outcomes often are endpoints in CRTs. Analyses of such data need to account for the correlation among cluster members. The intracluster correlation coefficient (ICC) is used to assess the similarity among binary and continuous outcomes that belong to the same cluster. However, estimating the ICC in CRTs with time-to-event outcomes is a challenge because of the presence of censored observations. The literature suggests that the ICC may be estimated using either censoring indicators or observed event times. A simulation study explores the effect of administrative censoring on estimating the ICC. Results show that ICC estimators derived from censoring indicators or observed event times are negatively biased. Analytic work further supports these results. Observed event times are preferred to estimate the ICC under minimum frequency of administrative censoring. To our knowledge, the existing literature provides no practical guidance on the estimation of ICC when substantial amount of administrative censoring is present. The results from this study corroborate the need for further methodological research on estimating the ICC for correlated time-to-event outcomes. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Comparison study on disturbance estimation techniques in precise slow motion control

NASA Astrophysics Data System (ADS)

Fan, S.; Nagamune, R.; Altintas, Y.; Fan, D.; Zhang, Z.

2010-08-01

Precise low speed motion control is important for the industrial applications of both micro-milling machine tool feed drives and electro-optical tracking servo systems. It calls for precise position and instantaneous velocity measurement and disturbance, which involves direct drive motor force ripple, guide way friction and cutting force etc., estimation. This paper presents a comparison study on dynamic response and noise rejection performance of three existing disturbance estimation techniques, including the time-delayed estimators, the state augmented Kalman Filters and the conventional disturbance observers. The design technique essentials of these three disturbance estimators are introduced. For designing time-delayed estimators, it is proposed to substitute Kalman Filter for Luenberger state observer to improve noise suppression performance. The results show that the noise rejection performances of the state augmented Kalman Filters and the time-delayed estimators are much better than the conventional disturbance observers. These two estimators can give not only the estimation of the disturbance but also the low noise level estimations of position and instantaneous velocity. The bandwidth of the state augmented Kalman Filters is wider than the time-delayed estimators. In addition, the state augmented Kalman Filters can give unbiased estimations of the slow varying disturbance and the instantaneous velocity, while the time-delayed estimators can not. The simulation and experiment conducted on X axis of a 2.5-axis prototype micro milling machine are provided.

The Value Estimation of an HFGW Frequency Time Standard for Telecommunications Network Optimization

NASA Astrophysics Data System (ADS)

Harper, Colby; Stephenson, Gary

2007-01-01

The emerging technology of gravitational wave control is used to augment a communication system using a development roadmap suggested in Stephenson (2003) for applications emphasized in Baker (2005). In the present paper consideration is given to the value of a High Frequency Gravitational Wave (HFGW) channel purely as providing a method of frequency and time reference distribution for use within conventional Radio Frequency (RF) telecommunications networks. Specifically, the native value of conventional telecommunications networks may be optimized by using an unperturbed frequency time standard (FTS) to (1) improve terminal navigation and Doppler estimation performance via improved time difference of arrival (TDOA) from a universal time reference, and (2) improve acquisition speed, coding efficiency, and dynamic bandwidth efficiency through the use of a universal frequency reference. A model utilizing a discounted cash flow technique provides an estimation of the additional value using HFGW FTS technology could bring to a mixed technology HFGW/RF network. By applying a simple net present value analysis with supporting reference valuations to such a network, it is demonstrated that an HFGW FTS could create a sizable improvement within an otherwise conventional RF telecommunications network. Our conservative model establishes a low-side value estimate of approximately 50B USD Net Present Value for an HFGW FTS service, with reasonable potential high-side values to significant multiples of this low-side value floor.

A novel recursive Fourier transform for nonuniform sampled signals: application to heart rate variability spectrum estimation.

PubMed

Holland, Alexander; Aboy, Mateo

2009-07-01

We present a novel method to iteratively calculate discrete Fourier transforms for discrete time signals with sample time intervals that may be widely nonuniform. The proposed recursive Fourier transform (RFT) does not require interpolation of the samples to uniform time intervals, and each iterative transform update of N frequencies has computational order N. Because of the inherent non-uniformity in the time between successive heart beats, an application particularly well suited for this transform is power spectral density (PSD) estimation for heart rate variability. We compare RFT based spectrum estimation with Lomb-Scargle Transform (LST) based estimation. PSD estimation based on the LST also does not require uniform time samples, but the LST has a computational order greater than Nlog(N). We conducted an assessment study involving the analysis of quasi-stationary signals with various levels of randomly missing heart beats. Our results indicate that the RFT leads to comparable estimation performance to the LST with significantly less computational overhead and complexity for applications requiring iterative spectrum estimations.

Efficient multidimensional regularization for Volterra series estimation

NASA Astrophysics Data System (ADS)

Birpoutsoukis, Georgios; Csurcsia, Péter Zoltán; Schoukens, Johan

2018-05-01

This paper presents an efficient nonparametric time domain nonlinear system identification method. It is shown how truncated Volterra series models can be efficiently estimated without the need of long, transient-free measurements. The method is a novel extension of the regularization methods that have been developed for impulse response estimates of linear time invariant systems. To avoid the excessive memory needs in case of long measurements or large number of estimated parameters, a practical gradient-based estimation method is also provided, leading to the same numerical results as the proposed Volterra estimation method. Moreover, the transient effects in the simulated output are removed by a special regularization method based on the novel ideas of transient removal for Linear Time-Varying (LTV) systems. Combining the proposed methodologies, the nonparametric Volterra models of the cascaded water tanks benchmark are presented in this paper. The results for different scenarios varying from a simple Finite Impulse Response (FIR) model to a 3rd degree Volterra series with and without transient removal are compared and studied. It is clear that the obtained models capture the system dynamics when tested on a validation dataset, and their performance is comparable with the white-box (physical) models.

Temperature and relative humidity estimation and prediction in the tobacco drying process using Artificial Neural Networks.

PubMed

Martínez-Martínez, Víctor; Baladrón, Carlos; Gomez-Gil, Jaime; Ruiz-Ruiz, Gonzalo; Navas-Gracia, Luis M; Aguiar, Javier M; Carro, Belén

2012-10-17

This paper presents a system based on an Artificial Neural Network (ANN) for estimating and predicting environmental variables related to tobacco drying processes. This system has been validated with temperature and relative humidity data obtained from a real tobacco dryer with a Wireless Sensor Network (WSN). A fitting ANN was used to estimate temperature and relative humidity in different locations inside the tobacco dryer and to predict them with different time horizons. An error under 2% can be achieved when estimating temperature as a function of temperature and relative humidity in other locations. Moreover, an error around 1.5 times lower than that obtained with an interpolation method can be achieved when predicting the temperature inside the tobacco mass as a function of its present and past values with time horizons over 150 minutes. These results show that the tobacco drying process can be improved taking into account the predicted future value of the monitored variables and the estimated actual value of other variables using a fitting ANN as proposed.

Temperature and Relative Humidity Estimation and Prediction in the Tobacco Drying Process Using Artificial Neural Networks

PubMed Central

Martínez-Martínez, Víctor; Baladrón, Carlos; Gomez-Gil, Jaime; Ruiz-Ruiz, Gonzalo; Navas-Gracia, Luis M.; Aguiar, Javier M.; Carro, Belén

2012-01-01

This paper presents a system based on an Artificial Neural Network (ANN) for estimating and predicting environmental variables related to tobacco drying processes. This system has been validated with temperature and relative humidity data obtained from a real tobacco dryer with a Wireless Sensor Network (WSN). A fitting ANN was used to estimate temperature and relative humidity in different locations inside the tobacco dryer and to predict them with different time horizons. An error under 2% can be achieved when estimating temperature as a function of temperature and relative humidity in other locations. Moreover, an error around 1.5 times lower than that obtained with an interpolation method can be achieved when predicting the temperature inside the tobacco mass as a function of its present and past values with time horizons over 150 minutes. These results show that the tobacco drying process can be improved taking into account the predicted future value of the monitored variables and the estimated actual value of other variables using a fitting ANN as proposed. PMID:23202032

Theoretical Foundation of the RelTime Method for Estimating Divergence Times from Variable Evolutionary Rates

PubMed Central

Tamura, Koichiro; Tao, Qiqing; Kumar, Sudhir

2018-01-01

Abstract RelTime estimates divergence times by relaxing the assumption of a strict molecular clock in a phylogeny. It shows excellent performance in estimating divergence times for both simulated and empirical molecular sequence data sets in which evolutionary rates varied extensively throughout the tree. RelTime is computationally efficient and scales well with increasing size of data sets. Until now, however, RelTime has not had a formal mathematical foundation. Here, we show that the basis of the RelTime approach is a relative rate framework (RRF) that combines comparisons of evolutionary rates in sister lineages with the principle of minimum rate change between evolutionary lineages and their respective descendants. We present analytical solutions for estimating relative lineage rates and divergence times under RRF. We also discuss the relationship of RRF with other approaches, including the Bayesian framework. We conclude that RelTime will be useful for phylogenies with branch lengths derived not only from molecular data, but also morphological and biochemical traits. PMID:29893954

Improved analysis of ground vibrations produced by man-made sources.

PubMed

Ainalis, Daniel; Ducarne, Loïc; Kaufmann, Olivier; Tshibangu, Jean-Pierre; Verlinden, Olivier; Kouroussis, Georges

2018-03-01

Man-made sources of ground vibration must be carefully monitored in urban areas in order to ensure that structural damage and discomfort to residents is prevented or minimised. The research presented in this paper provides a comparative evaluation of various methods used to analyse a series of tri-axial ground vibration measurements generated by rail, road, and explosive blasting. The first part of the study is focused on comparing various techniques to estimate the dominant frequency, including time-frequency analysis. The comparative evaluation of the various methods to estimate the dominant frequency revealed that, depending on the method used, there can be significant variation in the estimates obtained. A new and improved analysis approach using the continuous wavelet transform was also presented, using the time-frequency distribution to estimate the localised dominant frequency and peak particle velocity. The technique can be used to accurately identify the level and frequency content of a ground vibration signal as it varies with time, and identify the number of times the threshold limits of damage are exceeded. Copyright © 2017 Elsevier B.V. All rights reserved.

Longitudinal Mediation Analysis with Time-varying Mediators and Exposures, with Application to Survival Outcomes

PubMed Central

Zheng, Wenjing; van der Laan, Mark

2017-01-01

In this paper, we study the effect of a time-varying exposure mediated by a time-varying intermediate variable. We consider general longitudinal settings, including survival outcomes. At a given time point, the exposure and mediator of interest are influenced by past covariates, mediators and exposures, and affect future covariates, mediators and exposures. Right censoring, if present, occurs in response to past history. To address the challenges in mediation analysis that are unique to these settings, we propose a formulation in terms of random interventions based on conditional distributions for the mediator. This formulation, in particular, allows for well-defined natural direct and indirect effects in the survival setting, and natural decomposition of the standard total effect. Upon establishing identifiability and the corresponding statistical estimands, we derive the efficient influence curves and establish their robustness properties. Applying Targeted Maximum Likelihood Estimation, we use these efficient influence curves to construct multiply robust and efficient estimators. We also present an inverse probability weighted estimator and a nested non-targeted substitution estimator for these parameters. PMID:29387520

Analysis models for the estimation of oceanic fields

NASA Technical Reports Server (NTRS)

Carter, E. F.; Robinson, A. R.

1987-01-01

A general model for statistically optimal estimates is presented for dealing with scalar, vector and multivariate datasets. The method deals with anisotropic fields and treats space and time dependence equivalently. Problems addressed include the analysis, or the production of synoptic time series of regularly gridded fields from irregular and gappy datasets, and the estimate of fields by compositing observations from several different instruments and sampling schemes. Technical issues are discussed, including the convergence of statistical estimates, the choice of representation of the correlations, the influential domain of an observation, and the efficiency of numerical computations.

A Geomagnetic Estimate of Mean Paleointensity

NASA Technical Reports Server (NTRS)

Voorhies, Coerte V.

2004-01-01

To test a statistical hypothesis about Earth's magnetic field against paleomagnetism, the present field is used to estimate time averaged paleointensity. The estimate used the modern magnetic multipole spectrum R(n), which gives the mean square induction represented by spherical harmonics of degree n averaged over the sphere of radius a = 6371.2 km. The hypothesis asserts that low degree multi-pole powers of the coresource field are distributed as chi-squared with 2n+1 degrees of freedom and expectation values, where c is the 3480 km radius of the Earth's core. (This is compatible with a usually mainly geocentric axial dipolar field). Amplitude K is estimated by fitting theoretical to observational spectra through degree 12. The resulting calibrated expectation spectrum is summed through degree 12 to estimate expected square intensity F(exp 2). The sum also estimates F(exp 2) averaged over geologic time, in so far as the present magnetic spectrum is a fair sample of that generated in the past by core geodynamic processes. Additional information is included in the original extended abstract.

19 CFR 132.12 - Procedure on opening of potentially filled quotas.

Code of Federal Regulations, 2010 CFR

2010-04-01

... consumption, with estimated duties attached, shall not be presented before 12 noon Eastern Standard Time in all time zones. However, an entry summary for consumption, or withdrawal for consumption, for... exact moment of the opening of the quota in all time zones. All importers prepared to present entry...

Estimation of excitation forces for wave energy converters control using pressure measurements

NASA Astrophysics Data System (ADS)

Abdelkhalik, O.; Zou, S.; Robinett, R.; Bacelli, G.; Wilson, D.

2017-08-01

Most control algorithms of wave energy converters require prediction of wave elevation or excitation force for a short future horizon, to compute the control in an optimal sense. This paper presents an approach that requires the estimation of the excitation force and its derivatives at present time with no need for prediction. An extended Kalman filter is implemented to estimate the excitation force. The measurements in this approach are selected to be the pressures at discrete points on the buoy surface, in addition to the buoy heave position. The pressures on the buoy surface are more directly related to the excitation force on the buoy as opposed to wave elevation in front of the buoy. These pressure measurements are also more accurate and easier to obtain. A singular arc control is implemented to compute the steady-state control using the estimated excitation force. The estimated excitation force is expressed in the Laplace domain and substituted in the control, before the latter is transformed to the time domain. Numerical simulations are presented for a Bretschneider wave case study.

Output-only modal parameter estimator of linear time-varying structural systems based on vector TAR model and least squares support vector machine

NASA Astrophysics Data System (ADS)

Zhou, Si-Da; Ma, Yuan-Chen; Liu, Li; Kang, Jie; Ma, Zhi-Sai; Yu, Lei

2018-01-01

Identification of time-varying modal parameters contributes to the structural health monitoring, fault detection, vibration control, etc. of the operational time-varying structural systems. However, it is a challenging task because there is not more information for the identification of the time-varying systems than that of the time-invariant systems. This paper presents a vector time-dependent autoregressive model and least squares support vector machine based modal parameter estimator for linear time-varying structural systems in case of output-only measurements. To reduce the computational cost, a Wendland's compactly supported radial basis function is used to achieve the sparsity of the Gram matrix. A Gamma-test-based non-parametric approach of selecting the regularization factor is adapted for the proposed estimator to replace the time-consuming n-fold cross validation. A series of numerical examples have illustrated the advantages of the proposed modal parameter estimator on the suppression of the overestimate and the short data. A laboratory experiment has further validated the proposed estimator.

Development and application of a modified dynamic time warping algorithm (DTW-S) to analyses of primate brain expression time series

PubMed Central

2011-01-01

Background Comparing biological time series data across different conditions, or different specimens, is a common but still challenging task. Algorithms aligning two time series represent a valuable tool for such comparisons. While many powerful computation tools for time series alignment have been developed, they do not provide significance estimates for time shift measurements. Results Here, we present an extended version of the original DTW algorithm that allows us to determine the significance of time shift estimates in time series alignments, the DTW-Significance (DTW-S) algorithm. The DTW-S combines important properties of the original algorithm and other published time series alignment tools: DTW-S calculates the optimal alignment for each time point of each gene, it uses interpolated time points for time shift estimation, and it does not require alignment of the time-series end points. As a new feature, we implement a simulation procedure based on parameters estimated from real time series data, on a series-by-series basis, allowing us to determine the false positive rate (FPR) and the significance of the estimated time shift values. We assess the performance of our method using simulation data and real expression time series from two published primate brain expression datasets. Our results show that this method can provide accurate and robust time shift estimates for each time point on a gene-by-gene basis. Using these estimates, we are able to uncover novel features of the biological processes underlying human brain development and maturation. Conclusions The DTW-S provides a convenient tool for calculating accurate and robust time shift estimates at each time point for each gene, based on time series data. The estimates can be used to uncover novel biological features of the system being studied. The DTW-S is freely available as an R package TimeShift at http://www.picb.ac.cn/Comparative/data.html. PMID:21851598

Development and application of a modified dynamic time warping algorithm (DTW-S) to analyses of primate brain expression time series.

PubMed

Yuan, Yuan; Chen, Yi-Ping Phoebe; Ni, Shengyu; Xu, Augix Guohua; Tang, Lin; Vingron, Martin; Somel, Mehmet; Khaitovich, Philipp

2011-08-18

Comparing biological time series data across different conditions, or different specimens, is a common but still challenging task. Algorithms aligning two time series represent a valuable tool for such comparisons. While many powerful computation tools for time series alignment have been developed, they do not provide significance estimates for time shift measurements. Here, we present an extended version of the original DTW algorithm that allows us to determine the significance of time shift estimates in time series alignments, the DTW-Significance (DTW-S) algorithm. The DTW-S combines important properties of the original algorithm and other published time series alignment tools: DTW-S calculates the optimal alignment for each time point of each gene, it uses interpolated time points for time shift estimation, and it does not require alignment of the time-series end points. As a new feature, we implement a simulation procedure based on parameters estimated from real time series data, on a series-by-series basis, allowing us to determine the false positive rate (FPR) and the significance of the estimated time shift values. We assess the performance of our method using simulation data and real expression time series from two published primate brain expression datasets. Our results show that this method can provide accurate and robust time shift estimates for each time point on a gene-by-gene basis. Using these estimates, we are able to uncover novel features of the biological processes underlying human brain development and maturation. The DTW-S provides a convenient tool for calculating accurate and robust time shift estimates at each time point for each gene, based on time series data. The estimates can be used to uncover novel biological features of the system being studied. The DTW-S is freely available as an R package TimeShift at http://www.picb.ac.cn/Comparative/data.html.

Methodology for time-domain estimation of storm time geoelectric fields using the 3-D magnetotelluric response tensors

USGS Publications Warehouse

Kelbert, Anna; Balch, Christopher; Pulkkinen, Antti; Egbert, Gary D; Love, Jeffrey J.; Rigler, E. Joshua; Fujii, Ikuko

2017-01-01

Geoelectric fields at the Earth's surface caused by magnetic storms constitute a hazard to the operation of electric power grids and related infrastructure. The ability to estimate these geoelectric fields in close to real time and provide local predictions would better equip the industry to mitigate negative impacts on their operations. Here we report progress toward this goal: development of robust algorithms that convolve a magnetic storm time series with a frequency domain impedance for a realistic three-dimensional (3-D) Earth, to estimate the local, storm time geoelectric field. Both frequency domain and time domain approaches are presented and validated against storm time geoelectric field data measured in Japan. The methods are then compared in the context of a real-time application.

Methodology for time-domain estimation of storm time geoelectric fields using the 3-D magnetotelluric response tensors

NASA Astrophysics Data System (ADS)

Kelbert, Anna; Balch, Christopher C.; Pulkkinen, Antti; Egbert, Gary D.; Love, Jeffrey J.; Rigler, E. Joshua; Fujii, Ikuko

2017-07-01

Geoelectric fields at the Earth's surface caused by magnetic storms constitute a hazard to the operation of electric power grids and related infrastructure. The ability to estimate these geoelectric fields in close to real time and provide local predictions would better equip the industry to mitigate negative impacts on their operations. Here we report progress toward this goal: development of robust algorithms that convolve a magnetic storm time series with a frequency domain impedance for a realistic three-dimensional (3-D) Earth, to estimate the local, storm time geoelectric field. Both frequency domain and time domain approaches are presented and validated against storm time geoelectric field data measured in Japan. The methods are then compared in the context of a real-time application.

Interval Timing Deficits Assessed by Time Reproduction Dual Tasks as Cognitive Endophenotypes for Attention-Deficit/Hyperactivity Disorder

PubMed Central

Hwang-Gu, Shoou-Lian; Gau, Susan Shur-Fen

2015-01-01

The literature has suggested timing processing as a potential endophenotype for attention deficit/hyperactivity disorder (ADHD); however, whether the subjective internal clock speed presented by verbal estimation and limited attention capacity presented by time reproduction could be endophenotypes for ADHD is still unknown. We assessed 223 youths with DSM-IV ADHD (age range: 10-17 years), 105 unaffected siblings, and 84 typically developing (TD) youths using psychiatric interviews, intelligence tests, verbal estimation and time reproduction tasks (single task and simple and difficult dual tasks) at 5-second, 12-second, and 17-second intervals. We found that youths with ADHD tended to overestimate time in verbal estimation more than their unaffected siblings and TD youths, implying that fast subjective internal clock speed might be a characteristic of ADHD, rather than an endophenotype for ADHD. Youths with ADHD and their unaffected siblings were less precise in time reproduction dual tasks than TD youths. The magnitude of estimated errors in time reproduction was greater in youths with ADHD and their unaffected siblings than in TD youths, with an increased time interval at the 17-second interval and with increased task demands on both simple and difficult dual tasks versus the single task. Increased impaired time reproduction in dual tasks with increased intervals and task demands were shown in youths with ADHD and their unaffected siblings, suggesting that time reproduction deficits explained by limited attention capacity might be a useful endophenotype of ADHD. PMID:25992899

A stochastic estimation procedure for intermittently-observed semi-Markov multistate models with back transitions.

PubMed

Aralis, Hilary; Brookmeyer, Ron

2017-01-01

Multistate models provide an important method for analyzing a wide range of life history processes including disease progression and patient recovery following medical intervention. Panel data consisting of the states occupied by an individual at a series of discrete time points are often used to estimate transition intensities of the underlying continuous-time process. When transition intensities depend on the time elapsed in the current state and back transitions between states are possible, this intermittent observation process presents difficulties in estimation due to intractability of the likelihood function. In this manuscript, we present an iterative stochastic expectation-maximization algorithm that relies on a simulation-based approximation to the likelihood function and implement this algorithm using rejection sampling. In a simulation study, we demonstrate the feasibility and performance of the proposed procedure. We then demonstrate application of the algorithm to a study of dementia, the Nun Study, consisting of intermittently-observed elderly subjects in one of four possible states corresponding to intact cognition, impaired cognition, dementia, and death. We show that the proposed stochastic expectation-maximization algorithm substantially reduces bias in model parameter estimates compared to an alternative approach used in the literature, minimal path estimation. We conclude that in estimating intermittently observed semi-Markov models, the proposed approach is a computationally feasible and accurate estimation procedure that leads to substantial improvements in back transition estimates.

Autoregressive-model-based missing value estimation for DNA microarray time series data.

PubMed

Choong, Miew Keen; Charbit, Maurice; Yan, Hong

2009-01-01

Missing value estimation is important in DNA microarray data analysis. A number of algorithms have been developed to solve this problem, but they have several limitations. Most existing algorithms are not able to deal with the situation where a particular time point (column) of the data is missing entirely. In this paper, we present an autoregressive-model-based missing value estimation method (ARLSimpute) that takes into account the dynamic property of microarray temporal data and the local similarity structures in the data. ARLSimpute is especially effective for the situation where a particular time point contains many missing values or where the entire time point is missing. Experiment results suggest that our proposed algorithm is an accurate missing value estimator in comparison with other imputation methods on simulated as well as real microarray time series datasets.

Finite-error metrological bounds on multiparameter Hamiltonian estimation

NASA Astrophysics Data System (ADS)

Kura, Naoto; Ueda, Masahito

2018-01-01

Estimation of multiple parameters in an unknown Hamiltonian is investigated. We present upper and lower bounds on the time required to complete the estimation within a prescribed error tolerance δ . The lower bound is given on the basis of the Cramér-Rao inequality, where the quantum Fisher information is bounded by the squared evolution time. The upper bound is obtained by an explicit construction of estimation procedures. By comparing the cases with different numbers of Hamiltonian channels, we also find that the few-channel procedure with adaptive feedback and the many-channel procedure with entanglement are equivalent in the sense that they require the same amount of time resource up to a constant factor.

Data-Rate Estimation for Autonomous Receiver Operation

NASA Technical Reports Server (NTRS)

Tkacenko, A.; Simon, M. K.

2005-01-01

In this article, we present a series of algorithms for estimating the data rate of a signal whose admissible data rates are integer base, integer powered multiples of a known basic data rate. These algorithms can be applied to the Electra radio currently used in the Deep Space Network (DSN), which employs data rates having the above relationship. The estimation is carried out in an autonomous setting in which very little a priori information is assumed. It is done by exploiting an elegant property of the split symbol moments estimator (SSME), which is traditionally used to estimate the signal-to-noise ratio (SNR) of the received signal. By quantizing the assumed symbol-timing error or jitter, we present an all-digital implementation of the SSME which can be used to jointly estimate the data rate, SNR, and jitter. Simulation results presented show that these joint estimation algorithms perform well, even in the low SNR regions typically encountered in the DSN.

A time-frequency analysis method to obtain stable estimates of magnetotelluric response function based on Hilbert-Huang transform

NASA Astrophysics Data System (ADS)

Cai, Jianhua

2017-05-01

The time-frequency analysis method represents signal as a function of time and frequency, and it is considered a powerful tool for handling arbitrary non-stationary time series by using instantaneous frequency and instantaneous amplitude. It also provides a possible alternative to the analysis of the non-stationary magnetotelluric (MT) signal. Based on the Hilbert-Huang transform (HHT), a time-frequency analysis method is proposed to obtain stable estimates of the magnetotelluric response function. In contrast to conventional methods, the response function estimation is performed in the time-frequency domain using instantaneous spectra rather than in the frequency domain, which allows for imaging the response parameter content as a function of time and frequency. The theory of the method is presented and the mathematical model and calculation procedure, which are used to estimate response function based on HHT time-frequency spectrum, are discussed. To evaluate the results, response function estimates are compared with estimates from a standard MT data processing method based on the Fourier transform. All results show that apparent resistivities and phases, which are calculated from the HHT time-frequency method, are generally more stable and reliable than those determined from the simple Fourier analysis. The proposed method overcomes the drawbacks of the traditional Fourier methods, and the resulting parameter minimises the estimation bias caused by the non-stationary characteristics of the MT data.

Estimation of the Horizon in Photographed Outdoor Scenes by Human and Machine

PubMed Central

Herdtweck, Christian; Wallraven, Christian

2013-01-01

We present three experiments on horizon estimation. In Experiment 1 we verify the human ability to estimate the horizon in static images from only visual input. Estimates are given without time constraints with emphasis on precision. The resulting estimates are used as baseline to evaluate horizon estimates from early visual processes. Stimuli are presented for only ms and then masked to purge visual short-term memory and enforcing estimates to rely on early processes, only. The high agreement between estimates and the lack of a training effect shows that enough information about viewpoint is extracted in the first few hundred milliseconds to make accurate horizon estimation possible. In Experiment 3 we investigate several strategies to estimate the horizon in the computer and compare human with machine “behavior” for different image manipulations and image scene types. PMID:24349073

A statistical approach to determining the uncertainty in power-law model estimates of emissions based on time-dependent chamber concentration measurements

EPA Science Inventory

The use of models for estimating emissions from products beyond the timeframe of an emissions test is a means of managing the time and expenses associated with product emissions certification. This paper presents a discussion of (1) the impact of uncertainty in test chamber emiss...

Estimating the Full Cost of Family-Financed Time Inputs to Education.

ERIC Educational Resources Information Center

Levine, Victor

This paper presents a methodology for estimating the full cost of parental time allocated to child-care activities at home. Building upon the human capital hypothesis, a model is developed in which the cost of an hour diverted from labor market activity is seen as consisting of three components: 1) direct wages foregone; 2) investments in…

Motion illusions in optical art presented for long durations are temporally distorted.

PubMed

Nather, Francisco Carlos; Mecca, Fernando Figueiredo; Bueno, José Lino Oliveira

2013-01-01

Static figurative images implying human body movements observed for shorter and longer durations affect the perception of time. This study examined whether images of static geometric shapes would affect the perception of time. Undergraduate participants observed two Optical Art paintings by Bridget Riley for 9 or 36 s (group G9 and G36, respectively). Paintings implying different intensities of movement (2.0 and 6.0 point stimuli) were randomly presented. The prospective paradigm in the reproduction method was used to record time estimations. Data analysis did not show time distortions in the G9 group. In the G36 group the paintings were differently perceived: that for the 2.0 point one are estimated to be shorter than that for the 6.0 point one. Also for G36, the 2.0 point painting was underestimated in comparison with the actual time of exposure. Motion illusions in static images affected time estimation according to the attention given to the complexity of movement by the observer, probably leading to changes in the storage velocity of internal clock pulses.

Estimating Attitude, Trajectory, and Gyro Biases in an Extended Kalman Filter using Earth Magnetic Field Data from the Rossi X-Ray Timing Explorer

NASA Technical Reports Server (NTRS)

Deutschmann, Julie; Bar-Itzhack, Itzhack

1997-01-01

Traditionally satellite attitude and trajectory have been estimated with completely separate systems, using different measurement data. The estimation of both trajectory and attitude for low earth orbit satellites has been successfully demonstrated in ground software using magnetometer and gyroscope data. Since the earth's magnetic field is a function of time and position, and since time is known quite precisely, the differences between the computed and measured magnetic field components, as measured by the magnetometers throughout the entire spacecraft orbit, are a function of both the spacecraft trajectory and attitude errors. Therefore, these errors can be used to estimate both trajectory and attitude. This work further tests the single augmented Extended Kalman Filter (EKF) which simultaneously and autonomously estimates spacecraft trajectory and attitude with data from the Rossi X-Ray Timing Explorer (RXTE) magnetometer and gyro-measured body rates. In addition, gyro biases are added to the state and the filter's ability to estimate them is presented.

An Indirect System Identification Technique for Stable Estimation of Continuous-Time Parameters of the Vestibulo-Ocular Reflex (VOR)

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.; Wallin, Ragnar; Boyle, Richard D.

2013-01-01

The vestibulo-ocular reflex (VOR) is a well-known dual mode bifurcating system that consists of slow and fast modes associated with nystagmus and saccade, respectively. Estimation of continuous-time parameters of nystagmus and saccade models are known to be sensitive to estimation methodology, noise and sampling rate. The stable and accurate estimation of these parameters are critical for accurate disease modelling, clinical diagnosis, robotic control strategies, mission planning for space exploration and pilot safety, etc. This paper presents a novel indirect system identification method for the estimation of continuous-time parameters of VOR employing standardised least-squares with dual sampling rates in a sparse structure. This approach permits the stable and simultaneous estimation of both nystagmus and saccade data. The efficacy of this approach is demonstrated via simulation of a continuous-time model of VOR with typical parameters found in clinical studies and in the presence of output additive noise.

Defining Tsunami Magnitude as Measure of Potential Impact

NASA Astrophysics Data System (ADS)

Titov, V. V.; Tang, L.

2016-12-01

The goal of tsunami forecast, as a system for predicting potential impact of a tsunami at coastlines, requires quick estimate of a tsunami magnitude. This goal has been recognized since the beginning of tsunami research. The work of Kajiura, Soloviev, Abe, Murty, and many others discussed several scales for tsunami magnitude based on estimates of tsunami energy. However, difficulties of estimating tsunami energy based on available tsunami measurements at coastal sea-level stations has carried significant uncertainties and has been virtually impossible in real time, before tsunami impacts coastlines. The slow process of tsunami magnitude estimates, including collection of vast amount of available coastal sea-level data from affected coastlines, made it impractical to use any tsunami magnitude scales in tsunami warning operations. Uncertainties of estimates made tsunami magnitudes difficult to use as universal scale for tsunami analysis. Historically, the earthquake magnitude has been used as a proxy of tsunami impact estimates, since real-time seismic data is available of real-time processing and ample amount of seismic data is available for an elaborate post event analysis. This measure of tsunami impact carries significant uncertainties in quantitative tsunami impact estimates, since the relation between the earthquake and generated tsunami energy varies from case to case. In this work, we argue that current tsunami measurement capabilities and real-time modeling tools allow for establishing robust tsunami magnitude that will be useful for tsunami warning as a quick estimate for tsunami impact and for post-event analysis as a universal scale for tsunamis inter-comparison. We present a method for estimating the tsunami magnitude based on tsunami energy and present application of the magnitude analysis for several historical events for inter-comparison with existing methods.

Reduced rank models for travel time estimation of low order mode pulses.

PubMed

Chandrayadula, Tarun K; Wage, Kathleen E; Worcester, Peter F; Dzieciuch, Matthew A; Mercer, James A; Andrew, Rex K; Howe, Bruce M

2013-10-01

Mode travel time estimation in the presence of internal waves (IWs) is a challenging problem. IWs perturb the sound speed, which results in travel time wander and mode scattering. A standard approach to travel time estimation is to pulse compress the broadband signal, pick the peak of the compressed time series, and average the peak time over multiple receptions to reduce variance. The peak-picking approach implicitly assumes there is a single strong arrival and does not perform well when there are multiple arrivals due to scattering. This article presents a statistical model for the scattered mode arrivals and uses the model to design improved travel time estimators. The model is based on an Empirical Orthogonal Function (EOF) analysis of the mode time series. Range-dependent simulations and data from the Long-range Ocean Acoustic Propagation Experiment (LOAPEX) indicate that the modes are represented by a small number of EOFs. The reduced-rank EOF model is used to construct a travel time estimator based on the Matched Subspace Detector (MSD). Analysis of simulation and experimental data show that the MSDs are more robust to IW scattering than peak picking. The simulation analysis also highlights how IWs affect the mode excitation by the source.

On the real-time estimation of the wheel-rail contact force by means of a new nonlinear estimator design model

NASA Astrophysics Data System (ADS)

Strano, Salvatore; Terzo, Mario

2018-05-01

The dynamics of the railway vehicles is strongly influenced by the interaction between the wheel and the rail. This kind of contact is affected by several conditioning factors such as vehicle speed, wear, adhesion level and, moreover, it is nonlinear. As a consequence, the modelling and the observation of this kind of phenomenon are complex tasks but, at the same time, they constitute a fundamental step for the estimation of the adhesion level or for the vehicle condition monitoring. This paper presents a novel technique for the real time estimation of the wheel-rail contact forces based on an estimator design model that takes into account the nonlinearities of the interaction by means of a fitting model functional to reproduce the contact mechanics in a wide range of slip and to be easily integrated in a complete model based estimator for railway vehicle.

Estimating the number of people in crowded scenes

NASA Astrophysics Data System (ADS)

Kim, Minjin; Kim, Wonjun; Kim, Changick

2011-01-01

This paper presents a method to estimate the number of people in crowded scenes without using explicit object segmentation or tracking. The proposed method consists of three steps as follows: (1) extracting space-time interest points using eigenvalues of the local spatio-temporal gradient matrix, (2) generating crowd regions based on space-time interest points, and (3) estimating the crowd density based on the multiple regression. In experimental results, the efficiency and robustness of our proposed method are demonstrated by using PETS 2009 dataset.

Nonparametric change point estimation for survival distributions with a partially constant hazard rate.

PubMed

Brazzale, Alessandra R; Küchenhoff, Helmut; Krügel, Stefanie; Schiergens, Tobias S; Trentzsch, Heiko; Hartl, Wolfgang

2018-04-05

We present a new method for estimating a change point in the hazard function of a survival distribution assuming a constant hazard rate after the change point and a decreasing hazard rate before the change point. Our method is based on fitting a stump regression to p values for testing hazard rates in small time intervals. We present three real data examples describing survival patterns of severely ill patients, whose excess mortality rates are known to persist far beyond hospital discharge. For designing survival studies in these patients and for the definition of hospital performance metrics (e.g. mortality), it is essential to define adequate and objective end points. The reliable estimation of a change point will help researchers to identify such end points. By precisely knowing this change point, clinicians can distinguish between the acute phase with high hazard (time elapsed after admission and before the change point was reached), and the chronic phase (time elapsed after the change point) in which hazard is fairly constant. We show in an extensive simulation study that maximum likelihood estimation is not robust in this setting, and we evaluate our new estimation strategy including bootstrap confidence intervals and finite sample bias correction.

Identifying demand for health resources using waiting times information.

PubMed

Blundell, R; Windmeijer, F

2000-09-01

In this paper the differences in average waiting times are utilized to identify the determinants of demand for health services. The equilibrium waiting time framework is used, but the full equilibrium assumption is relaxed by selecting areas with low waiting times and by estimating a (semi-)parametric selection model. Determinants of supply are used as instruments for the endogeneity of waiting times. A model for the demand for acute services at the ward level in the UK is estimated. The model estimates, and their implications for health service allocations in the UK, are contrasted against more standard allocation models. The present results show that it is critically important to account for rationing by waiting times when identifying needs from care utilization data. Copyright 2000 John Wiley & Sons, Ltd.

Using the entire history in the analysis of nested case cohort samples.

PubMed

Rivera, C L; Lumley, T

2016-08-15

Countermatching designs can provide more efficient estimates than simple matching or case-cohort designs in certain situations such as when good surrogate variables for an exposure of interest are available. We extend pseudolikelihood estimation for the Cox model under countermatching designs to models where time-varying covariates are considered. We also implement pseudolikelihood with calibrated weights to improve efficiency in nested case-control designs in the presence of time-varying variables. A simulation study is carried out, which considers four different scenarios including a binary time-dependent variable, a continuous time-dependent variable, and the case including interactions in each. Simulation results show that pseudolikelihood with calibrated weights under countermatching offers large gains in efficiency if compared to case-cohort. Pseudolikelihood with calibrated weights yielded more efficient estimators than pseudolikelihood estimators. Additionally, estimators were more efficient under countermatching than under case-cohort for the situations considered. The methods are illustrated using the Colorado Plateau uranium miners cohort. Furthermore, we present a general method to generate survival times with time-varying covariates. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Regression analysis of longitudinal data with correlated censoring and observation times.

PubMed

Li, Yang; He, Xin; Wang, Haiying; Sun, Jianguo

2016-07-01

Longitudinal data occur in many fields such as the medical follow-up studies that involve repeated measurements. For their analysis, most existing approaches assume that the observation or follow-up times are independent of the response process either completely or given some covariates. In practice, it is apparent that this may not be true. In this paper, we present a joint analysis approach that allows the possible mutual correlations that can be characterized by time-dependent random effects. Estimating equations are developed for the parameter estimation and the resulted estimators are shown to be consistent and asymptotically normal. The finite sample performance of the proposed estimators is assessed through a simulation study and an illustrative example from a skin cancer study is provided.

Annual forest inventory estimates based on the moving average

Treesearch

Francis A. Roesch; James R. Steinman; Michael T. Thompson

2002-01-01

Three interpretations of the simple moving average estimator, as applied to the USDA Forest Service's annual forest inventory design, are presented. A corresponding approach to composite estimation over arbitrarily defined land areas and time intervals is given for each interpretation, under the assumption that the investigator is armed with only the spatial/...

Measuring agreement of multivariate discrete survival times using a modified weighted kappa coefficient.

PubMed

Guo, Ying; Manatunga, Amita K

2009-03-01

Assessing agreement is often of interest in clinical studies to evaluate the similarity of measurements produced by different raters or methods on the same subjects. We present a modified weighted kappa coefficient to measure agreement between bivariate discrete survival times. The proposed kappa coefficient accommodates censoring by redistributing the mass of censored observations within the grid where the unobserved events may potentially happen. A generalized modified weighted kappa is proposed for multivariate discrete survival times. We estimate the modified kappa coefficients nonparametrically through a multivariate survival function estimator. The asymptotic properties of the kappa estimators are established and the performance of the estimators are examined through simulation studies of bivariate and trivariate survival times. We illustrate the application of the modified kappa coefficient in the presence of censored observations with data from a prostate cancer study.

A Geomagnetic Estimate of Mean Paleointensity

NASA Technical Reports Server (NTRS)

Voorhies, Coerte

2004-01-01

To test a statistical hypothesis about Earth's magnetic field against paleomagnetism, the present field is used to estimate time averaged paleointensity. The estimate uses the modem magnetic multipole spectrum R(n), which gives the mean square induction represented by spherical harmonics of degree n averaged over the sphere of radius a = 6371.2 km. The hypothesis asserts that the low degree multipole powers of the core-source field are distributed as chi-squared with 2n+l degrees of freedom and expectation values {R(n)} = K[(n+l/2)/n(n+l](c/a)(sup 2n+4), where c is the 3480 km radius of Earth's core. (This is compatible with a usually mainly geocentric axial dipolar field). Amplitude K is estimated by fitting theoretical to observational spectra through degree 12. The resulting calibrated expectation spectrum is summed through degree 12 to estimate expected square intensity {F(sup 2)}. The sum also estimates {F(sup 2)} averaged over geologic time, in so far as the present magnetic spectrum is a fair sample of that generated in the past by core geodynamic processes.

Robust Bayesian Fluorescence Lifetime Estimation, Decay Model Selection and Instrument Response Determination for Low-Intensity FLIM Imaging

PubMed Central

Rowley, Mark I.; Coolen, Anthonius C. C.; Vojnovic, Borivoj; Barber, Paul R.

2016-01-01

We present novel Bayesian methods for the analysis of exponential decay data that exploit the evidence carried by every detected decay event and enables robust extension to advanced processing. Our algorithms are presented in the context of fluorescence lifetime imaging microscopy (FLIM) and particular attention has been paid to model the time-domain system (based on time-correlated single photon counting) with unprecedented accuracy. We present estimates of decay parameters for mono- and bi-exponential systems, offering up to a factor of two improvement in accuracy compared to previous popular techniques. Results of the analysis of synthetic and experimental data are presented, and areas where the superior precision of our techniques can be exploited in Förster Resonance Energy Transfer (FRET) experiments are described. Furthermore, we demonstrate two advanced processing methods: decay model selection to choose between differing models such as mono- and bi-exponential, and the simultaneous estimation of instrument and decay parameters. PMID:27355322

Estimating satellite pose and motion parameters using a novelty filter and neural net tracker

NASA Technical Reports Server (NTRS)

Lee, Andrew J.; Casasent, David; Vermeulen, Pieter; Barnard, Etienne

1989-01-01

A system for determining the position, orientation and motion of a satellite with respect to a robotic spacecraft using video data is advanced. This system utilizes two levels of pose and motion estimation: an initial system which provides coarse estimates of pose and motion, and a second system which uses the coarse estimates and further processing to provide finer pose and motion estimates. The present paper emphasizes the initial coarse pose and motion estimation sybsystem. This subsystem utilizes novelty detection and filtering for locating novel parts and a neural net tracker to track these parts over time. Results of using this system on a sequence of images of a spin stabilized satellite are presented.

The FIA Panel Design and Compatible Estimators for the Components of Change

Treesearch

Francis A. Roesch

2006-01-01

The FIA annual panel design and its relation to compatible estimation systems for the components of change are discussed. Estimation for the traditional components of growth, as presented by Meyer (1953, Forest Mensuration) is bypassed in favor of a focus on estimation for the discrete analogs to Eriksson’s (1995, For. Sci. 41(4):796- 822) time invariant redefinitions...

Developmental Differences in Frequency Judgments of Words and Pictures.

ERIC Educational Resources Information Center

Ghatala, Elizabeth S.; Levin, Joel R.

Children in kindergarten, third grade, and fifth grade were presented a list of either pictures or words (with items presented varying numbers of times on the study trail). In both picture and word conditions, half of the subjects estimated how many times each item had been presented (absolute judgments) and the other half judged which of two…

A model for estimating the cost impact of schedule perturbations on aerospace research and development programs

NASA Technical Reports Server (NTRS)

Bishop, D. F.

1972-01-01

The problem of determining the cost impact attributable to perturbations in an aerospace R and D program schedule is discussed in terms of the diminishing availability of funds. The methodology from which a model is presented for updating R and D cost estimates as a function of perturbations in program time is presented.

Temperature-based death time estimation with only partially known environmental conditions.

PubMed

Mall, Gita; Eckl, Mona; Sinicina, Inga; Peschel, Oliver; Hubig, Michael

2005-07-01

The temperature-oriented death time determination is based on mathematical model curves of postmortem rectal cooling. All mathematical models require knowledge of the environmental conditions. In medico-legal practice homicide is sometimes not immediately suspected at the death scene but afterwards during external examination of the body. The environmental temperature at the death scene remains unknown or can only be roughly reconstructed. In such cases the question arises whether it is possible to estimate the time since death from rectal temperature data alone recorded over a longer time span. The present study theoretically deduces formulae which are independent of the initial and environmental temperatures and thus proves that the information needed for death time estimation is contained in the rectal temperature data. Since the environmental temperature at the death scene may differ from that during the temperature recording, an additional factor has to be used. This is that the body core is thermally well isolated from the environment and that the rectal temperature decrease after a sudden change of environmental temperature will continue for some time at a rate similar to that before the sudden change. The present study further provides a curve-fitting procedure for such scenarios. The procedure was tested in rectal cooling data of from 35 corpses using the most commonly applied model of Henssge. In all cases the time of death was exactly known. After admission to the medico-legal institute the bodies were kept at a constant environmental temperature for 12-36 h and the rectal temperatures were recorded continuously. The curve-fitting procedure led to valid estimates of the time since death in all experiments despite the unknown environmental conditions before admission to the institute. The estimation bias was investigated statistically. The 95% confidence intervals amounted to +/-4 h, which seems reasonable compared to the 95% confidence intervals of the Henssge model with known environmental temperature. The presented method may be of use for determining the time since death even in cases in which the environmental temperature and rectal temperature at the death scene have unintentionally not been recorded.

Recent advancements in GRACE mascon regularization and uncertainty assessment

NASA Astrophysics Data System (ADS)

Loomis, B. D.; Luthcke, S. B.

2017-12-01

The latest release of the NASA Goddard Space Flight Center (GSFC) global time-variable gravity mascon product applies a new regularization strategy along with new methods for estimating noise and leakage uncertainties. The critical design component of mascon estimation is the construction of the applied regularization matrices, and different strategies exist between the different centers that produce mascon solutions. The new approach from GSFC directly applies the pre-fit Level 1B inter-satellite range-acceleration residuals in the design of time-dependent regularization matrices, which are recomputed at each step of our iterative solution method. We summarize this new approach, demonstrating the simultaneous increase in recovered time-variable gravity signal and reduction in the post-fit inter-satellite residual magnitudes, until solution convergence occurs. We also present our new approach for estimating mascon noise uncertainties, which are calibrated to the post-fit inter-satellite residuals. Lastly, we present a new technique for end users to quickly estimate the signal leakage errors for any selected grouping of mascons, and we test the viability of this leakage assessment procedure on the mascon solutions produced by other processing centers.

Estimation of Traffic Variables Using Point Processing Techniques

DOT National Transportation Integrated Search

1978-05-01

An alternative approach to estimating aggregate traffic variables on freeways--spatial mean velocity and density--is presented. Vehicle arrival times at a given location on a roadway, typically a presence detector, are regarded as a point or counting...

Observers for a class of systems with nonlinearities satisfying an incremental quadratic inequality

NASA Technical Reports Server (NTRS)

Acikmese, Ahmet Behcet; Martin, Corless

2004-01-01

We consider the problem of state estimation from nonlinear time-varying system whose nonlinearities satisfy an incremental quadratic inequality. Observers are presented which guarantee that the state estimation error exponentially converges to zero.

Ionospheric modelling to boost the PPP-RTK positioning and navigation in Australia

NASA Astrophysics Data System (ADS)

Arsov, Kirco; Terkildsen, Michael; Olivares, German

2017-04-01

This paper deals with implementation of 3-D ionospheric model to support the GNSS positioning and navigation activities in Australia. We will introduce two strategies for Slant Total Electron Content (STEC) estimation from GNSS CORS sites in Australia. In the first scenario, the STEC is estimated in the PPP-RTK network processing. The ionosphere is estimated together with other GNSS network parameters, such as Satellite Clocks, Satellite Phase Biases, etc. Another approach is where STEC is estimated on a station by station basis by taking advantage of already known station position and different satellite ambiguities relations. Accuracy studies and considerations will be presented and discussed. Furthermore, based on this STEC, 3-D ionosphere modeling will be performed. We will present the simple interpolation, 3-D Tomography and bi-cubic splines as modeling techniques. In order to assess these models, a (user) PPP-RTK test bed is established and a sensitivity matrix will be introduced and analyzed based on time to first fix (TTFF) of ambiguities, positioning accuracy, PPP-RTK solution convergence time etc. Different spatial configurations and constellations will be presented and assessed.

Robust, automatic GPS station velocities and velocity time series

NASA Astrophysics Data System (ADS)

Blewitt, G.; Kreemer, C.; Hammond, W. C.

2014-12-01

Automation in GPS coordinate time series analysis makes results more objective and reproducible, but not necessarily as robust as the human eye to detect problems. Moreover, it is not a realistic option to manually scan our current load of >20,000 time series per day. This motivates us to find an automatic way to estimate station velocities that is robust to outliers, discontinuities, seasonality, and noise characteristics (e.g., heteroscedasticity). Here we present a non-parametric method based on the Theil-Sen estimator, defined as the median of velocities vij=(xj-xi)/(tj-ti) computed between all pairs (i, j). Theil-Sen estimators produce statistically identical solutions to ordinary least squares for normally distributed data, but they can tolerate up to 29% of data being problematic. To mitigate seasonality, our proposed estimator only uses pairs approximately separated by an integer number of years (N-δt)<(tj-ti )<(N+δt), where δt is chosen to be small enough to capture seasonality, yet large enough to reduce random error. We fix N=1 to maximally protect against discontinuities. In addition to estimating an overall velocity, we also use these pairs to estimate velocity time series. To test our methods, we process real data sets that have already been used with velocities published in the NA12 reference frame. Accuracy can be tested by the scatter of horizontal velocities in the North American plate interior, which is known to be stable to ~0.3 mm/yr. This presents new opportunities for time series interpretation. For example, the pattern of velocity variations at the interannual scale can help separate tectonic from hydrological processes. Without any step detection, velocity estimates prove to be robust for stations affected by the Mw7.2 2010 El Mayor-Cucapah earthquake, and velocity time series show a clear change after the earthquake, without any of the usual parametric constraints, such as relaxation of postseismic velocities to their preseismic values.

Improving the Depth-Time Fit of Holocene Climate Proxy Measures by Increasing Coherence with a Reference Time-Series

NASA Astrophysics Data System (ADS)

Rahim, K. J.; Cumming, B. F.; Hallett, D. J.; Thomson, D. J.

2007-12-01

An accurate assessment of historical local Holocene data is important in making future climate predictions. Holocene climate is often obtained through proxy measures such as diatoms or pollen using radiocarbon dating. Wiggle Match Dating (WMD) uses an iterative least squares approach to tune a core with a large amount of 14C dates to the 14C calibration curve. This poster will present a new method of tuning a time series with when only a modest number of 14C dates are available. The method presented uses the multitaper spectral estimation, and it specifically makes use of a multitaper spectral coherence tuning technique. Holocene climate reconstructions are often based on a simple depth-time fit such as a linear interpolation, splines, or low order polynomials. Many of these models make use of only a small number of 14C dates, each of which is a point estimate with a significant variance. This technique attempts to tune the 14C dates to a reference series, such as tree rings, varves, or the radiocarbon calibration curve. The amount of 14C in the atmosphere is not constant, and a significant source of variance is solar activity. A decrease in solar activity coincides with an increase in cosmogenic isotope production, and an increase in cosmogenic isotope production coincides with a decrease in temperature. The method presented uses multitaper coherence estimates and adjusts the phase of the time series to line up significant line components with that of the reference series in attempt to obtain a better depth-time fit then the original model. Given recent concerns and demonstrations of the variation in estimated dates from radiocarbon labs, methods to confirm and tune the depth-time fit can aid climate reconstructions by improving and serving to confirm the accuracy of the underlying depth-time fit. Climate reconstructions can then be made on the improved depth-time fit. This poster presents a run though of this process using Chauvin Lake in the Canadian prairies and Mt. Barr Cirque Lake located in British Columbia as examples.

Estimating procedure times for surgeries by determining location parameters for the lognormal model.

PubMed

Spangler, William E; Strum, David P; Vargas, Luis G; May, Jerrold H

2004-05-01

We present an empirical study of methods for estimating the location parameter of the lognormal distribution. Our results identify the best order statistic to use, and indicate that using the best order statistic instead of the median may lead to less frequent incorrect rejection of the lognormal model, more accurate critical value estimates, and higher goodness-of-fit. Using simulation data, we constructed and compared two models for identifying the best order statistic, one based on conventional nonlinear regression and the other using a data mining/machine learning technique. Better surgical procedure time estimates may lead to improved surgical operations.

Pathfinder. Volume 9, Number 2, March/April 2011

DTIC Science & Technology

2011-03-01

vides audio, video, desktop sharing and chat.” The platform offers a real-time, Web- based presentation tool to create information and general...collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources...gathering and maintaining the data needed, and completing and reviewing the collection of information . Send comments regarding this burden estimate or

Ecology and thermal inactivation of microbes in and on interplanetary space vehicle components

NASA Technical Reports Server (NTRS)

Reyes, A. L.; Campbell, J. E.

1976-01-01

The heat resistance of Bacillus subtilis var. niger was measured from 85 to 125 C using moisture levels of % RH or = 0.001 to 100. Curves are presented which characterize thermal destruction using thermal death times defined as F values at a given combination of three moisture and temperature conditions. The times required at 100 C for reductions of 99.99% of the initial population were estimated for the three moisture conditions. The linear model (from which estimates of D are obtained) was satisfactory for estimating thermal death times (% RH or = 0.07) in the plate count range. Estimates based on observed thermal death times and D values for % RH = 100 diverged so that D values generally gave a more conservative estimate over the temperature range 90 to 125 C. Estimates of Z sub F and Z sub L ranged from 32.1 to 58.3 C for % RH of or = 0.07 and 100. A Z sub D = 30.0 was obtained for data observed at % RH or = 0.07.

Input Forces Estimation for Nonlinear Systems by Applying a Square-Root Cubature Kalman Filter.

PubMed

Song, Xuegang; Zhang, Yuexin; Liang, Dakai

2017-10-10

This work presents a novel inverse algorithm to estimate time-varying input forces in nonlinear beam systems. With the system parameters determined, the input forces can be estimated in real-time from dynamic responses, which can be used for structural health monitoring. In the process of input forces estimation, the Runge-Kutta fourth-order algorithm was employed to discretize the state equations; a square-root cubature Kalman filter (SRCKF) was employed to suppress white noise; the residual innovation sequences, a priori state estimate, gain matrix, and innovation covariance generated by SRCKF were employed to estimate the magnitude and location of input forces by using a nonlinear estimator. The nonlinear estimator was based on the least squares method. Numerical simulations of a large deflection beam and an experiment of a linear beam constrained by a nonlinear spring were employed. The results demonstrated accuracy of the nonlinear algorithm.

Estimation of multiple accelerated motions using chirp-Fourier transform and clustering.

PubMed

Alexiadis, Dimitrios S; Sergiadis, George D

2007-01-01

Motion estimation in the spatiotemporal domain has been extensively studied and many methodologies have been proposed, which, however, cannot handle both time-varying and multiple motions. Extending previously published ideas, we present an efficient method for estimating multiple, linearly time-varying motions. It is shown that the estimation of accelerated motions is equivalent to the parameter estimation of superpositioned chirp signals. From this viewpoint, one can exploit established signal processing tools such as the chirp-Fourier transform. It is shown that accelerated motion results in energy concentration along planes in the 4-D space: spatial frequencies-temporal frequency-chirp rate. Using fuzzy c-planes clustering, we estimate the plane/motion parameters. The effectiveness of our method is verified on both synthetic as well as real sequences and its advantages are highlighted.

On Time Delay Margin Estimation for Adaptive Control and Optimal Control Modification

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.

2011-01-01

This paper presents methods for estimating time delay margin for adaptive control of input delay systems with almost linear structured uncertainty. The bounded linear stability analysis method seeks to represent an adaptive law by a locally bounded linear approximation within a small time window. The time delay margin of this input delay system represents a local stability measure and is computed analytically by three methods: Pade approximation, Lyapunov-Krasovskii method, and the matrix measure method. These methods are applied to the standard model-reference adaptive control, s-modification adaptive law, and optimal control modification adaptive law. The windowing analysis results in non-unique estimates of the time delay margin since it is dependent on the length of a time window and parameters which vary from one time window to the next. The optimal control modification adaptive law overcomes this limitation in that, as the adaptive gain tends to infinity and if the matched uncertainty is linear, then the closed-loop input delay system tends to a LTI system. A lower bound of the time delay margin of this system can then be estimated uniquely without the need for the windowing analysis. Simulation results demonstrates the feasibility of the bounded linear stability method for time delay margin estimation.

Parameter Estimates in Differential Equation Models for Chemical Kinetics

ERIC Educational Resources Information Center

Winkel, Brian

2011-01-01

We discuss the need for devoting time in differential equations courses to modelling and the completion of the modelling process with efforts to estimate the parameters in the models using data. We estimate the parameters present in several differential equation models of chemical reactions of order n, where n = 0, 1, 2, and apply more general…

Cox model with interval-censored covariate in cohort studies.

PubMed

Ahn, Soohyun; Lim, Johan; Paik, Myunghee Cho; Sacco, Ralph L; Elkind, Mitchell S

2018-05-18

In cohort studies the outcome is often time to a particular event, and subjects are followed at regular intervals. Periodic visits may also monitor a secondary irreversible event influencing the event of primary interest, and a significant proportion of subjects develop the secondary event over the period of follow-up. The status of the secondary event serves as a time-varying covariate, but is recorded only at the times of the scheduled visits, generating incomplete time-varying covariates. While information on a typical time-varying covariate is missing for entire follow-up period except the visiting times, the status of the secondary event are unavailable only between visits where the status has changed, thus interval-censored. One may view interval-censored covariate of the secondary event status as missing time-varying covariates, yet missingness is partial since partial information is provided throughout the follow-up period. Current practice of using the latest observed status produces biased estimators, and the existing missing covariate techniques cannot accommodate the special feature of missingness due to interval censoring. To handle interval-censored covariates in the Cox proportional hazards model, we propose an available-data estimator, a doubly robust-type estimator as well as the maximum likelihood estimator via EM algorithm and present their asymptotic properties. We also present practical approaches that are valid. We demonstrate the proposed methods using our motivating example from the Northern Manhattan Study. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Dynamic modeling and parameter estimation of a radial and loop type distribution system network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jun Qui; Heng Chen; Girgis, A.A.

1993-05-01

This paper presents a new identification approach to three-phase power system modeling and model reduction taking power system network as multi-input, multi-output (MIMO) processes. The model estimate can be obtained in discrete-time input-output form, discrete- or continuous-time state-space variable form, or frequency-domain impedance transfer function matrix form. An algorithm for determining the model structure of this MIMO process is described. The effect of measurement noise on the approach is also discussed. This approach has been applied on a sample system and simulation results are also presented in this paper.

Spread-Spectrum Carrier Estimation With Unknown Doppler Shift

NASA Technical Reports Server (NTRS)

DeLeon, Phillip L.; Scaife, Bradley J.

1998-01-01

We present a method for the frequency estimation of a BPSK modulated, spread-spectrum carrier with unknown Doppler shift. The approach relies on a classic periodogram in conjunction with a spectral matched filter. Simulation results indicate accurate carrier estimation with processing gains near 40. A DSP-based prototype has been implemented for real-time carrier estimation for use in New Mexico State University's proposal for NASA's Demand Assignment Multiple Access service.

H∞ state estimation of stochastic memristor-based neural networks with time-varying delays.

PubMed

Bao, Haibo; Cao, Jinde; Kurths, Jürgen; Alsaedi, Ahmed; Ahmad, Bashir

2018-03-01

This paper addresses the problem of H ∞ state estimation for a class of stochastic memristor-based neural networks with time-varying delays. Under the framework of Filippov solution, the stochastic memristor-based neural networks are transformed into systems with interval parameters. The present paper is the first to investigate the H ∞ state estimation problem for continuous-time Itô-type stochastic memristor-based neural networks. By means of Lyapunov functionals and some stochastic technique, sufficient conditions are derived to ensure that the estimation error system is asymptotically stable in the mean square with a prescribed H ∞ performance. An explicit expression of the state estimator gain is given in terms of linear matrix inequalities (LMIs). Compared with other results, our results reduce control gain and control cost effectively. Finally, numerical simulations are provided to demonstrate the efficiency of the theoretical results. Copyright © 2018 Elsevier Ltd. All rights reserved.

Photogrammetric Trajectory Estimation of Foam Debris Ejected From an F-15 Aircraft

NASA Technical Reports Server (NTRS)

Smith, Mark S.

2006-01-01

Photogrammetric analysis of high-speed digital video data was performed to estimate trajectories of foam debris ejected from an F-15B aircraft. This work was part of a flight test effort to study the transport properties of insulating foam shed by the Space Shuttle external tank during ascent. The conical frustum-shaped pieces of debris, called "divots," were ejected from a flight test fixture mounted underneath the F-15B aircraft. Two onboard cameras gathered digital video data at two thousand frames per second. Time histories of divot positions were determined from the videos post flight using standard photogrammetry techniques. Divot velocities were estimated by differentiating these positions with respect to time. Time histories of divot rotations were estimated using four points on the divot face. Estimated divot position, rotation, and Mach number for selected cases are presented. Uncertainty in the results is discussed.

Real-Time Algebraic Derivative Estimations Using a Novel Low-Cost Architecture Based on Reconfigurable Logic

PubMed Central

Morales, Rafael; Rincón, Fernando; Gazzano, Julio Dondo; López, Juan Carlos

2014-01-01

Time derivative estimation of signals plays a very important role in several fields, such as signal processing and control engineering, just to name a few of them. For that purpose, a non-asymptotic algebraic procedure for the approximate estimation of the system states is used in this work. The method is based on results from differential algebra and furnishes some general formulae for the time derivatives of a measurable signal in which two algebraic derivative estimators run simultaneously, but in an overlapping fashion. The algebraic derivative algorithm presented in this paper is computed online and in real-time, offering high robustness properties with regard to corrupting noises, versatility and ease of implementation. Besides, in this work, we introduce a novel architecture to accelerate this algebraic derivative estimator using reconfigurable logic. The core of the algorithm is implemented in an FPGA, improving the speed of the system and achieving real-time performance. Finally, this work proposes a low-cost platform for the integration of hardware in the loop in MATLAB. PMID:24859033

Nonlinear Estimation of Discrete-Time Signals Under Random Observation Delay

DOE Office of Scientific and Technical Information (OSTI.GOV)

Caballero-Aguila, R.; Jimenez-Lopez, J. D.; Hermoso-Carazo, A.

2008-11-06

This paper presents an approximation to the nonlinear least-squares estimation problem of discrete-time stochastic signals using nonlinear observations with additive white noise which can be randomly delayed by one sampling time. The observation delay is modelled by a sequence of independent Bernoulli random variables whose values, zero or one, indicate that the real observation arrives on time or it is delayed and, hence, the available measurement to estimate the signal is not up-to-date. Assuming that the state-space model generating the signal is unknown and only the covariance functions of the processes involved in the observation equation are ready for use,more » a filtering algorithm based on linear approximations of the real observations is proposed.« less

Dynamic Stability Analysis of Linear Time-varying Systems via an Extended Modal Identification Approach

NASA Astrophysics Data System (ADS)

Ma, Zhisai; Liu, Li; Zhou, Sida; Naets, Frank; Heylen, Ward; Desmet, Wim

2017-03-01

The problem of linear time-varying(LTV) system modal analysis is considered based on time-dependent state space representations, as classical modal analysis of linear time-invariant systems and current LTV system modal analysis under the "frozen-time" assumption are not able to determine the dynamic stability of LTV systems. Time-dependent state space representations of LTV systems are first introduced, and the corresponding modal analysis theories are subsequently presented via a stability-preserving state transformation. The time-varying modes of LTV systems are extended in terms of uniqueness, and are further interpreted to determine the system's stability. An extended modal identification is proposed to estimate the time-varying modes, consisting of the estimation of the state transition matrix via a subspace-based method and the extraction of the time-varying modes by the QR decomposition. The proposed approach is numerically validated by three numerical cases, and is experimentally validated by a coupled moving-mass simply supported beam experimental case. The proposed approach is capable of accurately estimating the time-varying modes, and provides a new way to determine the dynamic stability of LTV systems by using the estimated time-varying modes.

Intersection delay estimation from floating car data via principal curves: a case study on Beijing's road network

NASA Astrophysics Data System (ADS)

Liu, Xiliang; Lu, Feng; Zhang, Hengcai; Qiu, Peiyuan

2013-06-01

It is a pressing task to estimate the real-time travel time on road networks reliably in big cities, even though floating car data has been widely used to reflect the real traffic. Currently floating car data are mainly used to estimate the real-time traffic conditions on road segments, and has done little for turn delay estimation. However, turn delays on road intersections contribute significantly to the overall travel time on road networks in modern cities. In this paper, we present a technical framework to calculate the turn delays on road networks with float car data. First, the original floating car data collected with GPS equipped taxies was cleaned and matched to a street map with a distributed system based on Hadoop and MongoDB. Secondly, the refined trajectory data set was distributed among 96 time intervals (from 0: 00 to 23: 59). All of the intersections where the trajectories passed were connected with the trajectory segments, and constituted an experiment sample, while the intersections on arterial streets were specially selected to form another experiment sample. Thirdly, a principal curve-based algorithm was presented to estimate the turn delays at the given intersections. The algorithm argued is not only statistically fitted the real traffic conditions, but also is insensitive to data sparseness and missing data problems, which currently are almost inevitable with the widely used floating car data collecting technology. We adopted the floating car data collected from March to June in Beijing city in 2011, which contains more than 2.6 million trajectories generated from about 20000 GPS-equipped taxicabs and accounts for about 600 GB in data volume. The result shows the principal curve based algorithm we presented takes precedence over traditional methods, such as mean and median based approaches, and holds a higher estimation accuracy (about 10%-15% higher in RMSE), as well as reflecting the changing trend of traffic congestion. With the estimation result for the travel delay at intersections, we analyzed the spatio-temporal distribution of turn delays in three time scenarios (0: 00-0: 15, 8: 15-8: 30 and 12: 00-12: 15). It indicates that during one's single trip in Beijing, average 60% of the travel time on the road networks is wasted on the intersections, and this situation is even worse in daytime. Although the 400 main intersections take only 2.7% of all the intersections, they occupy about 18% travel time.

On protecting the planet against cosmic attack: Ultrafast real-time estimate of the asteroid's radial velocity

NASA Astrophysics Data System (ADS)

Zakharchenko, V. D.; Kovalenko, I. G.

2014-05-01

A new method for the line-of-sight velocity estimation of a high-speed near-Earth object (asteroid, meteorite) is suggested. The method is based on the use of fractional, one-half order derivative of a Doppler signal. The algorithm suggested is much simpler and more economical than the classical one, and it appears preferable for use in orbital weapon systems of threat response. Application of fractional differentiation to quick evaluation of mean frequency location of the reflected Doppler signal is justified. The method allows an assessment of the mean frequency in the time domain without spectral analysis. An algorithm structure for the real-time estimation is presented. The velocity resolution estimates are made for typical asteroids in the X-band. It is shown that the wait time can be shortened by orders of magnitude compared with similar value in the case of a standard spectral processing.

State estimation for advanced control of wave energy converters

DOE Data Explorer

Coe, Ryan; Bacelli, Giorgio

2017-04-25

A report on state estimation for advanced control of wave energy converters (WECs), with supporting data models and slides from the overview presentation. The methods discussed are intended for use to enable real-time closed loop control of WECs.

New Flutter Analysis Technique for Time-Domain Computational Aeroelasticity

NASA Technical Reports Server (NTRS)

Pak, Chan-Gi; Lung, Shun-Fat

2017-01-01

A new time-domain approach for computing flutter speed is presented. Based on the time-history result of aeroelastic simulation, the unknown unsteady aerodynamics model is estimated using a system identification technique. The full aeroelastic model is generated via coupling the estimated unsteady aerodynamic model with the known linear structure model. The critical dynamic pressure is computed and used in the subsequent simulation until the convergence of the critical dynamic pressure is achieved. The proposed method is applied to a benchmark cantilevered rectangular wing.

Estimation and enhancement of real-time software reliability through mutation analysis

NASA Technical Reports Server (NTRS)

Geist, Robert; Offutt, A. J.; Harris, Frederick C., Jr.

1992-01-01

A simulation-based technique for obtaining numerical estimates of the reliability of N-version, real-time software is presented. An extended stochastic Petri net is employed to represent the synchronization structure of N versions of the software, where dependencies among versions are modeled through correlated sampling of module execution times. Test results utilizing specifications for NASA's planetary lander control software indicate that mutation-based testing could hold greater potential for enhancing reliability than the desirable but perhaps unachievable goal of independence among N versions.

A Computationally Efficient Method for Polyphonic Pitch Estimation

NASA Astrophysics Data System (ADS)

Zhou, Ruohua; Reiss, Joshua D.; Mattavelli, Marco; Zoia, Giorgio

2009-12-01

This paper presents a computationally efficient method for polyphonic pitch estimation. The method employs the Fast Resonator Time-Frequency Image (RTFI) as the basic time-frequency analysis tool. The approach is composed of two main stages. First, a preliminary pitch estimation is obtained by means of a simple peak-picking procedure in the pitch energy spectrum. Such spectrum is calculated from the original RTFI energy spectrum according to harmonic grouping principles. Then the incorrect estimations are removed according to spectral irregularity and knowledge of the harmonic structures of the music notes played on commonly used music instruments. The new approach is compared with a variety of other frame-based polyphonic pitch estimation methods, and results demonstrate the high performance and computational efficiency of the approach.

Variability of Travel Times on New Jersey Highways

DOT National Transportation Integrated Search

2011-06-01

This report presents the results of a link and path travel time study conducted on selected New Jersey (NJ) highways to produce estimates of the corresponding variability of travel time (VTT) by departure time of the day and days of the week. The tra...

APPLICATION OF TRAVEL TIME RELIABILITY FOR PERFORMANCE ORIENTED OPERATIONAL PLANNING OF EXPRESSWAYS

NASA Astrophysics Data System (ADS)

Mehran, Babak; Nakamura, Hideki

Evaluation of impacts of congestion improvement scheme s on travel time reliability is very significant for road authorities since travel time reliability repr esents operational performance of expressway segments. In this paper, a methodology is presented to estimate travel tim e reliability prior to implementation of congestion relief schemes based on travel time variation modeling as a function of demand, capacity, weather conditions and road accident s. For subject expressway segmen ts, traffic conditions are modeled over a whole year considering demand and capacity as random variables. Patterns of demand and capacity are generated for each five minute interval by appl ying Monte-Carlo simulation technique, and accidents are randomly generated based on a model that links acci dent rate to traffic conditions. A whole year analysis is performed by comparing de mand and available capacity for each scenario and queue length is estimated through shockwave analysis for each time in terval. Travel times are estimated from refined speed-flow relationships developed for intercity expressways and buffer time index is estimated consequently as a measure of travel time reliability. For validation, estimated reliability indices are compared with measured values from empirical data, and it is shown that the proposed method is suitable for operational evaluation and planning purposes.

Divergence between human populations estimated from linkage disequilibrium.

PubMed

Sved, John A; McRae, Allan F; Visscher, Peter M

2008-12-01

Observed linkage disequilibrium (LD) between genetic markers in different populations descended independently from a common ancestral population can be used to estimate their absolute time of divergence, because the correlation of LD between populations will be reduced each generation by an amount that, approximately, depends only on the recombination rate between markers. Although drift leads to divergence in allele frequencies, it has less effect on divergence in LD values. We derived the relationship between LD and time of divergence and verified it with coalescent simulations. We then used HapMap Phase II data to estimate time of divergence between human populations. Summed over large numbers of pairs of loci, we find a positive correlation of LD between African and non-African populations at levels of up to approximately 0.3 cM. We estimate that the observed correlation of LD is consistent with an effective separation time of approximately 1,000 generations or approximately 25,000 years before present. The most likely explanation for such relatively low separation times is the existence of substantial levels of migration between populations after the initial separation. Theory and results from coalescent simulations confirm that low levels of migration can lead to a downward bias in the estimate of separation time.

InSAR analysis of surface deformation over permafrost to estimate active layer thickness based on one-dimensional heat transfer model of soils

PubMed Central

Li, Zhiwei; Zhao, Rong; Hu, Jun; Wen, Lianxing; Feng, Guangcai; Zhang, Zeyu; Wang, Qijie

2015-01-01

This paper presents a novel method to estimate active layer thickness (ALT) over permafrost based on InSAR (Interferometric Synthetic Aperture Radar) observation and the heat transfer model of soils. The time lags between the periodic feature of InSAR-observed surface deformation over permafrost and the meteorologically recorded temperatures are assumed to be the time intervals that the temperature maximum to diffuse from the ground surface downward to the bottom of the active layer. By exploiting the time lags and the one-dimensional heat transfer model of soils, we estimate the ALTs. Using the frozen soil region in southern Qinghai-Tibet Plateau (QTP) as examples, we provided a conceptual demonstration of the estimation of the InSAR pixel-wise ALTs. In the case study, the ALTs are ranging from 1.02 to 3.14 m and with an average of 1.95 m. The results are compatible with those sparse ALT observations/estimations by traditional methods, while with extraordinary high spatial resolution at pixel level (~40 meter). The presented method is simple, and can potentially be used for deriving high-resolution ALTs in other remote areas similar to QTP, where only sparse observations are available now. PMID:26480892

InSAR analysis of surface deformation over permafrost to estimate active layer thickness based on one-dimensional heat transfer model of soils.

PubMed

Li, Zhiwei; Zhao, Rong; Hu, Jun; Wen, Lianxing; Feng, Guangcai; Zhang, Zeyu; Wang, Qijie

2015-10-20

This paper presents a novel method to estimate active layer thickness (ALT) over permafrost based on InSAR (Interferometric Synthetic Aperture Radar) observation and the heat transfer model of soils. The time lags between the periodic feature of InSAR-observed surface deformation over permafrost and the meteorologically recorded temperatures are assumed to be the time intervals that the temperature maximum to diffuse from the ground surface downward to the bottom of the active layer. By exploiting the time lags and the one-dimensional heat transfer model of soils, we estimate the ALTs. Using the frozen soil region in southern Qinghai-Tibet Plateau (QTP) as examples, we provided a conceptual demonstration of the estimation of the InSAR pixel-wise ALTs. In the case study, the ALTs are ranging from 1.02 to 3.14 m and with an average of 1.95 m. The results are compatible with those sparse ALT observations/estimations by traditional methods, while with extraordinary high spatial resolution at pixel level (~40 meter). The presented method is simple, and can potentially be used for deriving high-resolution ALTs in other remote areas similar to QTP, where only sparse observations are available now.

Do subitizing deficits in developmental dyscalculia involve pattern recognition weakness?

PubMed

Ashkenazi, Sarit; Mark-Zigdon, Nitza; Henik, Avishai

2013-01-01

The abilities of children diagnosed with developmental dyscalculia (DD) were examined in two types of object enumeration: subitizing, and small estimation (5-9 dots). Subitizing is usually defined as a fast and accurate assessment of a number of small dots (range 1 to 4 dots), and estimation is an imprecise process to assess a large number of items (range 5 dots or more). Based on reaction time (RT) and accuracy analysis, our results indicated a deficit in the subitizing and small estimation range among DD participants in relation to controls. There are indications that subitizing is based on pattern recognition, thus presenting dots in a canonical shape in the estimation range should result in a subitizing-like pattern. In line with this theory, our control group presented a subitizing-like pattern in the small estimation range for canonically arranged dots, whereas the DD participants presented a deficit in the estimation of canonically arranged dots. The present finding indicates that pattern recognition difficulties may play a significant role in both subitizing and subitizing deficits among those with DD. © 2012 Blackwell Publishing Ltd.

Using Empirical Mode Decomposition to process Marine Magnetotelluric Data

NASA Astrophysics Data System (ADS)

Chen, J.; Jegen, M. D.; Heincke, B. H.; Moorkamp, M.

2014-12-01

The magnetotelluric (MT) data always exhibits nonstationarities due to variations of source mechanisms causing MT variations on different time and spatial scales. An additional non-stationary component is introduced through noise, which is particularly pronounced in marine MT data through motion induced noise caused by time-varying wave motion and currents. We present a new heuristic method for dealing with the non-stationarity of MT time series based on Empirical Mode Decomposition (EMD). The EMD method is used in combination with the derived instantaneous spectra to determine impedance estimates. The procedure is tested on synthetic and field MT data. In synthetic tests the reliability of impedance estimates from EMD-based method is compared to the synthetic responses of a 1D layered model. To examine how estimates are affected by noise, stochastic stationary and non-stationary noise are added on the time series. Comparisons reveal that estimates by the EMD-based method are generally more stable than those by simple Fourier analysis. Furthermore, the results are compared to those derived by a commonly used Fourier-based MT data processing software (BIRRP), which incorporates additional sophisticated robust estimations to deal with noise issues. It is revealed that the results from both methods are already comparable, even though no robust estimate procedures are implemented in the EMD approach at present stage. The processing scheme is then applied to marine MT field data. Testing is performed on short, relatively quiet segments of several data sets, as well as on long segments of data with many non-stationary noise packages. Compared to BIRRP, the new method gives comparable or better impedance estimates, furthermore, the estimates are extended to lower frequencies and less noise biased estimates with smaller error bars are obtained at high frequencies. The new processing methodology represents an important step towards deriving a better resolved Earth model to greater depth underneath the seafloor.

Motion Field Estimation for a Dynamic Scene Using a 3D LiDAR

PubMed Central

Li, Qingquan; Zhang, Liang; Mao, Qingzhou; Zou, Qin; Zhang, Pin; Feng, Shaojun; Ochieng, Washington

2014-01-01

This paper proposes a novel motion field estimation method based on a 3D light detection and ranging (LiDAR) sensor for motion sensing for intelligent driverless vehicles and active collision avoidance systems. Unlike multiple target tracking methods, which estimate the motion state of detected targets, such as cars and pedestrians, motion field estimation regards the whole scene as a motion field in which each little element has its own motion state. Compared to multiple target tracking, segmentation errors and data association errors have much less significance in motion field estimation, making it more accurate and robust. This paper presents an intact 3D LiDAR-based motion field estimation method, including pre-processing, a theoretical framework for the motion field estimation problem and practical solutions. The 3D LiDAR measurements are first projected to small-scale polar grids, and then, after data association and Kalman filtering, the motion state of every moving grid is estimated. To reduce computing time, a fast data association algorithm is proposed. Furthermore, considering the spatial correlation of motion among neighboring grids, a novel spatial-smoothing algorithm is also presented to optimize the motion field. The experimental results using several data sets captured in different cities indicate that the proposed motion field estimation is able to run in real-time and performs robustly and effectively. PMID:25207868

Motion field estimation for a dynamic scene using a 3D LiDAR.

PubMed

Li, Qingquan; Zhang, Liang; Mao, Qingzhou; Zou, Qin; Zhang, Pin; Feng, Shaojun; Ochieng, Washington

2014-09-09

This paper proposes a novel motion field estimation method based on a 3D light detection and ranging (LiDAR) sensor for motion sensing for intelligent driverless vehicles and active collision avoidance systems. Unlike multiple target tracking methods, which estimate the motion state of detected targets, such as cars and pedestrians, motion field estimation regards the whole scene as a motion field in which each little element has its own motion state. Compared to multiple target tracking, segmentation errors and data association errors have much less significance in motion field estimation, making it more accurate and robust. This paper presents an intact 3D LiDAR-based motion field estimation method, including pre-processing, a theoretical framework for the motion field estimation problem and practical solutions. The 3D LiDAR measurements are first projected to small-scale polar grids, and then, after data association and Kalman filtering, the motion state of every moving grid is estimated. To reduce computing time, a fast data association algorithm is proposed. Furthermore, considering the spatial correlation of motion among neighboring grids, a novel spatial-smoothing algorithm is also presented to optimize the motion field. The experimental results using several data sets captured in different cities indicate that the proposed motion field estimation is able to run in real-time and performs robustly and effectively.

Time distortion when users at-risk for social media addiction engage in non-social media tasks.

PubMed

Turel, Ofir; Brevers, Damien; Bechara, Antoine

2018-02-01

There is a growing concern over the addictiveness of Social Media use. Additional representative indicators of impaired control are needed in order to distinguish presumed social media addiction from normal use. (1) To examine the existence of time distortion during non-social media use tasks that involve social media cues among those who may be considered at-risk for social media addiction. (2) To examine the usefulness of this distortion for at-risk vs. low/no-risk classification. We used a task that prevented Facebook use and invoked Facebook reflections (survey on self-control strategies) and subsequently measured estimated vs. actual task completion time. We captured the level of addiction using the Bergen Facebook Addiction Scale in the survey, and we used a common cutoff criterion to classify people as at-risk vs. low/no-risk of Facebook addiction. The at-risk group presented significant upward time estimate bias and the low/no-risk group presented significant downward time estimate bias. The bias was positively correlated with Facebook addiction scores. It was efficacious, especially when combined with self-reported estimates of extent of Facebook use, in classifying people to the two categories. Our study points to a novel, easy to obtain, and useful marker of at-risk for social media addiction, which may be considered for inclusion in diagnosis tools and procedures. Copyright © 2017 Elsevier Ltd. All rights reserved.

Stochastic Residual-Error Analysis For Estimating Hydrologic Model Predictive Uncertainty

EPA Science Inventory

A hybrid time series-nonparametric sampling approach, referred to herein as semiparametric, is presented for the estimation of model predictive uncertainty. The methodology is a two-step procedure whereby a distributed hydrologic model is first calibrated, then followed by brute ...

Efficient algorithms for single-axis attitude estimation

NASA Technical Reports Server (NTRS)

Shuster, M. D.

1981-01-01

The computationally efficient algorithms determine attitude from the measurement of art lengths and dihedral angles. The dependence of these algorithms on the solution of trigonometric equations was reduced. Both single time and batch estimators are presented along with the covariance analysis of each algorithm.

FracFit: A Robust Parameter Estimation Tool for Anomalous Transport Problems

NASA Astrophysics Data System (ADS)

Kelly, J. F.; Bolster, D.; Meerschaert, M. M.; Drummond, J. D.; Packman, A. I.

2016-12-01

Anomalous transport cannot be adequately described with classical Fickian advection-dispersion equations (ADE). Rather, fractional calculus models may be used, which capture non-Fickian behavior (e.g. skewness and power-law tails). FracFit is a robust parameter estimation tool based on space- and time-fractional models used to model anomalous transport. Currently, four fractional models are supported: 1) space fractional advection-dispersion equation (sFADE), 2) time-fractional dispersion equation with drift (TFDE), 3) fractional mobile-immobile equation (FMIE), and 4) tempered fractional mobile-immobile equation (TFMIE); additional models may be added in the future. Model solutions using pulse initial conditions and continuous injections are evaluated using stable distribution PDFs and CDFs or subordination integrals. Parameter estimates are extracted from measured breakthrough curves (BTCs) using a weighted nonlinear least squares (WNLS) algorithm. Optimal weights for BTCs for pulse initial conditions and continuous injections are presented, facilitating the estimation of power-law tails. Two sample applications are analyzed: 1) continuous injection laboratory experiments using natural organic matter and 2) pulse injection BTCs in the Selke river. Model parameters are compared across models and goodness-of-fit metrics are presented, assisting model evaluation. The sFADE and time-fractional models are compared using space-time duality (Baeumer et. al., 2009), which links the two paradigms.

An exploration of emergency department presentations related to high heel footwear in Victoria, Australia, 2006-2010.

PubMed

Williams, Cylie M; Haines, Terry P

2014-01-23

Many women are warned against the dangers of wearing high heel footwear however there is limited empirical evidence demonstrating an association between wearing high heel with injury. Gait laboratory testing has found a higher heel height placed the foot in a position that increases the risk of ankle sprain. Women have also been surveyed about wearing high heels and approximately half of those reported inconvenience and pain after wearing a high heel shoe. This study aims to explore emergency department presentations of injuries and the estimated costs that have been directly attributed to wearing high heeled footwear within Victoria, Australia during 2006-2010. The Victorian Emergency Minimum Dataset (VEMD) was searched for all injuries attributed to wearing high heel footwear presenting to emergency departments in Victoria Australia, between the years of 2006-2010. The VEMD produced a report detailing sex, age at presentation, month of presentation, time of day of presentation, day of presentation, location that injury occurred and type of injury for presentation. Monash Health in Victoria Australia, provided emergency department estimates for injury types to calculate an estimated cost of an acute injury related to wearing high heel footwear. There were 240 injuries presenting to Victorian emergency departments directly attributed to wearing high heeled footwear. The majority of people injured were women (n = 236) and all were less than 55 years of age. More injuries presented on a Sunday (n = 83) and more in the 8 am-12 pm time bracket (n = 64). There were also more injuries presenting in the months of November, December and January (n = 80). The most commonly injured body part was the ankle (n = 123). The emergency department estimate of the cost of these injuries over this time-frame was almost $72,000 (mean of $316.72 per presentation). People who wear high heel footwear on weekends appear to be at higher risk for injury that leads to emergency department presentation. However, there was not a large cost associated with emergency department presentations attributable to wearing high heel footwear over a 5 year period.

An exploration of emergency department presentations related to high heel footwear in Victoria, Australia, 2006–2010

PubMed Central

2014-01-01

Background Many women are warned against the dangers of wearing high heel footwear however there is limited empirical evidence demonstrating an association between wearing high heel with injury. Gait laboratory testing has found a higher heel height placed the foot in a position that increases the risk of ankle sprain. Women have also been surveyed about wearing high heels and approximately half of those reported inconvenience and pain after wearing a high heel shoe. This study aims to explore emergency department presentations of injuries and the estimated costs that have been directly attributed to wearing high heeled footwear within Victoria, Australia during 2006–2010. Methods The Victorian Emergency Minimum Dataset (VEMD) was searched for all injuries attributed to wearing high heel footwear presenting to emergency departments in Victoria Australia, between the years of 2006–2010. The VEMD produced a report detailing sex, age at presentation, month of presentation, time of day of presentation, day of presentation, location that injury occurred and type of injury for presentation. Monash Health in Victoria Australia, provided emergency department estimates for injury types to calculate an estimated cost of an acute injury related to wearing high heel footwear. Results There were 240 injuries presenting to Victorian emergency departments directly attributed to wearing high heeled footwear. The majority of people injured were women (n = 236) and all were less than 55 years of age. More injuries presented on a Sunday (n = 83) and more in the 8 am-12 pm time bracket (n = 64). There were also more injuries presenting in the months of November, December and January (n = 80). The most commonly injured body part was the ankle (n = 123). The emergency department estimate of the cost of these injuries over this time-frame was almost $72,000 (mean of $316.72 per presentation). Conclusions People who wear high heel footwear on weekends appear to be at higher risk for injury that leads to emergency department presentation. However, there was not a large cost associated with emergency department presentations attributable to wearing high heel footwear over a 5 year period. PMID:24456691

Neural networks for tracking of unknown SISO discrete-time nonlinear dynamic systems.

PubMed

Aftab, Muhammad Saleheen; Shafiq, Muhammad

2015-11-01

This article presents a Lyapunov function based neural network tracking (LNT) strategy for single-input, single-output (SISO) discrete-time nonlinear dynamic systems. The proposed LNT architecture is composed of two feedforward neural networks operating as controller and estimator. A Lyapunov function based back propagation learning algorithm is used for online adjustment of the controller and estimator parameters. The controller and estimator error convergence and closed-loop system stability analysis is performed by Lyapunov stability theory. Moreover, two simulation examples and one real-time experiment are investigated as case studies. The achieved results successfully validate the controller performance. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Typical teleoperator time delay profiles, phase 2. [remotely controlled manipulator arms

NASA Technical Reports Server (NTRS)

Wetherington, R. D.; Walsh, J. R.

1974-01-01

The results of the second phase of a study on time delays in communications systems applicable to the teleoperator program are presented. Estimates of the maximum time delays that will be encountered and presents time delay profiles are given for (1) ground control to teleoperator in low earth orbit, (2) ground control to teleoperator in geosynchronous orbit, and (3) low earth orbit control to teleoperator in low earth orbit.

Estimating latent time of maturation and survival costs of reproduction in continuous time from capture-recapture data

USGS Publications Warehouse

Ergon, T.; Yoccoz, N.G.; Nichols, J.D.; Thomson, David L.; Cooch, Evan G.; Conroy, Michael J.

2009-01-01

In many species, age or time of maturation and survival costs of reproduction may vary substantially within and among populations. We present a capture-mark-recapture model to estimate the latent individual trait distribution of time of maturation (or other irreversible transitions) as well as survival differences associated with the two states (representing costs of reproduction). Maturation can take place at any point in continuous time, and mortality hazard rates for each reproductive state may vary according to continuous functions over time. Although we explicitly model individual heterogeneity in age/time of maturation, we make the simplifying assumption that death hazard rates do not vary among individuals within groups of animals. However, the estimates of the maturation distribution are fairly robust against individual heterogeneity in survival as long as there is no individual level correlation between mortality hazards and latent time of maturation. We apply the model to biweekly capture?recapture data of overwintering field voles (Microtus agrestis) in cyclically fluctuating populations to estimate time of maturation and survival costs of reproduction. Results show that onset of seasonal reproduction is particularly late and survival costs of reproduction are particularly large in declining populations.

Annual Estimates of Global Anthropogenic Methane Emissions: 1860-1994

DOE Data Explorer

Stern, David I. [Boston Univ., MA (United States); Kaufmann, Robert K. [Boston Univ., MA (United States)

1998-01-01

The authors provide the first estimates, by year, of global man-made emissions of methane, from 1860 through 1994. The methods, including the rationale for the various coefficients and assumptions used in deriving the estimates, are described fully in Stern and Kaufmann (1995, 1996), which provides the estimates for the period 1860-1993; the data presented here are revised and updated through 1994. Some formulae and coefficients were also revised in that process. Estimates are provided for total anthropogenic emissions, as well as emissions for the following component categories: Flaring and Venting of Natural Gas; Oil and Gas Supply Systems, Excluding Flaring; Coal Mining; Biomass Burning; Livestock Farming; Rice Farming and Related Activities; Landfills. Changes in emissions over time were estimated by treating emissions as a function of variables (such as population or coal production) for which historical time series are available.

Predicting Loss-of-Control Boundaries Toward a Piloting Aid

NASA Technical Reports Server (NTRS)

Barlow, Jonathan; Stepanyan, Vahram; Krishnakumar, Kalmanje

2012-01-01

This work presents an approach to predicting loss-of-control with the goal of providing the pilot a decision aid focused on maintaining the pilot's control action within predicted loss-of-control boundaries. The predictive architecture combines quantitative loss-of-control boundaries, a data-based predictive control boundary estimation algorithm and an adaptive prediction method to estimate Markov model parameters in real-time. The data-based loss-of-control boundary estimation algorithm estimates the boundary of a safe set of control inputs that will keep the aircraft within the loss-of-control boundaries for a specified time horizon. The adaptive prediction model generates estimates of the system Markov Parameters, which are used by the data-based loss-of-control boundary estimation algorithm. The combined algorithm is applied to a nonlinear generic transport aircraft to illustrate the features of the architecture.

Food consumption and digestion time estimation of spotted scat, Scatophagus argus, using X-radiography technique

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hashim, Marina; Abidin, Diana Atiqah Zainal; Das, Simon K.

The present study was conducted to investigate the food consumption pattern and gastric emptying time using x-radiography technique in scats fish, Scatophagus argus feeding to satiation in laboratory conditions. Prior to feeding experiment, fish of various sizes were examined their stomach volume, using freshly prepared stomachs ligatured at the tips of the burret, where the maximum amount of distilled water collected in the stomach were measured (ml). Stomach volume is correlated with maximum food intake (S{sub max}) and it can estimate the maximum stomach distension by allometric model i.e volume=0.0000089W{sup 2.93}. Gastric emptying time was estimated using a qualitative X-radiographymore » technique, where the fish of various sizes were fed to satiation at different time since feeding. All the experimental fish was feed into satiation using radio-opaque barium sulphate (BaSO{sub 4}) paste injected in the wet shrimp in proportion to the body weight. The BaSO{sub 4} was found suitable to track the movement of feed/prey in the stomach over time and gastric emptying time of scats fish can be estimated. The results of qualitative X-Radiography observation of gastric motility, showed the fish (200 gm) that fed to maximum satiation meal (circa 11 gm) completely emptied their stomach within 30 - 36 hrs. The results of the present study will provide the first baseline information on the stomach volume, gastric emptying of scats fish in captivity.« less

Food consumption and digestion time estimation of spotted scat, Scatophagus argus, using X-radiography technique

NASA Astrophysics Data System (ADS)

Hashim, Marina; Abidin, Diana Atiqah Zainal; Das, Simon K.; Ghaffar, Mazlan Abd.

2014-09-01

The present study was conducted to investigate the food consumption pattern and gastric emptying time using x-radiography technique in scats fish, Scatophagus argus feeding to satiation in laboratory conditions. Prior to feeding experiment, fish of various sizes were examined their stomach volume, using freshly prepared stomachs ligatured at the tips of the burret, where the maximum amount of distilled water collected in the stomach were measured (ml). Stomach volume is correlated with maximum food intake (Smax) and it can estimate the maximum stomach distension by allometric model i.e volume=0.0000089W2.93. Gastric emptying time was estimated using a qualitative X-radiography technique, where the fish of various sizes were fed to satiation at different time since feeding. All the experimental fish was feed into satiation using radio-opaque barium sulphate (BaSO4) paste injected in the wet shrimp in proportion to the body weight. The BaSO4 was found suitable to track the movement of feed/prey in the stomach over time and gastric emptying time of scats fish can be estimated. The results of qualitative X-Radiography observation of gastric motility, showed the fish (200 gm) that fed to maximum satiation meal (circa 11 gm) completely emptied their stomach within 30 - 36 hrs. The results of the present study will provide the first baseline information on the stomach volume, gastric emptying of scats fish in captivity.

An interview technique for recording work postures in epidemiological studies. Music-Norrtälje Study Group.

PubMed

Wiktorin, C; Selin, K; Ekenvall, L; Alfredsson, L

1996-02-01

The aim of the study was to present and evaluate a work-task-oriented interview technique focusing on the placement of the hands relative to the body and assessing per cent time spent in five standard work postures during a working day. The reproducibility of estimated time spent in each work posture was tested by the test-retest method in 32 subjects; 16 were interviewed by the same interviewer and 16 were interviewed by another one at the retest. The validity concerning estimated time spent in th five standard work postures was tested in relation to observations in 58 male blue-collar workers. The mean registration (assessment) time was 6 hours and 15 minutes. No evident differences in the reproducibility depending on same or different interviewers at test and retest could be observed. The linear relationship between times estimated by the interview and by observations was high for four of the work postures: 'sitting' (r = 0.86), 'standing with hands above shoulder level' (r = 0.87), 'between shoulder and knuckle level' (r = 0.75), and 'below knuckle level' (r = 0.93). When the work posture 'standing with hands between shoulder and knuckle level' was divided into 'hands fixed' (r = 0.62) and 'hands not fixed' (r = 0.50) the correlations were weak. Current musculoskeletal complaints did not influence the accuracy of the estimations. The present task-oriented interview technique may be the best available method to estimate these work postures in a way that requires few resources compared to observations and technical measurements.

Regression analysis of clustered failure time data with informative cluster size under the additive transformation models.

PubMed

Chen, Ling; Feng, Yanqin; Sun, Jianguo

2017-10-01

This paper discusses regression analysis of clustered failure time data, which occur when the failure times of interest are collected from clusters. In particular, we consider the situation where the correlated failure times of interest may be related to cluster sizes. For inference, we present two estimation procedures, the weighted estimating equation-based method and the within-cluster resampling-based method, when the correlated failure times of interest arise from a class of additive transformation models. The former makes use of the inverse of cluster sizes as weights in the estimating equations, while the latter can be easily implemented by using the existing software packages for right-censored failure time data. An extensive simulation study is conducted and indicates that the proposed approaches work well in both the situations with and without informative cluster size. They are applied to a dental study that motivated this study.

A quantile regression model for failure-time data with time-dependent covariates

PubMed Central

Gorfine, Malka; Goldberg, Yair; Ritov, Ya’acov

2017-01-01

Summary Since survival data occur over time, often important covariates that we wish to consider also change over time. Such covariates are referred as time-dependent covariates. Quantile regression offers flexible modeling of survival data by allowing the covariates to vary with quantiles. This article provides a novel quantile regression model accommodating time-dependent covariates, for analyzing survival data subject to right censoring. Our simple estimation technique assumes the existence of instrumental variables. In addition, we present a doubly-robust estimator in the sense of Robins and Rotnitzky (1992, Recovery of information and adjustment for dependent censoring using surrogate markers. In: Jewell, N. P., Dietz, K. and Farewell, V. T. (editors), AIDS Epidemiology. Boston: Birkhaäuser, pp. 297–331.). The asymptotic properties of the estimators are rigorously studied. Finite-sample properties are demonstrated by a simulation study. The utility of the proposed methodology is demonstrated using the Stanford heart transplant dataset. PMID:27485534

A double hit model for the distribution of time to AIDS onset

NASA Astrophysics Data System (ADS)

Chillale, Nagaraja Rao

2013-09-01

Incubation time is a key epidemiologic descriptor of an infectious disease. In the case of HIV infection this is a random variable and is probably the longest one. The probability distribution of incubation time is the major determinant of the relation between the incidences of HIV infection and its manifestation to Aids. This is also one of the key factors used for accurate estimation of AIDS incidence in a region. The present article i) briefly reviews the work done, points out uncertainties in estimation of AIDS onset time and stresses the need for its precise estimation, ii) highlights some of the modelling features of onset distribution including immune failure mechanism, and iii) proposes a 'Double Hit' model for the distribution of time to AIDS onset in the cases of (a) independent and (b) dependent time variables of the two markers and examined the applicability of a few standard probability models.

Analytical model for real time, noninvasive estimation of blood glucose level.

PubMed

Adhyapak, Anoop; Sidley, Matthew; Venkataraman, Jayanti

2014-01-01

The paper presents an analytical model to estimate blood glucose level from measurements made non-invasively and in real time by an antenna strapped to a patient's wrist. Some promising success has been shown by the RIT ETA Lab research group that an antenna's resonant frequency can track, in real time, changes in glucose concentration. Based on an in-vitro study of blood samples of diabetic patients, the paper presents a modified Cole-Cole model that incorporates a factor to represent the change in glucose level. A calibration technique using the input impedance technique is discussed and the results show a good estimation as compared to the glucose meter readings. An alternate calibration methodology has been developed that is based on the shift in the antenna resonant frequency using an equivalent circuit model containing a shunt capacitor to represent the shift in resonant frequency with changing glucose levels. Work under progress is the optimization of the technique with a larger sample of patients.

Using hypothetical data to assess the effect of numerical format and context on the perception of coronary heart disease risk.

PubMed

Fair, Anna K I; Murray, Peter G; Thomas, Anna; Cobain, Mark R

2008-01-01

To test the hypothesis that responses to coronary heart disease (CHD) risk estimates are heightened by use of ratio formats, peer group risk information, and long time frames. Cross-sectional, experimental, between-factors design. Three regions in England. A total of 740 men and women ages 30 to 70 years. Risk perception, "emotional" response, intention to change lifestyle. Logistic regression was used to investigate the impact of numerical format (ratio vs. percentage), peer group risk (personal vs. peer group), and time frame (10-year vs. 30-year) on risk perception. Analysis of variance was used to investigate the impact of these factors on emotional response and intention to change lifestyle questions. Higher perceived risk was observed when risk was presented as a ratio (p < .001) and when it was supplemented with peer group risk estimates (p = .006). Emotional responses to risk information were heightened when risk was presented as a ratio (p = .0004) and supplemented with peer group risk estimates (p = .002). Presentation with ratios also increased intention to make lifestyle changes (p = .047). Perception of CHD risk information is affected by the presentation format. Where absolute risks may appear low, use of ratios and supplementation of personal risk estimates with peer group risk may increase risk perception.

Discrete-time state estimation for stochastic polynomial systems over polynomial observations

NASA Astrophysics Data System (ADS)

Hernandez-Gonzalez, M.; Basin, M.; Stepanov, O.

2018-07-01

This paper presents a solution to the mean-square state estimation problem for stochastic nonlinear polynomial systems over polynomial observations confused with additive white Gaussian noises. The solution is given in two steps: (a) computing the time-update equations and (b) computing the measurement-update equations for the state estimate and error covariance matrix. A closed form of this filter is obtained by expressing conditional expectations of polynomial terms as functions of the state estimate and error covariance. As a particular case, the mean-square filtering equations are derived for a third-degree polynomial system with second-degree polynomial measurements. Numerical simulations show effectiveness of the proposed filter compared to the extended Kalman filter.

Application of multivariate autoregressive spectrum estimation to ULF waves

NASA Technical Reports Server (NTRS)

Ioannidis, G. A.

1975-01-01

The estimation of the power spectrum of a time series by fitting a finite autoregressive model to the data has recently found widespread application in the physical sciences. The extension of this method to the analysis of vector time series is presented here through its application to ULF waves observed in the magnetosphere by the ATS 6 synchronous satellite. Autoregressive spectral estimates of the power and cross-power spectra of these waves are computed with computer programs developed by the author and are compared with the corresponding Blackman-Tukey spectral estimates. The resulting spectral density matrices are then analyzed to determine the direction of propagation and polarization of the observed waves.

Freeway travel-time estimation and forecasting.

DOT National Transportation Integrated Search

2012-09-01

This project presents a microsimulation-based framework for generating short-term forecasts of travel time on freeway corridors. The microsimulation model that is developed (GTsim), replicates freeway capacity drop and relaxation phenomena critical f...

Time-of-flight PET time calibration using data consistency

NASA Astrophysics Data System (ADS)

Defrise, Michel; Rezaei, Ahmadreza; Nuyts, Johan

2018-05-01

This paper presents new data driven methods for the time of flight (TOF) calibration of positron emission tomography (PET) scanners. These methods are derived from the consistency condition for TOF PET, they can be applied to data measured with an arbitrary tracer distribution and are numerically efficient because they do not require a preliminary image reconstruction from the non-TOF data. Two-dimensional simulations are presented for one of the methods, which only involves the two first moments of the data with respect to the TOF variable. The numerical results show that this method estimates the detector timing offsets with errors that are larger than those obtained via an initial non-TOF reconstruction, but remain smaller than of the TOF resolution and thereby have a limited impact on the quantitative accuracy of the activity image estimated with standard maximum likelihood reconstruction algorithms.

Babies in traffic: infant vocalizations and listener sex modulate auditory motion perception.

PubMed

Neuhoff, John G; Hamilton, Grace R; Gittleson, Amanda L; Mejia, Adolfo

2014-04-01

Infant vocalizations and "looming sounds" are classes of environmental stimuli that are critically important to survival but can have dramatically different emotional valences. Here, we simultaneously presented listeners with a stationary infant vocalization and a 3D virtual looming tone for which listeners made auditory time-to-arrival judgments. Negatively valenced infant cries produced more cautious (anticipatory) estimates of auditory arrival time of the tone over a no-vocalization control. Positively valenced laughs had the opposite effect, and across all conditions, men showed smaller anticipatory biases than women. In Experiment 2, vocalization-matched vocoded noise stimuli did not influence concurrent auditory time-to-arrival estimates compared with a control condition. In Experiment 3, listeners estimated the egocentric distance of a looming tone that stopped before arriving. For distant stopping points, women estimated the stopping point as closer when the tone was presented with an infant cry than when it was presented with a laugh. For near stopping points, women showed no differential effect of vocalization type. Men did not show differential effects of vocalization type at either distance. Our results support the idea that both the sex of the listener and the emotional valence of infant vocalizations can influence auditory motion perception and can modulate motor responses to other behaviorally relevant environmental sounds. We also find support for previous work that shows sex differences in emotion processing are diminished under conditions of higher stress.

Estimating time-varying exposure-outcome associations using case-control data: logistic and case-cohort analyses.

PubMed

Keogh, Ruth H; Mangtani, Punam; Rodrigues, Laura; Nguipdop Djomo, Patrick

2016-01-05

Traditional analyses of standard case-control studies using logistic regression do not allow estimation of time-varying associations between exposures and the outcome. We present two approaches which allow this. The motivation is a study of vaccine efficacy as a function of time since vaccination. Our first approach is to estimate time-varying exposure-outcome associations by fitting a series of logistic regressions within successive time periods, reusing controls across periods. Our second approach treats the case-control sample as a case-cohort study, with the controls forming the subcohort. In the case-cohort analysis, controls contribute information at all times they are at risk. Extensions allow left truncation, frequency matching and, using the case-cohort analysis, time-varying exposures. Simulations are used to investigate the methods. The simulation results show that both methods give correct estimates of time-varying effects of exposures using standard case-control data. Using the logistic approach there are efficiency gains by reusing controls over time and care should be taken over the definition of controls within time periods. However, using the case-cohort analysis there is no ambiguity over the definition of controls. The performance of the two analyses is very similar when controls are used most efficiently under the logistic approach. Using our methods, case-control studies can be used to estimate time-varying exposure-outcome associations where they may not previously have been considered. The case-cohort analysis has several advantages, including that it allows estimation of time-varying associations as a continuous function of time, while the logistic regression approach is restricted to assuming a step function form for the time-varying association.

Trajectory prediction for ballistic missiles based on boost-phase LOS measurements

NASA Astrophysics Data System (ADS)

Yeddanapudi, Murali; Bar-Shalom, Yaakov

1997-10-01

This paper addresses the problem of the estimation of the trajectory of a tactical ballistic missile using line of sight (LOS) measurements from one or more passive sensors (typically satellites). The major difficulties of this problem include: the estimation of the unknown time of launch, incorporation of (inaccurate) target thrust profiles to model the target dynamics during the boost phase and an overall ill-conditioning of the estimation problem due to poor observability of the target motion via the LOS measurements. We present a robust estimation procedure based on the Levenberg-Marquardt algorithm that provides both the target state estimate and error covariance taking into consideration the complications mentioned above. An important consideration in the defense against tactical ballistic missiles is the determination of the target position and error covariance at the acquisition range of a surveillance radar in the vicinity of the impact point. We present a systematic procedure to propagate the target state and covariance to a nominal time, when it is within the detection range of a surveillance radar to obtain a cueing volume. Mont Carlo simulation studies on typical single and two sensor scenarios indicate that the proposed algorithms are accurate in terms of the estimates and the estimator calculated covariances are consistent with the errors.

Micromechanics of transformation fields in ageing linear viscoelastic composites: effects of phase dissolution or precipitation

NASA Astrophysics Data System (ADS)

Honorio, Tulio

2017-11-01

Transformation fields, in an affine formulation characterizing mechanical behavior, describe a variety of physical phenomena regardless their origin. Different composites, notably geomaterials, present a viscoelastic behavior, which is, in some cases of industrial interest, ageing, i.e. it evolves independently with respect to time and loading time. Here, a general formulation of the micromechanics of prestressed or prestrained composites in Ageing Linear Viscoelasticity (ALV) is presented. Emphasis is put on the estimation of effective transformation fields in ALV. The result generalizes Ageing Linear Thermo- and Poro-Viscoelasticity and it can be used in approaches coping with a phase transformation. Additionally, the results are extended to the case of locally transforming materials due to non-coupled dissolution and/or precipitation of a given (elastic or viscoelastic) phase. The estimations of locally transforming composites can be made with respect to different morphologies. As an application, estimations of the coefficient of thermal expansion of a hydrating alite paste are presented.

Time series models on analysing mortality rates and acute childhood lymphoid leukaemia.

PubMed

Kis, Maria

2005-01-01

In this paper we demonstrate applying time series models on medical research. The Hungarian mortality rates were analysed by autoregressive integrated moving average models and seasonal time series models examined the data of acute childhood lymphoid leukaemia.The mortality data may be analysed by time series methods such as autoregressive integrated moving average (ARIMA) modelling. This method is demonstrated by two examples: analysis of the mortality rates of ischemic heart diseases and analysis of the mortality rates of cancer of digestive system. Mathematical expressions are given for the results of analysis. The relationships between time series of mortality rates were studied with ARIMA models. Calculations of confidence intervals for autoregressive parameters by tree methods: standard normal distribution as estimation and estimation of the White's theory and the continuous time case estimation. Analysing the confidence intervals of the first order autoregressive parameters we may conclude that the confidence intervals were much smaller than other estimations by applying the continuous time estimation model.We present a new approach to analysing the occurrence of acute childhood lymphoid leukaemia. We decompose time series into components. The periodicity of acute childhood lymphoid leukaemia in Hungary was examined using seasonal decomposition time series method. The cyclic trend of the dates of diagnosis revealed that a higher percent of the peaks fell within the winter months than in the other seasons. This proves the seasonal occurrence of the childhood leukaemia in Hungary.

Real-time vehicle noise cancellation techniques for gunshot acoustics

NASA Astrophysics Data System (ADS)

Ramos, Antonio L. L.; Holm, Sverre; Gudvangen, Sigmund; Otterlei, Ragnvald

2012-06-01

Acoustical sniper positioning systems rely on the detection and direction-of-arrival (DOA) estimation of the shockwave and the muzzle blast in order to provide an estimate of a potential snipers location. Field tests have shown that detecting and estimating the DOA of the muzzle blast is a rather difficult task in the presence of background noise sources, e.g., vehicle noise, especially in long range detection and absorbing terrains. In our previous work presented in the 2011 edition of this conference we highlight the importance of improving the SNR of the gunshot signals prior to the detection and recognition stages, aiming at lowering the false alarm and miss-detection rates and, thereby, increasing the reliability of the system. This paper reports on real-time noise cancellation techniques, like Spectral Subtraction and Adaptive Filtering, applied to gunshot signals. Our model assumes the background noise as being short-time stationary and uncorrelated to the impulsive gunshot signals. In practice, relatively long periods without signal occur and can be used to estimate the noise spectrum and its first and second order statistics as required in the spectral subtraction and adaptive filtering techniques, respectively. The results presented in this work are supported with extensive simulations based on real data.

Improving cluster-based missing value estimation of DNA microarray data.

PubMed

Brás, Lígia P; Menezes, José C

2007-06-01

We present a modification of the weighted K-nearest neighbours imputation method (KNNimpute) for missing values (MVs) estimation in microarray data based on the reuse of estimated data. The method was called iterative KNN imputation (IKNNimpute) as the estimation is performed iteratively using the recently estimated values. The estimation efficiency of IKNNimpute was assessed under different conditions (data type, fraction and structure of missing data) by the normalized root mean squared error (NRMSE) and the correlation coefficients between estimated and true values, and compared with that of other cluster-based estimation methods (KNNimpute and sequential KNN). We further investigated the influence of imputation on the detection of differentially expressed genes using SAM by examining the differentially expressed genes that are lost after MV estimation. The performance measures give consistent results, indicating that the iterative procedure of IKNNimpute can enhance the prediction ability of cluster-based methods in the presence of high missing rates, in non-time series experiments and in data sets comprising both time series and non-time series data, because the information of the genes having MVs is used more efficiently and the iterative procedure allows refining the MV estimates. More importantly, IKNN has a smaller detrimental effect on the detection of differentially expressed genes.

National health expenditures, 1990

PubMed Central

Levit, Katharine R.; Lazenby, Helen C.; Cowan, Cathy A.; Letsch, Suzanne W.

1991-01-01

During 1990, health expenditures as a share of gross national product rose to 12.2 percent, up from 11.6 percent in 1989. This dramatic increase is the second largest increase in the past three decades. The national health expenditure estimates presented in this article document rapidly rising health care costs and provide a context for understanding the health care financing crisis facing the Nation today. The 1990 national health expenditures incorporate the most recently available data. They differ from historical estimates presented in the preceding article. The length of time and complicated process of producing projections required use of 1989 national health expenditures—data available prior to the completion of the 1990 estimates presented here. PMID:10114934

Introduction to State Estimation of High-Rate System Dynamics.

PubMed

Hong, Jonathan; Laflamme, Simon; Dodson, Jacob; Joyce, Bryan

2018-01-13

Engineering systems experiencing high-rate dynamic events, including airbags, debris detection, and active blast protection systems, could benefit from real-time observability for enhanced performance. However, the task of high-rate state estimation is challenging, in particular for real-time applications where the rate of the observer's convergence needs to be in the microsecond range. This paper identifies the challenges of state estimation of high-rate systems and discusses the fundamental characteristics of high-rate systems. A survey of applications and methods for estimators that have the potential to produce accurate estimations for a complex system experiencing highly dynamic events is presented. It is argued that adaptive observers are important to this research. In particular, adaptive data-driven observers are advantageous due to their adaptability and lack of dependence on the system model.

Uncertainty estimates of altimetric Global Mean Sea Level timeseries

NASA Astrophysics Data System (ADS)

Scharffenberg, Martin; Hemming, Michael; Stammer, Detlef

2016-04-01

An attempt is being presented concerned with providing uncertainty measures for global mean sea level time series. For this purpose sea surface height (SSH) fields, simulated by the high resolution STORM/NCEP model for the period 1993 - 2010, were subsampled along altimeter tracks and processed similar to techniques used by five working groups to estimate GMSL. Results suggest that the spatial and temporal resolution have a substantial impact on GMSL estimates. Major impacts can especially result from the interpolation technique or the treatment of SSH outliers and easily lead to artificial temporal variability in the resulting time series.

Considerations for analysis of time-to-event outcomes measured with error: Bias and correction with SIMEX.

PubMed

Oh, Eric J; Shepherd, Bryan E; Lumley, Thomas; Shaw, Pamela A

2018-04-15

For time-to-event outcomes, a rich literature exists on the bias introduced by covariate measurement error in regression models, such as the Cox model, and methods of analysis to address this bias. By comparison, less attention has been given to understanding the impact or addressing errors in the failure time outcome. For many diseases, the timing of an event of interest (such as progression-free survival or time to AIDS progression) can be difficult to assess or reliant on self-report and therefore prone to measurement error. For linear models, it is well known that random errors in the outcome variable do not bias regression estimates. With nonlinear models, however, even random error or misclassification can introduce bias into estimated parameters. We compare the performance of 2 common regression models, the Cox and Weibull models, in the setting of measurement error in the failure time outcome. We introduce an extension of the SIMEX method to correct for bias in hazard ratio estimates from the Cox model and discuss other analysis options to address measurement error in the response. A formula to estimate the bias induced into the hazard ratio by classical measurement error in the event time for a log-linear survival model is presented. Detailed numerical studies are presented to examine the performance of the proposed SIMEX method under varying levels and parametric forms of the error in the outcome. We further illustrate the method with observational data on HIV outcomes from the Vanderbilt Comprehensive Care Clinic. Copyright © 2017 John Wiley & Sons, Ltd.

Generation and Validation of Spatial Distribution of Hourly Wind Speed Time-Series using Machine Learning

NASA Astrophysics Data System (ADS)

Veronesi, F.; Grassi, S.

2016-09-01

Wind resource assessment is a key aspect of wind farm planning since it allows to estimate the long term electricity production. Moreover, wind speed time-series at high resolution are helpful to estimate the temporal changes of the electricity generation and indispensable to design stand-alone systems, which are affected by the mismatch of supply and demand. In this work, we present a new generalized statistical methodology to generate the spatial distribution of wind speed time-series, using Switzerland as a case study. This research is based upon a machine learning model and demonstrates that statistical wind resource assessment can successfully be used for estimating wind speed time-series. In fact, this method is able to obtain reliable wind speed estimates and propagate all the sources of uncertainty (from the measurements to the mapping process) in an efficient way, i.e. minimizing computational time and load. This allows not only an accurate estimation, but the creation of precise confidence intervals to map the stochasticity of the wind resource for a particular site. The validation shows that machine learning can minimize the bias of the wind speed hourly estimates. Moreover, for each mapped location this method delivers not only the mean wind speed, but also its confidence interval, which are crucial data for planners.

Virtual Estimator for Piecewise Linear Systems Based on Observability Analysis

PubMed Central

Morales-Morales, Cornelio; Adam-Medina, Manuel; Cervantes, Ilse; Vela-Valdés and, Luis G.; García Beltrán, Carlos Daniel

2013-01-01

This article proposes a virtual sensor for piecewise linear systems based on observability analysis that is in function of a commutation law related with the system's outpu. This virtual sensor is also known as a state estimator. Besides, it presents a detector of active mode when the commutation sequences of each linear subsystem are arbitrary and unknown. For the previous, this article proposes a set of virtual estimators that discern the commutation paths of the system and allow estimating their output. In this work a methodology in order to test the observability for piecewise linear systems with discrete time is proposed. An academic example is presented to show the obtained results. PMID:23447007

New instantaneous frequency estimation method based on the use of image processing techniques

NASA Astrophysics Data System (ADS)

Borda, Monica; Nafornita, Ioan; Isar, Alexandru

2003-05-01

The aim of this paper is to present a new method for the estimation of the instantaneous frequency of a frequency modulated signal, corrupted by additive noise. This method represents an example of fusion of two theories: the time-frequency representations and the mathematical morphology. Any time-frequency representation of a useful signal is concentrated around its instantaneous frequency law and realizes the diffusion of the noise that perturbs the useful signal in the time - frequency plane. In this paper a new time-frequency representation, useful for the estimation of the instantaneous frequency, is proposed. This time-frequency representation is the product of two others time-frequency representations: the Wigner - Ville time-frequency representation and a new one obtained by filtering with a hard thresholding filter the Gabor representation of the signal to be processed. Using the image of this new time-frequency representation the instantaneous frequency of the useful signal can be extracted with the aid of some mathematical morphology operators: the conversion in binary form, the dilation and the skeleton. The simulations of the proposed method have proved its qualities. It is better than other estimation methods, like those based on the use of adaptive notch filters.

Estimation of Handling Qualities Parameters of the Tu-144 Supersonic Transport Aircraft from Flight Test Data

NASA Technical Reports Server (NTRS)

Curry, Timothy J.; Batterson, James G. (Technical Monitor)

2000-01-01

Low order equivalent system (LOES) models for the Tu-144 supersonic transport aircraft were identified from flight test data. The mathematical models were given in terms of transfer functions with a time delay by the military standard MIL-STD-1797A, "Flying Qualities of Piloted Aircraft," and the handling qualities were predicted from the estimated transfer function coefficients. The coefficients and the time delay in the transfer functions were estimated using a nonlinear equation error formulation in the frequency domain. Flight test data from pitch, roll, and yaw frequency sweeps at various flight conditions were used for parameter estimation. Flight test results are presented in terms of the estimated parameter values, their standard errors, and output fits in the time domain. Data from doublet maneuvers at the same flight conditions were used to assess the predictive capabilities of the identified models. The identified transfer function models fit the measured data well and demonstrated good prediction capabilities. The Tu-144 was predicted to be between level 2 and 3 for all longitudinal maneuvers and level I for all lateral maneuvers. High estimates of the equivalent time delay in the transfer function model caused the poor longitudinal rating.

A soft-computing methodology for noninvasive time-spatial temperature estimation.

PubMed

Teixeira, César A; Ruano, Maria Graça; Ruano, António E; Pereira, Wagner C A

2008-02-01

The safe and effective application of thermal therapies is restricted due to lack of reliable noninvasive temperature estimators. In this paper, the temporal echo-shifts of backscattered ultrasound signals, collected from a gel-based phantom, were tracked and assigned with the past temperature values as radial basis functions neural networks input information. The phantom was heated using a piston-like therapeutic ultrasound transducer. The neural models were assigned to estimate the temperature at different intensities and points arranged across the therapeutic transducer radial line (60 mm apart from the transducer face). Model inputs, as well as the number of neurons were selected using the multiobjective genetic algorithm (MOGA). The best attained models present, in average, a maximum absolute error less than 0.5 degrees C, which is pointed as the borderline between a reliable and an unreliable estimator in hyperthermia/diathermia. In order to test the spatial generalization capacity, the best models were tested using spatial points not yet assessed, and some of them presented a maximum absolute error inferior to 0.5 degrees C, being "elected" as the best models. It should be also stressed that these best models present implementational low-complexity, as desired for real-time applications.

Decadal variations in atmospheric water vapor time series estimated using GNSS, ERA-Interim, and synoptic data

NASA Astrophysics Data System (ADS)

Alshawaf, Fadwa; Dick, Galina; Heise, Stefan; Balidakis, Kyriakos; Schmidt, Torsten; Wickert, Jens

2017-04-01

Ground-based GNSS (Global Navigation Satellite Systems) have efficiently been used since the 1990s as a meteorological observing system. Recently scientists used GNSS time series of precipitable water vapor (PWV) for climate research although they may not be sufficiently long. In this work, we compare the trend estimated from GNSS time series with that estimated from European Center for Medium-RangeWeather Forecasts Reanalysis (ERA-Interim) data and meteorological measurements.We aim at evaluating climate evolution in Central Europe by monitoring different atmospheric variables such as temperature and PWV. PWV time series were obtained by three methods: 1) estimated from ground-based GNSS observations using the method of precise point positioning, 2) inferred from ERA-Interim data, and 3) determined based on daily surface measurements of temperature and relative humidity. The other variables are available from surface meteorological stations or received from ERA-Interim. The PWV trend component estimated from GNSS data strongly correlates (>70%) with that estimated from the other data sets. The linear trend is estimated by straight line fitting over 30 years of seasonally-adjusted PWV time series obtained using the meteorological measurements. The results show a positive trend in the PWV time series with an increase of 0.2-0.7 mm/decade with a mean standard deviations of 0.016 mm/decade. In this paper, we present the results at three GNSS stations. The temporal increment of the PWV correlates with the temporal increase in the temperature levels.

Bio-inspired vision based robot control using featureless estimations of time-to-contact.

PubMed

Zhang, Haijie; Zhao, Jianguo

2017-01-31

Marvelous vision based dynamic behaviors of insects and birds such as perching, landing, and obstacle avoidance have inspired scientists to propose the idea of time-to-contact, which is defined as the time for a moving observer to contact an object or surface if the current velocity is maintained. Since with only a vision sensor, time-to-contact can be directly estimated from consecutive images, it is widely used for a variety of robots to fulfill various tasks such as obstacle avoidance, docking, chasing, perching and landing. However, most of existing methods to estimate the time-to-contact need to extract and track features during the control process, which is time-consuming and cannot be applied to robots with limited computation power. In this paper, we adopt a featureless estimation method, extend this method to more general settings with angular velocities, and improve the estimation results using Kalman filtering. Further, we design an error based controller with gain scheduling strategy to control the motion of mobile robots. Experiments for both estimation and control are conducted using a customized mobile robot platform with low-cost embedded systems. Onboard experimental results demonstrate the effectiveness of the proposed approach, with the robot being controlled to successfully dock in front of a vertical wall. The estimation and control methods presented in this paper can be applied to computation-constrained miniature robots for agile locomotion such as landing, docking, or navigation.

DEKF system for crowding estimation by a multiple-model approach

NASA Astrophysics Data System (ADS)

Cravino, F.; Dellucca, M.; Tesei, A.

1994-03-01

A distributed extended Kalman filter (DEKF) network devoted to real-time crowding estimation for surveillance in complex scenes is presented. Estimation is carried out by extracting a set of significant features from sequences of images. Feature values are associated by virtual sensors with the estimated number of people using nonlinear models obtained in an off-line training phase. Different models are used, depending on the positions and dimensions of the crowded subareas detected in each image.

Robust time and frequency domain estimation methods in adaptive control

NASA Technical Reports Server (NTRS)

Lamaire, Richard Orville

1987-01-01

A robust identification method was developed for use in an adaptive control system. The type of estimator is called the robust estimator, since it is robust to the effects of both unmodeled dynamics and an unmeasurable disturbance. The development of the robust estimator was motivated by a need to provide guarantees in the identification part of an adaptive controller. To enable the design of a robust control system, a nominal model as well as a frequency-domain bounding function on the modeling uncertainty associated with this nominal model must be provided. Two estimation methods are presented for finding parameter estimates, and, hence, a nominal model. One of these methods is based on the well developed field of time-domain parameter estimation. In a second method of finding parameter estimates, a type of weighted least-squares fitting to a frequency-domain estimated model is used. The frequency-domain estimator is shown to perform better, in general, than the time-domain parameter estimator. In addition, a methodology for finding a frequency-domain bounding function on the disturbance is used to compute a frequency-domain bounding function on the additive modeling error due to the effects of the disturbance and the use of finite-length data. The performance of the robust estimator in both open-loop and closed-loop situations is examined through the use of simulations.

Psychosocial Assessment of Self-Harm Patients and Risk of Repeat Presentation: An Instrumental Variable Analysis Using Time of Hospital Presentation.

PubMed

Carroll, Robert; Metcalfe, Chris; Steeg, Sarah; Davies, Neil M; Cooper, Jayne; Kapur, Nav; Gunnell, David

2016-01-01

Clinical guidelines have recommended psychosocial assessment of self-harm patients for years, yet estimates of its impact on the risk of repeat self-harm vary. Assessing the association of psychosocial assessment with risk of repeat self-harm is challenging due to the effects of confounding by indication. We analysed data from a cohort study of 15,113 patients presenting to the emergency departments of three UK hospitals to investigate the association of psychosocial assessment with risk of repeat hospital presentation for self-harm. Time of day of hospital presentation was used as an instrument for psychosocial assessment, attempting to control for confounding by indication. Conventional regression analysis suggested psychosocial assessment was not associated with risk of repeat self-harm within 12 months (Risk Difference (RD) 0.00 95% confidence interval (95%CI) -0.01 to 0.02). In contrast, IV analysis suggested risk of repeat self-harm was reduced by 18% (RD -0.18, 95%CI -0.32 to -0.03) in those patients receiving a psychosocial assessment. However, the instrument of time of day did not remove all potential effects of confounding by indication, suggesting the IV effect estimate may be biased. We found that psychosocial assessments reduce risk of repeat self-harm. This is in-line with other non-randomised studies based on populations in which allocation to assessment was less subject to confounding by indication. However, as our instrument did not fully balance important confounders across time of day, the IV effect estimate should be interpreted with caution.

Investigating flow patterns and related dynamics in multi-instability turbulent plasmas using a three-point cross-phase time delay estimation velocimetry scheme

NASA Astrophysics Data System (ADS)

Brandt, C.; Thakur, S. C.; Tynan, G. R.

2016-04-01

Complexities of flow patterns in the azimuthal cross-section of a cylindrical magnetized helicon plasma and the corresponding plasma dynamics are investigated by means of a novel scheme for time delay estimation velocimetry. The advantage of this introduced method is the capability of calculating the time-averaged 2D velocity fields of propagating wave-like structures and patterns in complex spatiotemporal data. It is able to distinguish and visualize the details of simultaneously present superimposed entangled dynamics and it can be applied to fluid-like systems exhibiting frequently repeating patterns (e.g., waves in plasmas, waves in fluids, dynamics in planetary atmospheres, etc.). The velocity calculations are based on time delay estimation obtained from cross-phase analysis of time series. Each velocity vector is unambiguously calculated from three time series measured at three different non-collinear spatial points. This method, when applied to fast imaging, has been crucial to understand the rich plasma dynamics in the azimuthal cross-section of a cylindrical linear magnetized helicon plasma. The capabilities and the limitations of this velocimetry method are discussed and demonstrated for two completely different plasma regimes, i.e., for quasi-coherent wave dynamics and for complex broadband wave dynamics involving simultaneously present multiple instabilities.

Investigating flow patterns and related dynamics in multi-instability turbulent plasmas using a three-point cross-phase time delay estimation velocimetry scheme

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brandt, C.; Max-Planck-Institute for Plasma Physics, Wendelsteinstr. 1, D-17491 Greifswald; Thakur, S. C.

2016-04-15

Complexities of flow patterns in the azimuthal cross-section of a cylindrical magnetized helicon plasma and the corresponding plasma dynamics are investigated by means of a novel scheme for time delay estimation velocimetry. The advantage of this introduced method is the capability of calculating the time-averaged 2D velocity fields of propagating wave-like structures and patterns in complex spatiotemporal data. It is able to distinguish and visualize the details of simultaneously present superimposed entangled dynamics and it can be applied to fluid-like systems exhibiting frequently repeating patterns (e.g., waves in plasmas, waves in fluids, dynamics in planetary atmospheres, etc.). The velocity calculationsmore » are based on time delay estimation obtained from cross-phase analysis of time series. Each velocity vector is unambiguously calculated from three time series measured at three different non-collinear spatial points. This method, when applied to fast imaging, has been crucial to understand the rich plasma dynamics in the azimuthal cross-section of a cylindrical linear magnetized helicon plasma. The capabilities and the limitations of this velocimetry method are discussed and demonstrated for two completely different plasma regimes, i.e., for quasi-coherent wave dynamics and for complex broadband wave dynamics involving simultaneously present multiple instabilities.« less

Time-Varying Delay Estimation Applied to the Surface Electromyography Signals Using the Parametric Approach

NASA Astrophysics Data System (ADS)

Luu, Gia Thien; Boualem, Abdelbassit; Duy, Tran Trung; Ravier, Philippe; Butteli, Olivier

Muscle Fiber Conduction Velocity (MFCV) can be calculated from the time delay between the surface electromyographic (sEMG) signals recorded by electrodes aligned with the fiber direction. In order to take into account the non-stationarity during the dynamic contraction (the most daily life situation) of the data, the developed methods have to consider that the MFCV changes over time, which induces time-varying delays and the data is non-stationary (change of Power Spectral Density (PSD)). In this paper, the problem of TVD estimation is considered using a parametric method. First, the polynomial model of TVD has been proposed. Then, the TVD model parameters are estimated by using a maximum likelihood estimation (MLE) strategy solved by a deterministic optimization technique (Newton) and stochastic optimization technique, called simulated annealing (SA). The performance of the two techniques is also compared. We also derive two appropriate Cramer-Rao Lower Bounds (CRLB) for the estimated TVD model parameters and for the TVD waveforms. Monte-Carlo simulation results show that the estimation of both the model parameters and the TVD function is unbiased and that the variance obtained is close to the derived CRBs. A comparison with non-parametric approaches of the TVD estimation is also presented and shows the superiority of the method proposed.

The MusIC method: a fast and quasi-optimal solution to the muscle forces estimation problem.

PubMed

Muller, A; Pontonnier, C; Dumont, G

2018-02-01

The present paper aims at presenting a fast and quasi-optimal method of muscle forces estimation: the MusIC method. It consists in interpolating a first estimation in a database generated offline thanks to a classical optimization problem, and then correcting it to respect the motion dynamics. Three different cost functions - two polynomial criteria and a min/max criterion - were tested on a planar musculoskeletal model. The MusIC method provides a computation frequency approximately 10 times higher compared to a classical optimization problem with a relative mean error of 4% on cost function evaluation.

Approaches and Data Quality for Global Precipitation Estimation

NASA Astrophysics Data System (ADS)

Huffman, G. J.; Bolvin, D. T.; Nelkin, E. J.

2015-12-01

The space and time scales on which precipitation varies are small compared to the satellite coverage that we have, so it is necessary to merge "all" of the available satellite estimates. Differing retrieval capabilities from the various satellites require inter-calibration for the satellite estimates, while "morphing", i.e., Lagrangian time interpolation, is used to lengthen the period over which time interpolation is valid. Additionally, estimates from geostationary-Earth-orbit infrared data are plentiful, but of sufficiently lower quality compared to low-Earth-orbit passive microwave estimates that they are only used when needed. Finally, monthly surface precipitation gauge data can be used to reduce bias and improve patterns of occurrence for monthly satellite data, and short-interval satellite estimates can be improved with a simple scaling such that they sum to the monthly satellite-gauge combination. The presentation will briefly consider some of the design decisions for practical computation of the Global Precipitation Measurement (GPM) mission product Integrated Multi-satellitE Retrievals for GPM (IMERG), then examine design choices that maximize value for end users. For example, data fields are provided in the output file that provide insight into the basis for the estimated precipitation, including error, sensor providing the estimate, precipitation phase (solid/liquid), and intermediate precipitation estimates. Another important initiative is successive computations for the same data date/time at longer latencies as additional data are received, which for IMERG is currently done at 6 hours, 16 hours, and 3 months after observation time. Importantly, users require long records for each latency, which runs counter to the data archiving practices at most archive sites. As well, the assignment of Digital Object Identifiers (DOI's) for near-real-time data sets (at 6 and 16 hours for IMERG) is not a settled issue.

Temporal Relatedness: Personality and Behavioral Correlates

ERIC Educational Resources Information Center

Getsinger, Stephen H.

1975-01-01

Two studies explored the relationship of temporal relatedness to self actualization, sex, and certain temporal behaviors. Subjects who obtained higher time-relatedness scores demonstrated greater self-actualization, evaluated the present time mode more positively, overestimated time intervals in an estimation task, and performed less accurately in…

49 CFR 260.3 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-10-01

... subtitle IV of title 49, United States Code. (s) Subsidy cost of a direct loan means the net present value... the net present value, at the time when the guaranteed loan is disbursed, of the following estimated...

49 CFR 260.3 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-10-01

... subtitle IV of title 49, United States Code. (s) Subsidy cost of a direct loan means the net present value... the net present value, at the time when the guaranteed loan is disbursed, of the following estimated...

49 CFR 260.3 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-10-01

... subtitle IV of title 49, United States Code. (s) Subsidy cost of a direct loan means the net present value... the net present value, at the time when the guaranteed loan is disbursed, of the following estimated...

49 CFR 260.3 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-10-01

... subtitle IV of title 49, United States Code. (s) Subsidy cost of a direct loan means the net present value... the net present value, at the time when the guaranteed loan is disbursed, of the following estimated...

Making historic loss data comparable over time and place

NASA Astrophysics Data System (ADS)

Eichner, Jan; Steuer, Markus; Löw, Petra

2017-04-01

When utilizing historic loss data for present day risk assessment, it is necessary to make the data comparable over time and place. To achieve this, the assessment of costs from natural hazard events requires consistent and homogeneous methodologies for loss estimation as well as a robust treatment of loss data to estimate and/or reduce distorting effects due to a temporal bias in the reporting of small-scale loss events. Here we introduce Munich Re's NatCatSERVICE loss database and present a novel methodology of peril-specific normalization of the historic losses (to account for socio-economic growth of assets over time), and we introduce a metric of severity classification (called CatClass) that allows for a global comparison of impact severity across countries of different stages of economic development.

Tumor response estimation in radar-based microwave breast cancer detection.

PubMed

Kurrant, Douglas J; Fear, Elise C; Westwick, David T

2008-12-01

Radar-based microwave imaging techniques have been proposed for early stage breast cancer detection. A considerable challenge for the successful implementation of these techniques is the reduction of clutter, or components of the signal originating from objects other than the tumor. In particular, the reduction of clutter from the late-time scattered fields is required in order to detect small (subcentimeter diameter) tumors. In this paper, a method to estimate the tumor response contained in the late-time scattered fields is presented. The method uses a parametric function to model the tumor response. A maximum a posteriori estimation approach is used to evaluate the optimal values for the estimates of the parameters. A pattern classification technique is then used to validate the estimation. The ability of the algorithm to estimate a tumor response is demonstrated by using both experimental and simulated data obtained with a tissue sensing adaptive radar system.

Additive mixed effect model for recurrent gap time data.

PubMed

Ding, Jieli; Sun, Liuquan

2017-04-01

Gap times between recurrent events are often of primary interest in medical and observational studies. The additive hazards model, focusing on risk differences rather than risk ratios, has been widely used in practice. However, the marginal additive hazards model does not take the dependence among gap times into account. In this paper, we propose an additive mixed effect model to analyze gap time data, and the proposed model includes a subject-specific random effect to account for the dependence among the gap times. Estimating equation approaches are developed for parameter estimation, and the asymptotic properties of the resulting estimators are established. In addition, some graphical and numerical procedures are presented for model checking. The finite sample behavior of the proposed methods is evaluated through simulation studies, and an application to a data set from a clinic study on chronic granulomatous disease is provided.

Finite-time and finite-size scalings in the evaluation of large-deviation functions: Numerical approach in continuous time.

PubMed

Guevara Hidalgo, Esteban; Nemoto, Takahiro; Lecomte, Vivien

2017-06-01

Rare trajectories of stochastic systems are important to understand because of their potential impact. However, their properties are by definition difficult to sample directly. Population dynamics provides a numerical tool allowing their study, by means of simulating a large number of copies of the system, which are subjected to selection rules that favor the rare trajectories of interest. Such algorithms are plagued by finite simulation time and finite population size, effects that can render their use delicate. In this paper, we present a numerical approach which uses the finite-time and finite-size scalings of estimators of the large deviation functions associated to the distribution of rare trajectories. The method we propose allows one to extract the infinite-time and infinite-size limit of these estimators, which-as shown on the contact process-provides a significant improvement of the large deviation function estimators compared to the standard one.

Magnetometer-only attitude and angular velocity filtering estimation for attitude changing spacecraft

NASA Astrophysics Data System (ADS)

Ma, Hongliang; Xu, Shijie

2014-09-01

This paper presents an improved real-time sequential filter (IRTSF) for magnetometer-only attitude and angular velocity estimation of spacecraft during its attitude changing (including fast and large angular attitude maneuver, rapidly spinning or uncontrolled tumble). In this new magnetometer-only attitude determination technique, both attitude dynamics equation and first time derivative of measured magnetic field vector are directly leaded into filtering equations based on the traditional single vector attitude determination method of gyroless and real-time sequential filter (RTSF) of magnetometer-only attitude estimation. The process noise model of IRTSF includes attitude kinematics and dynamics equations, and its measurement model consists of magnetic field vector and its first time derivative. The observability of IRTSF for small or large angular velocity changing spacecraft is evaluated by an improved Lie-Differentiation, and the degrees of observability of IRTSF for different initial estimation errors are analyzed by the condition number and a solved covariance matrix. Numerical simulation results indicate that: (1) the attitude and angular velocity of spacecraft can be estimated with sufficient accuracy using IRTSF from magnetometer-only data; (2) compared with that of RTSF, the estimation accuracies and observability degrees of attitude and angular velocity using IRTSF from magnetometer-only data are both improved; and (3) universality: the IRTSF of magnetometer-only attitude and angular velocity estimation is observable for any different initial state estimation error vector.

Estimating Dynamical Systems: Derivative Estimation Hints From Sir Ronald A. Fisher.

PubMed

Deboeck, Pascal R

2010-08-06

The fitting of dynamical systems to psychological data offers the promise of addressing new and innovative questions about how people change over time. One method of fitting dynamical systems is to estimate the derivatives of a time series and then examine the relationships between derivatives using a differential equation model. One common approach for estimating derivatives, Local Linear Approximation (LLA), produces estimates with correlated errors. Depending on the specific differential equation model used, such correlated errors can lead to severely biased estimates of differential equation model parameters. This article shows that the fitting of dynamical systems can be improved by estimating derivatives in a manner similar to that used to fit orthogonal polynomials. Two applications using simulated data compare the proposed method and a generalized form of LLA when used to estimate derivatives and when used to estimate differential equation model parameters. A third application estimates the frequency of oscillation in observations of the monthly deaths from bronchitis, emphysema, and asthma in the United Kingdom. These data are publicly available in the statistical program R, and functions in R for the method presented are provided.

Corrected score estimation in the proportional hazards model with misclassified discrete covariates

PubMed Central

Zucker, David M.; Spiegelman, Donna

2013-01-01

SUMMARY We consider Cox proportional hazards regression when the covariate vector includes error-prone discrete covariates along with error-free covariates, which may be discrete or continuous. The misclassification in the discrete error-prone covariates is allowed to be of any specified form. Building on the work of Nakamura and his colleagues, we present a corrected score method for this setting. The method can handle all three major study designs (internal validation design, external validation design, and replicate measures design), both functional and structural error models, and time-dependent covariates satisfying a certain ‘localized error’ condition. We derive the asymptotic properties of the method and indicate how to adjust the covariance matrix of the regression coefficient estimates to account for estimation of the misclassification matrix. We present the results of a finite-sample simulation study under Weibull survival with a single binary covariate having known misclassification rates. The performance of the method described here was similar to that of related methods we have examined in previous works. Specifically, our new estimator performed as well as or, in a few cases, better than the full Weibull maximum likelihood estimator. We also present simulation results for our method for the case where the misclassification probabilities are estimated from an external replicate measures study. Our method generally performed well in these simulations. The new estimator has a broader range of applicability than many other estimators proposed in the literature, including those described in our own earlier work, in that it can handle time-dependent covariates with an arbitrary misclassification structure. We illustrate the method on data from a study of the relationship between dietary calcium intake and distal colon cancer. PMID:18219700

Estimating secular velocities from GPS data contaminated by postseismic motion at sites with limited pre-earthquake data

NASA Astrophysics Data System (ADS)

Murray, J. R.; Svarc, J. L.

2016-12-01

Constant secular velocities estimated from Global Positioning System (GPS)-derived position time series are a central input for modeling interseismic deformation in seismically active regions. Both postseismic motion and temporally correlated noise produce long-period signals that are difficult to separate from secular motion and can bias velocity estimates. For GPS sites installed post-earthquake it is especially challenging to uniquely estimate velocities and postseismic signals and to determine when the postseismic transient has decayed sufficiently to enable use of subsequent data for estimating secular rates. Within 60 km of the 2003 M6.5 San Simeon and 2004 M6 Parkfield earthquakes in California, 16 continuous GPS sites (group 1) were established prior to mid-2001, and 52 stations (group 2) were installed following the events. We use group 1 data to investigate how early in the post-earthquake time period one may reliably begin using group 2 data to estimate velocities. For each group 1 time series, we obtain eight velocity estimates using observation time windows with successively later start dates (2006 - 2013) and a parameterization that includes constant velocity, annual, and semi-annual terms but no postseismic decay. We compare these to velocities estimated using only pre-San Simeon data to find when the pre- and post-earthquake velocities match within uncertainties. To obtain realistic velocity uncertainties, for each time series we optimize a temporally correlated noise model consisting of white, flicker, random walk, and, in some cases, band-pass filtered noise contributions. Preliminary results suggest velocities can be reliably estimated using data from 2011 to the present. Ongoing work will assess velocity bias as a function of epicentral distance and length of post-earthquake time series as well as explore spatio-temporal filtering of detrended group 1 time series to provide empirical corrections for postseismic motion in group 2 time series.

Bounded influence function based inference in joint modelling of ordinal partial linear model and accelerated failure time model.

PubMed

Chakraborty, Arindom

2016-12-01

A common objective in longitudinal studies is to characterize the relationship between a longitudinal response process and a time-to-event data. Ordinal nature of the response and possible missing information on covariates add complications to the joint model. In such circumstances, some influential observations often present in the data may upset the analysis. In this paper, a joint model based on ordinal partial mixed model and an accelerated failure time model is used, to account for the repeated ordered response and time-to-event data, respectively. Here, we propose an influence function-based robust estimation method. Monte Carlo expectation maximization method-based algorithm is used for parameter estimation. A detailed simulation study has been done to evaluate the performance of the proposed method. As an application, a data on muscular dystrophy among children is used. Robust estimates are then compared with classical maximum likelihood estimates. © The Author(s) 2014.

Quantifying the uncertainty introduced by discretization and time-averaging in two-fluid model predictions

DOE PAGES

Syamlal, Madhava; Celik, Ismail B.; Benyahia, Sofiane

2017-07-12

The two-fluid model (TFM) has become a tool for the design and troubleshooting of industrial fluidized bed reactors. To use TFM for scale up with confidence, the uncertainty in its predictions must be quantified. Here, we study two sources of uncertainty: discretization and time-averaging. First, we show that successive grid refinement may not yield grid-independent transient quantities, including cross-section–averaged quantities. Successive grid refinement would yield grid-independent time-averaged quantities on sufficiently fine grids. A Richardson extrapolation can then be used to estimate the discretization error, and the grid convergence index gives an estimate of the uncertainty. Richardson extrapolation may not workmore » for industrial-scale simulations that use coarse grids. We present an alternative method for coarse grids and assess its ability to estimate the discretization error. Second, we assess two methods (autocorrelation and binning) and find that the autocorrelation method is more reliable for estimating the uncertainty introduced by time-averaging TFM data.« less

Real-Time Stability and Control Derivative Extraction From F-15 Flight Data

NASA Technical Reports Server (NTRS)

Smith, Mark S.; Moes, Timothy R.; Morelli, Eugene A.

2003-01-01

A real-time, frequency-domain, equation-error parameter identification (PID) technique was used to estimate stability and control derivatives from flight data. This technique is being studied to support adaptive control system concepts currently being developed by NASA (National Aeronautics and Space Administration), academia, and industry. This report describes the basic real-time algorithm used for this study and implementation issues for onboard usage as part of an indirect-adaptive control system. A confidence measures system for automated evaluation of PID results is discussed. Results calculated using flight data from a modified F-15 aircraft are presented. Test maneuvers included pilot input doublets and automated inputs at several flight conditions. Estimated derivatives are compared to aerodynamic model predictions. Data indicate that the real-time PID used for this study performs well enough to be used for onboard parameter estimation. For suitable test inputs, the parameter estimates converged rapidly to sufficient levels of accuracy. The devised confidence measures used were moderately successful.

Robust inference in discrete hazard models for randomized clinical trials.

PubMed

Nguyen, Vinh Q; Gillen, Daniel L

2012-10-01

Time-to-event data in which failures are only assessed at discrete time points are common in many clinical trials. Examples include oncology studies where events are observed through periodic screenings such as radiographic scans. When the survival endpoint is acknowledged to be discrete, common methods for the analysis of observed failure times include the discrete hazard models (e.g., the discrete-time proportional hazards and the continuation ratio model) and the proportional odds model. In this manuscript, we consider estimation of a marginal treatment effect in discrete hazard models where the constant treatment effect assumption is violated. We demonstrate that the estimator resulting from these discrete hazard models is consistent for a parameter that depends on the underlying censoring distribution. An estimator that removes the dependence on the censoring mechanism is proposed and its asymptotic distribution is derived. Basing inference on the proposed estimator allows for statistical inference that is scientifically meaningful and reproducible. Simulation is used to assess the performance of the presented methodology in finite samples.

Polynomial Phase Estimation Based on Adaptive Short-Time Fourier Transform

PubMed Central

Jing, Fulong; Zhang, Chunjie; Si, Weijian; Wang, Yu; Jiao, Shuhong

2018-01-01

Polynomial phase signals (PPSs) have numerous applications in many fields including radar, sonar, geophysics, and radio communication systems. Therefore, estimation of PPS coefficients is very important. In this paper, a novel approach for PPS parameters estimation based on adaptive short-time Fourier transform (ASTFT), called the PPS-ASTFT estimator, is proposed. Using the PPS-ASTFT estimator, both one-dimensional and multi-dimensional searches and error propagation problems, which widely exist in PPSs field, are avoided. In the proposed algorithm, the instantaneous frequency (IF) is estimated by S-transform (ST), which can preserve information on signal phase and provide a variable resolution similar to the wavelet transform (WT). The width of the ASTFT analysis window is equal to the local stationary length, which is measured by the instantaneous frequency gradient (IFG). The IFG is calculated by the principal component analysis (PCA), which is robust to the noise. Moreover, to improve estimation accuracy, a refinement strategy is presented to estimate signal parameters. Since the PPS-ASTFT avoids parameter search, the proposed algorithm can be computed in a reasonable amount of time. The estimation performance, computational cost, and implementation of the PPS-ASTFT are also analyzed. The conducted numerical simulations support our theoretical results and demonstrate an excellent statistical performance of the proposed algorithm. PMID:29438317

Polynomial Phase Estimation Based on Adaptive Short-Time Fourier Transform.

PubMed

Jing, Fulong; Zhang, Chunjie; Si, Weijian; Wang, Yu; Jiao, Shuhong

2018-02-13

Polynomial phase signals (PPSs) have numerous applications in many fields including radar, sonar, geophysics, and radio communication systems. Therefore, estimation of PPS coefficients is very important. In this paper, a novel approach for PPS parameters estimation based on adaptive short-time Fourier transform (ASTFT), called the PPS-ASTFT estimator, is proposed. Using the PPS-ASTFT estimator, both one-dimensional and multi-dimensional searches and error propagation problems, which widely exist in PPSs field, are avoided. In the proposed algorithm, the instantaneous frequency (IF) is estimated by S-transform (ST), which can preserve information on signal phase and provide a variable resolution similar to the wavelet transform (WT). The width of the ASTFT analysis window is equal to the local stationary length, which is measured by the instantaneous frequency gradient (IFG). The IFG is calculated by the principal component analysis (PCA), which is robust to the noise. Moreover, to improve estimation accuracy, a refinement strategy is presented to estimate signal parameters. Since the PPS-ASTFT avoids parameter search, the proposed algorithm can be computed in a reasonable amount of time. The estimation performance, computational cost, and implementation of the PPS-ASTFT are also analyzed. The conducted numerical simulations support our theoretical results and demonstrate an excellent statistical performance of the proposed algorithm.

Fundamental performance of transverse wind estimator from Shack-Hartmann wave-front sensor measurements.

PubMed

Li, Zhenghan; Li, Xinyang

2018-04-30

Real time transverse wind estimation contributes to predictive correction which is used to compensate for the time delay error in the control systems of adaptive optics (AO) system. Many methods that apply Shack-Hartmann wave-front sensor to wind profile measurement have been proposed. One of the obvious problems is the lack of a fundamental benchmark to compare the various methods. In this work, we present the fundamental performance limits for transverse wind estimator from Shack-Hartmann wave-front sensor measurements using Cramér-Rao lower bound (CRLB). The bound provides insight into the nature of the transverse wind estimation, thereby suggesting how to design and improve the estimator in the different application scenario. We analyze the theoretical bound and find that factors such as slope measurement noise, wind velocity and atmospheric coherence length r 0 have important influence on the performance. Then, we introduced the non-iterative gradient-based transverse wind estimator. The source of the deterministic bias of the gradient-based transverse wind estimators is analyzed for the first time. Finally, we derived biased CRLB for the gradient-based transverse wind estimators from Shack-Hartmann wave-front sensor measurements and the bound can predict the performance of estimator more accurately.

Regression to fuzziness method for estimation of remaining useful life in power plant components

NASA Astrophysics Data System (ADS)

Alamaniotis, Miltiadis; Grelle, Austin; Tsoukalas, Lefteri H.

2014-10-01

Mitigation of severe accidents in power plants requires the reliable operation of all systems and the on-time replacement of mechanical components. Therefore, the continuous surveillance of power systems is a crucial concern for the overall safety, cost control, and on-time maintenance of a power plant. In this paper a methodology called regression to fuzziness is presented that estimates the remaining useful life (RUL) of power plant components. The RUL is defined as the difference between the time that a measurement was taken and the estimated failure time of that component. The methodology aims to compensate for a potential lack of historical data by modeling an expert's operational experience and expertise applied to the system. It initially identifies critical degradation parameters and their associated value range. Once completed, the operator's experience is modeled through fuzzy sets which span the entire parameter range. This model is then synergistically used with linear regression and a component's failure point to estimate the RUL. The proposed methodology is tested on estimating the RUL of a turbine (the basic electrical generating component of a power plant) in three different cases. Results demonstrate the benefits of the methodology for components for which operational data is not readily available and emphasize the significance of the selection of fuzzy sets and the effect of knowledge representation on the predicted output. To verify the effectiveness of the methodology, it was benchmarked against the data-based simple linear regression model used for predictions which was shown to perform equal or worse than the presented methodology. Furthermore, methodology comparison highlighted the improvement in estimation offered by the adoption of appropriate of fuzzy sets for parameter representation.

Seismic potential for large and great interplate earthquakes along the Chilean and Southern Peruvian Margins of South America: A quantitative reappraisal

NASA Astrophysics Data System (ADS)

Nishenko, Stuart P.

1985-04-01

The seismic potential of the Chilean and southern Peruvian margins of South America is reevaluated to delineate those areas or segments of the margin that may be expected to experience large or great interplate earthquakes within the next 20 years (1984-2004). Long-term estimates of seismic potential (or the conditional probability of recurrence within a specified period of time) are based on (1) statistical analysis of historic repeat time data using Weibull distributions and (2) deterministic estimates of recurrence times based on the time-predictable model of earthquake recurrence. Both methods emphasize the periodic nature of large and great earthquake recurrence, and are compared with estimates of probability based on the assumption of Poisson-type behavior. The estimates of seismic potential presented in this study are long-term forecasts only, as the temporal resolution (or standard deviation) of both methods is taken to range from ±15% to ±25% of the average or estimated repeat time. At present, the Valparaiso region of central Chile (32°-35°S) has a high potential or probability of recurrence in the next 20 years. Coseismic uplift data associated with previous shocks in 1822 and 1906 suggest that this area may have already started to rerupture in 1971-1973. Average repeat times also suggest this area is due for a great shock within the next 20 years. Flanking segments of the Chilean margin, Coquimbo-Illapel (30°-32°S) and Talca-Concepcion (35°-38°S), presently have poorly constrained but possibly quite high potentials for a series of large or great shocks within the next 20 years. In contrast, the rupture zone of the great 1960 earthquake (37°-46°S) has the lowest potential along the margin and is not expected to rerupture in a great earthquake within the next 100 years. In the north, the seismic potentials of the Mollendo-Arica (17°-18°S) and Arica-Antofagasta (18°-24°S) segments (which last ruptured during great earthquakes in 1868 and 1877) are also high, but poorly constrained.

An improvement of the measurement of time series irreversibility with visibility graph approach

NASA Astrophysics Data System (ADS)

Wu, Zhenyu; Shang, Pengjian; Xiong, Hui

2018-07-01

We propose a method to improve the measure of real-valued time series irreversibility which contains two tools: the directed horizontal visibility graph and the Kullback-Leibler divergence. The degree of time irreversibility is estimated by the Kullback-Leibler divergence between the in and out degree distributions presented in the associated visibility graph. In our work, we reframe the in and out degree distributions by encoding them with different embedded dimensions used in calculating permutation entropy(PE). With this improved method, we can not only estimate time series irreversibility efficiently, but also detect time series irreversibility from multiple dimensions. We verify the validity of our method and then estimate the amount of time irreversibility of series generated by chaotic maps as well as global stock markets over the period 2005-2015. The result shows that the amount of time irreversibility reaches the peak with embedded dimension d = 3 under circumstances of experiment and financial markets.

Mesospheric temperatures estimated from the meteor decay times over King Sejong Station(62.2°S, 58.8°W), Antarctica

NASA Astrophysics Data System (ADS)

Kim, J.; Kim, Y.; Jee, G.

2010-12-01

A VHF meteor radar has ben operated at King Sejong Station (62.2°S, 58.8°W), Antarctica since March 2007 for the observations of the neutral winds in the mesosphere and lower thermosphere region. In addition, the radar observation allows usto estimate the neutral temperature from the measured meteor decay times of the meteor echoes by utilizing Hocking's method (Hocking, 1999). For this temperature estimation, the meteor echoes observed from March 2007 to July 2009 were divded, for the first time, into weak and strong echoes depending on the strength of estimated relative electron line densities. The estimated temperatures are then compared the temperature measurements from the spectral airglow temperature imager (SATI) which has also been operated at the same location since 2002. The estimated temperatures from strong echoes were significantly lower than the temperatures estimated from weak echoes by on average about 31 K. As was done in most previous studies, we also derived the temperature by using all echoes without dividing into weak and strong, which produces about 10 K lower than the weak echoes. Among these hree estimated temperatures, the one from weak echoes was most similar to the SATI temperature. This result indicates that the strong echoes tend to reduce the estimated temperature and therefore need to be removed in the estimation procedure. We will also present the comparison of the estimated temperature with other measurements, for example, from the TIMED/SABER instrument and the NRLMSISE-00 empirical model results as a further validation.

Estimating investment worthiness of an ergonomic intervention for preventing low back pain from a firm's perspective.

PubMed

Hughes, Richard E; Nelson, Nancy A

2009-05-01

A mathematical model was developed for estimating the net present value (NPV) of the cash flow resulting from an investment in an intervention to prevent occupational low back pain (LBP). It combines biomechanics, epidemiology, and finance to give an integrated tool for a firm to use to estimate the investment worthiness of an intervention based on a biomechanical analysis of working postures and hand loads. The model can be used by an ergonomist to estimate the investment worthiness of a proposed intervention. The analysis would begin with a biomechanical evaluation of the current job design and post-intervention job. Economic factors such as hourly labor cost, overhead, workers' compensation costs of LBP claims, and discount rate are combined with the biomechanical analysis to estimate the investment worthiness of the proposed intervention. While this model is limited to low back pain, the simulation framework could be applied to other musculoskeletal disorders. The model uses Monte Carlo simulation to compute the statistical distribution of NPV, and it uses a discrete event simulation paradigm based on four states: (1) working and no history of lost time due to LBP, (2) working and history of lost time due to LBP, (3) lost time due to LBP, and (4) leave job. Probabilities of transitions are based on an extensive review of the epidemiologic review of the low back pain literature. An example is presented.

Estimation of time- and state-dependent delays and other parameters in functional differential equations

NASA Technical Reports Server (NTRS)

Murphy, K. A.

1988-01-01

A parameter estimation algorithm is developed which can be used to estimate unknown time- or state-dependent delays and other parameters (e.g., initial condition) appearing within a nonlinear nonautonomous functional differential equation. The original infinite dimensional differential equation is approximated using linear splines, which are allowed to move with the variable delay. The variable delays are approximated using linear splines as well. The approximation scheme produces a system of ordinary differential equations with nice computational properties. The unknown parameters are estimated within the approximating systems by minimizing a least-squares fit-to-data criterion. Convergence theorems are proved for time-dependent delays and state-dependent delays within two classes, which say essentially that fitting the data by using approximations will, in the limit, provide a fit to the data using the original system. Numerical test examples are presented which illustrate the method for all types of delay.

Estimation of time- and state-dependent delays and other parameters in functional differential equations

NASA Technical Reports Server (NTRS)

Murphy, K. A.

1990-01-01

A parameter estimation algorithm is developed which can be used to estimate unknown time- or state-dependent delays and other parameters (e.g., initial condition) appearing within a nonlinear nonautonomous functional differential equation. The original infinite dimensional differential equation is approximated using linear splines, which are allowed to move with the variable delay. The variable delays are approximated using linear splines as well. The approximation scheme produces a system of ordinary differential equations with nice computational properties. The unknown parameters are estimated within the approximating systems by minimizing a least-squares fit-to-data criterion. Convergence theorems are proved for time-dependent delays and state-dependent delays within two classes, which say essentially that fitting the data by using approximations will, in the limit, provide a fit to the data using the original system. Numerical test examples are presented which illustrate the method for all types of delay.

Dipolar filtered magic-sandwich-echoes as a tool for probing molecular motions using time domain NMR

NASA Astrophysics Data System (ADS)

Filgueiras, Jefferson G.; da Silva, Uilson B.; Paro, Giovanni; d'Eurydice, Marcel N.; Cobo, Márcio F.; deAzevedo, Eduardo R.

2017-12-01

We present a simple 1 H NMR approach for characterizing intermediate to fast regime molecular motions using 1 H time-domain NMR at low magnetic field. The method is based on a Goldmann Shen dipolar filter (DF) followed by a Mixed Magic Sandwich Echo (MSE). The dipolar filter suppresses the signals arising from molecular segments presenting sub kHz mobility, so only signals from mobile segments are detected. Thus, the temperature dependence of the signal intensities directly evidences the onset of molecular motions with rates higher than kHz. The DF-MSE signal intensity is described by an analytical function based on the Anderson Weiss theory, from where parameters related to the molecular motion (e.g. correlation times and activation energy) can be estimated when performing experiments as function of the temperature. Furthermore, we propose the use of the Tikhonov regularization for estimating the width of the distribution of correlation times.

A novel time of arrival estimation algorithm using an energy detector receiver in MMW systems

NASA Astrophysics Data System (ADS)

Liang, Xiaolin; Zhang, Hao; Lyu, Tingting; Xiao, Han; Gulliver, T. Aaron

2017-12-01

This paper presents a new time of arrival (TOA) estimation technique using an improved energy detection (ED) receiver based on the empirical mode decomposition (EMD) in an impulse radio (IR) 60 GHz millimeter wave (MMW) system. A threshold is employed via analyzing the characteristics of the received energy values with an extreme learning machine (ELM). The effect of the channel and integration period on the TOA estimation is evaluated. Several well-known ED-based TOA algorithms are used to compare with the proposed technique. It is shown that this ELM-based technique has lower TOA estimation error compared to other approaches and provides robust performance with the IEEE 802.15.3c channel models.

A real-time digital program for estimating aircraft stability and control parameters from flight test data by using the maximum likelihood method

NASA Technical Reports Server (NTRS)

Grove, R. D.; Mayhew, S. C.

1973-01-01

A computer program (Langley program C1123) has been developed for estimating aircraft stability and control parameters from flight test data. These parameters are estimated by the maximum likelihood estimation procedure implemented on a real-time digital simulation system, which uses the Control Data 6600 computer. This system allows the investigator to interact with the program in order to obtain satisfactory results. Part of this system, the control and display capabilities, is described for this program. This report also describes the computer program by presenting the program variables, subroutines, flow charts, listings, and operational features. Program usage is demonstrated with a test case using pseudo or simulated flight data.

Fractional Brownian motion time-changed by gamma and inverse gamma process

NASA Astrophysics Data System (ADS)

Kumar, A.; Wyłomańska, A.; Połoczański, R.; Sundar, S.

2017-02-01

Many real time-series exhibit behavior adequate to long range dependent data. Additionally very often these time-series have constant time periods and also have characteristics similar to Gaussian processes although they are not Gaussian. Therefore there is need to consider new classes of systems to model these kinds of empirical behavior. Motivated by this fact in this paper we analyze two processes which exhibit long range dependence property and have additional interesting characteristics which may be observed in real phenomena. Both of them are constructed as the superposition of fractional Brownian motion (FBM) and other process. In the first case the internal process, which plays role of the time, is the gamma process while in the second case the internal process is its inverse. We present in detail their main properties paying main attention to the long range dependence property. Moreover, we show how to simulate these processes and estimate their parameters. We propose to use a novel method based on rescaled modified cumulative distribution function for estimation of parameters of the second considered process. This method is very useful in description of rounded data, like waiting times of subordinated processes delayed by inverse subordinators. By using the Monte Carlo method we show the effectiveness of proposed estimation procedures. Finally, we present the applications of proposed models to real time series.

Low Variance Couplings for Stochastic Models of Intracellular Processes with Time-Dependent Rate Functions.

PubMed

Anderson, David F; Yuan, Chaojie

2018-04-18

A number of coupling strategies are presented for stochastically modeled biochemical processes with time-dependent parameters. In particular, the stacked coupling is introduced and is shown via a number of examples to provide an exceptionally low variance between the generated paths. This coupling will be useful in the numerical computation of parametric sensitivities and the fast estimation of expectations via multilevel Monte Carlo methods. We provide the requisite estimators in both cases.

Estimating Upper Bounds for Occupancy and Number of Manatees in Areas Potentially Affected by Oil from the Deepwater Horizon Oil Spill

PubMed Central

Martin, Julien; Edwards, Holly H.; Bled, Florent; Fonnesbeck, Christopher J.; Dupuis, Jérôme A.; Gardner, Beth; Koslovsky, Stacie M.; Aven, Allen M.; Ward-Geiger, Leslie I.; Carmichael, Ruth H.; Fagan, Daniel E.; Ross, Monica A.; Reinert, Thomas R.

2014-01-01

The explosion of the Deepwater Horizon drilling platform created the largest marine oil spill in U.S. history. As part of the Natural Resource Damage Assessment process, we applied an innovative modeling approach to obtain upper estimates for occupancy and for number of manatees in areas potentially affected by the oil spill. Our data consisted of aerial survey counts in waters of the Florida Panhandle, Alabama and Mississippi. Our method, which uses a Bayesian approach, allows for the propagation of uncertainty associated with estimates from empirical data and from the published literature. We illustrate that it is possible to derive estimates of occupancy rate and upper estimates of the number of manatees present at the time of sampling, even when no manatees were observed in our sampled plots during surveys. We estimated that fewer than 2.4% of potentially affected manatee habitat in our Florida study area may have been occupied by manatees. The upper estimate for the number of manatees present in potentially impacted areas (within our study area) was estimated with our model to be 74 (95%CI 46 to 107). This upper estimate for the number of manatees was conditioned on the upper 95%CI value of the occupancy rate. In other words, based on our estimates, it is highly probable that there were 107 or fewer manatees in our study area during the time of our surveys. Because our analyses apply to habitats considered likely manatee habitats, our inference is restricted to these sites and to the time frame of our surveys. Given that manatees may be hard to see during aerial surveys, it was important to account for imperfect detection. The approach that we described can be useful for determining the best allocation of resources for monitoring and conservation. PMID:24670971

Optimal design and use of retry in fault tolerant real-time computer systems

NASA Technical Reports Server (NTRS)

Lee, Y. H.; Shin, K. G.

1983-01-01

A new method to determin an optimal retry policy and for use in retry of fault characterization is presented. An optimal retry policy for a given fault characteristic, which determines the maximum allowable retry durations to minimize the total task completion time was derived. The combined fault characterization and retry decision, in which the characteristics of fault are estimated simultaneously with the determination of the optimal retry policy were carried out. Two solution approaches were developed, one based on the point estimation and the other on the Bayes sequential decision. The maximum likelihood estimators are used for the first approach, and the backward induction for testing hypotheses in the second approach. Numerical examples in which all the durations associated with faults have monotone hazard functions, e.g., exponential, Weibull and gamma distributions are presented. These are standard distributions commonly used for modeling analysis and faults.

Time-varying effect moderation using the structural nested mean model: estimation using inverse-weighted regression with residuals

PubMed Central

Almirall, Daniel; Griffin, Beth Ann; McCaffrey, Daniel F.; Ramchand, Rajeev; Yuen, Robert A.; Murphy, Susan A.

2014-01-01

This article considers the problem of examining time-varying causal effect moderation using observational, longitudinal data in which treatment, candidate moderators, and possible confounders are time varying. The structural nested mean model (SNMM) is used to specify the moderated time-varying causal effects of interest in a conditional mean model for a continuous response given time-varying treatments and moderators. We present an easy-to-use estimator of the SNMM that combines an existing regression-with-residuals (RR) approach with an inverse-probability-of-treatment weighting (IPTW) strategy. The RR approach has been shown to identify the moderated time-varying causal effects if the time-varying moderators are also the sole time-varying confounders. The proposed IPTW+RR approach provides estimators of the moderated time-varying causal effects in the SNMM in the presence of an additional, auxiliary set of known and measured time-varying confounders. We use a small simulation experiment to compare IPTW+RR versus the traditional regression approach and to compare small and large sample properties of asymptotic versus bootstrap estimators of the standard errors for the IPTW+RR approach. This article clarifies the distinction between time-varying moderators and time-varying confounders. We illustrate the methodology in a case study to assess if time-varying substance use moderates treatment effects on future substance use. PMID:23873437

Probabilistic Methodology for Estimation of Number and Economic Loss (Cost) of Future Landslides in the San Francisco Bay Region, California

USGS Publications Warehouse

Crovelli, Robert A.; Coe, Jeffrey A.

2008-01-01

The Probabilistic Landslide Assessment Cost Estimation System (PLACES) presented in this report estimates the number and economic loss (cost) of landslides during a specified future time in individual areas, and then calculates the sum of those estimates. The analytic probabilistic methodology is based upon conditional probability theory and laws of expectation and variance. The probabilistic methodology is expressed in the form of a Microsoft Excel computer spreadsheet program. Using historical records, the PLACES spreadsheet is used to estimate the number of future damaging landslides and total damage, as economic loss, from future landslides caused by rainstorms in 10 counties of the San Francisco Bay region in California. Estimates are made for any future 5-year period of time. The estimated total number of future damaging landslides for the entire 10-county region during any future 5-year period of time is about 330. Santa Cruz County has the highest estimated number of damaging landslides (about 90), whereas Napa, San Francisco, and Solano Counties have the lowest estimated number of damaging landslides (5?6 each). Estimated direct costs from future damaging landslides for the entire 10-county region for any future 5-year period are about US $76 million (year 2000 dollars). San Mateo County has the highest estimated costs ($16.62 million), and Solano County has the lowest estimated costs (about $0.90 million). Estimated direct costs are also subdivided into public and private costs.

Implicit Particle Filter for Power System State Estimation with Large Scale Renewable Power Integration.

NASA Astrophysics Data System (ADS)

Uzunoglu, B.; Hussaini, Y.

2017-12-01

Implicit Particle Filter is a sequential Monte Carlo method for data assimilation that guides the particles to the high-probability by an implicit step . It optimizes a nonlinear cost function which can be inherited from legacy assimilation routines . Dynamic state estimation for almost real-time applications in power systems are becomingly increasingly more important with integration of variable wind and solar power generation. New advanced state estimation tools that will replace the old generation state estimation in addition to having a general framework of complexities should be able to address the legacy software and able to integrate the old software in a mathematical framework while allowing the power industry need for a cautious and evolutionary change in comparison to a complete revolutionary approach while addressing nonlinearity and non-normal behaviour. This work implements implicit particle filter as a state estimation tool for the estimation of the states of a power system and presents the first implicit particle filter application study on a power system state estimation. The implicit particle filter is introduced into power systems and the simulations are presented for a three-node benchmark power system . The performance of the filter on the presented problem is analyzed and the results are presented.

Efficient Implementation of a Symbol Timing Estimator for Broadband PLC.

PubMed

Nombela, Francisco; García, Enrique; Mateos, Raúl; Hernández, Álvaro

2015-08-21

Broadband Power Line Communications (PLC) have taken advantage of the research advances in multi-carrier modulations to mitigate frequency selective fading, and their adoption opens up a myriad of applications in the field of sensory and automation systems, multimedia connectivity or smart spaces. Nonetheless, the use of these multi-carrier modulations, such as Wavelet-OFDM, requires a highly accurate symbol timing estimation for reliably recovering of transmitted data. Furthermore, the PLC channel presents some particularities that prevent the direct use of previous synchronization algorithms proposed in wireless communication systems. Therefore more research effort should be involved in the design and implementation of novel and robust synchronization algorithms for PLC, thus enabling real-time synchronization. This paper proposes a symbol timing estimator for broadband PLC based on cross-correlation with multilevel complementary sequences or Zadoff-Chu sequences and its efficient implementation in a FPGA; the obtained results show a 90% of success rate in symbol timing estimation for a certain PLC channel model and a reduced resource consumption for its implementation in a Xilinx Kyntex FPGA.

Introduction to State Estimation of High-Rate System Dynamics

PubMed Central

Dodson, Jacob; Joyce, Bryan

2018-01-01

Engineering systems experiencing high-rate dynamic events, including airbags, debris detection, and active blast protection systems, could benefit from real-time observability for enhanced performance. However, the task of high-rate state estimation is challenging, in particular for real-time applications where the rate of the observer’s convergence needs to be in the microsecond range. This paper identifies the challenges of state estimation of high-rate systems and discusses the fundamental characteristics of high-rate systems. A survey of applications and methods for estimators that have the potential to produce accurate estimations for a complex system experiencing highly dynamic events is presented. It is argued that adaptive observers are important to this research. In particular, adaptive data-driven observers are advantageous due to their adaptability and lack of dependence on the system model. PMID:29342855

Blind estimation of reverberation time

NASA Astrophysics Data System (ADS)

Ratnam, Rama; Jones, Douglas L.; Wheeler, Bruce C.; O'Brien, William D.; Lansing, Charissa R.; Feng, Albert S.

2003-11-01

The reverberation time (RT) is an important parameter for characterizing the quality of an auditory space. Sounds in reverberant environments are subject to coloration. This affects speech intelligibility and sound localization. Many state-of-the-art audio signal processing algorithms, for example in hearing-aids and telephony, are expected to have the ability to characterize the listening environment, and turn on an appropriate processing strategy accordingly. Thus, a method for characterization of room RT based on passively received microphone signals represents an important enabling technology. Current RT estimators, such as Schroeder's method, depend on a controlled sound source, and thus cannot produce an online, blind RT estimate. Here, a method for estimating RT without prior knowledge of sound sources or room geometry is presented. The diffusive tail of reverberation was modeled as an exponentially damped Gaussian white noise process. The time-constant of the decay, which provided a measure of the RT, was estimated using a maximum-likelihood procedure. The estimates were obtained continuously, and an order-statistics filter was used to extract the most likely RT from the accumulated estimates. The procedure was illustrated for connected speech. Results obtained for simulated and real room data are in good agreement with the real RT values.

Parameter estimation in spiking neural networks: a reverse-engineering approach.

PubMed

Rostro-Gonzalez, H; Cessac, B; Vieville, T

2012-04-01

This paper presents a reverse engineering approach for parameter estimation in spiking neural networks (SNNs). We consider the deterministic evolution of a time-discretized network with spiking neurons, where synaptic transmission has delays, modeled as a neural network of the generalized integrate and fire type. Our approach aims at by-passing the fact that the parameter estimation in SNN results in a non-deterministic polynomial-time hard problem when delays are to be considered. Here, this assumption has been reformulated as a linear programming (LP) problem in order to perform the solution in a polynomial time. Besides, the LP problem formulation makes the fact that the reverse engineering of a neural network can be performed from the observation of the spike times explicit. Furthermore, we point out how the LP adjustment mechanism is local to each neuron and has the same structure as a 'Hebbian' rule. Finally, we present a generalization of this approach to the design of input-output (I/O) transformations as a practical method to 'program' a spiking network, i.e. find a set of parameters allowing us to exactly reproduce the network output, given an input. Numerical verifications and illustrations are provided.

A comparison of methods to estimate seismic phase delays--Numerical examples for coda wave interferometry

USGS Publications Warehouse

Mikesell, T. Dylan; Malcolm, Alison E.; Yang, Di; Haney, Matthew M.

2015-01-01

Time-shift estimation between arrivals in two seismic traces before and after a velocity perturbation is a crucial step in many seismic methods. The accuracy of the estimated velocity perturbation location and amplitude depend on this time shift. Windowed cross correlation and trace stretching are two techniques commonly used to estimate local time shifts in seismic signals. In the work presented here, we implement Dynamic Time Warping (DTW) to estimate the warping function – a vector of local time shifts that globally minimizes the misfit between two seismic traces. We illustrate the differences of all three methods compared to one another using acoustic numerical experiments. We show that DTW is comparable to or better than the other two methods when the velocity perturbation is homogeneous and the signal-to-noise ratio is high. When the signal-to-noise ratio is low, we find that DTW and windowed cross correlation are more accurate than the stretching method. Finally, we show that the DTW algorithm has better time resolution when identifying small differences in the seismic traces for a model with an isolated velocity perturbation. These results impact current methods that utilize not only time shifts between (multiply) scattered waves, but also amplitude and decoherence measurements. DTW is a new tool that may find new applications in seismology and other geophysical methods (e.g., as a waveform inversion misfit function).

The detrimental influence of attention on time-to-contact perception.

PubMed

Baurès, Robin; Balestra, Marianne; Rosito, Maxime; VanRullen, Rufin

2018-04-23

To which extent is attention necessary to estimate the time-to-contact (TTC) of a moving object, that is, determining when the object will reach a specific point? While numerous studies have aimed at determining the visual cues and gaze strategy that allow this estimation, little is known about if and how attention is involved or required in this process. To answer this question, we carried out an experiment in which the participants estimated the TTC of a moving ball, either alone (single-task condition) or concurrently with a Rapid Serial Visual Presentation task embedded within the ball (dual-task condition). The results showed that participants had a better estimation when attention was driven away from the TTC task. This suggests that drawing attention away from the TTC estimation limits cognitive interference, intrusion of knowledge, or expectations that significantly modify the visually-based TTC estimation, and argues in favor of a limited attention to correctly estimate the TTC.

Consequences of varied soil hydraulic and meteorological complexity on unsaturated zone time lag estimates.

PubMed

Vero, S E; Ibrahim, T G; Creamer, R E; Grant, J; Healy, M G; Henry, T; Kramers, G; Richards, K G; Fenton, O

2014-12-01

The true efficacy of a programme of agricultural mitigation measures within a catchment to improve water quality can be determined only after a certain hydrologic time lag period (subsequent to implementation) has elapsed. As the biophysical response to policy is not synchronous, accurate estimates of total time lag (unsaturated and saturated) become critical to manage the expectations of policy makers. The estimation of the vertical unsaturated zone component of time lag is vital as it indicates early trends (initial breakthrough), bulk (centre of mass) and total (Exit) travel times. Typically, estimation of time lag through the unsaturated zone is poor, due to the lack of site specific soil physical data, or by assuming saturated conditions. Numerical models (e.g. Hydrus 1D) enable estimates of time lag with varied levels of input data. The current study examines the consequences of varied soil hydraulic and meteorological complexity on unsaturated zone time lag estimates using simulated and actual soil profiles. Results indicated that: greater temporal resolution (from daily to hourly) of meteorological data was more critical as the saturated hydraulic conductivity of the soil decreased; high clay content soils failed to converge reflecting prevalence of lateral component as a contaminant pathway; elucidation of soil hydraulic properties was influenced by the complexity of soil physical data employed (textural menu, ROSETTA, full and partial soil water characteristic curves), which consequently affected time lag ranges; as the importance of the unsaturated zone increases with respect to total travel times the requirements for high complexity/resolution input data become greater. The methodology presented herein demonstrates that decisions made regarding input data and landscape position will have consequences for the estimated range of vertical travel times. Insufficiencies or inaccuracies regarding such input data can therefore mislead policy makers regarding the achievability of water quality targets. Copyright © 2014 Elsevier B.V. All rights reserved.

Ultra wide-band localization and SLAM: a comparative study for mobile robot navigation.

PubMed

Segura, Marcelo J; Auat Cheein, Fernando A; Toibero, Juan M; Mut, Vicente; Carelli, Ricardo

2011-01-01

In this work, a comparative study between an Ultra Wide-Band (UWB) localization system and a Simultaneous Localization and Mapping (SLAM) algorithm is presented. Due to its high bandwidth and short pulses length, UWB potentially allows great accuracy in range measurements based on Time of Arrival (TOA) estimation. SLAM algorithms recursively estimates the map of an environment and the pose (position and orientation) of a mobile robot within that environment. The comparative study presented here involves the performance analysis of implementing in parallel an UWB localization based system and a SLAM algorithm on a mobile robot navigating within an environment. Real time results as well as error analysis are also shown in this work.

Comprehensive evaluation of attitude and orbit estimation using real earth magnetic field data

NASA Technical Reports Server (NTRS)

Deutschmann, Julie; Bar-Itzhack, Itzhack

1997-01-01

A single, augmented extended Kalman filter (EKF) which simultaneously and autonomously estimates spacecraft attitude and orbit was developed and tested with simulated and real magnetometer and rate data. Since the earth's magnetic field is a function of time and position, and since time is accurately known, the differences between the computed and measured magnetic field components, as measured by the magnetometers throughout the entire spacecraft's orbit, are a function of orbit and attitude errors. These differences can be used to estimate the orbit and attitude. The test results of the EKF with magnetometer and gyro data from three NASA satellites are presented and evaluated.

An influential factor for external radiation dose estimation for residents after the Fukushima Daiichi Nuclear Power Plant accident-time spent outdoors for residents in Iitate Village.

PubMed

Ishikawa, Tetsuo; Yasumura, Seiji; Ohtsuru, Akira; Sakai, Akira; Akahane, Keiichi; Yonai, Shunsuke; Sakata, Ritsu; Ozasa, Kotaro; Hayashi, Masayuki; Ohira, Tetsuya; Kamiya, Kenji; Abe, Masafumi

2016-06-01

Many studies have been conducted on radiation doses to residents after the Fukushima Daiichi Nuclear Power Plant (FDNPP) accident. Time spent outdoors is an influential factor for external dose estimation. Since little information was available on actual time spent outdoors for residents, different values of average time spent outdoors per day have been used in dose estimation studies on the FDNPP accident. The most conservative value of 24 h was sometimes used, while 2.4 h was adopted for indoor workers in the UNSCEAR 2013 report. Fukushima Medical University has been estimating individual external doses received by residents as a part of the Fukushima Health Management Survey by collecting information on the records of moves and activities (the Basic Survey) after the accident from each resident. In the present study, these records were analyzed to estimate an average time spent outdoors per day. As an example, in Iitate Village, its arithmetic mean was 2.08 h (95% CI: 1.64-2.51) for a total of 170 persons selected from respondents to the Basic Survey. This is a much smaller value than commonly assumed. When 2.08 h is used for the external dose estimation, the dose is about 25% (23-26% when using the above 95% CI) less compared with the dose estimated for the commonly used value of 8 h.

Time scale bias in erosion rates of glaciated landscapes

PubMed Central

Ganti, Vamsi; von Hagke, Christoph; Scherler, Dirk; Lamb, Michael P.; Fischer, Woodward W.; Avouac, Jean-Philippe

2016-01-01

Deciphering erosion rates over geologic time is fundamental for understanding the interplay between climate, tectonic, and erosional processes. Existing techniques integrate erosion over different time scales, and direct comparison of such rates is routinely done in earth science. On the basis of a global compilation, we show that erosion rate estimates in glaciated landscapes may be affected by a systematic averaging bias that produces higher estimated erosion rates toward the present, which do not reflect straightforward changes in erosion rates through time. This trend can result from a heavy-tailed distribution of erosional hiatuses (that is, time periods where no or relatively slow erosion occurs). We argue that such a distribution can result from the intermittency of erosional processes in glaciated landscapes that are tightly coupled to climate variability from decadal to millennial time scales. In contrast, we find no evidence for a time scale bias in spatially averaged erosion rates of landscapes dominated by river incision. We discuss the implications of our findings in the context of the proposed coupling between climate and tectonics, and interpreting erosion rate estimates with different averaging time scales through geologic time. PMID:27713925

Time scale bias in erosion rates of glaciated landscapes.

PubMed

Ganti, Vamsi; von Hagke, Christoph; Scherler, Dirk; Lamb, Michael P; Fischer, Woodward W; Avouac, Jean-Philippe

2016-10-01

Deciphering erosion rates over geologic time is fundamental for understanding the interplay between climate, tectonic, and erosional processes. Existing techniques integrate erosion over different time scales, and direct comparison of such rates is routinely done in earth science. On the basis of a global compilation, we show that erosion rate estimates in glaciated landscapes may be affected by a systematic averaging bias that produces higher estimated erosion rates toward the present, which do not reflect straightforward changes in erosion rates through time. This trend can result from a heavy-tailed distribution of erosional hiatuses (that is, time periods where no or relatively slow erosion occurs). We argue that such a distribution can result from the intermittency of erosional processes in glaciated landscapes that are tightly coupled to climate variability from decadal to millennial time scales. In contrast, we find no evidence for a time scale bias in spatially averaged erosion rates of landscapes dominated by river incision. We discuss the implications of our findings in the context of the proposed coupling between climate and tectonics, and interpreting erosion rate estimates with different averaging time scales through geologic time.

Multiple rings around Wolf-Rayet evolution

NASA Technical Reports Server (NTRS)

Marston, A. P.

1995-01-01

We present optical narrow-band imaging of multiple rings existing around galactic Wolf-Rayet (WR) stars. The existence of multiple rings of material around Wolf-Rayet stars clearly illustrates the various phases of evolution that massive stars go through. The objects presented here show evidence of a three stage evolution. O stars produce an outer ring with the cavity being partially filled by ejecta from a red supergiant of luminous blue variable phase. A wind from the Wolf-Rayet star then passes into the ejecta materials. A simple model is presented for this three stage evolution. Using observations of the size and dynamics of the rings allows estimates of time scales for each stage of the massive star evolution. These are consistent with recent theoretical evolutionary models. Mass estimates for the ejecta, from the model presented, are consistent with previous ring nebula mass estimates from IRAS data, showing a number of ring nebulae to have large masses, most of which must in be in the form of neutral material. Finally, we illustrate how further observations will allow the determination of many of the parameters of the evolution of massive stars such as total mass loss, average mass loss rates, stellar abundances, and total time spent in each evolutionary phase.

Impacts and the origin of life

NASA Technical Reports Server (NTRS)

Oberbeck, Verne R.; Fogleman, Guy

1989-01-01

Consideration is given to the estimate of Maher and Stevenson (1988) of the time at which life could have developed on earth through chemical evolution within a time interval between impact events, assuming chemical or prebiotic evolution times of 100,000 to 10,000,000 yrs. An error in the equations used to determine the time periods between impact events in estimating this time is noted. A revised equation is presented and used to calculate the point in time at which impact events became infrequent enough for life to form. By using this equation, the finding of Maher and Stevenson that life could have first originated between 4,100 and 4,300 million years ago is changed to 3,700 to 4,000 million years ago.

Accurate acceleration of kinetic Monte Carlo simulations through the modification of rate constants.

PubMed

Chatterjee, Abhijit; Voter, Arthur F

2010-05-21

We present a novel computational algorithm called the accelerated superbasin kinetic Monte Carlo (AS-KMC) method that enables a more efficient study of rare-event dynamics than the standard KMC method while maintaining control over the error. In AS-KMC, the rate constants for processes that are observed many times are lowered during the course of a simulation. As a result, rare processes are observed more frequently than in KMC and the time progresses faster. We first derive error estimates for AS-KMC when the rate constants are modified. These error estimates are next employed to develop a procedure for lowering process rates with control over the maximum error. Finally, numerical calculations are performed to demonstrate that the AS-KMC method captures the correct dynamics, while providing significant CPU savings over KMC in most cases. We show that the AS-KMC method can be employed with any KMC model, even when no time scale separation is present (although in such cases no computational speed-up is observed), without requiring the knowledge of various time scales present in the system.

Quantum algorithms for Gibbs sampling and hitting-time estimation

DOE PAGES

Chowdhury, Anirban Narayan; Somma, Rolando D.

2017-02-01

In this paper, we present quantum algorithms for solving two problems regarding stochastic processes. The first algorithm prepares the thermal Gibbs state of a quantum system and runs in time almost linear in √Nβ/Ζ and polynomial in log(1/ϵ), where N is the Hilbert space dimension, β is the inverse temperature, Ζ is the partition function, and ϵ is the desired precision of the output state. Our quantum algorithm exponentially improves the dependence on 1/ϵ and quadratically improves the dependence on β of known quantum algorithms for this problem. The second algorithm estimates the hitting time of a Markov chain. Formore » a sparse stochastic matrix Ρ, it runs in time almost linear in 1/(ϵΔ 3/2), where ϵ is the absolute precision in the estimation and Δ is a parameter determined by Ρ, and whose inverse is an upper bound of the hitting time. Our quantum algorithm quadratically improves the dependence on 1/ϵ and 1/Δ of the analog classical algorithm for hitting-time estimation. Finally, both algorithms use tools recently developed in the context of Hamiltonian simulation, spectral gap amplification, and solving linear systems of equations.« less

Design of a two-level power system linear state estimator

NASA Astrophysics Data System (ADS)

Yang, Tao

The availability of synchro-phasor data has raised the possibility of a linear state estimator if the inputs are only complex currents and voltages and if there are enough such measurements to meet observability and redundancy requirements. Moreover, the new digital substations can perform some of the computation at the substation itself resulting in a more accurate two-level state estimator. The objective of this research is to develop a two-level linear state estimator processing synchro-phasor data and estimating the states at both the substation level and the control center level. Both the mathematical algorithms that are different from those in the present state estimation procedure and the layered architecture of databases, communications and application programs that are required to support this two-level linear state estimator are described in this dissertation. Besides, as the availability of phasor measurements at substations will increase gradually, this research also describes how the state estimator can be enhanced to handle both the traditional state estimator and the proposed linear state estimator simultaneously. This provides a way to immediately utilize the benefits in those parts of the system where such phasor measurements become available and provides a pathway to transition to the smart grid of the future. The design procedure of the two-level state estimator is applied to two study systems. The first study system is the IEEE-14 bus system. The second one is the 179 bus Western Electricity Coordinating Council (WECC) system. The static database for the substations is constructed from the power flow data of these systems and the real-time measurement database is produced by a power system dynamic simulating tool (TSAT). Time-skew problems that may be caused by communication delays are also considered and simulated. We used the Network Simulator (NS) tool to simulate a simple communication system and analyse its time delay performance. These time delays were too small to affect the results especially since the measurement data is time-stamped and the state estimator for these small systems could be run with subseconf frequency. Keywords: State Estimation, Synchro-Phasor Measurement, Distributed System, Energy Control Center, Substation, Time-skew

Sequential Bayesian Filters for Estimating Time Series of Wrapped and Unwrapped Angles with Hyperparameter Estimation

NASA Astrophysics Data System (ADS)

Umehara, Hiroaki; Okada, Masato; Naruse, Yasushi

2018-03-01

The estimation of angular time series data is a widespread issue relating to various situations involving rotational motion and moving objects. There are two kinds of problem settings: the estimation of wrapped angles, which are principal values in a circular coordinate system (e.g., the direction of an object), and the estimation of unwrapped angles in an unbounded coordinate system such as for the positioning and tracking of moving objects measured by the signal-wave phase. Wrapped angles have been estimated in previous studies by sequential Bayesian filtering; however, the hyperparameters that are to be solved and that control the properties of the estimation model were given a priori. The present study establishes a procedure of hyperparameter estimation from the observation data of angles only, using the framework of Bayesian inference completely as the maximum likelihood estimation. Moreover, the filter model is modified to estimate the unwrapped angles. It is proved that without noise our model reduces to the existing algorithm of Itoh's unwrapping transform. It is numerically confirmed that our model is an extension of unwrapping estimation from Itoh's unwrapping transform to the case with noise.

Individual differences in non-symbolic numerical abilities predict mathematical achievements but contradict ATOM.

PubMed

Agrillo, Christian; Piffer, Laura; Adriano, Andrea

2013-07-01

A significant debate surrounds the nature of the cognitive mechanisms involved in non-symbolic number estimation. Several studies have suggested the existence of the same cognitive system for estimation of time, space, and number, called "a theory of magnitude" (ATOM). In addition, researchers have proposed the theory that non-symbolic number abilities might support our mathematical skills. Despite the large number of studies carried out, no firm conclusions can be drawn on either topic. In the present study, we correlated the performance of adults on non-symbolic magnitude estimations and symbolic numerical tasks. Non-symbolic magnitude abilities were assessed by asking participants to estimate which auditory tone lasted longer (time), which line was longer (space), and which group of dots was more numerous (number). To assess symbolic numerical abilities, participants were required to perform mental calculations and mathematical reasoning. We found a positive correlation between non-symbolic and symbolic numerical abilities. On the other hand, no correlation was found among non-symbolic estimations of time, space, and number. Our study supports the idea that mathematical abilities rely on rudimentary numerical skills that predate verbal language. By contrast, the lack of correlation among non-symbolic estimations of time, space, and number is incompatible with the idea that these magnitudes are entirely processed by the same cognitive system.

An overall estimation of losses caused by diseases in the Brazilian fish farms.

PubMed

Tavares-Dias, Marcos; Martins, Maurício Laterça

2017-12-01

Parasitic and infectious diseases are common in finfish, but are difficult to accurately estimate the economic impacts on the production in a country with large dimensions like Brazil. The aim of this study was to estimate the costs caused by economic losses of finfish due to mortality by diseases in Brazil. A model for estimating the costs related to parasitic and bacterial diseases in farmed fish and an estimative of these economic impacts are presented. We used official data of production and mortality of finfish for rough estimation of economic losses. The losses herein presented are related to direct and indirect economic costs for freshwater farmed fish, which were estimated in US$ 84 million per year. Finally, it was possible to establish by the first time an estimative of overall losses in finfish production in Brazil using data available from production. Therefore, this current estimative must help researchers and policy makers to approximate the economic costs of diseases for fish farming industry, as well as for developing of public policies on the control measures of diseases and priority research lines.

Estimating contaminant loads in rivers: An application of adjusted maximum likelihood to type 1 censored data

USGS Publications Warehouse

Cohn, Timothy A.

2005-01-01

This paper presents an adjusted maximum likelihood estimator (AMLE) that can be used to estimate fluvial transport of contaminants, like phosphorus, that are subject to censoring because of analytical detection limits. The AMLE is a generalization of the widely accepted minimum variance unbiased estimator (MVUE), and Monte Carlo experiments confirm that it shares essentially all of the MVUE's desirable properties, including high efficiency and negligible bias. In particular, the AMLE exhibits substantially less bias than alternative censored‐data estimators such as the MLE (Tobit) or the MLE followed by a jackknife. As with the MLE and the MVUE the AMLE comes close to achieving the theoretical Frechet‐Cramér‐Rao bounds on its variance. This paper also presents a statistical framework, applicable to both censored and complete data, for understanding and estimating the components of uncertainty associated with load estimates. This can serve to lower the cost and improve the efficiency of both traditional and real‐time water quality monitoring.

Adaptive Fault Detection on Liquid Propulsion Systems with Virtual Sensors: Algorithms and Architectures

NASA Technical Reports Server (NTRS)

Matthews, Bryan L.; Srivastava, Ashok N.

2010-01-01

Prior to the launch of STS-119 NASA had completed a study of an issue in the flow control valve (FCV) in the Main Propulsion System of the Space Shuttle using an adaptive learning method known as Virtual Sensors. Virtual Sensors are a class of algorithms that estimate the value of a time series given other potentially nonlinearly correlated sensor readings. In the case presented here, the Virtual Sensors algorithm is based on an ensemble learning approach and takes sensor readings and control signals as input to estimate the pressure in a subsystem of the Main Propulsion System. Our results indicate that this method can detect faults in the FCV at the time when they occur. We use the standard deviation of the predictions of the ensemble as a measure of uncertainty in the estimate. This uncertainty estimate was crucial to understanding the nature and magnitude of transient characteristics during startup of the engine. This paper overviews the Virtual Sensors algorithm and discusses results on a comprehensive set of Shuttle missions and also discusses the architecture necessary for deploying such algorithms in a real-time, closed-loop system or a human-in-the-loop monitoring system. These results were presented at a Flight Readiness Review of the Space Shuttle in early 2009.

Realizing actual feedback control of complex network

NASA Astrophysics Data System (ADS)

Tu, Chengyi; Cheng, Yuhua

2014-06-01

In this paper, we present the concept of feedbackability and how to identify the Minimum Feedbackability Set of an arbitrary complex directed network. Furthermore, we design an estimator and a feedback controller accessing one MFS to realize actual feedback control, i.e. control the system to our desired state according to the estimated system internal state from the output of estimator. Last but not least, we perform numerical simulations of a small linear time-invariant dynamics network and a real simple food network to verify the theoretical results. The framework presented here could make an arbitrary complex directed network realize actual feedback control and deepen our understanding of complex systems.

A simple model for the estimation of rain-induced attenuation along earth-space paths at millimeter wavelengths

NASA Technical Reports Server (NTRS)

Stutzman, W. L.; Dishman, W. K.

1982-01-01

A simple attenuation model (SAM) is presented for estimating rain-induced attenuation along an earth-space path. The rain model uses an effective spatial rain distribution which is uniform for low rain rates and which has an exponentially shaped horizontal rain profile for high rain rates. When compared to other models, the SAM performed well in the important region of low percentages of time, and had the lowest percent standard deviation of all percent time values tested.

Effects of Assuming Independent Component Failure Times, if They Actually Dependent, in a Series System.

DTIC Science & Technology

1984-10-26

test for independence; ons i ser, -, of the poduct life estimator; dependent risks; 119 ASRACT Coniinue on ’wme-se f nereiary-~and iaen r~f> by Worst...the failure times associated with different failure - modes when we really should use a bivariate (or multivariate) distribution, then what is the...dependencies may be present, then what is the magnitude of the estimation error? S The third specific aim will attempt to obtain bounds on the

Investment opportunity : the FPL low-cost solar dry kiln

Treesearch

George B. Harpole

1988-01-01

Two equations are presented that may be used to estimate a maximum investment limit and working capital requirements for the FPL low-cost solar dry kiln systems. The equations require data for drying cycle time, green lumber cost, and kiln-dried lumber costs. Results are intended to provide a preliminary estimate.

Is the Professor In? Faculty Presence during Office Hours

ERIC Educational Resources Information Center

Pfund, Rory A.; Rogan, Jessica D.; Burnham, Bryan R.; Norcross, John C.

2013-01-01

Two studies were conducted on the availability of full-time faculty during their posted office hours. In the first, we surveyed students and faculty at a single university on their estimates of the percentage of faculty present during office hours. Students ("N" = 380) and faculty ("N" = 176) estimated that 77% and 83% of…

ESTIMATION OF EARLY INTERNAL DOSES TO FUKUSHIMA RESIDENTS AFTER THE NUCLEAR DISASTER BASED ON THE ATMOSPHERIC DISPERSION SIMULATION.

PubMed

Kim, Eunjoo; Tani, Kotaro; Kunishima, Naoaki; Kurihara, Osamu; Sakai, Kazuo; Akashi, Makoto

2016-11-01

Estimating the early internal doses to residents in the Fukushima Daiichi Nuclear Power Station accident is a difficult task because limited human/environmental measurement data are available. Hence, the feasibility of using atmospheric dispersion simulations created by the Worldwide version of System for Prediction of Environmental Emergency Dose Information 2nd Version (WSPEEDI-II) in the estimation was examined in the present study. This examination was done by comparing the internal doses evaluated based on the human measurements with those calculated using time series air concentration maps ( 131 I and 137 Cs) generated by WSPEEDI-II. The results showed that the latter doses were several times higher than the former doses. However, this discrepancy could be minimised by taking into account personal behaviour data that will be available soon. This article also presents the development of a prototype system for estimating the internal dose based on the simulations. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Phytoplankton production in the Sargasso Sea as determined using optical mooring data

NASA Technical Reports Server (NTRS)

Waters, K. J.; Smith, R. C.; Marra, J.

1994-01-01

Optical measurements from an untended mooring provide high-frequency observations of in-water optical properties and permit the estimation of important biological parameters continuously as a function of time. A 9-month time series, composed of three separate deployments, of optical data from the BIOWATT 1987 deep-sea mooring located in the oligotrophic waters of the Sargasso Sea at 34 deg N, 70 deg W are presented. These data have been tested using several bio-optical models for the purpose of providing a continuous estimate of phytoplankton productivity. The data are discussed in the context of contemporaneous shipboard observations and for future ocean color satellite observations. We present a continuous estimation of phytoplankton productivity for the 9-month time series. Results from the first 70-day deployment are emphasized to demonstrate the utility of optical observations as proxy measures of biological parameters, to present preliminary analysis, and to compare our bio-optical observations with concurrent physical observations. The bio-optical features show variation in response to physical forcings including diel variations of incident solar irradiance, episodic changes corresponding to wind forcing, variability caused by advective mesoscale eddy events in the vicinity of the mooring, and seasonal variability corresponding to changes in solar radiation, shoaling of the mixed layer depth, and succession of phytoplankton populations.

Investigation of safety analysis methods using computer vision techniques

NASA Astrophysics Data System (ADS)

Shirazi, Mohammad Shokrolah; Morris, Brendan Tran

2017-09-01

This work investigates safety analysis methods using computer vision techniques. The vision-based tracking system is developed to provide the trajectory of road users including vehicles and pedestrians. Safety analysis methods are developed to estimate time to collision (TTC) and postencroachment time (PET) that are two important safety measurements. Corresponding algorithms are presented and their advantages and drawbacks are shown through their success in capturing the conflict events in real time. The performance of the tracking system is evaluated first, and probability density estimation of TTC and PET are shown for 1-h monitoring of a Las Vegas intersection. Finally, an idea of an intersection safety map is introduced, and TTC values of two different intersections are estimated for 1 day from 8:00 a.m. to 6:00 p.m.

Characterization of a symbol rate timing recovery technique for a 2B1Q digital receiver

NASA Astrophysics Data System (ADS)

Aboulnasr, T.; Hage, M.; Sayar, B.; Aly, S.

1994-02-01

This paper presents a study of several implementations of the Mueller and Muller symbol rate timing recovery algorithm for ISDN transmission over digital subscriber loops (DSL). Implementations of this algorithm using various estimates of a specified timing function are investigated. It will be shown that despite the fact that all of the estimates considered are derived based on one set of conditions, their performance varies widely in a real system. The intrinsic properties of these estimates are first analyzed, then their performance on real subscriber loops is studied through extensive simulations of a practical digital receiver. The effect of various system parameters such as channel distortion and additive noise are included. Possible sources of convergence problems are also identified and corrective action proposed.

Nonlinear finite element model updating for damage identification of civil structures using batch Bayesian estimation

NASA Astrophysics Data System (ADS)

Ebrahimian, Hamed; Astroza, Rodrigo; Conte, Joel P.; de Callafon, Raymond A.

2017-02-01

This paper presents a framework for structural health monitoring (SHM) and damage identification of civil structures. This framework integrates advanced mechanics-based nonlinear finite element (FE) modeling and analysis techniques with a batch Bayesian estimation approach to estimate time-invariant model parameters used in the FE model of the structure of interest. The framework uses input excitation and dynamic response of the structure and updates a nonlinear FE model of the structure to minimize the discrepancies between predicted and measured response time histories. The updated FE model can then be interrogated to detect, localize, classify, and quantify the state of damage and predict the remaining useful life of the structure. As opposed to recursive estimation methods, in the batch Bayesian estimation approach, the entire time history of the input excitation and output response of the structure are used as a batch of data to estimate the FE model parameters through a number of iterations. In the case of non-informative prior, the batch Bayesian method leads to an extended maximum likelihood (ML) estimation method to estimate jointly time-invariant model parameters and the measurement noise amplitude. The extended ML estimation problem is solved efficiently using a gradient-based interior-point optimization algorithm. Gradient-based optimization algorithms require the FE response sensitivities with respect to the model parameters to be identified. The FE response sensitivities are computed accurately and efficiently using the direct differentiation method (DDM). The estimation uncertainties are evaluated based on the Cramer-Rao lower bound (CRLB) theorem by computing the exact Fisher Information matrix using the FE response sensitivities with respect to the model parameters. The accuracy of the proposed uncertainty quantification approach is verified using a sampling approach based on the unscented transformation. Two validation studies, based on realistic structural FE models of a bridge pier and a moment resisting steel frame, are performed to validate the performance and accuracy of the presented nonlinear FE model updating approach and demonstrate its application to SHM. These validation studies show the excellent performance of the proposed framework for SHM and damage identification even in the presence of high measurement noise and/or way-out initial estimates of the model parameters. Furthermore, the detrimental effects of the input measurement noise on the performance of the proposed framework are illustrated and quantified through one of the validation studies.

Improving spatio-temporal benefit transfers for pest control by generalist predators in cotton in the southwestern U.S.

USGS Publications Warehouse

Wiederholt, Ruscena; Bagstad, Kenneth J.; McCracken, Gary F.; Diffendorfer, Jay E.; Loomis, John B.; Semmens, Darius J.; Russell, Amy L.; Sansone, Chris; LaSharr, Kelsie; Cryan, Paul; Reynoso, Claudia; Medellin, Rodrigo A.; Lopez-Hoffman, Laura

2017-01-01

Given rapid changes in agricultural practice, it is critical to understand how alterations in ecological, technological, and economic conditions over time and space impact ecosystem services in agroecosystems. Here, we present a benefit transfer approach to quantify cotton pest-control services provided by a generalist predator, the Mexican free-tailed bat (Tadarida brasiliensis mexicana), in the southwestern United States. We show that pest-control estimates derived using (1) a compound spatial–temporal model – which incorporates spatial and temporal variability in crop pest-control service values – are likely to exhibit less error than those derived using (2) a simple-spatial model (i.e., a model that extrapolates values derived for one area directly, without adjustment, to other areas) or (3) a simple-temporal model (i.e., a model that extrapolates data from a few points in time over longer time periods). Using our compound spatial–temporal approach, the annualized pest-control value was \\$12.2 million, in contrast to an estimate of \\$70.1 million (5.7 times greater), obtained from the simple-spatial approach. Using estimates from one year (simple-temporal approach) revealed large value differences (0.4 times smaller to 2 times greater). Finally, we present a detailed protocol for valuing pest-control services, which can be used to develop robust pest-control transfer functions for generalist predators in agroecosystems.

Efficient implementation of a real-time estimation system for thalamocortical hidden Parkinsonian properties

NASA Astrophysics Data System (ADS)

Yang, Shuangming; Deng, Bin; Wang, Jiang; Li, Huiyan; Liu, Chen; Fietkiewicz, Chris; Loparo, Kenneth A.

2017-01-01

Real-time estimation of dynamical characteristics of thalamocortical cells, such as dynamics of ion channels and membrane potentials, is useful and essential in the study of the thalamus in Parkinsonian state. However, measuring the dynamical properties of ion channels is extremely challenging experimentally and even impossible in clinical applications. This paper presents and evaluates a real-time estimation system for thalamocortical hidden properties. For the sake of efficiency, we use a field programmable gate array for strictly hardware-based computation and algorithm optimization. In the proposed system, the FPGA-based unscented Kalman filter is implemented into a conductance-based TC neuron model. Since the complexity of TC neuron model restrains its hardware implementation in parallel structure, a cost efficient model is proposed to reduce the resource cost while retaining the relevant ionic dynamics. Experimental results demonstrate the real-time capability to estimate thalamocortical hidden properties with high precision under both normal and Parkinsonian states. While it is applied to estimate the hidden properties of the thalamus and explore the mechanism of the Parkinsonian state, the proposed method can be useful in the dynamic clamp technique of the electrophysiological experiments, the neural control engineering and brain-machine interface studies.

Noninvasive microwave ablation zone radii estimation using x-ray CT image analysis.

PubMed

Weiss, Noam; Goldberg, S Nahum; Nissenbaum, Yitzhak; Sosna, Jacob; Azhari, Haim

2016-08-01

The aims of this study were to noninvasively and automatically estimate both the radius of the ablated liver tissue and the radius encircling the treated zone, which also defines where the tissue is definitely untreated during a microwave (MW) thermal ablation procedure. Fourteen ex vivo bovine fresh liver specimens were ablated at 40 W using a 14 G microwave antenna, for durations of 3, 6, 8, and 10 min. The tissues were scanned every 5 s during the ablation using an x-ray CT scanner. In order to estimate the radius of the ablation zone, the acquired images were transformed into a polar presentation by displaying the Hounsfield units (HU) as a function of angle and radius. From this polar presentation, the average HU radial profile was analyzed at each time point and the ablation zone radius was estimated. In addition, textural analysis was applied to the original CT images. The proposed algorithm identified high entropy regions and estimated the treated zone radius per time. The estimated ablated zone radii as a function of treatment durations were compared, by means of correlation coefficient and root mean square error (RMSE) to gross pathology measurements taken immediately post-treatment from similarly ablated tissue. Both the estimated ablation radii and the treated zone radii demonstrated strong correlation with the measured gross pathology values (R(2) ≥ 0.89 and R(2) ≥ 0.86, respectively). The automated ablation radii estimation had an average discrepancy of less than 1 mm (RMSE = 0.65 mm) from the gross pathology measured values, while the treated zone radii showed a slight overestimation of approximately 1.5 mm (RMSE = 1.6 mm). Noninvasive monitoring of MW ablation using x-ray CT and image analysis is feasible. Automatic estimations of the ablation zone radius and the radius encompassing the treated zone that highly correlate with actual ablation measured values can be obtained. This technique can therefore potentially be used to obtain real time monitoring and improve the clinical outcome.

Spatio-temporal Granger causality: a new framework

PubMed Central

Luo, Qiang; Lu, Wenlian; Cheng, Wei; Valdes-Sosa, Pedro A.; Wen, Xiaotong; Ding, Mingzhou; Feng, Jianfeng

2015-01-01

That physiological oscillations of various frequencies are present in fMRI signals is the rule, not the exception. Herein, we propose a novel theoretical framework, spatio-temporal Granger causality, which allows us to more reliably and precisely estimate the Granger causality from experimental datasets possessing time-varying properties caused by physiological oscillations. Within this framework, Granger causality is redefined as a global index measuring the directed information flow between two time series with time-varying properties. Both theoretical analyses and numerical examples demonstrate that Granger causality is a monotonically increasing function of the temporal resolution used in the estimation. This is consistent with the general principle of coarse graining, which causes information loss by smoothing out very fine-scale details in time and space. Our results confirm that the Granger causality at the finer spatio-temporal scales considerably outperforms the traditional approach in terms of an improved consistency between two resting-state scans of the same subject. To optimally estimate the Granger causality, the proposed theoretical framework is implemented through a combination of several approaches, such as dividing the optimal time window and estimating the parameters at the fine temporal and spatial scales. Taken together, our approach provides a novel and robust framework for estimating the Granger causality from fMRI, EEG, and other related data. PMID:23643924

Empirical estimation of present-day Antarctic glacial isostatic adjustment and ice mass change

NASA Astrophysics Data System (ADS)

Gunter, B. C.; Didova, O.; Riva, R. E. M.; Ligtenberg, S. R. M.; Lenaerts, J. T. M.; King, M. A.; van den Broeke, M. R.; Urban, T.

2014-04-01

This study explores an approach that simultaneously estimates Antarctic mass balance and glacial isostatic adjustment (GIA) through the combination of satellite gravity and altimetry data sets. The results improve upon previous efforts by incorporating a firn densification model to account for firn compaction and surface processes as well as reprocessed data sets over a slightly longer period of time. A range of different Gravity Recovery and Climate Experiment (GRACE) gravity models were evaluated and a new Ice, Cloud, and Land Elevation Satellite (ICESat) surface height trend map computed using an overlapping footprint approach. When the GIA models created from the combination approach were compared to in situ GPS ground station displacements, the vertical rates estimated showed consistently better agreement than recent conventional GIA models. The new empirically derived GIA rates suggest the presence of strong uplift in the Amundsen Sea sector in West Antarctica (WA) and the Philippi/Denman sectors, as well as subsidence in large parts of East Antarctica (EA). The total GIA-related mass change estimates for the entire Antarctic ice sheet ranged from 53 to 103 Gt yr-1, depending on the GRACE solution used, with an estimated uncertainty of ±40 Gt yr-1. Over the time frame February 2003-October 2009, the corresponding ice mass change showed an average value of -100 ± 44 Gt yr-1 (EA: 5 ± 38, WA: -105 ± 22), consistent with other recent estimates in the literature, with regional mass loss mostly concentrated in WA. The refined approach presented in this study shows the contribution that such data combinations can make towards improving estimates of present-day GIA and ice mass change, particularly with respect to determining more reliable uncertainties.

The Informed Railroad Traveler (smartphone application) real-time street parking availability estimation.

DOT National Transportation Integrated Search

2016-10-03

Real-time parking availability information is important in urban areas, and if available could reduce congestion, pollution, and gas consumption. This project presents a software solution called PhonePark for detecting the availability of on-street p...

Wireless data collection system for travel time estimation and traffic performance evaluation.

DOT National Transportation Integrated Search

2012-05-01

This report presents the results of the third and final research and development project of an implementable wireless : travel time data collection system. Utilizing Bluetooth wireless technology as a platform, the prior projects focused on : data co...

Introduction and application of the multiscale coefficient of variation analysis.

PubMed

Abney, Drew H; Kello, Christopher T; Balasubramaniam, Ramesh

2017-10-01

Quantifying how patterns of behavior relate across multiple levels of measurement typically requires long time series for reliable parameter estimation. We describe a novel analysis that estimates patterns of variability across multiple scales of analysis suitable for time series of short duration. The multiscale coefficient of variation (MSCV) measures the distance between local coefficient of variation estimates within particular time windows and the overall coefficient of variation across all time samples. We first describe the MSCV analysis and provide an example analytical protocol with corresponding MATLAB implementation and code. Next, we present a simulation study testing the new analysis using time series generated by ARFIMA models that span white noise, short-term and long-term correlations. The MSCV analysis was observed to be sensitive to specific parameters of ARFIMA models varying in the type of temporal structure and time series length. We then apply the MSCV analysis to short time series of speech phrases and musical themes to show commonalities in multiscale structure. The simulation and application studies provide evidence that the MSCV analysis can discriminate between time series varying in multiscale structure and length.

Relating Time-Dependent Acceleration and Height Using an Elevator

NASA Astrophysics Data System (ADS)

Kinser, Jason M.

2015-04-01

A simple experiment in relating a time-dependent linear acceleration function to height is explored through the use of a smartphone and an elevator. Given acceleration as a function of time1, a(t), the velocity function and position functions are determined through integration as in v (t ) =∫ a (t ) d t (1) and x (t ) =∫ v (t ) dt. Mobile devices such as smartphones or tablets have accelerometers that capture slowly evolving acceleration with respect to time and can deliver those measurements as a CSV file. A recent example measured the oscillations of the elevator as it starts its motion.2 In the application presented here the mobile device is used to estimate the height of the elevator ride. By estimating the functional form of the acceleration of an elevator ride, it is possible to estimate the height of the ride through Eqs. (1) and (2).

A Data-Driven Approach for Daily Real-Time Estimates and Forecasts of Near-Surface Soil Moisture

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Reichle, Rolf H.; Mahanama, Sarith P. P.

2017-01-01

NASAs Soil Moisture Active Passive (SMAP) mission provides global surface soil moisture retrievals with a revisit time of 2-3 days and a latency of 24 hours. Here, to enhance the utility of the SMAP data, we present an approach for improving real-time soil moisture estimates (nowcasts) and for forecasting soil moisture several days into the future. The approach, which involves using an estimate of loss processes (evaporation and drainage) and precipitation to evolve the most recent SMAP retrieval forward in time, is evaluated against subsequent SMAP retrievals themselves. The nowcast accuracy over the continental United States (CONUS) is shown to be markedly higher than that achieved with the simple yet common persistence approach. The accuracy of soil moisture forecasts, which rely on precipitation forecasts rather than on precipitation measurements, is reduced relative to nowcast accuracy but is still significantly higher than that obtained through persistence.

A kinematic model to estimate effective dose of radioactive substances in a human body

NASA Astrophysics Data System (ADS)

Sasaki, S.; Yamada, T.

2013-05-01

The great earthquake occurred in the north-east area in Japan in March 11, 2011. Facility system to control Fukushima Daiichi nuclear power station was completely destroyed by the following giant tsunami. From the damaged reactor containment vessels, an amount of radioactive substances had leaked and diffused in the vicinity of this station. Radiological internal exposure became a serious social issue both in Japan and all over the world. The present study provides an easily understandable, kinematic-based model to estimate the effective dose of radioactive substances in a human body by simplifying the complicated mechanism of metabolism. International Commission on Radiological Protection (ICRP) has developed a sophisticated model, which is well-known as a standard method to calculate the effective dose for radiological protection. However, owing to that ICRP method is fine, it is rather difficult for non-professional people of radiology to gasp the whole images of the movement and the influences of radioactive substances in a human body. Therefore, in the present paper we propose a newly-derived and easily-understandable model to estimate the effective dose. The present method is very similar with the traditional and conventional tank model in hydrology. Ingestion flux of radioactive substances corresponds to rain intensity and the storage of radioactive substances to the water storage in a basin in runoff analysis. The key of the present method is to estimate the energy radiated in the radioactive nuclear disintegration of an atom by using classical theory of β decay and special relativity for various kinds of radioactive atoms. The parameters used in this model are only physical half-time and biological half-time, and there are no operational parameters or coefficients to adjust our theoretical runoff to ICRP. Figure shows the time-varying effective dose with ingestion duration, and we can confirm the validity of our model. The time-varying effective dose with ingestion duration

Errors in the estimation method for the rejection of vibrations in adaptive optics systems

NASA Astrophysics Data System (ADS)

Kania, Dariusz

2017-06-01

In recent years the problem of the mechanical vibrations impact in adaptive optics (AO) systems has been renewed. These signals are damped sinusoidal signals and have deleterious effect on the system. One of software solutions to reject the vibrations is an adaptive method called AVC (Adaptive Vibration Cancellation) where the procedure has three steps: estimation of perturbation parameters, estimation of the frequency response of the plant, update the reference signal to reject/minimalize the vibration. In the first step a very important problem is the estimation method. A very accurate and fast (below 10 ms) estimation method of these three parameters has been presented in several publications in recent years. The method is based on using the spectrum interpolation and MSD time windows and it can be used to estimate multifrequency signals. In this paper the estimation method is used in the AVC method to increase the system performance. There are several parameters that affect the accuracy of obtained results, e.g. CiR - number of signal periods in a measurement window, N - number of samples in the FFT procedure, H - time window order, SNR, b - number of ADC bits, γ - damping ratio of the tested signal. Systematic errors increase when N, CiR, H decrease and when γ increases. The value for systematic error is approximately 10^-10 Hz/Hz for N = 2048 and CiR = 0.1. This paper presents equations that can used to estimate maximum systematic errors for given values of H, CiR and N before the start of the estimation process.

Peak-Seeking Control Using Gradient and Hessian Estimates

NASA Technical Reports Server (NTRS)

Ryan, John J.; Speyer, Jason L.

2010-01-01

A peak-seeking control method is presented which utilizes a linear time-varying Kalman filter. Performance function coordinate and magnitude measurements are used by the Kalman filter to estimate the gradient and Hessian of the performance function. The gradient and Hessian are used to command the system toward a local extremum. The method is naturally applied to multiple-input multiple-output systems. Applications of this technique to a single-input single-output example and a two-input one-output example are presented.

On the estimation of risk associated with an attenuation prediction

NASA Technical Reports Server (NTRS)

Crane, R. K.

1992-01-01

Viewgraphs from a presentation on the estimation of risk associated with an attenuation prediction is presented. Topics covered include: link failure - attenuation exceeding a specified threshold for a specified time interval or intervals; risk - the probability of one or more failures during the lifetime of the link or during a specified accounting interval; the problem - modeling the probability of attenuation by rainfall to provide a prediction of the attenuation threshold for a specified risk; and an accounting for the inadequacy of a model or models.

Problems in the estimation of human exposure to components of acid precipitation precursors.

PubMed Central

Ferris, B G; Spengler, J D

1985-01-01

Problems associated with estimation of human exposure to ambient air pollutants are discussed. Ideally, we would prefer to have some indication of actual dose. For most pollutants this is not presently feasible. Specific problems discussed are adequacy of outdoor monitors; the need to correct for exposures and time spent indoors; the need to have particle size distributions described and the chemistry of the particles presented. These indicate the need to develop lightweight accurate and reliable personal monitors. Images FIGURE 1. PMID:4076094

Indirect estimation of the Convective Lognormal Transfer function model parameters for describing solute transport in unsaturated and undisturbed soil.

PubMed

Mohammadi, Mohammad Hossein; Vanclooster, Marnik

2012-05-01

Solute transport in partially saturated soils is largely affected by fluid velocity distribution and pore size distribution within the solute transport domain. Hence, it is possible to describe the solute transport process in terms of the pore size distribution of the soil, and indirectly in terms of the soil hydraulic properties. In this paper, we present a conceptual approach that allows predicting the parameters of the Convective Lognormal Transfer model from knowledge of soil moisture and the Soil Moisture Characteristic (SMC), parameterized by means of the closed-form model of Kosugi (1996). It is assumed that in partially saturated conditions, the air filled pore volume act as an inert solid phase, allowing the use of the Arya et al. (1999) pragmatic approach to estimate solute travel time statistics from the saturation degree and SMC parameters. The approach is evaluated using a set of partially saturated transport experiments as presented by Mohammadi and Vanclooster (2011). Experimental results showed that the mean solute travel time, μ(t), increases proportionally with the depth (travel distance) and decreases with flow rate. The variance of solute travel time σ²(t) first decreases with flow rate up to 0.4-0.6 Ks and subsequently increases. For all tested BTCs predicted solute transport with μ(t) estimated from the conceptual model performed much better as compared to predictions with μ(t) and σ²(t) estimated from calibration of solute transport at shallow soil depths. The use of μ(t) estimated from the conceptual model therefore increases the robustness of the CLT model in predicting solute transport in heterogeneous soils at larger depths. In view of the fact that reasonable indirect estimates of the SMC can be made from basic soil properties using pedotransfer functions, the presented approach may be useful for predicting solute transport at field or watershed scales. Copyright © 2012 Elsevier B.V. All rights reserved.

Indirect estimation of the Convective Lognormal Transfer function model parameters for describing solute transport in unsaturated and undisturbed soil

NASA Astrophysics Data System (ADS)

Mohammadi, Mohammad Hossein; Vanclooster, Marnik

2012-05-01

Solute transport in partially saturated soils is largely affected by fluid velocity distribution and pore size distribution within the solute transport domain. Hence, it is possible to describe the solute transport process in terms of the pore size distribution of the soil, and indirectly in terms of the soil hydraulic properties. In this paper, we present a conceptual approach that allows predicting the parameters of the Convective Lognormal Transfer model from knowledge of soil moisture and the Soil Moisture Characteristic (SMC), parameterized by means of the closed-form model of Kosugi (1996). It is assumed that in partially saturated conditions, the air filled pore volume act as an inert solid phase, allowing the use of the Arya et al. (1999) pragmatic approach to estimate solute travel time statistics from the saturation degree and SMC parameters. The approach is evaluated using a set of partially saturated transport experiments as presented by Mohammadi and Vanclooster (2011). Experimental results showed that the mean solute travel time, μt, increases proportionally with the depth (travel distance) and decreases with flow rate. The variance of solute travel time σ2t first decreases with flow rate up to 0.4-0.6 Ks and subsequently increases. For all tested BTCs predicted solute transport with μt estimated from the conceptual model performed much better as compared to predictions with μt and σ2t estimated from calibration of solute transport at shallow soil depths. The use of μt estimated from the conceptual model therefore increases the robustness of the CLT model in predicting solute transport in heterogeneous soils at larger depths. In view of the fact that reasonable indirect estimates of the SMC can be made from basic soil properties using pedotransfer functions, the presented approach may be useful for predicting solute transport at field or watershed scales.

Estimating soil hydraulic parameters from transient flow experiments in a centrifuge using parameter optimization technique

USGS Publications Warehouse

Šimůnek, Jirka; Nimmo, John R.

2005-01-01

A modified version of the Hydrus software package that can directly or inversely simulate water flow in a transient centrifugal field is presented. The inverse solver for parameter estimation of the soil hydraulic parameters is then applied to multirotation transient flow experiments in a centrifuge. Using time‐variable water contents measured at a sequence of several rotation speeds, soil hydraulic properties were successfully estimated by numerical inversion of transient experiments. The inverse method was then evaluated by comparing estimated soil hydraulic properties with those determined independently using an equilibrium analysis. The optimized soil hydraulic properties compared well with those determined using equilibrium analysis and steady state experiment. Multirotation experiments in a centrifuge not only offer significant time savings by accelerating time but also provide significantly more information for the parameter estimation procedure compared to multistep outflow experiments in a gravitational field.

Satellite Angular Rate Estimation From Vector Measurements

NASA Technical Reports Server (NTRS)

Azor, Ruth; Bar-Itzhack, Itzhack Y.; Harman, Richard R.

1996-01-01

This paper presents an algorithm for estimating the angular rate vector of a satellite which is based on the time derivatives of vector measurements expressed in a reference and body coordinate. The computed derivatives are fed into a spacial Kalman filter which yields an estimate of the spacecraft angular velocity. The filter, named Extended Interlaced Kalman Filter (EIKF), is an extension of the Kalman filter which, although being linear, estimates the state of a nonlinear dynamic system. It consists of two or three parallel Kalman filters whose individual estimates are fed to one another and are considered as known inputs by the other parallel filter(s). The nonlinear dynamics stem from the nonlinear differential equation that describes the rotation of a three dimensional body. Initial results, using simulated data, and real Rossi X ray Timing Explorer (RXTE) data indicate that the algorithm is efficient and robust.

Subjective time in near and far representational space.

PubMed

Zäch, Peter; Brugger, Peter

2008-03-01

We set out to measure healthy subjects' estimates of temporal duration during the imagination of left and right sides of an object located in either near or far representational space. Duration estimates during the observation of small-scale scenes are shorter than those during the observation of the same scenes presented in a larger scale. It is not known whether a similar space-time relationship also exists for objects merely imagined and whether subjective time varies with a forced focus on either the left or the right side of a mental image. Eyes closed, 40 healthy, right-handed subjects (20 women) had to imagine a standard Swiss railway clock either at a distance of 30 cm or 6 m. They were required to focus on the imagined movement of the second hand and provide estimates of elapsed durations of 15 and 30 seconds. Separate estimates for the left and right side of the clockface were obtained. The magnitude of implicit line bisection error was assessed in a separate task. Irrespective of side of the clockface, duration estimates were shorter for the clockface imagined in far space than for the one imagined immediately in front of the inner eye. For men, but not women, duration judgments (left relative to right side of the clockface) correlated with relative lengths of left and right line segments in the bisection task. Subjective time seems to run faster during the inspection of a small-size compared with a larger-size mental image. This finding underlines the equivalence of the laws that guide both exploration and representation of space. Together with the observed correlation between spatial and temporal measures of lateral asymmetries, the result also illustrates the conceptual similarities in the processing of space and time. The normative data presented here may be useful for clinical applications of the paradigm in patients with hemispatial neglect or a distorted perception of time.

Estimation of Spatiotemporal Sensitivity Using Band-limited Signals with No Additional Acquisitions for k-t Parallel Imaging.

PubMed

Takeshima, Hidenori; Saitoh, Kanako; Nitta, Shuhei; Shiodera, Taichiro; Takeguchi, Tomoyuki; Bannae, Shuhei; Kuhara, Shigehide

2018-03-13

Dynamic MR techniques, such as cardiac cine imaging, benefit from shorter acquisition times. The goal of the present study was to develop a method that achieves short acquisition times, while maintaining a cost-effective reconstruction, for dynamic MRI. k - t sensitivity encoding (SENSE) was identified as the base method to be enhanced meeting these two requirements. The proposed method achieves a reduction in acquisition time by estimating the spatiotemporal (x - f) sensitivity without requiring the acquisition of the alias-free signals, typical of the k - t SENSE technique. The cost-effective reconstruction, in turn, is achieved by a computationally efficient estimation of the x - f sensitivity from the band-limited signals of the aliased inputs. Such band-limited signals are suitable for sensitivity estimation because the strongly aliased signals have been removed. For the same reduction factor 4, the net reduction factor 4 for the proposed method was significantly higher than the factor 2.29 achieved by k - t SENSE. The processing time is reduced from 4.1 s for k - t SENSE to 1.7 s for the proposed method. The image quality obtained using the proposed method proved to be superior (mean squared error [MSE] ± standard deviation [SD] = 6.85 ± 2.73) compared to the k - t SENSE case (MSE ± SD = 12.73 ± 3.60) for the vertical long-axis (VLA) view, as well as other views. In the present study, k - t SENSE was identified as a suitable base method to be improved achieving both short acquisition times and a cost-effective reconstruction. To enhance these characteristics of base method, a novel implementation is proposed, estimating the x - f sensitivity without the need for an explicit scan of the reference signals. Experimental results showed that the acquisition, computational times and image quality for the proposed method were improved compared to the standard k - t SENSE method.

The effects of quantity and depth of processing on children's time perception.

PubMed

Arlin, M

1986-08-01

Two experiments were conducted to investigate the effects of quantity and depth of processing on children's time perception. These experiments tested the appropriateness of two adult time-perception models (attentional and storage size) for younger ages. Children were given stimulus sets of equal time which varied by level of processing (deep/shallow) and quantity (list length). In the first experiment, 28 children in Grade 6 reproduced presentation times of various quantities of pictures under deep (living/nonliving categorization) or shallow (repeating label) conditions. Students also compared pairs of durations. In the second experiment, 128 children in Grades K, 2, 4, and 6 reproduced presentation times under similar conditions with three or six pictures and with deep or shallow processing requirements. Deep processing led to decreased estimation of time. Higher quantity led to increased estimation of time. Comparative judgments were influenced by quantity. The interaction between age and depth of processing was significant. Older children were more affected by depth differences than were younger children. Results were interpreted as supporting different aspects of each adult model as explanations of children's time perception. The processing effect supported the attentional model and the quantity effect supported the storage size model.

Estimating Vehicle Fuel Consumption and Emissions Using GPS Big Data

PubMed Central

Kan, Zihan; Zhang, Xia

2018-01-01

The energy consumption and emissions from vehicles adversely affect human health and urban sustainability. Analysis of GPS big data collected from vehicles can provide useful insights about the quantity and distribution of such energy consumption and emissions. Previous studies, which estimated fuel consumption/emissions from traffic based on GPS sampled data, have not sufficiently considered vehicle activities and may have led to erroneous estimations. By adopting the analytical construct of the space-time path in time geography, this study proposes methods that more accurately estimate and visualize vehicle energy consumption/emissions based on analysis of vehicles’ mobile activities (MA) and stationary activities (SA). First, we build space-time paths of individual vehicles, extract moving parameters, and identify MA and SA from each space-time path segment (STPS). Then we present an N-Dimensional framework for estimating and visualizing fuel consumption/emissions. For each STPS, fuel consumption, hot emissions, and cold start emissions are estimated based on activity type, i.e., MA, SA with engine-on and SA with engine-off. In the case study, fuel consumption and emissions of a single vehicle and a road network are estimated and visualized with GPS data. The estimation accuracy of the proposed approach is 88.6%. We also analyze the types of activities that produced fuel consumption on each road segment to explore the patterns and mechanisms of fuel consumption in the study area. The results not only show the effectiveness of the proposed approaches in estimating fuel consumption/emissions but also indicate their advantages for uncovering the relationships between fuel consumption and vehicles’ activities in road networks. PMID:29561813

Estimating Vehicle Fuel Consumption and Emissions Using GPS Big Data.

PubMed

Kan, Zihan; Tang, Luliang; Kwan, Mei-Po; Zhang, Xia

2018-03-21

The energy consumption and emissions from vehicles adversely affect human health and urban sustainability. Analysis of GPS big data collected from vehicles can provide useful insights about the quantity and distribution of such energy consumption and emissions. Previous studies, which estimated fuel consumption/emissions from traffic based on GPS sampled data, have not sufficiently considered vehicle activities and may have led to erroneous estimations. By adopting the analytical construct of the space-time path in time geography, this study proposes methods that more accurately estimate and visualize vehicle energy consumption/emissions based on analysis of vehicles' mobile activities ( MA ) and stationary activities ( SA ). First, we build space-time paths of individual vehicles, extract moving parameters, and identify MA and SA from each space-time path segment (STPS). Then we present an N-Dimensional framework for estimating and visualizing fuel consumption/emissions. For each STPS, fuel consumption, hot emissions, and cold start emissions are estimated based on activity type, i.e., MA , SA with engine-on and SA with engine-off. In the case study, fuel consumption and emissions of a single vehicle and a road network are estimated and visualized with GPS data. The estimation accuracy of the proposed approach is 88.6%. We also analyze the types of activities that produced fuel consumption on each road segment to explore the patterns and mechanisms of fuel consumption in the study area. The results not only show the effectiveness of the proposed approaches in estimating fuel consumption/emissions but also indicate their advantages for uncovering the relationships between fuel consumption and vehicles' activities in road networks.

Flight Investigation of Prescribed Simultaneous Independent Surface Excitations for Real-Time Parameter Identification

NASA Technical Reports Server (NTRS)

Moes, Timothy R.; Smith, Mark S.; Morelli, Eugene A.

2003-01-01

Near real-time stability and control derivative extraction is required to support flight demonstration of Intelligent Flight Control System (IFCS) concepts being developed by NASA, academia, and industry. Traditionally, flight maneuvers would be designed and flown to obtain stability and control derivative estimates using a postflight analysis technique. The goal of the IFCS concept is to be able to modify the control laws in real time for an aircraft that has been damaged in flight. In some IFCS implementations, real-time parameter identification (PID) of the stability and control derivatives of the damaged aircraft is necessary for successfully reconfiguring the control system. This report investigates the usefulness of Prescribed Simultaneous Independent Surface Excitations (PreSISE) to provide data for rapidly obtaining estimates of the stability and control derivatives. Flight test data were analyzed using both equation-error and output-error PID techniques. The equation-error PID technique is known as Fourier Transform Regression (FTR) and is a frequency-domain real-time implementation. Selected results were compared with a time-domain output-error technique. The real-time equation-error technique combined with the PreSISE maneuvers provided excellent derivative estimation in the longitudinal axis. However, the PreSISE maneuvers as presently defined were not adequate for accurate estimation of the lateral-directional derivatives.

Evaluation of precipitation estimates over CONUS derived from satellite, radar, and rain gauge datasets (2002-2012)

NASA Astrophysics Data System (ADS)

Prat, O. P.; Nelson, B. R.

2014-10-01

We use a suite of quantitative precipitation estimates (QPEs) derived from satellite, radar, and surface observations to derive precipitation characteristics over CONUS for the period 2002-2012. This comparison effort includes satellite multi-sensor datasets (bias-adjusted TMPA 3B42, near-real time 3B42RT), radar estimates (NCEP Stage IV), and rain gauge observations. Remotely sensed precipitation datasets are compared with surface observations from the Global Historical Climatology Network (GHCN-Daily) and from the PRISM (Parameter-elevation Regressions on Independent Slopes Model). The comparisons are performed at the annual, seasonal, and daily scales over the River Forecast Centers (RFCs) for CONUS. Annual average rain rates present a satisfying agreement with GHCN-D for all products over CONUS (± 6%). However, differences at the RFC are more important in particular for near-real time 3B42RT precipitation estimates (-33 to +49%). At annual and seasonal scales, the bias-adjusted 3B42 presented important improvement when compared to its near real time counterpart 3B42RT. However, large biases remained for 3B42 over the Western US for higher average accumulation (≥ 5 mm day-1) with respect to GHCN-D surface observations. At the daily scale, 3B42RT performed poorly in capturing extreme daily precipitation (> 4 in day-1) over the Northwest. Furthermore, the conditional analysis and the contingency analysis conducted illustrated the challenge of retrieving extreme precipitation from remote sensing estimates.

Methodologies for Adaptive Flight Envelope Estimation and Protection

NASA Technical Reports Server (NTRS)

Tang, Liang; Roemer, Michael; Ge, Jianhua; Crassidis, Agamemnon; Prasad, J. V. R.; Belcastro, Christine

2009-01-01

This paper reports the latest development of several techniques for adaptive flight envelope estimation and protection system for aircraft under damage upset conditions. Through the integration of advanced fault detection algorithms, real-time system identification of the damage/faulted aircraft and flight envelop estimation, real-time decision support can be executed autonomously for improving damage tolerance and flight recoverability. Particularly, a bank of adaptive nonlinear fault detection and isolation estimators were developed for flight control actuator faults; a real-time system identification method was developed for assessing the dynamics and performance limitation of impaired aircraft; online learning neural networks were used to approximate selected aircraft dynamics which were then inverted to estimate command margins. As off-line training of network weights is not required, the method has the advantage of adapting to varying flight conditions and different vehicle configurations. The key benefit of the envelope estimation and protection system is that it allows the aircraft to fly close to its limit boundary by constantly updating the controller command limits during flight. The developed techniques were demonstrated on NASA s Generic Transport Model (GTM) simulation environments with simulated actuator faults. Simulation results and remarks on future work are presented.

Use of global positioning system measurements to determine geocentric coordinates and variations in Earth orientation

NASA Technical Reports Server (NTRS)

Malla, R. P.; Wu, S.-C.; Lichten, S. M.

1993-01-01

Geocentric tracking station coordinates and short-period Earth-orientation variations can be measured with Global Positioning System (GPS) measurements. Unless calibrated, geocentric coordinate errors and changes in Earth orientation can lead to significant deep-space tracking errors. Ground-based GPS estimates of daily and subdaily changes in Earth orientation presently show centimeter-level precision. Comparison between GPS-estimated Earth-rotation variations, which are the differences between Universal Time 1 and Universal Coordinated Time (UT1-UTC), and those calculated from ocean tide models suggests that observed subdaily variations in Earth rotation are dominated by oceanic tidal effects. Preliminary GPS estimates for the geocenter location (from a 3-week experiment) agree with independent satellite laser-ranging estimates to better than 10 cm. Covariance analysis predicts that temporal resolution of GPS estimates for Earth orientation and geocenter improves significantly when data collected from low Earth-orbiting satellites as well as from ground sites are combined. The low Earth GPS tracking data enhance the accuracy and resolution for measuring high-frequency global geodynamical signals over time scales of less than 1 day.

Estimating economic gains for landowners due to time-dependent changes in biotechnology

Treesearch

John E. Wagner; Thomas P. Holmes

1998-01-01

This paper presents a model for examining the economic value of biotechnological research given time-dependent changes in biotechnology. Previous papers examined this issue assuming a time-neutral change in biotechnology. However, when analyzing the genetic improvements of increasing a tree's resistance to a pathogen, this assumption is untenable. The authors...

Modulation of Response Timing in ADHD, Effects of Reinforcement Valence and Magnitude

ERIC Educational Resources Information Center

Luman, Marjolein; Oosterlaan, Jaap; Sergeant, Joseph A.

2008-01-01

The present study investigated the impact of reinforcement valence and magnitude on response timing in children with ADHD. Children were required to estimate a 1-s interval, and both the median response time (response tendency) and the intrasubject-variability (response stability) were investigated. In addition, heart rate and skin conductance…

Temporal processing dysfunction in schizophrenia.

PubMed

Carroll, Christine A; Boggs, Jennifer; O'Donnell, Brian F; Shekhar, Anantha; Hetrick, William P

2008-07-01

Schizophrenia may be associated with a fundamental disturbance in the temporal coordination of information processing in the brain, leading to classic symptoms of schizophrenia such as thought disorder and disorganized and contextually inappropriate behavior. Despite the growing interest and centrality of time-dependent conceptualizations of the pathophysiology of schizophrenia, there remains a paucity of research directly examining overt timing performance in the disorder. Accordingly, the present study investigated timing in schizophrenia using a well-established task of time perception. Twenty-three individuals with schizophrenia and 22 non-psychiatric control participants completed a temporal bisection task, which required participants to make temporal judgments about auditory and visually presented durations ranging from 300 to 600 ms. Both schizophrenia and control groups displayed greater visual compared to auditory timing variability, with no difference between groups in the visual modality. However, individuals with schizophrenia exhibited less temporal precision than controls in the perception of auditory durations. These findings correlated with parameter estimates obtained from a quantitative model of time estimation, and provide evidence of a fundamental deficit in temporal auditory precision in schizophrenia.

Estimate of the soil water retention curve from the sorptivity and β parameter calculated from an upward infiltration experiment

NASA Astrophysics Data System (ADS)

Moret-Fernández, D.; Latorre, B.

2017-01-01

The water retention curve (θ(h)), which defines the relationship between the volumetric water content (θ) and the matric potential (h), is of paramount importance to characterize the hydraulic behaviour of soils. Because current methods to estimate θ(h) are, in general, tedious and time consuming, alternative procedures to determine θ(h) are needed. Using an upward infiltration curve, the main objective of this work is to present a method to determine the parameters of the van Genuchten (1980) water retention curve (α and n) from the sorptivity (S) and the β parameter defined in the 1D infiltration equation proposed by Haverkamp et al. (1994). The first specific objective is to present an equation, based on the Haverkamp et al. (1994) analysis, which allows describing an upward infiltration process. Secondary, assuming a known saturated hydraulic conductivity, Ks, calculated on a finite soil column by the Darcy's law, a numerical procedure to calculate S and β by the inverse analysis of an exfiltration curve is presented. Finally, the α and n values are numerically calculated from Ks, S and β. To accomplish the first specific objective, cumulative upward infiltration curves simulated with HYDRUS-1D for sand, loam, silt and clay soils were compared to those calculated with the proposed equation, after applying the corresponding β and S calculated from the theoretical Ks, α and n. The same curves were used to: (i) study the influence of the exfiltration time on S and β estimations, (ii) evaluate the limits of the inverse analysis, and (iii) validate the feasibility of the method to estimate α and n. Next, the θ(h) parameters estimated with the numerical method on experimental soils were compared to those obtained with pressure cells. The results showed that the upward infiltration curve could be correctly described by the modified Haverkamp et al. (1994) equation. While S was only affected by early-time exfiltration data, the β parameter had a significant influence on the long-time exfiltration curve, which accuracy increased with time. The 1D infiltration model was only suitable for β < 1.7 (sand, loam and silt). After omitting the clay soil, an excellent relationship (R2 = 0.99, p < 0.005) was observed between the theoretical α and n values of the synthetic soils and those estimated from the inverse analysis. Consistent results, with a significant relationship (p < 0.001) between the n values estimated with the pressure cell and the upward infiltration analysis, were also obtained on the experimental soils.

Present-day deformation in Europe, as seen by the EPOS-GNSS prototype solution in double difference, and first co- and post-seismic displacements associated with 2016 Amatrice and Norcia earthquakes (Italy)

NASA Astrophysics Data System (ADS)

Socquet, Anne; Déprez, Aline; Cotte, Nathalie; Maubant, Louise; Walpersdorf, Andrea; Bato, Mary Grace

2017-04-01

We present here a new pan-European velocity field, obtained by processing 500+ cGPS stations in double difference, in the framework of the implementation phase of the European Plate Observing System (EPOS) project. This prototype solution spans the 2000-2016 period, and includes data from RING, NOA, RENAG and European Permanent Network (EPN) cGPS netwprks. The data set is first split into daily sub-networks (between 8 and 14 sub-networks). The sub-networks consist in about 40 stations, with 2 overlapping stations. For each day and for each sub-network, the GAMIT processing is conducted independently. Once each sub-network achieves satisfactory results, a daily combination is performed in order to produce SINEX files. The Chi square value associated with the combination allows us to evaluate its quality. Eventually, a multi year combination generates position time series for each station. Each time series is visualized and the jumps associated with material change (antenna or receiver) are estimated and corrected. This procedure allows us to generate daily solutions and position time series for all stations. The associated "interseismic" velocity field has then been estimated using a times series analysis using MIDAS software, and compared to another independent estimate obtained by Kalman filtering with globk software. In addition to this velocity field we made a specific zoom on Italy and present a strain rate map as well as time series showing co- and post- seismic movements associated with the 2016 Amatrice and Norcia earthquakes.

Asteroid orbital error analysis: Theory and application

NASA Technical Reports Server (NTRS)

Muinonen, K.; Bowell, Edward

1992-01-01

We present a rigorous Bayesian theory for asteroid orbital error estimation in which the probability density of the orbital elements is derived from the noise statistics of the observations. For Gaussian noise in a linearized approximation the probability density is also Gaussian, and the errors of the orbital elements at a given epoch are fully described by the covariance matrix. The law of error propagation can then be applied to calculate past and future positional uncertainty ellipsoids (Cappellari et al. 1976, Yeomans et al. 1987, Whipple et al. 1991). To our knowledge, this is the first time a Bayesian approach has been formulated for orbital element estimation. In contrast to the classical Fisherian school of statistics, the Bayesian school allows a priori information to be formally present in the final estimation. However, Bayesian estimation does give the same results as Fisherian estimation when no priori information is assumed (Lehtinen 1988, and reference therein).

The extended Fourier transform for 2D spectral estimation.

PubMed

Armstrong, G S; Mandelshtam, V A

2001-11-01

We present a linear algebraic method, named the eXtended Fourier Transform (XFT), for spectral estimation from truncated time signals. The method is a hybrid of the discrete Fourier transform (DFT) and the regularized resolvent transform (RRT) (J. Chen et al., J. Magn. Reson. 147, 129-137 (2000)). Namely, it estimates the remainder of a finite DFT by RRT. The RRT estimation corresponds to solution of an ill-conditioned problem, which requires regularization. The regularization depends on a parameter, q, that essentially controls the resolution. By varying q from 0 to infinity one can "tune" the spectrum between a high-resolution spectral estimate and the finite DFT. The optimal value of q is chosen according to how well the data fits the form of a sum of complex sinusoids and, in particular, the signal-to-noise ratio. Both 1D and 2D XFT are presented with applications to experimental NMR signals. Copyright 2001 Academic Press.

Online Estimation of Model Parameters of Lithium-Ion Battery Using the Cubature Kalman Filter

NASA Astrophysics Data System (ADS)

Tian, Yong; Yan, Rusheng; Tian, Jindong; Zhou, Shijie; Hu, Chao

2017-11-01

Online estimation of state variables, including state-of-charge (SOC), state-of-energy (SOE) and state-of-health (SOH) is greatly crucial for the operation safety of lithium-ion battery. In order to improve estimation accuracy of these state variables, a precise battery model needs to be established. As the lithium-ion battery is a nonlinear time-varying system, the model parameters significantly vary with many factors, such as ambient temperature, discharge rate and depth of discharge, etc. This paper presents an online estimation method of model parameters for lithium-ion battery based on the cubature Kalman filter. The commonly used first-order resistor-capacitor equivalent circuit model is selected as the battery model, based on which the model parameters are estimated online. Experimental results show that the presented method can accurately track the parameters variation at different scenarios.

The effect of concurrent hand movement on estimated time to contact in a prediction motion task.

PubMed

Zheng, Ran; Maraj, Brian K V

2018-04-27

In many activities, we need to predict the arrival of an occluded object. This action is called prediction motion or motion extrapolation. Previous researchers have found that both eye tracking and the internal clocking model are involved in the prediction motion task. Additionally, it is reported that concurrent hand movement facilitates the eye tracking of an externally generated target in a tracking task, even if the target is occluded. The present study examined the effect of concurrent hand movement on the estimated time to contact in a prediction motion task. We found different (accurate/inaccurate) concurrent hand movements had the opposite effect on the eye tracking accuracy and estimated TTC in the prediction motion task. That is, the accurate concurrent hand tracking enhanced eye tracking accuracy and had the trend to increase the precision of estimated TTC, but the inaccurate concurrent hand tracking decreased eye tracking accuracy and disrupted estimated TTC. However, eye tracking accuracy does not determine the precision of estimated TTC.

Computing moment to moment BOLD activation for real-time neurofeedback

PubMed Central

Hinds, Oliver; Ghosh, Satrajit; Thompson, Todd W.; Yoo, Julie J.; Whitfield-Gabrieli, Susan; Triantafyllou, Christina; Gabrieli, John D.E.

2013-01-01

Estimating moment to moment changes in blood oxygenation level dependent (BOLD) activation levels from functional magnetic resonance imaging (fMRI) data has applications for learned regulation of regional activation, brain state monitoring, and brain-machine interfaces. In each of these contexts, accurate estimation of the BOLD signal in as little time as possible is desired. This is a challenging problem due to the low signal-to-noise ratio of fMRI data. Previous methods for real-time fMRI analysis have either sacrificed the ability to compute moment to moment activation changes by averaging several acquisitions into a single activation estimate or have sacrificed accuracy by failing to account for prominent sources of noise in the fMRI signal. Here we present a new method for computing the amount of activation present in a single fMRI acquisition that separates moment to moment changes in the fMRI signal intensity attributable to neural sources from those due to noise, resulting in a feedback signal more reflective of neural activation. This method computes an incremental general linear model fit to the fMRI timeseries, which is used to calculate the expected signal intensity at each new acquisition. The difference between the measured intensity and the expected intensity is scaled by the variance of the estimator in order to transform this residual difference into a statistic. Both synthetic and real data were used to validate this method and compare it to the only other published real-time fMRI method. PMID:20682350

Vascular and nerve damage in workers exposed to vibrating tools. The importance of objective measurements of exposure time.

PubMed

Gerhardsson, Lars; Balogh, Istvan; Hambert, Per-Arne; Hjortsberg, Ulf; Karlsson, Jan-Erik

2005-01-01

The aim of the present study was to compare the development of vibration white fingers (VWF) in workers in relation to different ways of exposure estimation, and their relationship to the standard ISO 5349, annex A. Nineteen vibration exposed (grinding machines) male workers completed a questionnaire followed by a structured interview including questions regarding their estimated hand-held vibration exposure. Neurophysiological tests such as fractionated nerve conduction velocity in hands and arms, vibrotactile perception thresholds and temperature thresholds were determined. The subjective estimation of the mean daily exposure-time to vibrating tools was 192 min (range 18-480 min) among the workers. The estimated mean exposure time calculated from the consumption of grinding wheels was 42 min (range 18-60 min), approximately a four-fold overestimation (Wilcoxon's signed ranks test, p<0.001). Thus, objective measurements of the exposure time, related to the standard ISO 5349, which in this case were based on the consumption of grinding wheels, will in most cases give a better basis for adequate risk assessment than self-exposure assessment.

Real-time detection of moving objects from moving vehicles using dense stereo and optical flow

NASA Technical Reports Server (NTRS)

Talukder, Ashit; Matthies, Larry

2004-01-01

Dynamic scene perception is very important for autonomous vehicles operating around other moving vehicles and humans. Most work on real-time object tracking from moving platforms has used sparse features or assumed flat scene structures. We have recently extended a real-time, dense stereo system to include real-time, dense optical flow, enabling more comprehensive dynamic scene analysis. We describe algorithms to robustly estimate 6-DOF robot egomotion in the presence of moving objects using dense flow and dense stereo. We then use dense stereo and egomotion estimates to identity other moving objects while the robot itself is moving. We present results showing accurate egomotion estimation and detection of moving people and vehicles under general 6-DOF motion of the robot and independently moving objects. The system runs at 18.3 Hz on a 1.4 GHz Pentium M laptop, computing 160x120 disparity maps and optical flow fields, egomotion, and moving object segmentation. We believe this is a significant step toward general unconstrained dynamic scene analysis for mobile robots, as well as for improved position estimation where GPS is unavailable.

Investigation of the 16-year and 18-year ZTD Time Series Derived from GPS Data Processing

NASA Astrophysics Data System (ADS)

Bałdysz, Zofia; Nykiel, Grzegorz; Figurski, Mariusz; Szafranek, Karolina; KroszczyńSki, Krzysztof

2015-08-01

The GPS system can play an important role in activities related to the monitoring of climate. Long time series, coherent strategy, and very high quality of tropospheric parameter Zenith Tropospheric Delay (ZTD) estimated on the basis of GPS data analysis allows to investigate its usefulness for climate research as a direct GPS product. This paper presents results of analysis of 16-year time series derived from EUREF Permanent Network (EPN) reprocessing performed by the Military University of Technology. For 58 stations Lomb-Scargle periodograms were performed in order to obtain information about the oscillations in ZTD time series. Seasonal components and linear trend were estimated using Least Square Estimation (LSE) and Mann—Kendall trend test was used to confirm the presence of a linear trend designated by LSE method. In order to verify the impact of the length of time series on trend value, comparison between 16 and 18 years were performed.

Transient deformation from daily GPS displacement time series: postseismic deformation, ETS and evolving strain rates

NASA Astrophysics Data System (ADS)

Bock, Y.; Fang, P.; Moore, A. W.; Kedar, S.; Liu, Z.; Owen, S. E.; Glasscoe, M. T.

2016-12-01

Detection of time-dependent crustal deformation relies on the availability of accurate surface displacements, proper time series analysis to correct for secular motion, coseismic and non-tectonic instrument offsets, periodic signatures at different frequencies, and a realistic estimate of uncertainties for the parameters of interest. As part of the NASA Solid Earth Science ESDR System (SESES) project, daily displacement time series are estimated for about 2500 stations, focused on tectonic plate boundaries and having a global distribution for accessing the terrestrial reference frame. The "combined" time series are optimally estimated from independent JPL GIPSY and SIO GAMIT solutions, using a consistent set of input epoch-date coordinates and metadata. The longest time series began in 1992; more than 30% of the stations have experienced one or more of 35 major earthquakes with significant postseismic deformation. Here we present three examples of time-dependent deformation that have been detected in the SESES displacement time series. (1) Postseismic deformation is a fundamental time-dependent signal that indicates a viscoelastic response of the crust/mantle lithosphere, afterslip, or poroelastic effects at different spatial and temporal scales. It is critical to identify and estimate the extent of postseismic deformation in both space and time not only for insight into the crustal deformation and earthquake cycles and their underlying physical processes, but also to reveal other time-dependent signals. We report on our database of characterized postseismic motions using a principal component analysis to isolate different postseismic processes. (2) Starting with the SESES combined time series and applying a time-dependent Kalman filter, we examine episodic tremor and slow slip (ETS) in the Cascadia subduction zone. We report on subtle slip details, allowing investigation of the spatiotemporal relationship between slow slip transients and tremor and their underlying physical mechanisms. (3) We present evolving strain dilatation and shear rates based on the SESES velocities for regional subnetworks as a metric for assigning earthquake probabilities and detection of possible time-dependent deformation related to underlying physical processes.

The Clock’N Test as a Possible Measure of Emotions: Normative Data Collected on a Non-clinical Population

PubMed Central

Gros, Auriane; Manera, Valeria; Daumas, Anaïs; Guillemin, Sophie; Rouaud, Olivier; Martin, Martine Lemesle; Giroud, Maurice; Béjot, Yannick

2016-01-01

Objective: At present emotional experience and implicit emotion regulation (IER) abilities are mainly assessed though self-reports, which are subjected to several biases. The aim of the present studies was to validate the Clock’N test, a recently developed time estimation task employing emotional priming to assess implicitly emotional reactivity and IER. Methods: In Study 1, the Clock’N test was administered to 150 healthy participants with different age, laterality and gender, in order to ascertain whether these factors affected the test results. In phase 1 participant were asked to judge the duration of seven sounds. In phase 2, before judging the duration of the same sounds, participants were presented with short arousing video-clip used as emotional priming stimuli. Time warp was calculated as the difference in time estimation between phase 2 and phase 1, and used to assess how emotions affected subjective time estimations. In study 2, a representative sample was selected to provide normative scores to be employed to assess emotional reactivity (Score 1) and IER (Score 2), and to calculate statistical cutoffs, based on the 10th and 90th score distribution percentiles. Results: Converging with previous findings, the results of study 1 suggested that the Clock’N test can be employed to assess both emotional reactivity, as indexed by an initial time underestimation, and IER, as indexed by a progressive shift to time overestimation. No effects of gender, age and laterality were found. Conclusions: These results suggest that the Clock’N test is adapted to assess emotional reactivity and IER. After collection of data on the test discriminant and convergent validity, this test may be employed to assess deficits in these abilities in different clinical populations. PMID:26903825

Technical notes and correspondence: Stochastic robustness of linear time-invariant control systems

NASA Technical Reports Server (NTRS)

Stengel, Robert F.; Ray, Laura R.

1991-01-01

A simple numerical procedure for estimating the stochastic robustness of a linear time-invariant system is described. Monte Carlo evaluations of the system's eigenvalues allows the probability of instability and the related stochastic root locus to be estimated. This analysis approach treats not only Gaussian parameter uncertainties but non-Gaussian cases, including uncertain-but-bounded variation. Confidence intervals for the scalar probability of instability address computational issues inherent in Monte Carlo simulation. Trivial extensions of the procedure admit consideration of alternate discriminants; thus, the probabilities that stipulated degrees of instability will be exceeded or that closed-loop roots will leave desirable regions can also be estimated. Results are particularly amenable to graphical presentation.

Performance comparison of attitude determination, attitude estimation, and nonlinear observers algorithms

NASA Astrophysics Data System (ADS)

MOHAMMED, M. A. SI; BOUSSADIA, H.; BELLAR, A.; ADNANE, A.

2017-01-01

This paper presents a brief synthesis and useful performance analysis of different attitude filtering algorithms (attitude determination algorithms, attitude estimation algorithms, and nonlinear observers) applied to Low Earth Orbit Satellite in terms of accuracy, convergence time, amount of memory, and computation time. This latter is calculated in two ways, using a personal computer and also using On-board computer 750 (OBC 750) that is being used in many SSTL Earth observation missions. The use of this comparative study could be an aided design tool to the designer to choose from an attitude determination or attitude estimation or attitude observer algorithms. The simulation results clearly indicate that the nonlinear Observer is the more logical choice.

Analytical estimation show low depth-independent water loss due to vapor flux from deep aquifers

NASA Astrophysics Data System (ADS)

Selker, John S.

2017-06-01

Recent articles have provided estimates of evaporative flux from water tables in deserts that span 5 orders of magnitude. In this paper, we present an analytical calculation that indicates aquifer vapor flux to be limited to 0.01 mm/yr for sites where there is negligible recharge and the water table is well over 20 m below the surface. This value arises from the geothermal gradient, and therefore, is nearly independent of the actual depth of the aquifer. The value is in agreement with several numerical studies, but is 500 times lower than recently reported experimental values, and 100 times larger than an earlier analytical estimate.

Ultra Wide-Band Localization and SLAM: A Comparative Study for Mobile Robot Navigation

PubMed Central

Segura, Marcelo J.; Auat Cheein, Fernando A.; Toibero, Juan M.; Mut, Vicente; Carelli, Ricardo

2011-01-01

In this work, a comparative study between an Ultra Wide-Band (UWB) localization system and a Simultaneous Localization and Mapping (SLAM) algorithm is presented. Due to its high bandwidth and short pulses length, UWB potentially allows great accuracy in range measurements based on Time of Arrival (TOA) estimation. SLAM algorithms recursively estimates the map of an environment and the pose (position and orientation) of a mobile robot within that environment. The comparative study presented here involves the performance analysis of implementing in parallel an UWB localization based system and a SLAM algorithm on a mobile robot navigating within an environment. Real time results as well as error analysis are also shown in this work. PMID:22319397

IEEE 802.15.4 ZigBee-Based Time-of-Arrival Estimation for Wireless Sensor Networks.

PubMed

Cheon, Jeonghyeon; Hwang, Hyunsu; Kim, Dongsun; Jung, Yunho

2016-02-05

Precise time-of-arrival (TOA) estimation is one of the most important techniques in RF-based positioning systems that use wireless sensor networks (WSNs). Because the accuracy of TOA estimation is proportional to the RF signal bandwidth, using broad bandwidth is the most fundamental approach for achieving higher accuracy. Hence, ultra-wide-band (UWB) systems with a bandwidth of 500 MHz are commonly used. However, wireless systems with broad bandwidth suffer from the disadvantages of high complexity and high power consumption. Therefore, it is difficult to employ such systems in various WSN applications. In this paper, we present a precise time-of-arrival (TOA) estimation algorithm using an IEEE 802.15.4 ZigBee system with a narrow bandwidth of 2 MHz. In order to overcome the lack of bandwidth, the proposed algorithm estimates the fractional TOA within the sampling interval. Simulation results show that the proposed TOA estimation algorithm provides an accuracy of 0.5 m at a signal-to-noise ratio (SNR) of 8 dB and achieves an SNR gain of 5 dB as compared with the existing algorithm. In addition, experimental results indicate that the proposed algorithm provides accurate TOA estimation in a real indoor environment.

A Modularized Efficient Framework for Non-Markov Time Series Estimation

NASA Astrophysics Data System (ADS)

Schamberg, Gabriel; Ba, Demba; Coleman, Todd P.

2018-06-01

We present a compartmentalized approach to finding the maximum a-posteriori (MAP) estimate of a latent time series that obeys a dynamic stochastic model and is observed through noisy measurements. We specifically consider modern signal processing problems with non-Markov signal dynamics (e.g. group sparsity) and/or non-Gaussian measurement models (e.g. point process observation models used in neuroscience). Through the use of auxiliary variables in the MAP estimation problem, we show that a consensus formulation of the alternating direction method of multipliers (ADMM) enables iteratively computing separate estimates based on the likelihood and prior and subsequently "averaging" them in an appropriate sense using a Kalman smoother. As such, this can be applied to a broad class of problem settings and only requires modular adjustments when interchanging various aspects of the statistical model. Under broad log-concavity assumptions, we show that the separate estimation problems are convex optimization problems and that the iterative algorithm converges to the MAP estimate. As such, this framework can capture non-Markov latent time series models and non-Gaussian measurement models. We provide example applications involving (i) group-sparsity priors, within the context of electrophysiologic specrotemporal estimation, and (ii) non-Gaussian measurement models, within the context of dynamic analyses of learning with neural spiking and behavioral observations.

Evaluation of Bayesian estimation of a hidden continuous-time Markov chain model with application to threshold violation in water-quality indicators

USGS Publications Warehouse

Deviney, Frank A.; Rice, Karen; Brown, Donald E.

2012-01-01

Natural resource managers require information concerning  the frequency, duration, and long-term probability of occurrence of water-quality indicator (WQI) violations of defined thresholds. The timing of these threshold crossings often is hidden from the observer, who is restricted to relatively infrequent observations. Here, a model for the hidden process is linked with a model for the observations, and the parameters describing duration, return period, and long-term probability of occurrence are estimated using Bayesian methods. A simulation experiment is performed to evaluate the approach under scenarios based on the equivalent of a total monitoring period of 5-30 years and an observation frequency of 1-50 observations per year. Given constant threshold crossing rate, accuracy and precision of parameter estimates increased with longer total monitoring period and more-frequent observations. Given fixed monitoring period and observation frequency, accuracy and precision of parameter estimates increased with longer times between threshold crossings. For most cases where the long-term probability of being in violation is greater than 0.10, it was determined that at least 600 observations are needed to achieve precise estimates.  An application of the approach is presented using 22 years of quasi-weekly observations of acid-neutralizing capacity from Deep Run, a stream in Shenandoah National Park, Virginia. The time series also was sub-sampled to simulate monthly and semi-monthly sampling protocols. Estimates of the long-term probability of violation were unbiased despite sampling frequency; however, the expected duration and return period were over-estimated using the sub-sampled time series with respect to the full quasi-weekly time series.

Total ozone trend significance from space time variability of daily Dobson data

NASA Technical Reports Server (NTRS)

Wilcox, R. W.

1981-01-01

Estimates of standard errors of total ozone time and area means, as derived from ozone's natural temporal and spatial variability and autocorrelation in middle latitudes determined from daily Dobson data are presented. Assessing the significance of apparent total ozone trends is equivalent to assessing the standard error of the means. Standard errors of time averages depend on the temporal variability and correlation of the averaged parameter. Trend detectability is discussed, both for the present network and for satellite measurements.

A computer program for estimating the power-density spectrum of advanced continuous simulation language generated time histories

NASA Technical Reports Server (NTRS)

Dunn, H. J.

1981-01-01

A computer program for performing frequency analysis of time history data is presented. The program uses circular convolution and the fast Fourier transform to calculate power density spectrum (PDS) of time history data. The program interfaces with the advanced continuous simulation language (ACSL) so that a frequency analysis may be performed on ACSL generated simulation variables. An example of the calculation of the PDS of a Van de Pol oscillator is presented.

Statistical properties of Fourier-based time-lag estimates

NASA Astrophysics Data System (ADS)

Epitropakis, A.; Papadakis, I. E.

2016-06-01

Context. The study of X-ray time-lag spectra in active galactic nuclei (AGN) is currently an active research area, since it has the potential to illuminate the physics and geometry of the innermost region (I.e. close to the putative super-massive black hole) in these objects. To obtain reliable information from these studies, the statistical properties of time-lags estimated from data must be known as accurately as possible. Aims: We investigated the statistical properties of Fourier-based time-lag estimates (I.e. based on the cross-periodogram), using evenly sampled time series with no missing points. Our aim is to provide practical "guidelines" on estimating time-lags that are minimally biased (I.e. whose mean is close to their intrinsic value) and have known errors. Methods: Our investigation is based on both analytical work and extensive numerical simulations. The latter consisted of generating artificial time series with various signal-to-noise ratios and sampling patterns/durations similar to those offered by AGN observations with present and past X-ray satellites. We also considered a range of different model time-lag spectra commonly assumed in X-ray analyses of compact accreting systems. Results: Discrete sampling, binning and finite light curve duration cause the mean of the time-lag estimates to have a smaller magnitude than their intrinsic values. Smoothing (I.e. binning over consecutive frequencies) of the cross-periodogram can add extra bias at low frequencies. The use of light curves with low signal-to-noise ratio reduces the intrinsic coherence, and can introduce a bias to the sample coherence, time-lag estimates, and their predicted error. Conclusions: Our results have direct implications for X-ray time-lag studies in AGN, but can also be applied to similar studies in other research fields. We find that: a) time-lags should be estimated at frequencies lower than ≈ 1/2 the Nyquist frequency to minimise the effects of discrete binning of the observed time series; b) smoothing of the cross-periodogram should be avoided, as this may introduce significant bias to the time-lag estimates, which can be taken into account by assuming a model cross-spectrum (and not just a model time-lag spectrum); c) time-lags should be estimated by dividing observed time series into a number, say m, of shorter data segments and averaging the resulting cross-periodograms; d) if the data segments have a duration ≳ 20 ks, the time-lag bias is ≲15% of its intrinsic value for the model cross-spectra and power-spectra considered in this work. This bias should be estimated in practise (by considering possible intrinsic cross-spectra that may be applicable to the time-lag spectra at hand) to assess the reliability of any time-lag analysis; e) the effects of experimental noise can be minimised by only estimating time-lags in the frequency range where the sample coherence is larger than 1.2/(1 + 0.2m). In this range, the amplitude of noise variations caused by measurement errors is smaller than the amplitude of the signal's intrinsic variations. As long as m ≳ 20, time-lags estimated by averaging over individual data segments have analytical error estimates that are within 95% of the true scatter around their mean, and their distribution is similar, albeit not identical, to a Gaussian.

The influence of taxon sampling on Bayesian divergence time inference under scenarios of rate heterogeneity among lineages.

PubMed

Soares, André E R; Schrago, Carlos G

2015-01-07

Although taxon sampling is commonly considered an important issue in phylogenetic inference, it is rarely considered in the Bayesian estimation of divergence times. In fact, the studies conducted to date have presented ambiguous results, and the relevance of taxon sampling for molecular dating remains unclear. In this study, we developed a series of simulations that, after six hundred Bayesian molecular dating analyses, allowed us to evaluate the impact of taxon sampling on chronological estimates under three scenarios of among-lineage rate heterogeneity. The first scenario allowed us to examine the influence of the number of terminals on the age estimates based on a strict molecular clock. The second scenario imposed an extreme example of lineage specific rate variation, and the third scenario permitted extensive rate variation distributed along the branches. We also analyzed empirical data on selected mitochondrial genomes of mammals. Our results showed that in the strict molecular-clock scenario (Case I), taxon sampling had a minor impact on the accuracy of the time estimates, although the precision of the estimates was greater with an increased number of terminals. The effect was similar in the scenario (Case III) based on rate variation distributed among the branches. Only under intensive rate variation among lineages (Case II) taxon sampling did result in biased estimates. The results of an empirical analysis corroborated the simulation findings. We demonstrate that taxonomic sampling affected divergence time inference but that its impact was significant if the rates deviated from those derived for the strict molecular clock. Increased taxon sampling improved the precision and accuracy of the divergence time estimates, but the impact on precision is more relevant. On average, biased estimates were obtained only if lineage rate variation was pronounced. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Particle Smoother with Sequential Importance Resampling for soil hydraulic parameter estimation: A lysimeter experiment

NASA Astrophysics Data System (ADS)

Montzka, Carsten; Hendricks Franssen, Harrie-Jan; Moradkhani, Hamid; Pütz, Thomas; Han, Xujun; Vereecken, Harry

2013-04-01

An adequate description of soil hydraulic properties is essential for a good performance of hydrological forecasts. So far, several studies showed that data assimilation could reduce the parameter uncertainty by considering soil moisture observations. However, these observations and also the model forcings were recorded with a specific measurement error. It seems a logical step to base state updating and parameter estimation on observations made at multiple time steps, in order to reduce the influence of outliers at single time steps given measurement errors and unknown model forcings. Such outliers could result in erroneous state estimation as well as inadequate parameters. This has been one of the reasons to use a smoothing technique as implemented for Bayesian data assimilation methods such as the Ensemble Kalman Filter (i.e. Ensemble Kalman Smoother). Recently, an ensemble-based smoother has been developed for state update with a SIR particle filter. However, this method has not been used for dual state-parameter estimation. In this contribution we present a Particle Smoother with sequentially smoothing of particle weights for state and parameter resampling within a time window as opposed to the single time step data assimilation used in filtering techniques. This can be seen as an intermediate variant between a parameter estimation technique using global optimization with estimation of single parameter sets valid for the whole period, and sequential Monte Carlo techniques with estimation of parameter sets evolving from one time step to another. The aims are i) to improve the forecast of evaporation and groundwater recharge by estimating hydraulic parameters, and ii) to reduce the impact of single erroneous model inputs/observations by a smoothing method. In order to validate the performance of the proposed method in a real world application, the experiment is conducted in a lysimeter environment.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blaut, Arkadiusz

We present the results of the estimation of parameters with LISA for nearly monochromatic gravitational waves in the low and high frequency regimes for the time-delay interferometry response. Angular resolution of the detector and the estimation errors of the signal's parameters in the high frequency regimes are calculated as functions of the position in the sky and as functions of the frequency. For the long-wavelength domain we give compact formulas for the estimation errors valid on a wide range of the parameter space.

Building occupancy simulation and data assimilation using a graph-based agent-oriented model

NASA Astrophysics Data System (ADS)

Rai, Sanish; Hu, Xiaolin

2018-07-01

Building occupancy simulation and estimation simulates the dynamics of occupants and estimates their real-time spatial distribution in a building. It requires a simulation model and an algorithm for data assimilation that assimilates real-time sensor data into the simulation model. Existing building occupancy simulation models include agent-based models and graph-based models. The agent-based models suffer high computation cost for simulating large numbers of occupants, and graph-based models overlook the heterogeneity and detailed behaviors of individuals. Recognizing the limitations of existing models, this paper presents a new graph-based agent-oriented model which can efficiently simulate large numbers of occupants in various kinds of building structures. To support real-time occupancy dynamics estimation, a data assimilation framework based on Sequential Monte Carlo Methods is also developed and applied to the graph-based agent-oriented model to assimilate real-time sensor data. Experimental results show the effectiveness of the developed model and the data assimilation framework. The major contributions of this work are to provide an efficient model for building occupancy simulation that can accommodate large numbers of occupants and an effective data assimilation framework that can provide real-time estimations of building occupancy from sensor data.

A Timing Estimation Method Based-on Skewness Analysis in Vehicular Wireless Networks.

PubMed

Cui, Xuerong; Li, Juan; Wu, Chunlei; Liu, Jian-Hang

2015-11-13

Vehicle positioning technology has drawn more and more attention in vehicular wireless networks to reduce transportation time and traffic accidents. Nowadays, global navigation satellite systems (GNSS) are widely used in land vehicle positioning, but most of them are lack precision and reliability in situations where their signals are blocked. Positioning systems base-on short range wireless communication are another effective way that can be used in vehicle positioning or vehicle ranging. IEEE 802.11p is a new real-time short range wireless communication standard for vehicles, so a new method is proposed to estimate the time delay or ranges between vehicles based on the IEEE 802.11p standard which includes three main steps: cross-correlation between the received signal and the short preamble, summing up the correlated results in groups, and finding the maximum peak using a dynamic threshold based on the skewness analysis. With the range between each vehicle or road-side infrastructure, the position of neighboring vehicles can be estimated correctly. Simulation results were presented in the International Telecommunications Union (ITU) vehicular multipath channel, which show that the proposed method provides better precision than some well-known timing estimation techniques, especially in low signal to noise ratio (SNR) environments.

Monaural Sound Localization Based on Reflective Structure and Homomorphic Deconvolution

PubMed Central

Park, Yeonseok; Choi, Anthony

2017-01-01

The asymmetric structure around the receiver provides a particular time delay for the specific incoming propagation. This paper designs a monaural sound localization system based on the reflective structure around the microphone. The reflective plates are placed to present the direction-wise time delay, which is naturally processed by convolutional operation with a sound source. The received signal is separated for estimating the dominant time delay by using homomorphic deconvolution, which utilizes the real cepstrum and inverse cepstrum sequentially to derive the propagation response’s autocorrelation. Once the localization system accurately estimates the information, the time delay model computes the corresponding reflection for localization. Because of the structure limitation, two stages of the localization process perform the estimation procedure as range and angle. The software toolchain from propagation physics and algorithm simulation realizes the optimal 3D-printed structure. The acoustic experiments in the anechoic chamber denote that 79.0% of the study range data from the isotropic signal is properly detected by the response value, and 87.5% of the specific direction data from the study range signal is properly estimated by the response time. The product of both rates shows the overall hit rate to be 69.1%. PMID:28946625

Simplified methods for real-time prediction of storm surge uncertainty: The city of Venice case study

NASA Astrophysics Data System (ADS)

Mel, Riccardo; Viero, Daniele Pietro; Carniello, Luca; Defina, Andrea; D'Alpaos, Luigi

2014-09-01

Providing reliable and accurate storm surge forecasts is important for a wide range of problems related to coastal environments. In order to adequately support decision-making processes, it also become increasingly important to be able to estimate the uncertainty associated with the storm surge forecast. The procedure commonly adopted to do this uses the results of a hydrodynamic model forced by a set of different meteorological forecasts; however, this approach requires a considerable, if not prohibitive, computational cost for real-time application. In the present paper we present two simplified methods for estimating the uncertainty affecting storm surge prediction with moderate computational effort. In the first approach we use a computationally fast, statistical tidal model instead of a hydrodynamic numerical model to estimate storm surge uncertainty. The second approach is based on the observation that the uncertainty in the sea level forecast mainly stems from the uncertainty affecting the meteorological fields; this has led to the idea to estimate forecast uncertainty via a linear combination of suitable meteorological variances, directly extracted from the meteorological fields. The proposed methods were applied to estimate the uncertainty in the storm surge forecast in the Venice Lagoon. The results clearly show that the uncertainty estimated through a linear combination of suitable meteorological variances nicely matches the one obtained using the deterministic approach and overcomes some intrinsic limitations in the use of a statistical tidal model.

A Real-Time Systems Symposium Preprint.

DTIC Science & Technology

1983-09-01

Real - Time Systems Symposium Preprint Interim Tech...estimate of the occurence of the error. Unclassii ledSECUqITY CLASSIF’ICA T" NO MI*IA If’ inDI /’rrd erter for~~ble. ’Corrputnqg A REAL - TIME SYSTEMS SYMPOSIUM...ABSTRACT This technical report contains a preprint of a paper accepted for presentation at the REAL - TIME SYSTEMS SYMPOSIUM, Arlington,

Adaptive Green-Kubo estimates of transport coefficients from molecular dynamics based on robust error analysis.

PubMed

Jones, Reese E; Mandadapu, Kranthi K

2012-04-21

We present a rigorous Green-Kubo methodology for calculating transport coefficients based on on-the-fly estimates of: (a) statistical stationarity of the relevant process, and (b) error in the resulting coefficient. The methodology uses time samples efficiently across an ensemble of parallel replicas to yield accurate estimates, which is particularly useful for estimating the thermal conductivity of semi-conductors near their Debye temperatures where the characteristic decay times of the heat flux correlation functions are large. Employing and extending the error analysis of Zwanzig and Ailawadi [Phys. Rev. 182, 280 (1969)] and Frenkel [in Proceedings of the International School of Physics "Enrico Fermi", Course LXXV (North-Holland Publishing Company, Amsterdam, 1980)] to the integral of correlation, we are able to provide tight theoretical bounds for the error in the estimate of the transport coefficient. To demonstrate the performance of the method, four test cases of increasing computational cost and complexity are presented: the viscosity of Ar and water, and the thermal conductivity of Si and GaN. In addition to producing accurate estimates of the transport coefficients for these materials, this work demonstrates precise agreement of the computed variances in the estimates of the correlation and the transport coefficient with the extended theory based on the assumption that fluctuations follow a Gaussian process. The proposed algorithm in conjunction with the extended theory enables the calculation of transport coefficients with the Green-Kubo method accurately and efficiently.

Adaptive Green-Kubo estimates of transport coefficients from molecular dynamics based on robust error analysis

NASA Astrophysics Data System (ADS)

Jones, Reese E.; Mandadapu, Kranthi K.

2012-04-01

We present a rigorous Green-Kubo methodology for calculating transport coefficients based on on-the-fly estimates of: (a) statistical stationarity of the relevant process, and (b) error in the resulting coefficient. The methodology uses time samples efficiently across an ensemble of parallel replicas to yield accurate estimates, which is particularly useful for estimating the thermal conductivity of semi-conductors near their Debye temperatures where the characteristic decay times of the heat flux correlation functions are large. Employing and extending the error analysis of Zwanzig and Ailawadi [Phys. Rev. 182, 280 (1969)], 10.1103/PhysRev.182.280 and Frenkel [in Proceedings of the International School of Physics "Enrico Fermi", Course LXXV (North-Holland Publishing Company, Amsterdam, 1980)] to the integral of correlation, we are able to provide tight theoretical bounds for the error in the estimate of the transport coefficient. To demonstrate the performance of the method, four test cases of increasing computational cost and complexity are presented: the viscosity of Ar and water, and the thermal conductivity of Si and GaN. In addition to producing accurate estimates of the transport coefficients for these materials, this work demonstrates precise agreement of the computed variances in the estimates of the correlation and the transport coefficient with the extended theory based on the assumption that fluctuations follow a Gaussian process. The proposed algorithm in conjunction with the extended theory enables the calculation of transport coefficients with the Green-Kubo method accurately and efficiently.

Time and temperature dependent modulus of pyrrone and polyimide moldings

NASA Technical Reports Server (NTRS)

Lander, L. L.

1972-01-01

A method is presented by which the modulus obtained from a stress relaxation test can be used to estimate the modulus which would be obtained from a sonic vibration test. The method was applied to stress relaxation, sonic vibration, and high speed stress-strain data which was obtained on a flexible epoxy. The modulus as measured by the three test methods was identical for identical test times, and a change of test temperature was equivalent to a shift in the logarithmic time scale. An estimate was then made of the dynamic modulus of moldings of two Pyrrones and two polyimides, using stress relaxation data and the method of analysis which was developed for the epoxy. Over the common temperature range (350 to 500 K) in which data from both types of tests were available, the estimated dynamic modulus value differed by only a few percent from the measured value. As a result, it is concluded that, over the 500 to 700 K temperature range, the estimated dynamic modulus values are accurate.

Building a kinetic Monte Carlo model with a chosen accuracy.

PubMed

Bhute, Vijesh J; Chatterjee, Abhijit

2013-06-28

The kinetic Monte Carlo (KMC) method is a popular modeling approach for reaching large materials length and time scales. The KMC dynamics is erroneous when atomic processes that are relevant to the dynamics are missing from the KMC model. Recently, we had developed for the first time an error measure for KMC in Bhute and Chatterjee [J. Chem. Phys. 138, 084103 (2013)]. The error measure, which is given in terms of the probability that a missing process will be selected in the correct dynamics, requires estimation of the missing rate. In this work, we present an improved procedure for estimating the missing rate. The estimate found using the new procedure is within an order of magnitude of the correct missing rate, unlike our previous approach where the estimate was larger by orders of magnitude. This enables one to find the error in the KMC model more accurately. In addition, we find the time for which the KMC model can be used before a maximum error in the dynamics has been reached.

A computational approach to estimate postmortem interval using opacity development of eye for human subjects.

PubMed

Cantürk, İsmail; Özyılmaz, Lale

2018-07-01

This paper presents an approach to postmortem interval (PMI) estimation, which is a very debated and complicated area of forensic science. Most of the reported methods to determine PMI in the literature are not practical because of the need for skilled persons and significant amounts of time, and give unsatisfactory results. Additionally, the error margin of PMI estimation increases proportionally with elapsed time after death. It is crucial to develop practical PMI estimation methods for forensic science. In this study, a computational system is developed to determine the PMI of human subjects by investigating postmortem opacity development of the eye. Relevant features from the eye images were extracted using image processing techniques to reflect gradual opacity development. The features were then investigated to predict the time after death using machine learning methods. The experimental results prove that the development of opacity can be utilized as a practical computational tool to determine PMI for human subjects. Copyright © 2018 Elsevier Ltd. All rights reserved.

A new parametric method to smooth time-series data of metabolites in metabolic networks.

PubMed

Miyawaki, Atsuko; Sriyudthsak, Kansuporn; Hirai, Masami Yokota; Shiraishi, Fumihide

2016-12-01

Mathematical modeling of large-scale metabolic networks usually requires smoothing of metabolite time-series data to account for measurement or biological errors. Accordingly, the accuracy of smoothing curves strongly affects the subsequent estimation of model parameters. Here, an efficient parametric method is proposed for smoothing metabolite time-series data, and its performance is evaluated. To simplify parameter estimation, the method uses S-system-type equations with simple power law-type efflux terms. Iterative calculation using this method was found to readily converge, because parameters are estimated stepwise. Importantly, smoothing curves are determined so that metabolite concentrations satisfy mass balances. Furthermore, the slopes of smoothing curves are useful in estimating parameters, because they are probably close to their true behaviors regardless of errors that may be present in the actual data. Finally, calculations for each differential equation were found to converge in much less than one second if initial parameters are set at appropriate (guessed) values. Copyright © 2016 Elsevier Inc. All rights reserved.

Classes of Split-Plot Response Surface Designs for Equivalent Estimation

NASA Technical Reports Server (NTRS)

Parker, Peter A.; Kowalski, Scott M.; Vining, G. Geoffrey

2006-01-01

When planning an experimental investigation, we are frequently faced with factors that are difficult or time consuming to manipulate, thereby making complete randomization impractical. A split-plot structure differentiates between the experimental units associated with these hard-to-change factors and others that are relatively easy-to-change and provides an efficient strategy that integrates the restrictions imposed by the experimental apparatus. Several industrial and scientific examples are presented to illustrate design considerations encountered in the restricted randomization context. In this paper, we propose classes of split-plot response designs that provide an intuitive and natural extension from the completely randomized context. For these designs, the ordinary least squares estimates of the model are equivalent to the generalized least squares estimates. This property provides best linear unbiased estimators and simplifies model estimation. The design conditions that allow for equivalent estimation are presented enabling design construction strategies to transform completely randomized Box-Behnken, equiradial, and small composite designs into a split-plot structure.

Fitting a Structured Juvenile-Adult Model for Green Tree Frogs to Population Estimates from Capture-Mark-Recapture Field Data

USGS Publications Warehouse

Ackleh, A.S.; Carter, J.; Deng, K.; Huang, Q.; Pal, N.; Yang, X.

2012-01-01

We derive point and interval estimates for an urban population of green tree frogs (Hyla cinerea) from capture-mark-recapture field data obtained during the years 2006-2009. We present an infinite-dimensional least-squares approach which compares a mathematical population model to the statistical population estimates obtained from the field data. The model is composed of nonlinear first-order hyperbolic equations describing the dynamics of the amphibian population where individuals are divided into juveniles (tadpoles) and adults (frogs). To solve the least-squares problem, an explicit finite difference approximation is developed. Convergence results for the computed parameters are presented. Parameter estimates for the vital rates of juveniles and adults are obtained, and standard deviations for these estimates are computed. Numerical results for the model sensitivity with respect to these parameters are given. Finally, the above-mentioned parameter estimates are used to illustrate the long-time behavior of the population under investigation. ?? 2011 Society for Mathematical Biology.

Cratering time scales for the Galilean satellites

NASA Technical Reports Server (NTRS)

Shoemaker, E. M.; Wolfe, R. F.

1982-01-01

An attempt is made to estimate the present cratering rate for each Galilean satellite within the correct order of magnitude and to extend the cratering rates back into the geologic past on the basis of evidence from the earth-moon system. For collisions with long and short period comets, the magnitudes and size distributions of the comet nuclei, the distribution of their perihelion distances, and the completeness of discovery are addressed. The diameters and masses of cometary nuclei are assessed, as are crater diameters and cratering rates. The dynamical relations between long period and short period comets are discussed, and the population of Jupiter-crossing asteroids is assessed. Estimated present cratering rates on the Galilean satellites are compared and variations of cratering rate with time are considered. Finally, the consistency of derived cratering time scales with the cratering record of the icy Galilean satellites is discussed.

Real-time stereo matching using orthogonal reliability-based dynamic programming.

PubMed

Gong, Minglun; Yang, Yee-Hong

2007-03-01

A novel algorithm is presented in this paper for estimating reliable stereo matches in real time. Based on the dynamic programming-based technique we previously proposed, the new algorithm can generate semi-dense disparity maps using as few as two dynamic programming passes. The iterative best path tracing process used in traditional dynamic programming is replaced by a local minimum searching process, making the algorithm suitable for parallel execution. Most computations are implemented on programmable graphics hardware, which improves the processing speed and makes real-time estimation possible. The experiments on the four new Middlebury stereo datasets show that, on an ATI Radeon X800 card, the presented algorithm can produce reliable matches for 60% approximately 80% of pixels at the rate of 10 approximately 20 frames per second. If needed, the algorithm can be configured for generating full density disparity maps.

Reduced-rank technique for joint channel estimation in TD-SCDMA systems

NASA Astrophysics Data System (ADS)

Kamil Marzook, Ali; Ismail, Alyani; Mohd Ali, Borhanuddin; Sali, Adawati; Khatun, Sabira

2013-02-01

In time division-synchronous code division multiple access systems, increasing the system capacity by exploiting the inserting of the largest number of users in one time slot (TS) requires adding more estimation processes to estimate the joint channel matrix for the whole system. The increase in the number of channel parameters due the increase in the number of users in one TS directly affects the precision of the estimator's performance. This article presents a novel channel estimation with low complexity, which relies on reducing the rank order of the total channel matrix H. The proposed method exploits the rank deficiency of H to reduce the number of parameters that characterise this matrix. The adopted reduced-rank technique is based on truncated singular value decomposition algorithm. The algorithms for reduced-rank joint channel estimation (JCE) are derived and compared against traditional full-rank JCEs: least squares (LS) or Steiner and enhanced (LS or MMSE) algorithms. Simulation results of the normalised mean square error showed the superiority of reduced-rank estimators. In addition, the channel impulse responses founded by reduced-rank estimator for all active users offers considerable performance improvement over the conventional estimator along the channel window length.

Fisher information in a quantum-critical environment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sun Zhe; Ma Jian; Lu Xiaoming

2010-08-15

We consider a process of parameter estimation in a spin-j system surrounded by a quantum-critical spin chain. Quantum Fisher information lies at the heart of the estimation task. We employ Ising spin chain in a transverse field as the environment which exhibits a quantum phase transition. Fisher information decays with time almost monotonously when the environment reaches the critical point. By choosing a fixed time or taking the time average, one can see the quantum Fisher information presents a sudden drop at the critical point. Different initial states of the environment are considered. The phenomenon that the quantum Fisher information,more » namely, the precision of estimation, changes dramatically can be used to detect the quantum criticality of the environment. We also introduce a general method to obtain the maximal Fisher information for a given state.« less

An adaptive bit synchronization algorithm under time-varying environment.

NASA Technical Reports Server (NTRS)

Chow, L. R.; Owen, H. A., Jr.; Wang, P. P.

1973-01-01

This paper presents an adaptive estimation algorithm for bit synchronization, assuming that the parameters of the incoming data process are time-varying. Experiment results have proved that this synchronizer is workable either judged by the amount of data required or the speed of convergence.

An optimally weighted estimator of the linear power spectrum disentangling the growth of density perturbations across galaxy surveys

NASA Astrophysics Data System (ADS)

Sorini, D.

2017-04-01

Measuring the clustering of galaxies from surveys allows us to estimate the power spectrum of matter density fluctuations, thus constraining cosmological models. This requires careful modelling of observational effects to avoid misinterpretation of data. In particular, signals coming from different distances encode information from different epochs. This is known as ``light-cone effect'' and is going to have a higher impact as upcoming galaxy surveys probe larger redshift ranges. Generalising the method by Feldman, Kaiser and Peacock (1994) [1], I define a minimum-variance estimator of the linear power spectrum at a fixed time, properly taking into account the light-cone effect. An analytic expression for the estimator is provided, and that is consistent with the findings of previous works in the literature. I test the method within the context of the Halofit model, assuming Planck 2014 cosmological parameters [2]. I show that the estimator presented recovers the fiducial linear power spectrum at present time within 5% accuracy up to k ~ 0.80 h Mpc-1 and within 10% up to k ~ 0.94 h Mpc-1, well into the non-linear regime of the growth of density perturbations. As such, the method could be useful in the analysis of the data from future large-scale surveys, like Euclid.

Chaotic behaviour of the short-term variations in ozone column observed in Arctic

NASA Astrophysics Data System (ADS)

Petkov, Boyan H.; Vitale, Vito; Mazzola, Mauro; Lanconelli, Christian; Lupi, Angelo

2015-09-01

The diurnal variations observed in the ozone column at Ny-Ålesund, Svalbard during different periods of 2009, 2010 and 2011 have been examined to test the hypothesis that they could be a result of a chaotic process. It was found that each of the attractors, reconstructed by applying the time delay technique and corresponding to any of the three time series can be embedded by 6-dimensional space. Recurrence plots, depicted to characterise the attractor features revealed structures typical for a chaotic system. In addition, the two positive Lyapunov exponents found for the three attractors, the fractal Hausdorff dimension presented by the Kaplan-Yorke estimator and the feasibility to predict the short-term ozone column variations within 10-20 h, knowing the past behaviour make the assumption about their chaotic character more realistic. The similarities of the estimated parameters in all three cases allow us to hypothesise that the three time series under study likely present one-dimensional projections of the same chaotic system taken at different time intervals.

Turbulent stresses in the surf-zone: Which way is up?

USGS Publications Warehouse

Haines, John W.; Gelfenbaum, Guy; Edge, B.L

1997-01-01

Velocity observations from a vertical stack of three-component Acoustic Doppler Velocimeters (ADVs) within the energetic surf-zone are presented. Rapid temporal sampling and small sampling volume provide observations suitable for investigation of the role of turbulent fluctuations in surf-zone dynamics. While sensor performance was good, failure to recover reliable measures of tilt from the vertical compromise the data value. We will present some cursory observations supporting the ADV performance, and examine the sensitivity of stress estimates to uncertainty in the sensor orientation. It is well known that turbulent stress estimates are highly sensitive to orientation relative to vertical when wave motions are dominant. Analyses presented examine the potential to use observed flow-field characteristics to constrain sensor orientation. Results show that such an approach may provide a consistent orientation to a fraction of a degree, but the inherent sensitivity of stress estimates requires a still more restrictive constraint. Regardless, the observations indicate the degree to which stress estimates are dependent on orientation, and provide some indication of the temporal variability in time-averaged stress estimates.

Capturing Context-Related Change in Emotional Dynamics via Fixed Moderated Time Series Analysis.

PubMed

Adolf, Janne K; Voelkle, Manuel C; Brose, Annette; Schmiedek, Florian

2017-01-01

Much of recent affect research relies on intensive longitudinal studies to assess daily emotional experiences. The resulting data are analyzed with dynamic models to capture regulatory processes involved in emotional functioning. Daily contexts, however, are commonly ignored. This may not only result in biased parameter estimates and wrong conclusions, but also ignores the opportunity to investigate contextual effects on emotional dynamics. With fixed moderated time series analysis, we present an approach that resolves this problem by estimating context-dependent change in dynamic parameters in single-subject time series models. The approach examines parameter changes of known shape and thus addresses the problem of observed intra-individual heterogeneity (e.g., changes in emotional dynamics due to observed changes in daily stress). In comparison to existing approaches to unobserved heterogeneity, model estimation is facilitated and different forms of change can readily be accommodated. We demonstrate the approach's viability given relatively short time series by means of a simulation study. In addition, we present an empirical application, targeting the joint dynamics of affect and stress and how these co-vary with daily events. We discuss potentials and limitations of the approach and close with an outlook on the broader implications for understanding emotional adaption and development.

An "intelligent" approach based on side-by-side cascade-correlation neural networks for estimating thermophysical properties from photothermal responses

NASA Astrophysics Data System (ADS)

Grieu, Stéphane; Faugeroux, Olivier; Traoré, Adama; Claudet, Bernard; Bodnar, Jean-Luc

2015-01-01

In the present paper, an artificial-intelligence-based approach dealing with the estimation of thermophysical properties is designed and evaluated. This new and "intelligent" approach makes use of photothermal responses obtained when subjecting materials to a light flux. So, the main objective of the present work was to estimate simultaneously both the thermal diffusivity and conductivity of materials, from front-face or rear-face photothermal responses to pseudo random binary signals. To this end, we used side-by-side feedforward neural networks trained with the cascade-correlation algorithm. In addition, computation time was a key point to consider. That is why the developed algorithms are computationally tractable.

A recursive solution for a fading memory filter derived from Kalman filter theory

NASA Technical Reports Server (NTRS)

Statman, J. I.

1986-01-01

A simple recursive solution for a class of fading memory tracking filters is presented. A fading memory filter provides estimates of filter states based on past measurements, similar to a traditional Kalman filter. Unlike a Kalman filter, an exponentially decaying weight is applied to older measurements, discounting their effect on present state estimates. It is shown that Kalman filters and fading memory filters are closely related solutions to a general least squares estimator problem. Closed form filter transfer functions are derived for a time invariant, steady state, fading memory filter. These can be applied in loop filter implementation of the Deep Space Network (DSN) Advanced Receiver carrier phase locked loop (PLL).

A simple method to assess unsaturated zone time lag in the travel time from ground surface to receptor.

PubMed

Sousa, Marcelo R; Jones, Jon P; Frind, Emil O; Rudolph, David L

2013-01-01

In contaminant travel from ground surface to groundwater receptors, the time taken in travelling through the unsaturated zone is known as the unsaturated zone time lag. Depending on the situation, this time lag may or may not be significant within the context of the overall problem. A method is presented for assessing the importance of the unsaturated zone in the travel time from source to receptor in terms of estimates of both the absolute and the relative advective times. A choice of different techniques for both unsaturated and saturated travel time estimation is provided. This method may be useful for practitioners to decide whether to incorporate unsaturated processes in conceptual and numerical models and can also be used to roughly estimate the total travel time between points near ground surface and a groundwater receptor. This method was applied to a field site located in a glacial aquifer system in Ontario, Canada. Advective travel times were estimated using techniques with different levels of sophistication. The application of the proposed method indicates that the time lag in the unsaturated zone is significant at this field site and should be taken into account. For this case, sophisticated and simplified techniques lead to similar assessments when the same knowledge of the hydraulic conductivity field is assumed. When there is significant uncertainty regarding the hydraulic conductivity, simplified calculations did not lead to a conclusive decision. Copyright © 2012 Elsevier B.V. All rights reserved.

Model-Based Design of Long-Distance Tracer Transport Experiments in Plants.

PubMed

Bühler, Jonas; von Lieres, Eric; Huber, Gregor J

2018-01-01

Studies of long-distance transport of tracer isotopes in plants offer a high potential for functional phenotyping, but so far measurement time is a bottleneck because continuous time series of at least 1 h are required to obtain reliable estimates of transport properties. Hence, usual throughput values are between 0.5 and 1 samples h -1 . Here, we propose to increase sample throughput by introducing temporal gaps in the data acquisition of each plant sample and measuring multiple plants one after each other in a rotating scheme. In contrast to common time series analysis methods, mechanistic tracer transport models allow the analysis of interrupted time series. The uncertainties of the model parameter estimates are used as a measure of how much information was lost compared to complete time series. A case study was set up to systematically investigate different experimental schedules for different throughput scenarios ranging from 1 to 12 samples h -1 . Selected designs with only a small amount of data points were found to be sufficient for an adequate parameter estimation, implying that the presented approach enables a substantial increase of sample throughput. The presented general framework for automated generation and evaluation of experimental schedules allows the determination of a maximal sample throughput and the respective optimal measurement schedule depending on the required statistical reliability of data acquired by future experiments.

Successful treatment with levothyroxine for idiopathic hypersomnia patients with subclinical hypothyroidism.

PubMed

Shinno, Hideto; Inami, Yasushi; Inagaki, Takuji; Kawamukai, Tetsuya; Utani, Etsuko; Nakamura, Yu; Horiguchi, Jun

2009-01-01

Our objective was to discuss the effect of levothyroxine on excessive daytime sleepiness (EDS) and a prolonged nocturnal sleep at patients with idiopathic hypersomnia who presented with subclinical hypothyroidism. We present two patients with hypersomnia who complained of EDS and a prolonged nocturnal sleep time. Sleep architecture and subjective daytime sleepiness were estimated by polysomnography (PSG) and Epworth Sleepiness Scale (ESS), respectively. Diagnoses were made using the International Classification of Sleep Disorders, 2nd Edition criteria for idiopathic hypersomnia with long sleep time. PSG demonstrated a short sleep latency, a prolonged total sleep time and normal proportions of all non-rapid eye movement (REM) and REM sleep stages. Nocturnal PSG excluded other causes of EDS. No medical, neurological and mental disorders were present. Their laboratory data indicated mildly elevated thyrotropin, despite free thyroxine (T4) and triiodothyronine (T3) estimates within their reference ranges, which is a characteristic of latent hypothyroidism. Levothyroxine (25 microg/day) was administrated orally. After treatment with levothyroxine for 8 weeks, the mean daily sleep times decreased. EDS was also improved, and a significant decrease in the ESS score was observed. Levothyroxine was effective for their hypersomnia and well tolerated. It should be noted that hypersomnia may be associated with subclinical hypothyroidism, although few abnormalities in physical and neurological examinations are present.

Fast gradient-based algorithm on extended landscapes for wave-front reconstruction of Earth observation satellite

NASA Astrophysics Data System (ADS)

Thiebaut, C.; Perraud, L.; Delvit, J. M.; Latry, C.

2016-07-01

We present an on-board satellite implementation of a gradient-based (optical flows) algorithm for the shifts estimation between images of a Shack-Hartmann wave-front sensor on extended landscapes. The proposed algorithm has low complexity in comparison with classical correlation methods which is a big advantage for being used on-board a satellite at high instrument data rate and in real-time. The electronic board used for this implementation is designed for space applications and is composed of radiation-hardened software and hardware. Processing times of both shift estimations and pre-processing steps are compatible of on-board real-time computation.

Analysis of conditional genetic effects and variance components in developmental genetics.

PubMed

Zhu, J

1995-12-01

A genetic model with additive-dominance effects and genotype x environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t-1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects.

Analysis of Conditional Genetic Effects and Variance Components in Developmental Genetics

PubMed Central

Zhu, J.

1995-01-01

A genetic model with additive-dominance effects and genotype X environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t - 1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects. PMID:8601500

Estimating post-marketing exposure to pharmaceutical products using ex-factory distribution data.

PubMed

Telfair, Tamara; Mohan, Aparna K; Shahani, Shalini; Klincewicz, Stephen; Atsma, Willem Jan; Thomas, Adrian; Fife, Daniel

2006-10-01

The pharmaceutical industry has an obligation to identify adverse reactions to drug products during all phases of drug development, including the post-marketing period. Estimates of population exposure to pharmaceutical products are important to the post-marketing surveillance of drugs, and provide a context for assessing the various risks and benefits, including drug safety, associated with drug treatment. This paper describes a systematic approach to estimating post-marketing drug exposure using ex-factory shipment data to estimate the quantity of medication available, and dosage information (stratified by indication or other factors as appropriate) to convert the quantity of medication to person time of exposure. Unlike the non-standardized methods often used to estimate exposure, this approach provides estimates whose calculations are explicit, documented, and consistent across products and over time. The methods can readily be carried out by an individual or small group specializing in this function, and lend themselves to automation. The present estimation approach is practical and relatively uncomplicated to implement. We believe it is a useful innovation. Copyright 2006 John Wiley & Sons, Ltd.

A time-dependent probabilistic seismic-hazard model for California

USGS Publications Warehouse

Cramer, C.H.; Petersen, M.D.; Cao, T.; Toppozada, Tousson R.; Reichle, M.

2000-01-01

For the purpose of sensitivity testing and illuminating nonconsensus components of time-dependent models, the California Department of Conservation, Division of Mines and Geology (CDMG) has assembled a time-dependent version of its statewide probabilistic seismic hazard (PSH) model for California. The model incorporates available consensus information from within the earth-science community, except for a few faults or fault segments where consensus information is not available. For these latter faults, published information has been incorporated into the model. As in the 1996 CDMG/U.S. Geological Survey (USGS) model, the time-dependent models incorporate three multisegment ruptures: a 1906, an 1857, and a southern San Andreas earthquake. Sensitivity tests are presented to show the effect on hazard and expected damage estimates of (1) intrinsic (aleatory) sigma, (2) multisegment (cascade) vs. independent segment (no cascade) ruptures, and (3) time-dependence vs. time-independence. Results indicate that (1) differences in hazard and expected damage estimates between time-dependent and independent models increase with decreasing intrinsic sigma, (2) differences in hazard and expected damage estimates between full cascading and not cascading are insensitive to intrinsic sigma, (3) differences in hazard increase with increasing return period (decreasing probability of occurrence), and (4) differences in moment-rate budgets increase with decreasing intrinsic sigma and with the degree of cascading, but are within the expected uncertainty in PSH time-dependent modeling and do not always significantly affect hazard and expected damage estimates.

Hazard Function Estimation with Cause-of-Death Data Missing at Random.

PubMed

Wang, Qihua; Dinse, Gregg E; Liu, Chunling

2012-04-01

Hazard function estimation is an important part of survival analysis. Interest often centers on estimating the hazard function associated with a particular cause of death. We propose three nonparametric kernel estimators for the hazard function, all of which are appropriate when death times are subject to random censorship and censoring indicators can be missing at random. Specifically, we present a regression surrogate estimator, an imputation estimator, and an inverse probability weighted estimator. All three estimators are uniformly strongly consistent and asymptotically normal. We derive asymptotic representations of the mean squared error and the mean integrated squared error for these estimators and we discuss a data-driven bandwidth selection method. A simulation study, conducted to assess finite sample behavior, demonstrates that the proposed hazard estimators perform relatively well. We illustrate our methods with an analysis of some vascular disease data.

Uncertainties associated with parameter estimation in atmospheric infrasound arrays.

PubMed

Szuberla, Curt A L; Olson, John V

2004-01-01

This study describes a method for determining the statistical confidence in estimates of direction-of-arrival and trace velocity stemming from signals present in atmospheric infrasound data. It is assumed that the signal source is far enough removed from the infrasound sensor array that a plane-wave approximation holds, and that multipath and multiple source effects are not present. Propagation path and medium inhomogeneities are assumed not to be known at the time of signal detection, but the ensemble of time delays of signal arrivals between array sensor pairs is estimable and corrupted by uncorrelated Gaussian noise. The method results in a set of practical uncertainties that lend themselves to a geometric interpretation. Although quite general, this method is intended for use by analysts interpreting data from atmospheric acoustic arrays, or those interested in designing and deploying them. The method is applied to infrasound arrays typical of those deployed as a part of the International Monitoring System of the Comprehensive Nuclear-Test-Ban Treaty Organization.

UWB pulse detection and TOA estimation using GLRT

NASA Astrophysics Data System (ADS)

Xie, Yan; Janssen, Gerard J. M.; Shakeri, Siavash; Tiberius, Christiaan C. J. M.

2017-12-01

In this paper, a novel statistical approach is presented for time-of-arrival (TOA) estimation based on first path (FP) pulse detection using a sub-Nyquist sampling ultra-wide band (UWB) receiver. The TOA measurement accuracy, which cannot be improved by averaging of the received signal, can be enhanced by the statistical processing of a number of TOA measurements. The TOA statistics are modeled and analyzed for a UWB receiver using threshold crossing detection of a pulse signal with noise. The detection and estimation scheme based on the Generalized Likelihood Ratio Test (GLRT) detector, which captures the full statistical information of the measurement data, is shown to achieve accurate TOA estimation and allows for a trade-off between the threshold level, the noise level, the amplitude and the arrival time of the first path pulse, and the accuracy of the obtained final TOA.

Using GNSS for Assessment Recent Sea Level Rise in the Northwestern Part of the Arabian Gulf

NASA Astrophysics Data System (ADS)

Alothman, A. O.; Bos, M. S.; Fernandes, R.

2017-12-01

Due to the global warming acting recently (in the 21st century) on the planet Earth, an associated sea level rise is predicted to reach up to 30 cm to 60 cm in some regions. Sea level monitoring is important for the Kingdom of Saudi Arabia, since it is surrounded by very long cost of about 3400 km in length and hundreds of isolated islands. The eastern coast line of KSA, in the Arabian Gulf, needs some monitoring in the long term, due to low land nature of the region. Also, the ongoing oil withdrawal activities in the area, may affect the regional sea level rise. In addition to these two facts, the tectonic structure of the Arabian Peninsula is one factor. The Regional Relative sea level in the eastern cost of Saudi Arabia has been estimated in the past using tide gauge data of more than 28 years using the vertical displacement of permanent Global Navigation Satellite System GNSS stations having time span of only about 3 years. In this paper, we discuss and update the methodology and results from Alothman et al. (2014), particularly by checking and extending the GNSS solutions. Since 3 of the 6 GPS stations used only started observing in the end of 2011, the longer time series have now significantly lower uncertainties in the estimated vertical rate. Longer time span of GNSS observations were included and 500 synthetic time series were estimated and seasonal signals were analysed. it is concluded that the varying seasonal signal present in the GNSS time series causes an underestimation of 0.1 mm/yr for short time series of 3 years. In addition to the implications of using short time series to estimate the vertical land motion, we found that if the varying seasonal signals are present in the data, the problem is aggravated. This finding can be useful for other studies analyzing short GNSS time series.

Nonparametric analysis of bivariate gap time with competing risks.

PubMed

Huang, Chiung-Yu; Wang, Chenguang; Wang, Mei-Cheng

2016-09-01

This article considers nonparametric methods for studying recurrent disease and death with competing risks. We first point out that comparisons based on the well-known cumulative incidence function can be confounded by different prevalence rates of the competing events, and that comparisons of the conditional distribution of the survival time given the failure event type are more relevant for investigating the prognosis of different patterns of recurrence disease. We then propose nonparametric estimators for the conditional cumulative incidence function as well as the conditional bivariate cumulative incidence function for the bivariate gap times, that is, the time to disease recurrence and the residual lifetime after recurrence. To quantify the association between the two gap times in the competing risks setting, a modified Kendall's tau statistic is proposed. The proposed estimators for the conditional bivariate cumulative incidence distribution and the association measure account for the induced dependent censoring for the second gap time. Uniform consistency and weak convergence of the proposed estimators are established. Hypothesis testing procedures for two-sample comparisons are discussed. Numerical simulation studies with practical sample sizes are conducted to evaluate the performance of the proposed nonparametric estimators and tests. An application to data from a pancreatic cancer study is presented to illustrate the methods developed in this article. © 2016, The International Biometric Society.

Criterion-Related Validity of the Distance- and Time-Based Walk/Run Field Tests for Estimating Cardiorespiratory Fitness: A Systematic Review and Meta-Analysis.

PubMed

Mayorga-Vega, Daniel; Bocanegra-Parrilla, Raúl; Ornelas, Martha; Viciana, Jesús

2016-01-01

The main purpose of the present meta-analysis was to examine the criterion-related validity of the distance- and time-based walk/run tests for estimating cardiorespiratory fitness among apparently healthy children and adults. Relevant studies were searched from seven electronic bibliographic databases up to August 2015 and through other sources. The Hunter-Schmidt's psychometric meta-analysis approach was conducted to estimate the population criterion-related validity of the following walk/run tests: 5,000 m, 3 miles, 2 miles, 3,000 m, 1.5 miles, 1 mile, 1,000 m, ½ mile, 600 m, 600 yd, ¼ mile, 15 min, 12 min, 9 min, and 6 min. From the 123 included studies, a total of 200 correlation values were analyzed. The overall results showed that the criterion-related validity of the walk/run tests for estimating maximum oxygen uptake ranged from low to moderate (rp = 0.42-0.79), with the 1.5 mile (rp = 0.79, 0.73-0.85) and 12 min walk/run tests (rp = 0.78, 0.72-0.83) having the higher criterion-related validity for distance- and time-based field tests, respectively. The present meta-analysis also showed that sex, age and maximum oxygen uptake level do not seem to affect the criterion-related validity of the walk/run tests. When the evaluation of an individual's maximum oxygen uptake attained during a laboratory test is not feasible, the 1.5 mile and 12 min walk/run tests represent useful alternatives for estimating cardiorespiratory fitness. As in the assessment with any physical fitness field test, evaluators must be aware that the performance score of the walk/run field tests is simply an estimation and not a direct measure of cardiorespiratory fitness.

An asymptotic method for estimating the vertical ozone distribution in the Earth's atmosphere from satellite measurements of backscattered solar UV-radiation

NASA Technical Reports Server (NTRS)

Ishov, Alexander G.

1994-01-01

An asymptotic approach to solution of the inverse problems of remote sensing is presented. It consists in changing integral operators characteristic of outgoing radiation into their asymptotic analogues. Such approach does not add new principal uncertainties into the problem and significantly reduces computation time that allows to develop the real (or about) time algorithms for interpretation of satellite measurements. The asymptotic approach has been realized for estimating vertical ozone distribution from satellite measurements of backscatter solar UV radiation in the Earth's atmosphere.

Super-Resolution Algorithm in Cumulative Virtual Blanking

NASA Astrophysics Data System (ADS)

Montillet, J. P.; Meng, X.; Roberts, G. W.; Woolfson, M. S.

2008-11-01

The proliferation of mobile devices and the emergence of wireless location-based services have generated consumer demand for precise location. In this paper, the MUSIC super-resolution algorithm is applied to time delay estimation for positioning purposes in cellular networks. The goal is to position a Mobile Station with UMTS technology. The problem of Base-Stations herability is solved using Cumulative Virtual Blanking. A simple simulator is presented using DS-SS signal. The results show that MUSIC algorithm improves the time delay estimation in both the cases whether or not Cumulative Virtual Blanking was carried out.

The size of the irregular migrant population in the European Union – counting the uncountable?

PubMed

Vogel, Dita; Kovacheva, Vesela; Prescott, Hannah

2011-01-01

It is difficult to estimate the size of the irregular migrant population in a specific city or country, and even more difficult to arrive at estimates at the European level. A review of past attempts at European-level estimates reveals that they rely on rough and outdated rules-of-thumb. In this paper, we present our own European level estimates for 2002, 2005, and 2008. We aggregate country-specific information, aiming at approximate comparability by consistent use of minimum and maximum estimates and by adjusting for obvious differences in definition and timescale. While the aggregated estimates are not considered highly reliable, they do -- for the first time -- provide transparency. The provision of more systematic medium quality estimates is shown to be the most promising way for improvement. The presented estimate indicates a minimum of 1.9 million and a maximum of 3.8 million irregular foreign residents in the 27 member states of the European Union (2008). Unlike rules-of-thumb, the aggregated EU estimates indicate a decline in the number of irregular foreign residents between 2002 and 2008. This decline has been influenced by the EU enlargement and legalisation programmes.

Acute and chronic respiratory effects of sodium borate particulate exposures.

PubMed Central

Wegman, D H; Eisen, E A; Hu, X; Woskie, S R; Smith, R G; Garabrant, D H

1994-01-01

This study examined work-related chronic abnormality in pulmonary function and work-related acute irritant symptoms associated with exposure to borate dust in mining and processing operations. Chronic effects were examined by pulmonary function at the beginning and end of a 7-year interval. Time-specific estimates of sodium borate particulate exposures were used to estimate cumulative exposure during the study interval. Change in pulmonary function over the 7 years was found unrelated to the estimate of cumulative exposure during that interval. Exposure-response associations also were examined with respect to short-term peak exposures and incidence of five symptoms of acute respiratory irritation. Hourly measures of health outcome and continuous measures of particulate exposure were made on each subject throughout the day. Whenever a subject reported one of the irritant symptoms, a symptom intensity score was also recorded along with the approximate time of onset. The findings indicated that exposure-response relationships were present for each of the specific symptoms at several symptom intensity levels. The associations were present when exposure was estimated by both day-long and short-term (15-min) time-weighted average exposures. Associations persisted after taking account of smoking, age, and the presence of a common cold. No significant difference in response rate was found between workers exposed to different types of sodium borate dusts. PMID:7889871

Combining nutation and surface gravity observations to estimate the Earth's core and inner core resonant frequencies

NASA Astrophysics Data System (ADS)

Ziegler, Yann; Lambert, Sébastien; Rosat, Séverine; Nurul Huda, Ibnu; Bizouard, Christian

2017-04-01

Nutation time series derived from very long baseline interferometry (VLBI) and time varying surface gravity data recorded by superconducting gravimeters (SG) have long been used separately to assess the Earth's interior via the estimation of the free core and inner core resonance effects on nutation or tidal gravity. The results obtained from these two techniques have been shown recently to be consistent, making relevant the combination of VLBI and SG observables and the estimation of Earth's interior parameters in a single inversion. We present here the intermediate results of the ongoing project of combining nutation and surface gravity time series to improve estimates of the Earth's core and inner core resonant frequencies. We use VLBI nutation time series spanning 1984-2016 derived by the International VLBI Service for geodesy and astrometry (IVS) as the result of a combination of inputs from various IVS analysis centers, and surface gravity data from about 15 SG stations. We address here the resonance model used for describing the Earth's interior response to tidal excitation, the data preparation consisting of the error recalibration and amplitude fitting for nutation data, and processing of SG time-varying gravity to remove any gaps, spikes, steps and other disturbances, followed by the tidal analysis with the ETERNA 3.4 software package, the preliminary estimates of the resonant periods, and the correlations between parameters.

Modelling the effect on injuries and fatalities when changing mode of transport from car to bicycle.

PubMed

Nilsson, Philip; Stigson, Helena; Ohlin, Maria; Strandroth, Johan

2017-03-01

Several studies have estimated the health effects of active commuting, where a transport mode shift from car to bicycle reduces risk of mortality and morbidity. Previous studies mainly assess the negative aspects of bicycling by referring to fatalities or police reported injuries. However, most bicycle crashes are not reported by the police and therefore hospital reported data would cover a much higher rate of injuries from bicycle crashes. The aim of the present study was to estimate the effect on injuries and fatalities from traffic crashes when shifting mode of transport from car to bicycle by using hospital reported data. This present study models the change in number of injuries and fatalities due to a transport mode change using a given flow change from car to bicycle and current injury and fatality risk per distance for bicyclists and car occupants. show that bicyclists have a much higher injury risk (29 times) and fatality risk (10 times) than car occupants. In a scenario where car occupants in Stockholm living close to their work place shifts transport mode to bicycling, injuries, fatalities and health loss expressed in Disability-Adjusted Life Years (DALY) were estimated to increase. The vast majority of the estimated DALY increase was caused by severe injuries and fatalities and it tends to fluctuate so that the number of severe crashes may exceed the estimation with a large margin. Although the estimated increase of traffic crashes and DALY, a transport mode shift is seen as a way towards a more sustainable society. Thus, this present study highlights the need of strategic preventive measures in order to minimize the negative impacts from increased bicycling. Copyright © 2016 Elsevier Ltd. All rights reserved.

Estimation of position and velocity for a low dynamic vehicle in near space using nonresolved photometric and astrometric data.

PubMed

Jing, Nan; Li, Chuang; Chong, Yaqin

2017-01-20

An estimation method for indirectly observable parameters for a typical low dynamic vehicle (LDV) is presented. The estimation method utilizes apparent magnitude, azimuth angle, and elevation angle to estimate the position and velocity of a typical LDV, such as a high altitude balloon (HAB). In order to validate the accuracy of the estimated parameters gained from an unscented Kalman filter, two sets of experiments are carried out to obtain the nonresolved photometric and astrometric data. In the experiments, a HAB launch is planned; models of the HAB dynamics and kinematics and observation models are built to use as time update and measurement update functions, respectively. When the HAB is launched, a ground-based optoelectronic detector is used to capture the object images, which are processed using aperture photometry technology to obtain the time-varying apparent magnitude of the HAB. Two sets of actual and estimated parameters are given to clearly indicate the parameter differences. Two sets of errors between the actual and estimated parameters are also given to show how the estimated position and velocity differ with respect to the observation time. The similar distribution curve results from the two scenarios, which agree within 3σ, verify that nonresolved photometric and astrometric data can be used to estimate the indirectly observable state parameters (position and velocity) for a typical LDV. This technique can be applied to small and dim space objects in the future.

Fossil-Fuel C02 Emissions Database and Exploration System

NASA Astrophysics Data System (ADS)

Krassovski, M.; Boden, T.; Andres, R. J.; Blasing, T. J.

2012-12-01

The Carbon Dioxide Information Analysis Center (CDIAC) at Oak Ridge National Laboratory (ORNL) quantifies the release of carbon from fossil-fuel use and cement production at global, regional, and national spatial scales. The CDIAC emission time series estimates are based largely on annual energy statistics published at the national level by the United Nations (UN). CDIAC has developed a relational database to house collected data and information and a web-based interface to help users worldwide identify, explore and download desired emission data. The available information is divided in two major group: time series and gridded data. The time series data is offered for global, regional and national scales. Publications containing historical energy statistics make it possible to estimate fossil fuel CO2 emissions back to 1751. Etemad et al. (1991) published a summary compilation that tabulates coal, brown coal, peat, and crude oil production by nation and year. Footnotes in the Etemad et al.(1991) publication extend the energy statistics time series back to 1751. Summary compilations of fossil fuel trade were published by Mitchell (1983, 1992, 1993, 1995). Mitchell's work tabulates solid and liquid fuel imports and exports by nation and year. These pre-1950 production and trade data were digitized and CO2 emission calculations were made following the procedures discussed in Marland and Rotty (1984) and Boden et al. (1995). The gridded data presents annual and monthly estimates. Annual data presents a time series recording 1° latitude by 1° longitude CO2 emissions in units of million metric tons of carbon per year from anthropogenic sources for 1751-2008. The monthly, fossil-fuel CO2 emissions estimates from 1950-2008 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2011), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). This presentation introduces newly build database and web interface, reflects the present state and functionality of the Fossil-Fuel CO2 Emissions Database and Exploration System as well as future plans for expansion.

Adaptive Monocular Visual-Inertial SLAM for Real-Time Augmented Reality Applications in Mobile Devices.

PubMed

Piao, Jin-Chun; Kim, Shin-Dug

2017-11-07

Simultaneous localization and mapping (SLAM) is emerging as a prominent issue in computer vision and next-generation core technology for robots, autonomous navigation and augmented reality. In augmented reality applications, fast camera pose estimation and true scale are important. In this paper, we present an adaptive monocular visual-inertial SLAM method for real-time augmented reality applications in mobile devices. First, the SLAM system is implemented based on the visual-inertial odometry method that combines data from a mobile device camera and inertial measurement unit sensor. Second, we present an optical-flow-based fast visual odometry method for real-time camera pose estimation. Finally, an adaptive monocular visual-inertial SLAM is implemented by presenting an adaptive execution module that dynamically selects visual-inertial odometry or optical-flow-based fast visual odometry. Experimental results show that the average translation root-mean-square error of keyframe trajectory is approximately 0.0617 m with the EuRoC dataset. The average tracking time is reduced by 7.8%, 12.9%, and 18.8% when different level-set adaptive policies are applied. Moreover, we conducted experiments with real mobile device sensors, and the results demonstrate the effectiveness of performance improvement using the proposed method.

Determining prescription durations based on the parametric waiting time distribution.

PubMed

Støvring, Henrik; Pottegård, Anton; Hallas, Jesper

2016-12-01

The purpose of the study is to develop a method to estimate the duration of single prescriptions in pharmacoepidemiological studies when the single prescription duration is not available. We developed an estimation algorithm based on maximum likelihood estimation of a parametric two-component mixture model for the waiting time distribution (WTD). The distribution component for prevalent users estimates the forward recurrence density (FRD), which is related to the distribution of time between subsequent prescription redemptions, the inter-arrival density (IAD), for users in continued treatment. We exploited this to estimate percentiles of the IAD by inversion of the estimated FRD and defined the duration of a prescription as the time within which 80% of current users will have presented themselves again. Statistical properties were examined in simulation studies, and the method was applied to empirical data for four model drugs: non-steroidal anti-inflammatory drugs (NSAIDs), warfarin, bendroflumethiazide, and levothyroxine. Simulation studies found negligible bias when the data-generating model for the IAD coincided with the FRD used in the WTD estimation (Log-Normal). When the IAD consisted of a mixture of two Log-Normal distributions, but was analyzed with a single Log-Normal distribution, relative bias did not exceed 9%. Using a Log-Normal FRD, we estimated prescription durations of 117, 91, 137, and 118 days for NSAIDs, warfarin, bendroflumethiazide, and levothyroxine, respectively. Similar results were found with a Weibull FRD. The algorithm allows valid estimation of single prescription durations, especially when the WTD reliably separates current users from incident users, and may replace ad-hoc decision rules in automated implementations. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Cost estimating methods for advanced space systems

NASA Technical Reports Server (NTRS)

Cyr, Kelley

1988-01-01

Parametric cost estimating methods for space systems in the conceptual design phase are developed. The approach is to identify variables that drive cost such as weight, quantity, development culture, design inheritance, and time. The relationship between weight and cost is examined in detail. A theoretical model of cost is developed and tested statistically against a historical data base of major research and development programs. It is concluded that the technique presented is sound, but that it must be refined in order to produce acceptable cost estimates.

An Estimation of the Logarithmic Timescale in Ergodic Dynamics

NASA Astrophysics Data System (ADS)

Gomez, Ignacio S.

An estimation of the logarithmic timescale in quantum systems having an ergodic dynamics in the semiclassical limit, is presented. The estimation is based on an extension of the Krieger’s finite generator theorem for discretized σ-algebras and using the time rescaling property of the Kolmogorov-Sinai entropy. The results are in agreement with those obtained in the literature but with a simpler mathematics and within the context of the ergodic theory. Moreover, some consequences of the Poincaré’s recurrence theorem are also explored.

Costing the satellite power system

NASA Technical Reports Server (NTRS)

Hazelrigg, G. A., Jr.

1978-01-01

The paper presents a methodology for satellite power system costing, places approximate limits on the accuracy possible in cost estimates made at this time, and outlines the use of probabilistic cost information in support of the decision-making process. Reasons for using probabilistic costing or risk analysis procedures instead of standard deterministic costing procedures are considered. Components of cost, costing estimating relationships, grass roots costing, and risk analysis are discussed. Risk analysis using a Monte Carlo simulation model is used to estimate future costs.

A two-thermocouple probe technique for estimating thermocouple time constants in flows with combustion: In situ parameter identification of a first-order lag system

NASA Astrophysics Data System (ADS)

Tagawa, M.; Shimoji, T.; Ohta, Y.

1998-09-01

A two-thermocouple probe, composed of two fine-wire thermocouples of unequal diameters, is a novel technique for estimating thermocouple time constants without any dynamic calibration of the thermocouple response. This technique is most suitable for measuring fluctuating temperatures in turbulent combustion. In the present study, the reliability and applicability of this technique are appraised in a turbulent wake of a heated cylinder (without combustion). A fine-wire resistance thermometer (cold wire) of fast response is simultaneously used to provide a reference temperature. A quantitative and detailed comparison between the cold-wire measurement and the compensated thermocouple ones shows that a previous estimation scheme gives thermocouple time constants smaller than appropriate values, unless the noise in the thermocouple signals is negligible and/or the spatial resolution of the two-thermocouple probe is sufficiently high. The scheme has been improved so as to maximize the correlation coefficient between the two compensated-thermocouple outputs. The improved scheme offers better compensation of the thermocouple response. The present approach is generally applicable to in situ parameter identification of a first-order lag system.

The TRMM Multi-satellite Precipitation Analysis (TMPA): Quasi-Global Precipitation Estimates at Fine Scales

NASA Technical Reports Server (NTRS)

Huffman, George J.; Adler, Robert F.; Bolvin, David T.; Gu, Guojun; Nelkin, Eric J.; Bowman, Kenneth P.; Stocker, Erich; Wolff, David B.

2006-01-01

The TRMM Multi-satellite Precipitation Analysis (TMPA) provides a calibration-based sequential scheme for combining multiple precipitation estimates from satellites, as well as gauge analyses where feasible, at fine scales (0.25 degrees x 0.25 degrees and 3-hourly). It is available both after and in real time, based on calibration by the TRMM Combined Instrument and TRMM Microwave Imager precipitation products, respectively. Only the after-real-time product incorporates gauge data at the present. The data set covers the latitude band 50 degrees N-S for the period 1998 to the delayed present. Early validation results are as follows: The TMPA provides reasonable performance at monthly scales, although it is shown to have precipitation rate dependent low bias due to lack of sensitivity to low precipitation rates in one of the input products (based on AMSU-B). At finer scales the TMPA is successful at approximately reproducing the surface-observation-based histogram of precipitation, as well as reasonably detecting large daily events. The TMPA, however, has lower skill in correctly specifying moderate and light event amounts on short time intervals, in common with other fine-scale estimators. Examples are provided of a flood event and diurnal cycle determination.

Anticipating abrupt shifts in temporal evolution of probability of eruption

NASA Astrophysics Data System (ADS)

Rohmer, J.; Loschetter, A.

2016-04-01

Estimating the probability of eruption by jointly accounting for different sources of monitoring parameters over time is a key component for volcano risk management. In the present study, we are interested in the transition from a state of low-to-moderate probability value to a state of high probability value. By using the data of MESIMEX exercise at the Vesuvius volcano, we investigated the potential for time-varying indicators related to the correlation structure or to the variability of the probability time series for detecting in advance this critical transition. We found that changes in the power spectra and in the standard deviation estimated over a rolling time window both present an abrupt increase, which marks the approaching shift. Our numerical experiments revealed that the transition from an eruption probability of 10-15% to > 70% could be identified up to 1-3 h in advance. This additional lead time could be useful to place different key services (e.g., emergency services for vulnerable groups, commandeering additional transportation means, etc.) on a higher level of alert before the actual call for evacuation.

Statistical tools for analysis and modeling of cosmic populations and astronomical time series: CUDAHM and TSE

NASA Astrophysics Data System (ADS)

Loredo, Thomas; Budavari, Tamas; Scargle, Jeffrey D.

2018-01-01

This presentation provides an overview of open-source software packages addressing two challenging classes of astrostatistics problems. (1) CUDAHM is a C++ framework for hierarchical Bayesian modeling of cosmic populations, leveraging graphics processing units (GPUs) to enable applying this computationally challenging paradigm to large datasets. CUDAHM is motivated by measurement error problems in astronomy, where density estimation and linear and nonlinear regression must be addressed for populations of thousands to millions of objects whose features are measured with possibly complex uncertainties, potentially including selection effects. An example calculation demonstrates accurate GPU-accelerated luminosity function estimation for simulated populations of $10^6$ objects in about two hours using a single NVIDIA Tesla K40c GPU. (2) Time Series Explorer (TSE) is a collection of software in Python and MATLAB for exploratory analysis and statistical modeling of astronomical time series. It comprises a library of stand-alone functions and classes, as well as an application environment for interactive exploration of times series data. The presentation will summarize key capabilities of this emerging project, including new algorithms for analysis of irregularly-sampled time series.

Conditional nonlinear optimal perturbations based on the particle swarm optimization and their applications to the predictability problems

NASA Astrophysics Data System (ADS)

Zheng, Qin; Yang, Zubin; Sha, Jianxin; Yan, Jun

2017-02-01

In predictability problem research, the conditional nonlinear optimal perturbation (CNOP) describes the initial perturbation that satisfies a certain constraint condition and causes the largest prediction error at the prediction time. The CNOP has been successfully applied in estimation of the lower bound of maximum predictable time (LBMPT). Generally, CNOPs are calculated by a gradient descent algorithm based on the adjoint model, which is called ADJ-CNOP. This study, through the two-dimensional Ikeda model, investigates the impacts of the nonlinearity on ADJ-CNOP and the corresponding precision problems when using ADJ-CNOP to estimate the LBMPT. Our conclusions are that (1) when the initial perturbation is large or the prediction time is long, the strong nonlinearity of the dynamical model in the prediction variable will lead to failure of the ADJ-CNOP method, and (2) when the objective function has multiple extreme values, ADJ-CNOP has a large probability of producing local CNOPs, hence making a false estimation of the LBMPT. Furthermore, the particle swarm optimization (PSO) algorithm, one kind of intelligent algorithm, is introduced to solve this problem. The method using PSO to compute CNOP is called PSO-CNOP. The results of numerical experiments show that even with a large initial perturbation and long prediction time, or when the objective function has multiple extreme values, PSO-CNOP can always obtain the global CNOP. Since the PSO algorithm is a heuristic search algorithm based on the population, it can overcome the impact of nonlinearity and the disturbance from multiple extremes of the objective function. In addition, to check the estimation accuracy of the LBMPT presented by PSO-CNOP and ADJ-CNOP, we partition the constraint domain of initial perturbations into sufficiently fine grid meshes and take the LBMPT obtained by the filtering method as a benchmark. The result shows that the estimation presented by PSO-CNOP is closer to the true value than the one by ADJ-CNOP with the forecast time increasing.

A comparison of time dependent Cox regression, pooled logistic regression and cross sectional pooling with simulations and an application to the Framingham Heart Study.

PubMed

Ngwa, Julius S; Cabral, Howard J; Cheng, Debbie M; Pencina, Michael J; Gagnon, David R; LaValley, Michael P; Cupples, L Adrienne

2016-11-03

Typical survival studies follow individuals to an event and measure explanatory variables for that event, sometimes repeatedly over the course of follow up. The Cox regression model has been used widely in the analyses of time to diagnosis or death from disease. The associations between the survival outcome and time dependent measures may be biased unless they are modeled appropriately. In this paper we explore the Time Dependent Cox Regression Model (TDCM), which quantifies the effect of repeated measures of covariates in the analysis of time to event data. This model is commonly used in biomedical research but sometimes does not explicitly adjust for the times at which time dependent explanatory variables are measured. This approach can yield different estimates of association compared to a model that adjusts for these times. In order to address the question of how different these estimates are from a statistical perspective, we compare the TDCM to Pooled Logistic Regression (PLR) and Cross Sectional Pooling (CSP), considering models that adjust and do not adjust for time in PLR and CSP. In a series of simulations we found that time adjusted CSP provided identical results to the TDCM while the PLR showed larger parameter estimates compared to the time adjusted CSP and the TDCM in scenarios with high event rates. We also observed upwardly biased estimates in the unadjusted CSP and unadjusted PLR methods. The time adjusted PLR had a positive bias in the time dependent Age effect with reduced bias when the event rate is low. The PLR methods showed a negative bias in the Sex effect, a subject level covariate, when compared to the other methods. The Cox models yielded reliable estimates for the Sex effect in all scenarios considered. We conclude that survival analyses that explicitly account in the statistical model for the times at which time dependent covariates are measured provide more reliable estimates compared to unadjusted analyses. We present results from the Framingham Heart Study in which lipid measurements and myocardial infarction data events were collected over a period of 26 years.

Functional localization of a "Time Keeper" function separate from attentional resources and task strategy.

PubMed

Tracy, J I; Faro, S H; Mohamed, F B; Pinsk, M; Pinus, A

2000-03-01

The functional neuroanatomy of time estimation has not been well-documented. This research investigated the fMRI measured brain response to an explicit, prospective time interval production (TIP) task. The study tested for the presence of brain activity reflecting a primary time keeper function, distinct from the brain systems involved either in conscious strategies to monitor time or attentional resource and other cognitive processes to accomplish the task. In the TIP task participants were given a time interval and asked to indicate when it elapsed. Two control tasks (counting forwards, backwards) were administered, in addition to a dual task format of the TIP task. Whole brain images were collected at 1.5 Tesla. Analyses (n = 6) yielded a statistical parametric map (SPM ¿z¿) reflecting time keeping and not strategy (counting, number manipulation) or attention resource utilization. Additional SPM ¿z¿s involving activation associated with the accuracy and magnitude the of time estimation response are presented. Results revealed lateral cerebellar and inferior temporal lobe activation were associated with primary time keeping. Behavioral data provided evidence that the procedures for the explicit time judgements did not occur automatically and utilized controlled processes. Activation sites associated with accuracy, magnitude, and the dual task provided indications of the other structures involved in time estimation that implemented task components related to controlled processing. The data are consistent with prior proposals that the cerebellum is a repository of codes for time processing, but also implicate temporal lobe structures for this type of time estimation task. Copyright 2000 Academic Press.

Numerical scheme approximating solution and parameters in a beam equation

NASA Astrophysics Data System (ADS)

Ferdinand, Robert R.

2003-12-01

We present a mathematical model which describes vibration in a metallic beam about its equilibrium position. This model takes the form of a nonlinear second-order (in time) and fourth-order (in space) partial differential equation with boundary and initial conditions. A finite-element Galerkin approximation scheme is used to estimate model solution. Infinite-dimensional model parameters are then estimated numerically using an inverse method procedure which involves the minimization of a least-squares cost functional. Numerical results are presented and future work to be done is discussed.

The impact of estimation errors on evaluations of timber production opportunities.

Treesearch

Dennis L. Schweitzer

1970-01-01

Errors in estimating costs and return, the timing of harvests, and the cost of using funds can greatly affect the apparent desirability of investments in timber production. Partial derivatives are used to measure the impact of these errors on the predicted present net worth of potential investments in timber production. Graphs that illustrate the impact of each type...

Monthly leaf area index estimates from point-in-time measurements and needle phenology for Pinus taeda

Treesearch

D.A. Sampson; T.J. Albaugh; Kurt H. Johnsen; H.L. Allen; Stanley J. Zarnoch

2003-01-01

Abstract: Leaf area index (LAI) of loblolly pine (Pinus taeda L.) trees of the southern United States varies almost twofold interannually; loblolly pine, essentially, carries two foliage cohorts at peak LAI (September) and one at minimum (March–April). Herein, we present an approach that may be site invariant to estimate monthly...

Near-Miss Effects on Response Latencies and Win Estimations of Slot Machine Players

ERIC Educational Resources Information Center

Dixon, Mark R.; Schreiber, James E.

2004-01-01

The present study examined the degree to which slot machine near-miss trials, or trials that displayed 2 of 3 winning symbols on the payoff line, affected response times and win estimations of 12 recreational slot machine players. Participants played a commercial slot machine in a casino-like laboratory for course extra-credit points. Videotaped…

Exceptional Information: Recognizing Threats and Exploiting Opportunities

DTIC Science & Technology

2017-06-09

EXCEPTIONAL INFORMATION : RECOGNIZING THREATS AND EXPLOITING OPPORTUNITIES A thesis presented to the Faculty of the U.S. Army...No. 0704-0188 Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for... information . Send comments regarding this burden estimate or any other aspect of this collection of information , including suggestions for reducing this

Comparison and testing of extended Kalman filters for attitude estimation of the Earth radiation budget satellite

NASA Technical Reports Server (NTRS)

Deutschmann, Julie; Bar-Itzhack, Itzhack Y.; Rokni, Mohammad

1990-01-01

The testing and comparison of two Extended Kalman Filters (EKFs) developed for the Earth Radiation Budget Satellite (ERBS) is described. One EKF updates the attitude quaternion using a four component additive error quaternion. This technique is compared to that of a second EKF, which uses a multiplicative error quaternion. A brief development of the multiplicative algorithm is included. The mathematical development of the additive EKF was presented in the 1989 Flight Mechanics/Estimation Theory Symposium along with some preliminary testing results using real spacecraft data. A summary of the additive EKF algorithm is included. The convergence properties, singularity problems, and normalization techniques of the two filters are addressed. Both filters are also compared to those from the ERBS operational ground support software, which uses a batch differential correction algorithm to estimate attitude and gyro biases. Sensitivity studies are performed on the estimation of sensor calibration states. The potential application of the EKF for real time and non-real time ground attitude determination and sensor calibration for future missions such as the Gamma Ray Observatory (GRO) and the Small Explorer Mission (SMEX) is also presented.

Real-time video analysis for retail stores

NASA Astrophysics Data System (ADS)

Hassan, Ehtesham; Maurya, Avinash K.

2015-03-01

With the advancement in video processing technologies, we can capture subtle human responses in a retail store environment which play decisive role in the store management. In this paper, we present a novel surveillance video based analytic system for retail stores targeting localized and global traffic estimate. Development of an intelligent system for human traffic estimation in real-life poses a challenging problem because of the variation and noise involved. In this direction, we begin with a novel human tracking system by an intelligent combination of motion based and image level object detection. We demonstrate the initial evaluation of this approach on available standard dataset yielding promising result. Exact traffic estimate in a retail store require correct separation of customers from service providers. We present a role based human classification framework using Gaussian mixture model for this task. A novel feature descriptor named graded colour histogram is defined for object representation. Using, our role based human classification and tracking system, we have defined a novel computationally efficient framework for two types of analytics generation i.e., region specific people count and dwell-time estimation. This system has been extensively evaluated and tested on four hours of real-life video captured from a retail store.

Oscillometric Blood Pressure Estimation: Past, Present, and Future.

PubMed

Forouzanfar, Mohamad; Dajani, Hilmi R; Groza, Voicu Z; Bolic, Miodrag; Rajan, Sreeraman; Batkin, Izmail

2015-01-01

The use of automated blood pressure (BP) monitoring is growing as it does not require much expertise and can be performed by patients several times a day at home. Oscillometry is one of the most common measurement methods used in automated BP monitors. A review of the literature shows that a large variety of oscillometric algorithms have been developed for accurate estimation of BP but these algorithms are scattered in many different publications or patents. Moreover, considering that oscillometric devices dominate the home BP monitoring market, little effort has been made to survey the underlying algorithms that are used to estimate BP. In this review, a comprehensive survey of the existing oscillometric BP estimation algorithms is presented. The survey covers a broad spectrum of algorithms including the conventional maximum amplitude and derivative oscillometry as well as the recently proposed learning algorithms, model-based algorithms, and algorithms that are based on analysis of pulse morphology and pulse transit time. The aim is to classify the diverse underlying algorithms, describe each algorithm briefly, and discuss their advantages and disadvantages. This paper will also review the artifact removal techniques in oscillometry and the current standards for the automated BP monitors.

Distributed flow sensing for closed-loop speed control of a flexible fish robot.

PubMed

Zhang, Feitian; Lagor, Francis D; Yeo, Derrick; Washington, Patrick; Paley, Derek A

2015-10-23

Flexibility plays an important role in fish behavior by enabling high maneuverability for predator avoidance and swimming in turbulent flow. This paper presents a novel flexible fish robot equipped with distributed pressure sensors for flow sensing. The body of the robot is molded from soft, hyperelastic material, which provides flexibility. Its Joukowski-foil shape is conducive to modeling the fluid analytically. A quasi-steady potential-flow model is adopted for real-time flow estimation, whereas a discrete-time vortex-shedding flow model is used for higher-fidelity simulation. The dynamics for the flexible fish robot yield a reduced model for one-dimensional swimming. A recursive Bayesian filter assimilates pressure measurements to estimate flow speed, angle of attack, and foil camber. The closed-loop speed-control strategy combines an inverse-mapping feedforward controller based on an average model derived for periodic actuation of angle-of-attack and a proportional-integral feedback controller utilizing the estimated flow information. Simulation and experimental results are presented to show the effectiveness of the estimation and control strategy. The paper provides a systematic approach to distributed flow sensing for closed-loop speed control of a flexible fish robot by regulating the flapping amplitude.

Real-time two-dimensional temperature imaging using ultrasound.

PubMed

Liu, Dalong; Ebbini, Emad S

2009-01-01

We present a system for real-time 2D imaging of temperature change in tissue media using pulse-echo ultrasound. The frontend of the system is a SonixRP ultrasound scanner with a research interface giving us the capability of controlling the beam sequence and accessing radio frequency (RF) data in real-time. The beamformed RF data is streamlined to the backend of the system, where the data is processed using a two-dimensional temperature estimation algorithm running in the graphics processing unit (GPU). The estimated temperature is displayed in real-time providing feedback that can be used for real-time control of the heating source. Currently we have verified our system with elastography tissue mimicking phantom and in vitro porcine heart tissue, excellent repeatability and sensitivity were demonstrated.

Experimental determination of the navigation error of the 4-D navigation, guidance, and control systems on the NASA B-737 airplane

NASA Technical Reports Server (NTRS)

Knox, C. E.

1978-01-01

Navigation error data from these flights are presented in a format utilizing three independent axes - horizontal, vertical, and time. The navigation position estimate error term and the autopilot flight technical error term are combined to form the total navigation error in each axis. This method of error presentation allows comparisons to be made between other 2-, 3-, or 4-D navigation systems and allows experimental or theoretical determination of the navigation error terms. Position estimate error data are presented with the navigation system position estimate based on dual DME radio updates that are smoothed with inertial velocities, dual DME radio updates that are smoothed with true airspeed and magnetic heading, and inertial velocity updates only. The normal mode of navigation with dual DME updates that are smoothed with inertial velocities resulted in a mean error of 390 m with a standard deviation of 150 m in the horizontal axis; a mean error of 1.5 m low with a standard deviation of less than 11 m in the vertical axis; and a mean error as low as 252 m with a standard deviation of 123 m in the time axis.

Is my bottom-up uncertainty estimation on metal measurement adequate?

NASA Astrophysics Data System (ADS)

Marques, J. R.; Faustino, M. G.; Monteiro, L. R.; Ulrich, J. C.; Pires, M. A. F.; Cotrim, M. E. B.

2018-03-01

Is the estimated uncertainty under GUM recommendation associated with metal measurement adequately estimated? How to evaluate if the measurement uncertainty really covers all uncertainty that is associated with the analytical procedure? Considering that, many laboratories frequently underestimate or less frequently overestimate uncertainties on its results; this paper presents the evaluation of estimated uncertainties on two ICP-OES procedures of seven metal measurements according to GUM approach. Horwitz function and proficiency tests scaled standard uncertainties were used in this evaluation. Our data shows that most elements expanded uncertainties were from two to four times underestimated. Possible causes and corrections are discussed herein.

Evaluation of Piloted Inputs for Onboard Frequency Response Estimation

NASA Technical Reports Server (NTRS)

Grauer, Jared A.; Martos, Borja

2013-01-01

Frequency response estimation results are presented using piloted inputs and a real-time estimation method recently developed for multisine inputs. A nonlinear simulation of the F-16 and a Piper Saratoga research aircraft were subjected to different piloted test inputs while the short period stabilator/elevator to pitch rate frequency response was estimated. Results show that the method can produce accurate results using wide-band piloted inputs instead of multisines. A new metric is introduced for evaluating which data points to include in the analysis and recommendations are provided for applying this method with piloted inputs.

Recent results of nonlinear estimators applied to hereditary systems.

NASA Technical Reports Server (NTRS)

Schiess, J. R.; Roland, V. R.; Wells, W. R.

1972-01-01

An application of the extended Kalman filter to delayed systems to estimate the state and time delay is presented. Two nonlinear estimators are discussed and the results compared with those of the Kalman filter. For all the filters considered, the hereditary system was treated with the delay in the pure form and by using Pade approximations of the delay. A summary of the convergence properties of the filters studied is given. The results indicate that the linear filter applied to the delayed system performs inadequately while the nonlinear filters provide reasonable estimates of both the state and the parameters.

Computer simulation results of attitude estimation of earth orbiting satellites

NASA Technical Reports Server (NTRS)

Kou, S. R.

1976-01-01

Computer simulation results of attitude estimation of Earth-orbiting satellites (including Space Telescope) subjected to environmental disturbances and noises are presented. Decomposed linear recursive filter and Kalman filter were used as estimation tools. Six programs were developed for this simulation, and all were written in the basic language and were run on HP 9830A and HP 9866A computers. Simulation results show that a decomposed linear recursive filter is accurate in estimation and fast in response time. Furthermore, for higher order systems, this filter has computational advantages (i.e., less integration errors and roundoff errors) over a Kalman filter.

Actuarial status of the old-age and survivors insurance and disability insurance trust funds.

PubMed

Ballantyne, H C

1982-06-01

The 1982 Annual Report of the Board of Trustees of the Old-Age and Survivors Insurance (OASI) and Disability Insurance (DI) Trust Funds indicates sever financial problems in both the short and the long range. The short-range financial status is significantly worse than was estimated last year, after enactment of the 1981 legislation, because of continuing unfavorable economic conditions. The estimated long-range deficit is the same as the deficit that was estimated last year before the 1981 legislation and is therefore somewhat worse than was estimated immediately after enactment of the legislation. Under present law, which authorizes temporary interfund borrowing amount the OASI, DI, and Hospital Insurance (HI) Trust Funds, the OASI Trust Fund would become unable to pay benefits on time by July 1983. The assets of the DI Trust Fund, on the other hand, are expected to grow rapidly in both the short and long range. If the assets of both the OASI and DI Trust Funds were combined, however, the two funds would still become unable to pay benefits on time by the latter half of 1983, based on all four sets of economic and demographic assumptions in the 1982 report. Even if the temporary interfund borrowing authority in present law were extended, the combined assets of the OASI, DI, and HI Trust Funds would become insufficient to pay benefits on time by 1984, based on the two less favorable sets of assumptions in the 1982 report. Based on the other two, more favorable, sets of assumptions, the three combined funds could pay benefits on time through the 1980's but there would be little or no margin of safety to permit timely payment of benefits if economic conditions are even slightly less favorable.

Shear wave arrival time estimates correlate with local speckle pattern.

PubMed

Mcaleavey, Stephen A; Osapoetra, Laurentius O; Langdon, Jonathan

2015-12-01

We present simulation and phantom studies demonstrating a strong correlation between errors in shear wave arrival time estimates and the lateral position of the local speckle pattern in targets with fully developed speckle. We hypothesize that the observed arrival time variations are largely due to the underlying speckle pattern, and call the effect speckle bias. Arrival time estimation is a key step in quantitative shear wave elastography, performed by tracking tissue motion via cross-correlation of RF ultrasound echoes or similar methods. Variations in scatterer strength and interference of echoes from scatterers within the tracking beam result in an echo that does not necessarily describe the average motion within the beam, but one favoring areas of constructive interference and strong scattering. A swept-receive image, formed by fixing the transmit beam and sweeping the receive aperture over the region of interest, is used to estimate the local speckle pattern. Metrics for the lateral position of the speckle are found to correlate strongly (r > 0.7) with the estimated shear wave arrival times both in simulations and in phantoms. Lateral weighting of the swept-receive pattern improved the correlation between arrival time estimates and speckle position. The simulations indicate that high RF echo correlation does not equate to an accurate shear wave arrival time estimate-a high correlation coefficient indicates that motion is being tracked with high precision, but the location tracked is uncertain within the tracking beam width. The presence of a strong on-axis speckle is seen to imply high RF correlation and low bias. The converse does not appear to be true-highly correlated RF echoes can still produce biased arrival time estimates. The shear wave arrival time bias is relatively stable with variations in shear wave amplitude and sign (-20 μm to 20 μm simulated) compared with the variation with different speckle realizations obtained along a given tracking vector. We show that the arrival time bias is weakly dependent on shear wave amplitude compared with the variation with axial position/ local speckle pattern. Apertures of f/3 to f/8 on transmit and f/2 and f/4 on receive were simulated. Arrival time error and correlation with speckle pattern are most strongly determined by the receive aperture.

Shear Wave Arrival Time Estimates Correlate with Local Speckle Pattern

PubMed Central

McAleavey, Stephen A.; Osapoetra, Laurentius O.; Langdon, Jonathan

2016-01-01

We present simulation and phantom studies demonstrating a strong correlation between errors in shear wave arrival time estimates and the lateral position of the local speckle pattern in targets with fully developed speckle. We hypothesize that the observed arrival time variations are largely due to the underlying speckle pattern, and call the effect speckle bias. Arrival time estimation is a key step in quantitative shear wave elastography, performed by tracking tissue motion via cross correlation of RF ultrasound echoes or similar methods. Variations in scatterer strength and interference of echoes from scatterers within the tracking beam result in an echo that does not necessarily describe the average motion within the beam, but one favoring areas of constructive interference and strong scattering. A swept-receive image, formed by fixing the transmit beam and sweeping the receive aperture over the region of interest, is used to estimate the local speckle pattern. Metrics for the lateral position of the speckle are found to correlate strongly (r>0.7) with the estimated shear wave arrival times both in simulations and in phantoms. Lateral weighting of the swept-receive pattern improved the correlation between arrival time estimates and speckle position. The simulations indicate that high RF echo correlation does not equate to an accurate shear wave arrival time estimate – a high correlation coefficient indicates that motion is being tracked with high precision, but the location tracked is uncertain within the tracking beam width. The presence of a strong on-axis speckle is seen to imply high RF correlation and low bias. The converse does not appear to be true – highly correlated RF echoes can still produce biased arrival time estimates. The shear wave arrival time bias is relatively stable with variations in shear wave amplitude and sign (−20 μm to 20 μm simulated) compared to the variation with different speckle realizations obtained along a given tracking vector. We show that the arrival time bias is weakly dependent on shear wave amplitude compared to the variation with axial position/local speckle pattern. Apertures of f/3 to f/8 on transmit and f/2 and f/4 on receive were simulated. Arrival time error and correlation with speckle pattern are most strongly determined by the receive aperture. PMID:26670847

GPS constraints on M 7-8 earthquake recurrence times for the New Madrid seismic zone

USGS Publications Warehouse

Stuart, W.D.

2001-01-01

Newman et al. (1999) estimate the time interval between the 1811-1812 earthquake sequence near New Madrid, Missouri and a future similar sequence to be at least 2,500 years, an interval significantly longer than other recently published estimates. To calculate the recurrence time, they assume that slip on a vertical half-plane at depth contributes to the current interseismic motion of GPS benchmarks. Compared to other plausible fault models, the half-plane model gives nearly the maximum rate of ground motion for the same interseismic slip rate. Alternative models with smaller interseismic fault slip area can satisfy the present GPS data by having higher slip rate and thus can have earthquake recurrence times much less than 2,500 years.

CISN ShakeAlert: Accounting for site amplification effects and quantifying time and spatial dependence of uncertainty estimates in the Virtual Seismologist earthquake early warning algorithm

NASA Astrophysics Data System (ADS)

Caprio, M.; Cua, G. B.; Wiemer, S.; Fischer, M.; Heaton, T. H.; CISN EEW Team

2011-12-01

The Virtual Seismologist (VS) earthquake early warning (EEW) algorithm is one of 3 EEW approaches being incorporated into the California Integrated Seismic Network (CISN) ShakeAlert system, a prototype EEW system being tested in real-time in California. The VS algorithm, implemented by the Swiss Seismological Service at ETH Zurich, is a Bayesian approach to EEW, wherein the most probable source estimate at any given time is a combination of contributions from a likehihood function that evolves in response to incoming data from the on-going earthquake, and selected prior information, which can include factors such as network topology, the Gutenberg-Richter relationship or previously observed seismicity. The VS codes have been running in real-time at the Southern California Seismic Network (SCSN) since July 2008, and at the Northern California Seismic Network (NCSN) since February 2009. With the aim of improving the convergence of real-time VS magnitude estimates to network magnitudes, we evaluate various empirical and Vs30-based approaches to accounting for site amplification. Empirical station corrections for SCSN stations are derived from M>3.0 events from 2005 through 2009. We evaluate the performance of the various approaches using an independent 2010 dataset. In addition, we analyze real-time VS performance from 2008 to the present to quantify the time and spatial dependence of VS uncertainty estimates. We also summarize real-time VS performance for significant 2011 events in California. Improved magnitude and uncertainty estimates potentially increase the utility of EEW information for end-users, particularly those intending to automate damage-mitigating actions based on real-time information.

Estimating short-run and long-run interaction mechanisms in interictal state.

PubMed

Ozkaya, Ata; Korürek, Mehmet

2010-04-01

We address the issue of analyzing electroencephalogram (EEG) from seizure patients in order to test, model and determine the statistical properties that distinguish between EEG states (interictal, pre-ictal, ictal) by introducing a new class of time series analysis methods. In the present study: firstly, we employ statistical methods to determine the non-stationary behavior of focal interictal epileptiform series within very short time intervals; secondly, for such intervals that are deemed non-stationary we suggest the concept of Autoregressive Integrated Moving Average (ARIMA) process modelling, well known in time series analysis. We finally address the queries of causal relationships between epileptic states and between brain areas during epileptiform activity. We estimate the interaction between different EEG series (channels) in short time intervals by performing Granger-causality analysis and also estimate such interaction in long time intervals by employing Cointegration analysis, both analysis methods are well-known in econometrics. Here we find: first, that the causal relationship between neuronal assemblies can be identified according to the duration and the direction of their possible mutual influences; second, that although the estimated bidirectional causality in short time intervals yields that the neuronal ensembles positively affect each other, in long time intervals neither of them is affected (increasing amplitudes) from this relationship. Moreover, Cointegration analysis of the EEG series enables us to identify whether there is a causal link from the interictal state to ictal state.

The digital phase-locked loop as a near-optimum FM demodulator.

NASA Technical Reports Server (NTRS)

Kelly, C. N.; Gupta, S. C.

1972-01-01

This paper presents an approach to the optimum digital demodulation of a continuous-time FM signal using stochastic estimation theory. The primary result is a digital phase-locked loop realization possessing performance characteristics that approach those of the analog counterpart. Some practical considerations are presented and simulation results for a first-order message model are presented.

Development of flat conductor cable for commercial and residential wiring

NASA Technical Reports Server (NTRS)

Carden, J. R.

1977-01-01

The overall spectrum of the space technology spin-off development project: development of Flat Conductor Cable (FCC) for commercial and residential wiring, is presented. A discussion of the background, program milestones, industry participants, system outgrowth, hardware availability, cost estimates, and overall status of the program is presented for the 1970-to-present time period.

Evaluation of precipitation estimates over CONUS derived from satellite, radar, and rain gauge data sets at daily to annual scales (2002-2012)

NASA Astrophysics Data System (ADS)

Prat, O. P.; Nelson, B. R.

2015-04-01

We use a suite of quantitative precipitation estimates (QPEs) derived from satellite, radar, and surface observations to derive precipitation characteristics over the contiguous United States (CONUS) for the period 2002-2012. This comparison effort includes satellite multi-sensor data sets (bias-adjusted TMPA 3B42, near-real-time 3B42RT), radar estimates (NCEP Stage IV), and rain gauge observations. Remotely sensed precipitation data sets are compared with surface observations from the Global Historical Climatology Network-Daily (GHCN-D) and from the PRISM (Parameter-elevation Regressions on Independent Slopes Model). The comparisons are performed at the annual, seasonal, and daily scales over the River Forecast Centers (RFCs) for CONUS. Annual average rain rates present a satisfying agreement with GHCN-D for all products over CONUS (±6%). However, differences at the RFC are more important in particular for near-real-time 3B42RT precipitation estimates (-33 to +49%). At annual and seasonal scales, the bias-adjusted 3B42 presented important improvement when compared to its near-real-time counterpart 3B42RT. However, large biases remained for 3B42 over the western USA for higher average accumulation (≥ 5 mm day-1) with respect to GHCN-D surface observations. At the daily scale, 3B42RT performed poorly in capturing extreme daily precipitation (> 4 in. day-1) over the Pacific Northwest. Furthermore, the conditional analysis and a contingency analysis conducted illustrated the challenge in retrieving extreme precipitation from remote sensing estimates.

Analysing malaria drug trials on a per-individual or per-clone basis: a comparison of methods.

PubMed

Jaki, Thomas; Parry, Alice; Winter, Katherine; Hastings, Ian

2013-07-30

There are a variety of methods used to estimate the effectiveness of antimalarial drugs in clinical trials, invariably on a per-person basis. A person, however, may have more than one malaria infection present at the time of treatment. We evaluate currently used methods for analysing malaria trials on a per-individual basis and introduce a novel method to estimate the cure rate on a per-infection (clone) basis. We used simulated and real data to highlight the differences of the various methods. We give special attention to classifying outcomes as cured, recrudescent (infections that never fully cleared) or ambiguous on the basis of genetic markers at three loci. To estimate cure rates on a per-clone basis, we used the genetic information within an individual before treatment to determine the number of clones present. We used the genetic information obtained at the time of treatment failure to classify clones as recrudescence or new infections. On the per-individual level, we find that the most accurate methods of classification label an individual as newly infected if all alleles are different at the beginning and at the time of failure and as a recrudescence if all or some alleles were the same. The most appropriate analysis method is survival analysis or alternatively for complete data/per-protocol analysis a proportion estimate that treats new infections as successes. We show that the analysis of drug effectiveness on a per-clone basis estimates the cure rate accurately and allows more detailed evaluation of the performance of the treatment. Copyright © 2012 John Wiley & Sons, Ltd.

[Winter wheat area estimation with MODIS-NDVI time series based on parcel].

PubMed

Li, Le; Zhang, Jin-shui; Zhu, Wen-quan; Hu, Tan-gao; Hou, Dong

2011-05-01

Several attributes of MODIS (moderate resolution imaging spectrometer) data, especially the short temporal intervals and the global coverage, provide an extremely efficient way to map cropland and monitor its seasonal change. However, the reliability of their measurement results is challenged because of the limited spatial resolution. The parcel data has clear geo-location and obvious boundary information of cropland. Also, the spectral differences and the complexity of mixed pixels are weak in parcels. All of these make that area estimation based on parcels presents more advantage than on pixels. In the present study, winter wheat area estimation based on MODIS-NDVI time series has been performed with the support of cultivated land parcel in Tongzhou, Beijing. In order to extract the regional winter wheat acreage, multiple regression methods were used to simulate the stable regression relationship between MODIS-NDVI time series data and TM samples in parcels. Through this way, the consistency of the extraction results from MODIS and TM can stably reach up to 96% when the amount of samples accounts for 15% of the whole area. The results shows that the use of parcel data can effectively improve the error in recognition results in MODIS-NDVI based multi-series data caused by the low spatial resolution. Therefore, with combination of moderate and low resolution data, the winter wheat area estimation became available in large-scale region which lacks completed medium resolution images or has images covered with clouds. Meanwhile, it carried out the preliminary experiments for other crop area estimation.

Novel blood pressure and pulse pressure estimation based on pulse transit time and stroke volume approximation.

PubMed

Lee, Joonnyong; Sohn, JangJay; Park, Jonghyun; Yang, SeungMan; Lee, Saram; Kim, Hee Chan

2018-06-18

Non-invasive continuous blood pressure monitors are of great interest to the medical community due to their value in hypertension management. Recently, studies have shown the potential of pulse pressure as a therapeutic target for hypertension, but not enough attention has been given to non-invasive continuous monitoring of pulse pressure. Although accurate pulse pressure estimation can be of direct value to hypertension management and indirectly to the estimation of systolic blood pressure, as it is the sum of pulse pressure and diastolic blood pressure, only a few inadequate methods of pulse pressure estimation have been proposed. We present a novel, non-invasive blood pressure and pulse pressure estimation method based on pulse transit time and pre-ejection period. Pre-ejection period and pulse transit time were measured non-invasively using electrocardiogram, seismocardiogram, and photoplethysmogram measured from the torso. The proposed method used the 2-element Windkessel model to model pulse pressure with the ratio of stroke volume, approximated by pre-ejection period, and arterial compliance, estimated by pulse transit time. Diastolic blood pressure was estimated using pulse transit time, and systolic blood pressure was estimated as the sum of the two estimates. The estimation method was verified in 11 subjects in two separate conditions with induced cardiovascular response and the results were compared against a reference measurement and values obtained from a previously proposed method. The proposed method yielded high agreement with the reference (pulse pressure correlation with reference R ≥ 0.927, diastolic blood pressure correlation with reference R ≥ 0.854, systolic blood pressure correlation with reference R ≥ 0.914) and high estimation accuracy in pulse pressure (mean root-mean-squared error ≤ 3.46 mmHg) and blood pressure (mean root-mean-squared error ≤ 6.31 mmHg for diastolic blood pressure and ≤ 8.41 mmHg for systolic blood pressure) over a wide range of hemodynamic changes. The proposed pulse pressure estimation method provides accurate estimates in situations with and without significant changes in stroke volume. The proposed method improves upon the currently available systolic blood pressure estimation methods by providing accurate pulse pressure estimates.

Real-time reflectometry measurement validation in H-mode regimes for plasma position control.

PubMed

Santos, J; Guimarais, L; Manso, M

2010-10-01

It has been shown that in H-mode regimes, reflectometry electron density profiles and an estimate for the density at the separatrix can be jointly used to track the separatrix within the precision required for plasma position control on ITER. We present a method to automatically remove, from the position estimation procedure, measurements performed during collapse and recovery phases of edge localized modes (ELMs). Based on the rejection mechanism, the method also produces an estimate confidence value to be fed to the position feedback controller. Preliminary results show that the method improves the real-time experimental separatrix tracking capabilities and has the potential to eliminate the need for an external online source of ELM event signaling during control feedback operation.

Fast state estimation subject to random data loss in discrete-time nonlinear stochastic systems

NASA Astrophysics Data System (ADS)

Mahdi Alavi, S. M.; Saif, Mehrdad

2013-12-01

This paper focuses on the design of the standard observer in discrete-time nonlinear stochastic systems subject to random data loss. By the assumption that the system response is incrementally bounded, two sufficient conditions are subsequently derived that guarantee exponential mean-square stability and fast convergence of the estimation error for the problem at hand. An efficient algorithm is also presented to obtain the observer gain. Finally, the proposed methodology is employed for monitoring the Continuous Stirred Tank Reactor (CSTR) via a wireless communication network. The effectiveness of the designed observer is extensively assessed by using an experimental tested-bed that has been fabricated for performance evaluation of the over wireless-network estimation techniques under realistic radio channel conditions.

Re-visiting the Amplifier Gains of the HST/ACS Wide Field Channel CCDs

NASA Astrophysics Data System (ADS)

Desjardins, Tyler D.; Grogin, Norman A.; ACS Team

2018-06-01

For the first time since HST Servicing Mission 4 (SM4) in May 2009, we present an analysis of the amplifier gains of the Advanced Camera for Surveys (ACS) Wide Field Channel (WFC) CCDs. Using a series of in-flight flat-field exposures taken in November 2017 with a tungsten calibration lamp, we utilize the photon transfer method to estimate the gains of the WFC1 and WFC2 CCD amplifiers. We find evidence that the gains of the four readout amplifiers have changed by a small, but statistically significant, 1–2% since SM4. We further present a study of historical ACS/WFC observations of the globular cluster NGC 104 (47 Tuc) in an attempt to estimate the time dependence of the gains.

Evaluating the performance of real-time streamflow forecasting using multi-satellite precipitation products in the Upper Zambezi, Africa

NASA Astrophysics Data System (ADS)

Demaria, E. M.; Valdes, J. B.; Wi, S.; Serrat-Capdevila, A.; Valdés-Pineda, R.; Durcik, M.

2016-12-01

In under-instrumented basins around the world, accurate and timely forecasts of river streamflows have the potential of assisting water and natural resource managers in their management decisions. The Upper Zambezi river basin is the largest basin in southern Africa and its water resources are critical to sustainable economic growth and poverty reduction in eight riparian countries. We present a real-time streamflow forecast for the basin using a multi-model-multi-satellite approach that allows accounting for model and input uncertainties. Three distributed hydrologic models with different levels of complexity: VIC, HYMOD_DS, and HBV_DS are setup at a daily time step and a 0.25 degree spatial resolution for the basin. The hydrologic models are calibrated against daily observed streamflows at the Katima-Mulilo station using a Genetic Algorithm. Three real-time satellite products: Climate Prediction Center's morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and Tropical Rainfall Measuring Mission (TRMM-3B42RT) are bias-corrected with daily CHIRPS estimates. Uncertainty bounds for predicted flows are estimated with the Inverse Variance Weighting method. Because concentration times in the basin range from a few days to more than a week, we include the use of precipitation forecasts from the Global Forecasting System (GFS) to predict daily streamflows in the basin with a 10-days lead time. The skill of GFS-predicted streamflows is evaluated and the usefulness of the forecasts for short term water allocations is presented.

Targeted Maximum Likelihood Estimation for Dynamic and Static Longitudinal Marginal Structural Working Models

PubMed Central

Schwab, Joshua; Gruber, Susan; Blaser, Nello; Schomaker, Michael; van der Laan, Mark

2015-01-01

This paper describes a targeted maximum likelihood estimator (TMLE) for the parameters of longitudinal static and dynamic marginal structural models. We consider a longitudinal data structure consisting of baseline covariates, time-dependent intervention nodes, intermediate time-dependent covariates, and a possibly time-dependent outcome. The intervention nodes at each time point can include a binary treatment as well as a right-censoring indicator. Given a class of dynamic or static interventions, a marginal structural model is used to model the mean of the intervention-specific counterfactual outcome as a function of the intervention, time point, and possibly a subset of baseline covariates. Because the true shape of this function is rarely known, the marginal structural model is used as a working model. The causal quantity of interest is defined as the projection of the true function onto this working model. Iterated conditional expectation double robust estimators for marginal structural model parameters were previously proposed by Robins (2000, 2002) and Bang and Robins (2005). Here we build on this work and present a pooled TMLE for the parameters of marginal structural working models. We compare this pooled estimator to a stratified TMLE (Schnitzer et al. 2014) that is based on estimating the intervention-specific mean separately for each intervention of interest. The performance of the pooled TMLE is compared to the performance of the stratified TMLE and the performance of inverse probability weighted (IPW) estimators using simulations. Concepts are illustrated using an example in which the aim is to estimate the causal effect of delayed switch following immunological failure of first line antiretroviral therapy among HIV-infected patients. Data from the International Epidemiological Databases to Evaluate AIDS, Southern Africa are analyzed to investigate this question using both TML and IPW estimators. Our results demonstrate practical advantages of the pooled TMLE over an IPW estimator for working marginal structural models for survival, as well as cases in which the pooled TMLE is superior to its stratified counterpart. PMID:25909047

Tracking the time-varying cortical connectivity patterns by adaptive multivariate estimators.

PubMed

Astolfi, L; Cincotti, F; Mattia, D; De Vico Fallani, F; Tocci, A; Colosimo, A; Salinari, S; Marciani, M G; Hesse, W; Witte, H; Ursino, M; Zavaglia, M; Babiloni, F

2008-03-01

The directed transfer function (DTF) and the partial directed coherence (PDC) are frequency-domain estimators that are able to describe interactions between cortical areas in terms of the concept of Granger causality. However, the classical estimation of these methods is based on the multivariate autoregressive modelling (MVAR) of time series, which requires the stationarity of the signals. In this way, transient pathways of information transfer remains hidden. The objective of this study is to test a time-varying multivariate method for the estimation of rapidly changing connectivity relationships between cortical areas of the human brain, based on DTF/PDC and on the use of adaptive MVAR modelling (AMVAR) and to apply it to a set of real high resolution EEG data. This approach will allow the observation of rapidly changing influences between the cortical areas during the execution of a task. The simulation results indicated that time-varying DTF and PDC are able to estimate correctly the imposed connectivity patterns under reasonable operative conditions of signal-to-noise ratio (SNR) ad number of trials. An SNR of five and a number of trials of at least 20 provide a good accuracy in the estimation. After testing the method by the simulation study, we provide an application to the cortical estimations obtained from high resolution EEG data recorded from a group of healthy subject during a combined foot-lips movement and present the time-varying connectivity patterns resulting from the application of both DTF and PDC. Two different cortical networks were detected with the proposed methods, one constant across the task and the other evolving during the preparation of the joint movement.

A complex permittivity model for field estimation of soil water contents using time domain reflectometry

USDA-ARS?s Scientific Manuscript database

Accurate electromagnetic sensing of soil water contents (') under field conditions is complicated by the dependence of permittivity on specific surface area, temperature, and apparent electrical conductivity, all which may vary across space or time. We present a physically-based mixing model to pred...

Neuromorphic Event-Based 3D Pose Estimation

PubMed Central

Reverter Valeiras, David; Orchard, Garrick; Ieng, Sio-Hoi; Benosman, Ryad B.

2016-01-01

Pose estimation is a fundamental step in many artificial vision tasks. It consists of estimating the 3D pose of an object with respect to a camera from the object's 2D projection. Current state of the art implementations operate on images. These implementations are computationally expensive, especially for real-time applications. Scenes with fast dynamics exceeding 30–60 Hz can rarely be processed in real-time using conventional hardware. This paper presents a new method for event-based 3D object pose estimation, making full use of the high temporal resolution (1 μs) of asynchronous visual events output from a single neuromorphic camera. Given an initial estimate of the pose, each incoming event is used to update the pose by combining both 3D and 2D criteria. We show that the asynchronous high temporal resolution of the neuromorphic camera allows us to solve the problem in an incremental manner, achieving real-time performance at an update rate of several hundreds kHz on a conventional laptop. We show that the high temporal resolution of neuromorphic cameras is a key feature for performing accurate pose estimation. Experiments are provided showing the performance of the algorithm on real data, including fast moving objects, occlusions, and cases where the neuromorphic camera and the object are both in motion. PMID:26834547

Optimization and experimental validation of a thermal cycle that maximizes entropy coefficient fisher identifiability for lithium iron phosphate cells

NASA Astrophysics Data System (ADS)

Mendoza, Sergio; Rothenberger, Michael; Hake, Alison; Fathy, Hosam

2016-03-01

This article presents a framework for optimizing the thermal cycle to estimate a battery cell's entropy coefficient at 20% state of charge (SOC). Our goal is to maximize Fisher identifiability: a measure of the accuracy with which a parameter can be estimated. Existing protocols in the literature for estimating entropy coefficients demand excessive laboratory time. Identifiability optimization makes it possible to achieve comparable accuracy levels in a fraction of the time. This article demonstrates this result for a set of lithium iron phosphate (LFP) cells. We conduct a 24-h experiment to obtain benchmark measurements of their entropy coefficients. We optimize a thermal cycle to maximize parameter identifiability for these cells. This optimization proceeds with respect to the coefficients of a Fourier discretization of this thermal cycle. Finally, we compare the estimated parameters using (i) the benchmark test, (ii) the optimized protocol, and (iii) a 15-h test from the literature (by Forgez et al.). The results are encouraging for two reasons. First, they confirm the simulation-based prediction that the optimized experiment can produce accurate parameter estimates in 2 h, compared to 15-24. Second, the optimized experiment also estimates a thermal time constant representing the effects of thermal capacitance and convection heat transfer.

Decentralized Observer with a Consensus Filter for Distributed Discrete-Time Linear Systems

NASA Technical Reports Server (NTRS)

Acikmese, Behcet; Mandic, Milan

2011-01-01

This paper presents a decentralized observer with a consensus filter for the state observation of a discrete-time linear distributed systems. In this setup, each agent in the distributed system has an observer with a model of the plant that utilizes the set of locally available measurements, which may not make the full plant state detectable. This lack of detectability is overcome by utilizing a consensus filter that blends the state estimate of each agent with its neighbors' estimates. We assume that the communication graph is connected for all times as well as the sensing graph. It is proven that the state estimates of the proposed observer asymptotically converge to the actual plant states under arbitrarily changing, but connected, communication and sensing topologies. As a byproduct of this research, we also obtained a result on the location of eigenvalues, the spectrum, of the Laplacian for a family of graphs with self-loops.

The validity of birth and pregnancy histories in rural Bangladesh.

PubMed

Espeut, Donna; Becker, Stan

2015-08-28

Maternity histories provide a means of estimating fertility and mortality from surveys. The present analysis compares two types of maternity histories-birth histories and pregnancy histories-in three respects: (1) completeness of live birth and infant death reporting; (2) accuracy of the time placement of live births and infant deaths; and (3) the degree to which reported versus actual total fertility measures differ. The analysis covers a 15-year time span and is based on two data sources from Matlab, Bangladesh: the 1994 Matlab Demographic and Health Survey and, as gold standard, the vital events data from Matlab's Demographic Surveillance System. Both histories are near perfect in live-birth completeness; however, pregnancy histories do better in the completeness and time accuracy of deaths during the first year of life. Birth or pregnancy histories can be used for fertility estimation, but pregnancy histories are advised for estimating infant mortality.

Hazard Function Estimation with Cause-of-Death Data Missing at Random

PubMed Central

Wang, Qihua; Dinse, Gregg E.; Liu, Chunling

2010-01-01

Hazard function estimation is an important part of survival analysis. Interest often centers on estimating the hazard function associated with a particular cause of death. We propose three nonparametric kernel estimators for the hazard function, all of which are appropriate when death times are subject to random censorship and censoring indicators can be missing at random. Specifically, we present a regression surrogate estimator, an imputation estimator, and an inverse probability weighted estimator. All three estimators are uniformly strongly consistent and asymptotically normal. We derive asymptotic representations of the mean squared error and the mean integrated squared error for these estimators and we discuss a data-driven bandwidth selection method. A simulation study, conducted to assess finite sample behavior, demonstrates that the proposed hazard estimators perform relatively well. We illustrate our methods with an analysis of some vascular disease data. PMID:22267874

On the more accurate channel model and positioning based on time-of-arrival for visible light localization

NASA Astrophysics Data System (ADS)

Amini, Changeez; Taherpour, Abbas; Khattab, Tamer; Gazor, Saeed

2017-01-01

This paper presents an improved propagation channel model for the visible light in indoor environments. We employ this model to derive an enhanced positioning algorithm using on the relation between the time-of-arrivals (TOAs) and the distances for two cases either by assuming known or unknown transmitter and receiver vertical distances. We propose two estimators, namely the maximum likelihood estimator and an estimator by employing the method of moments. To have an evaluation basis for these methods, we calculate the Cramer-Rao lower bound (CRLB) for the performance of the estimations. We show that the proposed model and estimations result in a superior performance in positioning when the transmitter and receiver are perfectly synchronized in comparison to the existing state-of-the-art counterparts. Moreover, the corresponding CRLB of the proposed model represents almost about 20 dB reduction in the localization error bound in comparison with the previous model for some practical scenarios.

Waveform Optimization for Target Estimation by Cognitive Radar with Multiple Antennas.

PubMed

Yao, Yu; Zhao, Junhui; Wu, Lenan

2018-05-29

A new scheme based on Kalman filtering to optimize the waveforms of an adaptive multi-antenna radar system for target impulse response (TIR) estimation is presented. This work aims to improve the performance of TIR estimation by making use of the temporal correlation between successive received signals, and minimize the mean square error (MSE) of TIR estimation. The waveform design approach is based upon constant learning from the target feature at the receiver. Under the multiple antennas scenario, a dynamic feedback loop control system is established to real-time monitor the change in the target features extracted form received signals. The transmitter adapts its transmitted waveform to suit the time-invariant environment. Finally, the simulation results show that, as compared with the waveform design method based on the MAP criterion, the proposed waveform design algorithm is able to improve the performance of TIR estimation for extended targets with multiple iterations, and has a relatively lower level of complexity.

Multifractals embedded in short time series: An unbiased estimation of probability moment

NASA Astrophysics Data System (ADS)

Qiu, Lu; Yang, Tianguang; Yin, Yanhua; Gu, Changgui; Yang, Huijie

2016-12-01

An exact estimation of probability moments is the base for several essential concepts, such as the multifractals, the Tsallis entropy, and the transfer entropy. By means of approximation theory we propose a new method called factorial-moment-based estimation of probability moments. Theoretical prediction and computational results show that it can provide us an unbiased estimation of the probability moments of continuous order. Calculations on probability redistribution model verify that it can extract exactly multifractal behaviors from several hundred recordings. Its powerfulness in monitoring evolution of scaling behaviors is exemplified by two empirical cases, i.e., the gait time series for fast, normal, and slow trials of a healthy volunteer, and the closing price series for Shanghai stock market. By using short time series with several hundred lengths, a comparison with the well-established tools displays significant advantages of its performance over the other methods. The factorial-moment-based estimation can evaluate correctly the scaling behaviors in a scale range about three generations wider than the multifractal detrended fluctuation analysis and the basic estimation. The estimation of partition function given by the wavelet transform modulus maxima has unacceptable fluctuations. Besides the scaling invariance focused in the present paper, the proposed factorial moment of continuous order can find its various uses, such as finding nonextensive behaviors of a complex system and reconstructing the causality relationship network between elements of a complex system.

Stochastic modeling for time series InSAR: with emphasis on atmospheric effects

NASA Astrophysics Data System (ADS)

Cao, Yunmeng; Li, Zhiwei; Wei, Jianchao; Hu, Jun; Duan, Meng; Feng, Guangcai

2018-02-01

Despite the many applications of time series interferometric synthetic aperture radar (TS-InSAR) techniques in geophysical problems, error analysis and assessment have been largely overlooked. Tropospheric propagation error is still the dominant error source of InSAR observations. However, the spatiotemporal variation of atmospheric effects is seldom considered in the present standard TS-InSAR techniques, such as persistent scatterer interferometry and small baseline subset interferometry. The failure to consider the stochastic properties of atmospheric effects not only affects the accuracy of the estimators, but also makes it difficult to assess the uncertainty of the final geophysical results. To address this issue, this paper proposes a network-based variance-covariance estimation method to model the spatiotemporal variation of tropospheric signals, and to estimate the temporal variance-covariance matrix of TS-InSAR observations. The constructed stochastic model is then incorporated into the TS-InSAR estimators both for parameters (e.g., deformation velocity, topography residual) estimation and uncertainty assessment. It is an incremental and positive improvement to the traditional weighted least squares methods to solve the multitemporal InSAR time series. The performance of the proposed method is validated by using both simulated and real datasets.

Application of wavelet-based multi-model Kalman filters to real-time flood forecasting

NASA Astrophysics Data System (ADS)

Chou, Chien-Ming; Wang, Ru-Yih

2004-04-01

This paper presents the application of a multimodel method using a wavelet-based Kalman filter (WKF) bank to simultaneously estimate decomposed state variables and unknown parameters for real-time flood forecasting. Applying the Haar wavelet transform alters the state vector and input vector of the state space. In this way, an overall detail plus approximation describes each new state vector and input vector, which allows the WKF to simultaneously estimate and decompose state variables. The wavelet-based multimodel Kalman filter (WMKF) is a multimodel Kalman filter (MKF), in which the Kalman filter has been substituted for a WKF. The WMKF then obtains M estimated state vectors. Next, the M state-estimates, each of which is weighted by its possibility that is also determined on-line, are combined to form an optimal estimate. Validations conducted for the Wu-Tu watershed, a small watershed in Taiwan, have demonstrated that the method is effective because of the decomposition of wavelet transform, the adaptation of the time-varying Kalman filter and the characteristics of the multimodel method. Validation results also reveal that the resulting method enhances the accuracy of the runoff prediction of the rainfall-runoff process in the Wu-Tu watershed.

Menu driven heat treatment control of thin walled bodies

DOEpatents

Kothmann, Richard E.; Booth, Jr., Russell R.; Grimm, Noel P.; Batenburg, Abram; Thomas, Vaughn M.

1992-01-01

A process for controlling the heating of a thin-walled body according to a predetermined temperature program by means of electrically controllable heaters, comprising: disposing the heaters adjacent one surface of the body such that each heater is in facing relation with a respective zone of the surface; supplying heat-generating power to each heater and monitoring the temperature at each surface zone; and for each zone: deriving (16,18,20), on the basis of the temperature values obtained in the monitoring step, estimated temperature values of the surface at successive time intervals each having a first selected duration; generating (28), on the basis of the estimated temperature values derived in each time interval, representations of the temperature, THSIFUT, which each surface zone will have, based on the level of power presently supplied to each heater, at a future time which is separated from the present time interval by a second selected duration; determining (30) the difference between THSIFUT and the desired temperature, FUTREFTVZL, at the future time which is separated from the present time interval by the second selected duration; providing (52) a representation indicating the power level which sould be supplied to each heater in order to reduce the difference obtained in the determining step; and adjusting the power level supplied to each heater by the supplying step in response to the value of the representation provided in the providing step.

Multiple-taper spectral analysis: A stand-alone C-subroutine

NASA Astrophysics Data System (ADS)

Lees, Jonathan M.; Park, Jeffrey

1995-03-01

A simple set of subroutines in ANSI-C are presented for multiple taper spectrum estimation. The multitaper approach provides an optimal spectrum estimate by minimizing spectral leakage while reducing the variance of the estimate by averaging orthogonal eigenspectrum estimates. The orthogonal tapers are Slepian nπ prolate functions used as tapers on the windowed time series. Because the taper functions are orthogonal, combining them to achieve an average spectrum does not introduce spurious correlations as standard smoothed single-taper estimates do. Furthermore, estimates of the degrees of freedom and F-test values at each frequency provide diagnostics for determining levels of confidence in narrow band (single frequency) periodicities. The program provided is portable and has been tested on both Unix and Macintosh systems.

Groundwater Change in Storage Estimation by Using Monitoring Wells Data

NASA Astrophysics Data System (ADS)

Flores, C. I.

2016-12-01

In present times, remarkable attention is being given to models and data in hydrology, regarding their role in meeting water management requirements to enable well-informed decisions. Water management under the Sustainable Groundwater Management Act (SGMA) is currently challenging, due to it requires that groundwater sustainability agencies (GSAs) formulate groundwater sustainability plans (GSPs) to comply with new regulations and perform a responsible management to secure California's groundwater resources, particularly when droughts and climate change conditions are present. In this scenario, water budgets and change in groundwater storage estimations are key components for decision makers, but their computation is often difficult, lengthy and uncertain. Therefore, this work presents an innovative approach to integrate hydrologic modeling and available groundwater data into a single simplified tool, a proxy function, that estimate in real time the change in storage based on monitoring wells data. A hydrologic model was developed and calibrated for water years 1970 to 2015, the Yolo County IWFM, which was applied to generate the proxy as a study case, by regressing simulated change in storage versus change in head for the cities of Davis and Woodland area, and obtain a linear function dependent on heads variations over time. Later, the proxy was applied to actual groundwater data in this region to predict the change in storage. Results from this work provide proxy functions to approximate change in storage based on monitoring data for daily, monthly and yearly frameworks, being as well easily transferable to any spreadsheet or database to perform simply yet crucial computations in real time for sustainable groundwater management.

Spatiotemporal interpolation of discharge across a river network by using synthetic SWOT satellite data

NASA Astrophysics Data System (ADS)

Paiva, Rodrigo C. D.; Durand, Michael T.; Hossain, Faisal

2015-01-01

Recent efforts have sought to estimate river discharge and other surface water-related quantities using spaceborne sensors, with better spatial coverage but worse temporal sampling as compared with in situ measurements. The Surface Water and Ocean Topography (SWOT) mission will provide river discharge estimates globally from space. However, questions on how to optimally use the spatially distributed but asynchronous satellite observations to generate continuous fields still exist. This paper presents a statistical model (River Kriging-RK), for estimating discharge time series in a river network in the context of the SWOT mission. RK uses discharge estimates at different locations and times to produce a continuous field using spatiotemporal kriging. A key component of RK is the space-time river discharge covariance, which was derived analytically from the diffusive wave approximation of Saint Venant's equations. The RK covariance also accounts for the loss of correlation at confluences. The model performed well in a case study on Ganges-Brahmaputra-Meghna (GBM) River system in Bangladesh using synthetic SWOT observations. The correlation model reproduced empirically derived values. RK (R2=0.83) outperformed other kriging-based methods (R2=0.80), as well as a simple time series linear interpolation (R2=0.72). RK was used to combine discharge from SWOT and in situ observations, improving estimates when the latter is included (R2=0.91). The proposed statistical concepts may eventually provide a feasible framework to estimate continuous discharge time series across a river network based on SWOT data, other altimetry missions, and/or in situ data.

Comprehensive Evaluation of Attitude and Orbit Estimation Using Actual Earth Magnetic Field Data

NASA Technical Reports Server (NTRS)

Deutschmann, Julie K.; Bar-Itzhack, Itzhack Y.

2000-01-01

A single, augmented Extended Kalman Filter (EKF), which simultaneously and autonomously estimates spacecraft attitude and orbit has been developed and successfully tested with real magnetometer and gyro data only. Because the earth magnetic field is a function of time and position, and because time is known quite precisely, the differences between the computed and measured magnetic field components, as measured by the magnetometers throughout the entire spacecraft orbit, are a function of both orbit and attitude errors. Thus, conceivably these differences could be used to estimate both orbit and attitude; an observability study validated this assumption. The results of testing the EKF with actual magnetometer and gyro data, from four satellites supported by the NASA Goddard Space Flight Center (GSFC) Guidance, Navigation, and Control Center, are presented and evaluated. They confirm the assumption that a single EKF can estimate both attitude and orbit when using gyros and magnetometers only.

Estimating Photosynthetically Available Radiation (PAR) at the Earth's surface from satellite observations

NASA Technical Reports Server (NTRS)

Frouin, Robert

1993-01-01

Current satellite algorithms to estimate photosynthetically available radiation (PAR) at the earth' s surface are reviewed. PAR is deduced either from an insolation estimate or obtained directly from top-of-atmosphere solar radiances. The characteristics of both approaches are contrasted and typical results are presented. The inaccuracies reported, about 10 percent and 6 percent on daily and monthly time scales, respectively, are useful to model oceanic and terrestrial primary productivity. At those time scales variability due to clouds in the ratio of PAR and insolation is reduced, making it possible to deduce PAR directly from insolation climatologies (satellite or other) that are currently available or being produced. Improvements, however, are needed in conditions of broken cloudiness and over ice/snow. If not addressed properly, calibration/validation issues may prevent quantitative use of the PAR estimates in studies of climatic change. The prospects are good for an accurate, long-term climatology of PAR over the globe.

deltaGseg: macrostate estimation via molecular dynamics simulations and multiscale time series analysis.

PubMed

Low, Diana H P; Motakis, Efthymios

2013-10-01

Binding free energy calculations obtained through molecular dynamics simulations reflect intermolecular interaction states through a series of independent snapshots. Typically, the free energies of multiple simulated series (each with slightly different starting conditions) need to be estimated. Previous approaches carry out this task by moving averages at certain decorrelation times, assuming that the system comes from a single conformation description of binding events. Here, we discuss a more general approach that uses statistical modeling, wavelets denoising and hierarchical clustering to estimate the significance of multiple statistically distinct subpopulations, reflecting potential macrostates of the system. We present the deltaGseg R package that performs macrostate estimation from multiple replicated series and allows molecular biologists/chemists to gain physical insight into the molecular details that are not easily accessible by experimental techniques. deltaGseg is a Bioconductor R package available at http://bioconductor.org/packages/release/bioc/html/deltaGseg.html.

Providing long-term trend and gravimetric factor at Chandler period from superconducting gravimeter records by using Singular Spectrum Analysis along with its multivariate extension

NASA Astrophysics Data System (ADS)

Gruszczynska, M.; Rosat, S.; Klos, A.; Bogusz, J.

2017-12-01

In this study, Singular Spectrum Analysis (SSA) along with its multivariate extension MSSA (Multichannel SSA) were used to estimate long-term trend and gravimetric factor at the Chandler wobble frequency from superconducting gravimeter (SG) records. We have used data from seven stations located worldwide and contributing to the International Geodynamics and Earth Tides Service (IGETS). The timespan ranged from 15 to 19 years. Before applying SSA and MSSA, we had removed local tides, atmospheric (ECMWF data), hydrological (MERRA2 products) loadings and non-tidal ocean loading (ECCO2 products) effects. In the first part of analysis, we used the SSA approach in order to estimate the long-term trends from SG observations. We use the technique based on the classical Karhunen-Loève spectral decomposition of time series into long-term trend, oscillations and noise. In the second part, we present the determination of common time-varying pole tide (annual and Chandler wobble) to estimate gravimetric factor from SG time series using the MSSA approach. The presented method takes advantage over traditional methods like Least Squares Estimation by determining common modes of variability which reflect common geophysical field. We adopted a 6-year lag-window as the optimal length to extract common seasonal signals and the Chandler components of the Earth polar motion. The signals characterized by annual and Chandler wobble account for approximately 62% of the total variance of residual SG data. Then, we estimated the amplitude factors and phase lags of Chandler wobble with respect to the IERS (International Earth Rotation and Reference Systems Service) polar motion observations. The resulting gravimetric factors at the Chandler Wobble period are finally compared with previously estimates. A robust estimate of the gravimetric Earth response to the Chandlerian component of the polar motion is required to better constrain the mantle anelasticity at this frequency and hence the attenuation models of the Earth interior.

Born iterative reconstruction using perturbed-phase field estimates.

PubMed

Astheimer, Jeffrey P; Waag, Robert C

2008-10-01

A method of image reconstruction from scattering measurements for use in ultrasonic imaging is presented. The method employs distorted-wave Born iteration but does not require using a forward-problem solver or solving large systems of equations. These calculations are avoided by limiting intermediate estimates of medium variations to smooth functions in which the propagated fields can be approximated by phase perturbations derived from variations in a geometric path along rays. The reconstruction itself is formed by a modification of the filtered-backpropagation formula that includes correction terms to account for propagation through an estimated background. Numerical studies that validate the method for parameter ranges of interest in medical applications are presented. The efficiency of this method offers the possibility of real-time imaging from scattering measurements.

Comparison of Statistical Approaches Dealing with Time-dependent Confounding in Drug Effectiveness Studies

PubMed Central

Karim, Mohammad Ehsanul; Petkau, John; Gustafson, Paul; Platt, Robert W.; Tremlett, Helen

2017-01-01

In longitudinal studies, if the time-dependent covariates are affected by the past treatment, time-dependent confounding may be present. For a time-to-event response, marginal structural Cox models (MSCMs) are frequently used to deal with such confounding. To avoid some of the problems of fitting MSCM, the sequential Cox approach has been suggested as an alternative. Although the estimation mechanisms are different, both approaches claim to estimate the causal effect of treatment by appropriately adjusting for time-dependent confounding. We carry out simulation studies to assess the suitability of the sequential Cox approach for analyzing time-to-event data in the presence of a time-dependent covariate that may or may not be a time-dependent confounder. Results from these simulations revealed that the sequential Cox approach is not as effective as MSCM in addressing the time-dependent confounding. The sequential Cox approach was also found to be inadequate in the presence of a time-dependent covariate. We propose a modified version of the sequential Cox approach that correctly estimates the treatment effect in both of the above scenarios. All approaches are applied to investigate the impact of beta-interferon treatment in delaying disability progression in the British Columbia Multiple Sclerosis cohort (1995 – 2008). PMID:27659168

Comparison of statistical approaches dealing with time-dependent confounding in drug effectiveness studies.

PubMed

Karim, Mohammad Ehsanul; Petkau, John; Gustafson, Paul; Platt, Robert W; Tremlett, Helen

2018-06-01

In longitudinal studies, if the time-dependent covariates are affected by the past treatment, time-dependent confounding may be present. For a time-to-event response, marginal structural Cox models are frequently used to deal with such confounding. To avoid some of the problems of fitting marginal structural Cox model, the sequential Cox approach has been suggested as an alternative. Although the estimation mechanisms are different, both approaches claim to estimate the causal effect of treatment by appropriately adjusting for time-dependent confounding. We carry out simulation studies to assess the suitability of the sequential Cox approach for analyzing time-to-event data in the presence of a time-dependent covariate that may or may not be a time-dependent confounder. Results from these simulations revealed that the sequential Cox approach is not as effective as marginal structural Cox model in addressing the time-dependent confounding. The sequential Cox approach was also found to be inadequate in the presence of a time-dependent covariate. We propose a modified version of the sequential Cox approach that correctly estimates the treatment effect in both of the above scenarios. All approaches are applied to investigate the impact of beta-interferon treatment in delaying disability progression in the British Columbia Multiple Sclerosis cohort (1995-2008).

Decadal GPS Time Series and Velocity Fields Spanning the North American Continent and Beyond: New Data Products, Cyberinfrastructure and Case Studies from the EarthScope Plate Boundary Observatory (PBO) and Other Regional Networks

NASA Astrophysics Data System (ADS)

Phillips, D. A.; Herring, T.; Melbourne, T. I.; Murray, M. H.; Szeliga, W. M.; Floyd, M.; Puskas, C. M.; King, R. W.; Boler, F. M.; Meertens, C. M.; Mattioli, G. S.

2017-12-01

The Geodesy Advancing Geosciences and EarthScope (GAGE) Facility, operated by UNAVCO, provides a diverse suite of geodetic data, derived products and cyberinfrastructure services to support community Earth science research and education. GPS data and products including decadal station position time series and velocities are provided for 2000+ continuous GPS stations from the Plate Boundary Observatory (PBO) and other networks distributed throughout the high Arctic, North America, and Caribbean regions. The position time series contain a multitude of signals in addition to the secular motions, including coseismic and postseismic displacements, interseismic strain accumulation, and transient signals associated with hydrologic and other processes. We present our latest velocity field solutions, new time series offset estimate products, and new time series examples associated with various phenomena. Position time series, and the signals they contain, are inherently dependent upon analysis parameters such as network scaling and reference frame realization. The estimation of scale changes for example, a common practice, has large impacts on vertical motion estimates. GAGE/PBO velocities and time series are currently provided in IGS (IGb08) and North America (NAM08, IGb08 rotated to a fixed North America Plate) reference frames. We are reprocessing all data (1996 to present) as part of the transition from IGb08 to IGS14 that began in 2017. New NAM14 and IGS14 data products are discussed. GAGE/PBO GPS data products are currently generated using onsite computing clusters. As part of an NSF funded EarthCube Building Blocks project called "Deploying MultiFacility Cyberinfrastructure in Commercial and Private Cloud-based Systems (GeoSciCloud)", we are investigating performance, cost, and efficiency differences between local computing resources and cloud based resources. Test environments include a commercial cloud provider (Amazon/AWS), NSF cloud-like infrastructures within XSEDE (TACC, the Texas Advanced Computing Center), and in-house cyberinfrastructures. Preliminary findings from this effort are presented. Web services developed by UNAVCO to facilitate the discovery, customization and dissemination of GPS data and products are also presented.

Indirectly estimated absolute lung cancer mortality rates by smoking status and histological type based on a systematic review

PubMed Central

2013-01-01

Background National smoking-specific lung cancer mortality rates are unavailable, and studies presenting estimates are limited, particularly by histology. This hinders interpretation. We attempted to rectify this by deriving estimates indirectly, combining data from national rates and epidemiological studies. Methods We estimated study-specific absolute mortality rates and variances by histology and smoking habit (never/ever/current/former) based on relative risk estimates derived from studies published in the 20th century, coupled with WHO mortality data for age 70–74 for the relevant country and period. Studies with populations grossly unrepresentative nationally were excluded. 70–74 was chosen based on analyses of large cohort studies presenting rates by smoking and age. Variations by sex, period and region were assessed by meta-analysis and meta-regression. Results 148 studies provided estimates (Europe 59, America 54, China 22, other Asia 13), 54 providing estimates by histology (squamous cell carcinoma, adenocarcinoma). For all smoking habits and lung cancer types, mortality rates were higher in males, the excess less evident for never smokers. Never smoker rates were clearly highest in China, and showed some increasing time trend, particularly for adenocarcinoma. Ever smoker rates were higher in parts of Europe and America than in China, with the time trend very clear, especially for adenocarcinoma. Variations by time trend and continent were clear for current smokers (rates being higher in Europe and America than Asia), but less clear for former smokers. Models involving continent and trend explained much variability, but non-linearity was sometimes seen (with rates lower in 1991–99 than 1981–90), and there was regional variation within continent (with rates in Europe often high in UK and low in Scandinavia, and higher in North than South America). Conclusions The indirect method may be questioned, because of variations in definition of smoking and lung cancer type in the epidemiological database, changes over time in diagnosis of lung cancer types, lack of national representativeness of some studies, and regional variation in smoking misclassification. However, the results seem consistent with the literature, and provide additional information on variability by time and region, including evidence of a rise in never smoker adenocarcinoma rates relative to squamous cell carcinoma rates. PMID:23570286

rpsftm: An R Package for Rank Preserving Structural Failure Time Models

PubMed Central

Allison, Annabel; White, Ian R; Bond, Simon

2018-01-01

Treatment switching in a randomised controlled trial occurs when participants change from their randomised treatment to the other trial treatment during the study. Failure to account for treatment switching in the analysis (i.e. by performing a standard intention-to-treat analysis) can lead to biased estimates of treatment efficacy. The rank preserving structural failure time model (RPSFTM) is a method used to adjust for treatment switching in trials with survival outcomes. The RPSFTM is due to Robins and Tsiatis (1991) and has been developed by White et al. (1997, 1999). The method is randomisation based and uses only the randomised treatment group, observed event times, and treatment history in order to estimate a causal treatment effect. The treatment effect, ψ, is estimated by balancing counter-factual event times (that would be observed if no treatment were received) between treatment groups. G-estimation is used to find the value of ψ such that a test statistic Z(ψ) = 0. This is usually the test statistic used in the intention-to-treat analysis, for example, the log rank test statistic. We present an R package that implements the method of rpsftm. PMID:29564164

rpsftm: An R Package for Rank Preserving Structural Failure Time Models.

PubMed

Allison, Annabel; White, Ian R; Bond, Simon

2017-12-04

Treatment switching in a randomised controlled trial occurs when participants change from their randomised treatment to the other trial treatment during the study. Failure to account for treatment switching in the analysis (i.e. by performing a standard intention-to-treat analysis) can lead to biased estimates of treatment efficacy. The rank preserving structural failure time model (RPSFTM) is a method used to adjust for treatment switching in trials with survival outcomes. The RPSFTM is due to Robins and Tsiatis (1991) and has been developed by White et al. (1997, 1999). The method is randomisation based and uses only the randomised treatment group, observed event times, and treatment history in order to estimate a causal treatment effect. The treatment effect, ψ , is estimated by balancing counter-factual event times (that would be observed if no treatment were received) between treatment groups. G-estimation is used to find the value of ψ such that a test statistic Z ( ψ ) = 0. This is usually the test statistic used in the intention-to-treat analysis, for example, the log rank test statistic. We present an R package that implements the method of rpsftm.

Spectral Unmixing Analysis of Time Series Landsat 8 Images

NASA Astrophysics Data System (ADS)

Zhuo, R.; Xu, L.; Peng, J.; Chen, Y.

2018-05-01

Temporal analysis of Landsat 8 images opens up new opportunities in the unmixing procedure. Although spectral analysis of time series Landsat imagery has its own advantage, it has rarely been studied. Nevertheless, using the temporal information can provide improved unmixing performance when compared to independent image analyses. Moreover, different land cover types may demonstrate different temporal patterns, which can aid the discrimination of different natures. Therefore, this letter presents time series K-P-Means, a new solution to the problem of unmixing time series Landsat imagery. The proposed approach is to obtain the "purified" pixels in order to achieve optimal unmixing performance. The vertex component analysis (VCA) is used to extract endmembers for endmember initialization. First, nonnegative least square (NNLS) is used to estimate abundance maps by using the endmember. Then, the estimated endmember is the mean value of "purified" pixels, which is the residual of the mixed pixel after excluding the contribution of all nondominant endmembers. Assembling two main steps (abundance estimation and endmember update) into the iterative optimization framework generates the complete algorithm. Experiments using both simulated and real Landsat 8 images show that the proposed "joint unmixing" approach provides more accurate endmember and abundance estimation results compared with "separate unmixing" approach.

Doing Your Thing: Fourth Grade.

ERIC Educational Resources Information Center

Potter, Beverly

The fourth grade instructional unit, part of a grade school level career education series, is designed to assist learners in relating present experiences to past and future ones. Before the main body of the lessons is described, field testing results are reported, and key items are presented: the concepts, the estimated instructional time, the…

Estimating Solar PV Output Using Modern Space/Time Geostatistics (Presentation)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, S. J.; George, R.; Bush, B.

2009-04-29

This presentation describes a project that uses mapping techniques to predict solar output at subhourly resolution at any spatial point, develop a methodology that is applicable to natural resources in general, and demonstrate capability of geostatistical techniques to predict the output of a potential solar plant.

Minimum follow-up time required for the estimation of statistical cure of cancer patients: verification using data from 42 cancer sites in the SEER database

PubMed Central

Tai, Patricia; Yu, Edward; Cserni, Gábor; Vlastos, Georges; Royce, Melanie; Kunkler, Ian; Vinh-Hung, Vincent

2005-01-01

Background The present commonly used five-year survival rates are not adequate to represent the statistical cure. In the present study, we established the minimum number of years required for follow-up to estimate statistical cure rate, by using a lognormal distribution of the survival time of those who died of their cancer. We introduced the term, threshold year, the follow-up time for patients dying from the specific cancer covers most of the survival data, leaving less than 2.25% uncovered. This is close enough to cure from that specific cancer. Methods Data from the Surveillance, Epidemiology and End Results (SEER) database were tested if the survival times of cancer patients who died of their disease followed the lognormal distribution using a minimum chi-square method. Patients diagnosed from 1973–1992 in the registries of Connecticut and Detroit were chosen so that a maximum of 27 years was allowed for follow-up to 1999. A total of 49 specific organ sites were tested. The parameters of those lognormal distributions were found for each cancer site. The cancer-specific survival rates at the threshold years were compared with the longest available Kaplan-Meier survival estimates. Results The characteristics of the cancer-specific survival times of cancer patients who died of their disease from 42 cancer sites out of 49 sites were verified to follow different lognormal distributions. The threshold years validated for statistical cure varied for different cancer sites, from 2.6 years for pancreas cancer to 25.2 years for cancer of salivary gland. At the threshold year, the statistical cure rates estimated for 40 cancer sites were found to match the actuarial long-term survival rates estimated by the Kaplan-Meier method within six percentage points. For two cancer sites: breast and thyroid, the threshold years were so long that the cancer-specific survival rates could yet not be obtained because the SEER data do not provide sufficiently long follow-up. Conclusion The present study suggests a certain threshold year is required to wait before the statistical cure rate can be estimated for each cancer site. For some cancers, such as breast and thyroid, the 5- or 10-year survival rates inadequately reflect statistical cure rates, and highlight the need for long-term follow-up of these patients. PMID:15904508

Quantile Regression for Recurrent Gap Time Data

PubMed Central

Luo, Xianghua; Huang, Chiung-Yu; Wang, Lan

2014-01-01

Summary Evaluating covariate effects on gap times between successive recurrent events is of interest in many medical and public health studies. While most existing methods for recurrent gap time analysis focus on modeling the hazard function of gap times, a direct interpretation of the covariate effects on the gap times is not available through these methods. In this article, we consider quantile regression that can provide direct assessment of covariate effects on the quantiles of the gap time distribution. Following the spirit of the weighted risk-set method by Luo and Huang (2011, Statistics in Medicine 30, 301–311), we extend the martingale-based estimating equation method considered by Peng and Huang (2008, Journal of the American Statistical Association 103, 637–649) for univariate survival data to analyze recurrent gap time data. The proposed estimation procedure can be easily implemented in existing software for univariate censored quantile regression. Uniform consistency and weak convergence of the proposed estimators are established. Monte Carlo studies demonstrate the effectiveness of the proposed method. An application to data from the Danish Psychiatric Central Register is presented to illustrate the methods developed in this article. PMID:23489055

Joint coverage probability in a simulation study on Continuous-Time Markov Chain parameter estimation.

PubMed

Benoit, Julia S; Chan, Wenyaw; Doody, Rachelle S

2015-01-01

Parameter dependency within data sets in simulation studies is common, especially in models such as Continuous-Time Markov Chains (CTMC). Additionally, the literature lacks a comprehensive examination of estimation performance for the likelihood-based general multi-state CTMC. Among studies attempting to assess the estimation, none have accounted for dependency among parameter estimates. The purpose of this research is twofold: 1) to develop a multivariate approach for assessing accuracy and precision for simulation studies 2) to add to the literature a comprehensive examination of the estimation of a general 3-state CTMC model. Simulation studies are conducted to analyze longitudinal data with a trinomial outcome using a CTMC with and without covariates. Measures of performance including bias, component-wise coverage probabilities, and joint coverage probabilities are calculated. An application is presented using Alzheimer's disease caregiver stress levels. Comparisons of joint and component-wise parameter estimates yield conflicting inferential results in simulations from models with and without covariates. In conclusion, caution should be taken when conducting simulation studies aiming to assess performance and choice of inference should properly reflect the purpose of the simulation.

Relationship between parental estimate and an objective measure of child television watching

PubMed Central

Robinson, Jodie L; Winiewicz, Dana D; Fuerch, Janene H; Roemmich, James N; Epstein, Leonard H

2006-01-01

Many young children have televisions in their bedrooms, which may influence the relationship between parental estimate and objective measures of child television usage/week. Parental estimates of child television time of eighty 4–7 year old children (6.0 ± 1.2 years) at the 75th BMI percentile or greater (90.8 ± 6.8 BMI percentile) were compared to an objective measure of television time obtained from TV Allowance™ devices attached to every television in the home over a three week period. Results showed that parents overestimate their child's television time compared to an objective measure when no television is present in the bedroom by 4 hours/week (25.4 ± 11.5 vs. 21.4 ± 9.1) in comparison to underestimating television time by over 3 hours/week (26.5 ± 17.2 vs. 29.8 ± 14.4) when the child has a television in their bedroom (p = 0.02). Children with a television in their bedroom spend more objectively measured hours in television time than children without a television in their bedroom (29.8 ± 14.2 versus 21.4 ± 9.1, p = 0.003). Research on child television watching should take into account television watching in bedrooms, since it may not be adequately assessed by parental estimates. PMID:17129381

A straightforward frequency-estimation technique for GPS carrier-phase time transfer.

PubMed

Hackman, Christine; Levine, Judah; Parker, Thomas E; Piester, Dirk; Becker, Jürgen

2006-09-01

Although Global Positioning System (GPS) carrier-phase time transfer (GPSCPTT) offers frequency stability approaching 10-15 at averaging times of 1 d, a discontinuity occurs in the time-transfer estimates between the end of one processing batch (1-3 d in length) and the beginning of the next. The average frequency over a multiday analysis period often has been computed by first estimating and removing these discontinuities, i.e., through concatenation. We present a new frequency-estimation technique in which frequencies are computed from the individual batches then averaged to obtain the mean frequency for a multiday period. This allows the frequency to be computed without the uncertainty associated with the removal of the discontinuities and requires fewer computational resources. The new technique was tested by comparing the fractional frequency-difference values it yields to those obtained using a GPSCPTT concatenation method and those obtained using two-way satellite time-and-frequency transfer (TWSTFT). The clocks studied were located in Braunschweig, Germany, and in Boulder, CO. The frequencies obtained from the GPSCPTT measurements using either method agreed with those obtained from TWSTFT at several parts in 1016. The frequency values obtained from the GPSCPTT data by use of the new method agreed with those obtained using the concatenation technique at 1-4 x 10(-16).

Multiple scene attitude estimator performance for LANDSAT-1

NASA Technical Reports Server (NTRS)

Rifman, S. S.; Monuki, A. T.; Shortwell, C. P.

1979-01-01

Initial results are presented to demonstrate the performance of a linear sequential estimator (Kalman Filter) used to estimate a LANDSAT 1 spacecraft attitude time series defined for four scenes. With the revised estimator a GCP poor scene - a scene with no usable geodetic control points (GCPs) - can be rectified to higher accuracies than otherwise based on the use of GCPs in adjacent scenes. Attitude estimation errors was determined by the use of GCPs located in the GCP-poor test scene, but which are not used to update the Kalman filter. Initial results achieved indicate that errors of 500m (rms) can be attained for the GCP-poor scenes. Operational factors are related to various scenarios.

Observation of Rayleigh-Taylor-instability evolution in a plasma with magnetic and viscous effects

DOE PAGES

Adams, Colin S.; Moser, Auna L.; Hsu, Scott C.

2015-11-06

We present time-resolved observations of Rayleigh-Taylor-instability (RTI) evolution at the interface between an unmagnetized plasma jet colliding with a stagnated, magnetized plasma. The observed instability growth time (~10μs) is consistent with the estimated linear RTI growth rate calculated using experimentally inferred values of density (~10 14cm–3) and deceleration (~10 9 m/s 2). The observed mode wavelength (≳1 cm) nearly doubles within a linear growth time. Furthermore, theoretical estimates of magnetic and viscous stabilization and idealized magnetohydrodynamic simulations including a physical viscosity model both suggest that the observed instability evolution is subject to magnetic and/or viscous effects.

Time delay estimation using new spectral and adaptive filtering methods with applications to underwater target detection

NASA Astrophysics Data System (ADS)

Hasan, Mohammed A.

1997-11-01

In this dissertation, we present several novel approaches for detection and identification of targets of arbitrary shapes from the acoustic backscattered data and using the incident waveform. This problem is formulated as time- delay estimation and sinusoidal frequency estimation problems which both have applications in many other important areas in signal processing. Solving time-delay estimation problem allows the identification of the specular components in the backscattered signal from elastic and non-elastic targets. Thus, accurate estimation of these time delays would help in determining the existence of certain clues for detecting targets. Several new methods for solving these two problems in the time, frequency and wavelet domains are developed. In the time domain, a new block fast transversal filter (BFTF) is proposed for a fast implementation of the least squares (LS) method. This BFTF algorithm is derived by using data-related constrained block-LS cost function to guarantee global optimality. The new soft-constrained algorithm provides an efficient way of transferring weight information between blocks of data and thus it is computationally very efficient compared with other LS- based schemes. Additionally, the tracking ability of the algorithm can be controlled by varying the block length and/or a soft constrained parameter. The effectiveness of this algorithm is tested on several underwater acoustic backscattered data for elastic targets and non-elastic (cement chunk) objects. In the frequency domain, the time-delay estimation problem is converted to a sinusoidal frequency estimation problem by using the discrete Fourier transform. Then, the lagged sample covariance matrices of the resulting signal are computed and studied in terms of their eigen- structure. These matrices are shown to be robust and effective in extracting bases for the signal and noise subspaces. New MUSIC and matrix pencil-based methods are derived these subspaces. The effectiveness of the method is demonstrated on the problem of detection of multiple specular components in the acoustic backscattered data. Finally, a method for the estimation of time delays using wavelet decomposition is derived. The sub-band adaptive filtering uses discrete wavelet transform for multi- resolution or sub-band decomposition. Joint time delay estimation for identifying multi-specular components and subsequent adaptive filtering processes are performed on the signal in each sub-band. This would provide multiple 'look' of the signal at different resolution scale which results in more accurate estimates for delays associated with the specular components. Simulation results on the simulated and real shallow water data are provided which show the promise of this new scheme for target detection in a heavy cluttered environment.

Robust Low-dose CT Perfusion Deconvolution via Tensor Total-Variation Regularization

PubMed Central

Zhang, Shaoting; Chen, Tsuhan; Sanelli, Pina C.

2016-01-01

Acute brain diseases such as acute strokes and transit ischemic attacks are the leading causes of mortality and morbidity worldwide, responsible for 9% of total death every year. ‘Time is brain’ is a widely accepted concept in acute cerebrovascular disease treatment. Efficient and accurate computational framework for hemodynamic parameters estimation can save critical time for thrombolytic therapy. Meanwhile the high level of accumulated radiation dosage due to continuous image acquisition in CT perfusion (CTP) raised concerns on patient safety and public health. However, low-radiation leads to increased noise and artifacts which require more sophisticated and time-consuming algorithms for robust estimation. In this paper, we focus on developing a robust and efficient framework to accurately estimate the perfusion parameters at low radiation dosage. Specifically, we present a tensor total-variation (TTV) technique which fuses the spatial correlation of the vascular structure and the temporal continuation of the blood signal flow. An efficient algorithm is proposed to find the solution with fast convergence and reduced computational complexity. Extensive evaluations are carried out in terms of sensitivity to noise levels, estimation accuracy, contrast preservation, and performed on digital perfusion phantom estimation, as well as in-vivo clinical subjects. Our framework reduces the necessary radiation dose to only 8% of the original level and outperforms the state-of-art algorithms with peak signal-to-noise ratio improved by 32%. It reduces the oscillation in the residue functions, corrects over-estimation of cerebral blood flow (CBF) and under-estimation of mean transit time (MTT), and maintains the distinction between the deficit and normal regions. PMID:25706579

Real Time Tracking of Magmatic Intrusions by means of Ground Deformation Modeling during Volcanic Crises.

PubMed

Cannavò, Flavio; Camacho, Antonio G; González, Pablo J; Mattia, Mario; Puglisi, Giuseppe; Fernández, José

2015-06-09

Volcano observatories provide near real-time information and, ultimately, forecasts about volcano activity. For this reason, multiple physical and chemical parameters are continuously monitored. Here, we present a new method to efficiently estimate the location and evolution of magmatic sources based on a stream of real-time surface deformation data, such as High-Rate GPS, and a free-geometry magmatic source model. The tool allows tracking inflation and deflation sources in time, providing estimates of where a volcano might erupt, which is important in understanding an on-going crisis. We show a successful simulated application to the pre-eruptive period of May 2008, at Mount Etna (Italy). The proposed methodology is able to track the fast dynamics of the magma migration by inverting the real-time data within seconds. This general method is suitable for integration in any volcano observatory. The method provides first order unsupervised and realistic estimates of the locations of magmatic sources and of potential eruption sites, information that is especially important for civil protection purposes.

Regression analysis of case K interval-censored failure time data in the presence of informative censoring.

PubMed

Wang, Peijie; Zhao, Hui; Sun, Jianguo

2016-12-01

Interval-censored failure time data occur in many fields such as demography, economics, medical research, and reliability and many inference procedures on them have been developed (Sun, 2006; Chen, Sun, and Peace, 2012). However, most of the existing approaches assume that the mechanism that yields interval censoring is independent of the failure time of interest and it is clear that this may not be true in practice (Zhang et al., 2007; Ma, Hu, and Sun, 2015). In this article, we consider regression analysis of case K interval-censored failure time data when the censoring mechanism may be related to the failure time of interest. For the problem, an estimated sieve maximum-likelihood approach is proposed for the data arising from the proportional hazards frailty model and for estimation, a two-step procedure is presented. In the addition, the asymptotic properties of the proposed estimators of regression parameters are established and an extensive simulation study suggests that the method works well. Finally, we apply the method to a set of real interval-censored data that motivated this study. © 2016, The International Biometric Society.

Real Time Tracking of Magmatic Intrusions by means of Ground Deformation Modeling during Volcanic Crises

PubMed Central

Cannavò, Flavio; Camacho, Antonio G.; González, Pablo J.; Mattia, Mario; Puglisi, Giuseppe; Fernández, José

2015-01-01

Volcano observatories provide near real-time information and, ultimately, forecasts about volcano activity. For this reason, multiple physical and chemical parameters are continuously monitored. Here, we present a new method to efficiently estimate the location and evolution of magmatic sources based on a stream of real-time surface deformation data, such as High-Rate GPS, and a free-geometry magmatic source model. The tool allows tracking inflation and deflation sources in time, providing estimates of where a volcano might erupt, which is important in understanding an on-going crisis. We show a successful simulated application to the pre-eruptive period of May 2008, at Mount Etna (Italy). The proposed methodology is able to track the fast dynamics of the magma migration by inverting the real-time data within seconds. This general method is suitable for integration in any volcano observatory. The method provides first order unsupervised and realistic estimates of the locations of magmatic sources and of potential eruption sites, information that is especially important for civil protection purposes. PMID:26055494

The influence of purge times on the yields of essential oil components extracted from plants by pressurized liquid extraction.

PubMed

Wianowska, Dorota

2014-01-01

The influence of different purge times on the yield of the main essential oil constituents of rosemary (Rosmarinus officinalis L.), thyme (Thymus vulgaris L.), and chamomile (Chamomilla recutita L.) was investigated. The pressurized liquid extraction process was performed by applying different extraction temperatures and solvents. The results presented in the paper show that the estimated yield of essential oil components extracted from the plants in the pressurized liquid extraction process is purge time-dependent. The differences in the estimated yields are mainly connected with the evaporation of individual essential oil components and the applied solvent during the purge; the more volatile an essential oil constituent is, the greater is its loss during purge time, and the faster the evaporation of the solvent during the purge process is, the higher the concentration of less volatile essential oil components in the pressurized liquid extraction receptacle. The effect of purge time on the estimated yield of individual essential oil constituents is additionally differentiated by the extraction temperature and the extraction ability of the applied solvent.

Effective channel estimation and efficient symbol detection for multi-input multi-output underwater acoustic communications

NASA Astrophysics Data System (ADS)

Ling, Jun

Achieving reliable underwater acoustic communications (UAC) has long been recognized as a challenging problem owing to the scarce bandwidth available and the reverberant spread in both time and frequency domains. To pursue high data rates, we consider a multi-input multi-output (MIMO) UAC system, and our focus is placed on two main issues regarding a MIMO UAC system: (1) channel estimation, which involves the design of the training sequences and the development of a reliable channel estimation algorithm, and (2) symbol detection, which requires interference cancelation schemes due to simultaneous transmission from multiple transducers. To enhance channel estimation performance, we present a cyclic approach for designing training sequences with good auto- and cross-correlation properties, and a channel estimation algorithm called the iterative adaptive approach (IAA). Sparse channel estimates can be obtained by combining IAA with the Bayesian information criterion (BIC). Moreover, we present sparse learning via iterative minimization (SLIM) and demonstrate that SLIM gives similar performance to IAA but at a much lower computational cost. Furthermore, an extension of the SLIM algorithm is introduced to estimate the sparse and frequency modulated acoustic channels. The extended algorithm is referred to as generalization of SLIM (GoSLIM). Regarding symbol detection, a linear minimum mean-squared error based detection scheme, called RELAX-BLAST, which is a combination of vertical Bell Labs layered space-time (V-BLAST) algorithm and the cyclic principle of the RELAX algorithm, is presented and it is shown that RELAX-BLAST outperforms V-BLAST. We show that RELAX-BLAST can be implemented efficiently by making use of the conjugate gradient method and diagonalization properties of circulant matrices. This fast implementation approach requires only simple fast Fourier transform operations and facilitates parallel implementations. The effectiveness of the proposed MIMO schemes is verified by both computer simulations and experimental results obtained by analyzing the measurements acquired in multiple in-water experiments.

Adjusting survival estimates for premature transmitter failure: A case study from the Sacramento-San Joaquin Delta

USGS Publications Warehouse

Holbrook, Christopher M.; Perry, Russell W.; Brandes, Patricia L.; Adams, Noah S.

2013-01-01

In telemetry studies, premature tag failure causes negative bias in fish survival estimates because tag failure is interpreted as fish mortality. We used mark-recapture modeling to adjust estimates of fish survival for a previous study where premature tag failure was documented. High rates of tag failure occurred during the Vernalis Adaptive Management Plan’s (VAMP) 2008 study to estimate survival of fall-run Chinook salmon (Oncorhynchus tshawytscha) during migration through the San Joaquin River and Sacramento-San Joaquin Delta, California. Due to a high rate of tag failure, the observed travel time distribution was likely negatively biased, resulting in an underestimate of tag survival probability in this study. Consequently, the bias-adjustment method resulted in only a small increase in estimated fish survival when the observed travel time distribution was used to estimate the probability of tag survival. Since the bias-adjustment failed to remove bias, we used historical travel time data and conducted a sensitivity analysis to examine how fish survival might have varied across a range of tag survival probabilities. Our analysis suggested that fish survival estimates were low (95% confidence bounds range from 0.052 to 0.227) over a wide range of plausible tag survival probabilities (0.48–1.00), and this finding is consistent with other studies in this system. When tags fail at a high rate, available methods to adjust for the bias may perform poorly. Our example highlights the importance of evaluating the tag life assumption during survival studies, and presents a simple framework for evaluating adjusted survival estimates when auxiliary travel time data are available.

Estimation of hysteretic damping of structures by stochastic subspace identification

NASA Astrophysics Data System (ADS)

Bajrić, Anela; Høgsberg, Jan

2018-05-01

Output-only system identification techniques can estimate modal parameters of structures represented by linear time-invariant systems. However, the extension of the techniques to structures exhibiting non-linear behavior has not received much attention. This paper presents an output-only system identification method suitable for random response of dynamic systems with hysteretic damping. The method applies the concept of Stochastic Subspace Identification (SSI) to estimate the model parameters of a dynamic system with hysteretic damping. The restoring force is represented by the Bouc-Wen model, for which an equivalent linear relaxation model is derived. Hysteretic properties can be encountered in engineering structures exposed to severe cyclic environmental loads, as well as in vibration mitigation devices, such as Magneto-Rheological (MR) dampers. The identification technique incorporates the equivalent linear damper model in the estimation procedure. Synthetic data, representing the random vibrations of systems with hysteresis, validate the estimated system parameters by the presented identification method at low and high-levels of excitation amplitudes.

The Use of Radar to Improve Rainfall Estimation over the Tennessee and San Joaquin River Valleys

NASA Technical Reports Server (NTRS)

Petersen, Walter A.; Gatlin, Patrick N.; Felix, Mariana; Carey, Lawrence D.

2010-01-01

This slide presentation provides an overview of the collaborative radar rainfall project between the Tennessee Valley Authority (TVA), the Von Braun Center for Science & Innovation (VCSI), NASA MSFC and UAHuntsville. Two systems were used in this project, Advanced Radar for Meteorological & Operational Research (ARMOR) Rainfall Estimation Processing System (AREPS), a demonstration project of real-time radar rainfall using a research radar and NEXRAD Rainfall Estimation Processing System (NREPS). The objectives, methodology, some results and validation, operational experience and lessons learned are reviewed. The presentation. Another project that is using radar to improve rainfall estimations is in California, specifically the San Joaquin River Valley. This is part of a overall project to develop a integrated tool to assist water management within the San Joaquin River Valley. This involves integrating several components: (1) Radar precipitation estimates, (2) Distributed hydro model, (3) Snowfall measurements and Surface temperature / moisture measurements. NREPS was selected to provide precipitation component.

Change-in-ratio estimators for populations with more than two subclasses

USGS Publications Warehouse

Udevitz, Mark S.; Pollock, Kenneth H.

1991-01-01

Change-in-ratio methods have been developed to estimate the size of populations with two or three population subclasses. Most of these methods require the often unreasonable assumption of equal sampling probabilities for individuals in all subclasses. This paper presents new models based on the weaker assumption that ratios of sampling probabilities are constant over time for populations with three or more subclasses. Estimation under these models requires that a value be assumed for one of these ratios when there are two samples. Explicit expressions are given for the maximum likelihood estimators under models for two samples with three or more subclasses and for three samples with two subclasses. A numerical method using readily available statistical software is described for obtaining the estimators and their standard errors under all of the models. Likelihood ratio tests that can be used in model selection are discussed. Emphasis is on the two-sample, three-subclass models for which Monte-Carlo simulation results and an illustrative example are presented.

Ratios for estimating logging residue in the Pacific Northwest.

Treesearch

James O. Howard

1981-01-01

Ratios are presented for estimating the volume of logging residue for any location in Idaho, Washington, and Oregon. They show cubic-foot volume of logging residue per 1,000 board feet of timber harvested and per acre harvested. Tables show gross and net volumes, with and without bark. The volumes of live and dead and cull residue at the time of harvest are also given...

A New Mixing Diagnostic and Gulf Oil Spill Movement

DTIC Science & Technology

2010-10-01

could be used with new estimates of the suppression parameter to yield appreciably larger estimates of the hydrogen content in the shallow lunar ...paradigm for mixing in fluid flows with simple time dependence. Its skeletal structure is based on analysis of invariant attracting and repelling...continues to the present day. Model analysis and forecasts are compared to independent (nonassimilated) infrared frontal po- sitions and drifter trajectories

Real-Time Detection of Tsunami Ionospheric Disturbances with a Stand-Alone GNSS Receiver: An Integration of GPS and Galileo Systems

NASA Astrophysics Data System (ADS)

Savastano, Giorgio; Komjathy, Attila; Verkhoglyadova, Olga; Wei, Yong; Mazzoni, Augusto; Crespi, Mattia

2017-04-01

Tsunamis can produce gravity waves that propagate up to the ionosphere generating disturbed electron densities in the E and F regions. These ionospheric disturbances are studied in detail using ionospheric total electron content (TEC) measurements collected by continuously operating ground-based receivers from the Global Navigation Satellite Systems (GNSS). Here, we present results using a new approach, named VARION (Variometric Approach for Real-Time Ionosphere Observation), and for the first time, we estimate slant TEC (sTEC) variations in a real-time scenario from GPS and Galileo constellations. Specifically, we study the 2016 New Zealand tsunami event using GNSS receivers with multi-constellation tracking capabilities located in the Pacific region. We compare sTEC estimates obtained using GPS and Galileo constellations. The efficiency of the real-time sTEC estimation using the VARION algorithm has been demonstrated for the 2012 Haida Gwaii tsunami event. TEC variations induced by the tsunami event are computed using 56 GPS receivers in Hawai'i. We observe TEC perturbations with amplitudes up to 0.25 TEC units and traveling ionospheric disturbances moving away from the epicenter at a speed of about 316 m/s. We present comparisons with the real-time tsunami model MOST (Method of Splitting Tsunami) provided by the NOAA Center for Tsunami Research. We observe variations in TEC that correlate well in time and space with the propagating tsunami waves. We conclude that the integration of different satellite constellations is a crucial step forward to increasing the reliability of real-time tsunami detection systems using ground-based GNSS receivers as an augmentation to existing tsunami early warning systems.

Terrestrial reference frame solution with the Vienna VLBI Software VieVS and implication of tropospheric gradient estimation

NASA Astrophysics Data System (ADS)

Spicakova, H.; Plank, L.; Nilsson, T.; Böhm, J.; Schuh, H.

2011-07-01

The Vienna VLBI Software (VieVS) has been developed at the Institute of Geodesy and Geophysics at TU Vienna since 2008. In this presentation, we present the module Vie_glob which is the part of VieVS that allows the parameter estimation from multiple VLBI sessions in a so-called global solution. We focus on the determination of the terrestrial reference frame (TRF) using all suitable VLBI sessions since 1984. We compare different analysis options like the choice of loading corrections or of one of the models for the tropospheric delays. The effect of atmosphere loading corrections on station heights if neglected at observation level will be shown. Time series of station positions (using a previously determined TRF as a priori values) are presented and compared to other estimates of site positions from individual IVS (International VLBI Service for Geodesy and Astrometry) Analysis Centers.

A modified NARMAX model-based self-tuner with fault tolerance for unknown nonlinear stochastic hybrid systems with an input-output direct feed-through term.

PubMed

Tsai, Jason S-H; Hsu, Wen-Teng; Lin, Long-Guei; Guo, Shu-Mei; Tann, Joseph W

2014-01-01

A modified nonlinear autoregressive moving average with exogenous inputs (NARMAX) model-based state-space self-tuner with fault tolerance is proposed in this paper for the unknown nonlinear stochastic hybrid system with a direct transmission matrix from input to output. Through the off-line observer/Kalman filter identification method, one has a good initial guess of modified NARMAX model to reduce the on-line system identification process time. Then, based on the modified NARMAX-based system identification, a corresponding adaptive digital control scheme is presented for the unknown continuous-time nonlinear system, with an input-output direct transmission term, which also has measurement and system noises and inaccessible system states. Besides, an effective state space self-turner with fault tolerance scheme is presented for the unknown multivariable stochastic system. A quantitative criterion is suggested by comparing the innovation process error estimated by the Kalman filter estimation algorithm, so that a weighting matrix resetting technique by adjusting and resetting the covariance matrices of parameter estimate obtained by the Kalman filter estimation algorithm is utilized to achieve the parameter estimation for faulty system recovery. Consequently, the proposed method can effectively cope with partially abrupt and/or gradual system faults and input failures by the fault detection. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Children's accuracy of portion size estimation using digital food images: effects of interface design and size of image on computer screen.

PubMed

Baranowski, Tom; Baranowski, Janice C; Watson, Kathleen B; Martin, Shelby; Beltran, Alicia; Islam, Noemi; Dadabhoy, Hafza; Adame, Su-heyla; Cullen, Karen; Thompson, Debbe; Buday, Richard; Subar, Amy

2011-03-01

To test the effect of image size and presence of size cues on the accuracy of portion size estimation by children. Children were randomly assigned to seeing images with or without food size cues (utensils and checked tablecloth) and were presented with sixteen food models (foods commonly eaten by children) in varying portion sizes, one at a time. They estimated each food model's portion size by selecting a digital food image. The same food images were presented in two ways: (i) as small, graduated portion size images all on one screen or (ii) by scrolling across large, graduated portion size images, one per sequential screen. Laboratory-based with computer and food models. Volunteer multi-ethnic sample of 120 children, equally distributed by gender and ages (8 to 13 years) in 2008-2009. Average percentage of correctly classified foods was 60·3 %. There were no differences in accuracy by any design factor or demographic characteristic. Multiple small pictures on the screen at once took half the time to estimate portion size compared with scrolling through large pictures. Larger pictures had more overestimation of size. Multiple images of successively larger portion sizes of a food on one computer screen facilitated quicker portion size responses with no decrease in accuracy. This is the method of choice for portion size estimation on a computer.

An optimally weighted estimator of the linear power spectrum disentangling the growth of density perturbations across galaxy surveys

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sorini, D., E-mail: sorini@mpia-hd.mpg.de

2017-04-01

Measuring the clustering of galaxies from surveys allows us to estimate the power spectrum of matter density fluctuations, thus constraining cosmological models. This requires careful modelling of observational effects to avoid misinterpretation of data. In particular, signals coming from different distances encode information from different epochs. This is known as ''light-cone effect'' and is going to have a higher impact as upcoming galaxy surveys probe larger redshift ranges. Generalising the method by Feldman, Kaiser and Peacock (1994) [1], I define a minimum-variance estimator of the linear power spectrum at a fixed time, properly taking into account the light-cone effect. Anmore » analytic expression for the estimator is provided, and that is consistent with the findings of previous works in the literature. I test the method within the context of the Halofit model, assuming Planck 2014 cosmological parameters [2]. I show that the estimator presented recovers the fiducial linear power spectrum at present time within 5% accuracy up to k ∼ 0.80 h Mpc{sup −1} and within 10% up to k ∼ 0.94 h Mpc{sup −1}, well into the non-linear regime of the growth of density perturbations. As such, the method could be useful in the analysis of the data from future large-scale surveys, like Euclid.« less

Estimating the k2 Tidal Gravity Love Number of Mars

NASA Technical Reports Server (NTRS)

Smith, David E.; Zuber, Maria; Torrence, Mark; Dunn, Peter

2003-01-01

Analysis of the orbits of spacecraft can be used to infer global tidal parameters. For Mars, the Mars Global Surveyor (MGS) spacecraft has been used to estimate the second degree Love number, k2 from the tracking DSN tracking Doppler and range data by several authors. Unfortunately, neither of the spacecraft presently in orbit are ideally suited to tidal recovery because they are in sun-synchronous orbits that vary only slightly in local time; and, further, the sub-solar location only varies by about 25 degrees in latitude. Never-the less respectable estimates of the k2 tide have been made by several authors. We present an updated solution of the degree 2 zonal Love number, compare with previous dues, and analyze the sensitivity of the solution to orbital parameters, spacecraft maneuvers, and solution methodology. Estimating the k2 Tidal Gravity Love Number of Mars.

Method development estimating ambient mercury concentration from monitored mercury wet deposition

NASA Astrophysics Data System (ADS)

Chen, S. M.; Qiu, X.; Zhang, L.; Yang, F.; Blanchard, P.

2013-05-01

Speciated atmospheric mercury data have recently been monitored at multiple locations in North America; but the spatial coverage is far less than the long-established mercury wet deposition network. The present study describes a first attempt linking ambient concentration with wet deposition using Beta distribution fitting of a ratio estimate. The mean, median, mode, standard deviation, and skewness of the fitted Beta distribution parameters were generated using data collected in 2009 at 11 monitoring stations. Comparing the normalized histogram and the fitted density function, the empirical and fitted Beta distribution of the ratio shows a close fit. The estimated ambient mercury concentration was further partitioned into reactive gaseous mercury and particulate bound mercury using linear regression model developed by Amos et al. (2012). The method presented here can be used to roughly estimate mercury ambient concentration at locations and/or times where such measurement is not available but where wet deposition is monitored.

A cross-country Exchange Market Pressure (EMP) dataset.

PubMed

Desai, Mohit; Patnaik, Ila; Felman, Joshua; Shah, Ajay

2017-06-01

The data presented in this article are related to the research article titled - "An exchange market pressure measure for cross country analysis" (Patnaik et al. [1]). In this article, we present the dataset for Exchange Market Pressure values (EMP) for 139 countries along with their conversion factors, ρ (rho). Exchange Market Pressure, expressed in percentage change in exchange rate, measures the change in exchange rate that would have taken place had the central bank not intervened. The conversion factor ρ can interpreted as the change in exchange rate associated with $1 billion of intervention. Estimates of conversion factor ρ allow us to calculate a monthly time series of EMP for 139 countries. Additionally, the dataset contains the 68% confidence interval (high and low values) for the point estimates of ρ 's. Using the standard errors of estimates of ρ 's, we obtain one sigma intervals around mean estimates of EMP values. These values are also reported in the dataset.

A kinematic model to estimate the effective dose of radioactive isotopes in the human body for radiological protection

NASA Astrophysics Data System (ADS)

Sasaki, S.; Yamada, T.

2013-12-01

The great earthquake attacked the north-east area in Japan in March 11, 2011. The system of electrical facilities to control Fukushima Daiichi nuclear power station was completely destroyed by the following tsunamis. From the damaged reactor containment vessels, an amount of radioactive substances had leaked and been diffused in the vicinity of this station. Radiological internal exposure becomes a serious social issue both in Japan and all over the world. The present study provides an easily understandable, kinematic-based model to estimate the effective dose of radioactive substances in a human body by simplified the complicated mechanism of metabolism. International Commission on Radiological Protection (ICRP) has developed an exact model, which is well-known as a standard method to calculate the effective dose for radiological protection. However, owing to that the above method accord too much with the actual mechanism of metabolism in human bodies, it becomes rather difficult for non-professional people of radiology to gasp the whole images of the movement and the influences of radioactive substances in a human body. Therefore, in the present paper we propose a newly-derived and easily-understandable model to estimate the effective dose. The present method is very similar with the traditional and conventional hydrological tank model. Ingestion flux of radioactive substances corresponds to rain intensity and the storage of radioactive substances to the water storage in a basin in runoff analysis. The key of this method is to estimate the energy radiated from the radioactive nuclear disintegration of an atom by using classical theory of E. Fermi of beta decay and special relativity for various kinds of radioactive atoms. The parameters used in this study are only physical half-time and biological half-time, and there are no intentional and operational parameters of coefficients to adjust our theoretical runoff to observation of ICRP. Figure.1 compares time series of effective cesium-137 dose according to age calculated by ICRP software with calculated by the present method. Plots are calculated values by ICRP, the solid line is analytic solution given from the present method. It should be noted that the present study does not consider complicated mechanism, but it could give equally accurate results comparing to existing research. Time series of effective Cs-137 dose according to age when food contains 1 Bq/year is ingested for 1 year. (Plots are calculated values by ICRP. The solid line is analytic solution given from the present method)

Moving Sound Source Localization Based on Sequential Subspace Estimation in Actual Room Environments

NASA Astrophysics Data System (ADS)

Tsuji, Daisuke; Suyama, Kenji

This paper presents a novel method for moving sound source localization and its performance evaluation in actual room environments. The method is based on the MUSIC (MUltiple SIgnal Classification) which is one of the most high resolution localization methods. When using the MUSIC, a computation of eigenvectors of correlation matrix is required for the estimation. It needs often a high computational costs. Especially, in the situation of moving source, it becomes a crucial drawback because the estimation must be conducted at every the observation time. Moreover, since the correlation matrix varies its characteristics due to the spatial-temporal non-stationarity, the matrix have to be estimated using only a few observed samples. It makes the estimation accuracy degraded. In this paper, the PAST (Projection Approximation Subspace Tracking) is applied for sequentially estimating the eigenvectors spanning the subspace. In the PAST, the eigen-decomposition is not required, and therefore it is possible to reduce the computational costs. Several experimental results in the actual room environments are shown to present the superior performance of the proposed method.

Statistical aspects of point count sampling

USGS Publications Warehouse

Barker, R.J.; Sauer, J.R.; Ralph, C.J.; Sauer, J.R.; Droege, S.

1995-01-01

The dominant feature of point counts is that they do not census birds, but instead provide incomplete counts of individuals present within a survey plot. Considering a simple model for point count sampling, we demon-strate that use of these incomplete counts can bias estimators and testing procedures, leading to inappropriate conclusions. A large portion of the variability in point counts is caused by the incomplete counting, and this within-count variation can be confounded with ecologically meaningful varia-tion. We recommend caution in the analysis of estimates obtained from point counts. Using; our model, we also consider optimal allocation of sampling effort. The critical step in the optimization process is in determining the goals of the study and methods that will be used to meet these goals. By explicitly defining the constraints on sampling and by estimating the relationship between precision and bias of estimators and time spent counting, we can predict the optimal time at a point for each of several monitoring goals. In general, time spent at a point will differ depending on the goals of the study.

Application of chlorine-36 technique in determining the age of modern groundwater in the Al-Zulfi province, Saudi Arabia.

PubMed

Challan, Mohsen B

2016-06-01

The present study aims to estimate the residence time of groundwater based on bomb-produced (36)Cl. (36)Cl/Cl ratios in the water samples are determined by inductively coupled plasma mass spectrometry and liquid scintillation counting. (36)Cl/Cl ratios in the groundwater were estimated to be 1.0-2.0 × 10(-12). Estimates of residence time were obtained by comparing the measured bomb-derived (36)Cl concentrations in groundwater with the background reference. Dating based on a (36)Cl bomb pulse may be more reliable and sensitive for groundwater recharged before 1975, back as far as the mid-1950s. The above (36)Cl background concentration was deduced by determining the background-corrected Dye-3 ice core data from the frozen Arctic data, according to the estimated total (36)Cl resources. The residence time of 7.81 × 10(4) y is obtained from extrapolated groundwater flow velocity. (36)Cl concentration in groundwater does not reflect the input of bomb pulse (36)Cl, and it belongs to the era before 1950.

Remaining dischargeable time prediction for lithium-ion batteries using unscented Kalman filter

NASA Astrophysics Data System (ADS)

Dong, Guangzhong; Wei, Jingwen; Chen, Zonghai; Sun, Han; Yu, Xiaowei

2017-10-01

To overcome the range anxiety, one of the important strategies is to accurately predict the range or dischargeable time of the battery system. To accurately predict the remaining dischargeable time (RDT) of a battery, a RDT prediction framework based on accurate battery modeling and state estimation is presented in this paper. Firstly, a simplified linearized equivalent-circuit-model is developed to simulate the dynamic characteristics of a battery. Then, an online recursive least-square-algorithm method and unscented-Kalman-filter are employed to estimate the system matrices and SOC at every prediction point. Besides, a discrete wavelet transform technique is employed to capture the statistical information of past dynamics of input currents, which are utilized to predict the future battery currents. Finally, the RDT can be predicted based on the battery model, SOC estimation results and predicted future battery currents. The performance of the proposed methodology has been verified by a lithium-ion battery cell. Experimental results indicate that the proposed method can provide an accurate SOC and parameter estimation and the predicted RDT can solve the range anxiety issues.

FPGA-based architecture for motion recovering in real-time

NASA Astrophysics Data System (ADS)

Arias-Estrada, Miguel; Maya-Rueda, Selene E.; Torres-Huitzil, Cesar

2002-03-01

A key problem in the computer vision field is the measurement of object motion in a scene. The main goal is to compute an approximation of the 3D motion from the analysis of an image sequence. Once computed, this information can be used as a basis to reach higher level goals in different applications. Motion estimation algorithms pose a significant computational load for the sequential processors limiting its use in practical applications. In this work we propose a hardware architecture for motion estimation in real time based on FPGA technology. The technique used for motion estimation is Optical Flow due to its accuracy, and the density of velocity estimation, however other techniques are being explored. The architecture is composed of parallel modules working in a pipeline scheme to reach high throughput rates near gigaflops. The modules are organized in a regular structure to provide a high degree of flexibility to cover different applications. Some results will be presented and the real-time performance will be discussed and analyzed. The architecture is prototyped in an FPGA board with a Virtex device interfaced to a digital imager.

Real-time detection of moving objects from moving vehicles using dense stereo and optical flow

NASA Technical Reports Server (NTRS)

Talukder, Ashit; Matthies, Larry

2004-01-01

Dynamic scene perception is very important for autonomous vehicles operating around other moving vehicles and humans. Most work on real-time object tracking from moving platforms has used sparse features or assumed flat scene structures. We have recently extended a real-time, dense stereo system to include realtime, dense optical flow, enabling more comprehensive dynamic scene analysis. We describe algorithms to robustly estimate 6-DOF robot egomotion in the presence of moving objects using dense flow and dense stereo. We then use dense stereo and egomotion estimates to identify & other moving objects while the robot itself is moving. We present results showing accurate egomotion estimation and detection of moving people and vehicles under general 6-DOF motion of the robot and independently moving objects. The system runs at 18.3 Hz on a 1.4 GHz Pentium M laptop, computing 160x120 disparity maps and optical flow fields, egomotion, and moving object segmentation. We believe this is a significant step toward general unconstrained dynamic scene analysis for mobile robots, as well as for improved position estimation where GPS is unavailable.

Real-time Detection of Moving Objects from Moving Vehicles Using Dense Stereo and Optical Flow

NASA Technical Reports Server (NTRS)

Talukder, Ashit; Matthies, Larry

2004-01-01

Dynamic scene perception is very important for autonomous vehicles operating around other moving vehicles and humans. Most work on real-time object tracking from moving platforms has used sparse features or assumed flat scene structures. We have recently extended a real-time. dense stereo system to include realtime. dense optical flow, enabling more comprehensive dynamic scene analysis. We describe algorithms to robustly estimate 6-DOF robot egomotion in the presence of moving objects using dense flow and dense stereo. We then use dense stereo and egomotion estimates to identify other moving objects while the robot itself is moving. We present results showing accurate egomotion estimation and detection of moving people and vehicles under general 6DOF motion of the robot and independently moving objects. The system runs at 18.3 Hz on a 1.4 GHz Pentium M laptop. computing 160x120 disparity maps and optical flow fields, egomotion, and moving object segmentation. We believe this is a significant step toward general unconstrained dynamic scene analysis for mobile robots, as well as for improved position estimation where GPS is unavailable.

Towards real-time diffuse optical tomography for imaging brain functions cooperated with Kalman estimator

NASA Astrophysics Data System (ADS)

Wang, Bingyuan; Zhang, Yao; Liu, Dongyuan; Ding, Xuemei; Dan, Mai; Pan, Tiantian; Wang, Yihan; Li, Jiao; Zhou, Zhongxing; Zhang, Limin; Zhao, Huijuan; Gao, Feng

2018-02-01

Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging method to monitor the cerebral hemodynamic through the optical changes measured at the scalp surface. It has played a more and more important role in psychology and medical imaging communities. Real-time imaging of brain function using NIRS makes it possible to explore some sophisticated human brain functions unexplored before. Kalman estimator has been frequently used in combination with modified Beer-Lamber Law (MBLL) based optical topology (OT), for real-time brain function imaging. However, the spatial resolution of the OT is low, hampering the application of OT in exploring some complicated brain functions. In this paper, we develop a real-time imaging method combining diffuse optical tomography (DOT) and Kalman estimator, much improving the spatial resolution. Instead of only presenting one spatially distributed image indicating the changes of the absorption coefficients at each time point during the recording process, one real-time updated image using the Kalman estimator is provided. Its each voxel represents the amplitude of the hemodynamic response function (HRF) associated with this voxel. We evaluate this method using some simulation experiments, demonstrating that this method can obtain more reliable spatial resolution images. Furthermore, a statistical analysis is also conducted to help to decide whether a voxel in the field of view is activated or not.

Wavefront correction with Kalman filtering for the WFIRST-AFTA coronagraph instrument

NASA Astrophysics Data System (ADS)

Riggs, A. J. Eldorado; Kasdin, N. Jeremy; Groff, Tyler D.

2015-09-01

The only way to characterize most exoplanets spectrally is via direct imaging. For example, the Coronagraph Instrument (CGI) on the proposed Wide-Field Infrared Survey Telescope-Astrophysics Focused Telescope Assets (WFIRST-AFTA) mission plans to image and characterize several cool gas giants around nearby stars. The integration time on these faint exoplanets will be many hours to days. A crucial assumption for mission planning is that the time required to dig a dark hole (a region of high star-to-planet contrast) with deformable mirrors is small compared to science integration time. The science camera must be used as the wavefront sensor to avoid non-common path aberrations, but this approach can be quite time intensive. Several estimation images are required to build an estimate of the starlight electric field before it can be partially corrected, and this process is repeated iteratively until high contrast is reached. Here we present simulated results of batch process and recursive wavefront estimation schemes. In particular, we test a Kalman filter and an iterative extended Kalman filter (IEKF) to reduce the total exposure time and improve the robustness of wavefront correction for the WFIRST-AFTA CGI. An IEKF or other nonlinear filter also allows recursive, real-time estimation of sources incoherent with the star, such as exoplanets and disks, and may therefore reduce detection uncertainty.

Signal-to-noise ratio estimation on SEM images using cubic spline interpolation with Savitzky-Golay smoothing.

PubMed

Sim, K S; Kiani, M A; Nia, M E; Tso, C P

2014-01-01

A new technique based on cubic spline interpolation with Savitzky-Golay noise reduction filtering is designed to estimate signal-to-noise ratio of scanning electron microscopy (SEM) images. This approach is found to present better result when compared with two existing techniques: nearest neighbourhood and first-order interpolation. When applied to evaluate the quality of SEM images, noise can be eliminated efficiently with optimal choice of scan rate from real-time SEM images, without generating corruption or increasing scanning time. © 2013 The Authors Journal of Microscopy © 2013 Royal Microscopical Society.

The epoch state navigation filter. [for maximum likelihood estimates of position and velocity vectors

NASA Technical Reports Server (NTRS)

Battin, R. H.; Croopnick, S. R.; Edwards, J. A.

1977-01-01

The formulation of a recursive maximum likelihood navigation system employing reference position and velocity vectors as state variables is presented. Convenient forms of the required variational equations of motion are developed together with an explicit form of the associated state transition matrix needed to refer measurement data from the measurement time to the epoch time. Computational advantages accrue from this design in that the usual forward extrapolation of the covariance matrix of estimation errors can be avoided without incurring unacceptable system errors. Simulation data for earth orbiting satellites are provided to substantiate this assertion.

29 CFR 18.7 - Prehearing statements.

Code of Federal Regulations, 2011 CFR

2011-07-01

... to reach stipulation to the fullest extent possible; (3) Facts in dispute; (4) Witnesses, except to... location of hearing and estimated time required for presentation of the party's or parties' case; (8) Any...

Rain volume estimation over areas using satellite and radar data

NASA Technical Reports Server (NTRS)

Doneaud, A. A.; Vonderhaar, T. H.

1985-01-01

The feasibility of rain volume estimation over fixed and floating areas was investigated using rapid scan satellite data following a technique recently developed with radar data, called the Area Time Integral (ATI) technique. The radar and rapid scan GOES satellite data were collected during the Cooperative Convective Precipitation Experiment (CCOPE) and North Dakota Cloud Modification Project (NDCMP). Six multicell clusters and cells were analyzed to the present time. A two-cycle oscillation emphasizing the multicell character of the clusters is demonstrated. Three clusters were selected on each day, 12 June and 2 July. The 12 June clusters occurred during the daytime, while the 2 July clusters during the nighttime. A total of 86 time steps of radar and 79 time steps of satellite images were analyzed. There were approximately 12-min time intervals between radar scans on the average.

Marginal regression analysis of recurrent events with coarsened censoring times.

PubMed

Hu, X Joan; Rosychuk, Rhonda J

2016-12-01

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

Mediation Analysis with Survival Outcomes: Accelerated Failure Time vs. Proportional Hazards Models.

PubMed

Gelfand, Lois A; MacKinnon, David P; DeRubeis, Robert J; Baraldi, Amanda N

2016-01-01

Survival time is an important type of outcome variable in treatment research. Currently, limited guidance is available regarding performing mediation analyses with survival outcomes, which generally do not have normally distributed errors, and contain unobserved (censored) events. We present considerations for choosing an approach, using a comparison of semi-parametric proportional hazards (PH) and fully parametric accelerated failure time (AFT) approaches for illustration. We compare PH and AFT models and procedures in their integration into mediation models and review their ability to produce coefficients that estimate causal effects. Using simulation studies modeling Weibull-distributed survival times, we compare statistical properties of mediation analyses incorporating PH and AFT approaches (employing SAS procedures PHREG and LIFEREG, respectively) under varied data conditions, some including censoring. A simulated data set illustrates the findings. AFT models integrate more easily than PH models into mediation models. Furthermore, mediation analyses incorporating LIFEREG produce coefficients that can estimate causal effects, and demonstrate superior statistical properties. Censoring introduces bias in the coefficient estimate representing the treatment effect on outcome-underestimation in LIFEREG, and overestimation in PHREG. With LIFEREG, this bias can be addressed using an alternative estimate obtained from combining other coefficients, whereas this is not possible with PHREG. When Weibull assumptions are not violated, there are compelling advantages to using LIFEREG over PHREG for mediation analyses involving survival-time outcomes. Irrespective of the procedures used, the interpretation of coefficients, effects of censoring on coefficient estimates, and statistical properties should be taken into account when reporting results.

The first step toward genetic selection for host tolerance to infectious pathogens: obtaining the tolerance phenotype through group estimates

PubMed Central

Doeschl-Wilson, Andrea B.; Villanueva, Beatriz; Kyriazakis, Ilias

2012-01-01

Reliable phenotypes are paramount for meaningful quantification of genetic variation and for estimating individual breeding values on which genetic selection is based. In this paper, we assert that genetic improvement of host tolerance to disease, although desirable, may be first of all handicapped by the ability to obtain unbiased tolerance estimates at a phenotypic level. In contrast to resistance, which can be inferred by appropriate measures of within host pathogen burden, tolerance is more difficult to quantify as it refers to change in performance with respect to changes in pathogen burden. For this reason, tolerance phenotypes have only been specified at the level of a group of individuals, where such phenotypes can be estimated using regression analysis. However, few stsudies have raised the potential bias in these estimates resulting from confounding effects between resistance and tolerance. Using a simulation approach, we demonstrate (i) how these group tolerance estimates depend on within group variation and co-variation in resistance, tolerance, and vigor (performance in a pathogen free environment); and (ii) how tolerance estimates are affected by changes in pathogen virulence over the time course of infection and by the timing of measurements. We found that in order to obtain reliable group tolerance estimates, it is important to account for individual variation in vigor, if present, and that all individuals are at the same stage of infection when measurements are taken. The latter requirement makes estimation of tolerance based on cross-sectional field data challenging, as individuals become infected at different time points and the individual onset of infection is unknown. Repeated individual measurements of within host pathogen burden and performance would not only be valuable for inferring the infection status of individuals in field conditions, but would also provide tolerance estimates that capture the entire time course of infection. PMID:23412990

A multi-camera system for real-time pose estimation

NASA Astrophysics Data System (ADS)

Savakis, Andreas; Erhard, Matthew; Schimmel, James; Hnatow, Justin

2007-04-01

This paper presents a multi-camera system that performs face detection and pose estimation in real-time and may be used for intelligent computing within a visual sensor network for surveillance or human-computer interaction. The system consists of a Scene View Camera (SVC), which operates at a fixed zoom level, and an Object View Camera (OVC), which continuously adjusts its zoom level to match objects of interest. The SVC is set to survey the whole filed of view. Once a region has been identified by the SVC as a potential object of interest, e.g. a face, the OVC zooms in to locate specific features. In this system, face candidate regions are selected based on skin color and face detection is accomplished using a Support Vector Machine classifier. The locations of the eyes and mouth are detected inside the face region using neural network feature detectors. Pose estimation is performed based on a geometrical model, where the head is modeled as a spherical object that rotates upon the vertical axis. The triangle formed by the mouth and eyes defines a vertical plane that intersects the head sphere. By projecting the eyes-mouth triangle onto a two dimensional viewing plane, equations were obtained that describe the change in its angles as the yaw pose angle increases. These equations are then combined and used for efficient pose estimation. The system achieves real-time performance for live video input. Testing results assessing system performance are presented for both still images and video.

Analysis of mean time to data loss of fault-tolerant disk arrays RAID-6 based on specialized Markov chain

NASA Astrophysics Data System (ADS)

Rahman, P. A.; D'K Novikova Freyre Shavier, G.

2018-03-01

This scientific paper is devoted to the analysis of the mean time to data loss of redundant disk arrays RAID-6 with alternation of data considering different failure rates of disks both in normal state of the disk array and in degraded and rebuild states, and also nonzero time of the disk replacement. The reliability model developed by the authors on the basis of the Markov chain and obtained calculation formula for estimation of the mean time to data loss (MTTDL) of the RAID-6 disk arrays are also presented. At last, the technique of estimation of the initial reliability parameters and examples of calculation of the MTTDL of the RAID-6 disk arrays for the different numbers of disks are also given.

Cost-benefit analysis of the 55-mph speed limit

DOE Office of Scientific and Technical Information (OSTI.GOV)

Forester, T.H.; McNown, R.F.; Singell, L.D.

1984-01-01

This article presents the results of an empirical study which estimates the number of reduced fatalities as a result of the imposed 55-mph speed limit. Time series data for the US from 1952 to 1979 is employed in a regression model capturing the relation between fatalities, average speed, variability of speed, and the speed limit. Also discussed are the alternative approaches to valuing human life and the value of time. Provided is a series of benefit-cost ratios based on alternative measures of the benefits and costs from life saving. The paper concludes that the 55-mph speed limit is not costmore » efficient unless additional time on the highway is valued significantly below levels estimated in the best reasearch on the value of time. 12 references, 1 table.« less

Finding the Age of the Earth by Physics or by Faith?

ERIC Educational Resources Information Center

Brush, Stephen G.

1982-01-01

Refutes scientific creationists' arguments that the earth is less than 10,000 years old by presenting information related to the time scales for creation and evolution models, times from stellar distances, Kelvin's estimate of the earth's age, radioactive decay, radiometric dating, and the decay of the earth's magnetic field. (DC)

Characterizing the uncertainty of classification methods and its impact on the performance of crowdsourcing

NASA Astrophysics Data System (ADS)

Ribera, Javier; Tahboub, Khalid; Delp, Edward J.

2015-03-01

Video surveillance systems are widely deployed for public safety. Real-time monitoring and alerting are some of the key requirements for building an intelligent video surveillance system. Real-life settings introduce many challenges that can impact the performance of real-time video analytics. Video analytics are desired to be resilient to adverse and changing scenarios. In this paper we present various approaches to characterize the uncertainty of a classifier and incorporate crowdsourcing at the times when the method is uncertain about making a particular decision. Incorporating crowdsourcing when a real-time video analytic method is uncertain about making a particular decision is known as online active learning from crowds. We evaluate our proposed approach by testing a method we developed previously for crowd flow estimation. We present three different approaches to characterize the uncertainty of the classifier in the automatic crowd flow estimation method and test them by introducing video quality degradations. Criteria to aggregate crowdsourcing results are also proposed and evaluated. An experimental evaluation is conducted using a publicly available dataset.

Comparison of causality analysis on simultaneously measured fMRI and NIRS signals during motor tasks.

PubMed

Anwar, Abdul Rauf; Muthalib, Makii; Perrey, Stephane; Galka, Andreas; Granert, Oliver; Wolff, Stephan; Deuschl, Guenther; Raethjen, Jan; Heute, Ulrich; Muthuraman, Muthuraman

2013-01-01

Brain activity can be measured using different modalities. Since most of the modalities tend to complement each other, it seems promising to measure them simultaneously. In to be presented research, the data recorded from Functional Magnetic Resonance Imaging (fMRI) and Near Infrared Spectroscopy (NIRS), simultaneously, are subjected to causality analysis using time-resolved partial directed coherence (tPDC). Time-resolved partial directed coherence uses the principle of state space modelling to estimate Multivariate Autoregressive (MVAR) coefficients. This method is useful to visualize both frequency and time dynamics of causality between the time series. Afterwards, causality results from different modalities are compared by estimating the Spearman correlation. In to be presented study, we used directionality vectors to analyze correlation, rather than actual signal vectors. Results show that causality analysis of the fMRI correlates more closely to causality results of oxy-NIRS as compared to deoxy-NIRS in case of a finger sequencing task. However, in case of simple finger tapping, no clear difference between oxy-fMRI and deoxy-fMRI correlation is identified.

Quantification of uncertainty associated with United States high resolution fossil fuel CO2 emissions: updates, challenges and future plans

NASA Astrophysics Data System (ADS)

Gurney, K. R.; Chandrasekaran, V.; Mendoza, D. L.; Geethakumar, S.

2010-12-01

The Vulcan Project has estimated United States fossil fuel CO2 emissions at the hourly time scale and at spatial scales below the county level for the year 2002. Vulcan is built from a wide variety of observational data streams including regulated air pollutant emissions reporting, traffic monitoring, energy statistics, and US census data. In addition to these data sets, Vulcan relies on a series of modeling assumptions and constructs to interpolate in space, time and transform non-CO2 reporting into an estimate of CO2 combustion emissions. The recent version 2.0 of the Vulcan inventory has produced advances in a number of categories with particular emphasis on improved temporal structure. Onroad transportation emissions now avail of roughly 5000 automated traffic count monitors allowing for much improved diurnal and weekly time structure in our onroad transportation emissions. Though the inventory shows excellent agreement with independent national-level CO2 emissions estimates, uncertainty quantification has been a challenging task given the large number of data sources and numerous modeling assumptions. However, we have now accomplished a complete uncertainty estimate across all the Vulcan economic sectors and will present uncertainty estimates as a function of space, time, sector and fuel. We find that, like the underlying distribution of CO2 emissions themselves, the uncertainty is also strongly lognormal with high uncertainty associated with a relatively small number of locations. These locations typically are locations reliant upon coal combustion as the dominant CO2 source. We will also compare and contrast Vulcan fossil fuel CO2 emissions estimates against estimates built from DOE fuel-based surveys at the state level. We conclude that much of the difference between the Vulcan inventory and DOE statistics are not due to biased estimation but mechanistic differences in supply versus demand and combustion in space/time.

Position Estimation for Switched Reluctance Motor Based on the Single Threshold Angle

NASA Astrophysics Data System (ADS)

Zhang, Lei; Li, Pang; Yu, Yue

2017-05-01

This paper presents a position estimate model of switched reluctance motor based on the single threshold angle. In view of the relationship of between the inductance and rotor position, the position is estimated by comparing the real-time dynamic flux linkage with the threshold angle position flux linkage (7.5° threshold angle, 12/8SRM). The sensorless model is built by Maltab/Simulink, the simulation are implemented under the steady state and transient state different condition, and verified its validity and feasibility of the method..

Theoretical and simulated performance for a novel frequency estimation technique

NASA Technical Reports Server (NTRS)

Crozier, Stewart N.

1993-01-01

A low complexity, open-loop, discrete-time, delay-multiply-average (DMA) technique for estimating the frequency offset for digitally modulated MPSK signals is investigated. A nonlinearity is used to remove the MPSK modulation and generate the carrier component to be extracted. Theoretical and simulated performance results are presented and compared to the Cramer-Rao lower bound (CRLB) for the variance of the frequency estimation error. For all signal-to-noise ratios (SNR's) above threshold, it is shown that the CRLB can essentially be achieved with linear complexity.

Survival analysis with error-prone time-varying covariates: a risk set calibration approach

PubMed Central

Liao, Xiaomei; Zucker, David M.; Li, Yi; Spiegelman, Donna

2010-01-01

Summary Occupational, environmental, and nutritional epidemiologists are often interested in estimating the prospective effect of time-varying exposure variables such as cumulative exposure or cumulative updated average exposure, in relation to chronic disease endpoints such as cancer incidence and mortality. From exposure validation studies, it is apparent that many of the variables of interest are measured with moderate to substantial error. Although the ordinary regression calibration approach is approximately valid and efficient for measurement error correction of relative risk estimates from the Cox model with time-independent point exposures when the disease is rare, it is not adaptable for use with time-varying exposures. By re-calibrating the measurement error model within each risk set, a risk set regression calibration method is proposed for this setting. An algorithm for a bias-corrected point estimate of the relative risk using an RRC approach is presented, followed by the derivation of an estimate of its variance, resulting in a sandwich estimator. Emphasis is on methods applicable to the main study/external validation study design, which arises in important applications. Simulation studies under several assumptions about the error model were carried out, which demonstrated the validity and efficiency of the method in finite samples. The method was applied to a study of diet and cancer from Harvard’s Health Professionals Follow-up Study (HPFS). PMID:20486928

A-Posteriori Error Estimation for Hyperbolic Conservation Laws with Constraint

NASA Technical Reports Server (NTRS)

Barth, Timothy

2004-01-01

This lecture considers a-posteriori error estimates for the numerical solution of conservation laws with time invariant constraints such as those arising in magnetohydrodynamics (MHD) and gravitational physics. Using standard duality arguments, a-posteriori error estimates for the discontinuous Galerkin finite element method are then presented for MHD with solenoidal constraint. From these estimates, a procedure for adaptive discretization is outlined. A taxonomy of Green's functions for the linearized MHD operator is given which characterizes the domain of dependence for pointwise errors. The extension to other constrained systems such as the Einstein equations of gravitational physics are then considered. Finally, future directions and open problems are discussed.

Ground and Helicopter Emergency Medical Services Time Tradeoffs Assessed with Geographic Information.

PubMed

Widener, Michael J; Ginsberg, Zac; Schleith, Daniel; Floccare, Douglas J; Hirshon, Jon Mark; Galvagno, Samuel

2015-07-01

We describe how geographic information systems (GIS) can be used to assess and compare estimated transport time for helicopter and ground emergency medical services. Recent research shows that while the odds of a trauma patient's survival increase with helicopter emergency medical services (HEMS), they may not increase to the extent necessary to make HEMS cost effective. This study offers an analytic tool to objectively quantify the patient travel time advantage that HEMS offers compared to ground emergency medical services (GEMS). Using helicopter dispatch data from the Maryland State Police from 2000-2011, we computed transport time estimates for HEMS and GEMS, compare these results to a reference transport time of 60 min, and use geospatial interpolation to extrapolate the total response times for each mode across the study region. Mapping the region's trauma incidents and modeling response times, our findings indicate the GIS framework for calculating transportation time tradeoffs is useful in identifying which areas can be better served by HEMS or GEMS. The use of GIS and the analytical methodology described in this study present a method to compare transportation by air and ground in the prehospital setting that accounts for how mode, distance, and road infrastructure impact total transport time. Whether used to generate regional maps in advance or applied real-time, the presented framework provides a tool to identify earlier incident locations that favor HEMS over GEMS transport modes.

What can we learn about Mars from satellite magnetic field measurements?

NASA Astrophysics Data System (ADS)

Morschhauser, A.; Mittelholz, A.; Thomas, P.; Vervelidou, F.; Grott, M.; Johnson, C.; Lesur, V.; Lillis, R. J.

2017-12-01

The Mars orbiters MGS and MAVEN provide vector magnetic field data for Mars at a variety of altitudes, locations, and local times. In spite of the abundance of data, there are many open questions concerning the crustal magnetic field of Mars. In this contribution, we present our efforts to estimate the shutdown time of the Martian core dynamo and to estimate Martian paleopole locations, using magnetic field satellite data and models derived from these data [1]. Models are primarily based on MGS data, and we shortly present our recent advances to include MAVEN data. There exists some controversy concerning the timing of the Martian core dynamo shutdown [e.g., 2-5]. We address this question by studying the so-called visible magnetization [6-7] of impact craters larger than 400 km in diameter, and conclude that the dynamo ceased to operate in the Noachian period [8]. Further, paleopole locations have been used to constrain the dynamics of the Martian core dynamo [e.g. 4-5, 9]. However, such estimates are limited by the inherent non-uniqueness of inferring magnetization from magnetic field measurements. Here, we discuss how estimated paleopoles are influenced by this non-uniqueness and the limited signal-to-noise ratio of satellite measurements [6]. Furthermore, we discuss how paleopole locations may still be obtained from satellite magnetic field measurements. In this context, we present some new paleopole estimates for Mars including estimates of uncertainties. References: [1] A. Morschhauser et al. (2014), JGR, doi: 10.1002/2013JE004555 [2] R.J. Lillis et al. (2015), JGR, doi: 10.1002/2014je004774 [3] L.L. Hood et al. (2010), Icarus, doi: 10.1016/j.icarus.2010.01.009 [4] C. Milbury et al. (2012), JGR, doi: 10.1029/2012JE004099 [5] B. Langlais and M. Purucker (2007), PSS, 10.1016/j.pss.2006.03.008 [6] F. Vervelidou et al., On the accuracy of paleopole estimations from magnetic field measurements, GJI, under revision 2017 [7] D. Gubbins et al. (2011), GJI, doi: 10.1111/j.1365-246X.2011.05153.x [8] B. Langlais and M. Purucker (2007), PSS, 10.1016/j.pss.2006.03.008 [8] F. Vervelidou et al., Constraining the date of the martian dynamo shutdown by means of craters' magnetization signatures, JGR, submitted 2017 [9] J. Arkani-Hamed and D. Boutin (2004), JGR, 10.1029/2003JE002229

Basic research for the Earth dynamics program

NASA Technical Reports Server (NTRS)

Mueller, I. I.

1981-01-01

A comparison of data from Project MERIT Short Campaign is presented. The time delay weight matrix in VLBI geodetic parameter estimation was investigated. The utilization of range difference observations in geodynamics is discussed.

46 CFR 502.95 - Prehearing statements.

Code of Federal Regulations, 2011 CFR

2011-10-01

... the party or parties have communicated or conferred in a good faith effort to reach stipulation to the... location of hearing and estimated time required for presentation of the party's or parties' case. (8) Any...

Modeling, Real-Time Estimation, and Identification of UWB Indoor Wireless Channels

DOE PAGES

Olama, Mohammed M.; Djouadi, Seddik M.; Li, Yanyan; ...

2013-01-01

Stochastic differential equations (SDEs) are used to model ultrawideband (UWB) indoor wireless channels. We show that the impulse responses for time-varying indoor wireless channels can be approximated in a mean-square sense as close as desired by impulse responses that can be realized by SDEs. The state variables represent the inphase and quadrature components of the UWB channel. The expected maximization and extended Kalman filter are employed to recursively identify and estimate the channel parameters and states, respectively, from online received signal strength measured data. Both resolvable and nonresolvable multipath received signals are considered and represented as small-scaled Nakagami fading. Themore » proposed models together with the estimation algorithm are tested using UWB indoor measurement data demonstrating the method’s viability and the results are presented.« less

On the measurement of pilot perceptual workload - A comparison of assessment techniques addressing sensitivity and intrusion issues

NASA Technical Reports Server (NTRS)

Casali, J. G.; Wierwille, W. W.

1984-01-01

A flight simulator-based study was conducted to examine fourteen distinct mental workload estimation measures, including opinion, secondary task, physiological, and primary task measures. Both the relative sensitivity of the measures to changes in mental workload and the differential intrusion of the changes on primary task performance were assessed. The flight task was varied in difficulty by manipulation of the presentation rate and complexity of a hazard-perception task that required each of 48 licensed pilots to rely heavily on their perceptual abilities. Three rating scales (Modified Cooper-Harper, Multi-descriptor, and Workload-Compensation-Interference/Technical Effectiveness), two secondary task measures (time estimation and tapping regularity), one physiological measure (respiration frequency), and one primary task measure (danger-condition response time) were reliable indicants of workload changes. Recommendations for applying the workload measures are presented.

Charge Transfer Inefficiency in Pinned Photodiode CMOS image sensors: Simple Montecarlo modeling and experimental measurement based on a pulsed storage-gate method

NASA Astrophysics Data System (ADS)

Pelamatti, Alice; Goiffon, Vincent; Chabane, Aziouz; Magnan, Pierre; Virmontois, Cédric; Saint-Pé, Olivier; de Boisanger, Michel Breart

2016-11-01

The charge transfer time represents the bottleneck in terms of temporal resolution in Pinned Photodiode (PPD) CMOS image sensors. This work focuses on the modeling and estimation of this key parameter. A simple numerical model of charge transfer in PPDs is presented. The model is based on a Montecarlo simulation and takes into account both charge diffusion in the PPD and the effect of potential obstacles along the charge transfer path. This work also presents a new experimental approach for the estimation of the charge transfer time, called pulsed Storage Gate (SG) method. This method, which allows reproduction of a ;worst-case; transfer condition, is based on dedicated SG pixel structures and is particularly suitable to compare transfer efficiency performances for different pixel geometries.

Potential for bias and low precision in molecular divergence time estimation of the Canopy of Life: an example from aquatic bird families

PubMed Central

van Tuinen, Marcel; Torres, Christopher R.

2015-01-01

Uncertainty in divergence time estimation is frequently studied from many angles but rarely from the perspective of phylogenetic node age. If appropriate molecular models and fossil priors are used, a multi-locus, partitioned analysis is expected to equally minimize error in accuracy and precision across all nodes of a given phylogeny. In contrast, if available models fail to completely account for rate heterogeneity, substitution saturation and incompleteness of the fossil record, uncertainty in divergence time estimation may increase with node age. While many studies have stressed this concern with regard to deep nodes in the Tree of Life, the inference that molecular divergence time estimation of shallow nodes is less sensitive to erroneous model choice has not been tested explicitly in a Bayesian framework. Because of available divergence time estimation methods that permit fossil priors across any phylogenetic node and the present increase in efficient, cheap collection of species-level genomic data, insight is needed into the performance of divergence time estimation of shallow (<10 MY) nodes. Here, we performed multiple sensitivity analyses in a multi-locus data set of aquatic birds with six fossil constraints. Comparison across divergence time analyses that varied taxon and locus sampling, number and position of fossil constraint and shape of prior distribution showed various insights. Deviation from node ages obtained from a reference analysis was generally highest for the shallowest nodes but determined more by temporal placement than number of fossil constraints. Calibration with only the shallowest nodes significantly underestimated the aquatic bird fossil record, indicating the presence of saturation. Although joint calibration with all six priors yielded ages most consistent with the fossil record, ages of shallow nodes were overestimated. This bias was found in both mtDNA and nDNA regions. Thus, divergence time estimation of shallow nodes may suffer from bias and low precision, even when appropriate fossil priors and best available substitution models are chosen. Much care must be taken to address the possible ramifications of substitution saturation across the entire Tree of Life. PMID:26106406