Ambient temperature and biomarkers of heart failure: a repeated measures analysis.

PubMed

Wilker, Elissa H; Yeh, Gloria; Wellenius, Gregory A; Davis, Roger B; Phillips, Russell S; Mittleman, Murray A

2012-08-01

Extreme temperatures have been associated with hospitalization and death among individuals with heart failure, but few studies have explored the underlying mechanisms. We hypothesized that outdoor temperature in the Boston, Massachusetts, area (1- to 4-day moving averages) would be associated with higher levels of biomarkers of inflammation and myocyte injury in a repeated-measures study of individuals with stable heart failure. We analyzed data from a completed clinical trial that randomized 100 patients to 12 weeks of tai chi classes or to time-matched education control. B-type natriuretic peptide (BNP), C-reactive protein (CRP), and tumor necrosis factor (TNF) were measured at baseline, 6 weeks, and 12 weeks. Endothelin-1 was measured at baseline and 12 weeks. We used fixed effects models to evaluate associations with measures of temperature that were adjusted for time-varying covariates. Higher apparent temperature was associated with higher levels of BNP beginning with 2-day moving averages and reached statistical significance for 3- and 4-day moving averages. CRP results followed a similar pattern but were delayed by 1 day. A 5°C change in 3- and 4-day moving averages of apparent temperature was associated with 11.3% [95% confidence interval (CI): 1.1, 22.5; p = 0.03) and 11.4% (95% CI: 1.2, 22.5; p = 0.03) higher BNP. A 5°C change in the 4-day moving average of apparent temperature was associated with 21.6% (95% CI: 2.5, 44.2; p = 0.03) higher CRP. No clear associations with TNF or endothelin-1 were observed. Among patients undergoing treatment for heart failure, we observed positive associations between temperature and both BNP and CRP-predictors of heart failure prognosis and severity.

Work-related accidents among the Iranian population: a time series analysis, 2000–2011

PubMed Central

Karimlou, Masoud; Imani, Mehdi; Hosseini, Agha-Fatemeh; Dehnad, Afsaneh; Vahabi, Nasim; Bakhtiyari, Mahmood

2015-01-01

Background Work-related accidents result in human suffering and economic losses and are considered as a major health problem worldwide, especially in the economically developing world. Objectives To introduce seasonal autoregressive moving average (ARIMA) models for time series analysis of work-related accident data for workers insured by the Iranian Social Security Organization (ISSO) between 2000 and 2011. Methods In this retrospective study, all insured people experiencing at least one work-related accident during a 10-year period were included in the analyses. We used Box–Jenkins modeling to develop a time series model of the total number of accidents. Results There was an average of 1476 accidents per month (1476·05±458·77, mean±SD). The final ARIMA (p,d,q) (P,D,Q)s model for fitting to data was: ARIMA(1,1,1)×(0,1,1)12 consisting of the first ordering of the autoregressive, moving average and seasonal moving average parameters with 20·942 mean absolute percentage error (MAPE). Conclusions The final model showed that time series analysis of ARIMA models was useful for forecasting the number of work-related accidents in Iran. In addition, the forecasted number of work-related accidents for 2011 explained the stability of occurrence of these accidents in recent years, indicating a need for preventive occupational health and safety policies such as safety inspection. PMID:26119774

Work-related accidents among the Iranian population: a time series analysis, 2000-2011.

PubMed

Karimlou, Masoud; Salehi, Masoud; Imani, Mehdi; Hosseini, Agha-Fatemeh; Dehnad, Afsaneh; Vahabi, Nasim; Bakhtiyari, Mahmood

2015-01-01

Work-related accidents result in human suffering and economic losses and are considered as a major health problem worldwide, especially in the economically developing world. To introduce seasonal autoregressive moving average (ARIMA) models for time series analysis of work-related accident data for workers insured by the Iranian Social Security Organization (ISSO) between 2000 and 2011. In this retrospective study, all insured people experiencing at least one work-related accident during a 10-year period were included in the analyses. We used Box-Jenkins modeling to develop a time series model of the total number of accidents. There was an average of 1476 accidents per month (1476·05±458·77, mean±SD). The final ARIMA (p,d,q) (P,D,Q)s model for fitting to data was: ARIMA(1,1,1)×(0,1,1)12 consisting of the first ordering of the autoregressive, moving average and seasonal moving average parameters with 20·942 mean absolute percentage error (MAPE). The final model showed that time series analysis of ARIMA models was useful for forecasting the number of work-related accidents in Iran. In addition, the forecasted number of work-related accidents for 2011 explained the stability of occurrence of these accidents in recent years, indicating a need for preventive occupational health and safety policies such as safety inspection.

The change of sleeping and lying posture of Japanese black cows after moving into new environment.

PubMed

Fukasawa, Michiru; Komatsu, Tokushi; Higashiyama, Yumi

2018-04-25

The environmental change is one of the stressful events in livestock production. Change in environment disturbed cow behavior and cows needed several days to reach stable behavioral pattern, especially sleeping posture (SP) and lying posture (LP) have been used as an indicator for relax and well-acclimated to its environment. The aim of this study examines how long does Japanese black cow required for stabilization of SP and LP after moving into new environment. Seven pregnant Japanese black cows were used. Cows were moved into new tie-stall shed and measured sleeping and lying posture 17 times during 35 experimental days. Both SP and LP were detected by accelerometer fixed on middle occipital and hip-cross, respectively. Daily total time, frequency, and average bout of both SP and LP were calculated. Daily SP time was the shortest on day 1, and increased to the highest on day3. It decreased until day 9, after that stabilized about 65 min /day till the end of experiment. The longest average SP bout was shown on day 1, and it decreased to stabilize till day 7. Daily LP time was changed as same manner as daily SP time. The average SP bout showed the longest on day 1, and it decreased to stable level till day 7. On the other hand, the average LP bout showed the shortest on day1, and it was increased to stable level till on day 7. These results showed that pregnant Japanese black cows needed 1 week to stabilize their SP. However, there were different change pattern between the average SP and LP bout, even though the change pattern of daily SP and LP time were similar.

A New Trend-Following Indicator: Using SSA to Design Trading Rules

NASA Astrophysics Data System (ADS)

Leles, Michel Carlo Rodrigues; Mozelli, Leonardo Amaral; Guimarães, Homero Nogueira

Singular Spectrum Analysis (SSA) is a non-parametric approach that can be used to decompose a time-series as trends, oscillations and noise. Trend-following strategies rely on the principle that financial markets move in trends for an extended period of time. Moving Averages (MAs) are the standard indicator to design such strategies. In this study, SSA is used as an alternative method to enhance trend resolution in comparison with the traditional MA. New trading rules using SSA as indicator are proposed. This paper shows that for the Down Jones Industrial Average (DJIA) and Shangai Securities Composite Index (SSCI) time-series the SSA trading rules provided, in general, better results in comparison to MA trading rules.

Iterative Procedures for Exact Maximum Likelihood Estimation in the First-Order Gaussian Moving Average Model

DTIC Science & Technology

1990-11-01

1 = Q- 1 - 1 QlaaQ- 1.1 + a’Q-1a This is a simple case of a general formula called Woodbury’s formula by some authors; see, for example, Phadke and...1 2. The First-Order Moving Average Model ..... .................. 3. Some Approaches to the Iterative...the approximate likelihood function in some time series models. Useful suggestions have been the Cholesky decomposition of the covariance matrix and

THE VELOCITY DISTRIBUTION OF NEARBY STARS FROM HIPPARCOS DATA. II. THE NATURE OF THE LOW-VELOCITY MOVING GROUPS

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

Bovy, Jo; Hogg, David W., E-mail: jo.bovy@nyu.ed

2010-07-10

The velocity distribution of nearby stars ({approx}<100 pc) contains many overdensities or 'moving groups', clumps of comoving stars, that are inconsistent with the standard assumption of an axisymmetric, time-independent, and steady-state Galaxy. We study the age and metallicity properties of the low-velocity moving groups based on the reconstruction of the local velocity distribution in Paper I of this series. We perform stringent, conservative hypothesis testing to establish for each of these moving groups whether it could conceivably consist of a coeval population of stars. We conclude that they do not: the moving groups are neither trivially associated with their eponymousmore » open clusters nor with any other inhomogeneous star formation event. Concerning a possible dynamical origin of the moving groups, we test whether any of the moving groups has a higher or lower metallicity than the background population of thin disk stars, as would generically be the case if the moving groups are associated with resonances of the bar or spiral structure. We find clear evidence that the Hyades moving group has higher than average metallicity and weak evidence that the Sirius moving group has lower than average metallicity, which could indicate that these two groups are related to the inner Lindblad resonance of the spiral structure. Further, we find weak evidence that the Hercules moving group has higher than average metallicity, as would be the case if it is associated with the bar's outer Lindblad resonance. The Pleiades moving group shows no clear metallicity anomaly, arguing against a common dynamical origin for the Hyades and Pleiades groups. Overall, however, the moving groups are barely distinguishable from the background population of stars, raising the likelihood that the moving groups are associated with transient perturbations.« less

A novel approach to estimate emissions from large transportation networks: Hierarchical clustering-based link-driving-schedules for EPA-MOVES using dynamic time warping measures

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

Aziz, H. M. Abdul; Ukkusuri, Satish V.

We present that EPA-MOVES (Motor Vehicle Emission Simulator) is often integrated with traffic simulators to assess emission levels of large-scale urban networks with signalized intersections. High variations in speed profiles exist in the context of congested urban networks with signalized intersections. The traditional average-speed-based emission estimation technique with EPA-MOVES provides faster execution while underestimates the emissions in most cases because of ignoring the speed variation at congested networks with signalized intersections. In contrast, the atomic second-by-second speed profile (i.e., the trajectory of each vehicle)-based technique provides accurate emissions at the cost of excessive computational power and time. We addressed thismore » issue by developing a novel method to determine the link-driving-schedules (LDSs) for the EPA-MOVES tool. Our research developed a hierarchical clustering technique with dynamic time warping similarity measures (HC-DTW) to find the LDS for EPA-MOVES that is capable of producing emission estimates better than the average-speed-based technique with execution time faster than the atomic speed profile approach. We applied the HC-DTW on a sample data from a signalized corridor and found that HC-DTW can significantly reduce computational time without compromising the accuracy. The developed technique in this research can substantially contribute to the EPA-MOVES-based emission estimation process for large-scale urban transportation network by reducing the computational time with reasonably accurate estimates. This method is highly appropriate for transportation networks with higher variation in speed such as signalized intersections. Lastly, experimental results show error difference ranging from 2% to 8% for most pollutants except PM 10.« less

A novel approach to estimate emissions from large transportation networks: Hierarchical clustering-based link-driving-schedules for EPA-MOVES using dynamic time warping measures

DOE PAGES

Aziz, H. M. Abdul; Ukkusuri, Satish V.

2017-06-29

We present that EPA-MOVES (Motor Vehicle Emission Simulator) is often integrated with traffic simulators to assess emission levels of large-scale urban networks with signalized intersections. High variations in speed profiles exist in the context of congested urban networks with signalized intersections. The traditional average-speed-based emission estimation technique with EPA-MOVES provides faster execution while underestimates the emissions in most cases because of ignoring the speed variation at congested networks with signalized intersections. In contrast, the atomic second-by-second speed profile (i.e., the trajectory of each vehicle)-based technique provides accurate emissions at the cost of excessive computational power and time. We addressed thismore » issue by developing a novel method to determine the link-driving-schedules (LDSs) for the EPA-MOVES tool. Our research developed a hierarchical clustering technique with dynamic time warping similarity measures (HC-DTW) to find the LDS for EPA-MOVES that is capable of producing emission estimates better than the average-speed-based technique with execution time faster than the atomic speed profile approach. We applied the HC-DTW on a sample data from a signalized corridor and found that HC-DTW can significantly reduce computational time without compromising the accuracy. The developed technique in this research can substantially contribute to the EPA-MOVES-based emission estimation process for large-scale urban transportation network by reducing the computational time with reasonably accurate estimates. This method is highly appropriate for transportation networks with higher variation in speed such as signalized intersections. Lastly, experimental results show error difference ranging from 2% to 8% for most pollutants except PM 10.« less

Alternatives to the Moving Average

Treesearch

Paul C. van Deusen

2001-01-01

There are many possible estimators that could be used with annual inventory data. The 5-year moving average has been selected as a default estimator to provide initial results for states having available annual inventory data. User objectives for these estimates are discussed. The characteristics of a moving average are outlined. It is shown that moving average...

Time series modelling of increased soil temperature anomalies during long period

NASA Astrophysics Data System (ADS)

Shirvani, Amin; Moradi, Farzad; Moosavi, Ali Akbar

2015-10-01

Soil temperature just beneath the soil surface is highly dynamic and has a direct impact on plant seed germination and is probably the most distinct and recognisable factor governing emergence. Autoregressive integrated moving average as a stochastic model was developed to predict the weekly soil temperature anomalies at 10 cm depth, one of the most important soil parameters. The weekly soil temperature anomalies for the periods of January1986-December 2011 and January 2012-December 2013 were taken into consideration to construct and test autoregressive integrated moving average models. The proposed model autoregressive integrated moving average (2,1,1) had a minimum value of Akaike information criterion and its estimated coefficients were different from zero at 5% significance level. The prediction of the weekly soil temperature anomalies during the test period using this proposed model indicated a high correlation coefficient between the observed and predicted data - that was 0.99 for lead time 1 week. Linear trend analysis indicated that the soil temperature anomalies warmed up significantly by 1.8°C during the period of 1986-2011.

Substorm-related plasma sheet motions as determined from differential timing of plasma changes at the ISEE satellites

NASA Technical Reports Server (NTRS)

Forbes, T. G.; Hones, E. W., Jr.; Bame, S. J.; Asbridge, J. R.; Paschmann, G.; Sckopke, N.; Russell, C. T.

1981-01-01

From an ISEE survey of substorm dropouts and recoveries during the period February 5 to May 25, 1978, 66 timing events observed by the Los Alamos Scientific Laboratory/Max-Planck-Institut Fast Plasma Experiments were studied in detail. Near substorm onset, both the average timing velocity and the bulk flow velocity at the edge of the plasma sheet are inward, toward the center. Measured normal to the surface of the plasma sheet, the timing velocity is 23 + or - 18 km/s and the proton flow velocity is 20 + or - 8 km/s. During substorm recovery, the plasma sheet reappears moving outward with an average timing velocity of 133 + or - 31 km/s; however, the corresponding proton flow velocity is only 3 + or - 7 km/s in the same direction. It is suggested that the difference between the average timing velocity for the expansion of the plasma sheet and the plasma bulk flow perpendicular to the surface of the sheet during substorm recovery is most likely the result of surface waves moving past the position of the satellites.

Using Baidu Search Index to Predict Dengue Outbreak in China

NASA Astrophysics Data System (ADS)

Liu, Kangkang; Wang, Tao; Yang, Zhicong; Huang, Xiaodong; Milinovich, Gabriel J.; Lu, Yi; Jing, Qinlong; Xia, Yao; Zhao, Zhengyang; Yang, Yang; Tong, Shilu; Hu, Wenbiao; Lu, Jiahai

2016-12-01

This study identified the possible threshold to predict dengue fever (DF) outbreaks using Baidu Search Index (BSI). Time-series classification and regression tree models based on BSI were used to develop a predictive model for DF outbreak in Guangzhou and Zhongshan, China. In the regression tree models, the mean autochthonous DF incidence rate increased approximately 30-fold in Guangzhou when the weekly BSI for DF at the lagged moving average of 1-3 weeks was more than 382. When the weekly BSI for DF at the lagged moving average of 1-5 weeks was more than 91.8, there was approximately 9-fold increase of the mean autochthonous DF incidence rate in Zhongshan. In the classification tree models, the results showed that when the weekly BSI for DF at the lagged moving average of 1-3 weeks was more than 99.3, there was 89.28% chance of DF outbreak in Guangzhou, while, in Zhongshan, when the weekly BSI for DF at the lagged moving average of 1-5 weeks was more than 68.1, the chance of DF outbreak rose up to 100%. The study indicated that less cost internet-based surveillance systems can be the valuable complement to traditional DF surveillance in China.

The Hurst exponent in energy futures prices

NASA Astrophysics Data System (ADS)

Serletis, Apostolos; Rosenberg, Aryeh Adam

2007-07-01

This paper extends the work in Elder and Serletis [Long memory in energy futures prices, Rev. Financial Econ., forthcoming, 2007] and Serletis et al. [Detrended fluctuation analysis of the US stock market, Int. J. Bifurcation Chaos, forthcoming, 2007] by re-examining the empirical evidence for random walk type behavior in energy futures prices. In doing so, it uses daily data on energy futures traded on the New York Mercantile Exchange, over the period from July 2, 1990 to November 1, 2006, and a statistical physics approach-the ‘detrending moving average’ technique-providing a reliable framework for testing the information efficiency in financial markets as shown by Alessio et al. [Second-order moving average and scaling of stochastic time series, Eur. Phys. J. B 27 (2002) 197-200] and Carbone et al. [Time-dependent hurst exponent in financial time series. Physica A 344 (2004) 267-271; Analysis of clusters formed by the moving average of a long-range correlated time series. Phys. Rev. E 69 (2004) 026105]. The results show that energy futures returns display long memory and that the particular form of long memory is anti-persistence.

Forecast of Frost Days Based on Monthly Temperatures

NASA Astrophysics Data System (ADS)

Castellanos, M. T.; Tarquis, A. M.; Morató, M. C.; Saa-Requejo, A.

2009-04-01

Although frost can cause considerable crop damage and mitigation practices against forecasted frost exist, frost forecasting technologies have not changed for many years. The paper reports a new method to forecast the monthly number of frost days (FD) for several meteorological stations at Community of Madrid (Spain) based on successive application of two models. The first one is a stochastic model, autoregressive integrated moving average (ARIMA), that forecasts monthly minimum absolute temperature (tmin) and monthly average of minimum temperature (tminav) following Box-Jenkins methodology. The second model relates these monthly temperatures to minimum daily temperature distribution during one month. Three ARIMA models were identified for the time series analyzed with a stational period correspondent to one year. They present the same stational behavior (moving average differenced model) and different non-stational part: autoregressive model (Model 1), moving average differenced model (Model 2) and autoregressive and moving average model (Model 3). At the same time, the results point out that minimum daily temperature (tdmin), for the meteorological stations studied, followed a normal distribution each month with a very similar standard deviation through years. This standard deviation obtained for each station and each month could be used as a risk index for cold months. The application of Model 1 to predict minimum monthly temperatures showed the best FD forecast. This procedure provides a tool for crop managers and crop insurance companies to asses the risk of frost frequency and intensity, so that they can take steps to mitigate against frost damage and estimated the damage that frost would cost. This research was supported by Comunidad de Madrid Research Project 076/92. The cooperation of the Spanish National Meteorological Institute and the Spanish Ministerio de Agricultura, Pesca y Alimentation (MAPA) is gratefully acknowledged.

A monitoring tool for performance improvement in plastic surgery at the individual level.

PubMed

Maruthappu, Mahiben; Duclos, Antoine; Orgill, Dennis; Carty, Matthew J

2013-05-01

The assessment of performance in surgery is expanding significantly. Application of relevant frameworks to plastic surgery, however, has been limited. In this article, the authors present two robust graphic tools commonly used in other industries that may serve to monitor individual surgeon operative time while factoring in patient- and surgeon-specific elements. The authors reviewed performance data from all bilateral reduction mammaplasties performed at their institution by eight surgeons between 1995 and 2010. Operative time was used as a proxy for performance. Cumulative sum charts and exponentially weighted moving average charts were generated using a train-test analytic approach, and used to monitor surgical performance. Charts mapped crude, patient case-mix-adjusted, and case-mix and surgical-experience-adjusted performance. Operative time was found to decline from 182 minutes to 118 minutes with surgical experience (p < 0.001). Cumulative sum and exponentially weighted moving average charts were generated using 1995 to 2007 data (1053 procedures) and tested on 2008 to 2010 data (246 procedures). The sensitivity and accuracy of these charts were significantly improved by adjustment for case mix and surgeon experience. The consideration of patient- and surgeon-specific factors is essential for correct interpretation of performance in plastic surgery at the individual surgeon level. Cumulative sum and exponentially weighted moving average charts represent accurate methods of monitoring operative time to control and potentially improve surgeon performance over the course of a career.

KARMA4

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

Khalil, Mohammad; Salloum, Maher; Lee, Jina

2017-07-10

KARMA4 is a C++ library for autoregressive moving average (ARMA) modeling and forecasting of time-series data while incorporating both process and observation error. KARMA4 is designed for fitting and forecasting of time-series data for predictive purposes.

Heterogeneous CPU-GPU moving targets detection for UAV video

NASA Astrophysics Data System (ADS)

Li, Maowen; Tang, Linbo; Han, Yuqi; Yu, Chunlei; Zhang, Chao; Fu, Huiquan

2017-07-01

Moving targets detection is gaining popularity in civilian and military applications. On some monitoring platform of motion detection, some low-resolution stationary cameras are replaced by moving HD camera based on UAVs. The pixels of moving targets in the HD Video taken by UAV are always in a minority, and the background of the frame is usually moving because of the motion of UAVs. The high computational cost of the algorithm prevents running it at higher resolutions the pixels of frame. Hence, to solve the problem of moving targets detection based UAVs video, we propose a heterogeneous CPU-GPU moving target detection algorithm for UAV video. More specifically, we use background registration to eliminate the impact of the moving background and frame difference to detect small moving targets. In order to achieve the effect of real-time processing, we design the solution of heterogeneous CPU-GPU framework for our method. The experimental results show that our method can detect the main moving targets from the HD video taken by UAV, and the average process time is 52.16ms per frame which is fast enough to solve the problem.

Learning curves for single incision and conventional laparoscopic right hemicolectomy: a multidimensional analysis.

PubMed

Park, Yoonah; Yong, Yuen Geng; Yun, Seong Hyeon; Jung, Kyung Uk; Huh, Jung Wook; Cho, Yong Beom; Kim, Hee Cheol; Lee, Woo Yong; Chun, Ho-Kyung

2015-05-01

This study aimed to compare the learning curves and early postoperative outcomes for conventional laparoscopic (CL) and single incision laparoscopic (SIL) right hemicolectomy (RHC). This retrospective study included the initial 35 cases in each group. Learning curves were evaluated by the moving average of operative time, mean operative time of every five consecutive cases, and cumulative sum (CUSUM) analysis. The learning phase was considered overcome when the moving average of operative times reached a plateau, and when the mean operative time of every five consecutive cases reached a low point and subsequently did not vary by more than 30 minutes. Six patients with missing data in the CL RHC group were excluded from the analyses. According to the mean operative time of every five consecutive cases, learning phase of SIL and CL RHC was completed between 26 and 30 cases, and 16 and 20 cases, respectively. Moving average analysis revealed that approximately 31 (SIL) and 25 (CL) cases were needed to complete the learning phase, respectively. CUSUM analysis demonstrated that 10 (SIL) and two (CL) cases were required to reach a steady state of complication-free performance, respectively. Postoperative complications rate was higher in SIL than in CL group, but the difference was not statistically significant (17.1% vs. 3.4%). The learning phase of SIL RHC is longer than that of CL RHC. Early oncological outcomes of both techniques were comparable. However, SIL RHC had a statistically insignificant higher complication rate than CL RHC during the learning phase.

Queues with Choice via Delay Differential Equations

NASA Astrophysics Data System (ADS)

Pender, Jamol; Rand, Richard H.; Wesson, Elizabeth

Delay or queue length information has the potential to influence the decision of a customer to join a queue. Thus, it is imperative for managers of queueing systems to understand how the information that they provide will affect the performance of the system. To this end, we construct and analyze two two-dimensional deterministic fluid models that incorporate customer choice behavior based on delayed queue length information. In the first fluid model, customers join each queue according to a Multinomial Logit Model, however, the queue length information the customer receives is delayed by a constant Δ. We show that the delay can cause oscillations or asynchronous behavior in the model based on the value of Δ. In the second model, customers receive information about the queue length through a moving average of the queue length. Although it has been shown empirically that giving patients moving average information causes oscillations and asynchronous behavior to occur in U.S. hospitals, we analytically and mathematically show for the first time that the moving average fluid model can exhibit oscillations and determine their dependence on the moving average window. Thus, our analysis provides new insight on how operators of service systems should report queue length information to customers and how delayed information can produce unwanted system dynamics.

Modeling and roles of meteorological factors in outbreaks of highly pathogenic avian influenza H5N1.

PubMed

Biswas, Paritosh K; Islam, Md Zohorul; Debnath, Nitish C; Yamage, Mat

2014-01-01

The highly pathogenic avian influenza A virus subtype H5N1 (HPAI H5N1) is a deadly zoonotic pathogen. Its persistence in poultry in several countries is a potential threat: a mutant or genetically reassorted progenitor might cause a human pandemic. Its world-wide eradication from poultry is important to protect public health. The global trend of outbreaks of influenza attributable to HPAI H5N1 shows a clear seasonality. Meteorological factors might be associated with such trend but have not been studied. For the first time, we analyze the role of meteorological factors in the occurrences of HPAI outbreaks in Bangladesh. We employed autoregressive integrated moving average (ARIMA) and multiplicative seasonal autoregressive integrated moving average (SARIMA) to assess the roles of different meteorological factors in outbreaks of HPAI. Outbreaks were modeled best when multiplicative seasonality was incorporated. Incorporation of any meteorological variable(s) as inputs did not improve the performance of any multivariable models, but relative humidity (RH) was a significant covariate in several ARIMA and SARIMA models with different autoregressive and moving average orders. The variable cloud cover was also a significant covariate in two SARIMA models, but air temperature along with RH might be a predictor when moving average (MA) order at lag 1 month is considered.

Detrending moving average algorithm for multifractals

NASA Astrophysics Data System (ADS)

Gu, Gao-Feng; Zhou, Wei-Xing

2010-07-01

The detrending moving average (DMA) algorithm is a widely used technique to quantify the long-term correlations of nonstationary time series and the long-range correlations of fractal surfaces, which contains a parameter θ determining the position of the detrending window. We develop multifractal detrending moving average (MFDMA) algorithms for the analysis of one-dimensional multifractal measures and higher-dimensional multifractals, which is a generalization of the DMA method. The performance of the one-dimensional and two-dimensional MFDMA methods is investigated using synthetic multifractal measures with analytical solutions for backward (θ=0) , centered (θ=0.5) , and forward (θ=1) detrending windows. We find that the estimated multifractal scaling exponent τ(q) and the singularity spectrum f(α) are in good agreement with the theoretical values. In addition, the backward MFDMA method has the best performance, which provides the most accurate estimates of the scaling exponents with lowest error bars, while the centered MFDMA method has the worse performance. It is found that the backward MFDMA algorithm also outperforms the multifractal detrended fluctuation analysis. The one-dimensional backward MFDMA method is applied to analyzing the time series of Shanghai Stock Exchange Composite Index and its multifractal nature is confirmed.

Time Series ARIMA Models of Undergraduate Grade Point Average.

ERIC Educational Resources Information Center

Rogers, Bruce G.

The Auto-Regressive Integrated Moving Average (ARIMA) Models, often referred to as Box-Jenkins models, are regression methods for analyzing sequential dependent observations with large amounts of data. The Box-Jenkins approach, a three-stage procedure consisting of identification, estimation and diagnosis, was used to select the most appropriate…

Move-by-move dynamics of the advantage in chess matches reveals population-level learning of the game.

PubMed

Ribeiro, Haroldo V; Mendes, Renio S; Lenzi, Ervin K; del Castillo-Mussot, Marcelo; Amaral, Luís A N

2013-01-01

The complexity of chess matches has attracted broad interest since its invention. This complexity and the availability of large number of recorded matches make chess an ideal model systems for the study of population-level learning of a complex system. We systematically investigate the move-by-move dynamics of the white player's advantage from over seventy thousand high level chess matches spanning over 150 years. We find that the average advantage of the white player is positive and that it has been increasing over time. Currently, the average advantage of the white player is 0.17 pawns but it is exponentially approaching a value of 0.23 pawns with a characteristic time scale of 67 years. We also study the diffusion of the move dependence of the white player's advantage and find that it is non-Gaussian, has long-ranged anti-correlations and that after an initial period with no diffusion it becomes super-diffusive. We find that the duration of the non-diffusive period, corresponding to the opening stage of a match, is increasing in length and exponentially approaching a value of 15.6 moves with a characteristic time scale of 130 years. We interpret these two trends as a resulting from learning of the features of the game. Additionally, we find that the exponent [Formula: see text] characterizing the super-diffusive regime is increasing toward a value of 1.9, close to the ballistic regime. We suggest that this trend is due to the increased broadening of the range of abilities of chess players participating in major tournaments.

Move-by-Move Dynamics of the Advantage in Chess Matches Reveals Population-Level Learning of the Game

PubMed Central

Ribeiro, Haroldo V.; Mendes, Renio S.; Lenzi, Ervin K.; del Castillo-Mussot, Marcelo; Amaral, Luís A. N.

2013-01-01

The complexity of chess matches has attracted broad interest since its invention. This complexity and the availability of large number of recorded matches make chess an ideal model systems for the study of population-level learning of a complex system. We systematically investigate the move-by-move dynamics of the white player’s advantage from over seventy thousand high level chess matches spanning over 150 years. We find that the average advantage of the white player is positive and that it has been increasing over time. Currently, the average advantage of the white player is 0.17 pawns but it is exponentially approaching a value of 0.23 pawns with a characteristic time scale of 67 years. We also study the diffusion of the move dependence of the white player’s advantage and find that it is non-Gaussian, has long-ranged anti-correlations and that after an initial period with no diffusion it becomes super-diffusive. We find that the duration of the non-diffusive period, corresponding to the opening stage of a match, is increasing in length and exponentially approaching a value of 15.6 moves with a characteristic time scale of 130 years. We interpret these two trends as a resulting from learning of the features of the game. Additionally, we find that the exponent characterizing the super-diffusive regime is increasing toward a value of 1.9, close to the ballistic regime. We suggest that this trend is due to the increased broadening of the range of abilities of chess players participating in major tournaments. PMID:23382876

A strategy to decide whether to move the last case of the day in an operating room to another empty operating room to decrease overtime labor costs.

PubMed

Dexter, F

2000-10-01

We examined how to program an operating room (OR) information system to assist the OR manager in deciding whether to move the last case of the day in one OR to another OR that is empty to decrease overtime labor costs. We first developed a statistical strategy to predict whether moving the case would decrease overtime labor costs for first shift nurses and anesthesia providers. The strategy was based on using historical case duration data stored in a surgical services information system. Second, we estimated the incremental overtime labor costs achieved if our strategy was used for moving cases versus movement of cases by an OR manager who knew in advance exactly how long each case would last. We found that if our strategy was used to decide whether to move cases, then depending on parameter values, only 2.0 to 4.3 more min of overtime would be required per case than if the OR manager had perfect retrospective knowledge of case durations. The use of other information technologies to assist in the decision of whether to move a case, such as real-time patient tracking information systems, closed-circuit cameras, or graphical airport-style displays can, on average, reduce overtime by no more than only 2 to 4 min per case that can be moved. The use of other information technologies to assist in the decision of whether to move a case, such as real-time patient tracking information systems, closed-circuit cameras, or graphical airport-style displays, can, on average, reduce overtime by no more than only 2 to 4 min per case that can be moved.

Computational problems in autoregressive moving average (ARMA) models

NASA Technical Reports Server (NTRS)

Agarwal, G. C.; Goodarzi, S. M.; Oneill, W. D.; Gottlieb, G. L.

1981-01-01

The choice of the sampling interval and the selection of the order of the model in time series analysis are considered. Band limited (up to 15 Hz) random torque perturbations are applied to the human ankle joint. The applied torque input, the angular rotation output, and the electromyographic activity using surface electrodes from the extensor and flexor muscles of the ankle joint are recorded. Autoregressive moving average models are developed. A parameter constraining technique is applied to develop more reliable models. The asymptotic behavior of the system must be taken into account during parameter optimization to develop predictive models.

PERIODIC AUTOREGRESSIVE-MOVING AVERAGE (PARMA) MODELING WITH APPLICATIONS TO WATER RESOURCES.

USGS Publications Warehouse

Vecchia, A.V.

1985-01-01

Results involving correlation properties and parameter estimation for autogressive-moving average models with periodic parameters are presented. A multivariate representation of the PARMA model is used to derive parameter space restrictions and difference equations for the periodic autocorrelations. Close approximation to the likelihood function for Gaussian PARMA processes results in efficient maximum-likelihood estimation procedures. Terms in the Fourier expansion of the parameters are sequentially included, and a selection criterion is given for determining the optimal number of harmonics to be included. Application of the techniques is demonstrated through analysis of a monthly streamflow time series.

Comparison of estimators for rolling samples using Forest Inventory and Analysis data

Treesearch

Devin S. Johnson; Michael S. Williams; Raymond L. Czaplewski

2003-01-01

The performance of three classes of weighted average estimators is studied for an annual inventory design similar to the Forest Inventory and Analysis program of the United States. The first class is based on an ARIMA(0,1,1) time series model. The equal weight, simple moving average is a member of this class. The second class is based on an ARIMA(0,2,2) time series...

SU-F-T-497: Spatiotemporally Optimal, Personalized Prescription Scheme for Glioblastoma Patients Using the Proliferation and Invasion Glioma Model

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

Kim, M; Rockhill, J; Phillips, M

Purpose: To investigate a spatiotemporally optimal radiotherapy prescription scheme and its potential benefit for glioblastoma (GBM) patients using the proliferation and invasion (PI) glioma model. Methods: Standard prescription for GBM was assumed to deliver 46Gy in 23 fractions to GTV1+2cm margin and additional 14Gy in 7 fractions to GTV2+2cm margin. We simulated the tumor proliferation and invasion in 2D according to the PI glioma model with a moving velocity of 0.029(slow-move), 0.079(average-move), and 0.13(fast-move) mm/day for GTV2 with a radius of 1 and 2cm. For each tumor, the margin around GTV1 and GTV2 was varied to 0–6 cm and 1–3more » cm respectively. Total dose to GTV1 was constrained such that the equivalent uniform dose (EUD) to normal brain equals EUD with the standard prescription. A non-stationary dose policy, where the fractional dose varies, was investigated to estimate the temporal effect of the radiation dose. The efficacy of an optimal prescription scheme was evaluated by tumor cell-surviving fraction (SF), EUD, and the expected survival time. Results: Optimal prescription for the slow-move tumors was to use 3.0(small)-3.5(large) cm margins to GTV1, and 1.5cm margin to GTV2. For the average- and fast-move tumors, it was optimal to use 6.0cm margin for GTV1 suggesting that whole brain therapy is optimal, and then 1.5cm (average-move) and 1.5–3.0cm (fast-move, small-large) margins for GTV2. It was optimal to deliver the boost sequentially using a linearly decreasing fractional dose for all tumors. Optimal prescription led to 0.001–0.465% of the tumor SF resulted from using the standard prescription, and increased tumor EUD by 25.3–49.3% and the estimated survival time by 7.6–22.2 months. Conclusion: It is feasible to optimize a prescription scheme depending on the individual tumor characteristics. A personalized prescription scheme could potentially increase tumor EUD and the expected survival time significantly without increasing EUD to normal brain.« less

Mechanistic approach to generalized technical analysis of share prices and stock market indices

NASA Astrophysics Data System (ADS)

Ausloos, M.; Ivanova, K.

2002-05-01

Classical technical analysis methods of stock evolution are recalled, i.e. the notion of moving averages and momentum indicators. The moving averages lead to define death and gold crosses, resistance and support lines. Momentum indicators lead the price trend, thus give signals before the price trend turns over. The classical technical analysis investment strategy is thereby sketched. Next, we present a generalization of these tricks drawing on physical principles, i.e. taking into account not only the price of a stock but also the volume of transactions. The latter becomes a time dependent generalized mass. The notion of pressure, acceleration and force are deduced. A generalized (kinetic) energy is easily defined. It is understood that the momentum indicators take into account the sign of the fluctuations, while the energy is geared toward the absolute value of the fluctuations. They have different patterns which are checked by searching for the crossing points of their respective moving averages. The case of IBM evolution over 1990-2000 is used for illustrations.

Are U.S. Military Interventions Contagious over Time? Intervention Timing and Its Implications for Force Planning

DTIC Science & Technology

2013-01-01

29 3.5. ARIMA Models , Temporal Clustering of Conflicts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 3.6...39 3.9. ARIMA Models ...variance across a distribution. Autoregressive integrated moving average ( ARIMA ) models are used with time-series data sets and are designed to capture

Use of Time-Series, ARIMA Designs to Assess Program Efficacy.

ERIC Educational Resources Information Center

Braden, Jeffery P.; And Others

1990-01-01

Illustrates use of time-series designs for determining efficacy of interventions with fictitious data describing drug-abuse prevention program. Discusses problems and procedures associated with time-series data analysis using Auto Regressive Integrated Moving Averages (ARIMA) models. Example illustrates application of ARIMA analysis for…

Effect of air pollution on pediatric respiratory emergency room visits and hospital admissions.

PubMed

Farhat, S C L; Paulo, R L P; Shimoda, T M; Conceição, G M S; Lin, C A; Braga, A L F; Warth, M P N; Saldiva, P H N

2005-02-01

In order to assess the effect of air pollution on pediatric respiratory morbidity, we carried out a time series study using daily levels of PM10, SO2, NO2, ozone, and CO and daily numbers of pediatric respiratory emergency room visits and hospital admissions at the Children's Institute of the University of Sao Paulo Medical School, from August 1996 to August 1997. In this period there were 43,635 hospital emergency room visits, 4534 of which were due to lower respiratory tract disease. The total number of hospital admissions was 6785, 1021 of which were due to lower respiratory tract infectious and/or obstructive diseases. The three health end-points under investigation were the daily number of emergency room visits due to lower respiratory tract diseases, hospital admissions due to pneumonia, and hospital admissions due to asthma or bronchiolitis. Generalized additive Poisson regression models were fitted, controlling for smooth functions of time, temperature and humidity, and an indicator of weekdays. NO2 was positively associated with all outcomes. Interquartile range increases (65.04 microg/m3) in NO2 moving averages were associated with an 18.4% increase (95% confidence interval, 95% CI = 12.5-24.3) in emergency room visits due to lower respiratory tract diseases (4-day moving average), a 17.6% increase (95% CI = 3.3-32.7) in hospital admissions due to pneumonia or bronchopneumonia (3-day moving average), and a 31.4% increase (95% CI = 7.2-55.7) in hospital admissions due to asthma or bronchiolitis (2-day moving average). The study showed that air pollution considerably affects children's respiratory morbidity, deserving attention from the health authorities.

Multifractal detrending moving-average cross-correlation analysis

NASA Astrophysics Data System (ADS)

Jiang, Zhi-Qiang; Zhou, Wei-Xing

2011-07-01

There are a number of situations in which several signals are simultaneously recorded in complex systems, which exhibit long-term power-law cross correlations. The multifractal detrended cross-correlation analysis (MFDCCA) approaches can be used to quantify such cross correlations, such as the MFDCCA based on the detrended fluctuation analysis (MFXDFA) method. We develop in this work a class of MFDCCA algorithms based on the detrending moving-average analysis, called MFXDMA. The performances of the proposed MFXDMA algorithms are compared with the MFXDFA method by extensive numerical experiments on pairs of time series generated from bivariate fractional Brownian motions, two-component autoregressive fractionally integrated moving-average processes, and binomial measures, which have theoretical expressions of the multifractal nature. In all cases, the scaling exponents hxy extracted from the MFXDMA and MFXDFA algorithms are very close to the theoretical values. For bivariate fractional Brownian motions, the scaling exponent of the cross correlation is independent of the cross-correlation coefficient between two time series, and the MFXDFA and centered MFXDMA algorithms have comparative performances, which outperform the forward and backward MFXDMA algorithms. For two-component autoregressive fractionally integrated moving-average processes, we also find that the MFXDFA and centered MFXDMA algorithms have comparative performances, while the forward and backward MFXDMA algorithms perform slightly worse. For binomial measures, the forward MFXDMA algorithm exhibits the best performance, the centered MFXDMA algorithms performs worst, and the backward MFXDMA algorithm outperforms the MFXDFA algorithm when the moment order q<0 and underperforms when q>0. We apply these algorithms to the return time series of two stock market indexes and to their volatilities. For the returns, the centered MFXDMA algorithm gives the best estimates of hxy(q) since its hxy(2) is closest to 0.5, as expected, and the MFXDFA algorithm has the second best performance. For the volatilities, the forward and backward MFXDMA algorithms give similar results, while the centered MFXDMA and the MFXDFA algorithms fail to extract rational multifractal nature.

Learning curves for single incision and conventional laparoscopic right hemicolectomy: a multidimensional analysis

PubMed Central

Park, Yoonah; Yong, Yuen Geng; Jung, Kyung Uk; Huh, Jung Wook; Cho, Yong Beom; Kim, Hee Cheol; Lee, Woo Yong; Chun, Ho-Kyung

2015-01-01

Purpose This study aimed to compare the learning curves and early postoperative outcomes for conventional laparoscopic (CL) and single incision laparoscopic (SIL) right hemicolectomy (RHC). Methods This retrospective study included the initial 35 cases in each group. Learning curves were evaluated by the moving average of operative time, mean operative time of every five consecutive cases, and cumulative sum (CUSUM) analysis. The learning phase was considered overcome when the moving average of operative times reached a plateau, and when the mean operative time of every five consecutive cases reached a low point and subsequently did not vary by more than 30 minutes. Results Six patients with missing data in the CL RHC group were excluded from the analyses. According to the mean operative time of every five consecutive cases, learning phase of SIL and CL RHC was completed between 26 and 30 cases, and 16 and 20 cases, respectively. Moving average analysis revealed that approximately 31 (SIL) and 25 (CL) cases were needed to complete the learning phase, respectively. CUSUM analysis demonstrated that 10 (SIL) and two (CL) cases were required to reach a steady state of complication-free performance, respectively. Postoperative complications rate was higher in SIL than in CL group, but the difference was not statistically significant (17.1% vs. 3.4%). Conclusion The learning phase of SIL RHC is longer than that of CL RHC. Early oncological outcomes of both techniques were comparable. However, SIL RHC had a statistically insignificant higher complication rate than CL RHC during the learning phase. PMID:25960990

A Case Study to Improve Emergency Room Patient Flow at Womack Army Medical Center

DTIC Science & Technology

2009-06-01

use just the previous month, moving average 2-month period ( MA2 ) uses the average from the previous two months, moving average 3-month period (MA3...ED prior to discharge by provider) MA2 /MA3/MA4 - moving averages of 2-4 months in length MAD - mean absolute deviation (measure of accuracy for

Comparing the performance of FA, DFA and DMA using different synthetic long-range correlated time series

PubMed Central

Shao, Ying-Hui; Gu, Gao-Feng; Jiang, Zhi-Qiang; Zhou, Wei-Xing; Sornette, Didier

2012-01-01

Notwithstanding the significant efforts to develop estimators of long-range correlations (LRC) and to compare their performance, no clear consensus exists on what is the best method and under which conditions. In addition, synthetic tests suggest that the performance of LRC estimators varies when using different generators of LRC time series. Here, we compare the performances of four estimators [Fluctuation Analysis (FA), Detrended Fluctuation Analysis (DFA), Backward Detrending Moving Average (BDMA), and Centred Detrending Moving Average (CDMA)]. We use three different generators [Fractional Gaussian Noises, and two ways of generating Fractional Brownian Motions]. We find that CDMA has the best performance and DFA is only slightly worse in some situations, while FA performs the worst. In addition, CDMA and DFA are less sensitive to the scaling range than FA. Hence, CDMA and DFA remain “The Methods of Choice” in determining the Hurst index of time series. PMID:23150785

Simulation of Unsteady Flows Using an Unstructured Navier-Stokes Solver on Moving and Stationary Grids

NASA Technical Reports Server (NTRS)

Biedron, Robert T.; Vatsa, Veer N.; Atkins, Harold L.

2005-01-01

We apply an unsteady Reynolds-averaged Navier-Stokes (URANS) solver for unstructured grids to unsteady flows on moving and stationary grids. Example problems considered are relevant to active flow control and stability and control. Computational results are presented using the Spalart-Allmaras turbulence model and are compared to experimental data. The effect of grid and time-step refinement are examined.

Maximum likelihood estimation for periodic autoregressive moving average models

USGS Publications Warehouse

Vecchia, A.V.

1985-01-01

A useful class of models for seasonal time series that cannot be filtered or standardized to achieve second-order stationarity is that of periodic autoregressive moving average (PARMA) models, which are extensions of ARMA models that allow periodic (seasonal) parameters. An approximation to the exact likelihood for Gaussian PARMA processes is developed, and a straightforward algorithm for its maximization is presented. The algorithm is tested on several periodic ARMA(1, 1) models through simulation studies and is compared to moment estimation via the seasonal Yule-Walker equations. Applicability of the technique is demonstrated through an analysis of a seasonal stream-flow series from the Rio Caroni River in Venezuela.

Recent Enhancements To The FUN3D Flow Solver For Moving-Mesh Applications

NASA Technical Reports Server (NTRS)

Biedron, Robert T,; Thomas, James L.

2009-01-01

An unsteady Reynolds-averaged Navier-Stokes solver for unstructured grids has been extended to handle general mesh movement involving rigid, deforming, and overset meshes. Mesh deformation is achieved through analogy to elastic media by solving the linear elasticity equations. A general method for specifying the motion of moving bodies within the mesh has been implemented that allows for inherited motion through parent-child relationships, enabling simulations involving multiple moving bodies. Several example calculations are shown to illustrate the range of potential applications. For problems in which an isolated body is rotating with a fixed rate, a noninertial reference-frame formulation is available. An example calculation for a tilt-wing rotor is used to demonstrate that the time-dependent moving grid and noninertial formulations produce the same results in the limit of zero time-step size.

Generalized seasonal autoregressive integrated moving average models for count data with application to malaria time series with low case numbers.

PubMed

Briët, Olivier J T; Amerasinghe, Priyanie H; Vounatsou, Penelope

2013-01-01

With the renewed drive towards malaria elimination, there is a need for improved surveillance tools. While time series analysis is an important tool for surveillance, prediction and for measuring interventions' impact, approximations by commonly used Gaussian methods are prone to inaccuracies when case counts are low. Therefore, statistical methods appropriate for count data are required, especially during "consolidation" and "pre-elimination" phases. Generalized autoregressive moving average (GARMA) models were extended to generalized seasonal autoregressive integrated moving average (GSARIMA) models for parsimonious observation-driven modelling of non Gaussian, non stationary and/or seasonal time series of count data. The models were applied to monthly malaria case time series in a district in Sri Lanka, where malaria has decreased dramatically in recent years. The malaria series showed long-term changes in the mean, unstable variance and seasonality. After fitting negative-binomial Bayesian models, both a GSARIMA and a GARIMA deterministic seasonality model were selected based on different criteria. Posterior predictive distributions indicated that negative-binomial models provided better predictions than Gaussian models, especially when counts were low. The G(S)ARIMA models were able to capture the autocorrelation in the series. G(S)ARIMA models may be particularly useful in the drive towards malaria elimination, since episode count series are often seasonal and non-stationary, especially when control is increased. Although building and fitting GSARIMA models is laborious, they may provide more realistic prediction distributions than do Gaussian methods and may be more suitable when counts are low.

Video-Assisted Thoracic Surgical Lobectomy for Lung Cancer: Description of a Learning Curve.

PubMed

Yao, Fei; Wang, Jian; Yao, Ju; Hang, Fangrong; Cao, Shiqi; Cao, Yongke

2017-07-01

Video-assisted thoracic surgical (VATS) lobectomy is gaining popularity in the treatment of lung cancer. The aim of this study is to investigate the learning curve of VATS lobectomy by using multidimensional methods and to compare the learning curve groups with respect to perioperative clinical outcomes. We retrospectively reviewed a prospective database to identify 67 consecutive patients who underwent VATS lobectomy for lung cancer by a single surgeon. The learning curve was analyzed by using moving average and the cumulative sum (CUSUM) method. With the moving average and CUSUM analyses for the operation time, patients were stratified into two groups, with chronological order defining early and late experiences. Perioperative clinical outcomes were compared between the two learning curve groups. According to the moving average method, the peak point for operation time occurred at the 26th case. The CUSUM method also showed the operation time peak point at the 26th case. When results were compared between early- and late-experience periods, the operation time, duration of chest drainage, and postoperative hospital stay were significantly longer in the early-experience group (cases 1 to 26). The intraoperative estimated blood loss was significantly less in the late-experience group (cases 27 to 67). CUSUM charts showed a decreasing duration of chest drainage after the 36th case and shortening postoperative hospital stay after the 37th case. Multidimensional statistical analyses suggested that the learning curve for VATS lobectomy for lung cancer required ∼26 cases. Favorable intraoperative and postoperative care parameters for VATS lobectomy were observed in the late-experience group.

Generalized Seasonal Autoregressive Integrated Moving Average Models for Count Data with Application to Malaria Time Series with Low Case Numbers

PubMed Central

Briët, Olivier J. T.; Amerasinghe, Priyanie H.; Vounatsou, Penelope

2013-01-01

Introduction With the renewed drive towards malaria elimination, there is a need for improved surveillance tools. While time series analysis is an important tool for surveillance, prediction and for measuring interventions’ impact, approximations by commonly used Gaussian methods are prone to inaccuracies when case counts are low. Therefore, statistical methods appropriate for count data are required, especially during “consolidation” and “pre-elimination” phases. Methods Generalized autoregressive moving average (GARMA) models were extended to generalized seasonal autoregressive integrated moving average (GSARIMA) models for parsimonious observation-driven modelling of non Gaussian, non stationary and/or seasonal time series of count data. The models were applied to monthly malaria case time series in a district in Sri Lanka, where malaria has decreased dramatically in recent years. Results The malaria series showed long-term changes in the mean, unstable variance and seasonality. After fitting negative-binomial Bayesian models, both a GSARIMA and a GARIMA deterministic seasonality model were selected based on different criteria. Posterior predictive distributions indicated that negative-binomial models provided better predictions than Gaussian models, especially when counts were low. The G(S)ARIMA models were able to capture the autocorrelation in the series. Conclusions G(S)ARIMA models may be particularly useful in the drive towards malaria elimination, since episode count series are often seasonal and non-stationary, especially when control is increased. Although building and fitting GSARIMA models is laborious, they may provide more realistic prediction distributions than do Gaussian methods and may be more suitable when counts are low. PMID:23785448

The Prediction of Teacher Turnover Employing Time Series Analysis.

ERIC Educational Resources Information Center

Costa, Crist H.

The purpose of this study was to combine knowledge of teacher demographic data with time-series forecasting methods to predict teacher turnover. Moving averages and exponential smoothing were used to forecast discrete time series. The study used data collected from the 22 largest school districts in Iowa, designated as FACT schools. Predictions…

Monthly streamflow forecasting with auto-regressive integrated moving average

NASA Astrophysics Data System (ADS)

Nasir, Najah; Samsudin, Ruhaidah; Shabri, Ani

2017-09-01

Forecasting of streamflow is one of the many ways that can contribute to better decision making for water resource management. The auto-regressive integrated moving average (ARIMA) model was selected in this research for monthly streamflow forecasting with enhancement made by pre-processing the data using singular spectrum analysis (SSA). This study also proposed an extension of the SSA technique to include a step where clustering was performed on the eigenvector pairs before reconstruction of the time series. The monthly streamflow data of Sungai Muda at Jeniang, Sungai Muda at Jambatan Syed Omar and Sungai Ketil at Kuala Pegang was gathered from the Department of Irrigation and Drainage Malaysia. A ratio of 9:1 was used to divide the data into training and testing sets. The ARIMA, SSA-ARIMA and Clustered SSA-ARIMA models were all developed in R software. Results from the proposed model are then compared to a conventional auto-regressive integrated moving average model using the root-mean-square error and mean absolute error values. It was found that the proposed model can outperform the conventional model.

TERMA Framework for Biomedical Signal Analysis: An Economic-Inspired Approach.

PubMed

Elgendi, Mohamed

2016-11-02

Biomedical signals contain features that represent physiological events, and each of these events has peaks. The analysis of biomedical signals for monitoring or diagnosing diseases requires the detection of these peaks, making event detection a crucial step in biomedical signal processing. Many researchers have difficulty detecting these peaks to investigate, interpret and analyze their corresponding events. To date, there is no generic framework that captures these events in a robust, efficient and consistent manner. A new method referred to for the first time as two event-related moving averages ("TERMA") involves event-related moving averages and detects events in biomedical signals. The TERMA framework is flexible and universal and consists of six independent LEGO building bricks to achieve high accuracy detection of biomedical events. Results recommend that the window sizes for the two moving averages ( W 1 and W 2 ) have to follow the inequality ( 8 × W 1 ) ≥ W 2 ≥ ( 2 × W 1 ) . Moreover, TERMA is a simple yet efficient event detector that is suitable for wearable devices, point-of-care devices, fitness trackers and smart watches, compared to more complex machine learning solutions.

Moving Average Models with Bivariate Exponential and Geometric Distributions.

DTIC Science & Technology

1985-03-01

ordinary time series and of point processes. Developments in Statistics, Vol. 1, P.R. Krishnaiah , ed. Academic Press, New York. [9] Esary, J.D. and...valued and discrete - valued time series with ARMA correlation structure. Multivariate Analysis V, P.R. Krishnaiah , ed. North-Holland. 151-166. [28

A Computer Program for the Generation of ARIMA Data

ERIC Educational Resources Information Center

Green, Samuel B.; Noles, Keith O.

1977-01-01

The autoregressive integrated moving averages model (ARIMA) has been applied to time series data in psychological and educational research. A program is described that generates ARIMA data of a known order. The program enables researchers to explore statistical properties of ARIMA data and simulate systems producing time dependent observations.…

Highly-resolved numerical simulations of bed-load transport in a turbulent open-channel flow

NASA Astrophysics Data System (ADS)

Vowinckel, Bernhard; Kempe, Tobias; Nikora, Vladimir; Jain, Ramandeep; Fröhlich, Jochen

2015-11-01

The study presents the analysis of phase-resolving Direct Numerical Simulations of a horizontal turbulent open-channel flow laden with a large number of spherical particles. These particles have a mobility close to their threshold of incipient motion andare transported in bed-load mode. The coupling of the fluid phase with the particlesis realized by an Immersed Boundary Method. The Double-Averaging Methodology is applied for the first time convolutingthe data into a handy set of quantities averaged in time and space to describe the most prominent flow features.In addition, a systematic study elucidatesthe impact of mobility and sediment supply on the pattern formation of particle clusters ina very large computational domain. A detailed description of fluid quantities links the developed particle patterns to the enhancement of turbulence and to a modified hydraulic resistance. Conditional averaging isapplied toerosion events providingthe processes involved inincipient particle motion. Furthermore, the detection of moving particle clusters as well as their surrounding flow field is addressedby a a moving frameanalysis. Funded by German Research Foundation (DFG), project FR 1593/5-2, computational time provided by ZIH Dresden, Germany, and JSC Juelich, Germany.

An Estimation of the Likelihood of Significant Eruptions During 2000-2009 Using Poisson Statistics on Two-Point Moving Averages of the Volcanic Time Series

NASA Technical Reports Server (NTRS)

Wilson, Robert M.

2001-01-01

Since 1750, the number of cataclysmic volcanic eruptions (volcanic explosivity index (VEI)>=4) per decade spans 2-11, with 96 percent located in the tropics and extra-tropical Northern Hemisphere. A two-point moving average of the volcanic time series has higher values since the 1860's than before, being 8.00 in the 1910's (the highest value) and 6.50 in the 1980's, the highest since the 1910's peak. Because of the usual behavior of the first difference of the two-point moving averages, one infers that its value for the 1990's will measure approximately 6.50 +/- 1, implying that approximately 7 +/- 4 cataclysmic volcanic eruptions should be expected during the present decade (2000-2009). Because cataclysmic volcanic eruptions (especially those having VEI>=5) nearly always have been associated with short-term episodes of global cooling, the occurrence of even one might confuse our ability to assess the effects of global warming. Poisson probability distributions reveal that the probability of one or more events with a VEI>=4 within the next ten years is >99 percent. It is approximately 49 percent for an event with a VEI>=5, and 18 percent for an event with a VEI>=6. Hence, the likelihood that a climatically significant volcanic eruption will occur within the next ten years appears reasonably high.

Finite-size effect and the components of multifractality in transport economics volatility based on multifractal detrending moving average method

NASA Astrophysics Data System (ADS)

Chen, Feier; Tian, Kang; Ding, Xiaoxu; Miao, Yuqi; Lu, Chunxia

2016-11-01

Analysis of freight rate volatility characteristics attracts more attention after year 2008 due to the effect of credit crunch and slowdown in marine transportation. The multifractal detrended fluctuation analysis technique is employed to analyze the time series of Baltic Dry Bulk Freight Rate Index and the market trend of two bulk ship sizes, namely Capesize and Panamax for the period: March 1st 1999-February 26th 2015. In this paper, the degree of the multifractality with different fluctuation sizes is calculated. Besides, multifractal detrending moving average (MF-DMA) counting technique has been developed to quantify the components of multifractal spectrum with the finite-size effect taken into consideration. Numerical results show that both Capesize and Panamax freight rate index time series are of multifractal nature. The origin of multifractality for the bulk freight rate market series is found mostly due to nonlinear correlation.

Modeling Geodetic Processes with Levy α-Stable Distribution and FARIMA

NASA Astrophysics Data System (ADS)

Montillet, Jean-Philippe; Yu, Kegen

2015-04-01

Over the last years the scientific community has been using the auto regressive moving average (ARMA) model in the modeling of the noise in global positioning system (GPS) time series (daily solution). This work starts with the investigation of the limit of the ARMA model which is widely used in signal processing when the measurement noise is white. Since a typical GPS time series consists of geophysical signals (e.g., seasonal signal) and stochastic processes (e.g., coloured and white noise), the ARMA model may be inappropriate. Therefore, the application of the fractional auto-regressive integrated moving average (FARIMA) model is investigated. The simulation results using simulated time series as well as real GPS time series from a few selected stations around Australia show that the FARIMA model fits the time series better than other models when the coloured noise is larger than the white noise. The second fold of this work focuses on fitting the GPS time series with the family of Levy α-stable distributions. Using this distribution, a hypothesis test is developed to eliminate effectively coarse outliers from GPS time series, achieving better performance than using the rule of thumb of n standard deviations (with n chosen empirically).

Traffic-Related Air Pollution, Blood Pressure, and Adaptive Response of Mitochondrial Abundance.

PubMed

Zhong, Jia; Cayir, Akin; Trevisi, Letizia; Sanchez-Guerra, Marco; Lin, Xinyi; Peng, Cheng; Bind, Marie-Abèle; Prada, Diddier; Laue, Hannah; Brennan, Kasey J M; Dereix, Alexandra; Sparrow, David; Vokonas, Pantel; Schwartz, Joel; Baccarelli, Andrea A

2016-01-26

Exposure to black carbon (BC), a tracer of vehicular-traffic pollution, is associated with increased blood pressure (BP). Identifying biological factors that attenuate BC effects on BP can inform prevention. We evaluated the role of mitochondrial abundance, an adaptive mechanism compensating for cellular-redox imbalance, in the BC-BP relationship. At ≥ 1 visits among 675 older men from the Normative Aging Study (observations=1252), we assessed daily BP and ambient BC levels from a stationary monitor. To determine blood mitochondrial abundance, we used whole blood to analyze mitochondrial-to-nuclear DNA ratio (mtDNA/nDNA) using quantitative polymerase chain reaction. Every standard deviation increase in the 28-day BC moving average was associated with 1.97 mm Hg (95% confidence interval [CI], 1.23-2.72; P<0.0001) and 3.46 mm Hg (95% CI, 2.06-4.87; P<0.0001) higher diastolic and systolic BP, respectively. Positive BC-BP associations existed throughout all time windows. BC moving averages (5-day to 28-day) were associated with increased mtDNA/nDNA; every standard deviation increase in 28-day BC moving average was associated with 0.12 standard deviation (95% CI, 0.03-0.20; P=0.007) higher mtDNA/nDNA. High mtDNA/nDNA significantly attenuated the BC-systolic BP association throughout all time windows. The estimated effect of 28-day BC moving average on systolic BP was 1.95-fold larger for individuals at the lowest mtDNA/nDNA quartile midpoint (4.68 mm Hg; 95% CI, 3.03-6.33; P<0.0001), in comparison with the top quartile midpoint (2.40 mm Hg; 95% CI, 0.81-3.99; P=0.003). In older adults, short-term to moderate-term ambient BC levels were associated with increased BP and blood mitochondrial abundance. Our findings indicate that increased blood mitochondrial abundance is a compensatory response and attenuates the cardiac effects of BC. © 2015 American Heart Association, Inc.

Method and apparatus for ultrasonic characterization through the thickness direction of a moving web

DOEpatents

Jackson, Theodore; Hall, Maclin S.

2001-01-01

A method and apparatus for determining the caliper and/or the ultrasonic transit time through the thickness direction of a moving web of material using ultrasonic pulses generated by a rotatable wheel ultrasound apparatus. The apparatus includes a first liquid-filled tire and either a second liquid-filled tire forming a nip or a rotatable cylinder that supports a thin moving web of material such as a moving web of paper and forms a nip with the first liquid-filled tire. The components of ultrasonic transit time through the tires and fluid held within the tires may be resolved and separately employed to determine the separate contributions of the two tire thicknesses and the two fluid paths to the total path length that lies between two ultrasonic transducer surfaces contained within the tires in support of caliper measurements. The present invention provides the benefit of obtaining a transit time and caliper measurement at any point in time as a specimen passes through the nip of rotating tires and eliminates inaccuracies arising from nonuniform tire circumferential thickness by accurately retaining point-to-point specimen transit time and caliper variation information, rather than an average obtained through one or more tire rotations. Morever, ultrasonic transit time through the thickness direction of a moving web may be determined independent of small variations in the wheel axle spacing, tire thickness, and liquid and tire temperatures.

The Spin Move: A Reliable and Cost-Effective Gowning Technique for the 21st Century.

PubMed

Ochiai, Derek H; Adib, Farshad

2015-04-01

Operating room efficiency (ORE) and utilization are considered one of the most crucial components of quality improvement in every hospital. We introduced a new gowning technique that could optimize ORE. The Spin Move quickly and efficiently wraps a surgical gown around the surgeon's body. This saves the operative time expended through the traditional gowning techniques. In the Spin Move, while the surgeon is approaching the scrub nurse, he or she uses the left heel as the fulcrum. The torque, which is generated by twisting the right leg around the left leg, helps the surgeon to close the gown as quickly and safely as possible. From 2003 to 2012, the Spin Move was performed in 1,725 consecutive procedures with no complication. The estimated average time was 5.3 and 7.8 seconds for the Spin Move and traditional gowning, respectively. The estimated time saving for the senior author during this period was 71.875 minutes. Approximately 20,000 orthopaedic surgeons practice in the United States. If this technique had been used, 23,958 hours could have been saved. The money saving could have been $14,374,800.00 (23,958 hours × $600/operating room hour) during the past 10 years. The Spin Move is easy to perform and reproducible. It saves operating room time and increases ORE.

The Spin Move: A Reliable and Cost-Effective Gowning Technique for the 21st Century

PubMed Central

Ochiai, Derek H.; Adib, Farshad

2015-01-01

Operating room efficiency (ORE) and utilization are considered one of the most crucial components of quality improvement in every hospital. We introduced a new gowning technique that could optimize ORE. The Spin Move quickly and efficiently wraps a surgical gown around the surgeon's body. This saves the operative time expended through the traditional gowning techniques. In the Spin Move, while the surgeon is approaching the scrub nurse, he or she uses the left heel as the fulcrum. The torque, which is generated by twisting the right leg around the left leg, helps the surgeon to close the gown as quickly and safely as possible. From 2003 to 2012, the Spin Move was performed in 1,725 consecutive procedures with no complication. The estimated average time was 5.3 and 7.8 seconds for the Spin Move and traditional gowning, respectively. The estimated time saving for the senior author during this period was 71.875 minutes. Approximately 20,000 orthopaedic surgeons practice in the United States. If this technique had been used, 23,958 hours could have been saved. The money saving could have been $14,374,800.00 (23,958 hours × $600/operating room hour) during the past 10 years. The Spin Move is easy to perform and reproducible. It saves operating room time and increases ORE. PMID:26052490

Comparing Gravimetric and Real-Time Sampling of PM2.5 Concentrations Inside Truck Cabins

PubMed Central

Zhu, Ying; Smith, Thomas J.; Davis, Mary E.; Levy, Jonathan I.; Herrick, Robert; Jiang, Hongyu

2012-01-01

As part of a study on truck drivers’ exposure and health risk, pickup and delivery (P&D) truck drivers’ on-road exposure patterns to PM2.5 were assessed in five weeklong sampling trips in metropolitan areas of five U.S. cities from April to August of 2006. Drivers were sampled with real-time (DustTrak) and gravimetric samplers to measure average in-cabin PM2.5 concentrations and to compare their correspondence in moving trucks. In addition, GPS measurements of truck locations, meteorological data, and driver behavioral data were collected throughout the day to determine which factors influence the relationship between real-time and gravimetric samplers. Results indicate that the association between average real-time and gravimetric PM2.5 measurements on moving trucks was fairly consistent (Spearman rank correlation of 0.63), with DustTrak measurements exceeding gravimetric measurements by approximately a factor of 2. This ratio differed significantly only between the industrial Midwest cities and the other three sampled cities scattered in the South and West. There was also limited evidence of an effect of truck age. Filter samples collected concurrently with DustTrak measurements can be used to calibrate average mass concentration responses for the DustTrak, allowing for real-time measurements to be integrated into longer-term studies of inter-city and intra-urban exposure patterns for truck drivers. PMID:21991940

Comparing gravimetric and real-time sampling of PM(2.5) concentrations inside truck cabins.

PubMed

Zhu, Ying; Smith, Thomas J; Davis, Mary E; Levy, Jonathan I; Herrick, Robert; Jiang, Hongyu

2011-11-01

As part of a study on truck drivers' exposure and health risk, pickup and delivery (P&D) truck drivers' on-road exposure patterns to PM(2.5) were assessed in five, weeklong sampling trips in metropolitan areas of five U.S. cities from April to August of 2006. Drivers were sampled with real-time (DustTrak) and gravimetric samplers to measure average in-cabin PM(2.5) concentrations and to compare their correspondence in moving trucks. In addition, GPS measurements of truck locations, meteorological data, and driver behavioral data were collected throughout the day to determine which factors influence the relationship between real-time and gravimetric samplers. Results indicate that the association between average real-time and gravimetric PM(2.5) measurements on moving trucks was fairly consistent (Spearman rank correlation of 0.63), with DustTrak measurements exceeding gravimetric measurements by approximately a factor of 2. This ratio differed significantly only between the industrial Midwest cities and the other three sampled cities scattered in the South and West. There was also limited evidence of an effect of truck age. Filter samples collected concurrently with DustTrak measurements can be used to calibrate average mass concentration responses for the DustTrak, allowing for real-time measurements to be integrated into longer-term studies of inter-city and intra-urban exposure patterns for truck drivers.

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

ERIC Educational Resources Information Center

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

2001-01-01

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

Smoothing strategies combined with ARIMA and neural networks to improve the forecasting of traffic accidents.

PubMed

Barba, Lida; Rodríguez, Nibaldo; Montt, Cecilia

2014-01-01

Two smoothing strategies combined with autoregressive integrated moving average (ARIMA) and autoregressive neural networks (ANNs) models to improve the forecasting of time series are presented. The strategy of forecasting is implemented using two stages. In the first stage the time series is smoothed using either, 3-point moving average smoothing, or singular value Decomposition of the Hankel matrix (HSVD). In the second stage, an ARIMA model and two ANNs for one-step-ahead time series forecasting are used. The coefficients of the first ANN are estimated through the particle swarm optimization (PSO) learning algorithm, while the coefficients of the second ANN are estimated with the resilient backpropagation (RPROP) learning algorithm. The proposed models are evaluated using a weekly time series of traffic accidents of Valparaíso, Chilean region, from 2003 to 2012. The best result is given by the combination HSVD-ARIMA, with a MAPE of 0:26%, followed by MA-ARIMA with a MAPE of 1:12%; the worst result is given by the MA-ANN based on PSO with a MAPE of 15:51%.

Thermodynamics of a time-dependent and dissipative oval billiard: A heat transfer and billiard approach.

PubMed

Leonel, Edson D; Galia, Marcus Vinícius Camillo; Barreiro, Luiz Antonio; Oliveira, Diego F M

2016-12-01

We study some statistical properties for the behavior of the average squared velocity-hence the temperature-for an ensemble of classical particles moving in a billiard whose boundary is time dependent. We assume the collisions of the particles with the boundary of the billiard are inelastic, leading the average squared velocity to reach a steady-state dynamics for large enough time. The description of the stationary state is made by using two different approaches: (i) heat transfer motivated by the Fourier law and (ii) billiard dynamics using either numerical simulations and theoretical description.

Optimal chemotaxis in intermittent migration of animal cells

NASA Astrophysics Data System (ADS)

Romanczuk, P.; Salbreux, G.

2015-04-01

Animal cells can sense chemical gradients without moving and are faced with the challenge of migrating towards a target despite noisy information on the target position. Here we discuss optimal search strategies for a chaser that moves by switching between two phases of motion ("run" and "tumble"), reorienting itself towards the target during tumble phases, and performing persistent migration during run phases. We show that the chaser average run time can be adjusted to minimize the target catching time or the spatial dispersion of the chasers. We obtain analytical results for the catching time and for the spatial dispersion in the limits of small and large ratios of run time to tumble time and scaling laws for the optimal run times. Our findings have implications for optimal chemotactic strategies in animal cell migration.

Defense Applications of Signal Processing

DTIC Science & Technology

1999-08-27

class of multiscale autoregressive moving average (MARMA) processes. These are generalisations of ARMA models in time series analysis , and they contain...including the two theoretical sinusoidal components. Analysis of the amplitude and frequency time series provided some novel insight into the real...communication channels, underwater acoustic signals, radar systems , economic time series and biomedical signals [7]. The alpha stable (aS) distribution has

Large deviation probabilities for correlated Gaussian stochastic processes and daily temperature anomalies

NASA Astrophysics Data System (ADS)

Massah, Mozhdeh; Kantz, Holger

2016-04-01

As we have one and only one earth and no replicas, climate characteristics are usually computed as time averages from a single time series. For understanding climate variability, it is essential to understand how close a single time average will typically be to an ensemble average. To answer this question, we study large deviation probabilities (LDP) of stochastic processes and characterize them by their dependence on the time window. In contrast to iid variables for which there exists an analytical expression for the rate function, the correlated variables such as auto-regressive (short memory) and auto-regressive fractionally integrated moving average (long memory) processes, have not an analytical LDP. We study LDP for these processes, in order to see how correlation affects this probability in comparison to iid data. Although short range correlations lead to a simple correction of sample size, long range correlations lead to a sub-exponential decay of LDP and hence to a very slow convergence of time averages. This effect is demonstrated for a 120 year long time series of daily temperature anomalies measured in Potsdam (Germany).

[Comparison of predictive effect between the single auto regressive integrated moving average (ARIMA) model and the ARIMA-generalized regression neural network (GRNN) combination model on the incidence of scarlet fever].

PubMed

Zhu, Yu; Xia, Jie-lai; Wang, Jing

2009-09-01

Application of the 'single auto regressive integrated moving average (ARIMA) model' and the 'ARIMA-generalized regression neural network (GRNN) combination model' in the research of the incidence of scarlet fever. Establish the auto regressive integrated moving average model based on the data of the monthly incidence on scarlet fever of one city, from 2000 to 2006. The fitting values of the ARIMA model was used as input of the GRNN, and the actual values were used as output of the GRNN. After training the GRNN, the effect of the single ARIMA model and the ARIMA-GRNN combination model was then compared. The mean error rate (MER) of the single ARIMA model and the ARIMA-GRNN combination model were 31.6%, 28.7% respectively and the determination coefficient (R(2)) of the two models were 0.801, 0.872 respectively. The fitting efficacy of the ARIMA-GRNN combination model was better than the single ARIMA, which had practical value in the research on time series data such as the incidence of scarlet fever.

An Optimization of Inventory Demand Forecasting in University Healthcare Centre

NASA Astrophysics Data System (ADS)

Bon, A. T.; Ng, T. K.

2017-01-01

Healthcare industry becomes an important field for human beings nowadays as it concerns about one’s health. With that, forecasting demand for health services is an important step in managerial decision making for all healthcare organizations. Hence, a case study was conducted in University Health Centre to collect historical demand data of Panadol 650mg for 68 months from January 2009 until August 2014. The aim of the research is to optimize the overall inventory demand through forecasting techniques. Quantitative forecasting or time series forecasting model was used in the case study to forecast future data as a function of past data. Furthermore, the data pattern needs to be identified first before applying the forecasting techniques. Trend is the data pattern and then ten forecasting techniques are applied using Risk Simulator Software. Lastly, the best forecasting techniques will be find out with the least forecasting error. Among the ten forecasting techniques include single moving average, single exponential smoothing, double moving average, double exponential smoothing, regression, Holt-Winter’s additive, Seasonal additive, Holt-Winter’s multiplicative, seasonal multiplicative and Autoregressive Integrated Moving Average (ARIMA). According to the forecasting accuracy measurement, the best forecasting technique is regression analysis.

TERMA Framework for Biomedical Signal Analysis: An Economic-Inspired Approach

PubMed Central

Elgendi, Mohamed

2016-01-01

Biomedical signals contain features that represent physiological events, and each of these events has peaks. The analysis of biomedical signals for monitoring or diagnosing diseases requires the detection of these peaks, making event detection a crucial step in biomedical signal processing. Many researchers have difficulty detecting these peaks to investigate, interpret and analyze their corresponding events. To date, there is no generic framework that captures these events in a robust, efficient and consistent manner. A new method referred to for the first time as two event-related moving averages (“TERMA”) involves event-related moving averages and detects events in biomedical signals. The TERMA framework is flexible and universal and consists of six independent LEGO building bricks to achieve high accuracy detection of biomedical events. Results recommend that the window sizes for the two moving averages (W1 and W2) have to follow the inequality (8×W1)≥W2≥(2×W1). Moreover, TERMA is a simple yet efficient event detector that is suitable for wearable devices, point-of-care devices, fitness trackers and smart watches, compared to more complex machine learning solutions. PMID:27827852

25 CFR 700.173 - Average net earnings of business or farm.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 25 Indians 2 2011-04-01 2011-04-01 false Average net earnings of business or farm. 700.173 Section... PROCEDURES Moving and Related Expenses, Temporary Emergency Moves § 700.173 Average net earnings of business or farm. (a) Computing net earnings. For purposes of this subpart, the average annual net earnings of...

25 CFR 700.173 - Average net earnings of business or farm.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 25 Indians 2 2010-04-01 2010-04-01 false Average net earnings of business or farm. 700.173 Section... PROCEDURES Moving and Related Expenses, Temporary Emergency Moves § 700.173 Average net earnings of business or farm. (a) Computing net earnings. For purposes of this subpart, the average annual net earnings of...

Identification of moving vehicle forces on bridge structures via moving average Tikhonov regularization

NASA Astrophysics Data System (ADS)

Pan, Chu-Dong; Yu, Ling; Liu, Huan-Lin

2017-08-01

Traffic-induced moving force identification (MFI) is a typical inverse problem in the field of bridge structural health monitoring. Lots of regularization-based methods have been proposed for MFI. However, the MFI accuracy obtained from the existing methods is low when the moving forces enter into and exit a bridge deck due to low sensitivity of structural responses to the forces at these zones. To overcome this shortcoming, a novel moving average Tikhonov regularization method is proposed for MFI by combining with the moving average concepts. Firstly, the bridge-vehicle interaction moving force is assumed as a discrete finite signal with stable average value (DFS-SAV). Secondly, the reasonable signal feature of DFS-SAV is quantified and introduced for improving the penalty function (∣∣x∣∣2 2) defined in the classical Tikhonov regularization. Then, a feasible two-step strategy is proposed for selecting regularization parameter and balance coefficient defined in the improved penalty function. Finally, both numerical simulations on a simply-supported beam and laboratory experiments on a hollow tube beam are performed for assessing the accuracy and the feasibility of the proposed method. The illustrated results show that the moving forces can be accurately identified with a strong robustness. Some related issues, such as selection of moving window length, effect of different penalty functions, and effect of different car speeds, are discussed as well.

Development of a Robust Identifier for NPPs Transients Combining ARIMA Model and EBP Algorithm

NASA Astrophysics Data System (ADS)

Moshkbar-Bakhshayesh, Khalil; Ghofrani, Mohammad B.

2014-08-01

This study introduces a novel identification method for recognition of nuclear power plants (NPPs) transients by combining the autoregressive integrated moving-average (ARIMA) model and the neural network with error backpropagation (EBP) learning algorithm. The proposed method consists of three steps. First, an EBP based identifier is adopted to distinguish the plant normal states from the faulty ones. In the second step, ARIMA models use integrated (I) process to convert non-stationary data of the selected variables into stationary ones. Subsequently, ARIMA processes, including autoregressive (AR), moving-average (MA), or autoregressive moving-average (ARMA) are used to forecast time series of the selected plant variables. In the third step, for identification the type of transients, the forecasted time series are fed to the modular identifier which has been developed using the latest advances of EBP learning algorithm. Bushehr nuclear power plant (BNPP) transients are probed to analyze the ability of the proposed identifier. Recognition of transient is based on similarity of its statistical properties to the reference one, rather than the values of input patterns. More robustness against noisy data and improvement balance between memorization and generalization are salient advantages of the proposed identifier. Reduction of false identification, sole dependency of identification on the sign of each output signal, selection of the plant variables for transients training independent of each other, and extendibility for identification of more transients without unfavorable effects are other merits of the proposed identifier.

Fast Algorithms for Mining Co-evolving Time Series

DTIC Science & Technology

2011-09-01

Keogh et al., 2001, 2004] and (b) forecasting, like an autoregressive integrated moving average model ( ARIMA ) and related meth- ods [Box et al., 1994...computing hardware? We develop models to mine time series with missing values, to extract compact representation from time sequences, to segment the...sequences, and to do forecasting. For large scale data, we propose algorithms for learning time series models , in particular, including Linear Dynamical

Time Series Modelling of Syphilis Incidence in China from 2005 to 2012

PubMed Central

Zhang, Xingyu; Zhang, Tao; Pei, Jiao; Liu, Yuanyuan; Li, Xiaosong; Medrano-Gracia, Pau

2016-01-01

Background The infection rate of syphilis in China has increased dramatically in recent decades, becoming a serious public health concern. Early prediction of syphilis is therefore of great importance for heath planning and management. Methods In this paper, we analyzed surveillance time series data for primary, secondary, tertiary, congenital and latent syphilis in mainland China from 2005 to 2012. Seasonality and long-term trend were explored with decomposition methods. Autoregressive integrated moving average (ARIMA) was used to fit a univariate time series model of syphilis incidence. A separate multi-variable time series for each syphilis type was also tested using an autoregressive integrated moving average model with exogenous variables (ARIMAX). Results The syphilis incidence rates have increased three-fold from 2005 to 2012. All syphilis time series showed strong seasonality and increasing long-term trend. Both ARIMA and ARIMAX models fitted and estimated syphilis incidence well. All univariate time series showed highest goodness-of-fit results with the ARIMA(0,0,1)×(0,1,1) model. Conclusion Time series analysis was an effective tool for modelling the historical and future incidence of syphilis in China. The ARIMAX model showed superior performance than the ARIMA model for the modelling of syphilis incidence. Time series correlations existed between the models for primary, secondary, tertiary, congenital and latent syphilis. PMID:26901682

Time Series Modelling of Syphilis Incidence in China from 2005 to 2012.

PubMed

Zhang, Xingyu; Zhang, Tao; Pei, Jiao; Liu, Yuanyuan; Li, Xiaosong; Medrano-Gracia, Pau

2016-01-01

The infection rate of syphilis in China has increased dramatically in recent decades, becoming a serious public health concern. Early prediction of syphilis is therefore of great importance for heath planning and management. In this paper, we analyzed surveillance time series data for primary, secondary, tertiary, congenital and latent syphilis in mainland China from 2005 to 2012. Seasonality and long-term trend were explored with decomposition methods. Autoregressive integrated moving average (ARIMA) was used to fit a univariate time series model of syphilis incidence. A separate multi-variable time series for each syphilis type was also tested using an autoregressive integrated moving average model with exogenous variables (ARIMAX). The syphilis incidence rates have increased three-fold from 2005 to 2012. All syphilis time series showed strong seasonality and increasing long-term trend. Both ARIMA and ARIMAX models fitted and estimated syphilis incidence well. All univariate time series showed highest goodness-of-fit results with the ARIMA(0,0,1)×(0,1,1) model. Time series analysis was an effective tool for modelling the historical and future incidence of syphilis in China. The ARIMAX model showed superior performance than the ARIMA model for the modelling of syphilis incidence. Time series correlations existed between the models for primary, secondary, tertiary, congenital and latent syphilis.

Time Series in Education: The Analysis of Daily Attendance in Two High Schools

ERIC Educational Resources Information Center

Koopmans, Matthijs

2011-01-01

This presentation discusses the use of a time series approach to the analysis of daily attendance in two urban high schools over the course of one school year (2009-10). After establishing that the series for both schools were stationary, they were examined for moving average processes, autoregression, seasonal dependencies (weekly cycles),…

A Comparison of Alternative Approaches to the Analysis of Interrupted Time-Series.

ERIC Educational Resources Information Center

Harrop, John W.; Velicer, Wayne F.

1985-01-01

Computer generated data representative of 16 Auto Regressive Integrated Moving Averages (ARIMA) models were used to compare the results of interrupted time-series analysis using: (1) the known model identification, (2) an assumed (l,0,0) model, and (3) an assumed (3,0,0) model as an approximation to the General Transformation approach. (Author/BW)

Cause Resolving of Typhoon Precipitation Using Principle Component Analysis under Complex Interactive Effect of Terrain, Monsoon and Typhoon Vortex

NASA Astrophysics Data System (ADS)

Huang, C. L.; Hsu, N. S.

2015-12-01

This study develops a novel methodology to resolve the cause of typhoon-induced precipitation using principle component analysis (PCA) and to develop a long lead-time precipitation prediction model. The discovered spatial and temporal features of rainfall are utilized to develop a state-of-the-art descriptive statistical model which can be used to predict long lead-time precipitation during typhoons. The time series of 12-hour precipitation from different types of invasive moving track of typhoons are respectively precede the signal analytical process to qualify the causes of rainfall and to quantify affected degree of each induced cause. The causes include: (1) interaction between typhoon rain band and terrain; (2) co-movement effect induced by typhoon wind field with monsoon; (3) pressure gradient; (4) wind velocity; (5) temperature environment; (6) characteristic distance between typhoon center and surface target station; (7) distance between grade 7 storm radius and surface target station; and (8) relative humidity. The results obtained from PCA can detect the hidden pattern of the eight causes in space and time and can understand the future trends and changes of precipitation. This study applies the developed methodology in Taiwan Island which is constituted by complex diverse terrain formation and height. Results show that: (1) for the typhoon moving toward the direction of 245° to 330°, Causes (1), (2) and (6) are the primary ones to generate rainfall; and (2) for the direction of 330° to 380°, Causes (1), (4) and (6) are the primary ones. Besides, the developed precipitation prediction model by using PCA with the distributed moving track approach (PCA-DMT) is 32% more accurate by that of PCA without distributed moving track approach, and the former model can effectively achieve long lead-time precipitation prediction with an average predicted error of 13% within average 48 hours of forecasted lead-time.

Time series analysis of collective motions in proteins

NASA Astrophysics Data System (ADS)

Alakent, Burak; Doruker, Pemra; ćamurdan, Mehmet C.

2004-01-01

The dynamics of α-amylase inhibitor tendamistat around its native state is investigated using time series analysis of the principal components of the Cα atomic displacements obtained from molecular dynamics trajectories. Collective motion along a principal component is modeled as a homogeneous nonstationary process, which is the result of the damped oscillations in local minima superimposed on a random walk. The motion in local minima is described by a stationary autoregressive moving average model, consisting of the frequency, damping factor, moving average parameters and random shock terms. Frequencies for the first 50 principal components are found to be in the 3-25 cm-1 range, which are well correlated with the principal component indices and also with atomistic normal mode analysis results. Damping factors, though their correlation is less pronounced, decrease as principal component indices increase, indicating that low frequency motions are less affected by friction. The existence of a positive moving average parameter indicates that the stochastic force term is likely to disturb the mode in opposite directions for two successive sampling times, showing the modes tendency to stay close to minimum. All these four parameters affect the mean square fluctuations of a principal mode within a single minimum. The inter-minima transitions are described by a random walk model, which is driven by a random shock term considerably smaller than that for the intra-minimum motion. The principal modes are classified into three subspaces based on their dynamics: essential, semiconstrained, and constrained, at least in partial consistency with previous studies. The Gaussian-type distributions of the intermediate modes, called "semiconstrained" modes, are explained by asserting that this random walk behavior is not completely free but between energy barriers.

Autoregressive-moving-average hidden Markov model for vision-based fall prediction-An application for walker robot.

PubMed

Taghvaei, Sajjad; Jahanandish, Mohammad Hasan; Kosuge, Kazuhiro

2017-01-01

Population aging of the societies requires providing the elderly with safe and dependable assistive technologies in daily life activities. Improving the fall detection algorithms can play a major role in achieving this goal. This article proposes a real-time fall prediction algorithm based on the acquired visual data of a user with walking assistive system from a depth sensor. In the lack of a coupled dynamic model of the human and the assistive walker a hybrid "system identification-machine learning" approach is used. An autoregressive-moving-average (ARMA) model is fitted on the time-series walking data to forecast the upcoming states, and a hidden Markov model (HMM) based classifier is built on the top of the ARMA model to predict falling in the upcoming time frames. The performance of the algorithm is evaluated through experiments with four subjects including an experienced physiotherapist while using a walker robot in five different falling scenarios; namely, fall forward, fall down, fall back, fall left, and fall right. The algorithm successfully predicts the fall with a rate of 84.72%.

Real-time mid-infrared imaging of living microorganisms.

PubMed

Haase, Katharina; Kröger-Lui, Niels; Pucci, Annemarie; Schönhals, Arthur; Petrich, Wolfgang

2016-01-01

The speed and efficiency of quantum cascade laser-based mid-infrared microspectroscopy are demonstrated using two different model organisms as examples. For the slowly moving Amoeba proteus, a quantum cascade laser is tuned over the wavelength range of 7.6 µm to 8.6 µm (wavenumbers 1320 cm(-1) and 1160 cm(-1) , respectively). The recording of a hyperspectral image takes 11.3 s whereby an average signal-to-noise ratio of 29 is achieved. The limits of time resolution are tested by imaging the fast moving Caenorhabditis elegans at a discrete wavenumber of 1265 cm(-1) . Mid-infrared imaging is performed with the 640 × 480 pixel video graphics array (VGA) standard and at a full-frame time resolution of 0.02 s (i.e. well above the most common frame rate standards). An average signal-to-noise ratio of 16 is obtained. To the best of our knowledge, these findings constitute the first mid-infrared imaging of living organisms at VGA standard and video frame rate. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Class III correction using an inter-arch spring-loaded module

PubMed Central

2014-01-01

Background A retrospective study was conducted to determine the cephalometric changes in a group of Class III patients treated with the inter-arch spring-loaded module (CS2000®, Dynaflex, St. Ann, MO, USA). Methods Thirty Caucasian patients (15 males, 15 females) with an average pre-treatment age of 9.6 years were treated consecutively with this appliance and compared with a control group of subjects from the Bolton-Brush Study who were matched in age, gender, and craniofacial morphology to the treatment group. Lateral cephalograms were taken before treatment and after removal of the CS2000® appliance. The treatment effects of the CS2000® appliance were calculated by subtracting the changes due to growth (control group) from the treatment changes. Results All patients were improved to a Class I dental arch relationship with a positive overjet. Significant sagittal, vertical, and angular changes were found between the pre- and post-treatment radiographs. With an average treatment time of 1.3 years, the maxillary base moved forward by 0.8 mm, while the mandibular base moved backward by 2.8 mm together with improvements in the ANB and Wits measurements. The maxillary incisor moved forward by 1.3 mm and the mandibular incisor moved forward by 1.0 mm. The maxillary molar moved forward by 1.0 mm while the mandibular molar moved backward by 0.6 mm. The average overjet correction was 3.9 mm and 92% of the correction was due to skeletal contribution and 8% was due to dental contribution. The average molar correction was 5.2 mm and 69% of the correction was due to skeletal contribution and 31% was due to dental contribution. Conclusions Mild to moderate Class III malocclusion can be corrected using the inter-arch spring-loaded appliance with minimal patient compliance. The overjet correction was contributed by forward movement of the maxilla, backward and downward movement of the mandible, and proclination of the maxillary incisors. The molar relationship was corrected by mesialization of the maxillary molars, distalization of the mandibular molars together with a rotation of the occlusal plane. PMID:24934153

Long-Term PM2.5 Exposure and Respiratory, Cancer, and Cardiovascular Mortality in Older US Adults.

PubMed

Pun, Vivian C; Kazemiparkouhi, Fatemeh; Manjourides, Justin; Suh, Helen H

2017-10-15

The impact of chronic exposure to fine particulate matter (particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM2.5)) on respiratory disease and lung cancer mortality is poorly understood. In a cohort of 18.9 million Medicare beneficiaries (4.2 million deaths) living across the conterminous United States between 2000 and 2008, we examined the association between chronic PM2.5 exposure and cause-specific mortality. We evaluated confounding through adjustment for neighborhood behavioral covariates and decomposition of PM2.5 into 2 spatiotemporal scales. We found significantly positive associations of 12-month moving average PM2.5 exposures (per 10-μg/m3 increase) with respiratory, chronic obstructive pulmonary disease, and pneumonia mortality, with risk ratios ranging from 1.10 to 1.24. We also found significant PM2.5-associated elevated risks for cardiovascular and lung cancer mortality. Risk ratios generally increased with longer moving averages; for example, an elevation in 60-month moving average PM2.5 exposures was linked to 1.33 times the lung cancer mortality risk (95% confidence interval: 1.24, 1.40), as compared with 1.13 (95% confidence interval: 1.11, 1.15) for 12-month moving average exposures. Observed associations were robust in multivariable models, although evidence of unmeasured confounding remained. In this large cohort of US elderly, we provide important new evidence that long-term PM2.5 exposure is significantly related to increased mortality from respiratory disease, lung cancer, and cardiovascular disease. © The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Forecasting Daily Patient Outflow From a Ward Having No Real-Time Clinical Data

PubMed Central

Tran, Truyen; Luo, Wei; Phung, Dinh; Venkatesh, Svetha

2016-01-01

Background: Modeling patient flow is crucial in understanding resource demand and prioritization. We study patient outflow from an open ward in an Australian hospital, where currently bed allocation is carried out by a manager relying on past experiences and looking at demand. Automatic methods that provide a reasonable estimate of total next-day discharges can aid in efficient bed management. The challenges in building such methods lie in dealing with large amounts of discharge noise introduced by the nonlinear nature of hospital procedures, and the nonavailability of real-time clinical information in wards. Objective Our study investigates different models to forecast the total number of next-day discharges from an open ward having no real-time clinical data. Methods We compared 5 popular regression algorithms to model total next-day discharges: (1) autoregressive integrated moving average (ARIMA), (2) the autoregressive moving average with exogenous variables (ARMAX), (3) k-nearest neighbor regression, (4) random forest regression, and (5) support vector regression. Although the autoregressive integrated moving average model relied on past 3-month discharges, nearest neighbor forecasting used median of similar discharges in the past in estimating next-day discharge. In addition, the ARMAX model used the day of the week and number of patients currently in ward as exogenous variables. For the random forest and support vector regression models, we designed a predictor set of 20 patient features and 88 ward-level features. Results Our data consisted of 12,141 patient visits over 1826 days. Forecasting quality was measured using mean forecast error, mean absolute error, symmetric mean absolute percentage error, and root mean square error. When compared with a moving average prediction model, all 5 models demonstrated superior performance with the random forests achieving 22.7% improvement in mean absolute error, for all days in the year 2014. Conclusions In the absence of clinical information, our study recommends using patient-level and ward-level data in predicting next-day discharges. Random forest and support vector regression models are able to use all available features from such data, resulting in superior performance over traditional autoregressive methods. An intelligent estimate of available beds in wards plays a crucial role in relieving access block in emergency departments. PMID:27444059

The Press Relations of a Local School District: An Analysis of the Emergence of School Issues.

ERIC Educational Resources Information Center

Morris, Jon R.; Guenter, Cornelius

Press coverage of a suburban midwest school district is analyzed as a set of time series of observations including the amount and quality of coverage. Possible shifts in these series because of the emergence of controversial issues are analyzed statistically using the Integrated Moving Average Time Series Model. Evidence of significant shifts in…

Instantaneous Velocity Using Photogate Timers

ERIC Educational Resources Information Center

Wolbeck, John

2010-01-01

Photogate timers are commonly used in physics laboratories to determine the velocity of a passing object. In this application a card attached to a moving object breaks the beam of the photogate timer providing the time for the card to pass. The length L of the passing card can then be divided by this time to yield the average velocity (or speed)…

Smoothing Strategies Combined with ARIMA and Neural Networks to Improve the Forecasting of Traffic Accidents

PubMed Central

Rodríguez, Nibaldo

2014-01-01

Two smoothing strategies combined with autoregressive integrated moving average (ARIMA) and autoregressive neural networks (ANNs) models to improve the forecasting of time series are presented. The strategy of forecasting is implemented using two stages. In the first stage the time series is smoothed using either, 3-point moving average smoothing, or singular value Decomposition of the Hankel matrix (HSVD). In the second stage, an ARIMA model and two ANNs for one-step-ahead time series forecasting are used. The coefficients of the first ANN are estimated through the particle swarm optimization (PSO) learning algorithm, while the coefficients of the second ANN are estimated with the resilient backpropagation (RPROP) learning algorithm. The proposed models are evaluated using a weekly time series of traffic accidents of Valparaíso, Chilean region, from 2003 to 2012. The best result is given by the combination HSVD-ARIMA, with a MAPE of 0 : 26%, followed by MA-ARIMA with a MAPE of 1 : 12%; the worst result is given by the MA-ANN based on PSO with a MAPE of 15 : 51%. PMID:25243200

Timescale Halo: Average-Speed Targets Elicit More Positive and Less Negative Attributions than Slow or Fast Targets

PubMed Central

Hernandez, Ivan; Preston, Jesse Lee; Hepler, Justin

2014-01-01

Research on the timescale bias has found that observers perceive more capacity for mind in targets moving at an average speed, relative to slow or fast moving targets. The present research revisited the timescale bias as a type of halo effect, where normal-speed people elicit positive evaluations and abnormal-speed (slow and fast) people elicit negative evaluations. In two studies, participants viewed videos of people walking at a slow, average, or fast speed. We find evidence for a timescale halo effect: people walking at an average-speed were attributed more positive mental traits, but fewer negative mental traits, relative to slow or fast moving people. These effects held across both cognitive and emotional dimensions of mind and were mediated by overall positive/negative ratings of the person. These results suggest that, rather than eliciting greater perceptions of general mind, the timescale bias may reflect a generalized positivity toward average speed people relative to slow or fast moving people. PMID:24421882

HELIOSHEATH MAGNETIC FIELDS BETWEEN 104 AND 113 AU IN A REGION OF DECLINING SPEEDS AND A STAGNATION REGION

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

Burlaga, L. F.; Ness, N. F., E-mail: lburlagahsp@verizon.net, E-mail: nfnudel@yahoo.com

2012-04-10

We examine the relationships between the magnetic field and the radial velocity component V{sub R} observed in the heliosheath by instruments on Voyager 1 (V1). No increase in the magnetic field strength B was observed in a region where V{sub R} decreased linearly from 70 km s{sup -1} to 0 km s{sup -1} as plasma moved outward past V1. An unusually broad transition from positive to negative polarity was observed during a Almost-Equal-To 26 day interval when the heliospheric current sheet (HCS) moved below the latitude of V1 and the speed of V1 was comparable to the radial speed ofmore » the heliosheath flow. When V1 moved through a region where V{sub R} Almost-Equal-To 0 (the 'stagnation region'), B increased linearly with time by a factor of two, and the average of B was 0.14 nT. Nothing comparable to this was observed previously. The magnetic polarity was negative throughout the stagnation region for Almost-Equal-To 580 days until 2011 DOY 235, indicating that the HCS was below the latitude of V1. The average passage times of the magnetic holes and proton boundary layers were the same during 2009 and 2011, because the plasma moved past V1 during 2009 at the same speed that V1 moved through the stagnation region during 2011. The microscale fluctuations of B in the stagnation region during 2011 are qualitatively the same as those observed in the heliosheath during 2009. These results suggest that the stagnation region is a part of the heliosheath, rather than a 'transition region' associated with the heliopause.« less

Use of the temporal median and trimmed mean mitigates effects of respiratory motion in multiple-acquisition abdominal diffusion imaging

NASA Astrophysics Data System (ADS)

Jerome, N. P.; Orton, M. R.; d'Arcy, J. A.; Feiweier, T.; Tunariu, N.; Koh, D.-M.; Leach, M. O.; Collins, D. J.

2015-01-01

Respiratory motion commonly confounds abdominal diffusion-weighted magnetic resonance imaging, where averaging of successive samples at different parts of the respiratory cycle, performed in the scanner, manifests the motion as blurring of tissue boundaries and structural features and can introduce bias into calculated diffusion metrics. Storing multiple averages separately allows processing using metrics other than the mean; in this prospective volunteer study, median and trimmed mean values of signal intensity for each voxel over repeated averages and diffusion-weighting directions are shown to give images with sharper tissue boundaries and structural features for moving tissues, while not compromising non-moving structures. Expert visual scoring of derived diffusion maps is significantly higher for the median than for the mean, with modest improvement from the trimmed mean. Diffusion metrics derived from mono- and bi-exponential diffusion models are comparable for non-moving structures, demonstrating a lack of introduced bias from using the median. The use of the median is a simple and computationally inexpensive alternative to complex and expensive registration algorithms, requiring only additional data storage (and no additional scanning time) while returning visually superior images that will facilitate the appropriate placement of regions-of-interest when analysing abdominal diffusion-weighted magnetic resonance images, for assessment of disease characteristics and treatment response.

Use of the temporal median and trimmed mean mitigates effects of respiratory motion in multiple-acquisition abdominal diffusion imaging.

PubMed

Jerome, N P; Orton, M R; d'Arcy, J A; Feiweier, T; Tunariu, N; Koh, D-M; Leach, M O; Collins, D J

2015-01-21

Respiratory motion commonly confounds abdominal diffusion-weighted magnetic resonance imaging, where averaging of successive samples at different parts of the respiratory cycle, performed in the scanner, manifests the motion as blurring of tissue boundaries and structural features and can introduce bias into calculated diffusion metrics. Storing multiple averages separately allows processing using metrics other than the mean; in this prospective volunteer study, median and trimmed mean values of signal intensity for each voxel over repeated averages and diffusion-weighting directions are shown to give images with sharper tissue boundaries and structural features for moving tissues, while not compromising non-moving structures. Expert visual scoring of derived diffusion maps is significantly higher for the median than for the mean, with modest improvement from the trimmed mean. Diffusion metrics derived from mono- and bi-exponential diffusion models are comparable for non-moving structures, demonstrating a lack of introduced bias from using the median. The use of the median is a simple and computationally inexpensive alternative to complex and expensive registration algorithms, requiring only additional data storage (and no additional scanning time) while returning visually superior images that will facilitate the appropriate placement of regions-of-interest when analysing abdominal diffusion-weighted magnetic resonance images, for assessment of disease characteristics and treatment response.

Leg kinematics and muscle activity during treadmill running in the cockroach, Blaberus discoidalis: I. Slow running.

PubMed

Watson, J T; Ritzmann, R E

1998-01-01

We have combined high-speed video motion analysis of leg movements with electromyogram (EMG) recordings from leg muscles in cockroaches running on a treadmill. The mesothoracic (T2) and metathoracic (T3) legs have different kinematics. While in each leg the coxa-femur (CF) joint moves in unison with the femurtibia (FT) joint, the relative joint excursions differ between T2 and T3 legs. In T3 legs, the two joints move through approximately the same excursion. In T2 legs, the FT joint moves through a narrower range of angles than the CF joint. In spite of these differences in motion, no differences between the T2 and T3 legs were seen in timing or qualitative patterns of depressor coxa and extensor tibia activity. The average firing frequencies of slow depressor coxa (Ds) and slow extensor tibia (SETi) motor neurons are directly proportional to the average angular velocity of their joints during stance. The average Ds and SETi firing frequency appears to be modulated on a cycle-by-cycle basis to control running speed and orientation. In contrast, while the frequency variations within Ds and SETi bursts were consistent across cycles, the variations within each burst did not parallel variations in the velocity of the relevant joints.

[Establishing and applying of autoregressive integrated moving average model to predict the incidence rate of dysentery in Shanghai].

PubMed

Li, Jian; Wu, Huan-Yu; Li, Yan-Ting; Jin, Hui-Ming; Gu, Bao-Ke; Yuan, Zheng-An

2010-01-01

To explore the feasibility of establishing and applying of autoregressive integrated moving average (ARIMA) model to predict the incidence rate of dysentery in Shanghai, so as to provide the theoretical basis for prevention and control of dysentery. ARIMA model was established based on the monthly incidence rate of dysentery of Shanghai from 1990 to 2007. The parameters of model were estimated through unconditional least squares method, the structure was determined according to criteria of residual un-correlation and conclusion, and the model goodness-of-fit was determined through Akaike information criterion (AIC) and Schwarz Bayesian criterion (SBC). The constructed optimal model was applied to predict the incidence rate of dysentery of Shanghai in 2008 and evaluate the validity of model through comparing the difference of predicted incidence rate and actual one. The incidence rate of dysentery in 2010 was predicted by ARIMA model based on the incidence rate from January 1990 to June 2009. The model ARIMA (1, 1, 1) (0, 1, 2)(12) had a good fitness to the incidence rate with both autoregressive coefficient (AR1 = 0.443) during the past time series, moving average coefficient (MA1 = 0.806) and seasonal moving average coefficient (SMA1 = 0.543, SMA2 = 0.321) being statistically significant (P < 0.01). AIC and SBC were 2.878 and 16.131 respectively and predicting error was white noise. The mathematic function was (1-0.443B) (1-B) (1-B(12))Z(t) = (1-0.806B) (1-0.543B(12)) (1-0.321B(2) x 12) micro(t). The predicted incidence rate in 2008 was consistent with the actual one, with the relative error of 6.78%. The predicted incidence rate of dysentery in 2010 based on the incidence rate from January 1990 to June 2009 would be 9.390 per 100 thousand. ARIMA model can be used to fit the changes of incidence rate of dysentery and to forecast the future incidence rate in Shanghai. It is a predicted model of high precision for short-time forecast.

Examination of the Armagh Observatory Annual Mean Temperature Record, 1844-2004

NASA Technical Reports Server (NTRS)

Wilson, Robert M.; Hathaway, David H.

2006-01-01

The long-term annual mean temperature record (1844-2004) of the Armagh Observatory (Armagh, Northern Ireland, United Kingdom) is examined for evidence of systematic variation, in particular, as related to solar/geomagnetic forcing and secular variation. Indeed, both are apparent in the temperature record. Moving averages for 10 years of temperature are found to highly correlate against both 10-year moving averages of the aa-geomagnetic index and sunspot number, having correlation coefficients of approx. 0.7, inferring that nearly half the variance in the 10-year moving average of temperature can be explained by solar/geomagnetic forcing. The residuals appear episodic in nature, with cooling seen in the 1880s and again near 1980. Seven of the last 10 years of the temperature record has exceeded 10 C, unprecedented in the overall record. Variation of sunspot cyclic averages and 2-cycle moving averages of temperature strongly associate with similar averages for the solar/geomagnetic cycle, with the residuals displaying an apparent 9-cycle variation and a steep rise in temperature associated with cycle 23. Hale cycle averages of temperature for even-odd pairs of sunspot cycles correlate against similar averages for the solar/geomagnetic cycle and, especially, against the length of the Hale cycle. Indications are that annual mean temperature will likely exceed 10 C over the next decade.

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.

Structural Equation Modeling of Multivariate Time Series

ERIC Educational Resources Information Center

du Toit, Stephen H. C.; Browne, Michael W.

2007-01-01

The covariance structure of a vector autoregressive process with moving average residuals (VARMA) is derived. It differs from other available expressions for the covariance function of a stationary VARMA process and is compatible with current structural equation methodology. Structural equation modeling programs, such as LISREL, may therefore be…

ARMA-Based SEM When the Number of Time Points T Exceeds the Number of Cases N: Raw Data Maximum Likelihood.

ERIC Educational Resources Information Center

Hamaker, Ellen L.; Dolan, Conor V.; Molenaar, Peter C. M.

2003-01-01

Demonstrated, through simulation, that stationary autoregressive moving average (ARMA) models may be fitted readily when T>N, using normal theory raw maximum likelihood structural equation modeling. Also provides some illustrations based on real data. (SLD)

A stochastic approach to noise modeling for barometric altimeters.

PubMed

Sabatini, Angelo Maria; Genovese, Vincenzo

2013-11-18

The question whether barometric altimeters can be applied to accurately track human motions is still debated, since their measurement performance are rather poor due to either coarse resolution or drifting behavior problems. As a step toward accurate short-time tracking of changes in height (up to few minutes), we develop a stochastic model that attempts to capture some statistical properties of the barometric altimeter noise. The barometric altimeter noise is decomposed in three components with different physical origin and properties: a deterministic time-varying mean, mainly correlated with global environment changes, and a first-order Gauss-Markov (GM) random process, mainly accounting for short-term, local environment changes, the effects of which are prominent, respectively, for long-time and short-time motion tracking; an uncorrelated random process, mainly due to wideband electronic noise, including quantization noise. Autoregressive-moving average (ARMA) system identification techniques are used to capture the correlation structure of the piecewise stationary GM component, and to estimate its standard deviation, together with the standard deviation of the uncorrelated component. M-point moving average filters used alone or in combination with whitening filters learnt from ARMA model parameters are further tested in few dynamic motion experiments and discussed for their capability of short-time tracking small-amplitude, low-frequency motions.

Moving toward climate-informed agricultural decision support - can we use PRISM data for more than just monthly averages?

USDA-ARS?s Scientific Manuscript database

Decision support systems/models for agriculture are varied in target application and complexity, ranging from simple worksheets to near real-time forecast systems requiring significant computational and manpower resources. Until recently, most such decision support systems have been constructed with...

Activity of radio-tagged black-footed ferrets

USGS Publications Warehouse

Biggins, Dean E.; Shroeder, Max H.; Forrest, Steven C.; Richardson, Louise

1986-01-01

Activity of two radio-tagged black-footed ferrets (Mustela nigripes) was investigated during October-November 1981 (an adult male monitored for 16 days), and during August-November 1982 (a young female monitored for 101 days). Aboveground activity of the male averaged 2.95 hr/night, 15% of the total time monitored. From 22 September to 5 November, aboveground activity of the female averaged 1.9 hours; 26% of the time she was stationary and 74% of the time she was moving. During August the juvenile female emerged at least once on 93% of the nights. She was least active in November. Both animals were primarily nocturnal (although daylight activity was not uncommon), and timing of nightly activity was similar, peaking from 0100 to 0359.

Demand Forecasting: An Evaluation of DODs Accuracy Metric and Navys Procedures

DTIC Science & Technology

2016-06-01

inventory management improvement plan, mean of absolute scaled error, lead time adjusted squared error, forecast accuracy, benchmarking, naïve method...Manager JASA Journal of the American Statistical Association LASE Lead-time Adjusted Squared Error LCI Life Cycle Indicator MA Moving Average MAE...Mean Squared Error xvi NAVSUP Naval Supply Systems Command NDAA National Defense Authorization Act NIIN National Individual Identification Number

Field evaluation of the error arising from inadequate time averaging in the standard use of depth-integrating suspended-sediment samplers

USGS Publications Warehouse

Topping, David J.; Rubin, David M.; Wright, Scott A.; Melis, Theodore S.

2011-01-01

Several common methods for measuring suspended-sediment concentration in rivers in the United States use depth-integrating samplers to collect a velocity-weighted suspended-sediment sample in a subsample of a river cross section. Because depth-integrating samplers are always moving through the water column as they collect a sample, and can collect only a limited volume of water and suspended sediment, they collect only minimally time-averaged data. Four sources of error exist in the field use of these samplers: (1) bed contamination, (2) pressure-driven inrush, (3) inadequate sampling of the cross-stream spatial structure in suspended-sediment concentration, and (4) inadequate time averaging. The first two of these errors arise from misuse of suspended-sediment samplers, and the third has been the subject of previous study using data collected in the sand-bedded Middle Loup River in Nebraska. Of these four sources of error, the least understood source of error arises from the fact that depth-integrating samplers collect only minimally time-averaged data. To evaluate this fourth source of error, we collected suspended-sediment data between 1995 and 2007 at four sites on the Colorado River in Utah and Arizona, using a P-61 suspended-sediment sampler deployed in both point- and one-way depth-integrating modes, and D-96-A1 and D-77 bag-type depth-integrating suspended-sediment samplers. These data indicate that the minimal duration of time averaging during standard field operation of depth-integrating samplers leads to an error that is comparable in magnitude to that arising from inadequate sampling of the cross-stream spatial structure in suspended-sediment concentration. This random error arising from inadequate time averaging is positively correlated with grain size and does not largely depend on flow conditions or, for a given size class of suspended sediment, on elevation above the bed. Averaging over time scales >1 minute is the likely minimum duration required to result in substantial decreases in this error. During standard two-way depth integration, a depth-integrating suspended-sediment sampler collects a sample of the water-sediment mixture during two transits at each vertical in a cross section: one transit while moving from the water surface to the bed, and another transit while moving from the bed to the water surface. As the number of transits is doubled at an individual vertical, this error is reduced by ~30 percent in each size class of suspended sediment. For a given size class of suspended sediment, the error arising from inadequate sampling of the cross-stream spatial structure in suspended-sediment concentration depends only on the number of verticals collected, whereas the error arising from inadequate time averaging depends on both the number of verticals collected and the number of transits collected at each vertical. Summing these two errors in quadrature yields a total uncertainty in an equal-discharge-increment (EDI) or equal-width-increment (EWI) measurement of the time-averaged velocity-weighted suspended-sediment concentration in a river cross section (exclusive of any laboratory-processing errors). By virtue of how the number of verticals and transits influences the two individual errors within this total uncertainty, the error arising from inadequate time averaging slightly dominates that arising from inadequate sampling of the cross-stream spatial structure in suspended-sediment concentration. Adding verticals to an EDI or EWI measurement is slightly more effective in reducing the total uncertainty than adding transits only at each vertical, because a new vertical contributes both temporal and spatial information. However, because collection of depth-integrated samples at more transits at each vertical is generally easier and faster than at more verticals, addition of a combination of verticals and transits is likely a more practical approach to reducing the total uncertainty in most field situatio

In-use activity, fuel use, and emissions of heavy-duty diesel roll-off refuse trucks.

PubMed

Sandhu, Gurdas S; Frey, H Christopher; Bartelt-Hunt, Shannon; Jones, Elizabeth

2015-03-01

The objectives of this study were to quantify real-world activity, fuel use, and emissions for heavy duty diesel roll-off refuse trucks; evaluate the contribution of duty cycles and emissions controls to variability in cycle average fuel use and emission rates; quantify the effect of vehicle weight on fuel use and emission rates; and compare empirical cycle average emission rates with the U.S. Environmental Protection Agency's MOVES emission factor model predictions. Measurements were made at 1 Hz on six trucks of model years 2005 to 2012, using onboard systems. The trucks traveled 870 miles, had an average speed of 16 mph, and collected 165 tons of trash. The average fuel economy was 4.4 mpg, which is approximately twice previously reported values for residential trash collection trucks. On average, 50% of time is spent idling and about 58% of emissions occur in urban areas. Newer trucks with selective catalytic reduction and diesel particulate filter had NOx and PM cycle average emission rates that were 80% lower and 95% lower, respectively, compared to older trucks without. On average, the combined can and trash weight was about 55% of chassis weight. The marginal effect of vehicle weight on fuel use and emissions is highest at low loads and decreases as load increases. Among 36 cycle average rates (6 trucks×6 cycles), MOVES-predicted values and estimates based on real-world data have similar relative trends. MOVES-predicted CO2 emissions are similar to those of the real world, while NOx and PM emissions are, on average, 43% lower and 300% higher, respectively. The real-world data presented here can be used to estimate benefits of replacing old trucks with new trucks. Further, the data can be used to improve emission inventories and model predictions. In-use measurements of the real-world activity, fuel use, and emissions of heavy-duty diesel roll-off refuse trucks can be used to improve the accuracy of predictive models, such as MOVES, and emissions inventories. Further, the activity data from this study can be used to generate more representative duty cycles for more accurate chassis dynamometer testing. Comparisons of old and new model year diesel trucks are useful in analyzing the effect of fleet turnover. The analysis of effect of haul weight on fuel use can be used by fleet managers to optimize operations to reduce fuel cost.

On the Relationship between Solar Wind Speed, Earthward-Directed Coronal Mass Ejections, Geomagnetic Activity, and the Sunspot Cycle Using 12-Month Moving Averages

NASA Technical Reports Server (NTRS)

Wilson, Robert M.; Hathaway, David H.

2008-01-01

For 1996 .2006 (cycle 23), 12-month moving averages of the aa geomagnetic index strongly correlate (r = 0.92) with 12-month moving averages of solar wind speed, and 12-month moving averages of the number of coronal mass ejections (CMEs) (halo and partial halo events) strongly correlate (r = 0.87) with 12-month moving averages of sunspot number. In particular, the minimum (15.8, September/October 1997) and maximum (38.0, August 2003) values of the aa geomagnetic index occur simultaneously with the minimum (376 km/s) and maximum (547 km/s) solar wind speeds, both being strongly correlated with the following recurrent component (due to high-speed streams). The large peak of aa geomagnetic activity in cycle 23, the largest on record, spans the interval late 2002 to mid 2004 and is associated with a decreased number of halo and partial halo CMEs, whereas the smaller secondary peak of early 2005 seems to be associated with a slight rebound in the number of halo and partial halo CMEs. Based on the observed aaM during the declining portion of cycle 23, RM for cycle 24 is predicted to be larger than average, being about 168+/-60 (the 90% prediction interval), whereas based on the expected aam for cycle 24 (greater than or equal to 14.6), RM for cycle 24 should measure greater than or equal to 118+/-30, yielding an overlap of about 128+/-20.

Wildfire suppression cost forecasts from the US Forest Service

Treesearch

Karen L. Abt; Jeffrey P. Prestemon; Krista M. Gebert

2009-01-01

The US Forest Service and other land-management agencies seek better tools for nticipating future expenditures for wildfire suppression. We developed regression models for forecasting US Forest Service suppression spending at 1-, 2-, and 3-year lead times. We compared these models to another readily available forecast model, the 10-year moving average model,...

A simple derivation of Lorentz self-force

NASA Astrophysics Data System (ADS)

Haque, Asrarul

2014-09-01

We derive the Lorentz self-force for a charged particle in arbitrary non-relativistic motion by averaging the retarded fields. The derivation is simple and at the same time pedagogically accessible. We obtain the radiation reaction for a charged particle moving in a circle. We pin down the underlying concept of mass renormalization.

An efficient estimator to monitor rapidly changing forest conditions

Treesearch

Raymond L. Czaplewski; Michael T. Thompson; Gretchen G. Moisen

2012-01-01

Extensive expanses of forest often change at a slow pace. In this common situation, FIA produces informative estimates of current status with the Moving Average (MA) method and post-stratification with a remotely sensed map of forest-nonforest cover. However, MA "smoothes out" estimates over time, which confounds analyses of temporal trends; and post-...

Effects of Forecasts on the Revisions of Concurrent Seasonally Adjusted Data Using the X-11 Seasonal Adjustment Procedure.

ERIC Educational Resources Information Center

Bobbitt, Larry; Otto, Mark

Three Autoregressive Integrated Moving Averages (ARIMA) forecast procedures for Census Bureau X-11 concurrent seasonal adjustment were empirically tested. Forty time series from three Census Bureau economic divisions (business, construction, and industry) were analyzed. Forecasts were obtained from fitted seasonal ARIMA models augmented with…

Is Parental Involvement Lower at Larger Schools?

ERIC Educational Resources Information Center

Walsh, Patrick

2010-01-01

Parents who volunteer, or who lobby for improvements in school quality, are generally seen as providing a school-wide public good. If so, straightforward public-good theory predicts that free-riding will reduce average involvement at larger schools. This study uses longitudinal data to follow families over time, as their children move from middle…

Documentation of a spreadsheet for time-series analysis and drawdown estimation

USGS Publications Warehouse

Halford, Keith J.

2006-01-01

Drawdowns during aquifer tests can be obscured by barometric pressure changes, earth tides, regional pumping, and recharge events in the water-level record. These stresses can create water-level fluctuations that should be removed from observed water levels prior to estimating drawdowns. Simple models have been developed for estimating unpumped water levels during aquifer tests that are referred to as synthetic water levels. These models sum multiple time series such as barometric pressure, tidal potential, and background water levels to simulate non-pumping water levels. The amplitude and phase of each time series are adjusted so that synthetic water levels match measured water levels during periods unaffected by an aquifer test. Differences between synthetic and measured water levels are minimized with a sum-of-squares objective function. Root-mean-square errors during fitting and prediction periods were compared multiple times at four geographically diverse sites. Prediction error equaled fitting error when fitting periods were greater than or equal to four times prediction periods. The proposed drawdown estimation approach has been implemented in a spreadsheet application. Measured time series are independent so that collection frequencies can differ and sampling times can be asynchronous. Time series can be viewed selectively and magnified easily. Fitting and prediction periods can be defined graphically or entered directly. Synthetic water levels for each observation well are created with earth tides, measured time series, moving averages of time series, and differences between measured and moving averages of time series. Selected series and fitting parameters for synthetic water levels are stored and drawdowns are estimated for prediction periods. Drawdowns can be viewed independently and adjusted visually if an anomaly skews initial drawdowns away from 0. The number of observations in a drawdown time series can be reduced by averaging across user-defined periods. Raw or reduced drawdown estimates can be copied from the spreadsheet application or written to tab-delimited ASCII files.

Models for short term malaria prediction in Sri Lanka

PubMed Central

Briët, Olivier JT; Vounatsou, Penelope; Gunawardena, Dissanayake M; Galappaththy, Gawrie NL; Amerasinghe, Priyanie H

2008-01-01

Background Malaria in Sri Lanka is unstable and fluctuates in intensity both spatially and temporally. Although the case counts are dwindling at present, given the past history of resurgence of outbreaks despite effective control measures, the control programmes have to stay prepared. The availability of long time series of monitored/diagnosed malaria cases allows for the study of forecasting models, with an aim to developing a forecasting system which could assist in the efficient allocation of resources for malaria control. Methods Exponentially weighted moving average models, autoregressive integrated moving average (ARIMA) models with seasonal components, and seasonal multiplicative autoregressive integrated moving average (SARIMA) models were compared on monthly time series of district malaria cases for their ability to predict the number of malaria cases one to four months ahead. The addition of covariates such as the number of malaria cases in neighbouring districts or rainfall were assessed for their ability to improve prediction of selected (seasonal) ARIMA models. Results The best model for forecasting and the forecasting error varied strongly among the districts. The addition of rainfall as a covariate improved prediction of selected (seasonal) ARIMA models modestly in some districts but worsened prediction in other districts. Improvement by adding rainfall was more frequent at larger forecasting horizons. Conclusion Heterogeneity of patterns of malaria in Sri Lanka requires regionally specific prediction models. Prediction error was large at a minimum of 22% (for one of the districts) for one month ahead predictions. The modest improvement made in short term prediction by adding rainfall as a covariate to these prediction models may not be sufficient to merit investing in a forecasting system for which rainfall data are routinely processed. PMID:18460204

Compression of head-related transfer function using autoregressive-moving-average models and Legendre polynomials.

PubMed

Shekarchi, Sayedali; Hallam, John; Christensen-Dalsgaard, Jakob

2013-11-01

Head-related transfer functions (HRTFs) are generally large datasets, which can be an important constraint for embedded real-time applications. A method is proposed here to reduce redundancy and compress the datasets. In this method, HRTFs are first compressed by conversion into autoregressive-moving-average (ARMA) filters whose coefficients are calculated using Prony's method. Such filters are specified by a few coefficients which can generate the full head-related impulse responses (HRIRs). Next, Legendre polynomials (LPs) are used to compress the ARMA filter coefficients. LPs are derived on the sphere and form an orthonormal basis set for spherical functions. Higher-order LPs capture increasingly fine spatial details. The number of LPs needed to represent an HRTF, therefore, is indicative of its spatial complexity. The results indicate that compression ratios can exceed 98% while maintaining a spectral error of less than 4 dB in the recovered HRTFs.

Direct determination approach for the multifractal detrending moving average analysis

NASA Astrophysics Data System (ADS)

Xu, Hai-Chuan; Gu, Gao-Feng; Zhou, Wei-Xing

2017-11-01

In the canonical framework, we propose an alternative approach for the multifractal analysis based on the detrending moving average method (MF-DMA). We define a canonical measure such that the multifractal mass exponent τ (q ) is related to the partition function and the multifractal spectrum f (α ) can be directly determined. The performances of the direct determination approach and the traditional approach of the MF-DMA are compared based on three synthetic multifractal and monofractal measures generated from the one-dimensional p -model, the two-dimensional p -model, and the fractional Brownian motions. We find that both approaches have comparable performances to unveil the fractal and multifractal nature. In other words, without loss of accuracy, the multifractal spectrum f (α ) can be directly determined using the new approach with less computation cost. We also apply the new MF-DMA approach to the volatility time series of stock prices and confirm the presence of multifractality.

[A peak recognition algorithm designed for chromatographic peaks of transformer oil].

PubMed

Ou, Linjun; Cao, Jian

2014-09-01

In the field of the chromatographic peak identification of the transformer oil, the traditional first-order derivative requires slope threshold to achieve peak identification. In terms of its shortcomings of low automation and easy distortion, the first-order derivative method was improved by applying the moving average iterative method and the normalized analysis techniques to identify the peaks. Accurate identification of the chromatographic peaks was realized through using multiple iterations of the moving average of signal curves and square wave curves to determine the optimal value of the normalized peak identification parameters, combined with the absolute peak retention times and peak window. The experimental results show that this algorithm can accurately identify the peaks and is not sensitive to the noise, the chromatographic peak width or the peak shape changes. It has strong adaptability to meet the on-site requirements of online monitoring devices of dissolved gases in transformer oil.

Comparison of two non-convex mixed-integer nonlinear programming algorithms applied to autoregressive moving average model structure and parameter estimation

NASA Astrophysics Data System (ADS)

Uilhoorn, F. E.

2016-10-01

In this article, the stochastic modelling approach proposed by Box and Jenkins is treated as a mixed-integer nonlinear programming (MINLP) problem solved with a mesh adaptive direct search and a real-coded genetic class of algorithms. The aim is to estimate the real-valued parameters and non-negative integer, correlated structure of stationary autoregressive moving average (ARMA) processes. The maximum likelihood function of the stationary ARMA process is embedded in Akaike's information criterion and the Bayesian information criterion, whereas the estimation procedure is based on Kalman filter recursions. The constraints imposed on the objective function enforce stability and invertibility. The best ARMA model is regarded as the global minimum of the non-convex MINLP problem. The robustness and computational performance of the MINLP solvers are compared with brute-force enumeration. Numerical experiments are done for existing time series and one new data set.

Permeation of limonene through disposable nitrile gloves using a dextrous robot hand

PubMed Central

Banaee, Sean; S Que Hee, Shane

2017-01-01

Objectives: The purpose of this study was to investigate the permeation of the low-volatile solvent limonene through different disposable, unlined, unsupported, nitrile exam whole gloves (blue, purple, sterling, and lavender, from Kimberly-Clark). Methods: This study utilized a moving and static dextrous robot hand as part of a novel dynamic permeation system that allowed sampling at specific times. Quantitation of limonene in samples was based on capillary gas chromatography-mass spectrometry and the internal standard method (4-bromophenol). Results: The average post-permeation thicknesses (before reconditioning) for all gloves for both the moving and static hand were more than 10% of the pre-permeation ones (P≤0.05), although this was not so on reconditioning. The standardized breakthrough times and steady-state permeation periods were similar for the blue, purple, and sterling gloves. Both methods had similar sensitivity. The lavender glove showed a higher permeation rate (0.490±0.031 μg/cm2/min) for the moving robotic hand compared to the non-moving hand (P≤0.05), this being ascribed to a thickness threshold. Conclusions: Permeation parameters for the static and dynamic robot hand models indicate that both methods have similar sensitivity in detecting the analyte during permeation and the blue, purple, and sterling gloves behave similarly during the permeation process whether moving or non-moving. PMID:28111415

Modified Exponential Weighted Moving Average (EWMA) Control Chart on Autocorrelation Data

NASA Astrophysics Data System (ADS)

Herdiani, Erna Tri; Fandrilla, Geysa; Sunusi, Nurtiti

2018-03-01

In general, observations of the statistical process control are assumed to be mutually independence. However, this assumption is often violated in practice. Consequently, statistical process controls were developed for interrelated processes, including Shewhart, Cumulative Sum (CUSUM), and exponentially weighted moving average (EWMA) control charts in the data that were autocorrelation. One researcher stated that this chart is not suitable if the same control limits are used in the case of independent variables. For this reason, it is necessary to apply the time series model in building the control chart. A classical control chart for independent variables is usually applied to residual processes. This procedure is permitted provided that residuals are independent. In 1978, Shewhart modification for the autoregressive process was introduced by using the distance between the sample mean and the target value compared to the standard deviation of the autocorrelation process. In this paper we will examine the mean of EWMA for autocorrelation process derived from Montgomery and Patel. Performance to be investigated was investigated by examining Average Run Length (ARL) based on the Markov Chain Method.

Associations between Changes in City and Address Specific Temperature and QT Interval - The VA Normative Aging Study

PubMed Central

Mehta, Amar J.; Kloog, Itai; Zanobetti, Antonella; Coull, Brent A.; Sparrow, David; Vokonas, Pantel; Schwartz, Joel

2014-01-01

Background The underlying mechanisms of the association between ambient temperature and cardiovascular morbidity and mortality are not well understood, particularly for daily temperature variability. We evaluated if daily mean temperature and standard deviation of temperature was associated with heart rate-corrected QT interval (QTc) duration, a marker of ventricular repolarization in a prospective cohort of older men. Methods This longitudinal analysis included 487 older men participating in the VA Normative Aging Study with up to three visits between 2000–2008 (n = 743). We analyzed associations between QTc and moving averages (1–7, 14, 21, and 28 days) of the 24-hour mean and standard deviation of temperature as measured from a local weather monitor, and the 24-hour mean temperature estimated from a spatiotemporal prediction model, in time-varying linear mixed-effect regression. Effect modification by season, diabetes, coronary heart disease, obesity, and age was also evaluated. Results Higher mean temperature as measured from the local monitor, and estimated from the prediction model, was associated with longer QTc at moving averages of 21 and 28 days. Increased 24-hr standard deviation of temperature was associated with longer QTc at moving averages from 4 and up to 28 days; a 1.9°C interquartile range increase in 4-day moving average standard deviation of temperature was associated with a 2.8 msec (95%CI: 0.4, 5.2) longer QTc. Associations between 24-hr standard deviation of temperature and QTc were stronger in colder months, and in participants with diabetes and coronary heart disease. Conclusion/Significance In this sample of older men, elevated mean temperature was associated with longer QTc, and increased variability of temperature was associated with longer QTc, particularly during colder months and among individuals with diabetes and coronary heart disease. These findings may offer insight of an important underlying mechanism of temperature-related cardiovascular morbidity and mortality in an older population. PMID:25238150

Reduction of time-averaged irradiation speckle nonuniformity in laser-driven plasmas due to target ablation

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

Epstein, R.

1997-09-01

In inertial confinement fusion (ICF) experiments, irradiation uniformity is improved by passing laser beams through distributed phase plates (DPPs), which produce focused intensity profiles with well-controlled, reproducible envelopes modulated by fine random speckle. [C. B. Burckhardt, Appl. Opt. {bold 9}, 695 (1970); Y. Kato and K. Mima, Appl. Phys. B {bold 29}, 186 (1982); Y. Kato {ital et al.}, Phys. Rev. Lett. {bold 53}, 1057 (1984); Laboratory for Laser Energetics LLE Review 33, NTIS Document No. DOE/DP/40200-65, 1987 (unpublished), p. 1; Laboratory for Laser Energetics LLE Review 63, NTIS Document No. DOE/SF/19460-91, 1995 (unpublished), p. 1.] A uniformly ablating plasmamore » atmosphere acts to reduce the contribution of the speckle to the time-averaged irradiation nonuniformity by causing the intensity distribution to move relative to the absorption layer of the plasma. This occurs most directly as the absorption layer in the plasma moves with the ablation-driven flow, but it is shown that the effect of the accumulating ablated plasma on the phase of the laser light also makes a quantitatively significant contribution. Analytical results are obtained using the paraxial approximation applied to the beam propagation, and a simple statistical model is assumed for the properties of DPPs. The reduction in the time-averaged spatial spectrum of the speckle due to these effects is shown to be quantitatively significant within time intervals characteristic of atmospheric hydrodynamics under typical ICF irradiation intensities. {copyright} {ital 1997 American Institute of Physics.}« less

A 12-Year Analysis of Nonbattle Injury Among US Service Members Deployed to Iraq and Afghanistan.

PubMed

Le, Tuan D; Gurney, Jennifer M; Nnamani, Nina S; Gross, Kirby R; Chung, Kevin K; Stockinger, Zsolt T; Nessen, Shawn C; Pusateri, Anthony E; Akers, Kevin S

2018-05-30

Nonbattle injury (NBI) among deployed US service members increases the burden on medical systems and results in high rates of attrition, affecting the available force. The possible causes and trends of NBI in the Iraq and Afghanistan wars have, to date, not been comprehensively described. To describe NBI among service members deployed to Iraq and Afghanistan, quantify absolute numbers of NBIs and proportion of NBIs within the Department of Defense Trauma Registry, and document the characteristics of this injury category. In this retrospective cohort study, data from the Department of Defense Trauma Registry on 29 958 service members injured in Iraq and Afghanistan from January 1, 2003, through December 31, 2014, were obtained. Injury incidence, patterns, and severity were characterized by battle injury and NBI. Trends in NBI were modeled using time series analysis with autoregressive integrated moving average and the weighted moving average method. Statistical analysis was performed from January 1, 2003, to December 31, 2014. Primary outcomes were proportion of NBIs and the changes in NBI over time. Among 29 958 casualties (battle injury and NBI) analyzed, 29 003 were in men and 955 were in women; the median age at injury was 24 years (interquartile range, 21-29 years). Nonbattle injury caused 34.1% of total casualties (n = 10 203) and 11.5% of all deaths (206 of 1788). Rates of NBI were higher among women than among men (63.2% [604 of 955] vs 33.1% [9599 of 29 003]; P < .001) and in Operation New Dawn (71.0% [298 of 420]) and Operation Iraqi Freedom (36.3% [6655 of 18 334]) compared with Operation Enduring Freedom (29.0% [3250 of 11 204]) (P < .001). A higher proportion of NBIs occurred in members of the Air Force (66.3% [539 of 810]) and Navy (48.3% [394 of 815]) than in members of the Army (34.7% [7680 of 22 154]) and Marine Corps (25.7% [1584 of 6169]) (P < .001). Leading mechanisms of NBI included falls (2178 [21.3%]), motor vehicle crashes (1921 [18.8%]), machinery or equipment accidents (1283 [12.6%]), blunt objects (1107 [10.8%]), gunshot wounds (728 [7.1%]), and sports (697 [6.8%]), causing predominantly blunt trauma (7080 [69.4%]). The trend in proportion of NBIs did not decrease over time, remaining at approximately 35% (by weighted moving average) after 2006 and approximately 39% by autoregressive integrated moving average. Assuming stable battlefield conditions, the autoregressive integrated moving average model estimated that the proportion of NBIs from 2015 to 2022 would be approximately 41.0% (95% CI, 37.8%-44.3%). In this study, approximately one-third of injuries during the Iraq and Afghanistan wars resulted from NBI, and the proportion of NBIs was steady for 12 years. Understanding the possible causes of NBI during military operations may be useful to target protective measures and safety interventions, thereby conserving fighting strength on the battlefield.

Behavioural thermoregulation by subyearling fall (autumn) Chinook salmon oncorhynchus tshawytscha in a reservoir

USGS Publications Warehouse

Tiffan, K.F.; Kock, T.J.; Connor, W.P.; Steinhorst, R.K.; Rondorf, D.W.

2009-01-01

This study investigated behavioural thermoregulation by subyearling fall (autumn) Chinook salmon Oncorhynchus tshawytscha in a reservoir on the Snake River, Washington, U.S.A. During the summer, temperatures in the reservoir varied from 23?? C on the surface to 11?? C at 14 m depth. Subyearlings implanted with temperature-sensing radio transmitters were released at the surface at temperatures >20?? C during three blocks of time in summer 2004. Vertical profiles were taken to measure temperature and depth use as the fish moved downstream over an average of 5??6-7??2 h and 6??0-13??8 km. The majority of the subyearlings maintained average body temperatures that differed from average vertical profile temperatures during most of the time they were tracked. The mean proportion of the time subyearlings tracked within the 16-20?? C temperature range was larger than the proportion of time this range was available, which confirmed temperature selection opposed to random use. The subyearlings selected a depth and temperature combination that allowed them to increase their exposure to temperatures of 16-20?? C when temperatures 20?? C were available at lower and higher positions in the water column. A portion of the subyearlings that selected a temperature c. 17??0?? C during the day, moved into warmer water at night coincident with an increase in downstream movement rate. Though subyearlings used temperatures outside of the 16-20?? C range part of the time, behavioural thermoregulation probably reduced the effects of intermittent exposure to suboptimal temperatures. By doing so, it might enhance growth opportunity and life-history diversity in the population of subyearlings studied.

Near Real-Time Event Detection & Prediction Using Intelligent Software Agents

DTIC Science & Technology

2006-03-01

value was 0.06743. Multiple autoregressive integrated moving average ( ARIMA ) models were then build to see if the raw data, differenced data, or...slight improvement. The best adjusted r^2 value was found to be 0.1814. Successful results were not expected from linear or ARIMA -based modelling ...appear, 2005. [63] Mora-Lopez, L., Mora, J., Morales-Bueno, R., et al. Modelling time series of climatic parameters with probabilistic finite

Anticipating the effects of gravity when intercepting moving objects: differentiating up and down based on nonvisual cues.

PubMed

Senot, Patrice; Zago, Myrka; Lacquaniti, Francesco; McIntyre, Joseph

2005-12-01

Intercepting an object requires a precise estimate of its time of arrival at the interception point (time to contact or "TTC"). It has been proposed that knowledge about gravitational acceleration can be combined with first-order, visual-field information to provide a better estimate of TTC when catching falling objects. In this experiment, we investigated the relative role of visual and nonvisual information on motor-response timing in an interceptive task. Subjects were immersed in a stereoscopic virtual environment and asked to intercept with a virtual racket a ball falling from above or rising from below. The ball moved with different initial velocities and could accelerate, decelerate, or move at a constant speed. Depending on the direction of motion, the acceleration or deceleration of the ball could therefore be congruent or not with the acceleration that would be expected due to the force of gravity acting on the ball. Although the best success rate was observed for balls moving at a constant velocity, we systematically found a cross-effect of ball direction and acceleration on success rate and response timing. Racket motion was triggered on average 25 ms earlier when the ball fell from above than when it rose from below, whatever the ball's true acceleration. As visual-flow information was the same in both cases, this shift indicates an influence of the ball's direction relative to gravity on response timing, consistent with the anticipation of the effects of gravity on the flight of the ball.

A High Precision Prediction Model Using Hybrid Grey Dynamic Model

ERIC Educational Resources Information Center

Li, Guo-Dong; Yamaguchi, Daisuke; Nagai, Masatake; Masuda, Shiro

2008-01-01

In this paper, we propose a new prediction analysis model which combines the first order one variable Grey differential equation Model (abbreviated as GM(1,1) model) from grey system theory and time series Autoregressive Integrated Moving Average (ARIMA) model from statistics theory. We abbreviate the combined GM(1,1) ARIMA model as ARGM(1,1)…

Relating Factor Models for Longitudinal Data to Quasi-Simplex and NARMA Models

ERIC Educational Resources Information Center

Rovine, Michael J.; Molenaar, Peter C. M.

2005-01-01

In this article we show the one-factor model can be rewritten as a quasi-simplex model. Using this result along with addition theorems from time series analysis, we describe a common general model, the nonstationary autoregressive moving average (NARMA) model, that includes as a special case, any latent variable model with continuous indicators…

Revolving Doors: The Impact of Multiple School Transitions on Military Children

ERIC Educational Resources Information Center

Ruff, S. Beth; Keim, Michael A.

2014-01-01

There are 1.2 million school-age children with military parents in the United States, and approximately 90% attend public schools. On average, military children move three times more often than their civilian peers. Tensions at home, enrollment issues, adapting to new schools, and a lack of familiarity with military culture by public school…

Retention time and flow patterns in Lake Marion, South Carolina, 1984

USGS Publications Warehouse

Patterson, G.G.; Harvey, R.M.

1995-01-01

In 1984, six dye tracer tests were made on Lake Marion to determine flow patterns and retention times under conditions of high and low flow. During the high-flow tests, with an average inflow of about 29,000 cubic feet per second, the approximate travel time through the lake for the peak tracer concentration was 14 days. The retention time was about 20 days. During the low-flow tests, with an average inflow of about 9,000 cubic feet per second, the approximate travel time was 41 days, and the retention time was about 60 days. The primary factors controlling movement of water in the lake are lake inflow and outflow. The tracer cloud moved consistently downstream, slowing as the lake widened. Flow patterns in most of the coves, and in some areas along the northeastern shore, are influenced more by tributary inflow than by factors attributable to water from the main body of the lake.

78 FR 26879 - Medicare Program; Inpatient Rehabilitation Facility Prospective Payment System for Federal Fiscal...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-08

...: Centers for Medicare & Medicaid Services (CMS), HHS. ACTION: Proposed rule. SUMMARY: This proposed rule..., especially the teaching status adjustment factor. Therefore, we implemented a 3-year moving average approach... moving average to calculate the facility-level adjustment factors. For FY 2011, we issued a notice to...

A multimodel approach to interannual and seasonal prediction of Danube discharge anomalies

NASA Astrophysics Data System (ADS)

Rimbu, Norel; Ionita, Monica; Patrut, Simona; Dima, Mihai

2010-05-01

Interannual and seasonal predictability of Danube river discharge is investigated using three model types: 1) time series models 2) linear regression models of discharge with large-scale climate mode indices and 3) models based on stable teleconnections. All models are calibrated using discharge and climatic data for the period 1901-1977 and validated for the period 1978-2008 . Various time series models, like autoregressive (AR), moving average (MA), autoregressive and moving average (ARMA) or singular spectrum analysis and autoregressive moving average (SSA+ARMA) models have been calibrated and their skills evaluated. The best results were obtained using SSA+ARMA models. SSA+ARMA models proved to have the highest forecast skill also for other European rivers (Gamiz-Fortis et al. 2008). Multiple linear regression models using large-scale climatic mode indices as predictors have a higher forecast skill than the time series models. The best predictors for Danube discharge are the North Atlantic Oscillation (NAO) and the East Atlantic/Western Russia patterns during winter and spring. Other patterns, like Polar/Eurasian or Tropical Northern Hemisphere (TNH) are good predictors for summer and autumn discharge. Based on stable teleconnection approach (Ionita et al. 2008) we construct prediction models through a combination of sea surface temperature (SST), temperature (T) and precipitation (PP) from the regions where discharge and SST, T and PP variations are stable correlated. Forecast skills of these models are higher than forecast skills of the time series and multiple regression models. The models calibrated and validated in our study can be used for operational prediction of interannual and seasonal Danube discharge anomalies. References Gamiz-Fortis, S., D. Pozo-Vazquez, R.M. Trigo, and Y. Castro-Diez, Quantifying the predictability of winter river flow in Iberia. Part I: intearannual predictability. J. Climate, 2484-2501, 2008. Gamiz-Fortis, S., D. Pozo-Vazquez, R.M. Trigo, and Y. Castro-Diez, Quantifying the predictability of winter river flow in Iberia. Part II: seasonal predictability. J. Climate, 2503-2518, 2008. Ionita, M., G. Lohmann, and N. Rimbu, Prediction of spring Elbe river discharge based on stable teleconnections with global temperature and precipitation. J. Climate. 6215-6226, 2008.

Watershed Regressions for Pesticides (WARP) for Predicting Annual Maximum and Annual Maximum Moving-Average Concentrations of Atrazine in Streams

USGS Publications Warehouse

Stone, Wesley W.; Gilliom, Robert J.; Crawford, Charles G.

2008-01-01

Regression models were developed for predicting annual maximum and selected annual maximum moving-average concentrations of atrazine in streams using the Watershed Regressions for Pesticides (WARP) methodology developed by the National Water-Quality Assessment Program (NAWQA) of the U.S. Geological Survey (USGS). The current effort builds on the original WARP models, which were based on the annual mean and selected percentiles of the annual frequency distribution of atrazine concentrations. Estimates of annual maximum and annual maximum moving-average concentrations for selected durations are needed to characterize the levels of atrazine and other pesticides for comparison to specific water-quality benchmarks for evaluation of potential concerns regarding human health or aquatic life. Separate regression models were derived for the annual maximum and annual maximum 21-day, 60-day, and 90-day moving-average concentrations. Development of the regression models used the same explanatory variables, transformations, model development data, model validation data, and regression methods as those used in the original development of WARP. The models accounted for 72 to 75 percent of the variability in the concentration statistics among the 112 sampling sites used for model development. Predicted concentration statistics from the four models were within a factor of 10 of the observed concentration statistics for most of the model development and validation sites. Overall, performance of the models for the development and validation sites supports the application of the WARP models for predicting annual maximum and selected annual maximum moving-average atrazine concentration in streams and provides a framework to interpret the predictions in terms of uncertainty. For streams with inadequate direct measurements of atrazine concentrations, the WARP model predictions for the annual maximum and the annual maximum moving-average atrazine concentrations can be used to characterize the probable levels of atrazine for comparison to specific water-quality benchmarks. Sites with a high probability of exceeding a benchmark for human health or aquatic life can be prioritized for monitoring.

Respiratory sinus arrhythmia: time domain characterization using autoregressive moving average analysis

NASA Technical Reports Server (NTRS)

Triedman, J. K.; Perrott, M. H.; Cohen, R. J.; Saul, J. P.

1995-01-01

Fourier-based techniques are mathematically noncausal and are therefore limited in their application to feedback-containing systems, such as the cardiovascular system. In this study, a mathematically causal time domain technique, autoregressive moving average (ARMA) analysis, was used to parameterize the relations of respiration and arterial blood pressure to heart rate in eight humans before and during total cardiac autonomic blockade. Impulse-response curves thus generated showed the relation of respiration to heart rate to be characterized by an immediate increase in heart rate of 9.1 +/- 1.8 beats.min-1.l-1, followed by a transient mild decrease in heart rate to -1.2 +/- 0.5 beats.min-1.l-1 below baseline. The relation of blood pressure to heart rate was characterized by a slower decrease in heart rate of -0.5 +/- 0.1 beats.min-1.mmHg-1, followed by a gradual return to baseline. Both of these relations nearly disappeared after autonomic blockade, indicating autonomic mediation. Maximum values obtained from the respiration to heart rate impulse responses were also well correlated with frequency domain measures of high-frequency "vagal" heart rate control (r = 0.88). ARMA analysis may be useful as a time domain representation of autonomic heart rate control for cardiovascular modeling.

[The trial of business data analysis at the Department of Radiology by constructing the auto-regressive integrated moving-average (ARIMA) model].

PubMed

Tani, Yuji; Ogasawara, Katsuhiko

2012-01-01

This study aimed to contribute to the management of a healthcare organization by providing management information using time-series analysis of business data accumulated in the hospital information system, which has not been utilized thus far. In this study, we examined the performance of the prediction method using the auto-regressive integrated moving-average (ARIMA) model, using the business data obtained at the Radiology Department. We made the model using the data used for analysis, which was the number of radiological examinations in the past 9 years, and we predicted the number of radiological examinations in the last 1 year. Then, we compared the actual value with the forecast value. We were able to establish that the performance prediction method was simple and cost-effective by using free software. In addition, we were able to build the simple model by pre-processing the removal of trend components using the data. The difference between predicted values and actual values was 10%; however, it was more important to understand the chronological change rather than the individual time-series values. Furthermore, our method was highly versatile and adaptable compared to the general time-series data. Therefore, different healthcare organizations can use our method for the analysis and forecasting of their business data.

An Estimate of the Likelihood for a Climatically Significant Volcanic Eruption Within the Present Decade (2000-2009)

NASA Technical Reports Server (NTRS)

Wilson, Robert M.; Franklin, M. Rose (Technical Monitor)

2000-01-01

Since 1750, the number of cataclysmic volcanic eruptions (i.e., those having a volcanic explosivity index, or VEI, equal to 4 or larger) per decade is found to span 2-11, with 96% located in the tropics and extra-tropical Northern Hemisphere, A two-point moving average of the time series has higher values since the 1860s than before, measuring 8.00 in the 1910s (the highest value) and measuring 6.50 in the 1980s, the highest since the 18 1 0s' peak. On the basis of the usual behavior of the first difference of the two-point moving averages, one infers that the two-point moving average for the 1990s will measure about 6.50 +/- 1.00, implying that about 7 +/- 4 cataclysmic volcanic eruptions should be expected during the present decade (2000-2009). Because cataclysmic volcanic eruptions (especially, those having VEI equal to 5 or larger) nearly always have been associated with episodes of short-term global cooling, the occurrence of even one could ameliorate the effects of global warming. Poisson probability distributions reveal that the probability of one or more VEI equal to 4 or larger events occurring within the next ten years is >99%, while it is about 49% for VEI equal to 5 or larger events and 18% for VEI equal to 6 or larger events. Hence, the likelihood that a, climatically significant volcanic eruption will occur within the next 10 years appears reasonably high.

A comparison of several techniques for imputing tree level data

Treesearch

David Gartner

2002-01-01

As Forest Inventory and Analysis (FIA) changes from periodic surveys to the multipanel annual survey, new analytical methods become available. The current official statistic is the moving average. One alternative is an updated moving average. Several methods of updating plot per acre volume have been discussed previously. However, these methods may not be appropriate...

Intimate partner violence in Madrid: a time series analysis (2008-2016).

PubMed

Sanz-Barbero, Belén; Linares, Cristina; Vives-Cases, Carmen; González, José Luis; López-Ossorio, Juan José; Díaz, Julio

2018-06-02

This study analyzes whether there are time patterns in different intimate partner violence (IPV) indicators and aims to obtain models that can predict the behavior of these time series. Univariate autoregressive moving average models were used to analyze the time series corresponding to the number of daily calls to the 016 telephone IPV helpline and the number of daily police reports filed in the Community of Madrid during the period 2008-2015. Predictions were made for both dependent variables for 2016. The daily number of calls to the 016 telephone IPV helpline decreased during January 2008-April 2012 and increased during April 2012-December 2015. No statistically significant change was observed in the trend of the number of daily IPV police reports. The number of IPV police reports filed increased on weekends and on Christmas holidays. The number of calls to the 016 IPV help line increased on Mondays. Using data from 2008 to 2015, the univariate autoregressive moving average models predicted 64.2% of calls to the 016 telephone IPV helpline and 73.2% of police reports filed during 2016 in the Community of Madrid. Our results suggest the need for an increase in police and judicial resources on nonwork days. Also, the 016 telephone IPV helpline should be especially active on work days. Copyright © 2018 Elsevier Inc. All rights reserved.

Random walk of passive tracers among randomly moving obstacles.

PubMed

Gori, Matteo; Donato, Irene; Floriani, Elena; Nardecchia, Ilaria; Pettini, Marco

2016-04-14

This study is mainly motivated by the need of understanding how the diffusion behavior of a biomolecule (or even of a larger object) is affected by other moving macromolecules, organelles, and so on, inside a living cell, whence the possibility of understanding whether or not a randomly walking biomolecule is also subject to a long-range force field driving it to its target. By means of the Continuous Time Random Walk (CTRW) technique the topic of random walk in random environment is here considered in the case of a passively diffusing particle among randomly moving and interacting obstacles. The relevant physical quantity which is worked out is the diffusion coefficient of the passive tracer which is computed as a function of the average inter-obstacles distance. The results reported here suggest that if a biomolecule, let us call it a test molecule, moves towards its target in the presence of other independently interacting molecules, its motion can be considerably slowed down.

Weather variability and the incidence of cryptosporidiosis: comparison of time series poisson regression and SARIMA models.

PubMed

Hu, Wenbiao; Tong, Shilu; Mengersen, Kerrie; Connell, Des

2007-09-01

Few studies have examined the relationship between weather variables and cryptosporidiosis in Australia. This paper examines the potential impact of weather variability on the transmission of cryptosporidiosis and explores the possibility of developing an empirical forecast system. Data on weather variables, notified cryptosporidiosis cases, and population size in Brisbane were supplied by the Australian Bureau of Meteorology, Queensland Department of Health, and Australian Bureau of Statistics for the period of January 1, 1996-December 31, 2004, respectively. Time series Poisson regression and seasonal auto-regression integrated moving average (SARIMA) models were performed to examine the potential impact of weather variability on the transmission of cryptosporidiosis. Both the time series Poisson regression and SARIMA models show that seasonal and monthly maximum temperature at a prior moving average of 1 and 3 months were significantly associated with cryptosporidiosis disease. It suggests that there may be 50 more cases a year for an increase of 1 degrees C maximum temperature on average in Brisbane. Model assessments indicated that the SARIMA model had better predictive ability than the Poisson regression model (SARIMA: root mean square error (RMSE): 0.40, Akaike information criterion (AIC): -12.53; Poisson regression: RMSE: 0.54, AIC: -2.84). Furthermore, the analysis of residuals shows that the time series Poisson regression appeared to violate a modeling assumption, in that residual autocorrelation persisted. The results of this study suggest that weather variability (particularly maximum temperature) may have played a significant role in the transmission of cryptosporidiosis. A SARIMA model may be a better predictive model than a Poisson regression model in the assessment of the relationship between weather variability and the incidence of cryptosporidiosis.

Characteristics of typical non-road machinery emissions in China by using portable emission measurement system.

PubMed

Fu, Mingliang; Ge, Yunshan; Tan, Jianwei; Zeng, Tao; Liang, Bin

2012-10-15

Non-road machinery, especially construction equipment could be an important pollutant source of the deterioration in air quality in Chinese urban areas due to its large quantity and to the absence of stringent emission requirements. In this study, emission tests were performed on 12 excavators and 8 wheel loaders by using portable emission measurement system (PEMS) to determine their emission characteristics. The typical operating modes were categorized as idling mode, moving mode and working mode. Compared with those during idling and moving modes, the average time-based emission factors during working mode of HC were 2.61 and 1.27 times higher, NO(x) were 3.66 and 1.36 times higher, and PM were 4.05 and 1.95 times higher, respectively. Under all conditions, categories of the measured emissions increased with the rise in engine power. Compared with those of Stage I emission standard equipment, gaseous emissions and PM emitted from Stage II emission standard equipment were lower. The results indicated that, from Stage I to Stage II, the average reductions of HC, NO(x) and PM were 56%, 37% and 29% for the working mode, respectively. Those results also demonstrated the effectiveness of emission control regulation and the improvement of emission control technology. The data and tests show that the longer the accumulated working hours, the higher HC and NO(x) average fuel-based emission factors are. The emissions measured from the construction vehicles employed in this study were higher than the data collected in previous studies, which shows that it is critical for the government to put into effect more stringent emission regulations to further improve the air quality in Chinese urban areas. Copyright © 2012 Elsevier B.V. All rights reserved.

No Evidence of Suicide Increase Following Terrorist Attacks in the United States: An Interrupted Time-Series Analysis of September 11 and Oklahoma City

ERIC Educational Resources Information Center

Pridemore, William Alex; Trahan, Adam; Chamlin, Mitchell B.

2009-01-01

There is substantial evidence of detrimental psychological sequelae following disasters, including terrorist attacks. The effect of these events on extreme responses such as suicide, however, is unclear. We tested competing hypotheses about such effects by employing autoregressive integrated moving average techniques to model the impact of…

Predicting Rehabilitation Success Rate Trends among Ethnic Minorities Served by State Vocational Rehabilitation Agencies: A National Time Series Forecast Model Demonstration Study

ERIC Educational Resources Information Center

Moore, Corey L.; Wang, Ningning; Washington, Janique Tynez

2017-01-01

Purpose: This study assessed and demonstrated the efficacy of two select empirical forecast models (i.e., autoregressive integrated moving average [ARIMA] model vs. grey model [GM]) in accurately predicting state vocational rehabilitation agency (SVRA) rehabilitation success rate trends across six different racial and ethnic population cohorts…

Numerical modeling of a point-source image under relative motion of radiation receiver and atmosphere

NASA Astrophysics Data System (ADS)

Kucherov, A. N.; Makashev, N. K.; Ustinov, E. V.

1994-02-01

A procedure is proposed for numerical modeling of instantaneous and averaged (over various time intervals) distant-point-source images perturbed by a turbulent atmosphere that moves relative to the radiation receiver. Examples of image calculations under conditions of the significant effect of atmospheric turbulence in an approximation of geometrical optics are presented and analyzed.

Viscous Torques on a Levitating Body

NASA Technical Reports Server (NTRS)

Busse, F.; Wang, T.

1982-01-01

New analytical expressions for viscous torque generated by orthogonal sound waves agree well with experiment. It is possible to calculate torque on an object levitated in a fluid. Levitation has applications in containerless materials processing, coating, and fabrication of small precision parts. Sound waves cause fluid particles to move in elliptical paths and induce azimuthal circulation in boundary layer, giving rise to time-averaged torque.

Evaluation of performance of select fusion experiments and projected reactors

NASA Technical Reports Server (NTRS)

Miley, G. H.

1978-01-01

The performance of NASA Lewis fusion experiments (SUMMA and Bumpy Torus) is compared with other experiments and that necessary for a power reactor. Key parameters cited are gain (fusion power/input power) and the time average fusion power, both of which may be more significant for real fusion reactors than the commonly used Lawson parameter. The NASA devices are over 10 orders of magnitude below the required powerplant values in both gain and time average power. The best experiments elsewhere are also as much as 4 to 5 orders of magnitude low. However, the NASA experiments compare favorably with other alternate approaches that have received less funding than the mainline experiments. The steady-state character and efficiency of plasma heating are strong advantages of the NASA approach. The problem, though, is to move ahead to experiments of sufficient size to advance in gain and average power parameters.

Quantifying rapid changes in cardiovascular state with a moving ensemble average.

PubMed

Cieslak, Matthew; Ryan, William S; Babenko, Viktoriya; Erro, Hannah; Rathbun, Zoe M; Meiring, Wendy; Kelsey, Robert M; Blascovich, Jim; Grafton, Scott T

2018-04-01

MEAP, the moving ensemble analysis pipeline, is a new open-source tool designed to perform multisubject preprocessing and analysis of cardiovascular data, including electrocardiogram (ECG), impedance cardiogram (ICG), and continuous blood pressure (BP). In addition to traditional ensemble averaging, MEAP implements a moving ensemble averaging method that allows for the continuous estimation of indices related to cardiovascular state, including cardiac output, preejection period, heart rate variability, and total peripheral resistance, among others. Here, we define the moving ensemble technique mathematically, highlighting its differences from fixed-window ensemble averaging. We describe MEAP's interface and features for signal processing, artifact correction, and cardiovascular-based fMRI analysis. We demonstrate the accuracy of MEAP's novel B point detection algorithm on a large collection of hand-labeled ICG waveforms. As a proof of concept, two subjects completed a series of four physical and cognitive tasks (cold pressor, Valsalva maneuver, video game, random dot kinetogram) on 3 separate days while ECG, ICG, and BP were recorded. Critically, the moving ensemble method reliably captures the rapid cyclical cardiovascular changes related to the baroreflex during the Valsalva maneuver and the classic cold pressor response. Cardiovascular measures were seen to vary considerably within repetitions of the same cognitive task for each individual, suggesting that a carefully designed paradigm could be used to capture fast-acting event-related changes in cardiovascular state. © 2017 Society for Psychophysiological Research.

Parametric output-only identification of time-varying structures using a kernel recursive extended least squares TARMA approach

NASA Astrophysics Data System (ADS)

Ma, Zhi-Sai; Liu, Li; Zhou, Si-Da; Yu, Lei; Naets, Frank; Heylen, Ward; Desmet, Wim

2018-01-01

The problem of parametric output-only identification of time-varying structures in a recursive manner is considered. A kernelized time-dependent autoregressive moving average (TARMA) model is proposed by expanding the time-varying model parameters onto the basis set of kernel functions in a reproducing kernel Hilbert space. An exponentially weighted kernel recursive extended least squares TARMA identification scheme is proposed, and a sliding-window technique is subsequently applied to fix the computational complexity for each consecutive update, allowing the method to operate online in time-varying environments. The proposed sliding-window exponentially weighted kernel recursive extended least squares TARMA method is employed for the identification of a laboratory time-varying structure consisting of a simply supported beam and a moving mass sliding on it. The proposed method is comparatively assessed against an existing recursive pseudo-linear regression TARMA method via Monte Carlo experiments and shown to be capable of accurately tracking the time-varying dynamics. Furthermore, the comparisons demonstrate the superior achievable accuracy, lower computational complexity and enhanced online identification capability of the proposed kernel recursive extended least squares TARMA approach.

A generic sun-tracking algorithm for on-axis solar collector in mobile platforms

NASA Astrophysics Data System (ADS)

Lai, An-Chow; Chong, Kok-Keong; Lim, Boon-Han; Ho, Ming-Cheng; Yap, See-Hao; Heng, Chun-Kit; Lee, Jer-Vui; King, Yeong-Jin

2015-04-01

This paper proposes a novel dynamic sun-tracking algorithm which allows accurate tracking of the sun for both non-concentrated and concentrated photovoltaic systems located on mobile platforms to maximize solar energy extraction. The proposed algorithm takes not only the date, time, and geographical information, but also the dynamic changes of coordinates of the mobile platforms into account to calculate the sun position angle relative to ideal azimuth-elevation axes in real time using general sun-tracking formulas derived by Chong and Wong. The algorithm acquires data from open-loop sensors, i.e. global position system (GPS) and digital compass, which are readily available in many off-the-shelf portable gadgets, such as smart phone, to instantly capture the dynamic changes of coordinates of mobile platforms. Our experiments found that a highly accurate GPS is not necessary as the coordinate changes of practical mobile platforms are not fast enough to produce significant differences in the calculation of the incident angle. On the contrary, it is critical to accurately identify the quadrant and angle where the mobile platforms are moving toward in real time, which can be resolved by using digital compass. In our implementation, a noise filtering mechanism is found necessary to remove unexpected spikes in the readings of the digital compass to ensure stability in motor actuations and effectiveness in continuous tracking. Filtering mechanisms being studied include simple moving average and linear regression; the results showed that a compound function of simple moving average and linear regression produces a better outcome. Meanwhile, we found that a sampling interval is useful to avoid excessive motor actuations and power consumption while not sacrificing the accuracy of sun-tracking.

Weather explains high annual variation in butterfly dispersal

PubMed Central

Rytteri, Susu; Heikkinen, Risto K.; Heliölä, Janne; von Bagh, Peter

2016-01-01

Weather conditions fundamentally affect the activity of short-lived insects. Annual variation in weather is therefore likely to be an important determinant of their between-year variation in dispersal, but conclusive empirical studies are lacking. We studied whether the annual variation of dispersal can be explained by the flight season's weather conditions in a Clouded Apollo (Parnassius mnemosyne) metapopulation. This metapopulation was monitored using the mark–release–recapture method for 12 years. Dispersal was quantified for each monitoring year using three complementary measures: emigration rate (fraction of individuals moving between habitat patches), average residence time in the natal patch, and average distance moved. There was much variation both in dispersal and average weather conditions among the years. Weather variables significantly affected the three measures of dispersal and together with adjusting variables explained 79–91% of the variation observed in dispersal. Different weather variables became selected in the models explaining variation in three dispersal measures apparently because of the notable intercorrelations. In general, dispersal rate increased with increasing temperature, solar radiation, proportion of especially warm days, and butterfly density, and decreased with increasing cloudiness, rainfall, and wind speed. These results help to understand and model annually varying dispersal dynamics of species affected by global warming. PMID:27440662

The Performance of Multilevel Growth Curve Models under an Autoregressive Moving Average Process

ERIC Educational Resources Information Center

Murphy, Daniel L.; Pituch, Keenan A.

2009-01-01

The authors examined the robustness of multilevel linear growth curve modeling to misspecification of an autoregressive moving average process. As previous research has shown (J. Ferron, R. Dailey, & Q. Yi, 2002; O. Kwok, S. G. West, & S. B. Green, 2007; S. Sivo, X. Fan, & L. Witta, 2005), estimates of the fixed effects were unbiased, and Type I…

An Improved Harmonic Current Detection Method Based on Parallel Active Power Filter

NASA Astrophysics Data System (ADS)

Zeng, Zhiwu; Xie, Yunxiang; Wang, Yingpin; Guan, Yuanpeng; Li, Lanfang; Zhang, Xiaoyu

2017-05-01

Harmonic detection technology plays an important role in the applications of active power filter. The accuracy and real-time performance of harmonic detection are the precondition to ensure the compensation performance of Active Power Filter (APF). This paper proposed an improved instantaneous reactive power harmonic current detection algorithm. The algorithm uses an improved ip -iq algorithm which is combined with the moving average value filter. The proposed ip -iq algorithm can remove the αβ and dq coordinate transformation, decreasing the cost of calculation, simplifying the extraction process of fundamental components of load currents, and improving the detection speed. The traditional low-pass filter is replaced by the moving average filter, detecting the harmonic currents more precisely and quickly. Compared with the traditional algorithm, the THD (Total Harmonic Distortion) of the grid currents is reduced from 4.41% to 3.89% for the simulations and from 8.50% to 4.37% for the experiments after the improvement. The results show the proposed algorithm is more accurate and efficient.

Analysis Monthly Import of Palm Oil Products Using Box-Jenkins Model

NASA Astrophysics Data System (ADS)

Ahmad, Nurul F. Y.; Khalid, Kamil; Saifullah Rusiman, Mohd; Ghazali Kamardan, M.; Roslan, Rozaini; Che-Him, Norziha

2018-04-01

The palm oil industry has been an important component of the national economy especially the agriculture sector. The aim of this study is to identify the pattern of import of palm oil products, to model the time series using Box-Jenkins model and to forecast the monthly import of palm oil products. The method approach is included in the statistical test for verifying the equivalence model and statistical measurement of three models, namely Autoregressive (AR) model, Moving Average (MA) model and Autoregressive Moving Average (ARMA) model. The model identification of all product import palm oil is different in which the AR(1) was found to be the best model for product import palm oil while MA(3) was found to be the best model for products import palm kernel oil. For the palm kernel, MA(4) was found to be the best model. The results forecast for the next four months for products import palm oil, palm kernel oil and palm kernel showed the most significant decrease compared to the actual data.

The Influence of Sleep Disordered Breathing on Weight Loss in a National Weight Management Program.

PubMed

Janney, Carol A; Kilbourne, Amy M; Germain, Anne; Lai, Zongshan; Hoerster, Katherine D; Goodrich, David E; Klingaman, Elizabeth A; Verchinina, Lilia; Richardson, Caroline R

2016-01-01

To investigate the influence of sleep disordered breathing (SDB) on weight loss in overweight/obese veterans enrolled in MOVE!, a nationally implemented behavioral weight management program delivered by the National Veterans Health Administration health system. This observational study evaluated weight loss by SDB status in overweight/obese veterans enrolled in MOVE! from May 2008-February 2012 who had at least two MOVE! visits, baseline weight, and at least one follow-up weight (n = 84,770). SDB was defined by International Classification of Diseases, Ninth Revision, Clinical Modification codes. Primary outcome was weight change (lb) from MOVE! enrollment to 6- and 12-mo assessments. Weight change over time was modeled with repeated-measures analyses. SDB was diagnosed in one-third of the cohort (n = 28,269). At baseline, veterans with SDB weighed 29 [48] lb more than those without SDB (P < 0.001). On average, veterans attended eight MOVE! visits. Weight loss patterns over time were statistically different between veterans with and without SDB (P < 0.001); veterans with SDB lost less weight (-2.5 [0.1] lb) compared to those without SDB (-3.3 [0.1] lb; P = 0.001) at 6 months. At 12 mo, veterans with SDB continued to lose weight whereas veterans without SDB started to re-gain weight. Veterans with sleep disordered breathing (SDB) had significantly less weight loss over time than veterans without SDB. SDB should be considered in the development and implementation of weight loss programs due to its high prevalence and negative effect on health. © 2016 Associated Professional Sleep Societies, LLC.

Concept for an off-line gain stabilisation method.

PubMed

Pommé, S; Sibbens, G

2004-01-01

Conceptual ideas are presented for an off-line gain stabilisation method for spectrometry, in particular for alpha-particle spectrometry at low count rate. The method involves list mode storage of individual energy and time stamp data pairs. The 'Stieltjes integral' of measured spectra with respect to a reference spectrum is proposed as an indicator for gain instability. 'Exponentially moving averages' of the latter show the gain shift as a function of time. With this information, the data are relocated stochastically on a point-by-point basis.

Time of travel and dispersion of solutes in a 36.4-mile reach of the North Platte River downstream from Casper, Wyoming

USGS Publications Warehouse

Armentrout, G.W.; Larson, L.R.

1984-01-01

Time-of-travel and dispersion measurements made during a dye study November 7-8, 1978, are presented for a reach of the North Platte River from Casper, Wyo., to a bridge 2 miles downstream from below the Dave Johnston Power Plant. Rhodamine WT dye was injected into the river at Casper, and the resultant dye cloud was traced by sampling as it moved downstream. Samples were taken in three equal-flow sections of the river 's lateral transect at three sites, then analyzed in a fluorometer. The flow in the river was 940 cubic feet per second. The data consist of measured stream mileages and time, distance, and concentration graphs of the dye cloud. The peak concentration traveled through the reach in 24 hours, averaging 1.5 miles per hour; the leading edge took about 22 hours, averaging 1.7 miles per hour; and the trailing edge took 35 hours, averaging 1.0 mile per hour. Data from this study were compared with methods for estimating time of travel for a range of stream discharges.

Waste tyre pyrolysis: modelling of a moving bed reactor.

PubMed

Aylón, E; Fernández-Colino, A; Murillo, R; Grasa, G; Navarro, M V; García, T; Mastral, A M

2010-12-01

This paper describes the development of a new model for waste tyre pyrolysis in a moving bed reactor. This model comprises three different sub-models: a kinetic sub-model that predicts solid conversion in terms of reaction time and temperature, a heat transfer sub-model that calculates the temperature profile inside the particle and the energy flux from the surroundings to the tyre particles and, finally, a hydrodynamic model that predicts the solid flow pattern inside the reactor. These three sub-models have been integrated in order to develop a comprehensive reactor model. Experimental results were obtained in a continuous moving bed reactor and used to validate model predictions, with good approximation achieved between the experimental and simulated results. In addition, a parametric study of the model was carried out, which showed that tyre particle heating is clearly faster than average particle residence time inside the reactor. Therefore, this fast particle heating together with fast reaction kinetics enables total solid conversion to be achieved in this system in accordance with the predictive model. Copyright © 2010 Elsevier Ltd. All rights reserved.

Driving-forces model on individual behavior in scenarios considering moving threat agents

NASA Astrophysics Data System (ADS)

Li, Shuying; Zhuang, Jun; Shen, Shifei; Wang, Jia

2017-09-01

The individual behavior model is a contributory factor to improve the accuracy of agent-based simulation in different scenarios. However, few studies have considered moving threat agents, which often occur in terrorist attacks caused by attackers with close-range weapons (e.g., sword, stick). At the same time, many existing behavior models lack validation from cases or experiments. This paper builds a new individual behavior model based on seven behavioral hypotheses. The driving-forces model is an extension of the classical social force model considering scenarios including moving threat agents. An experiment was conducted to validate the key components of the model. Then the model is compared with an advanced Elliptical Specification II social force model, by calculating the fitting errors between the simulated and experimental trajectories, and being applied to simulate a specific circumstance. Our results show that the driving-forces model reduced the fitting error by an average of 33.9% and the standard deviation by an average of 44.5%, which indicates the accuracy and stability of the model in the studied situation. The new driving-forces model could be used to simulate individual behavior when analyzing the risk of specific scenarios using agent-based simulation methods, such as risk analysis of close-range terrorist attacks in public places.

Fast generation of video holograms of three-dimensional moving objects using a motion compensation-based novel look-up table.

PubMed

Kim, Seung-Cheol; Dong, Xiao-Bin; Kwon, Min-Woo; Kim, Eun-Soo

2013-05-06

A novel approach for fast generation of video holograms of three-dimensional (3-D) moving objects using a motion compensation-based novel-look-up-table (MC-N-LUT) method is proposed. Motion compensation has been widely employed in compression of conventional 2-D video data because of its ability to exploit high temporal correlation between successive video frames. Here, this concept of motion-compensation is firstly applied to the N-LUT based on its inherent property of shift-invariance. That is, motion vectors of 3-D moving objects are extracted between the two consecutive video frames, and with them motions of the 3-D objects at each frame are compensated. Then, through this process, 3-D object data to be calculated for its video holograms are massively reduced, which results in a dramatic increase of the computational speed of the proposed method. Experimental results with three kinds of 3-D video scenarios reveal that the average number of calculated object points and the average calculation time for one object point of the proposed method, have found to be reduced down to 86.95%, 86.53% and 34.99%, 32.30%, respectively compared to those of the conventional N-LUT and temporal redundancy-based N-LUT (TR-N-LUT) methods.

Low-Rank Matrix Recovery Approach for Clutter Rejection in Real-Time IR-UWB Radar-Based Moving Target Detection

PubMed Central

Sabushimike, Donatien; Na, Seung You; Kim, Jin Young; Bui, Ngoc Nam; Seo, Kyung Sik; Kim, Gil Gyeom

2016-01-01

The detection of a moving target using an IR-UWB Radar involves the core task of separating the waves reflected by the static background and by the moving target. This paper investigates the capacity of the low-rank and sparse matrix decomposition approach to separate the background and the foreground in the trend of UWB Radar-based moving target detection. Robust PCA models are criticized for being batched-data-oriented, which makes them inconvenient in realistic environments where frames need to be processed as they are recorded in real time. In this paper, a novel method based on overlapping-windows processing is proposed to cope with online processing. The method consists of processing a small batch of frames which will be continually updated without changing its size as new frames are captured. We prove that RPCA (via its Inexact Augmented Lagrange Multiplier (IALM) model) can successfully separate the two subspaces, which enhances the accuracy of target detection. The overlapping-windows processing method converges on the optimal solution with its batch counterpart (i.e., processing batched data with RPCA), and both methods prove the robustness and efficiency of the RPCA over the classic PCA and the commonly used exponential averaging method. PMID:27598159

An improved moving average technical trading rule

NASA Astrophysics Data System (ADS)

Papailias, Fotis; Thomakos, Dimitrios D.

2015-06-01

This paper proposes a modified version of the widely used price and moving average cross-over trading strategies. The suggested approach (presented in its 'long only' version) is a combination of cross-over 'buy' signals and a dynamic threshold value which acts as a dynamic trailing stop. The trading behaviour and performance from this modified strategy are different from the standard approach with results showing that, on average, the proposed modification increases the cumulative return and the Sharpe ratio of the investor while exhibiting smaller maximum drawdown and smaller drawdown duration than the standard strategy.

Relative distance between tracers as a measure of diffusivity within moving aggregates

NASA Astrophysics Data System (ADS)

Pönisch, Wolfram; Zaburdaev, Vasily

2018-02-01

Tracking of particles, be it a passive tracer or an actively moving bacterium in the growing bacterial colony, is a powerful technique to probe the physical properties of the environment of the particles. One of the most common measures of particle motion driven by fluctuations and random forces is its diffusivity, which is routinely obtained by measuring the mean squared displacement of the particles. However, often the tracer particles may be moving in a domain or an aggregate which itself experiences some regular or random motion and thus masks the diffusivity of tracers. Here we provide a method for assessing the diffusivity of tracer particles within mobile aggregates by measuring the so-called mean squared relative distance (MSRD) between two tracers. We provide analytical expressions for both the ensemble and time averaged MSRD allowing for direct identification of diffusivities from experimental data.

SU-C-204-06: Surface Imaging for the Set-Up of Proton Post-Mastectomy Chestwall Irradiation: Gated Images Vs Non Gated Images

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

Batin, E; Depauw, N; MacDonald, S

Purpose: Historically, the set-up for proton post-mastectomy chestwall irradiation at our institution started with positioning the patient using tattoos and lasers. One or more rounds of orthogonal X-rays at gantry 0° and beamline X-ray at treatment gantry angle were then taken to finalize the set-up position. As chestwall targets are shallow and superficial, surface imaging is a promising tool for set-up and needs to be investigated Methods: The orthogonal imaging was entirely replaced by AlignRT™ (ART) images. The beamline X-Ray image is kept as a confirmation, based primarily on three opaque markers placed on skin surface instead of bony anatomy.more » In the first phase of the process, ART gated images were used to set-up the patient and the same specific point of the breathing curve was used every day. The moves (translations and rotations) computed for each point of the breathing curve during the first five fractions were analyzed for ten patients. During a second phase of the study, ART gated images were replaced by ART non-gated images combined with real-time monitoring. In both cases, ART images were acquired just before treatment to access the patient position compare to the non-gated CT. Results: The average difference between the maximum move and the minimum move depending on the chosen breathing curve point was less than 1.7 mm for all translations and less than 0.7° for all rotations. The average position discrepancy over the course of treatment obtained by ART non gated images combined to real-time monitoring taken before treatment to the planning CT were smaller than the average position discrepancy obtained using ART gated images. The X-Ray validation images show similar results with both ART imaging process. Conclusion: The use of ART non gated images combined with real time imaging allows positioning post-mastectomy chestwall patients in less than 3 mm / 1°.« less

SU-F-E-09: Respiratory Signal Prediction Based On Multi-Layer Perceptron Neural Network Using Adjustable Training Samples

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

Sun, W; Jiang, M; Yin, F

Purpose: Dynamic tracking of moving organs, such as lung and liver tumors, under radiation therapy requires prediction of organ motions prior to delivery. The shift of moving organ may change a lot due to huge transform of respiration at different periods. This study aims to reduce the influence of that changes using adjustable training signals and multi-layer perceptron neural network (ASMLP). Methods: Respiratory signals obtained using a Real-time Position Management(RPM) device were used for this study. The ASMLP uses two multi-layer perceptron neural networks(MLPs) to infer respiration position alternately and the training sample will be updated with time. Firstly, amore » Savitzky-Golay finite impulse response smoothing filter was established to smooth the respiratory signal. Secondly, two same MLPs were developed to estimate respiratory position from its previous positions separately. Weights and thresholds were updated to minimize network errors according to Leverberg-Marquart optimization algorithm through backward propagation method. Finally, MLP 1 was used to predict 120∼150s respiration position using 0∼120s training signals. At the same time, MLP 2 was trained using 30∼150s training signals. Then MLP is used to predict 150∼180s training signals according to 30∼150s training signals. The respiration position is predicted as this way until it was finished. Results: In this experiment, the two methods were used to predict 2.5 minute respiratory signals. For predicting 1s ahead of response time, correlation coefficient was improved from 0.8250(MLP method) to 0.8856(ASMLP method). Besides, a 30% improvement of mean absolute error between MLP(0.1798 on average) and ASMLP(0.1267 on average) was achieved. For predicting 2s ahead of response time, correlation coefficient was improved from 0.61415 to 0.7098.Mean absolute error of MLP method(0.3111 on average) was reduced by 35% using ASMLP method(0.2020 on average). Conclusion: The preliminary results demonstrate that the ASMLP respiratory prediction method is more accurate than MLP method and can improve the respiration forecast accuracy.« less

A charged particle in a homogeneous magnetic field accelerated by a time-periodic Aharonov-Bohm flux

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

Kalvoda, T.; Stovicek, P., E-mail: stovicek@kmlinux.fjfi.cvut.cz

2011-10-15

We consider a nonrelativistic quantum charged particle moving on a plane under the influence of a uniform magnetic field and driven by a periodically time-dependent Aharonov-Bohm flux. We observe an acceleration effect in the case when the Aharonov-Bohm flux depends on time as a sinusoidal function whose frequency is in resonance with the cyclotron frequency. In particular, the energy of the particle increases linearly for large times. An explicit formula for the acceleration rate is derived with the aid of the quantum averaging method, and then it is checked against a numerical solution and a very good agreement is found.more » - Highlights: > A nonrelativistic quantum charged particle on a plane. > A homogeneous magnetic field and a periodically time-dependent Aharonov-Bohm flux. > The quantum averaging method applied to a time-dependent system. > A resonance of the AB flux with the cyclotron frequency. > An acceleration with linearly increasing energy; a formula for the acceleration rate.« less

SM91: Observations of interchange between acceleration and thermalization processes in auroral electrons

NASA Technical Reports Server (NTRS)

Pongratz, M.

1972-01-01

Results from a Nike-Tomahawk sounding rocket flight launched from Fort Churchill are presented. The rocket was launched into a breakup aurora at magnetic local midnight on 21 March 1968. The rocket was instrumented to measure electrons with an electrostatic analyzer electron spectrometer which made 29 measurements in the energy interval 0.5 KeV to 30 KeV. Complete energy spectra were obtained at a rate of 10/sec. Pitch angle information is presented via 3 computed average per rocket spin. The dumped electron average corresponds to averages over electrons moving nearly parallel to the B vector. The mirroring electron average corresponds to averages over electrons moving nearly perpendicular to the B vector. The average was also computed over the entire downward hemisphere (the precipitated electron average). The observations were obtained in an altitude range of 10 km at 230 km altitude.

Finding the average speed of a light-emitting toy car with a smartphone light sensor

NASA Astrophysics Data System (ADS)

Kapucu, Serkan

2017-07-01

This study aims to demonstrate how the average speed of a light-emitting toy car may be determined using a smartphone’s light sensor. The freely available Android smartphone application, ‘AndroSensor’, was used for the experiment. The classroom experiment combines complementary physics knowledge of optics and kinematics to find the average speed of a moving object. The speed of the toy car is found by determining the distance between the light-emitting toy car and the smartphone, and the time taken to travel these distances. To ensure that the average speed of the toy car calculated with the help of the AndroSensor was correct, the average speed was also calculated by analyzing video-recordings of the toy car. The resulting speeds found with these different methods were in good agreement with each other. Hence, it can be concluded that reliable measurements of the average speed of light-emitting objects can be determined with the help of the light sensor of an Android smartphone.

Dengue forecasting in São Paulo city with generalized additive models, artificial neural networks and seasonal autoregressive integrated moving average models.

PubMed

Baquero, Oswaldo Santos; Santana, Lidia Maria Reis; Chiaravalloti-Neto, Francisco

2018-01-01

Globally, the number of dengue cases has been on the increase since 1990 and this trend has also been found in Brazil and its most populated city-São Paulo. Surveillance systems based on predictions allow for timely decision making processes, and in turn, timely and efficient interventions to reduce the burden of the disease. We conducted a comparative study of dengue predictions in São Paulo city to test the performance of trained seasonal autoregressive integrated moving average models, generalized additive models and artificial neural networks. We also used a naïve model as a benchmark. A generalized additive model with lags of the number of cases and meteorological variables had the best performance, predicted epidemics of unprecedented magnitude and its performance was 3.16 times higher than the benchmark and 1.47 higher that the next best performing model. The predictive models captured the seasonal patterns but differed in their capacity to anticipate large epidemics and all outperformed the benchmark. In addition to be able to predict epidemics of unprecedented magnitude, the best model had computational advantages, since its training and tuning was straightforward and required seconds or at most few minutes. These are desired characteristics to provide timely results for decision makers. However, it should be noted that predictions are made just one month ahead and this is a limitation that future studies could try to reduce.

Rapid and safe learning of robotic gastrectomy for gastric cancer: multidimensional analysis in a comparison with laparoscopic gastrectomy.

PubMed

Kim, H-I; Park, M S; Song, K J; Woo, Y; Hyung, W J

2014-10-01

The learning curve of robotic gastrectomy has not yet been evaluated in comparison with the laparoscopic approach. We compared the learning curves of robotic gastrectomy and laparoscopic gastrectomy based on operation time and surgical success. We analyzed 172 robotic and 481 laparoscopic distal gastrectomies performed by single surgeon from May 2003 to April 2009. The operation time was analyzed using a moving average and non-linear regression analysis. Surgical success was evaluated by a cumulative sum plot with a target failure rate of 10%. Surgical failure was defined as laparoscopic or open conversion, insufficient lymph node harvest for staging, resection margin involvement, postoperative morbidity, and mortality. Moving average and non-linear regression analyses indicated stable state for operation time at 95 and 121 cases in robotic gastrectomy, and 270 and 262 cases in laparoscopic gastrectomy, respectively. The cumulative sum plot identified no cut-off point for surgical success in robotic gastrectomy and 80 cases in laparoscopic gastrectomy. Excluding the initial 148 laparoscopic gastrectomies that were performed before the first robotic gastrectomy, the two groups showed similar number of cases to reach steady state in operation time, and showed no cut-off point in analysis of surgical success. The experience of laparoscopic surgery could affect the learning process of robotic gastrectomy. An experienced laparoscopic surgeon requires fewer cases of robotic gastrectomy to reach steady state. Moreover, the surgical outcomes of robotic gastrectomy were satisfactory. Copyright © 2013 Elsevier Ltd. All rights reserved.

Motion tracing system for ultrasound guided HIFU

NASA Astrophysics Data System (ADS)

Xiao, Xu; Jiang, Tingyi; Corner, George; Huang, Zhihong

2017-03-01

One main limitation in HIFU treatment is the abdominal movement in liver and kidney caused by respiration. The study has set up a tracking model which mainly compromises of a target carrying box and a motion driving balloon. A real-time B-mode ultrasound guidance method suitable for tracking of the abdominal organ motion in 2D was established and tested. For the setup, the phantoms mimicking moving organs are carefully prepared with agar surrounding round-shaped egg-white as the target of focused ultrasound ablation. Physiological phantoms and animal tissues are driven moving reciprocally along the main axial direction of the ultrasound image probe with slightly motion perpendicular to the axial direction. The moving speed and range could be adjusted by controlling the inflation and deflation speed and amount of the balloon driven by a medical ventilator. A 6-DOF robotic arm was used to position the focused ultrasound transducer. The overall system was trying to estimate to simulate the actual movement caused by human respiration. HIFU ablation experiments using phantoms and animal organs were conducted to test the tracking effect. Ultrasound strain elastography was used to post estimate the efficiency of the tracking algorithms and system. In moving state, the axial size of the lesion (perpendicular to the movement direction) are averagely 4mm, which is one third larger than the lesion got when the target was not moving. This presents the possibility of developing a low-cost real-time method of tracking organ motion during HIFU treatment in liver or kidney.

Neural net forecasting for geomagnetic activity

NASA Technical Reports Server (NTRS)

Hernandez, J. V.; Tajima, T.; Horton, W.

1993-01-01

We use neural nets to construct nonlinear models to forecast the AL index given solar wind and interplanetary magnetic field (IMF) data. We follow two approaches: (1) the state space reconstruction approach, which is a nonlinear generalization of autoregressive-moving average models (ARMA) and (2) the nonlinear filter approach, which reduces to a moving average model (MA) in the linear limit. The database used here is that of Bargatze et al. (1985).

Tube Visualization and Properties from Isoconfigurational Averaging

NASA Astrophysics Data System (ADS)

Qin, Jian; Bisbee, Windsor; Milner, Scott

2012-02-01

We introduce a simulation method to visualize the confining tube in polymer melts and measure its properties. We studied bead-spring ring polymers, which conveniently suppresses constraint release and contour length fluctuations. We allow molecules to cross and reach topologically equilibrated states by invoking various molecular rebridging moves in Monte Carlo simulations. To reveal the confining tube, we start with a well equilibrated configuration, turn off rebridging moves, and run molecular dynamics simulation multiple times, each with different initial velocities. The resulting set of ``movies'' of molecular trajectories defines an isoconfigurational ensemble, with the bead positions at different times and in different ``movies'' giving rise to a cloud. The cloud shows the shape, range and strength of the tube confinement, which enables us to study the statistical properties of tube. Using this approach, we studied the effects of free surface, and found that the tube diameter near the surface is greater than the bulk value by about 25%.

Infinite charge mobility in muscovite at 300 K

NASA Astrophysics Data System (ADS)

Russell, F. Michael; Archilla, Juan F. R.; Frutos, Fabian; Medina-Carrasco, Santiago

2017-11-01

Evidence is presented for infinite charge mobility in natural crystals of muscovite mica at room temperature. Muscovite has a basic layered structure containing a flat monatomic sheet of potassium sandwiched between mirror silicate layers. It is an excellent electrical insulator. Studies of defects in muscovite crystals indicated that positive charge could propagate over great distances along atomic chains in the potassium sheets in the absence of an applied electric potential. The charge moved in association with anharmonic lattice excitations that moved at about sonic speed and created by nuclear recoil of the radioactive isotope 40K. This was verified by measuring currents passing through crystals when irradiated with energetic alpha particles at room temperature. The charge propagated more than 1000 times the range of the alpha particles of average energy and 250 times the range of channelling particles of maximum energy. The range is limited only by size of the crystal.

Structured Overlapping Grid Simulations of Contra-rotating Open Rotor Noise

NASA Technical Reports Server (NTRS)

Housman, Jeffrey A.; Kiris, Cetin C.

2015-01-01

Computational simulations using structured overlapping grids with the Launch Ascent and Vehicle Aerodynamics (LAVA) solver framework are presented for predicting tonal noise generated by a contra-rotating open rotor (CROR) propulsion system. A coupled Computational Fluid Dynamics (CFD) and Computational AeroAcoustics (CAA) numerical approach is applied. Three-dimensional time-accurate hybrid Reynolds Averaged Navier-Stokes/Large Eddy Simulation (RANS/LES) CFD simulations are performed in the inertial frame, including dynamic moving grids, using a higher-order accurate finite difference discretization on structured overlapping grids. A higher-order accurate free-stream preserving metric discretization with discrete enforcement of the Geometric Conservation Law (GCL) on moving curvilinear grids is used to create an accurate, efficient, and stable numerical scheme. The aeroacoustic analysis is based on a permeable surface Ffowcs Williams-Hawkings (FW-H) approach, evaluated in the frequency domain. A time-step sensitivity study was performed using only the forward row of blades to determine an adequate time-step. The numerical approach is validated against existing wind tunnel measurements.

MARD—A moving average rose diagram application for the geosciences

NASA Astrophysics Data System (ADS)

Munro, Mark A.; Blenkinsop, Thomas G.

2012-12-01

MARD 1.0 is a computer program for generating smoothed rose diagrams by using a moving average, which is designed for use across the wide range of disciplines encompassed within the Earth Sciences. Available in MATLAB®, Microsoft® Excel and GNU Octave formats, the program is fully compatible with both Microsoft® Windows and Macintosh operating systems. Each version has been implemented in a user-friendly way that requires no prior experience in programming with the software. MARD conducts a moving average smoothing, a form of signal processing low-pass filter, upon the raw circular data according to a set of pre-defined conditions selected by the user. This form of signal processing filter smoothes the angular dataset, emphasising significant circular trends whilst reducing background noise. Customisable parameters include whether the data is uni- or bi-directional, the angular range (or aperture) over which the data is averaged, and whether an unweighted or weighted moving average is to be applied. In addition to the uni- and bi-directional options, the MATLAB® and Octave versions also possess a function for plotting 2-dimensional dips/pitches in a single, lower, hemisphere. The rose diagrams from each version are exportable as one of a selection of common graphical formats. Frequently employed statistical measures that determine the vector mean, mean resultant (or length), circular standard deviation and circular variance are also included. MARD's scope is demonstrated via its application to a variety of datasets within the Earth Sciences.

An improved portmanteau test for autocorrelated errors in interrupted time-series regression models.

PubMed

Huitema, Bradley E; McKean, Joseph W

2007-08-01

A new portmanteau test for autocorrelation among the errors of interrupted time-series regression models is proposed. Simulation results demonstrate that the inferential properties of the proposed Q(H-M) test statistic are considerably more satisfactory than those of the well known Ljung-Box test and moderately better than those of the Box-Pierce test. These conclusions generally hold for a wide variety of autoregressive (AR), moving averages (MA), and ARMA error processes that are associated with time-series regression models of the form described in Huitema and McKean (2000a, 2000b).

Time-Series Analysis: Assessing the Effects of Multiple Educational Interventions in a Small-Enrollment Course

NASA Astrophysics Data System (ADS)

Warren, Aaron R.

2009-11-01

Time-series designs are an alternative to pretest-posttest methods that are able to identify and measure the impacts of multiple educational interventions, even for small student populations. Here, we use an instrument employing standard multiple-choice conceptual questions to collect data from students at regular intervals. The questions are modified by asking students to distribute 100 Confidence Points among the options in order to indicate the perceived likelihood of each answer option being the correct one. Tracking the class-averaged ratings for each option produces a set of time-series. ARIMA (autoregressive integrated moving average) analysis is then used to test for, and measure, changes in each series. In particular, it is possible to discern which educational interventions produce significant changes in class performance. Cluster analysis can also identify groups of students whose ratings evolve in similar ways. A brief overview of our methods and an example are presented.

Two-dimensional Lagrangian simulation of suspended sediment

USGS Publications Warehouse

Schoellhamer, David H.

1988-01-01

A two-dimensional laterally averaged model for suspended sediment transport in steady gradually varied flow that is based on the Lagrangian reference frame is presented. The layered Lagrangian transport model (LLTM) for suspended sediment performs laterally averaged concentration. The elevations of nearly horizontal streamlines and the simulation time step are selected to optimize model stability and efficiency. The computational elements are parcels of water that are moved along the streamlines in the Lagrangian sense and are mixed with neighboring parcels. Three applications show that the LLTM can accurately simulate theoretical and empirical nonequilibrium suspended sediment distributions and slug injections of suspended sediment in a laboratory flume.

Conventional and advanced time series estimation: application to the Australian and New Zealand Intensive Care Society (ANZICS) adult patient database, 1993-2006.

PubMed

Moran, John L; Solomon, Patricia J

2011-02-01

Time series analysis has seen limited application in the biomedical Literature. The utility of conventional and advanced time series estimators was explored for intensive care unit (ICU) outcome series. Monthly mean time series, 1993-2006, for hospital mortality, severity-of-illness score (APACHE III), ventilation fraction and patient type (medical and surgical), were generated from the Australia and New Zealand Intensive Care Society adult patient database. Analyses encompassed geographical seasonal mortality patterns, series structural time changes, mortality series volatility using autoregressive moving average and Generalized Autoregressive Conditional Heteroscedasticity models in which predicted variances are updated adaptively, and bivariate and multivariate (vector error correction models) cointegrating relationships between series. The mortality series exhibited marked seasonality, declining mortality trend and substantial autocorrelation beyond 24 lags. Mortality increased in winter months (July-August); the medical series featured annual cycling, whereas the surgical demonstrated long and short (3-4 months) cycling. Series structural breaks were apparent in January 1995 and December 2002. The covariance stationary first-differenced mortality series was consistent with a seasonal autoregressive moving average process; the observed conditional-variance volatility (1993-1995) and residual Autoregressive Conditional Heteroscedasticity effects entailed a Generalized Autoregressive Conditional Heteroscedasticity model, preferred by information criterion and mean model forecast performance. Bivariate cointegration, indicating long-term equilibrium relationships, was established between mortality and severity-of-illness scores at the database level and for categories of ICUs. Multivariate cointegration was demonstrated for {log APACHE III score, log ICU length of stay, ICU mortality and ventilation fraction}. A system approach to understanding series time-dependence may be established using conventional and advanced econometric time series estimators. © 2010 Blackwell Publishing Ltd.

High-Fidelity Simulations of Moving and Flexible Airfoils at Low Reynolds Numbers (Postprint)

DTIC Science & Technology

2010-02-01

1 hour per response, including the time for reviewing instructions, searching existing data sources, 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 any other...phased-averaged structures for both values of Reynolds number are found to be in good agreement with the experimental data . Finally, the effect of

Tennessee's forest land area was stable 1999-2005 but early successional forest area declined

Treesearch

Christopher M. Oswalt

2008-01-01

A new analysis of the most recent (2005) annualized moving average data for Tennessee indicates that the area of forest land in the State remained stable between 1999 and 2005. Although trends in forest land area vary from region to region within the State, Tennessee neither lost nor gained forest land between 1999 and 2005. However, Tennessee had more than 2.5 times...

1983 Annual Tropical Cyclone Report

DTIC Science & Technology

1983-01-01

intense cell of high pressure which extended throughout the troposphere and had a tremendous impact on Ellen. In addition to interfering with Ellenfs...level flow impacting Thelma is reflected in the rapidity with which the system sheared while moving northeastward at speeds up to 27 kt (50 km/hr). 95...Public reporting burder for this collection of information is estibated to average 1 hour per response, including the time for reviewing instructions

The Association between Air Pollution and Outpatient and Inpatient Visits in Shenzhen, China

PubMed Central

Liu, Yachuan; Chen, Shanen; Xu, Jian; Liu, Xiaojian; Wu, Yongsheng; Zhou, Lin; Cheng, Jinquan; Ma, Hanwu; Zheng, Jing; Lin, Denan; Zhang, Li; Chen, Lili

2018-01-01

Nowadays, air pollution is a severe environmental problem in China. To investigate the effects of ambient air pollution on health, a time series analysis of daily outpatient and inpatient visits in 2015 were conducted in Shenzhen (China). Generalized additive model was employed to analyze associations between six air pollutants (namely SO2, CO, NO2, O3, PM10, and PM2.5) and daily outpatient and inpatient visits after adjusting confounding meteorological factors, time and day of the week effects. Significant associations between air pollutants and two types of hospital visits were observed. The estimated increase in overall outpatient visits associated with each 10 µg/m3 increase in air pollutant concentration ranged from 0.48% (O3 at lag 2) to 11.48% (SO2 with 2-day moving average); for overall inpatient visits ranged from 0.73% (O3 at lag 7) to 17.13% (SO2 with 8-day moving average). Our results also suggested a heterogeneity of the health effects across different outcomes and in different populations. The findings in present study indicate that even in Shenzhen, a less polluted area in China, significant associations exist between air pollution and daily number of overall outpatient and inpatient visits. PMID:29360738

Weather explains high annual variation in butterfly dispersal.

PubMed

Kuussaari, Mikko; Rytteri, Susu; Heikkinen, Risto K; Heliölä, Janne; von Bagh, Peter

2016-07-27

Weather conditions fundamentally affect the activity of short-lived insects. Annual variation in weather is therefore likely to be an important determinant of their between-year variation in dispersal, but conclusive empirical studies are lacking. We studied whether the annual variation of dispersal can be explained by the flight season's weather conditions in a Clouded Apollo (Parnassius mnemosyne) metapopulation. This metapopulation was monitored using the mark-release-recapture method for 12 years. Dispersal was quantified for each monitoring year using three complementary measures: emigration rate (fraction of individuals moving between habitat patches), average residence time in the natal patch, and average distance moved. There was much variation both in dispersal and average weather conditions among the years. Weather variables significantly affected the three measures of dispersal and together with adjusting variables explained 79-91% of the variation observed in dispersal. Different weather variables became selected in the models explaining variation in three dispersal measures apparently because of the notable intercorrelations. In general, dispersal rate increased with increasing temperature, solar radiation, proportion of especially warm days, and butterfly density, and decreased with increasing cloudiness, rainfall, and wind speed. These results help to understand and model annually varying dispersal dynamics of species affected by global warming. © 2016 The Author(s).

Studies in astronomical time series analysis. I - Modeling random processes in the time domain

NASA Technical Reports Server (NTRS)

Scargle, J. D.

1981-01-01

Several random process models in the time domain are defined and discussed. Attention is given to the moving average model, the autoregressive model, and relationships between and combinations of these models. Consideration is then given to methods for investigating pulse structure, procedures of model construction, computational methods, and numerical experiments. A FORTRAN algorithm of time series analysis has been developed which is relatively stable numerically. Results of test cases are given to study the effect of adding noise and of different distributions for the pulse amplitudes. A preliminary analysis of the light curve of the quasar 3C 272 is considered as an example.

Features of pedestrian behavior in car-to-pedestrian contact situations in near-miss incidents in Japan.

PubMed

Matsui, Yasuhiro; Hitosugi, Masahito; Doi, Tsutomu; Oikawa, Shoko; Takahashi, Kunio; Ando, Kenichi

2013-01-01

The objective of this study is to evaluate the severe conditions between car-to-pedestrian near-miss situations using pedestrian time-to-vehicle (pedestrian TTV) which is the time when the pedestrian would reach the forward moving car line. Since the information available from the real-world accidents was limited, the authors focused on the near-miss situations captured by driving recorders installed in passenger cars. In their previous study, the authors found there were some similarities between accidents and near-miss incidents. It was made clear that the situations in pedestrians' accidents could be estimated from the near-miss incident data which included motion pictures capturing pedestrian behaviors. In their previous study, the vehicle time-to-collision (vehicle TTC) was investigated from the near-miss incident data. The authors analyzed data for 101 near-miss car-to-pedestrian incident events in which pedestrians were crossing the roads in front of a forward-moving car at an intersection or on a straight road. Using a video of near-miss car-to-pedestrian incidents captured by drive recorders and collected by the Society of Automotive Engineers of Japan (J-SAE) from 2005 to 2009, the pedestrian TTV was calculated. Based on the calculated pedestrian TTV, one of the severe conditions between car-to-pedestrian near-miss situations was evaluated for pedestrians who emerged from behind an obstruction such as a building, a parked vehicle and a moving vehicle. Focusing on the cases of the pedestrians who emerged from behind an obstruction, the averages of the vehicle TTC and pedestrian TTV were 1.31 and 1.05 seconds, respectively, and did not demonstrate a significant difference. Since the averages of the vehicle TTC and pedestrian TTV were similar, there would be a higher possibility of the contact between a car and pedestrian if the driver and pedestrian were not paying any attention. The authors propose that a moving speed of a pedestrian surrogate "dummy" should be determined considering the near-miss incident situations for the evaluation of a CDMBS for pedestrian detection. The authors also propose that the time-to-collision of the dummy to the tested car during the evaluation of the performance of the CDMBS for pedestrian detection should be determined considering the time such as the vehicle TTC in this study. Additionally or alternatively, the pedestrian TTV should be considered, in which the worst situation was assumed for a car that was moving toward a pedestrian without braking due to the car driver's inattentiveness and the pedestrian not slowing down their walking speed or stopping.

Speckle techniques for determining stresses in moving objects

NASA Technical Reports Server (NTRS)

Murphree, E. A.; Wilson, T. F.; Ranson, W. F.; Swinson, W. F.

1978-01-01

Laser speckle interferometry is a relatively new experimental technique which shows promise of alleviating many difficult problems in experimental mechanics. The method utilizes simple high-resolution photographs of the surface which is illuminated by coherent light. The result is a real-time or permanently stored whole-field record of interference fringes which yields a map of displacements in the object. In this thesis, the time-average theory using the Fourier transform is developed to present the application of this technique to measurement of in-plane displacement induced by the vibration of an object.

Unsteady Aerodynamic Force Sensing from Strain Data

NASA Technical Reports Server (NTRS)

Pak, Chan-Gi

2017-01-01

A simple approach for computing unsteady aerodynamic forces from simulated measured strain data is proposed in this study. First, the deflection and slope of the structure are computed from the unsteady strain using the two-step approach. Velocities and accelerations of the structure are computed using the autoregressive moving average model, on-line parameter estimator, low-pass filter, and a least-squares curve fitting method together with analytical derivatives with respect to time. Finally, aerodynamic forces over the wing are computed using modal aerodynamic influence coefficient matrices, a rational function approximation, and a time-marching algorithm.

Backfilling with guarantees granted upon job submission.

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

Leung, Vitus Joseph; Bunde, David P.; Lindsay, Alexander M.

2011-01-01

In this paper, we present scheduling algorithms that simultaneously support guaranteed starting times and favor jobs with system desired traits. To achieve the first of these goals, our algorithms keep a profile with potential starting times for every unfinished job and never move these starting times later, just as in Conservative Backfilling. To achieve the second, they exploit previously unrecognized flexibility in the handling of holes opened in this profile when jobs finish early. We find that, with one choice of job selection function, our algorithms can consistently yield a lower average waiting time than Conservative Backfilling while still providingmore » a guaranteed start time to each job as it arrives. In fact, in most cases, the algorithms give a lower average waiting time than the more aggressive EASY backfilling algorithm, which does not provide guaranteed start times. Alternately, with a different choice of job selection function, our algorithms can focus the benefit on the widest submitted jobs, the reason for the existence of parallel systems. In this case, these jobs experience significantly lower waiting time than Conservative Backfilling with minimal impact on other jobs.« less

Naive vs. Sophisticated Methods of Forecasting Public Library Circulations.

ERIC Educational Resources Information Center

Brooks, Terrence A.

1984-01-01

Two sophisticated--autoregressive integrated moving average (ARIMA), straight-line regression--and two naive--simple average, monthly average--forecasting techniques were used to forecast monthly circulation totals of 34 public libraries. Comparisons of forecasts and actual totals revealed that ARIMA and monthly average methods had smallest mean…

Determination of velocity correction factors for real-time air velocity monitoring in underground mines.

PubMed

Zhou, Lihong; Yuan, Liming; Thomas, Rick; Iannacchione, Anthony

2017-12-01

When there are installations of air velocity sensors in the mining industry for real-time airflow monitoring, a problem exists with how the monitored air velocity at a fixed location corresponds to the average air velocity, which is used to determine the volume flow rate of air in an entry with the cross-sectional area. Correction factors have been practically employed to convert a measured centerline air velocity to the average air velocity. However, studies on the recommended correction factors of the sensor-measured air velocity to the average air velocity at cross sections are still lacking. A comprehensive airflow measurement was made at the Safety Research Coal Mine, Bruceton, PA, using three measuring methods including single-point reading, moving traverse, and fixed-point traverse. The air velocity distribution at each measuring station was analyzed using an air velocity contour map generated with Surfer ® . The correction factors at each measuring station for both the centerline and the sensor location were calculated and are discussed.

Determination of velocity correction factors for real-time air velocity monitoring in underground mines

PubMed Central

Yuan, Liming; Thomas, Rick; Iannacchione, Anthony

2017-01-01

When there are installations of air velocity sensors in the mining industry for real-time airflow monitoring, a problem exists with how the monitored air velocity at a fixed location corresponds to the average air velocity, which is used to determine the volume flow rate of air in an entry with the cross-sectional area. Correction factors have been practically employed to convert a measured centerline air velocity to the average air velocity. However, studies on the recommended correction factors of the sensor-measured air velocity to the average air velocity at cross sections are still lacking. A comprehensive airflow measurement was made at the Safety Research Coal Mine, Bruceton, PA, using three measuring methods including single-point reading, moving traverse, and fixed-point traverse. The air velocity distribution at each measuring station was analyzed using an air velocity contour map generated with Surfer®. The correction factors at each measuring station for both the centerline and the sensor location were calculated and are discussed. PMID:29201495

Suspended Sediment Moves 10 km Before Entering Storage: Re-Interpreting a 20th Century Industrial Mercury Release as a Tracer Experiment, South River, Virginia

NASA Astrophysics Data System (ADS)

Pizzuto, J. E.

2014-12-01

Recent analyses suggest that the velocity of downstream transport of suspended sediment (averaged over long timescales that include periods of transport and storage in alluvial deposits) can be represented as the ratio Ls/T, where Ls is a distance particles move before entering storage and T is the waiting time particles spend in storage before being remobilized. Sediment budget analyses suggest that Ls is 1-100 km in the mid-Atlantic region, while T may be ~103 years, such that particles move 3-5 orders of magnitude slower than the water in the channel. Given the well-known inaccuracy of sediment budgets, independent verification from a tracer study would be desirable. Here, an historic industrial release of mercury is interpreted as a decadal sediment tracer experiment, releasing sediment particles "tagged" with mercury that are deposited on floodplains. As expected, floodplain mercury inventories decrease exponentially downstream, with a characteristic decay length of 10 km (95% confidence interval: 5-25 km) that defines the distance suspended particles typically move downstream before entering storage. Floodplain mercury inventories are not significantly different above and below three colonial age mill dams (present at the time of mercury release but now breached), suggesting that these results reflect ongoing processes. Suspended sediment routing models that neglect long-term storage, and the watershed management plans based on them, may need revision.

Axonal Membrane Proteins Are Transported in Distinct Carriers: A Two-Color Video Microscopy Study in Cultured Hippocampal NeuronsV⃞

PubMed Central

Kaether, Christoph; Skehel, Paul; Dotti, Carlos G.

2000-01-01

Neurons transport newly synthesized membrane proteins along axons by microtubule-mediated fast axonal transport. Membrane proteins destined for different axonal subdomains are thought to be transported in different transport carriers. To analyze this differential transport in living neurons, we tagged the amyloid precursor protein (APP) and synaptophysin (p38) with green fluorescent protein (GFP) variants. The resulting fusion proteins, APP-yellow fluorescent protein (YFP), p38-enhanced GFP, and p38-enhanced cyan fluorescent protein, were expressed in hippocampal neurons, and the cells were imaged by video microscopy. APP-YFP was transported in elongated tubules that moved extremely fast (on average 4.5 μm/s) and over long distances. In contrast, p38-enhanced GFP-transporting structures were more vesicular and moved four times slower (0.9 μm/s) and over shorter distances only. Two-color video microscopy showed that the two proteins were sorted to different carriers that moved with different characteristics along axons of doubly transfected neurons. Antisense treatment using oligonucleotides against the kinesin heavy chain slowed down the long, continuous movement of APP-YFP tubules and increased frequency of directional changes. These results demonstrate for the first time directly the sorting and transport of two axonal membrane proteins into different carriers. Moreover, the extremely fast-moving tubules represent a previously unidentified type of axonal carrier. PMID:10749925

Identification of multivariable nonlinear systems in the presence of colored noises using iterative hierarchical least squares algorithm.

PubMed

Jafari, Masoumeh; Salimifard, Maryam; Dehghani, Maryam

2014-07-01

This paper presents an efficient method for identification of nonlinear Multi-Input Multi-Output (MIMO) systems in the presence of colored noises. The method studies the multivariable nonlinear Hammerstein and Wiener models, in which, the nonlinear memory-less block is approximated based on arbitrary vector-based basis functions. The linear time-invariant (LTI) block is modeled by an autoregressive moving average with exogenous (ARMAX) model which can effectively describe the moving average noises as well as the autoregressive and the exogenous dynamics. According to the multivariable nature of the system, a pseudo-linear-in-the-parameter model is obtained which includes two different kinds of unknown parameters, a vector and a matrix. Therefore, the standard least squares algorithm cannot be applied directly. To overcome this problem, a Hierarchical Least Squares Iterative (HLSI) algorithm is used to simultaneously estimate the vector and the matrix of unknown parameters as well as the noises. The efficiency of the proposed identification approaches are investigated through three nonlinear MIMO case studies. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Short-term forecasts gain in accuracy. [Regression technique using ''Box-Jenkins'' analysis

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

Not Available

Box-Jenkins time-series models offer accuracy for short-term forecasts that compare with large-scale macroeconomic forecasts. Utilities need to be able to forecast peak demand in order to plan their generating, transmitting, and distribution systems. This new method differs from conventional models by not assuming specific data patterns, but by fitting available data into a tentative pattern on the basis of auto-correlations. Three types of models (autoregressive, moving average, or mixed autoregressive/moving average) can be used according to which provides the most appropriate combination of autocorrelations and related derivatives. Major steps in choosing a model are identifying potential models, estimating the parametersmore » of the problem, and running a diagnostic check to see if the model fits the parameters. The Box-Jenkins technique is well suited for seasonal patterns, which makes it possible to have as short as hourly forecasts of load demand. With accuracy up to two years, the method will allow electricity price-elasticity forecasting that can be applied to facility planning and rate design. (DCK)« less

Forecasting Instability Indicators in the Horn of Africa

DTIC Science & Technology

2008-03-01

further than 2 (Makridakis, et al, 1983, 359). 2-32 Autoregressive Integrated Moving Average ( ARIMA ) Model . Similar to the ARMA model except for...stationary process. ARIMA models are described as ARIMA (p,d,q), where p is the order of the autoregressive process, d is the degree of the...differential process, and q is the order of the moving average process. The ARMA (1,1) model shown above is equivalent to an ARIMA (1,0,1) model . An ARIMA

Evaluating and improving count-based population inference: A case study from 31 years of monitoring Sandhill Cranes

USGS Publications Warehouse

Gerber, Brian D.; Kendall, William L.

2017-01-01

Monitoring animal populations can be difficult. Limited resources often force monitoring programs to rely on unadjusted or smoothed counts as an index of abundance. Smoothing counts is commonly done using a moving-average estimator to dampen sampling variation. These indices are commonly used to inform management decisions, although their reliability is often unknown. We outline a process to evaluate the biological plausibility of annual changes in population counts and indices from a typical monitoring scenario and compare results with a hierarchical Bayesian time series (HBTS) model. We evaluated spring and fall counts, fall indices, and model-based predictions for the Rocky Mountain population (RMP) of Sandhill Cranes (Antigone canadensis) by integrating juvenile recruitment, harvest, and survival into a stochastic stage-based population model. We used simulation to evaluate population indices from the HBTS model and the commonly used 3-yr moving average estimator. We found counts of the RMP to exhibit biologically unrealistic annual change, while the fall population index was largely biologically realistic. HBTS model predictions suggested that the RMP changed little over 31 yr of monitoring, but the pattern depended on assumptions about the observational process. The HBTS model fall population predictions were biologically plausible if observed crane harvest mortality was compensatory up to natural mortality, as empirical evidence suggests. Simulations indicated that the predicted mean of the HBTS model was generally a more reliable estimate of the true population than population indices derived using a moving 3-yr average estimator. Practitioners could gain considerable advantages from modeling population counts using a hierarchical Bayesian autoregressive approach. Advantages would include: (1) obtaining measures of uncertainty; (2) incorporating direct knowledge of the observational and population processes; (3) accommodating missing years of data; and (4) forecasting population size.

Decadal Trends of Atlantic Basin Tropical Cyclones (1950-1999)

NASA Technical Reports Server (NTRS)

Wilson, Robert M.

2001-01-01

Ten-year moving averages of the seasonal rates for 'named storms,' tropical storms, hurricanes, and major (or intense) hurricanes in the Atlantic basin suggest that the present epoch is one of enhanced activity, marked by seasonal rates typically equal to or above respective long-term median rates. As an example, the 10-year moving average of the seasonal rates for named storms is now higher than for any previous year over the past 50 years, measuring 10.65 in 1994, or 2.65 units higher than its median rate of 8. Also, the 10-year moving average for tropical storms has more than doubled, from 2.15 in 1955 to 4.60 in 1992, with 16 of the past 20 years having a seasonal rate of three or more (the median rate). For hurricanes and major hurricanes, their respective 10-year moving averages turned upward, rising above long-term median rates (5.5 and 2, respectively) in 1992, a response to the abrupt increase in seasonal rates that occurred in 1995. Taken together, the outlook for future hurricane seasons is for all categories of Atlantic basin tropical cyclones to have seasonal rates at levels equal to or above long-term median rates, especially during non-El Nino-related seasons. Only during El Nino-related seasons does it appear likely that seasonal rates might be slightly diminished.

A general statistical test for correlations in a finite-length time series.

PubMed

Hanson, Jeffery A; Yang, Haw

2008-06-07

The statistical properties of the autocorrelation function from a time series composed of independently and identically distributed stochastic variables has been studied. Analytical expressions for the autocorrelation function's variance have been derived. It has been found that two common ways of calculating the autocorrelation, moving-average and Fourier transform, exhibit different uncertainty characteristics. For periodic time series, the Fourier transform method is preferred because it gives smaller uncertainties that are uniform through all time lags. Based on these analytical results, a statistically robust method has been proposed to test the existence of correlations in a time series. The statistical test is verified by computer simulations and an application to single-molecule fluorescence spectroscopy is discussed.

Solar corona electron density distribution

NASA Astrophysics Data System (ADS)

Esposito, P. B.; Edenhofer, P.; Lueneburg, E.

1980-07-01

The paper discusses the three and one-half months of single-frequency time delay data which were acquired from the Helios 2 spacecraft around the time of its solar occultation. The excess time delay due to integrated effect of free electrons along the signal's ray path could be separated and modeled following the determination of the spacecraft trajectory. An average solar corona and equatorial electron density profile during solar minimum were deduced from the time delay measurements acquired within 5-60 solar radii of the sun. As a point of reference at 10 solar radii from the sun, an average electron density was 4500 el/cu cm. However, an asymmetry was found in the electron density as the ray path moved from the west to east solar limb. This may be related to the fact that during entry into occultation the heliographic latitude of the ray path was about 6 deg, while during exit it was 7 deg. The Helios density model is compared with similar models deduced from different experimental techniques.

Real time detection of farm-level swine mycobacteriosis outbreak using time series modeling of the number of condemned intestines in abattoirs.

PubMed

Adachi, Yasumoto; Makita, Kohei

2015-09-01

Mycobacteriosis in swine is a common zoonosis found in abattoirs during meat inspections, and the veterinary authority is expected to inform the producer for corrective actions when an outbreak is detected. The expected value of the number of condemned carcasses due to mycobacteriosis therefore would be a useful threshold to detect an outbreak, and the present study aims to develop such an expected value through time series modeling. The model was developed using eight years of inspection data (2003 to 2010) obtained at 2 abattoirs of the Higashi-Mokoto Meat Inspection Center, Japan. The resulting model was validated by comparing the predicted time-dependent values for the subsequent 2 years with the actual data for 2 years between 2011 and 2012. For the modeling, at first, periodicities were checked using Fast Fourier Transformation, and the ensemble average profiles for weekly periodicities were calculated. An Auto-Regressive Integrated Moving Average (ARIMA) model was fitted to the residual of the ensemble average on the basis of minimum Akaike's information criterion (AIC). The sum of the ARIMA model and the weekly ensemble average was regarded as the time-dependent expected value. During 2011 and 2012, the number of whole or partial condemned carcasses exceeded the 95% confidence interval of the predicted values 20 times. All of these events were associated with the slaughtering of pigs from three producers with the highest rate of condemnation due to mycobacteriosis.

Assessing the impacts of Saskatchewan's minimum alcohol pricing regulations on alcohol-related crime.

PubMed

Stockwell, Tim; Zhao, Jinhui; Sherk, Adam; Callaghan, Russell C; Macdonald, Scott; Gatley, Jodi

2017-07-01

Saskatchewan's introduction in April 2010 of minimum prices graded by alcohol strength led to an average minimum price increase of 9.1% per Canadian standard drink (=13.45 g ethanol). This increase was shown to be associated with reduced consumption and switching to lower alcohol content beverages. Police also informally reported marked reductions in night-time alcohol-related crime. This study aims to assess the impacts of changes to Saskatchewan's minimum alcohol-pricing regulations between 2008 and 2012 on selected crime events often related to alcohol use. Data were obtained from Canada's Uniform Crime Reporting Survey. Auto-regressive integrated moving average time series models were used to test immediate and lagged associations between minimum price increases and rates of night-time and police identified alcohol-related crimes. Controls were included for simultaneous crime rates in the neighbouring province of Alberta, economic variables, linear trend, seasonality and autoregressive and/or moving-average effects. The introduction of increased minimum-alcohol prices was associated with an abrupt decrease in night-time alcohol-related traffic offences for men (-8.0%, P < 0.001), but not women. No significant immediate changes were observed for non-alcohol-related driving offences, disorderly conduct or violence. Significant monthly lagged effects were observed for violent offences (-19.7% at month 4 to -18.2% at month 6), which broadly corresponded to lagged effects in on-premise alcohol sales. Increased minimum alcohol prices may contribute to reductions in alcohol-related traffic-related and violent crimes perpetrated by men. Observed lagged effects for violent incidents may be due to a delay in bars passing on increased prices to their customers, perhaps because of inventory stockpiling. [Stockwell T, Zhao J, Sherk A, Callaghan RC, Macdonald S, Gatley J. Assessing the impacts of Saskatchewan's minimum alcohol pricing regulations on alcohol-related crime. Drug Alcohol Rev 2017;36:492-501]. © 2016 Australasian Professional Society on Alcohol and other Drugs.

Unsteady Airfoil Flow Solutions on Moving Zonal Grids

DTIC Science & Technology

1992-12-17

for the angle-of-attack of 15.5’, the comparisons diverge. This happens because of the different turbulence models used . At this angle- of attack, the...downstream in the wake . This vortex shedding phenomenon alters the chordwise pressure distribution on the upper surface of the airfoil resulting in higher...in- terest, turbulence modeling is used . Turbulence models are implemented with the time-averaged forms of the Navier-Stokes equations. Two widely

Nonlinear ARMA models for the D(st) index and their physical interpretation

NASA Technical Reports Server (NTRS)

Vassiliadis, D.; Klimas, A. J.; Baker, D. N.

1996-01-01

Time series models successfully reproduce or predict geomagnetic activity indices from solar wind parameters. A method is presented that converts a type of nonlinear filter, the nonlinear Autoregressive Moving Average (ARMA) model to the nonlinear damped oscillator physical model. The oscillator parameters, the growth and decay, the oscillation frequencies and the coupling strength to the input are derived from the filter coefficients. Mathematical methods are derived to obtain unique and consistent filter coefficients while keeping the prediction error low. These methods are applied to an oscillator model for the Dst geomagnetic index driven by the solar wind input. A data set is examined in two ways: the model parameters are calculated as averages over short time intervals, and a nonlinear ARMA model is calculated and the model parameters are derived as a function of the phase space.

Motile and non-motile sperm diagnostic manipulation using optoelectronic tweezers.

PubMed

Ohta, Aaron T; Garcia, Maurice; Valley, Justin K; Banie, Lia; Hsu, Hsan-Yin; Jamshidi, Arash; Neale, Steven L; Lue, Tom; Wu, Ming C

2010-12-07

Optoelectronic tweezers was used to manipulate human spermatozoa to determine whether their response to OET predicts sperm viability among non-motile sperm. We review the electro-physical basis for how live and dead human spermatozoa respond to OET. The maximal velocity that non-motile spermatozoa could be induced to move by attraction or repulsion to a moving OET field was measured. Viable sperm are attracted to OET fields and can be induced to move at an average maximal velocity of 8.8 ± 4.2 µm s(-1), while non-viable sperm are repelled to OET, and are induced to move at an average maximal velocity of -0.8 ± 1.0 µm s(-1). Manipulation of the sperm using OET does not appear to result in increased DNA fragmentation, making this a potential method by which to identify viable non-motile sperm for assisted reproductive technologies.

Transport of the moving barrier driven by chiral active particles

NASA Astrophysics Data System (ADS)

Liao, Jing-jing; Huang, Xiao-qun; Ai, Bao-quan

2018-03-01

Transport of a moving V-shaped barrier exposed to a bath of chiral active particles is investigated in a two-dimensional channel. Due to the chirality of active particles and the transversal asymmetry of the barrier position, active particles can power and steer the directed transport of the barrier in the longitudinal direction. The transport of the barrier is determined by the chirality of active particles. The moving barrier and active particles move in the opposite directions. The average velocity of the barrier is much larger than that of active particles. There exist optimal parameters (the chirality, the self-propulsion speed, the packing fraction, and the channel width) at which the average velocity of the barrier takes its maximal value. In particular, tailoring the geometry of the barrier and the active concentration provides novel strategies to control the transport properties of micro-objects or cargoes in an active medium.

[A new kinematics method of determing elbow rotation axis and evaluation of its feasibility].

PubMed

Han, W; Song, J; Wang, G Z; Ding, H; Li, G S; Gong, M Q; Jiang, X Y; Wang, M Y

2016-04-18

To study a new positioning method of elbow external fixation rotation axis, and to evaluate its feasibility. Four normal adult volunteers and six Sawbone elbow models were brought into this experiment. The kinematic data of five elbow flexion were collected respectively by optical positioning system. The rotation axes of the elbow joints were fitted by the least square method. The kinematic data and fitting results were visually displayed. According to the fitting results, the average moving planes and rotation axes were calculated. Thus, the rotation axes of new kinematic methods were obtained. By using standard clinical methods, the entrance and exit points of rotation axes of six Sawbone elbow models were located under X-ray. And The kirschner wires were placed as the representatives of rotation axes using traditional positioning methods. Then, the entrance point deviation, the exit point deviation and the angle deviation of two kinds of located rotation axes were compared. As to the four volunteers, the indicators represented circular degree and coplanarity of elbow flexion movement trajectory of each volunteer were both about 1 mm. All the distance deviations of the moving axes to the average moving rotation axes of the five volunteers were less than 3 mm. All the angle deviations of the moving axes to the average moving rotation axes of the five volunteers were less than 5°. As to the six Sawbone models, the average entrance point deviations, the average exit point deviations and the average angle deviations of two different rotation axes determined by two kinds of located methods were respectively 1.697 2 mm, 1.838 3 mm and 1.321 7°. All the deviations were very small. They were all in an acceptable range of clinical practice. The values that represent circular degree and coplanarity of volunteer's elbow single curvature movement trajectory are very small. The result shows that the elbow single curvature movement can be regarded as the approximate fixed axis movement. The new method can replace the traditional method in accuracy. It can make up the deficiency of the traditional fixed axis method.

The application of time series models to cloud field morphology analysis

NASA Technical Reports Server (NTRS)

Chin, Roland T.; Jau, Jack Y. C.; Weinman, James A.

1987-01-01

A modeling method for the quantitative description of remotely sensed cloud field images is presented. A two-dimensional texture modeling scheme based on one-dimensional time series procedures is adopted for this purpose. The time series procedure used is the seasonal autoregressive, moving average (ARMA) process in Box and Jenkins. Cloud field properties such as directionality, clustering and cloud coverage can be retrieved by this method. It has been demonstrated that a cloud field image can be quantitatively defined by a small set of parameters and synthesized surrogates can be reconstructed from these model parameters. This method enables cloud climatology to be studied quantitatively.

Theory of slightly fluctuating ratchets

NASA Astrophysics Data System (ADS)

Rozenbaum, V. M.; Shapochkina, I. V.; Lin, S. H.; Trakhtenberg, L. I.

2017-04-01

We consider a Brownian particle moving in a slightly fluctuating potential. Using the perturbation theory on small potential fluctuations, we derive a general analytical expression for the average particle velocity valid for both flashing and rocking ratchets with arbitrary, stochastic or deterministic, time dependence of potential energy fluctuations. The result is determined by the Green's function for diffusion in the time-independent part of the potential and by the features of correlations in the fluctuating part of the potential. The generality of the result allows describing complex ratchet systems with competing characteristic times; these systems are exemplified by the model of a Brownian photomotor with relaxation processes of finite duration.

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

Coruh, M; Ewell, L; Demez, N

Purpose: To estimate the dose delivered to a moving lung tumor by proton therapy beams of different modulation types, and compare with Monte Carlo predictions. Methods: A radiology support devices (RSD) phantom was irradiated with therapeutic proton radiation beams using two different types of modulation: uniform scanning (US) and double scattered (DS). The Eclipse© dose plan was designed to deliver 1.00Gy to the isocenter of a static ∼3×3×3cm (27cc) tumor in the phantom with 100% coverage. The peak to peak amplitude of tumor motion varied from 0.0 to 2.5cm. The radiation dose was measured with an ion-chamber (CC-13) located withinmore » the tumor. The time required to deliver the radiation dose varied from an average of 65s for the DS beams to an average of 95s for the US beams. Results: The amount of radiation dose varied from 100% (both US and DS) to the static tumor down to approximately 92% for the moving tumor. The ratio of US dose to DS dose ranged from approximately 1.01 for the static tumor, down to 0.99 for the 2.5cm moving tumor. A Monte Carlo simulation using TOPAS included a lung tumor with 4.0cm of peak to peak motion. In this simulation, the dose received by the tumor varied by ∼40% as the period of this motion varied from 1s to 4s. Conclusion: The radiation dose deposited to a moving tumor was less than for a static tumor, as expected. At large (2.5cm) amplitudes, the DS proton beams gave a dose closer to the desired dose than the US beams, but equal within experimental uncertainty. TOPAS Monte Carlo simulation can give insight into the moving tumor — dose relationship. This work was supported in part by the Philips corporation.« less

Characteristic Variability Timescales in the Gamma-ray Power Spectra of Blazars

NASA Astrophysics Data System (ADS)

Ryan, James Lee; Siemiginowska, Aneta; Sobolewska, Malgorzata; Grindlay, Jonathan E.

2018-01-01

We study the gamma-ray variability of 13 bright blazars observed with the Fermi Large Area Telescope in the 0.2-300 MeV band over 7.8 years.We find that continuous-time autoregressive moving average (CARMA) models provide adequate fits to the blazar light curves, and using the models we constrain the power spectral density (PSD) of each source.We also perform simulations to test the ability of CARMA modeling to recover the PSDs of artificial light curves with our data quality.Seven sources show evidence for a low-frequency break at an average timescale of ~1 year, with five of these sources showing evidence for an additional high-frequency break at an average timescale of ~7 days.We compare our results to previous studies, and discuss the possible physical interpretations of our results.

Focus on Teacher Salaries: An Update on Average Salaries and Recent Legislative Actions in the SREB States.

ERIC Educational Resources Information Center

Gaines, Gale F.

Focused state efforts have helped teacher salaries in Southern Regional Education Board (SREB) states move toward the national average. Preliminary 2000-01 estimates put SREB's average teacher salary at its highest point in 22 years compared to the national average. The SREB average teacher salary is approximately 90 percent of the national…

Adaptive Anchoring Model: How Static and Dynamic Presentations of Time Series Influence Judgments and Predictions.

PubMed

Kusev, Petko; van Schaik, Paul; Tsaneva-Atanasova, Krasimira; Juliusson, Asgeir; Chater, Nick

2018-01-01

When attempting to predict future events, people commonly rely on historical data. One psychological characteristic of judgmental forecasting of time series, established by research, is that when people make forecasts from series, they tend to underestimate future values for upward trends and overestimate them for downward ones, so-called trend-damping (modeled by anchoring on, and insufficient adjustment from, the average of recent time series values). Events in a time series can be experienced sequentially (dynamic mode), or they can also be retrospectively viewed simultaneously (static mode), not experienced individually in real time. In one experiment, we studied the influence of presentation mode (dynamic and static) on two sorts of judgment: (a) predictions of the next event (forecast) and (b) estimation of the average value of all the events in the presented series (average estimation). Participants' responses in dynamic mode were anchored on more recent events than in static mode for all types of judgment but with different consequences; hence, dynamic presentation improved prediction accuracy, but not estimation. These results are not anticipated by existing theoretical accounts; we develop and present an agent-based model-the adaptive anchoring model (ADAM)-to account for the difference between processing sequences of dynamically and statically presented stimuli (visually presented data). ADAM captures how variation in presentation mode produces variation in responses (and the accuracy of these responses) in both forecasting and judgment tasks. ADAM's model predictions for the forecasting and judgment tasks fit better with the response data than a linear-regression time series model. Moreover, ADAM outperformed autoregressive-integrated-moving-average (ARIMA) and exponential-smoothing models, while neither of these models accounts for people's responses on the average estimation task. Copyright © 2017 The Authors. Cognitive Science published by Wiley Periodicals, Inc. on behalf of Cognitive Science Society.

Non-universal tracer diffusion in crowded media of non-inert obstacles.

PubMed

Ghosh, Surya K; Cherstvy, Andrey G; Metzler, Ralf

2015-01-21

We study the diffusion of a tracer particle, which moves in continuum space between a lattice of excluded volume, immobile non-inert obstacles. In particular, we analyse how the strength of the tracer-obstacle interactions and the volume occupancy of the crowders alter the diffusive motion of the tracer. From the details of partitioning of the tracer diffusion modes between trapping states when bound to obstacles and bulk diffusion, we examine the degree of localisation of the tracer in the lattice of crowders. We study the properties of the tracer diffusion in terms of the ensemble and time averaged mean squared displacements, the trapping time distributions, the amplitude variation of the time averaged mean squared displacements, and the non-Gaussianity parameter of the diffusing tracer. We conclude that tracer-obstacle adsorption and binding triggers a transient anomalous diffusion. From a very narrow spread of recorded individual time averaged trajectories we exclude continuous type random walk processes as the underlying physical model of the tracer diffusion in our system. For moderate tracer-crowder attraction the motion is found to be fully ergodic, while at stronger attraction strength a transient disparity between ensemble and time averaged mean squared displacements occurs. We also put our results into perspective with findings from experimental single-particle tracking and simulations of the diffusion of tagged tracers in dense crowded suspensions. Our results have implications for the diffusion, transport, and spreading of chemical components in highly crowded environments inside living cells and other structured liquids.

An impact analysis of forecasting methods and forecasting parameters on bullwhip effect

NASA Astrophysics Data System (ADS)

Silitonga, R. Y. H.; Jelly, N.

2018-04-01

Bullwhip effect is an increase of variance of demand fluctuation from downstream to upstream of supply chain. Forecasting methods and forecasting parameters were recognized as some factors that affect bullwhip phenomena. To study these factors, we can develop simulations. There are several ways to simulate bullwhip effect in previous studies, such as mathematical equation modelling, information control modelling, computer program, and many more. In this study a spreadsheet program named Bullwhip Explorer was used to simulate bullwhip effect. Several scenarios were developed to show the change in bullwhip effect ratio because of the difference in forecasting methods and forecasting parameters. Forecasting methods used were mean demand, moving average, exponential smoothing, demand signalling, and minimum expected mean squared error. Forecasting parameters were moving average period, smoothing parameter, signalling factor, and safety stock factor. It showed that decreasing moving average period, increasing smoothing parameter, increasing signalling factor can create bigger bullwhip effect ratio. Meanwhile, safety stock factor had no impact to bullwhip effect.

Two-zone elastic-plastic single shock waves in solids.

PubMed

Zhakhovsky, Vasily V; Budzevich, Mikalai M; Inogamov, Nail A; Oleynik, Ivan I; White, Carter T

2011-09-23

By decoupling time and length scales in moving window molecular dynamics shock-wave simulations, a new regime of shock-wave propagation is uncovered characterized by a two-zone elastic-plastic shock-wave structure consisting of a leading elastic front followed by a plastic front, both moving with the same average speed and having a fixed net thickness that can extend to microns. The material in the elastic zone is in a metastable state that supports a pressure that can substantially exceed the critical pressure characteristic of the onset of the well-known split-elastic-plastic, two-wave propagation. The two-zone elastic-plastic wave is a general phenomenon observed in simulations of a broad class of crystalline materials and is within the reach of current experimental techniques.

Decomposition Analyses Applied to a Complex Ultradian Biorhythm: The Oscillating NADH Oxidase Activity of Plasma Membranes Having a Potential Time-Keeping (Clock) Function

PubMed Central

Foster, Ken; Anwar, Nasim; Pogue, Rhea; Morré, Dorothy M.; Keenan, T. W.; Morré, D. James

2003-01-01

Seasonal decomposition analyses were applied to the statistical evaluation of an oscillating activity for a plasma membrane NADH oxidase activity with a temperature compensated period of 24 min. The decomposition fits were used to validate the cyclic oscillatory pattern. Three measured values, average percentage error (MAPE), a measure of the periodic oscillation, mean average deviation (MAD), a measure of the absolute average deviations from the fitted values, and mean standard deviation (MSD), the measure of standard deviation from the fitted values plus R-squared and the Henriksson-Merton p value were used to evaluate accuracy. Decomposition was carried out by fitting a trend line to the data, then detrending the data if necessary, by subtracting the trend component. The data, with or without detrending, were then smoothed by subtracting a centered moving average of length equal to the period length determined by Fourier analysis. Finally, the time series were decomposed into cyclic and error components. The findings not only validate the periodic nature of the major oscillations but suggest, as well, that the minor intervening fluctuations also recur within each period with a reproducible pattern of recurrence. PMID:19330112

Out-of-plane ultrasonic velocity measurement

DOEpatents

Hall, M.S.; Brodeur, P.H.; Jackson, T.G.

1998-07-14

A method for improving the accuracy of measuring the velocity and time of flight of ultrasonic signals through moving web-like materials such as paper, paperboard and the like, includes a pair of ultrasonic transducers disposed on opposing sides of a moving web-like material. In order to provide acoustical coupling between the transducers and the web-like material, the transducers are disposed in fluid-filled wheels. Errors due to variances in the wheel thicknesses about their circumference which can affect time of flight measurements and ultimately the mechanical property being tested are compensated by averaging the ultrasonic signals for a predetermined number of revolutions. The invention further includes a method for compensating for errors resulting from the digitization of the ultrasonic signals. More particularly, the invention includes a method for eliminating errors known as trigger jitter inherent with digitizing oscilloscopes used to digitize the signals for manipulation by a digital computer. In particular, rather than cross-correlate ultrasonic signals taken during different sample periods as is known in the art in order to determine the time of flight of the ultrasonic signal through the moving web, a pulse echo box is provided to enable cross-correlation of predetermined transmitted ultrasonic signals with predetermined reflected ultrasonic or echo signals during the sample period. By cross-correlating ultrasonic signals in the same sample period, the error associated with trigger jitter is eliminated. 20 figs.

Out-of-plane ultrasonic velocity measurement

DOEpatents

Hall, Maclin S.; Brodeur, Pierre H.; Jackson, Theodore G.

1998-01-01

A method for improving the accuracy of measuring the velocity and time of flight of ultrasonic signals through moving web-like materials such as paper, paperboard and the like, includes a pair of ultrasonic transducers disposed on opposing sides of a moving web-like material. In order to provide acoustical coupling between the transducers and the web-like material, the transducers are disposed in fluid-filled wheels. Errors due to variances in the wheel thicknesses about their circumference which can affect time of flight measurements and ultimately the mechanical property being tested are compensated by averaging the ultrasonic signals for a predetermined number of revolutions. The invention further includes a method for compensating for errors resulting from the digitization of the ultrasonic signals. More particularly, the invention includes a method for eliminating errors known as trigger jitter inherent with digitizing oscilloscopes used to digitize the signals for manipulation by a digital computer. In particular, rather than cross-correlate ultrasonic signals taken during different sample periods as is known in the art in order to determine the time of flight of the ultrasonic signal through the moving web, a pulse echo box is provided to enable cross-correlation of predetermined transmitted ultrasonic signals with predetermined reflected ultrasonic or echo signals during the sample period. By cross-correlating ultrasonic signals in the same sample period, the error associated with trigger jitter is eliminated.

Flow Structure along the 1303 UCAV

NASA Astrophysics Data System (ADS)

Kosoglu, Mehmet A.; Rockwell, Donald

2007-11-01

The 1303 Unmanned Combat Air Vehicle is representative of a variety of UCAVs with blended wing-body configurations. Flow structure along a scale model of this configuration was investigated using dye visualization and particle image velocimetry for variations of Reynolds number and angle-of-attack. Both of these parameters substantially influence onset and structure of the leading-edge vortex (LEV) and a separation bubble/stall region along the tip. The onset of formation of the LEV initially occurs at a location well downstream of the apex and moves upstream for increasing values of either Reynolds number or angle-of-attack. In cases where a separation bubble or stall region exists, quantitative information on its structure was obtained via PIV imaging on a plane nearly parallel to the surface of the wing. By acquiring images on planes at successively larger elevations from the surface, it was possible to gain insight into the space-time features of the three-dimensional and highly time-dependent structure of the bubble or stall region. Time-averaged images indicate that maximum velocity defect decreases in magnitude and moves downstream with increasing elevation from the surface.

The impact of using weight estimated from mammographic images vs. self-reported weight on breast cancer risk calculation

NASA Astrophysics Data System (ADS)

Nair, Kalyani P.; Harkness, Elaine F.; Gadde, Soujanye; Lim, Yit Y.; Maxwell, Anthony J.; Moschidis, Emmanouil; Foden, Philip; Cuzick, Jack; Brentnall, Adam; Evans, D. Gareth; Howell, Anthony; Astley, Susan M.

2017-03-01

Personalised breast screening requires assessment of individual risk of breast cancer, of which one contributory factor is weight. Self-reported weight has been used for this purpose, but may be unreliable. We explore the use of volume of fat in the breast, measured from digital mammograms. Volumetric breast density measurements were used to determine the volume of fat in the breasts of 40,431 women taking part in the Predicting Risk Of Cancer At Screening (PROCAS) study. Tyrer-Cuzick risk using self-reported weight was calculated for each woman. Weight was also estimated from the relationship between self-reported weight and breast fat volume in the cohort, and used to re-calculate Tyrer-Cuzick risk. Women were assigned to risk categories according to 10 year risk (below average <2%, average 2-3.49%, above average 3.5-4.99%, moderate 5-7.99%, high >=8%) and the original and re-calculated Tyrer-Cuzick risks were compared. Of the 716 women diagnosed with breast cancer during the study, 15 (2.1%) moved into a lower risk category, and 37 (5.2%) moved into a higher category when using weight estimated from breast fat volume. Of the 39,715 women without a cancer diagnosis, 1009 (2.5%) moved into a lower risk category, and 1721 (4.3%) into a higher risk category. The majority of changes were between below average and average risk categories (38.5% of those with a cancer diagnosis, and 34.6% of those without). No individual moved more than one risk group. Automated breast fat measures may provide a suitable alternative to self-reported weight for risk assessment in personalized screening.

Investigation of furfural biodegradation in a continuous inflow cyclic biological reactor.

PubMed

Moussavi, Gholamreza; Leili, Mostafa; Nadafi, Kazem

2016-01-01

The performance of a continuous inflow cyclic biological reactor (CBR) containing moving media was investigated for the degradation of high concentrations of furfural. The effects of hydraulic retention time (HRT) and furfural initial concentrations (loading rate), as main operating parameters, on the bioreactor performance were studied. The results indicated that the CBR could remove over 98% of furfural and 71% of its chemical oxygen demand (COD) at inlet furfural concentrations up to 1,200 mg L(-1) (2.38 g L(-1) d(-1)), a 6-h cycle time and HRT of 12.1 h. The removal efficiency decreased slightly from 98 to 94% when HRT decreased from 12.1 to 10.5 h. The average removal efficiency of furfural and COD during the 345-day operational period under steady-state conditions were 97.7% and 82.1%, respectively. The efficiency also increased approximately 17.2% after addition of synthetic polyurethane cubes as moving media at a filling ratio of 10%.

SU-G-BRA-17: Tracking Multiple Targets with Independent Motion in Real-Time Using a Multi-Leaf Collimator

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

Ge, Y; Keall, P; Poulsen, P

Purpose: Multiple targets with large intrafraction independent motion are often involved in advanced prostate, lung, abdominal, and head and neck cancer radiotherapy. Current standard of care treats these with the originally planned fields, jeopardizing the treatment outcomes. A real-time multi-leaf collimator (MLC) tracking method has been developed to address this problem for the first time. This study evaluates the geometric uncertainty of the multi-target tracking method. Methods: Four treatment scenarios are simulated based on a prostate IMAT plan to treat a moving prostate target and static pelvic node target: 1) real-time multi-target MLC tracking; 2) real-time prostate-only MLC tracking; 3)more » correcting for prostate interfraction motion at setup only; and 4) no motion correction. The geometric uncertainty of the treatment is assessed by the sum of the erroneously underexposed target area and overexposed healthy tissue areas for each individual target. Two patient-measured prostate trajectories of average 2 and 5 mm motion magnitude are used for simulations. Results: Real-time multi-target tracking accumulates the least uncertainty overall. As expected, it covers the static nodes similarly well as no motion correction treatment and covers the moving prostate similarly well as the real-time prostate-only tracking. Multi-target tracking reduces >90% of uncertainty for the static nodal target compared to the real-time prostate-only tracking or interfraction motion correction. For prostate target, depending on the motion trajectory which affects the uncertainty due to leaf-fitting, multi-target tracking may or may not perform better than correcting for interfraction prostate motion by shifting patient at setup, but it reduces ∼50% of uncertainty compared to no motion correction. Conclusion: The developed real-time multi-target MLC tracking can adapt for the independently moving targets better than other available treatment adaptations. This will enable PTV margin reduction to minimize health tissue toxicity while remain tumor coverage when treating advanced disease with independently moving targets involved. The authors acknowledge funding support from the Australian NHMRC Australia Fellowship and NHMRC Project Grant No. APP1042375.« less

Sustained cooperation by running away from bad behavior

PubMed Central

Efferson, Charles; Roca, Carlos P.; Vogt, Sonja; Helbing, Dirk

2016-01-01

For cooperation to evolve, some mechanism must limit the rate at which cooperators are exposed to defectors. Only then can the advantages of mutual cooperation outweigh the costs of being exploited. Although researchers widely agree on this, they disagree intensely about which evolutionary mechanisms can explain the extraordinary cooperation exhibited by humans. Much of the controversy follows from disagreements about the informational regularity that allows cooperators to avoid defectors. Reliable information can allow cooperative individuals to avoid exploitation, but which mechanisms can sustain such a situation is a matter of considerable dispute. We conducted a behavioral experiment to see if cooperators could avoid defectors when provided with limited amounts of explicit information. We gave each participant the simple option to move away from her current neighborhood at any time. Participants were not identifiable as individuals, and they could not track each other's tendency to behave more or less cooperatively. More broadly, a participant had no information about the behavior she was likely to encounter if she moved, and so information about the risk of exploitation was extremely limited. Nonetheless, our results show that simply providing the option to move allowed cooperation to persist for a long period of time. Our results further show that movement, even though it involved considerable uncertainty, allowed would-be cooperators to assort positively and eliminate on average any individual payoff disadvantage associated with cooperation. This suggests that choosing to move, even under limited information, can completely reorganize the mix of selective forces relevant for the evolution of cooperation. PMID:26766895

Minor loop dependence of the magnetic forces and stiffness in a PM-HTS levitation system

NASA Astrophysics Data System (ADS)

Yang, Yong; Li, Chengshan

2017-12-01

Based upon the method of current vector potential and the critical state model of Bean, the vertical and lateral forces with different sizes of minor loop are simulated in two typical cooling conditions when a rectangular permanent magnet (PM) above a cylindrical high temperature superconductor (HTS) moves vertically and horizontally. The different values of average magnetic stiffness are calculated by various sizes of minor loop changing from 0.1 to 2 mm. The magnetic stiffness with zero traverse is obtained by using the method of linear extrapolation. The simulation results show that the extreme values of forces decrease with increasing size of minor loop. The magnetic hysteresis of the force curves also becomes small as the size of minor loop increases. This means that the vertical and lateral forces are significantly influenced by the size of minor loop because the forces intensely depend on the moving history of the PM. The vertical stiffness at every vertical position when the PM vertically descends to 1 mm is larger than that as the PM vertically ascents to 30 mm. When the PM moves laterally, the lateral stiffness during the PM passing through any horizontal position in the first time almost equal to the value during the PM passing through the same position in the second time in zero-field cooling (ZFC), however, the lateral stiffness in field cooling (FC) and the cross stiffness in ZFC and FC are significantly affected by the moving history of the PM.

Books average previous decade of economic misery.

PubMed

Bentley, R Alexander; Acerbi, Alberto; Ormerod, Paul; Lampos, Vasileios

2014-01-01

For the 20(th) century since the Depression, we find a strong correlation between a 'literary misery index' derived from English language books and a moving average of the previous decade of the annual U.S. economic misery index, which is the sum of inflation and unemployment rates. We find a peak in the goodness of fit at 11 years for the moving average. The fit between the two misery indices holds when using different techniques to measure the literary misery index, and this fit is significantly better than other possible correlations with different emotion indices. To check the robustness of the results, we also analysed books written in German language and obtained very similar correlations with the German economic misery index. The results suggest that millions of books published every year average the authors' shared economic experiences over the past decade.

Numerical Investigation of a Model Scramjet Combustor Using DDES

NASA Astrophysics Data System (ADS)

Shin, Junsu; Sung, Hong-Gye

2017-04-01

Non-reactive flows moving through a model scramjet were investigated using a delayed detached eddy simulation (DDES), which is a hybrid scheme combining Reynolds averaged Navier-Stokes scheme and a large eddy simulation. The three dimensional Navier-Stokes equations were solved numerically on a structural grid using finite volume methods. An in-house was developed. This code used a monotonic upstream-centered scheme for conservation laws (MUSCL) with an advection upstream splitting method by pressure weight function (AUSMPW+) for space. In addition, a 4th order Runge-Kutta scheme was used with preconditioning for time integration. The geometries and boundary conditions of a scramjet combustor operated by DLR, a German aerospace center, were considered. The profiles of the lower wall pressure and axial velocity obtained from a time-averaged solution were compared with experimental results. Also, the mixing efficiency and total pressure recovery factor were provided in order to inspect the performance of the combustor.

Effect of feedback from a socially interactive humanoid robot on reaching kinematics in children with and without cerebral palsy: A pilot study.

PubMed

Chen, Yuping; Garcia-Vergara, Sergio; Howard, Ayanna M

2017-08-17

To examine whether children with or without cerebral palsy (CP) would follow a humanoid robot's (i.e., Darwin) feedback to move their arm faster when playing virtual reality (VR) games. Seven children with mild CP and 10 able-bodied children participated. Real-time reaching was evaluated by playing the Super Pop VR TM system, including 2-game baseline, 3-game acquisition, and another 2-game extinction. During acquisition, Darwin provided verbal feedback to direct the child to reach a kinematically defined target goal (i.e., 80% of average movement time in baseline). Outcome variables included the percentage of successful reaches ("% successful reaches"), movement time (MT), average speed, path, and number of movement units. All games during acquisition and extinction had larger "%successful reaches," faster speeds, and faster MTs than the 2 games during baseline (p < .05). Children with and without CP could follow the robot's feedback for changing their reaching kinematics when playing VR games.

Prediction of South China sea level using seasonal ARIMA models

NASA Astrophysics Data System (ADS)

Fernandez, Flerida Regine; Po, Rodolfo; Montero, Neil; Addawe, Rizavel

2017-11-01

Accelerating sea level rise is an indicator of global warming and poses a threat to low-lying places and coastal countries. This study aims to fit a Seasonal Autoregressive Integrated Moving Average (SARIMA) model to the time series obtained from the TOPEX and Jason series of satellite radar altimetries of the South China Sea from the year 2008 to 2015. With altimetric measurements taken in a 10-day repeat cycle, monthly averages of the satellite altimetry measurements were taken to compose the data set used in the study. SARIMA models were then tried and fitted to the time series in order to find the best-fit model. Results show that the SARIMA(1,0,0)(0,1,1)12 model best fits the time series and was used to forecast the values for January 2016 to December 2016. The 12-month forecast using SARIMA(1,0,0)(0,1,1)12 shows that the sea level gradually increases from January to September 2016, and decreases until December 2016.

Up-down Asymmetries in Speed Perception

NASA Technical Reports Server (NTRS)

Thompson, Peter; Stone, Leland S.

1997-01-01

We compared speed matches for pairs of stimuli that moved in opposite directions (upward and downward). Stimuli were elliptical patches (2 deg horizontally by 1 deg vertically) of horizontal sinusoidal gratings of spatial. frequency 2 cycles/deg. Two sequential 380 msec reveal presentations were compared. One of each pair of gratings (the standard) moved at 4 Hz (2 deg/sec), the other (the test) moved at a rate determined by a simple up-down staircase. The point of subjectively equal speed was calculated from the average of the last eight reversals. The task was to fixate a central point and to determine which one of the pair appeared to move faster. Eight of 10 observers perceived the upward drifting grating as moving faster than a grating moving downward but otherwise identical. on average (N = 10), when the standard moved downward, it was matched by a test moving upward at 94.7+/-1.7(SE)% of the standard speed, and when the standard moved upward it was matched by a test moving downward at 105.1+/-2.3(SE)% of the standard speed. Extending this paradigm over a range of spatial (1.5 to 13.5 c/d) and temporal (1.5 to 13.5 Hz) frequencies, preliminary results (N = 4) suggest that, under the conditions of our experiment, upward matter is seen as faster than downward for speeds greater than approx.1 deg/sec, but the effect appears to reverse at speeds below approx.1 deg/sec with downward motion perceived as faster. Given that an up-down asymmetry has been observed for the optokinetic response, both perceptual and oculomotor contributions to this phenomenon deserve exploration.

The Influence of Sleep Disordered Breathing on Weight Loss in a National Weight Management Program

PubMed Central

Janney, Carol A.; Kilbourne, Amy M.; Germain, Anne; Lai, Zongshan; Hoerster, Katherine D.; Goodrich, David E.; Klingaman, Elizabeth A.; Verchinina, Lilia; Richardson, Caroline R.

2016-01-01

Study Objective: To investigate the influence of sleep disordered breathing (SDB) on weight loss in overweight/obese veterans enrolled in MOVE!, a nationally implemented behavioral weight management program delivered by the National Veterans Health Administration health system. Methods: This observational study evaluated weight loss by SDB status in overweight/obese veterans enrolled in MOVE! from May 2008–February 2012 who had at least two MOVE! visits, baseline weight, and at least one follow-up weight (n = 84,770). SDB was defined by International Classification of Diseases, Ninth Revision, Clinical Modification codes. Primary outcome was weight change (lb) from MOVE! enrollment to 6- and 12-mo assessments. Weight change over time was modeled with repeated-measures analyses. Results: SDB was diagnosed in one-third of the cohort (n = 28,269). At baseline, veterans with SDB weighed 29 [48] lb more than those without SDB (P < 0.001). On average, veterans attended eight MOVE! visits. Weight loss patterns over time were statistically different between veterans with and without SDB (P < 0.001); veterans with SDB lost less weight (−2.5 [0.1] lb) compared to those without SDB (−3.3 [0.1] lb; P = 0.001) at 6 months. At 12 mo, veterans with SDB continued to lose weight whereas veterans without SDB started to re-gain weight. Conclusions: Veterans with sleep disordered breathing (SDB) had significantly less weight loss over time than veterans without SDB. SDB should be considered in the development and implementation of weight loss programs due to its high prevalence and negative effect on health. Citation: Janney CA, Kilbourne AM, Germain A, Lai Z, Hoerster KD, Goodrich DE, Klingaman EA, Verchinina L, Richardson CR. The influence of sleep disordered breathing on weight loss in a national weight management program. SLEEP 2016;39(1):59–65. PMID:26350475

Atmospheric mold spore counts in relation to meteorological parameters

NASA Astrophysics Data System (ADS)

Katial, R. K.; Zhang, Yiming; Jones, Richard H.; Dyer, Philip D.

Fungal spore counts of Cladosporium, Alternaria, and Epicoccum were studied during 8 years in Denver, Colorado. Fungal spore counts were obtained daily during the pollinating season by a Rotorod sampler. Weather data were obtained from the National Climatic Data Center. Daily averages of temperature, relative humidity, daily precipitation, barometric pressure, and wind speed were studied. A time series analysis was performed on the data to mathematically model the spore counts in relation to weather parameters. Using SAS PROC ARIMA software, a regression analysis was performed, regressing the spore counts on the weather variables assuming an autoregressive moving average (ARMA) error structure. Cladosporium was found to be positively correlated (P<0.02) with average daily temperature, relative humidity, and negatively correlated with precipitation. Alternaria and Epicoccum did not show increased predictability with weather variables. A mathematical model was derived for Cladosporium spore counts using the annual seasonal cycle and significant weather variables. The model for Alternaria and Epicoccum incorporated the annual seasonal cycle. Fungal spore counts can be modeled by time series analysis and related to meteorological parameters controlling for seasonallity; this modeling can provide estimates of exposure to fungal aeroallergens.

Technical aspects of real time positron emission tracking for gated radiotherapy

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

Chamberland, Marc; Xu, Tong, E-mail: txu@physics.carleton.ca; McEwen, Malcolm R.

2016-02-15

Purpose: Respiratory motion can lead to treatment errors in the delivery of radiotherapy treatments. Respiratory gating can assist in better conforming the beam delivery to the target volume. We present a study of the technical aspects of a real time positron emission tracking system for potential use in gated radiotherapy. Methods: The tracking system, called PeTrack, uses implanted positron emission markers and position sensitive gamma ray detectors to track breathing motion in real time. PeTrack uses an expectation–maximization algorithm to track the motion of fiducial markers. A normalized least mean squares adaptive filter predicts the location of the markers amore » short time ahead to account for system response latency. The precision and data collection efficiency of a prototype PeTrack system were measured under conditions simulating gated radiotherapy. The lung insert of a thorax phantom was translated in the inferior–superior direction with regular sinusoidal motion and simulated patient breathing motion (maximum amplitude of motion ±10 mm, period 4 s). The system tracked the motion of a {sup 22}Na fiducial marker (0.34 MBq) embedded in the lung insert every 0.2 s. The position of the was marker was predicted 0.2 s ahead. For sinusoidal motion, the equation used to model the motion was fitted to the data. The precision of the tracking was estimated as the standard deviation of the residuals. Software was also developed to communicate with a Linac and toggle beam delivery. In a separate experiment involving a Linac, 500 monitor units of radiation were delivered to the phantom with a 3 × 3 cm photon beam and with 6 and 10 MV accelerating potential. Radiochromic films were inserted in the phantom to measure spatial dose distribution. In this experiment, the period of motion was set to 60 s to account for beam turn-on latency. The beam was turned off when the marker moved outside of a 5-mm gating window. Results: The precision of the tracking in the IS direction was 0.53 mm for a sinusoidally moving target, with an average count rate ∼250 cps. The average prediction error was 1.1 ± 0.6 mm when the marker moved according to irregular patient breathing motion. Across all beam deliveries during the radiochromic film measurements, the average prediction error was 0.8 ± 0.5 mm. The maximum error was 2.5 mm and the 95th percentile error was 1.5 mm. Clear improvement of the dose distribution was observed between gated and nongated deliveries. The full-width at halfmaximum of the dose profiles of gated deliveries differed by 3 mm or less than the static reference dose distribution. Monitoring of the beam on/off times showed synchronization with the location of the marker within the latency of the system. Conclusions: PeTrack can track the motion of internal fiducial positron emission markers with submillimeter precision. The system can be used to gate the delivery of a Linac beam based on the position of a moving fiducial marker. This highlights the potential of the system for use in respiratory-gated radiotherapy.« less

Moving through Life-Space Areas and Objectively Measured Physical Activity of Older People.

PubMed

Portegijs, Erja; Tsai, Li-Tang; Rantanen, Taina; Rantakokko, Merja

2015-01-01

Physical activity-an important determinant of health and function in old age-may vary according to the life-space area reached. Our aim was to study how moving through greater life-space areas is associated with greater physical activity of community-dwelling older people. The association between objectively measured physical activity and life-space area reached on different days by the same individual was studied using one-week longitudinal data, to provide insight in causal relationships. One-week surveillance of objectively assessed physical activity of community-dwelling 70-90-year-old people in central Finland from the "Life-space mobility in old age" cohort substudy (N = 174). In spring 2012, participants wore an accelerometer for 7 days and completed a daily diary including the largest life-space area reached (inside home, outside home, neighborhood, town, and beyond town). The daily step count, and the time in moderate (incl. walking) and low activity and sedentary behavior were assessed. Differences in physical activity between days on which different life-space areas were reached were tested using Generalized Estimation Equation models (within-group comparison). Participants' mean age was 80.4±4.2 years and 63.5% were female. Participants had higher average step counts (p < .001) and greater moderate and low activity time (p < .001) on days when greater life-space areas were reached, from the home to the town area. Only low activity time continued to increase when moving beyond the town. Community-dwelling older people were more physically active on days when they moved through greater life-space areas. While it is unknown whether physical activity was a motivator to leave the home, intervention studies are needed to determine whether facilitation of daily outdoor mobility, regardless of the purpose, may be beneficial in terms of promoting physical activity.

$1.8 Million and counting: how volatile agent education has decreased our spending $1000 per day.

PubMed

Miller, Scott A; Aschenbrenner, Carol A; Traunero, Justin R; Bauman, Loren A; Lobell, Samuel S; Kelly, Jeffrey S; Reynolds, John E

2016-12-01

Volatile anesthetic agents comprise a substantial portion of every hospital's pharmacy budget. Challenged with an initiative to lower anesthetic drug expenditures, we developed an education-based intervention focused on reducing volatile anesthetic costs while preserving access to all available volatile anesthetics. When postintervention evaluation demonstrated a dramatic year-over-year reduction in volatile agent acquisition costs, we undertook a retrospective analysis of volatile anesthetic purchasing data using time series analysis to determine the impact of our educational initiative. We obtained detailed volatile anesthetic purchasing data from the Central Supply of Wake Forest Baptist Health from 2007 to 2014 and integrated these data with the time course of our educational intervention. Aggregate volatile anesthetic purchasing data were analyzed for 7 consecutive fiscal years. The educational initiative emphasized tissue partition coefficients of volatile anesthetics in adipose tissue and muscle and their impact on case management. We used an interrupted time series analysis of monthly cost per unit data using autoregressive integrated moving average modeling, with the monthly cost per unit being the amount spent per bottle of anesthetic agent per month. The cost per unit decreased significantly after the intervention (t=-6.73, P<.001). The autoregressive integrated moving average model predicted that the average cost per unit decreased $48 after the intervention, with 95% confidence interval of $34 to $62. As evident from the data, the purchasing of desflurane and sevoflurane decreased, whereas that of isoflurane increased. An educational initiative focused solely on the selection of volatile anesthetic agent per case significantly reduced volatile anesthetic expense at a tertiary medical center. This approach appears promising for application in other hospitals in the rapidly evolving, value-added health care environment. We were able to accomplish this with instruction on tissue partition coefficients and each agent's individual cost per MAC-hour delivered. Copyright © 2016 Elsevier Inc. All rights reserved.

Tropical Cyclone Activity in the North Atlantic Basin During the Weather Satellite Era, 1960-2014

NASA Technical Reports Server (NTRS)

Wilson, Robert M.

2016-01-01

This Technical Publication (TP) represents an extension of previous work concerning the tropical cyclone activity in the North Atlantic basin during the weather satellite era, 1960-2014, in particular, that of an article published in The Journal of the Alabama Academy of Science. With the launch of the TIROS-1 polar-orbiting satellite in April 1960, a new era of global weather observation and monitoring began. Prior to this, the conditions of the North Atlantic basin were determined only from ship reports, island reports, and long-range aircraft reconnaissance. Consequently, storms that formed far from land, away from shipping lanes, and beyond the reach of aircraft possibly could be missed altogether, thereby leading to an underestimate of the true number of tropical cyclones forming in the basin. Additionally, new analysis techniques have come into use which sometimes has led to the inclusion of one or more storms at the end of a nominal hurricane season that otherwise would not have been included. In this TP, examined are the yearly (or seasonal) and 10-year moving average (10-year moving average) values of the (1) first storm day (FSD), last storm day (LSD), and length of season (LOS); (2) frequencies of tropical cyclones (by class); (3) average peak 1-minute sustained wind speed () and average lowest pressure (); (4) average genesis location in terms of north latitudinal () and west longitudinal () positions; (5) sum and average power dissipation index (); (6) sum and average accumulated cyclone energy (); (7) sum and average number of storm days (); (8) sum of the number of hurricane days (NHD) and number of major hurricane days (NMHD); (9) net tropical cyclone activity index (NTCA); (10) largest individual storm (LIS) PWS, LP, PDI, ACE, NSD, NHD, NMHD; and (11) number of category 4 and 5 hurricanes (N4/5). Also examined are the December-May (D-M) and June-November (J-N) averages and 10-year moving average values of several climatic factors, including the (1) oceanic Nino index (); (2) Atlantic multi-decadal oscillation () index; (3) Atlantic meridional mode () index; (4) global land-ocean temperature index (); and (5) quasi-biennial oscillation () index. Lastly, the associational aspects (using both linear and nonparametric statistical tests) between selected tropical cyclone parameters and the climatic factors are examined based on their 10-year moving average trend values.

Modeling of Density-Dependent Flow based on the Thermodynamically Constrained Averaging Theory

NASA Astrophysics Data System (ADS)

Weigand, T. M.; Schultz, P. B.; Kelley, C. T.; Miller, C. T.; Gray, W. G.

2016-12-01

The thermodynamically constrained averaging theory (TCAT) has been used to formulate general classes of porous medium models, including new models for density-dependent flow. The TCAT approach provides advantages that include a firm connection between the microscale, or pore scale, and the macroscale; a thermodynamically consistent basis; explicit inclusion of factors such as a diffusion that arises from gradients associated with pressure and activity and the ability to describe both high and low concentration displacement. The TCAT model is presented and closure relations for the TCAT model are postulated based on microscale averages and a parameter estimation is performed on a subset of the experimental data. Due to the sharpness of the fronts, an adaptive moving mesh technique was used to ensure grid independent solutions within the run time constraints. The optimized parameters are then used for forward simulations and compared to the set of experimental data not used for the parameter estimation.

Impacts of Climatic Variability on Vibrio parahaemolyticus Outbreaks in Taiwan

PubMed Central

Hsiao, Hsin-I; Jan, Man-Ser; Chi, Hui-Ju

2016-01-01

This study aimed to investigate and quantify the relationship between climate variation and incidence of Vibrio parahaemolyticus in Taiwan. Specifically, seasonal autoregressive integrated moving average (ARIMA) models (including autoregression, seasonality, and a lag-time effect) were employed to predict the role of climatic factors (including temperature, rainfall, relative humidity, ocean temperature and ocean salinity) on the incidence of V. parahaemolyticus in Taiwan between 2000 and 2011. The results indicated that average temperature (+), ocean temperature (+), ocean salinity of 6 months ago (+), maximum daily rainfall (current (−) and one month ago (−)), and average relative humidity (current and 9 months ago (−)) had significant impacts on the incidence of V. parahaemolyticus. Our findings offer a novel view of the quantitative relationship between climate change and food poisoning by V. parahaemolyticus in Taiwan. An early warning system based on climate change information for the disease control management is required in future. PMID:26848675

Impacts of Climatic Variability on Vibrio parahaemolyticus Outbreaks in Taiwan.

PubMed

Hsiao, Hsin-I; Jan, Man-Ser; Chi, Hui-Ju

2016-02-03

This study aimed to investigate and quantify the relationship between climate variation and incidence of Vibrio parahaemolyticus in Taiwan. Specifically, seasonal autoregressive integrated moving average (ARIMA) models (including autoregression, seasonality, and a lag-time effect) were employed to predict the role of climatic factors (including temperature, rainfall, relative humidity, ocean temperature and ocean salinity) on the incidence of V. parahaemolyticus in Taiwan between 2000 and 2011. The results indicated that average temperature (+), ocean temperature (+), ocean salinity of 6 months ago (+), maximum daily rainfall (current (-) and one month ago (-)), and average relative humidity (current and 9 months ago (-)) had significant impacts on the incidence of V. parahaemolyticus. Our findings offer a novel view of the quantitative relationship between climate change and food poisoning by V. parahaemolyticus in Taiwan. An early warning system based on climate change information for the disease control management is required in future.

Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network

PubMed Central

Marcek, Dusan; Durisova, Maria

2016-01-01

This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process. PMID:26977450

Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network.

PubMed

Falat, Lukas; Marcek, Dusan; Durisova, Maria

2016-01-01

This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process.

Forecasting Daily Volume and Acuity of Patients in the Emergency Department.

PubMed

Calegari, Rafael; Fogliatto, Flavio S; Lucini, Filipe R; Neyeloff, Jeruza; Kuchenbecker, Ricardo S; Schaan, Beatriz D

2016-01-01

This study aimed at analyzing the performance of four forecasting models in predicting the demand for medical care in terms of daily visits in an emergency department (ED) that handles high complexity cases, testing the influence of climatic and calendrical factors on demand behavior. We tested different mathematical models to forecast ED daily visits at Hospital de Clínicas de Porto Alegre (HCPA), which is a tertiary care teaching hospital located in Southern Brazil. Model accuracy was evaluated using mean absolute percentage error (MAPE), considering forecasting horizons of 1, 7, 14, 21, and 30 days. The demand time series was stratified according to patient classification using the Manchester Triage System's (MTS) criteria. Models tested were the simple seasonal exponential smoothing (SS), seasonal multiplicative Holt-Winters (SMHW), seasonal autoregressive integrated moving average (SARIMA), and multivariate autoregressive integrated moving average (MSARIMA). Performance of models varied according to patient classification, such that SS was the best choice when all types of patients were jointly considered, and SARIMA was the most accurate for modeling demands of very urgent (VU) and urgent (U) patients. The MSARIMA models taking into account climatic factors did not improve the performance of the SARIMA models, independent of patient classification.

Forecasting Daily Volume and Acuity of Patients in the Emergency Department

PubMed Central

Fogliatto, Flavio S.; Neyeloff, Jeruza; Kuchenbecker, Ricardo S.; Schaan, Beatriz D.

2016-01-01

This study aimed at analyzing the performance of four forecasting models in predicting the demand for medical care in terms of daily visits in an emergency department (ED) that handles high complexity cases, testing the influence of climatic and calendrical factors on demand behavior. We tested different mathematical models to forecast ED daily visits at Hospital de Clínicas de Porto Alegre (HCPA), which is a tertiary care teaching hospital located in Southern Brazil. Model accuracy was evaluated using mean absolute percentage error (MAPE), considering forecasting horizons of 1, 7, 14, 21, and 30 days. The demand time series was stratified according to patient classification using the Manchester Triage System's (MTS) criteria. Models tested were the simple seasonal exponential smoothing (SS), seasonal multiplicative Holt-Winters (SMHW), seasonal autoregressive integrated moving average (SARIMA), and multivariate autoregressive integrated moving average (MSARIMA). Performance of models varied according to patient classification, such that SS was the best choice when all types of patients were jointly considered, and SARIMA was the most accurate for modeling demands of very urgent (VU) and urgent (U) patients. The MSARIMA models taking into account climatic factors did not improve the performance of the SARIMA models, independent of patient classification. PMID:27725842

Identifying Active Travel Behaviors in Challenging Environments Using GPS, Accelerometers, and Machine Learning Algorithms.

PubMed

Ellis, Katherine; Godbole, Suneeta; Marshall, Simon; Lanckriet, Gert; Staudenmayer, John; Kerr, Jacqueline

2014-01-01

Active travel is an important area in physical activity research, but objective measurement of active travel is still difficult. Automated methods to measure travel behaviors will improve research in this area. In this paper, we present a supervised machine learning method for transportation mode prediction from global positioning system (GPS) and accelerometer data. We collected a dataset of about 150 h of GPS and accelerometer data from two research assistants following a protocol of prescribed trips consisting of five activities: bicycling, riding in a vehicle, walking, sitting, and standing. We extracted 49 features from 1-min windows of this data. We compared the performance of several machine learning algorithms and chose a random forest algorithm to classify the transportation mode. We used a moving average output filter to smooth the output predictions over time. The random forest algorithm achieved 89.8% cross-validated accuracy on this dataset. Adding the moving average filter to smooth output predictions increased the cross-validated accuracy to 91.9%. Machine learning methods are a viable approach for automating measurement of active travel, particularly for measuring travel activities that traditional accelerometer data processing methods misclassify, such as bicycling and vehicle travel.

Cluster structure of EU-15 countries derived from the correlation matrix analysis of macroeconomic index fluctuations

NASA Astrophysics Data System (ADS)

Gligor, M.; Ausloos, M.

2007-05-01

The statistical distances between countries, calculated for various moving average time windows, are mapped into the ultrametric subdominant space as in classical Minimal Spanning Tree methods. The Moving Average Minimal Length Path (MAMLP) algorithm allows a decoupling of fluctuations with respect to the mass center of the system from the movement of the mass center itself. A Hamiltonian representation given by a factor graph is used and plays the role of cost function. The present analysis pertains to 11 macroeconomic (ME) indicators, namely the GDP (x1), Final Consumption Expenditure (x2), Gross Capital Formation (x3), Net Exports (x4), Consumer Price Index (y1), Rates of Interest of the Central Banks (y2), Labour Force (z1), Unemployment (z2), GDP/hour worked (z3), GDP/capita (w1) and Gini coefficient (w2). The target group of countries is composed of 15 EU countries, data taken between 1995 and 2004. By two different methods (the Bipartite Factor Graph Analysis and the Correlation Matrix Eigensystem Analysis) it is found that the strongly correlated countries with respect to the macroeconomic indicators fluctuations can be partitioned into stable clusters.

Developing a Markov Model for Forecasting End Strength of Selected Marine Corps Reserve (SMCR) Officers

DTIC Science & Technology

2013-03-01

moving average ( ARIMA ) model because the data is not a times series. The best a manpower planner can do at this point is to make an educated assumption...MARKOV MODEL FOR FORECASTING END STRENGTH OF SELECTED MARINE CORPS RESERVE (SMCR) OFFICERS by Anthony D. Licari March 2013 Thesis Advisor...March 2013 3. REPORT TYPE AND DATES COVERED Master’s Thesis 4. TITLE AND SUBTITLE DEVELOPING A MARKOV MODEL FOR FORECASTING END STRENGTH OF

Proceedings of the Conference on the Design of Experiments in Army Research Development and Testing (32nd)

DTIC Science & Technology

1987-06-01

number of series among the 63 which were identified as a particular ARIMA form and were "best" modeled by a particular technique. Figure 1 illustrates a...th time from xe’s. The integrbted autoregressive - moving average model , denoted by ARIMA (p,d,q) is a result of combining d-th differencing process...Experiments, (4) Data Analysis and Modeling , (5) Theory and Probablistic Inference, (6) Fuzzy Statistics, (7) Forecasting and Prediction, (8) Small Sample

Genetically Engineered, Live Attenuated Vaccines Protect Nonhuman Primates Against Aerosol Challenge with a Virulent IE Strain of Venezuelan Equine Encephalitis Virus

DTIC Science & Technology

2005-01-21

integrated moving average ( ARIMA ) model [15,19]. Fore- casted values for the postexposure time periods were based on the training model extrapolated...Smith JF. Genetically engineered, live attenuated vaccines or Venezuelan equine encephalitis: testing in animal models . Vaccine 2003;21(25–26):3854–62...encephalitis: testing in animal models . Vaccine 2003;21(25-26):3854-62] and IE strains of VEE viruses. 15. SUBJECT TERMS Venezuelan equine

An Extension of the Time-Spectral Method to Overset Solvers

NASA Technical Reports Server (NTRS)

Leffell, Joshua Isaac; Murman, Scott M.; Pulliam, Thomas

2013-01-01

Relative motion in the Cartesian or overset framework causes certain spatial nodes to move in and out of the physical domain as they are dynamically blanked by moving solid bodies. This poses a problem for the conventional Time-Spectral approach, which expands the solution at every spatial node into a Fourier series spanning the period of motion. The proposed extension to the Time-Spectral method treats unblanked nodes in the conventional manner but expands the solution at dynamically blanked nodes in a basis of barycentric rational polynomials spanning partitions of contiguously defined temporal intervals. Rational polynomials avoid Runge's phenomenon on the equidistant time samples of these sub-periodic intervals. Fourier- and rational polynomial-based differentiation operators are used in tandem to provide a consistent hybrid Time-Spectral overset scheme capable of handling relative motion. The hybrid scheme is tested with a linear model problem and implemented within NASA's OVERFLOW Reynolds-averaged Navier- Stokes (RANS) solver. The hybrid Time-Spectral solver is then applied to inviscid and turbulent RANS cases of plunging and pitching airfoils and compared to time-accurate and experimental data. A limiter was applied in the turbulent case to avoid undershoots in the undamped turbulent eddy viscosity while maintaining accuracy. The hybrid scheme matches the performance of the conventional Time-Spectral method and converges to the time-accurate results with increased temporal resolution.

Kinesin-microtubule interactions during gliding assays under magnetic force

NASA Astrophysics Data System (ADS)

Fallesen, Todd L.

Conventional kinesin is a motor protein capable of converting the chemical energy of ATP into mechanical work. In the cell, this is used to actively transport vesicles through the intracellular matrix. The relationship between the velocity of a single kinesin, as it works against an increasing opposing load, has been well studied. The relationship between the velocity of a cargo being moved by multiple kinesin motors against an opposing load has not been established. A major difficulty in determining the force-velocity relationship for multiple motors is determining the number of motors that are moving a cargo against an opposing load. Here I report on a novel method for detaching microtubules bound to a superparamagnetic bead from kinesin anchor points in an upside down gliding assay using a uniform magnetic field perpendicular to the direction of microtubule travel. The anchor points are presumably kinesin motors bound to the surface which microtubules are gliding over. Determining the distance between anchor points, d, allows the calculation of the average number of kinesins, n, that are moving a microtubule. It is possible to calculate the fraction of motors able to move microtubules as well, which is determined to be ˜ 5%. Using a uniform magnetic field parallel to the direction of microtubule travel, it is possible to impart a uniform magnetic field on a microtubule bound to a superparamagnetic bead. We are able to decrease the average velocity of microtubules driven by multiple kinesin motors moving against an opposing force. Using the average number of kinesins on a microtubule, we estimate that there are an average 2-7 kinesins acting against the opposing force. By fitting Gaussians to the smoothed distributions of microtubule velocities acting against an opposing force, multiple velocities are seen, presumably for n, n-1, n-2, etc motors acting together. When these velocities are scaled for the average number of motors on a microtubule, the force-velocity relationship for multiple motors follows the same trend as for one motor, supporting the hypothesis that multiple motors share the load.

Fast shuttling of a particle under weak spring-constant noise of the moving trap

NASA Astrophysics Data System (ADS)

Lu, Xiao-Jing; Ruschhaupt, A.; Muga, J. G.

2018-05-01

We investigate the excitation of a quantum particle shuttled in a harmonic trap with weak spring-constant colored noise. The Ornstein-Uhlenbeck model for the noise correlation function describes a wide range of possible noises, in particular for short correlation times the white-noise limit examined by Lu et al. [Phys. Rev. A 89, 063414 (2014)], 10.1103/PhysRevA.89.063414 and, by averaging over correlation times, "1 /f flicker noise." We find expressions for the excitation energy in terms of static (independent of trap motion) and dynamical sensitivities, with opposite behavior with respect to shuttling time, and demonstrate that the excitation can be reduced by proper process timing and design of the trap trajectory.

Neural network versus classical time series forecasting models

NASA Astrophysics Data System (ADS)

Nor, Maria Elena; Safuan, Hamizah Mohd; Shab, Noorzehan Fazahiyah Md; Asrul, Mohd; Abdullah, Affendi; Mohamad, Nurul Asmaa Izzati; Lee, Muhammad Hisyam

2017-05-01

Artificial neural network (ANN) has advantage in time series forecasting as it has potential to solve complex forecasting problems. This is because ANN is data driven approach which able to be trained to map past values of a time series. In this study the forecast performance between neural network and classical time series forecasting method namely seasonal autoregressive integrated moving average models was being compared by utilizing gold price data. Moreover, the effect of different data preprocessing on the forecast performance of neural network being examined. The forecast accuracy was evaluated using mean absolute deviation, root mean square error and mean absolute percentage error. It was found that ANN produced the most accurate forecast when Box-Cox transformation was used as data preprocessing.

Books Average Previous Decade of Economic Misery

PubMed Central

Bentley, R. Alexander; Acerbi, Alberto; Ormerod, Paul; Lampos, Vasileios

2014-01-01

For the 20th century since the Depression, we find a strong correlation between a ‘literary misery index’ derived from English language books and a moving average of the previous decade of the annual U.S. economic misery index, which is the sum of inflation and unemployment rates. We find a peak in the goodness of fit at 11 years for the moving average. The fit between the two misery indices holds when using different techniques to measure the literary misery index, and this fit is significantly better than other possible correlations with different emotion indices. To check the robustness of the results, we also analysed books written in German language and obtained very similar correlations with the German economic misery index. The results suggest that millions of books published every year average the authors' shared economic experiences over the past decade. PMID:24416159

Dynamics of slow-moving landslides from permanent scatterer analysis.

PubMed

Hilley, George E; Bürgmann, Roland; Ferretti, Alessandro; Novali, Fabrizio; Rocca, Fabio

2004-06-25

High-resolution interferometric synthetic aperture radar (InSAR) permanent scatterer data allow us to resolve the rates and variations in the rates of slow-moving landslides. Satellite-to-ground distances (range changes) on landslides increase at rates of 5 to 7 millimeters per year, indicating average downslope sliding velocities from 27 to 38 millimeters per year. Time-series analysis shows that displacement occurs mainly during the high-precipitation season; during the 1997-1998 El Niño event, rates of range change increased to as much as 11 millimeters per year. The observed nonlinear relationship of creep and precipitation rates suggests that increased pore fluid pressures within the shallow subsurface may initiate and accelerate these features. Changes in the slope of a hill resulting from increases in the pore pressure and lithostatic stress gradients may then lead to landslides.

On the statistical and transport properties of a non-dissipative Fermi-Ulam model

NASA Astrophysics Data System (ADS)

Livorati, André L. P.; Dettmann, Carl P.; Caldas, Iberê L.; Leonel, Edson D.

2015-10-01

The transport and diffusion properties for the velocity of a Fermi-Ulam model were characterized using the decay rate of the survival probability. The system consists of an ensemble of non-interacting particles confined to move along and experience elastic collisions with two infinitely heavy walls. One is fixed, working as a returning mechanism of the colliding particles, while the other one moves periodically in time. The diffusion equation is solved, and the diffusion coefficient is numerically estimated by means of the averaged square velocity. Our results show remarkably good agreement of the theory and simulation for the chaotic sea below the first elliptic island in the phase space. From the decay rates of the survival probability, we obtained transport properties that can be extended to other nonlinear mappings, as well to billiard problems.

Modeling Seasonal Influenza Transmission and Its Association with Climate Factors in Thailand Using Time-Series and ARIMAX Analyses.

PubMed

Chadsuthi, Sudarat; Iamsirithaworn, Sopon; Triampo, Wannapong; Modchang, Charin

2015-01-01

Influenza is a worldwide respiratory infectious disease that easily spreads from one person to another. Previous research has found that the influenza transmission process is often associated with climate variables. In this study, we used autocorrelation and partial autocorrelation plots to determine the appropriate autoregressive integrated moving average (ARIMA) model for influenza transmission in the central and southern regions of Thailand. The relationships between reported influenza cases and the climate data, such as the amount of rainfall, average temperature, average maximum relative humidity, average minimum relative humidity, and average relative humidity, were evaluated using cross-correlation function. Based on the available data of suspected influenza cases and climate variables, the most appropriate ARIMA(X) model for each region was obtained. We found that the average temperature correlated with influenza cases in both central and southern regions, but average minimum relative humidity played an important role only in the southern region. The ARIMAX model that includes the average temperature with a 4-month lag and the minimum relative humidity with a 2-month lag is the appropriate model for the central region, whereas including the minimum relative humidity with a 4-month lag results in the best model for the southern region.

Studies on the dynamic stability of an axially moving nanobeam based on the nonlocal strain gradient theory

NASA Astrophysics Data System (ADS)

Wang, Jing; Shen, Huoming; Zhang, Bo; Liu, Juan

2018-06-01

In this paper, we studied the parametric resonance issue of an axially moving viscoelastic nanobeam with varying velocity. Based on the nonlocal strain gradient theory, we established the transversal vibration equation of the axially moving nanobeam and the corresponding boundary condition. By applying the average method, we obtained a set of self-governing ordinary differential equations when the excitation frequency of the moving parameters is twice the intrinsic frequency or near the sum of certain second-order intrinsic frequencies. On the plane of parametric excitation frequency and excitation amplitude, we can obtain the instability region generated by the resonance, and through numerical simulation, we analyze the influence of the scale effect and system parameters on the instability region. The results indicate that the viscoelastic damping decreases the resonance instability region, and the average velocity and stiffness make the instability region move to the left- and right-hand sides. Meanwhile, the scale effect of the system is obvious. The nonlocal parameter exhibits not only the stiffness softening effect but also the damping weakening effect, while the material characteristic length parameter exhibits the stiffness hardening effect and damping reinforcement effect.

Winter diel habitat use and movement by subadult bull trout in the upper Flathead River, Montana

USGS Publications Warehouse

Muhlfeld, Clint C.; Glutting, Steve; Hunt, Rick; Daniels, Durae; Marotz, Brian

2003-01-01

We evaluated the diel habitat use and movement of subadult bull trout Salvelinus confluentus by use of radiotelemetry during winter in the upper Flathead River, Montana. Of the 13 monitored bull trout, 12 (92%) made at least one diel movement to other habitat locations during their respective day–night tracking surveys and moved an average of 73% of the time. The median distance moved from day to night locations by the mobile fish was 86 m (range, 27–594 m). Diel shifts in habitat use by nine of the tagged fish were related to light intensity; nocturnal emergence generally commenced immediately after the onset of night, and daytime concealment occurred at daybreak. When diel shifts in microhabitat use occurred, subadult bull trout moved from deep, midchannel areas during the day to shallow, low-velocity areas along the channel margins without overhead cover at night. Resource managers who wish to protect the overwintering habitat features preferred by subadult bull trout in the upper Flathead River should use natural flow management strategies that maximize and stabilize channel margin habitats at night.

Peak Running Intensity of International Rugby: Implications for Training Prescription.

PubMed

Delaney, Jace A; Thornton, Heidi R; Pryor, John F; Stewart, Andrew M; Dascombe, Ben J; Duthie, Grant M

2017-09-01

To quantify the duration and position-specific peak running intensities of international rugby union for the prescription and monitoring of specific training methodologies. Global positioning systems (GPS) were used to assess the activity profile of 67 elite-level rugby union players from 2 nations across 33 international matches. A moving-average approach was used to identify the peak relative distance (m/min), average acceleration/deceleration (AveAcc; m/s 2 ), and average metabolic power (P met ) for a range of durations (1-10 min). Differences between positions and durations were described using a magnitude-based network. Peak running intensity increased as the length of the moving average decreased. There were likely small to moderate increases in relative distance and AveAcc for outside backs, halfbacks, and loose forwards compared with the tight 5 group across all moving-average durations (effect size [ES] = 0.27-1.00). P met demands were at least likely greater for outside backs and halfbacks than for the tight 5 (ES = 0.86-0.99). Halfbacks demonstrated the greatest relative distance and P met outputs but were similar to outside backs and loose forwards in AveAcc demands. The current study has presented a framework to describe the peak running intensities achieved during international rugby competition by position, which are considerably higher than previously reported whole-period averages. These data provide further knowledge of the peak activity profiles of international rugby competition, and this information can be used to assist coaches and practitioners in adequately preparing athletes for the most demanding periods of play.

Studies in astronomical time series analysis: Modeling random processes in the time domain

NASA Technical Reports Server (NTRS)

Scargle, J. D.

1979-01-01

Random process models phased in the time domain are used to analyze astrophysical time series data produced by random processes. A moving average (MA) model represents the data as a sequence of pulses occurring randomly in time, with random amplitudes. An autoregressive (AR) model represents the correlations in the process in terms of a linear function of past values. The best AR model is determined from sampled data and transformed to an MA for interpretation. The randomness of the pulse amplitudes is maximized by a FORTRAN algorithm which is relatively stable numerically. Results of test cases are given to study the effects of adding noise and of different distributions for the pulse amplitudes. A preliminary analysis of the optical light curve of the quasar 3C 273 is given.

GUMAP: A GUPIXWIN-compatible code for extracting regional spectra from nuclear microbeam list mode files

NASA Astrophysics Data System (ADS)

Russell, John L.; Campbell, John L.; Boyd, Nicholas I.; Dias, Johnny F.

2018-02-01

The newly developed GUMAP software creates element maps from OMDAQ list mode files, displays these maps individually or collectively, and facilitates on-screen definitions of specified regions from which a PIXE spectrum can be built. These include a free-hand region defined by moving the cursor. The regional charge is entered automatically into the spectrum file in a new GUPIXWIN-compatible format, enabling a GUPIXWIN analysis of the spectrum. The code defaults to the OMDAQ dead time treatment but also facilitates two other methods for dead time correction in sample regions with count rates different from the average.

Flow separation in a computational oscillating vocal fold model

NASA Astrophysics Data System (ADS)

Alipour, Fariborz; Scherer, Ronald C.

2004-09-01

A finite-volume computational model that solves the time-dependent glottal airflow within a forced-oscillation model of the glottis was employed to study glottal flow separation. Tracheal input velocity was independently controlled with a sinusoidally varying parabolic velocity profile. Control parameters included flow rate (Reynolds number), oscillation frequency and amplitude of the vocal folds, and the phase difference between the superior and inferior glottal margins. Results for static divergent glottal shapes suggest that velocity increase caused glottal separation to move downstream, but reduction in velocity increase and velocity decrease moved the separation upstream. At the fixed frequency, an increase of amplitude of the glottal walls moved the separation further downstream during glottal closing. Increase of Reynolds number caused the flow separation to move upstream in the glottis. The flow separation cross-sectional ratio ranged from approximately 1.1 to 1.9 (average of 1.47) for the divergent shapes. Results suggest that there may be a strong interaction of rate of change of airflow, inertia, and wall movement. Flow separation appeared to be ``delayed'' during the vibratory cycle, leading to movement of the separation point upstream of the glottal end only after a significant divergent angle was reached, and to persist upstream into the convergent phase of the cycle.

Who sleeps best? Longitudinal patterns and covariates of change in sleep quantity, quality, and timing across four university years.

PubMed

Galambos, Nancy L; Vargas Lascano, Dayuma I; Howard, Andrea L; Maggs, Jennifer L

2013-01-01

This study tracked change over time in sleep quantity, disturbance, and timing, and sleep's covariations with living situation, stress, social support, alcohol use, and grade point average (GPA) across four years of university in 186 Canadian students. Women slept longer as they moved through university, and men slept less; rise times were later each year. Students reported sleeping fewer hours, more sleep disturbances, and later rise times during years with higher stress. In years when students lived away from home, they reported more sleep disturbances, later bedtimes, and later rise times. Living on campus was associated with later bedtimes and rise times. Alcohol use was higher and GPA was lower when bedtimes were later. The implications of these observed patterns for understanding the correlates and consequences of university students' sleep are discussed.

Geophysical Factor Resolving of Rainfall Mechanism for Super Typhoons by Using Multiple Spatiotemporal Components Analysis

NASA Astrophysics Data System (ADS)

Huang, Chien-Lin; Hsu, Nien-Sheng

2016-04-01

This study develops a novel methodology to resolve the geophysical cause of typhoon-induced rainfall considering diverse dynamic co-evolution at multiple spatiotemporal components. The multi-order hidden patterns of complex hydrological process in chaos are detected to understand the fundamental laws of rainfall mechanism. The discovered spatiotemporal features are utilized to develop a state-of-the-art descriptive statistical model for mechanism validation, modeling and further prediction during typhoons. The time series of hourly typhoon precipitation from different types of moving track, atmospheric field and landforms are respectively precede the signal analytical process to qualify each type of rainfall cause and to quantify the corresponding affected degree based on the measured geophysical atmospheric-hydrological variables. This study applies the developed methodology in Taiwan Island which is constituted by complex diverse landform formation. The identified driving-causes include: (1) cloud height to ground surface; (2) co-movement effect induced by typhoon wind field with monsoon; (3) stem capacity; (4) interaction between typhoon rain band and terrain; (5) structural intensity variance of typhoon; and (6) integrated cloudy density of rain band. Results show that: (1) for the central maximum wind speed exceeding 51 m/sec, Causes (1) and (3) are the primary ones to generate rainfall; (2) for the typhoon moving toward the direction of 155° to 175°, Cause (2) is the primary one; (3) for the direction of 90° to 155°, Cause (4) is the primary one; (4) for the typhoon passing through mountain chain which above 3500 m, Cause (5) is the primary one; and (5) for the moving speed lower than 18 km/hr, Cause (6) is the primary one. Besides, the multiple geophysical component-based precipitation modeling can achieve 81% of average accuracy and 0.732 of average correlation coefficient (CC) within average 46 hours of duration, that improve their predictability.

Short-Term Exposure to Ambient Air Pollution and Biomarkers of Systemic Inflammation: The Framingham Heart Study.

PubMed

Li, Wenyuan; Dorans, Kirsten S; Wilker, Elissa H; Rice, Mary B; Ljungman, Petter L; Schwartz, Joel D; Coull, Brent A; Koutrakis, Petros; Gold, Diane R; Keaney, John F; Vasan, Ramachandran S; Benjamin, Emelia J; Mittleman, Murray A

2017-09-01

The objective of this study is to examine associations between short-term exposure to ambient air pollution and circulating biomarkers of systemic inflammation in participants from the Framingham Offspring and Third Generation cohorts in the greater Boston area. We included 3996 noncurrent smoking participants (mean age, 53.6 years; 54% women) who lived within 50 km from a central air pollution monitoring site in Boston, MA, and calculated the 1- to 7-day moving averages of fine particulate matter (diameter<2.5 µm), black carbon, sulfate, nitrogen oxides, and ozone before the examination visits. We used linear mixed effects models for C-reactive protein and tumor necrosis factor receptor 2, which were measured up to twice for each participant; we used linear regression models for interleukin-6, fibrinogen, and tumor necrosis factor α, which were measured once. We adjusted for demographics, socioeconomic position, lifestyle, time, and weather. The 3- to 7-day moving averages of fine particulate matter (diameter<2.5 µm) and sulfate were positively associated with C-reactive protein concentrations. A 5 µg/m 3 higher 5-day moving average fine particulate matter (diameter<2.5 µm) was associated with 4.2% (95% confidence interval: 0.8, 7.6) higher circulating C-reactive protein. Positive associations were also observed for nitrogen oxides with interleukin-6 and for black carbon, sulfate, and ozone with tumor necrosis factor receptor 2. However, black carbon, sulfate, and nitrogen oxides were negatively associated with fibrinogen, and sulfate was negatively associated with tumor necrosis factor α. Higher short-term exposure to relatively low levels of ambient air pollution was associated with higher levels of C-reactive protein, interleukin-6, and tumor necrosis factor receptor 2 but not fibrinogen or tumor necrosis factor α in individuals residing in the greater Boston area. © 2017 American Heart Association, Inc.

Tree-ring-based estimates of long-term seasonal precipitation in the Souris River Region of Saskatchewan, North Dakota and Manitoba

USGS Publications Warehouse

Ryberg, Karen R.; Vecchia, Aldo V.; Akyüz, F. Adnan; Lin, Wei

2016-01-01

Historically unprecedented flooding occurred in the Souris River Basin of Saskatchewan, North Dakota and Manitoba in 2011, during a longer term period of wet conditions in the basin. In order to develop a model of future flows, there is a need to evaluate effects of past multidecadal climate variability and/or possible climate change on precipitation. In this study, tree-ring chronologies and historical precipitation data in a four-degree buffer around the Souris River Basin were analyzed to develop regression models that can be used for predicting long-term variations of precipitation. To focus on longer term variability, 12-year moving average precipitation was modeled in five subregions (determined through cluster analysis of measures of precipitation) of the study area over three seasons (November–February, March–June and July–October). The models used multiresolution decomposition (an additive decomposition based on powers of two using a discrete wavelet transform) of tree-ring chronologies from Canada and the US and seasonal 12-year moving average precipitation based on Adjusted and Homogenized Canadian Climate Data and US Historical Climatology Network data. Results show that precipitation varies on long-term (multidecadal) time scales of 16, 32 and 64 years. Past extended pluvial and drought events, which can vary greatly with season and subregion, were highlighted by the models. Results suggest that the recent wet period may be a part of natural variability on a very long time scale.

Detection of small earthquakes with dense array data: example from the San Jacinto fault zone, southern California

NASA Astrophysics Data System (ADS)

Meng, Haoran; Ben-Zion, Yehuda

2018-01-01

We present a technique to detect small earthquakes not included in standard catalogues using data from a dense seismic array. The technique is illustrated with continuous waveforms recorded in a test day by 1108 vertical geophones in a tight array on the San Jacinto fault zone. Waveforms are first stacked without time-shift in nine non-overlapping subarrays to increase the signal-to-noise ratio. The nine envelope functions of the stacked records are then multiplied with each other to suppress signals associated with sources affecting only some of the nine subarrays. Running a short-term moving average/long-term moving average (STA/LTA) detection algorithm on the product leads to 723 triggers in the test day. Using a local P-wave velocity model derived for the surface layer from Betsy gunshot data, 5 s long waveforms of all sensors around each STA/LTA trigger are beamformed for various incident directions. Of the 723 triggers, 220 are found to have localized energy sources and 103 of these are confirmed as earthquakes by verifying their observation at 4 or more stations of the regional seismic network. This demonstrates the general validity of the method and allows processing further the validated events using standard techniques. The number of validated events in the test day is >5 times larger than that in the standard catalogue. Using these events as templates can lead to additional detections of many more earthquakes.

Movements of juvenile Gyrfalcons from western and interior Alaska following departure from their natal areas

USGS Publications Warehouse

McIntyre, Carol L.; Douglas, David C.; Adams, Layne G.

2009-01-01

Juvenile raptors often travel thousands of kilometers from the time they leave their natal areas to the time they enter a breeding population. Documenting movements and identifying areas used by raptors before they enter a breeding population is important for understanding the factors that influence their survival. In North America, juvenile Gyrfalcons (Falco rusticolus) are routinely observed outside the species' breeding range during the nonbreeding season, but the natal origins of these birds are rarely known. We used satellite telemetry to track the movements of juvenile Gyrfalcons during their first months of independence. We instrumented nestlings with lightweight satellite transmitters within 10 d of estimated fledging dates on the Seward Peninsula in western Alaska and in Denali National Park (Denali) in interior Alaska. Gyrfalcons spent an average of 41.4 ± 6.1 d (range  =  30–50 d) in their natal areas after fledging. The mean departure date from natal areas was 27 August ± 6.4 d. We tracked 15 individuals for an average of 70.5 ± 28.1 d post-departure; Gyrfalcons moved from 105 to 4299 km during this period and tended to move greater distances earlier in the tracking period than later in the tracking period. Gyrfalcons did not establish temporary winter ranges within the tracking period. We identified several movement patterns among Gyrfalcons, including unidirectional long-distance movements, multidirectional long- and short-distance movements, and shorter movements within a local region. Gyrfalcons from the Seward Peninsula remained in western Alaska or flew to eastern Russia with no movements into interior Alaska. In contrast, Gyrfalcons from Denali remained in interior Alaska, flew to northern and western Alaska, or flew to northern Alberta. Gyrfalcons from both study areas tended to move to coastal, riparian, and wetland areas during autumn and early winter. Because juvenile Gyrfalcons dispersed over a large geographic area and across three international boundaries, conservation efforts should focus on both regional and international scales.

Effects of improved spatial and temporal modeling of on-road vehicle emissions.

PubMed

Lindhjem, Christian E; Pollack, Alison K; DenBleyker, Allison; Shaw, Stephanie L

2012-04-01

Numerous emission and air quality modeling studies have suggested the need to accurately characterize the spatial and temporal variations in on-road vehicle emissions. The purpose of this study was to quantify the impact that using detailed traffic activity data has on emission estimates used to model air quality impacts. The on-road vehicle emissions are estimated by multiplying the vehicle miles traveled (VMT) by the fleet-average emission factors determined by road link and hour of day. Changes in the fraction of VMT from heavy-duty diesel vehicles (HDDVs) can have a significant impact on estimated fleet-average emissions because the emission factors for HDDV nitrogen oxides (NOx) and particulate matter (PM) are much higher than those for light-duty gas vehicles (LDGVs). Through detailed road link-level on-road vehicle emission modeling, this work investigated two scenarios for better characterizing mobile source emissions: (1) improved spatial and temporal variation of vehicle type fractions, and (2) use of Motor Vehicle Emission Simulator (MOVES2010) instead of MOBILE6 exhaust emission factors. Emissions were estimated for the Detroit and Atlanta metropolitan areas for summer and winter episodes. The VMT mix scenario demonstrated the importance of better characterizing HDDV activity by time of day, day of week, and road type. More HDDV activity occurs on restricted access road types on weekdays and at nonpeak times, compared to light-duty vehicles, resulting in 5-15% higher NOx and PM emission rates during the weekdays and 15-40% lower rates on weekend days. Use of MOVES2010 exhaust emission factors resulted in increases of more than 50% in NOx and PM for both HDDVs and LDGVs, relative to MOBILE6. Because LDGV PM emissions have been shown to increase with lower temperatures, the most dramatic increase from MOBILE6 to MOVES2010 emission rates occurred for PM2.5 from LDGVs that increased 500% during colder wintertime conditions found in Detroit, the northernmost city modeled.

Migratory Behavior and Physiological Development as Potential Determinants of Life History Diversity in Fall Chinook Salmon in the Clearwater River

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

Tiffan, Kenneth F.; Kock, Tobias J.; Connor, William P.

We studied the influence of behavior, water velocity, and physiological development on the downstream movement of subyearling fall Chinook Salmon Oncorhynchus tshawytscha in free-flowing and impounded reaches of the Clearwater and Snake rivers as potential mechanisms that might explain life history diversity in this stock. Movement rates and the percentage of radio-tagged fish that moved faster than the average current velocity were highest in the free-flowing Clearwater River compared to impounded reaches. This provided support for our hypothesis that water velocity is a primary determinant of downstream movement regardless of a fish’s physiological development. In contrast, movement rates slowed andmore » detections became fewer in impounded reaches where velocities were much lower. The percentage of fish that moved faster than the average current velocity continued to decline and reached zero in the lower-most reach of Lower Granite Reservoir suggesting that behavioral disposition to move downstream was low. These findings contrast those of a similar, previous study of Snake River subyearlings in spite of hydrodynamic conditions being similar. Physiological differences between Snake and Clearwater river migrants shed light on this disparity. Subyearlings from the Clearwater River were parr-like in their development and never showed an increase in gill Na+/K+-ATPase activity as did smolts from the Snake River. The later emergence timing and cooler rearing temperatures in the Clearwater River may suppress normal physiological development that causes many fish to delay downstream movement and adopt a yearling life history strategy.« less

Measuring multiple spike train synchrony.

PubMed

Kreuz, Thomas; Chicharro, Daniel; Andrzejak, Ralph G; Haas, Julie S; Abarbanel, Henry D I

2009-10-15

Measures of multiple spike train synchrony are essential in order to study issues such as spike timing reliability, network synchronization, and neuronal coding. These measures can broadly be divided in multivariate measures and averages over bivariate measures. One of the most recent bivariate approaches, the ISI-distance, employs the ratio of instantaneous interspike intervals (ISIs). In this study we propose two extensions of the ISI-distance, the straightforward averaged bivariate ISI-distance and the multivariate ISI-diversity based on the coefficient of variation. Like the original measure these extensions combine many properties desirable in applications to real data. In particular, they are parameter-free, time scale independent, and easy to visualize in a time-resolved manner, as we illustrate with in vitro recordings from a cortical neuron. Using a simulated network of Hindemarsh-Rose neurons as a controlled configuration we compare the performance of our methods in distinguishing different levels of multi-neuron spike train synchrony to the performance of six other previously published measures. We show and explain why the averaged bivariate measures perform better than the multivariate ones and why the multivariate ISI-diversity is the best performer among the multivariate methods. Finally, in a comparison against standard methods that rely on moving window estimates, we use single-unit monkey data to demonstrate the advantages of the instantaneous nature of our methods.

Evaluation of scaling invariance embedded in short time series.

PubMed

Pan, Xue; Hou, Lei; Stephen, Mutua; Yang, Huijie; Zhu, Chenping

2014-01-01

Scaling invariance of time series has been making great contributions in diverse research fields. But how to evaluate scaling exponent from a real-world series is still an open problem. Finite length of time series may induce unacceptable fluctuation and bias to statistical quantities and consequent invalidation of currently used standard methods. In this paper a new concept called correlation-dependent balanced estimation of diffusion entropy is developed to evaluate scale-invariance in very short time series with length ~10(2). Calculations with specified Hurst exponent values of 0.2,0.3,...,0.9 show that by using the standard central moving average de-trending procedure this method can evaluate the scaling exponents for short time series with ignorable bias (≤0.03) and sharp confidential interval (standard deviation ≤0.05). Considering the stride series from ten volunteers along an approximate oval path of a specified length, we observe that though the averages and deviations of scaling exponents are close, their evolutionary behaviors display rich patterns. It has potential use in analyzing physiological signals, detecting early warning signals, and so on. As an emphasis, the our core contribution is that by means of the proposed method one can estimate precisely shannon entropy from limited records.

Evaluation of Scaling Invariance Embedded in Short Time Series

PubMed Central

Pan, Xue; Hou, Lei; Stephen, Mutua; Yang, Huijie; Zhu, Chenping

2014-01-01

Scaling invariance of time series has been making great contributions in diverse research fields. But how to evaluate scaling exponent from a real-world series is still an open problem. Finite length of time series may induce unacceptable fluctuation and bias to statistical quantities and consequent invalidation of currently used standard methods. In this paper a new concept called correlation-dependent balanced estimation of diffusion entropy is developed to evaluate scale-invariance in very short time series with length . Calculations with specified Hurst exponent values of show that by using the standard central moving average de-trending procedure this method can evaluate the scaling exponents for short time series with ignorable bias () and sharp confidential interval (standard deviation ). Considering the stride series from ten volunteers along an approximate oval path of a specified length, we observe that though the averages and deviations of scaling exponents are close, their evolutionary behaviors display rich patterns. It has potential use in analyzing physiological signals, detecting early warning signals, and so on. As an emphasis, the our core contribution is that by means of the proposed method one can estimate precisely shannon entropy from limited records. PMID:25549356

Compact 3D Camera for Shake-the-Box Particle Tracking

NASA Astrophysics Data System (ADS)

Hesseling, Christina; Michaelis, Dirk; Schneiders, Jan

2017-11-01

Time-resolved 3D-particle tracking usually requires the time-consuming optical setup and calibration of 3 to 4 cameras. Here, a compact four-camera housing has been developed. The performance of the system using Shake-the-Box processing (Schanz et al. 2016) is characterized. It is shown that the stereo-base is large enough for sensible 3D velocity measurements. Results from successful experiments in water flows using LED illumination are presented. For large-scale wind tunnel measurements, an even more compact version of the system is mounted on a robotic arm. Once calibrated for a specific measurement volume, the necessity for recalibration is eliminated even when the system moves around. Co-axial illumination is provided through an optical fiber in the middle of the housing, illuminating the full measurement volume from one viewing direction. Helium-filled soap bubbles are used to ensure sufficient particle image intensity. This way, the measurement probe can be moved around complex 3D-objects. By automatic scanning and stitching of recorded particle tracks, the detailed time-averaged flow field of a full volume of cubic meters in size is recorded and processed. Results from an experiment at TU-Delft of the flow field around a cyclist are shown.

Transport in the barrier billiard

NASA Astrophysics Data System (ADS)

Saberi Fathi, S. M.; Ettoumi, W.; Courbage, M.

2016-06-01

We investigate transport properties of an ensemble of particles moving inside an infinite periodic horizontal planar barrier billiard. A particle moves among bars and elastically reflects on them. The motion is a uniform translation along the bars' axis. When the tangent of the incidence angle, α , is fixed and rational, the second moment of the displacement along the orthogonal axis at time n , , is either bounded or asymptotic to K n2 , when n →∞ . For irrational α , the collision map is ergodic and has a family of weakly mixing observables, the transport is not ballistic, and autocorrelation functions decay only in time average, but may not decay for a family of irrational α 's. An exhaustive numerical computation shows that the transport may be superdiffusive or subdiffusive with various rates or bounded strongly depending on the values of α . The variety of transport behaviors sounds reminiscent of well-known behavior of conservative systems. Considering then an ensemble of particles with nonfixed α , the system is nonergodic and certainly not mixing and has anomalous diffusion with self-similar space-time properties. However, we verified that such a system decomposes into ergodic subdynamics breaking self-similarity.

Development of temporal modelling for forecasting and prediction of malaria infections using time-series and ARIMAX analyses: a case study in endemic districts of Bhutan.

PubMed

Wangdi, Kinley; Singhasivanon, Pratap; Silawan, Tassanee; Lawpoolsri, Saranath; White, Nicholas J; Kaewkungwal, Jaranit

2010-09-03

Malaria still remains a public health problem in some districts of Bhutan despite marked reduction of cases in last few years. To strengthen the country's prevention and control measures, this study was carried out to develop forecasting and prediction models of malaria incidence in the endemic districts of Bhutan using time series and ARIMAX. This study was carried out retrospectively using the monthly reported malaria cases from the health centres to Vector-borne Disease Control Programme (VDCP) and the meteorological data from Meteorological Unit, Department of Energy, Ministry of Economic Affairs. Time series analysis was performed on monthly malaria cases, from 1994 to 2008, in seven malaria endemic districts. The time series models derived from a multiplicative seasonal autoregressive integrated moving average (ARIMA) was deployed to identify the best model using data from 1994 to 2006. The best-fit model was selected for each individual district and for the overall endemic area was developed and the monthly cases from January to December 2009 and 2010 were forecasted. In developing the prediction model, the monthly reported malaria cases and the meteorological factors from 1996 to 2008 of the seven districts were analysed. The method of ARIMAX modelling was employed to determine predictors of malaria of the subsequent month. It was found that the ARIMA (p, d, q) (P, D, Q)s model (p and P representing the auto regressive and seasonal autoregressive; d and D representing the non-seasonal differences and seasonal differencing; and q and Q the moving average parameters and seasonal moving average parameters, respectively and s representing the length of the seasonal period) for the overall endemic districts was (2,1,1)(0,1,1)12; the modelling data from each district revealed two most common ARIMA models including (2,1,1)(0,1,1)12 and (1,1,1)(0,1,1)12. The forecasted monthly malaria cases from January to December 2009 and 2010 varied from 15 to 82 cases in 2009 and 67 to 149 cases in 2010, where population in 2009 was 285,375 and the expected population of 2010 to be 289,085. The ARIMAX model of monthly cases and climatic factors showed considerable variations among the different districts. In general, the mean maximum temperature lagged at one month was a strong positive predictor of an increased malaria cases for four districts. The monthly number of cases of the previous month was also a significant predictor in one district, whereas no variable could predict malaria cases for two districts. The ARIMA models of time-series analysis were useful in forecasting the number of cases in the endemic areas of Bhutan. There was no consistency in the predictors of malaria cases when using ARIMAX model with selected lag times and climatic predictors. The ARIMA forecasting models could be employed for planning and managing malaria prevention and control programme in Bhutan.

A travel time forecasting model based on change-point detection method

NASA Astrophysics Data System (ADS)

LI, Shupeng; GUANG, Xiaoping; QIAN, Yongsheng; ZENG, Junwei

2017-06-01

Travel time parameters obtained from road traffic sensors data play an important role in traffic management practice. A travel time forecasting model is proposed for urban road traffic sensors data based on the method of change-point detection in this paper. The first-order differential operation is used for preprocessing over the actual loop data; a change-point detection algorithm is designed to classify the sequence of large number of travel time data items into several patterns; then a travel time forecasting model is established based on autoregressive integrated moving average (ARIMA) model. By computer simulation, different control parameters are chosen for adaptive change point search for travel time series, which is divided into several sections of similar state.Then linear weight function is used to fit travel time sequence and to forecast travel time. The results show that the model has high accuracy in travel time forecasting.

Distractor Interference during Smooth Pursuit Eye Movements

ERIC Educational Resources Information Center

Spering, Miriam; Gegenfurtner, Karl R.; Kerzel, Dirk

2006-01-01

When 2 targets for pursuit eye movements move in different directions, the eye velocity follows the vector average (S. G. Lisberger & V. P. Ferrera, 1997). The present study investigates the mechanisms of target selection when observers are instructed to follow a predefined horizontal target and to ignore a moving distractor stimulus. Results show…

Nonlinear System Identification for Aeroelastic Systems with Application to Experimental Data

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.

2008-01-01

Representation and identification of a nonlinear aeroelastic pitch-plunge system as a model of the Nonlinear AutoRegressive, Moving Average eXogenous (NARMAX) class is considered. A nonlinear difference equation describing this aircraft model is derived theoretically and shown to be of the NARMAX form. Identification methods for NARMAX models are applied to aeroelastic dynamics and its properties demonstrated via continuous-time simulations of experimental conditions. Simulation results show that (1) the outputs of the NARMAX model closely match those generated using continuous-time methods, and (2) NARMAX identification methods applied to aeroelastic dynamics provide accurate discrete-time parameter estimates. Application of NARMAX identification to experimental pitch-plunge dynamics data gives a high percent fit for cross-validated data.

A Comparison of Forecast Error Generators for Modeling Wind and Load Uncertainty

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

Lu, Ning; Diao, Ruisheng; Hafen, Ryan P.

2013-12-18

This paper presents four algorithms to generate random forecast error time series, including a truncated-normal distribution model, a state-space based Markov model, a seasonal autoregressive moving average (ARMA) model, and a stochastic-optimization based model. The error time series are used to create real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast time series that statistically match historically observed forecasting data sets, used for variable generation integration studies. A comparison is made using historical DA load forecast and actual load values to generate new sets of DA forecasts with similar stoical forecast error characteristics. This paper discusses and comparesmore » the capabilities of each algorithm to preserve the characteristics of the historical forecast data sets.« less

Using Point Clouds Generated from Unmanned Aerial Vehicles Imagery Processed with Structure from Motion to Address Tsunami vs Storm Wave Boulder Deposition in Watu Karung, Indonesia

NASA Astrophysics Data System (ADS)

Uribe, A. T.; Bunds, M. P.; Andreini, J.; Horns, D. M.; Harris, R. A.; Prasetyadi, C.; Yulianto, E.; Putra, P. S.

2017-12-01

Tsunamis pose a major hazard to coastal communities along the south coast of much of Indonesia due its location on the Australian-Sunda arc. Furthermore, tsunamis and high-energy wave events are the principal drivers of geomorphic change in the area and it is difficult to distinguish the effects of each. A potentially useful indicator of past tsunami activity is coastal imbricated boulder deposits. To address whether an imbricated boulder deposit located on a beach in Watu Karung (Java, Indonesia) could have been formed by non-tsunami wave activity and to investigate coastal geomorphic change, we generated three pairs of digital surface models (DSMs) over an approximately one year period using photographs taken from a small unmanned aerial vehicle and structure-from-motion photogrammetry. The first two DSMs were made from photographs taken on 7/30-31/2016 and 8/2/2016, immediately before and after a significant 4.2 m swell struck the beach during a +2.5 m spring high tide. The third DSM pair was made from imagery collected 7/12/2017. Each pair of DSMs consists of a 1 cm pixel DSM of the boulder deposit and a 4 cm DSM of the larger beach area that surrounds the boulders. In addition, prior to the 2016 wave event 21 boulders up to 75 kg were marked and hand-placed shoreward of the boulder deposit; their movement was tracked with RTK GPS measurements. In the 2016 wave event, every hand-placed boulder moved, with an average displacement of 27.6 m. At the same time, approximately 20 of 650 naturally - occurring boulders, up to 2 m in length, moved more than 10 cm and up to 5.6 m. Between 2016 and 2017, approximately 300 of 650 naturally - occurring boulders with an average length of 1.6 m moved varying distances of at least 10 cm and up to 30 m. In addition, changes in beach sand volume occurred in ten 25 m2 localized zones on the beach with an average volume change of approximately 65 m2. Changes in both boulder position and sand volume occurred during the 2016 to 2017 time period when no tsunamis affected Watu Karung—thus indicating that all changes were the result of storm wave events.

Experiment and modeling of paired effect on evacuation from a three-dimensional space

NASA Astrophysics Data System (ADS)

Jun, Hu; Huijun, Sun; Juan, Wei; Xiaodan, Chen; Lei, You; Musong, Gu

2014-10-01

A novel three-dimensional cellular automata evacuation model was proposed based on stairs factor for paired effect and variety velocities in pedestrian evacuation. In the model pedestrians' moving probability of target position at the next moment was defined based on distance profit and repulsive force profit, and evacuation strategy was elaborated in detail through analyzing variety velocities and repulsive phenomenon in moving process. At last, experiments with the simulation platform were conducted to study the relationships of evacuation time, average velocity and pedestrian velocity. The results showed that when the ratio of single pedestrian was higher in the system, the shortest route strategy was good for improving evacuation efficiency; in turn, if ratio of paired pedestrians was higher, it is good for improving evacuation efficiency to adopt strategy that avoided conflicts, and priority should be given to scattered evacuation.

Characteristic correlation study of UV disinfection performance for ballast water treatment

NASA Astrophysics Data System (ADS)

Ba, Te; Li, Hongying; Osman, Hafiiz; Kang, Chang-Wei

2016-11-01

Characteristic correlation between ultraviolet disinfection performance and operating parameters, including ultraviolet transmittance (UVT), lamp power and water flow rate, was studied by numerical and experimental methods. A three-stage model was developed to simulate the fluid flow, UV radiation and the trajectories of microorganisms. Navier-Stokes equation with k-epsilon turbulence was solved to model the fluid flow, while discrete ordinates (DO) radiation model and discrete phase model (DPM) were used to introduce UV radiation and microorganisms trajectories into the model, respectively. The UV dose statistical distribution for the microorganisms was found to move to higher value with the increase of UVT and lamp power, but moves to lower value when the water flow rate increases. Further investigation shows that the fluence rate increases exponentially with UVT but linearly with the lamp power. The average and minimum resident time decreases linearly with the water flow rate while the maximum resident time decrease rapidly in a certain range. The current study can be used as a digital design and performance evaluation tool of the UV reactor for ballast water treatment.

Respiratory-Induced Prostate Motion Using Wavelet Decomposition of the Real-Time Electromagnetic Tracking Signal

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

Lin, Yuting; Liu, Tian; Yang, Xiaofeng

2013-10-01

Purpose: The objective of this work is to characterize and quantify the impact of respiratory-induced prostate motion. Methods and Materials: Real-time intrafraction motion is observed with the Calypso 4-dimensional nonradioactive electromagnetic tracking system (Calypso Medical Technologies, Inc. Seattle, Washington). We report the results from a total of 1024 fractions from 31 prostate cancer patients. Wavelet transform was used to decompose the signal to extract and isolate the respiratory-induced prostate motion from the total prostate displacement. Results: Our results show that the average respiratory motion larger than 0.5 mm can be observed in 68% of the fractions. Fewer than 1% ofmore » the patients showed average respiratory motion of less than 0.2 mm, whereas 99% of the patients showed average respiratory-induced motion ranging between 0.2 and 2 mm. The maximum respiratory range of motion of 3 mm or greater was seen in only 25% of the fractions. In addition, about 2% patients showed anxiety, indicated by a breathing frequency above 24 times per minute. Conclusions: Prostate motion is influenced by respiration in most fractions. Real-time intrafraction data are sensitive enough to measure the impact of respiration by use of wavelet decomposition methods. Although the average respiratory amplitude observed in this study is small, this technique provides a tool that can be useful if one moves to smaller treatment margins (≤5 mm). This also opens ups the possibility of being able to develop patient specific margins, knowing that prostate motion is not unpredictable.« less

Association of heart rate variability in taxi drivers with marked changes in particulate air pollution in Beijing in 2008.

PubMed

Wu, Shaowei; Deng, Furong; Niu, Jie; Huang, Qinsheng; Liu, Youcheng; Guo, Xinbiao

2010-01-01

Heart rate variability (HRV), a marker of cardiac autonomic function, has been -associated with particulate matter (PM) air pollution, especially in older patients and those with cardio-vascular diseases. However, the effect of PM exposure on cardiac autonomic function in young, healthy adults has received less attention. We evaluated the relationship between exposure to traffic-related PM with an aerodynamic diameter

Estimating Perturbation and Meta-Stability in the Daily Attendance Rates of Six Small High Schools

NASA Astrophysics Data System (ADS)

Koopmans, Matthijs

This paper discusses the daily attendance rates in six small high schools over a ten-year period and evaluates how stable those rates are. “Stability” is approached from two vantage points: pulse models are fitted to estimate the impact of sudden perturbations and their reverberation through the series, and Autoregressive Fractionally Integrated Moving Average (ARFIMA) techniques are used to detect dependencies over the long range of the series. The analyses are meant to (1) exemplify the utility of time series approaches in educational research, which lacks a time series tradition, (2) discuss some time series features that seem to be particular to daily attendance rate trajectories such as the distinct downward pull coming from extreme observations, and (3) present an analytical approach to handle the important yet distinct patterns of variability that can be found in these data. The analysis also illustrates why the assumption of stability that underlies the habitual reporting of weekly, monthly and yearly averages in the educational literature is questionable, as it reveals dynamical processes (perturbation, meta-stability) that remain hidden in such summaries.

Using a traffic simulation model (VISSIM) with an emissions model (MOVES) to predict emissions from vehicles on a limited-access highway.

PubMed

Abou-Senna, Hatem; Radwan, Essam; Westerlund, Kurt; Cooper, C David

2013-07-01

The Intergovernmental Panel on Climate Change (IPCC) estimates that baseline global GHG emissions may increase 25-90% from 2000 to 2030, with carbon dioxide (CO2 emissions growing 40-110% over the same period. On-road vehicles are a major source of CO2 emissions in all the developed countries, and in many of the developing countries in the world. Similarly, several criteria air pollutants are associated with transportation, for example, carbon monoxide (CO), nitrogen oxides (NO(x)), and particulate matter (PM). Therefore, the need to accurately quantify transportation-related emissions from vehicles is essential. The new US. Environmental Protection Agency (EPA) mobile source emissions model, MOVES2010a (MOVES), can estimate vehicle emissions on a second-by-second basis, creating the opportunity to combine a microscopic traffic simulation model (such as VISSIM) with MOVES to obtain accurate results. This paper presents an examination of four different approaches to capture the environmental impacts of vehicular operations on a 10-mile stretch of Interstate 4 (I-4), an urban limited-access highway in Orlando, FL. First (at the most basic level), emissions were estimated for the entire 10-mile section "by hand" using one average traffic volume and average speed. Then three advanced levels of detail were studied using VISSIM/MOVES to analyze smaller links: average speeds and volumes (AVG), second-by-second link drive schedules (LDS), and second-by-second operating mode distributions (OPMODE). This paper analyzes how the various approaches affect predicted emissions of CO, NO(x), PM2.5, PM10, and CO2. The results demonstrate that obtaining precise and comprehensive operating mode distributions on a second-by-second basis provides more accurate emission estimates. Specifically, emission rates are highly sensitive to stop-and-go traffic and the associated driving cycles of acceleration, deceleration, and idling. Using the AVG or LDS approach may overestimate or underestimate emissions, respectively, compared to an operating mode distribution approach. Transportation agencies and researchers in the past have estimated emissions using one average speed and volume on a long stretch of roadway. With MOVES, there is an opportunity for higher precision and accuracy. Integrating a microscopic traffic simulation model (such as VISSIM) with MOVES allows one to obtain precise and accurate emissions estimates. The proposed emission rate estimation process also can be extended to gridded emissions for ozone modeling, or to localized air quality dispersion modeling, where temporal and spatial resolution of emissions is essential to predict the concentration of pollutants near roadways.

TRIO: Burst Buffer Based I/O Orchestration

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

Wang, Teng; Oral, H Sarp; Pritchard, Michael

The growing computing power on leadership HPC systems is often accompanied by ever-escalating failure rates. Checkpointing is a common defensive mechanism used by scientific applications for failure recovery. However, directly writing the large and bursty checkpointing dataset to parallel filesystem can incur significant I/O contention on storage servers. Such contention in turn degrades the raw bandwidth utilization of storage servers and prolongs the average job I/O time of concurrent applications. Recently burst buffer has been proposed as an intermediate layer to absorb the bursty I/O traffic from compute nodes to storage backend. But an I/O orchestration mechanism is still desiredmore » to efficiently move checkpointing data from bursty buffers to storage backend. In this paper, we propose a burst buffer based I/O orchestration framework, named TRIO, to intercept and reshape the bursty writes for better sequential write traffic to storage severs. Meanwhile, TRIO coordinates the flushing orders among concurrent burst buffers to alleviate the contention on storage server bandwidth. Our experimental results reveal that TRIO can deliver 30.5% higher bandwidth and reduce the average job I/O time by 37% on average for data-intensive applications in various checkpointing scenarios.« less

Distributed Sensor Fusion for Scalar Field Mapping Using Mobile Sensor Networks.

PubMed

La, Hung Manh; Sheng, Weihua

2013-04-01

In this paper, autonomous mobile sensor networks are deployed to measure a scalar field and build its map. We develop a novel method for multiple mobile sensor nodes to build this map using noisy sensor measurements. Our method consists of two parts. First, we develop a distributed sensor fusion algorithm by integrating two different distributed consensus filters to achieve cooperative sensing among sensor nodes. This fusion algorithm has two phases. In the first phase, the weighted average consensus filter is developed, which allows each sensor node to find an estimate of the value of the scalar field at each time step. In the second phase, the average consensus filter is used to allow each sensor node to find a confidence of the estimate at each time step. The final estimate of the value of the scalar field is iteratively updated during the movement of the mobile sensors via weighted average. Second, we develop the distributed flocking-control algorithm to drive the mobile sensors to form a network and track the virtual leader moving along the field when only a small subset of the mobile sensors know the information of the leader. Experimental results are provided to demonstrate our proposed algorithms.

Demand forecasting of electricity in Indonesia with limited historical data

NASA Astrophysics Data System (ADS)

Dwi Kartikasari, Mujiati; Rohmad Prayogi, Arif

2018-03-01

Demand forecasting of electricity is an important activity for electrical agents to know the description of electricity demand in future. Prediction of demand electricity can be done using time series models. In this paper, double moving average model, Holt’s exponential smoothing model, and grey model GM(1,1) are used to predict electricity demand in Indonesia under the condition of limited historical data. The result shows that grey model GM(1,1) has the smallest value of MAE (mean absolute error), MSE (mean squared error), and MAPE (mean absolute percentage error).

Acceleration and Velocity Sensing from Measured Strain

NASA Technical Reports Server (NTRS)

Pak, Chan-Gi; Truax, Roger

2016-01-01

A simple approach for computing acceleration and velocity of a structure from the strain is proposed in this study. First, deflection and slope of the structure are computed from the strain using a two-step theory. Frequencies of the structure are computed from the time histories of strain using a parameter estimation technique together with an Autoregressive Moving Average model. From deflection, slope, and frequencies of the structure, acceleration and velocity of the structure can be obtained using the proposed approach. shape sensing, fiber optic strain sensor, system equivalent reduction and expansion process.

Statistical description of turbulent transport for flux driven toroidal plasmas

NASA Astrophysics Data System (ADS)

Anderson, J.; Imadera, K.; Kishimoto, Y.; Li, J. Q.; Nordman, H.

2017-06-01

A novel methodology to analyze non-Gaussian probability distribution functions (PDFs) of intermittent turbulent transport in global full-f gyrokinetic simulations is presented. In this work, the auto-regressive integrated moving average (ARIMA) model is applied to time series data of intermittent turbulent heat transport to separate noise and oscillatory trends, allowing for the extraction of non-Gaussian features of the PDFs. It was shown that non-Gaussian tails of the PDFs from first principles based gyrokinetic simulations agree with an analytical estimation based on a two fluid model.

Average receiving scaling of the weighted polygon Koch networks with the weight-dependent walk

NASA Astrophysics Data System (ADS)

Ye, Dandan; Dai, Meifeng; Sun, Yanqiu; Shao, Shuxiang; Xie, Qi

2016-09-01

Based on the weighted Koch networks and the self-similarity of fractals, we present a family of weighted polygon Koch networks with a weight factor r(0 < r ≤ 1) . We study the average receiving time (ART) on weight-dependent walk (i.e., the walker moves to any of its neighbors with probability proportional to the weight of edge linking them), whose key step is to calculate the sum of mean first-passage times (MFPTs) for all nodes absorpt at a hub node. We use a recursive division method to divide the weighted polygon Koch networks in order to calculate the ART scaling more conveniently. We show that the ART scaling exhibits a sublinear or linear dependence on network order. Thus, the weighted polygon Koch networks are more efficient than expended Koch networks in receiving information. Finally, compared with other previous studies' results (i.e., Koch networks, weighted Koch networks), we find out that our models are more general.

Distributed parameter system coupled ARMA expansion identification and adaptive parallel IIR filtering - A unified problem statement. [Auto Regressive Moving-Average

NASA Technical Reports Server (NTRS)

Johnson, C. R., Jr.; Balas, M. J.

1980-01-01

A novel interconnection of distributed parameter system (DPS) identification and adaptive filtering is presented, which culminates in a common statement of coupled autoregressive, moving-average expansion or parallel infinite impulse response configuration adaptive parameterization. The common restricted complexity filter objectives are seen as similar to the reduced-order requirements of the DPS expansion description. The interconnection presents the possibility of an exchange of problem formulations and solution approaches not yet easily addressed in the common finite dimensional lumped-parameter system context. It is concluded that the shared problems raised are nevertheless many and difficult.

A fixed-memory moving, expanding window for obtaining scatter corrections in X-ray CT and other stochastic averages

NASA Astrophysics Data System (ADS)

Levine, Zachary H.; Pintar, Adam L.

2015-11-01

A simple algorithm for averaging a stochastic sequence of 1D arrays in a moving, expanding window is provided. The samples are grouped in bins which increase exponentially in size so that a constant fraction of the samples is retained at any point in the sequence. The algorithm is shown to have particular relevance for a class of Monte Carlo sampling problems which includes one characteristic of iterative reconstruction in computed tomography. The code is available in the CPC program library in both Fortran 95 and C and is also available in R through CRAN.

Hybrid Support Vector Regression and Autoregressive Integrated Moving Average Models Improved by Particle Swarm Optimization for Property Crime Rates Forecasting with Economic Indicators

PubMed Central

Alwee, Razana; Hj Shamsuddin, Siti Mariyam; Sallehuddin, Roselina

2013-01-01

Crimes forecasting is an important area in the field of criminology. Linear models, such as regression and econometric models, are commonly applied in crime forecasting. However, in real crimes data, it is common that the data consists of both linear and nonlinear components. A single model may not be sufficient to identify all the characteristics of the data. The purpose of this study is to introduce a hybrid model that combines support vector regression (SVR) and autoregressive integrated moving average (ARIMA) to be applied in crime rates forecasting. SVR is very robust with small training data and high-dimensional problem. Meanwhile, ARIMA has the ability to model several types of time series. However, the accuracy of the SVR model depends on values of its parameters, while ARIMA is not robust to be applied to small data sets. Therefore, to overcome this problem, particle swarm optimization is used to estimate the parameters of the SVR and ARIMA models. The proposed hybrid model is used to forecast the property crime rates of the United State based on economic indicators. The experimental results show that the proposed hybrid model is able to produce more accurate forecasting results as compared to the individual models. PMID:23766729

Scaling range of power laws that originate from fluctuation analysis

NASA Astrophysics Data System (ADS)

Grech, Dariusz; Mazur, Zygmunt

2013-05-01

We extend our previous study of scaling range properties performed for detrended fluctuation analysis (DFA) [Physica A0378-437110.1016/j.physa.2013.01.049 392, 2384 (2013)] to other techniques of fluctuation analysis (FA). The new technique, called modified detrended moving average analysis (MDMA), is introduced, and its scaling range properties are examined and compared with those of detrended moving average analysis (DMA) and DFA. It is shown that contrary to DFA, DMA and MDMA techniques exhibit power law dependence of the scaling range with respect to the length of the searched signal and with respect to the accuracy R2 of the fit to the considered scaling law imposed by DMA or MDMA methods. This power law dependence is satisfied for both uncorrelated and autocorrelated data. We find also a simple generalization of this power law relation for series with a different level of autocorrelations measured in terms of the Hurst exponent. Basic relations between scaling ranges for different techniques are also discussed. Our findings should be particularly useful for local FA in, e.g., econophysics, finances, or physiology, where the huge number of short time series has to be examined at once and wherever the preliminary check of the scaling range regime for each of the series separately is neither effective nor possible.

Weather variability, tides, and Barmah Forest virus disease in the Gladstone region, Australia.

PubMed

Naish, Suchithra; Hu, Wenbiao; Nicholls, Neville; Mackenzie, John S; McMichael, Anthony J; Dale, Pat; Tong, Shilu

2006-05-01

In this study we examined the impact of weather variability and tides on the transmission of Barmah Forest virus (BFV) disease and developed a weather-based forecasting model for BFV disease in the Gladstone region, Australia. We used seasonal autoregressive integrated moving-average (SARIMA) models to determine the contribution of weather variables to BFV transmission after the time-series data of response and explanatory variables were made stationary through seasonal differencing. We obtained data on the monthly counts of BFV cases, weather variables (e.g., mean minimum and maximum temperature, total rainfall, and mean relative humidity), high and low tides, and the population size in the Gladstone region between January 1992 and December 2001 from the Queensland Department of Health, Australian Bureau of Meteorology, Queensland Department of Transport, and Australian Bureau of Statistics, respectively. The SARIMA model shows that the 5-month moving average of minimum temperature (b=0.15, p-value<0.001) was statistically significantly and positively associated with BFV disease, whereas high tide in the current month (b=-1.03, p-value=0.04) was statistically significantly and inversely associated with it. However, no significant association was found for other variables. These results may be applied to forecast the occurrence of BFV disease and to use public health resources in BFV control and prevention.

Road traffic accidents prediction modelling: An analysis of Anambra State, Nigeria.

PubMed

Ihueze, Chukwutoo C; Onwurah, Uchendu O

2018-03-01

One of the major problems in the world today is the rate of road traffic crashes and deaths on our roads. Majority of these deaths occur in low-and-middle income countries including Nigeria. This study analyzed road traffic crashes in Anambra State, Nigeria with the intention of developing accurate predictive models for forecasting crash frequency in the State using autoregressive integrated moving average (ARIMA) and autoregressive integrated moving average with explanatory variables (ARIMAX) modelling techniques. The result showed that ARIMAX model outperformed the ARIMA (1,1,1) model generated when their performances were compared using the lower Bayesian information criterion, mean absolute percentage error, root mean square error; and higher coefficient of determination (R-Squared) as accuracy measures. The findings of this study reveal that incorporating human, vehicle and environmental related factors in time series analysis of crash dataset produces a more robust predictive model than solely using aggregated crash count. This study contributes to the body of knowledge on road traffic safety and provides an approach to forecasting using many human, vehicle and environmental factors. The recommendations made in this study if applied will help in reducing the number of road traffic crashes in Nigeria. Copyright © 2017 Elsevier Ltd. All rights reserved.

Identifying Active Travel Behaviors in Challenging Environments Using GPS, Accelerometers, and Machine Learning Algorithms

PubMed Central

Ellis, Katherine; Godbole, Suneeta; Marshall, Simon; Lanckriet, Gert; Staudenmayer, John; Kerr, Jacqueline

2014-01-01

Background: Active travel is an important area in physical activity research, but objective measurement of active travel is still difficult. Automated methods to measure travel behaviors will improve research in this area. In this paper, we present a supervised machine learning method for transportation mode prediction from global positioning system (GPS) and accelerometer data. Methods: We collected a dataset of about 150 h of GPS and accelerometer data from two research assistants following a protocol of prescribed trips consisting of five activities: bicycling, riding in a vehicle, walking, sitting, and standing. We extracted 49 features from 1-min windows of this data. We compared the performance of several machine learning algorithms and chose a random forest algorithm to classify the transportation mode. We used a moving average output filter to smooth the output predictions over time. Results: The random forest algorithm achieved 89.8% cross-validated accuracy on this dataset. Adding the moving average filter to smooth output predictions increased the cross-validated accuracy to 91.9%. Conclusion: Machine learning methods are a viable approach for automating measurement of active travel, particularly for measuring travel activities that traditional accelerometer data processing methods misclassify, such as bicycling and vehicle travel. PMID:24795875

Long-Term Prediction of Emergency Department Revenue and Visitor Volume Using Autoregressive Integrated Moving Average Model

PubMed Central

Chen, Chieh-Fan; Ho, Wen-Hsien; Chou, Huei-Yin; Yang, Shu-Mei; Chen, I-Te; Shi, Hon-Yi

2011-01-01

This study analyzed meteorological, clinical and economic factors in terms of their effects on monthly ED revenue and visitor volume. Monthly data from January 1, 2005 to September 30, 2009 were analyzed. Spearman correlation and cross-correlation analyses were performed to identify the correlation between each independent variable, ED revenue, and visitor volume. Autoregressive integrated moving average (ARIMA) model was used to quantify the relationship between each independent variable, ED revenue, and visitor volume. The accuracies were evaluated by comparing model forecasts to actual values with mean absolute percentage of error. Sensitivity of prediction errors to model training time was also evaluated. The ARIMA models indicated that mean maximum temperature, relative humidity, rainfall, non-trauma, and trauma visits may correlate positively with ED revenue, but mean minimum temperature may correlate negatively with ED revenue. Moreover, mean minimum temperature and stock market index fluctuation may correlate positively with trauma visitor volume. Mean maximum temperature, relative humidity and stock market index fluctuation may correlate positively with non-trauma visitor volume. Mean maximum temperature and relative humidity may correlate positively with pediatric visitor volume, but mean minimum temperature may correlate negatively with pediatric visitor volume. The model also performed well in forecasting revenue and visitor volume. PMID:22203886

Long-term prediction of emergency department revenue and visitor volume using autoregressive integrated moving average model.

PubMed

Chen, Chieh-Fan; Ho, Wen-Hsien; Chou, Huei-Yin; Yang, Shu-Mei; Chen, I-Te; Shi, Hon-Yi

2011-01-01

This study analyzed meteorological, clinical and economic factors in terms of their effects on monthly ED revenue and visitor volume. Monthly data from January 1, 2005 to September 30, 2009 were analyzed. Spearman correlation and cross-correlation analyses were performed to identify the correlation between each independent variable, ED revenue, and visitor volume. Autoregressive integrated moving average (ARIMA) model was used to quantify the relationship between each independent variable, ED revenue, and visitor volume. The accuracies were evaluated by comparing model forecasts to actual values with mean absolute percentage of error. Sensitivity of prediction errors to model training time was also evaluated. The ARIMA models indicated that mean maximum temperature, relative humidity, rainfall, non-trauma, and trauma visits may correlate positively with ED revenue, but mean minimum temperature may correlate negatively with ED revenue. Moreover, mean minimum temperature and stock market index fluctuation may correlate positively with trauma visitor volume. Mean maximum temperature, relative humidity and stock market index fluctuation may correlate positively with non-trauma visitor volume. Mean maximum temperature and relative humidity may correlate positively with pediatric visitor volume, but mean minimum temperature may correlate negatively with pediatric visitor volume. The model also performed well in forecasting revenue and visitor volume.

Towards a sensorimotor aesthetics of performing art.

PubMed

Calvo-Merino, B; Jola, C; Glaser, D E; Haggard, P

2008-09-01

The field of neuroaesthetics attempts to identify the brain processes underlying aesthetic experience, including but not limited to beauty. Previous neuroaesthetic studies have focussed largely on paintings and music, while performing arts such as dance have been less studied. Nevertheless, increasing knowledge of the neural mechanisms that represent the bodies and actions of others, and which contribute to empathy, make a neuroaesthetics of dance timely. Here, we present the first neuroscientific study of aesthetic perception in the context of the performing arts. We investigated brain areas whose activity during passive viewing of dance stimuli was related to later, independent aesthetic evaluation of the same stimuli. Brain activity of six naïve male subjects was measured using fMRI, while they watched 24 dance movements, and performed an irrelevant task. In a later session, participants rated each movement along a set of established aesthetic dimensions. The ratings were used to identify brain regions that were more active when viewing moves that received high average ratings than moves that received low average ratings. This contrast revealed bilateral activity in the occipital cortices and in right premotor cortex. Our results suggest a possible role of visual and sensorimotor brain areas in an automatic aesthetic response to dance. This sensorimotor response may explain why dance is widely appreciated in so many human cultures.

Hybrid support vector regression and autoregressive integrated moving average models improved by particle swarm optimization for property crime rates forecasting with economic indicators.

PubMed

Alwee, Razana; Shamsuddin, Siti Mariyam Hj; Sallehuddin, Roselina

2013-01-01

Crimes forecasting is an important area in the field of criminology. Linear models, such as regression and econometric models, are commonly applied in crime forecasting. However, in real crimes data, it is common that the data consists of both linear and nonlinear components. A single model may not be sufficient to identify all the characteristics of the data. The purpose of this study is to introduce a hybrid model that combines support vector regression (SVR) and autoregressive integrated moving average (ARIMA) to be applied in crime rates forecasting. SVR is very robust with small training data and high-dimensional problem. Meanwhile, ARIMA has the ability to model several types of time series. However, the accuracy of the SVR model depends on values of its parameters, while ARIMA is not robust to be applied to small data sets. Therefore, to overcome this problem, particle swarm optimization is used to estimate the parameters of the SVR and ARIMA models. The proposed hybrid model is used to forecast the property crime rates of the United State based on economic indicators. The experimental results show that the proposed hybrid model is able to produce more accurate forecasting results as compared to the individual models.

Statistical process control of mortality series in the Australian and New Zealand Intensive Care Society (ANZICS) adult patient database: implications of the data generating process.

PubMed

Moran, John L; Solomon, Patricia J

2013-05-24

Statistical process control (SPC), an industrial sphere initiative, has recently been applied in health care and public health surveillance. SPC methods assume independent observations and process autocorrelation has been associated with increase in false alarm frequency. Monthly mean raw mortality (at hospital discharge) time series, 1995-2009, at the individual Intensive Care unit (ICU) level, were generated from the Australia and New Zealand Intensive Care Society adult patient database. Evidence for series (i) autocorrelation and seasonality was demonstrated using (partial)-autocorrelation ((P)ACF) function displays and classical series decomposition and (ii) "in-control" status was sought using risk-adjusted (RA) exponentially weighted moving average (EWMA) control limits (3 sigma). Risk adjustment was achieved using a random coefficient (intercept as ICU site and slope as APACHE III score) logistic regression model, generating an expected mortality series. Application of time-series to an exemplar complete ICU series (1995-(end)2009) was via Box-Jenkins methodology: autoregressive moving average (ARMA) and (G)ARCH ((Generalised) Autoregressive Conditional Heteroscedasticity) models, the latter addressing volatility of the series variance. The overall data set, 1995-2009, consisted of 491324 records from 137 ICU sites; average raw mortality was 14.07%; average(SD) raw and expected mortalities ranged from 0.012(0.113) and 0.013(0.045) to 0.296(0.457) and 0.278(0.247) respectively. For the raw mortality series: 71 sites had continuous data for assessment up to or beyond lag40 and 35% had autocorrelation through to lag40; and of 36 sites with continuous data for ≥ 72 months, all demonstrated marked seasonality. Similar numbers and percentages were seen with the expected series. Out-of-control signalling was evident for the raw mortality series with respect to RA-EWMA control limits; a seasonal ARMA model, with GARCH effects, displayed white-noise residuals which were in-control with respect to EWMA control limits and one-step prediction error limits (3SE). The expected series was modelled with a multiplicative seasonal autoregressive model. The data generating process of monthly raw mortality series at the ICU level displayed autocorrelation, seasonality and volatility. False-positive signalling of the raw mortality series was evident with respect to RA-EWMA control limits. A time series approach using residual control charts resolved these issues.

Industrial Based Migration in India. A Case Study of Dumdum "Dunlop Industrial Zone"

NASA Astrophysics Data System (ADS)

Das, Biplab; Bandyopadhyay, Aditya; Sen, Jayashree

2012-10-01

Migration is a very important part in our present society. Basically Millions of people moved during the industrial revolution. Some simply moved from a village to a town in the hope of finding work whilst others moved from one country to another in search of a better way of life. The main reason for moving home during the 19th century was to find work. On one hand this involved migration from the countryside to the growing industrial cities, on the other it involved rates of migration, emigration, and the social changes that were drastically affecting factors such as marriage,birth and death rates. These social changes taking place as a result of capitalism had far ranging affects, such as lowering the average age of marriage and increasing the size of the average family.Migration was not just people moving out of the country, it also invloved a lot of people moving into Britain. In the 1840's Ireland suffered a terrible famine. Faced with a massive cost of feeding the starving population many local landowners paid for labourers to emigrate.There was a shift away from agriculturally based rural dwelling towards urban habitation to meet the mass demand for labour that new industry required. There became great regional differences in population levels and in the structure of their demography. This was due to rates of migration, emigration, and the social changes that were drastically affecting factors such as marriage, birth and death rates. These social changes taking place as a result of capitalism had far ranging affects, such as lowering the average age of marriage and increasing the size of the average family. There is n serious disagreement as to the extent of the population changes that occurred but one key question that always arouses debate is that of whether an expanding population resulted in economic growth or vice versa, i.e. was industrialization a catalyst for population growth? A clear answer is difficult to decipher as the two variables are so closely and fundamentally interlinked, but it seems that both factors provided impetus for each otherís take off. If anything, population and economic growth were complimentary towards one another rather than simply being causative factors.

Age Tracers and Residence Time in the Hudson River Estuary

NASA Astrophysics Data System (ADS)

Nadell, S. A.; Geyer, W. R.; Wang, T.

2016-02-01

The Hudson River is one of the most nutrient loaded rivers in the country, however phytoplankton bloom do not occur, possibly as a result of how quickly water moves though the Hudson River estuary. Slower water residence times may then allow for significant phytoplankton growth. Water age and residence time, which are compliments of one another under stead-state conditions, are important factors in determining where phytoplankton move and how long they spend within a favorable portion of the estuary. This research involved introducing a freshwater and saltwater age tracer into the Regional Ocean Modeling System (ROMS) for the Hudson River estuary domain to observe the distribution of ages within the spring-neap tidal cycle and across different river discharge rates. These discharge rates represented average (500 m3/s), relatively high (1000 m3/s), and relatively low (200 m3/s) river flow conditions for the Hudson River. Saltwater age followed a distribution similar to salinity, while freshwater age distribution mostly represented river transit time. Under steady state conditions, combined freshwater and saltwater age may be used to calculate a rough estimate of estuary residence time. The results show that the residence time of the full estuary appears to be at greater than the doubling time of phytoplankton for all discharge rates and by over five days for even the relatively high discharge case. This leads to the conclusion that other estuary factors, including light availability and salinity, may be more important for limiting phytoplankton growth than residence time.

The Micromechanics of the Moving Contact Line

NASA Technical Reports Server (NTRS)

Han, Minsub; Lichter, Seth; Lin, Chih-Yu; Perng, Yeong-Yan

1996-01-01

The proposed research is divided into three components concerned with molecular structure, molecular orientation, and continuum averages of discrete systems. In the experimental program, we propose exploring how changes in interfacial molecular structure generate contact line motion. Rather than rely on the electrostatic and electrokinetic fields arising from the molecules themselves, we augment their interactions by an imposed field at the solid/liquid interface. By controling the field, we can manipulate the molecular structure at the solid/liquid interface. In response to controlled changes in molecular structure, we observe the resultant contact line motion. In the analytical portion of the proposed research we seek to formulate a system of equations governing fluid motion which accounts for the orientation of fluid molecules. In preliminary work, we have focused on describing how molecular orientation affects the forces generated at the moving contact line. Ideally, as assumed above, the discrete behavior of molecules can be averaged into a continuum theory. In the numerical portion of the proposed research, we inquire whether the contact line region is, in fact, large enough to possess a well-defined average. Additionally, we ask what types of behavior distinguish discrete systems from continuum systems. Might the smallness of the contact line region, in itself, lead to behavior different from that in the bulk? Taken together, our proposed research seeks to identify and accurately account for some of the molecular dynamics of the moving contact line, and attempts to formulate a description from which one can compute the forces at the moving contact line.

Random walker in temporally deforming higher-order potential forces observed in a financial crisis.

PubMed

Watanabe, Kota; Takayasu, Hideki; Takayasu, Misako

2009-11-01

Basic peculiarities of market price fluctuations are known to be well described by a recently developed random-walk model in a temporally deforming quadratic potential force whose center is given by a moving average of past price traces [M. Takayasu, T. Mizuno, and H. Takayasu, Physica A 370, 91 (2006)]. By analyzing high-frequency financial time series of exceptional events, such as bubbles and crashes, we confirm the appearance of higher-order potential force in the markets. We show statistical significance of its existence by applying the information criterion. This time series analysis is expected to be applied widely for detecting a nonstationary symptom in random phenomena.

Vortex reconnection rate, and loop birth rate, for a random wavefield

NASA Astrophysics Data System (ADS)

Hannay, J. H.

2017-04-01

A time dependent, complex scalar wavefield in three dimensions contains curved zero lines, wave ‘vortices’, that move around. From time to time pairs of these lines contact each other and ‘reconnect’ in a well studied manner, and at other times tiny loops of new line appear from nowhere (births) and grow, or the reverse, existing loops shrink and disappear (deaths). These three types are known to be the only generic events. Here the average rate of their occurrences per unit volume is calculated exactly for a Gaussian random wavefield that has isotropic, stationary statistics, arising from a superposition of an infinity of plane waves in different directions. A simplifying ‘axis fixing’ technique is introduced to achieve this. The resulting formulas are proportional to the standard deviation of angular frequencies, and depend in a simple way on the second and fourth moments of the power spectrum of the plane waves. Reconnections turn out to be more common than births and deaths combined. As an expository preliminary, the case of two dimensions, where the vortices are points, is studied and the average rate of pair creation (and likewise destruction) per unit area is calculated.

A univariate model of river water nitrate time series

NASA Astrophysics Data System (ADS)

Worrall, F.; Burt, T. P.

1999-01-01

Four time series were taken from three catchments in the North and South of England. The sites chosen included two in predominantly agricultural catchments, one at the tidal limit and one downstream of a sewage treatment works. A time series model was constructed for each of these series as a means of decomposing the elements controlling river water nitrate concentrations and to assess whether this approach could provide a simple management tool for protecting water abstractions. Autoregressive (AR) modelling of the detrended and deseasoned time series showed a "memory effect". This memory effect expressed itself as an increase in the winter-summer difference in nitrate levels that was dependent upon the nitrate concentration 12 or 6 months previously. Autoregressive moving average (ARMA) modelling showed that one of the series contained seasonal, non-stationary elements that appeared as an increasing trend in the winter-summer difference. The ARMA model was used to predict nitrate levels and predictions were tested against data held back from the model construction process - predictions gave average percentage errors of less than 10%. Empirical modelling can therefore provide a simple, efficient method for constructing management models for downstream water abstraction.

The Preemptive Stocker Dispatching Rule of Automatic Material Handling System in 300 mm Semiconductor Manufacturing Factories

NASA Astrophysics Data System (ADS)

Wang, C. N.; Lin, H. S.; Hsu, H. P.; Wang, Yen-Hui; Chang, Y. P.

2016-04-01

The integrated circuit (IC) manufacturing industry is one of the biggest output industries in this century. The 300mm wafer fabs is the major fab size of this industry. The automatic material handling system (AMHS) has become one of the most concerned issues among semiconductor manufacturers. The major lot delivery of 300mm fabs is used overhead hoist transport (OHT). The traffic jams are happened frequently due to the wide variety of products and big amount of OHTs moving in the fabs. The purpose of this study is to enhance the delivery performance of automatic material handling and reduce the delay and waiting time of product transportation for both hot lots and normal lots. Therefore, this study proposes an effective OHT dispatching rule: preemptive stocker dispatching (PSD). Simulation experiments are conducted and one of the best differentiated preemptive rule, differentiated preemptive dispatching (DPD), is used for comparison. Compared with DPD, The results indicated that PSD rule can reduce average variable delivery time of normal lots by 13.15%, decreasing average variable delivery time of hot lots by 17.67%. Thus, the PSD rule can effectively reduce the delivery time and enhance productivity in 300 mm wafer fabs.

Real Time Search Algorithm for Observation Outliers During Monitoring Engineering Constructions

NASA Astrophysics Data System (ADS)

Latos, Dorota; Kolanowski, Bogdan; Pachelski, Wojciech; Sołoducha, Ryszard

2017-12-01

Real time monitoring of engineering structures in case of an emergency of disaster requires collection of a large amount of data to be processed by specific analytical techniques. A quick and accurate assessment of the state of the object is crucial for a probable rescue action. One of the more significant evaluation methods of large sets of data, either collected during a specified interval of time or permanently, is the time series analysis. In this paper presented is a search algorithm for those time series elements which deviate from their values expected during monitoring. Quick and proper detection of observations indicating anomalous behavior of the structure allows to take a variety of preventive actions. In the algorithm, the mathematical formulae used provide maximal sensitivity to detect even minimal changes in the object's behavior. The sensitivity analyses were conducted for the algorithm of moving average as well as for the Douglas-Peucker algorithm used in generalization of linear objects in GIS. In addition to determining the size of deviations from the average it was used the so-called Hausdorff distance. The carried out simulation and verification of laboratory survey data showed that the approach provides sufficient sensitivity for automatic real time analysis of large amount of data obtained from different and various sensors (total stations, leveling, camera, radar).

Distributed and Dynamic Neural Encoding of Multiple Motion Directions of Transparently Moving Stimuli in Cortical Area MT

PubMed Central

Xiao, Jianbo

2015-01-01

Segmenting visual scenes into distinct objects and surfaces is a fundamental visual function. To better understand the underlying neural mechanism, we investigated how neurons in the middle temporal cortex (MT) of macaque monkeys represent overlapping random-dot stimuli moving transparently in slightly different directions. It has been shown that the neuronal response elicited by two stimuli approximately follows the average of the responses elicited by the constituent stimulus components presented alone. In this scheme of response pooling, the ability to segment two simultaneously presented motion directions is limited by the width of the tuning curve to motion in a single direction. We found that, although the population-averaged neuronal tuning showed response averaging, subgroups of neurons showed distinct patterns of response tuning and were capable of representing component directions that were separated by a small angle—less than the tuning width to unidirectional stimuli. One group of neurons preferentially represented the component direction at a specific side of the bidirectional stimuli, weighting one stimulus component more strongly than the other. Another group of neurons pooled the component responses nonlinearly and showed two separate peaks in their tuning curves even when the average of the component responses was unimodal. We also show for the first time that the direction tuning of MT neurons evolved from initially representing the vector-averaged direction of slightly different stimuli to gradually representing the component directions. Our results reveal important neural processes underlying image segmentation and suggest that information about slightly different stimulus components is computed dynamically and distributed across neurons. SIGNIFICANCE STATEMENT Natural scenes often contain multiple entities. The ability to segment visual scenes into distinct objects and surfaces is fundamental to sensory processing and is crucial for generating the perception of our environment. Because cortical neurons are broadly tuned to a given visual feature, segmenting two stimuli that differ only slightly is a challenge for the visual system. In this study, we discovered that many neurons in the visual cortex are capable of representing individual components of slightly different stimuli by selectively and nonlinearly pooling the responses elicited by the stimulus components. We also show for the first time that the neural representation of individual stimulus components developed over a period of ∼70–100 ms, revealing a dynamic process of image segmentation. PMID:26658869

A comparison of moving object detection methods for real-time moving object detection

NASA Astrophysics Data System (ADS)

Roshan, Aditya; Zhang, Yun

2014-06-01

Moving object detection has a wide variety of applications from traffic monitoring, site monitoring, automatic theft identification, face detection to military surveillance. Many methods have been developed across the globe for moving object detection, but it is very difficult to find one which can work globally in all situations and with different types of videos. The purpose of this paper is to evaluate existing moving object detection methods which can be implemented in software on a desktop or laptop, for real time object detection. There are several moving object detection methods noted in the literature, but few of them are suitable for real time moving object detection. Most of the methods which provide for real time movement are further limited by the number of objects and the scene complexity. This paper evaluates the four most commonly used moving object detection methods as background subtraction technique, Gaussian mixture model, wavelet based and optical flow based methods. The work is based on evaluation of these four moving object detection methods using two (2) different sets of cameras and two (2) different scenes. The moving object detection methods have been implemented using MatLab and results are compared based on completeness of detected objects, noise, light change sensitivity, processing time etc. After comparison, it is observed that optical flow based method took least processing time and successfully detected boundary of moving objects which also implies that it can be implemented for real-time moving object detection.

Use of spatiotemporal characteristics of ambient PM2.5 in rural South India to infer local versus regional contributions.

PubMed

Kumar, M Kishore; Sreekanth, V; Salmon, Maëlle; Tonne, Cathryn; Marshall, Julian D

2018-08-01

This study uses spatiotemporal patterns in ambient concentrations to infer the contribution of regional versus local sources. We collected 12 months of monitoring data for outdoor fine particulate matter (PM 2.5 ) in rural southern India. Rural India includes more than one-tenth of the global population and annually accounts for around half a million air pollution deaths, yet little is known about the relative contribution of local sources to outdoor air pollution. We measured 1-min averaged outdoor PM 2.5 concentrations during June 2015-May 2016 in three villages, which varied in population size, socioeconomic status, and type and usage of domestic fuel. The daily geometric-mean PM 2.5 concentration was ∼30 μg m -3 (geometric standard deviation: ∼1.5). Concentrations exceeded the Indian National Ambient Air Quality standards (60 μg m -3 ) during 2-5% of observation days. Average concentrations were ∼25 μg m -3 higher during winter than during monsoon and ∼8 μg m -3 higher during morning hours than the diurnal average. A moving average subtraction method based on 1-min average PM 2.5 concentrations indicated that local contributions (e.g., nearby biomass combustion, brick kilns) were greater in the most populated village, and that overall the majority of ambient PM 2.5 in our study was regional, implying that local air pollution control strategies alone may have limited influence on local ambient concentrations. We compared the relatively new moving average subtraction method against a more established approach. Both methods broadly agree on the relative contribution of local sources across the three sites. The moving average subtraction method has broad applicability across locations. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

The influence of trading volume on market efficiency: The DCCA approach

NASA Astrophysics Data System (ADS)

Sukpitak, Jessada; Hengpunya, Varagorn

2016-09-01

For a single market, the cross-correlation between market efficiency and trading volume, which is an indicator of market liquidity, is attentively analysed. The study begins with creating time series of market efficiency by applying time-varying Hurst exponent with one year sliding window to daily closing prices. The time series of trading volume corresponding to the same time period used for the market efficiency is derived from one year moving average of daily trading volume. Subsequently, the detrended cross-correlation coefficient is employed to quantify the degree of cross-correlation between the two time series. It was found that values of cross-correlation coefficient of all considered stock markets are close to 0 and are clearly out of range in which correlation being considered significant in almost every time scale. Obtained results show that the market liquidity in term of trading volume hardly has effect on the market efficiency.

Breeding ecology of the redhead duck in western Montana

USGS Publications Warehouse

Lokemoen, J.T.

1966-01-01

The habits of the redhead duck (Aythya americana) were studied in the Flathead Valley of western Montana in 1960 and 1961 to determine their habitat preferences in this pothole breeding ground. The 2,600-acre study area, surrounding the Ninepipe Reservoir, contained 686 potholes. Redheads usually were paired by the time they arrived on the study area in March. The average density of redhead breeding pairs was 25 pairs per square mile. For all spring activities except nesting, the birds used large, deep, open potholes or breeding-pair potholes. The several breeding-pair potholes and the nesting pothole utilized by the pair comprised their home range. Starting in late April, the pairs moved about the home range as the hens selected nesting sites, usually in the dense emergent vegetation of small, shallow potholes. Hard-stem bulrush (Scirpus acutus) and cat-tail (Typha latifolia) were preferred nesting cover. Redhead nesting success was only 15 percent, a low rate apparently caused by degenerate nesting behavior complicated by high redhead density, a lack of suitable nest hosts, and certain habitat deficiencies. By late June most drakes and unsuccessful hens had moved from the potholes to nearby reservoirs. All successful hens led their newly hatched broods from the nesting potholes to larger brood potholes and many eventually moved to the reservoir. By mid-July virtually all redheads had moved from the potholes to the reservoirs, where they remained until fall migration.

Plasmoid growth and expulsion revealed by two-point ARTEMIS observations

NASA Astrophysics Data System (ADS)

Li, S.; Angelopoulos, V.; Runov, A.; kiehas, S.

2012-12-01

On 12 October 2011, the two ARTEMIS probes, in lunar orbit ~7 RE north of the neutral sheet, sequentially observed a tailward-moving, expanding plasmoid. Their observations reveal a multi-layered plasma sheet composed of tailward-flowing hot plasma within the plasmoid proper enshrouded by earthward-flowing, less energetic plasma. Prior observations of similar earthward flow structures ahead of or behind plasmoids have been interpreted as earthward outflow from a continuously active distant-tail neutral line (DNL) opposite an approaching plasmoid. However, no evidence of active DNL reconnection was observed by the probes as they traversed the plasmoid's leading and trailing edges, penetrating to slightly above its core. We suggest an alternate interpretation: compression of the ambient plasma by the tailward-moving plasmoid propels the plasma lobeward and earthward, i.e., over and above the plasmoid. Using the propagation velocity obtained from timing analysis, we estimate the average plasmoid size to be 9 RE and its expansion rate to be ~ 7 RE/min at the observation locations. The velocity inside the plasmoid proper was found to be non-uniform; the core likely moves as fast as 500 km/s, yet the outer layers move more slowly (and reverse direction), possibly resulting in the observed expansion. The absence of lobe reconnection, in particular on the earthward side, suggests that plasmoid formation and expulsion result from closed plasma sheet field line reconnection.

Aerial hawking and landing: approach behaviour in Natterer's bats, Myotis nattereri (Kuhl 1818).

PubMed

Melcón, Mariana L; Denzinger, Annette; Schnitzler, Hans-Ulrich

2007-12-01

We compared the flight and echolocation behaviour of a vespertilionid bat (Myotis nattereri) approaching a large stationary or a small moving target. Bats were trained to either land on a landing grid or to catch a moving tethered mealworm. When closing in on these two targets, the bats emitted groups of sounds with increasing number of signals and decreasing pulse interval and duration. When pursuing the mealworm, the approach phase always ended with a terminal group consisting of buzz I and buzz II. When landing, the bats emitted either a terminal group consisting of buzz I alone, with one or two extra pulses, or a group consisting of buzz I and buzz II. In all situations, buzz I ended on average between 47-63 ms prior to contact with the target of interest, which is approximately the reaction time of bats. Therefore, the information collected in buzz II does not guide the bats to the target. The relevant part of the approach phase to reach the target ends with buzz I. The basic sound pattern of this part is rather similar and independent of whether the bats approach the large stationary or the small moving target.

An analysis of underlying factors for seasonal variation in gonorrhoea in India: a 6-year statistical assessment.

PubMed

Kakran, M; Bala, M; Singh, V

2015-01-01

A statistical assessment of a disease is often necessary before resources can be allocated to any control programme. No literature on seasonal trends of gonorrhoea is available from India. The objectives were (1) to determine, if any, seasonal trends were present in India (2) to describe factors contributing to seasonality of gonorrhoea (3) to formulate approaches for gonorrhoea control at the national level. Seasonal indices for gonorrhoea were calculated quarterly in terms of a seasonal index between 2005 and 2010. Ratio-to-moving average method was used to determine the seasonal variation. The original data values in the time-series were expressed as percentages of moving averages. Results were also analyzed by second statistical method i.e. seasonal subseries plot. The seasonally adjusted average for culture-positive gonorrhoea cases was highest in the second quarter (128.61%) followed by third quarter (108.48%) while a trough was observed in the first (96.05%) and last quarter (64.85%). The second quarter peak was representative of summer vacations in schools and colleges. Moreover, April is the harvesting month followed by celebrations and social gatherings. Both these factors are associated with increased sexual activity and partner change. A trough in first and last quarter was indicative of festival season and winter leading to less patients reporting to the hospital. The findings highlight the immediate need to strengthen sexual health education among young people in schools and colleges and education on risk-reduction practices especially at crucial points in the calendar year for effective gonorrhoea control.

Noise is the new signal: Moving beyond zeroth-order geomorphology (Invited)

NASA Astrophysics Data System (ADS)

Jerolmack, D. J.

2010-12-01

The last several decades have witnessed a rapid growth in our understanding of landscape evolution, led by the development of geomorphic transport laws - time- and space-averaged equations relating mass flux to some physical process(es). In statistical mechanics this approach is called mean field theory (MFT), in which complex many-body interactions are replaced with an external field that represents the average effect of those interactions. Because MFT neglects all fluctuations around the mean, it has been described as a zeroth-order fluctuation model. The mean field approach to geomorphology has enabled the development of landscape evolution models, and led to a fundamental understanding of many landform patterns. Recent research, however, has highlighted two limitations of MFT: (1) The integral (averaging) time and space scales in geomorphic systems are sometimes poorly defined and often quite large, placing the mean field approximation on uncertain footing, and; (2) In systems exhibiting fractal behavior, an integral scale does not exist - e.g., properties like mass flux are scale-dependent. In both cases, fluctuations in sediment transport are non-negligible over the scales of interest. In this talk I will synthesize recent experimental and theoretical work that confronts these limitations. Discrete element models of fluid and grain interactions show promise for elucidating transport mechanics and pattern-forming instabilities, but require detailed knowledge of micro-scale processes and are computationally expensive. An alternative approach is to begin with a reasonable MFT, and then add higher-order terms that capture the statistical dynamics of fluctuations. In either case, moving beyond zeroth-order geomorphology requires a careful examination of the origins and structure of transport “noise”. I will attempt to show how studying the signal in noise can both reveal interesting new physics, and also help to formalize the applicability of geomorphic transport laws. Flooding on an experimental alluvial fan. Intensity is related to the cumulative amount of time flow has visited an area of the fan over the experiment. Dark areas represent an emergent channel network resulting from stochastic migration of river channels.

Are Math Grades Cyclical?

ERIC Educational Resources Information Center

Adams, Gerald J.; Dial, Micah

1998-01-01

The cyclical nature of mathematics grades was studied for a cohort of elementary school students from a large metropolitan school district in Texas over six years (average cohort size of 8495). The study used an autoregressive integrated moving average (ARIMA) model. Results indicate that grades do exhibit a significant cyclical pattern. (SLD)

Estimation of inhaled airborne particle number concentration by subway users in Seoul, Korea.

PubMed

Kim, Minhae; Park, Sechan; Namgung, Hyeong-Gyu; Kwon, Soon-Bark

2017-12-01

Exposure to airborne particulate matter (PM) causes several diseases in the human body. The smaller particles, which have relatively large surface areas, are actually more harmful to the human body since they can penetrate deeper parts of the lungs or become secondary pollutants by bonding with other atmospheric pollutants, such as nitrogen oxides. The purpose of this study is to present the number of PM inhaled by subway users as a possible reference material for any analysis of the hazards to the human body arising from the inhalation of such PM. Two transfer stations in Seoul, Korea, which have the greatest number of users, were selected for this study. For 0.3-0.422 μm PM, particle number concentration (PNC) was highest outdoors but decreased as the tester moved deeper underground. On the other hand, the PNC between 1 and 10 μm increased as the tester moved deeper underground and showed a high number concentration inside the subway train as well. An analysis of the particles to which subway users are actually exposed to (inhaled particle number), using particle concentration at each measurement location, the average inhalation rate of an adult, and the average stay time at each location, all showed that particles sized 0.01-0.422 μm are mostly inhaled from the outdoor air whereas particles sized 1-10 μm are inhaled as the passengers move deeper underground. Based on these findings, we expect that the inhaled particle number of subway users can be used as reference data for an evaluation of the hazards to health caused by PM inhalation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Passenger Flow Forecasting Research for Airport Terminal Based on SARIMA Time Series Model

NASA Astrophysics Data System (ADS)

Li, Ziyu; Bi, Jun; Li, Zhiyin

2017-12-01

Based on the data of practical operating of Kunming Changshui International Airport during2016, this paper proposes Seasonal Autoregressive Integrated Moving Average (SARIMA) model to predict the passenger flow. This article not only considers the non-stationary and autocorrelation of the sequence, but also considers the daily periodicity of the sequence. The prediction results can accurately describe the change trend of airport passenger flow and provide scientific decision support for the optimal allocation of airport resources and optimization of departure process. The result shows that this model is applicable to the short-term prediction of airport terminal departure passenger traffic and the average error ranges from 1% to 3%. The difference between the predicted and the true values of passenger traffic flow is quite small, which indicates that the model has fairly good passenger traffic flow prediction ability.

Rapid range shifts of species associated with high levels of climate warming.

PubMed

Chen, I-Ching; Hill, Jane K; Ohlemüller, Ralf; Roy, David B; Thomas, Chris D

2011-08-19

The distributions of many terrestrial organisms are currently shifting in latitude or elevation in response to changing climate. Using a meta-analysis, we estimated that the distributions of species have recently shifted to higher elevations at a median rate of 11.0 meters per decade, and to higher latitudes at a median rate of 16.9 kilometers per decade. These rates are approximately two and three times faster than previously reported. The distances moved by species are greatest in studies showing the highest levels of warming, with average latitudinal shifts being generally sufficient to track temperature changes. However, individual species vary greatly in their rates of change, suggesting that the range shift of each species depends on multiple internal species traits and external drivers of change. Rapid average shifts derive from a wide diversity of responses by individual species.

Evidence of redshifts in the average solar line profiles of C IV and Si IV from OSO-8 observations

NASA Technical Reports Server (NTRS)

Roussel-Dupre, D.; Shine, R. A.

1982-01-01

Line profiles of C IV and Si V obtained by the Colorado spectrometer on OSO-8 are presented. It is shown that the mean profiles are redshifted with a magnitude varying from 6-20 km/s, and with a mean of 12 km/s. An apparent average downflow of material in the 50,000-100,000 K temperature range is measured. The redshifts are observed in the line center positions of spatially and temporally averaged profiles and are measured either relative to chromospheric Si I lines or from a comparison of sun center and limb profiles. The observations of 6-20 km/s redshifts place constraints on the mechanisms that dominate EUV line emission since it requires a strong weighting of the emission in regions of downward moving material, and since there is little evidence for corresponding upward moving materials in these lines.

Alteration of Box-Jenkins methodology by implementing genetic algorithm method

NASA Astrophysics Data System (ADS)

Ismail, Zuhaimy; Maarof, Mohd Zulariffin Md; Fadzli, Mohammad

2015-02-01

A time series is a set of values sequentially observed through time. The Box-Jenkins methodology is a systematic method of identifying, fitting, checking and using integrated autoregressive moving average time series model for forecasting. Box-Jenkins method is an appropriate for a medium to a long length (at least 50) time series data observation. When modeling a medium to a long length (at least 50), the difficulty arose in choosing the accurate order of model identification level and to discover the right parameter estimation. This presents the development of Genetic Algorithm heuristic method in solving the identification and estimation models problems in Box-Jenkins. Data on International Tourist arrivals to Malaysia were used to illustrate the effectiveness of this proposed method. The forecast results that generated from this proposed model outperformed single traditional Box-Jenkins model.

Self-Trapping Self-Repelling Random Walks

NASA Astrophysics Data System (ADS)

Grassberger, Peter

2017-10-01

Although the title seems self-contradictory, it does not contain a misprint. The model we study is a seemingly minor modification of the "true self-avoiding walk" model of Amit, Parisi, and Peliti in two dimensions. The walks in it are self-repelling up to a characteristic time T* (which depends on various parameters), but spontaneously (i.e., without changing any control parameter) become self-trapping after that. For free walks, T* is astronomically large, but on finite lattices the transition is easily observable. In the self-trapped regime, walks are subdiffusive and intermittent, spending longer and longer times in small areas until they escape and move rapidly to a new area. In spite of this, these walks are extremely efficient in covering finite lattices, as measured by average cover times.

Water quality and hydrology in the Fort Belvoir area, Virginia, 1954-55

USGS Publications Warehouse

Durfor, Charles N.

1961-01-01

This report summarizes the results of an investigation of water quality and hydrology in the Fort Belvoir, Va., area for the period August 1954 to September 1955. It summarizes and evaluates information about the water resources of this area that are pertinent to the choice of location and operation of an Army nuclear power reactor. The quantity, quality, nature, and use of the local water that might be affected by the location and operation of a reactor in the area were subjects of investigation. Variations in the quality of the water caused by variation in streamflow, tidal effects, and pollution were important facets of the investigation. During extended periods of low streamflow in the Potomac River (usually in the late summer months), salty water moves upstream from Chesapeake Bay and increases the dissolved solids content of the surface waters adjacent to Fort Belvoir. When the streamflow is low the concentration of dissolved solids in the water near the river bottom exceeds that near the surface. The waters in Gunston Cove usually contain more dissolved oxygen than those in the Potomac River. During the summer, the content of dissolved oxygen in the cove waters frequently exceeds 100 percent of saturation. Surface floats that were released on a flood tide in Gunston Cove moved toward the inner portion of the cove in the same direction as the wind and the tide. The maximum average velocity of these floats was 0.65 feet per second. On an ebb tide, many surface floats that were released in Gunston Cove moved toward the inner portion of the cove in the direction of the wind, in opposition to the direction of the tidal movement. Floats released near the mouth of the cove on the same tide, moved with the tide out of the cove through a narrow pass at the end of a submerged sandbar extending from the Fort Belvoir shoreline. The maximum average velocity of the floats in the pass on this ebb tide was 0.85 feet per second. Measurements of subsurface flow direction indicate that the water in the deeper part of Gunston Cove tended to move toward Accotink Bay on the flood tide and out of the cove into the Potomac River on the ebb tide. The water 150-500 feet offshore from the reactor site tended to move toward Accotink Bay on the flood tide and toward Pohick Bay on the ebb tide, whereas waters 30 feet from the Fort Belvoir shoreline tended to move counterclockwise during part of the time. In Gunston Cove the maximum measured flood velocity was 0.48 feet-per second, and the maximum ebb velocity was 0.71 per second. During periods of low streamflow, pollutants that enter the Potomac River at Fort Belvoir may move as much as 5.5 miles upstream on a flood tide and as much as 5 miles downstream on an ebb tide. At higher flow rates movement of pollutants is less upstream and greater downstream. The time required to flush the 10-mile reach of the Potomac River adjacent to Fort Belvoir varies from a day or two at high-flow rates to several weeks at low-flow rates.

Supervision by a technically qualified surgeon affects the proficiency and safety of laparoscopic colectomy performed by novice surgeons.

PubMed

Ichikawa, Nobuki; Homma, Shigenori; Yoshida, Tadashi; Ohno, Yosuke; Kawamura, Hideki; Kamiizumi, You; Iijima, Hiroaki; Taketomi, Akinobu

2018-01-01

The use of laparoscopic colectomy is becoming widespread and acquisition of its technique is challenging. In this study, we investigated whether supervision by a technically qualified surgeon affects the proficiency and safety of laparoscopic colectomy performed by novice surgeons. The outcomes of 23 right colectomies and 19 high anterior resections for colon cancers performed by five novice surgeons (experience level of <10 cases) between 2014 and 2016 were assessed. A laparoscopic surgeon qualified by the Endoscopic Surgical Skill Qualification System (Japan Society for Endoscopic Surgery) participated in surgeries as the teaching assistant. In the right colectomy group, one patient (4.3%) required conversion to open surgery and postoperative morbidities occurred in two cases (8.6%). The operative time moving average gradually decreased from 216 to 150 min, and the blood loss decreased from 128 to 28 mL. In the CUSUM charts, the values for operative time decreased continuously after the 18th case, as compared to the Japanese standard. The values for blood loss also plateaued after the 18th case. In the high anterior resection group, one patient (5.2%) required conversion to open surgery and no postoperative complication occurred in any patient. The operative time moving average gradually decreased from 258 to 228 min, and the blood loss decreased from 33 to 18 mL. The CUSUM charts showed that the values of operative time plateaued after the 18th case, as compared to the Japanese standard. In the CUSUM chart for blood loss, no distinguishing peak or trend was noted. Supervision by a technically qualified surgeon affects the proficiency and safety of laparoscopic colectomy performed by novice surgeons. The trainee's learning curve in this study represents successful mentoring by the laparoscopic surgeon qualified by the Endoscopic Surgical Skill Qualification System.

Combined non-parametric and parametric approach for identification of time-variant systems

NASA Astrophysics Data System (ADS)

Dziedziech, Kajetan; Czop, Piotr; Staszewski, Wieslaw J.; Uhl, Tadeusz

2018-03-01

Identification of systems, structures and machines with variable physical parameters is a challenging task especially when time-varying vibration modes are involved. The paper proposes a new combined, two-step - i.e. non-parametric and parametric - modelling approach in order to determine time-varying vibration modes based on input-output measurements. Single-degree-of-freedom (SDOF) vibration modes from multi-degree-of-freedom (MDOF) non-parametric system representation are extracted in the first step with the use of time-frequency wavelet-based filters. The second step involves time-varying parametric representation of extracted modes with the use of recursive linear autoregressive-moving-average with exogenous inputs (ARMAX) models. The combined approach is demonstrated using system identification analysis based on the experimental mass-varying MDOF frame-like structure subjected to random excitation. The results show that the proposed combined method correctly captures the dynamics of the analysed structure, using minimum a priori information on the model.

Neural Control of a Tracking Task via Attention-Gated Reinforcement Learning for Brain-Machine Interfaces.

PubMed

Wang, Yiwen; Wang, Fang; Xu, Kai; Zhang, Qiaosheng; Zhang, Shaomin; Zheng, Xiaoxiang

2015-05-01

Reinforcement learning (RL)-based brain machine interfaces (BMIs) enable the user to learn from the environment through interactions to complete the task without desired signals, which is promising for clinical applications. Previous studies exploited Q-learning techniques to discriminate neural states into simple directional actions providing the trial initial timing. However, the movements in BMI applications can be quite complicated, and the action timing explicitly shows the intention when to move. The rich actions and the corresponding neural states form a large state-action space, imposing generalization difficulty on Q-learning. In this paper, we propose to adopt attention-gated reinforcement learning (AGREL) as a new learning scheme for BMIs to adaptively decode high-dimensional neural activities into seven distinct movements (directional moves, holdings and resting) due to the efficient weight-updating. We apply AGREL on neural data recorded from M1 of a monkey to directly predict a seven-action set in a time sequence to reconstruct the trajectory of a center-out task. Compared to Q-learning techniques, AGREL could improve the target acquisition rate to 90.16% in average with faster convergence and more stability to follow neural activity over multiple days, indicating the potential to achieve better online decoding performance for more complicated BMI tasks.

What triggers catch-up saccades during visual tracking?

PubMed

de Brouwer, Sophie; Yuksel, Demet; Blohm, Gunnar; Missal, Marcus; Lefèvre, Philippe

2002-03-01

When tracking moving visual stimuli, primates orient their visual axis by combining two kinds of eye movements, smooth pursuit and saccades, that have very different dynamics. Yet, the mechanisms that govern the decision to switch from one type of eye movement to the other are still poorly understood, even though they could bring a significant contribution to the understanding of how the CNS combines different kinds of control strategies to achieve a common motor and sensory goal. In this study, we investigated the oculomotor responses to a large range of different combinations of position error and velocity error during visual tracking of moving stimuli in humans. We found that the oculomotor system uses a prediction of the time at which the eye trajectory will cross the target, defined as the "eye crossing time" (T(XE)). The eye crossing time, which depends on both position error and velocity error, is the criterion used to switch between smooth and saccadic pursuit, i.e., to trigger catch-up saccades. On average, for T(XE) between 40 and 180 ms, no saccade is triggered and target tracking remains purely smooth. Conversely, when T(XE) becomes smaller than 40 ms or larger than 180 ms, a saccade is triggered after a short latency (around 125 ms).

Distractor interference during smooth pursuit eye movements.

PubMed

Spering, Miriam; Gegenfurtner, Karl R; Kerzel, Dirk

2006-10-01

When 2 targets for pursuit eye movements move in different directions, the eye velocity follows the vector average (S. G. Lisberger & V. P. Ferrera, 1997). The present study investigates the mechanisms of target selection when observers are instructed to follow a predefined horizontal target and to ignore a moving distractor stimulus. Results show that at 140 ms after distractor onset, horizontal eye velocity is decreased by about 25%. Vertical eye velocity increases or decreases by 1 degrees /s in the direction opposite from the distractor. This deviation varies in size with distractor direction, velocity, and contrast. The effect was present during the initiation and steady-state tracking phase of pursuit but only when the observer had prior information about target motion. Neither vector averaging nor winner-take-all models could predict the response to a moving to-be-ignored distractor during steady-state tracking of a predefined target. The contributions of perceptual mislocalization and spatial attention to the vertical deviation in pursuit are discussed. Copyright 2006 APA.

Changes in healthcare use among individuals who move into public housing: a population-based investigation.

PubMed

Hinds, Aynslie M; Bechtel, Brian; Distasio, Jino; Roos, Leslie L; Lix, Lisa M

2018-06-05

Residence in public housing, a subsidized and managed government program, may affect health and healthcare utilization. We compared healthcare use in the year before individuals moved into public housing with usage during their first year of tenancy. We also described trends in use. We used linked population-based administrative data housed in the Population Research Data Repository at the Manitoba Centre for Health Policy. The cohort consisted of individuals who moved into public housing in 2009 and 2010. We counted the number of hospitalizations, general practitioner (GP) visits, specialist visits, emergency department visits, and prescriptions drugs dispensed in the twelve 30-day intervals (i.e., months) immediately preceding and following the public housing move-in date. Generalized linear models with generalized estimating equations tested for a period (pre/post-move-in) by month interaction. Odds ratios (ORs), incident rate ratios (IRRs), and means are reported along with 95% confidence intervals (95% CIs). The cohort included 1942 individuals; the majority were female (73.4%) who lived in low income areas and received government assistance (68.1%). On average, the cohort had more than four health conditions. Over the 24 30-day intervals, the percentage of the cohort that visited a GP, specialist, and an emergency department ranged between 37.0% and 43.0%, 10.0% and 14.0%, and 6.0% and 10.0%, respectively, while the percentage of the cohort hospitalized ranged from 1.0% to 5.0%. Generally, these percentages were highest in the few months before the move-in date and lowest in the few months after the move-in date. The period by month interaction was statistically significant for hospitalizations, GP visits, and prescription drug use. The average change in the odds, rate, or mean was smaller in the post-move-in period than in the pre-move-in period. Use of some healthcare services declined after people moved into public housing; however, the decrease was only observed in the first few months and utilization rebounded. Knowledge of healthcare trends before individuals move in are informative for ensuring the appropriate supports are available to new public housing residents. Further study is needed to determine if decreased healthcare utilization following a move is attributable to decreased access.

Development of temporal modelling for forecasting and prediction of malaria infections using time-series and ARIMAX analyses: A case study in endemic districts of Bhutan

PubMed Central

2010-01-01

Background Malaria still remains a public health problem in some districts of Bhutan despite marked reduction of cases in last few years. To strengthen the country's prevention and control measures, this study was carried out to develop forecasting and prediction models of malaria incidence in the endemic districts of Bhutan using time series and ARIMAX. Methods This study was carried out retrospectively using the monthly reported malaria cases from the health centres to Vector-borne Disease Control Programme (VDCP) and the meteorological data from Meteorological Unit, Department of Energy, Ministry of Economic Affairs. Time series analysis was performed on monthly malaria cases, from 1994 to 2008, in seven malaria endemic districts. The time series models derived from a multiplicative seasonal autoregressive integrated moving average (ARIMA) was deployed to identify the best model using data from 1994 to 2006. The best-fit model was selected for each individual district and for the overall endemic area was developed and the monthly cases from January to December 2009 and 2010 were forecasted. In developing the prediction model, the monthly reported malaria cases and the meteorological factors from 1996 to 2008 of the seven districts were analysed. The method of ARIMAX modelling was employed to determine predictors of malaria of the subsequent month. Results It was found that the ARIMA (p, d, q) (P, D, Q)s model (p and P representing the auto regressive and seasonal autoregressive; d and D representing the non-seasonal differences and seasonal differencing; and q and Q the moving average parameters and seasonal moving average parameters, respectively and s representing the length of the seasonal period) for the overall endemic districts was (2,1,1)(0,1,1)12; the modelling data from each district revealed two most common ARIMA models including (2,1,1)(0,1,1)12 and (1,1,1)(0,1,1)12. The forecasted monthly malaria cases from January to December 2009 and 2010 varied from 15 to 82 cases in 2009 and 67 to 149 cases in 2010, where population in 2009 was 285,375 and the expected population of 2010 to be 289,085. The ARIMAX model of monthly cases and climatic factors showed considerable variations among the different districts. In general, the mean maximum temperature lagged at one month was a strong positive predictor of an increased malaria cases for four districts. The monthly number of cases of the previous month was also a significant predictor in one district, whereas no variable could predict malaria cases for two districts. Conclusions The ARIMA models of time-series analysis were useful in forecasting the number of cases in the endemic areas of Bhutan. There was no consistency in the predictors of malaria cases when using ARIMAX model with selected lag times and climatic predictors. The ARIMA forecasting models could be employed for planning and managing malaria prevention and control programme in Bhutan. PMID:20813066

Seasonal trend analysis and ARIMA modeling of relative humidity and wind speed time series around Yamula Dam

NASA Astrophysics Data System (ADS)

Eymen, Abdurrahman; Köylü, Ümran

2018-02-01

Local climate change is determined by analysis of long-term recorded meteorological data. In the statistical analysis of the meteorological data, the Mann-Kendall rank test, which is one of the non-parametrical tests, has been used; on the other hand, for determining the power of the trend, Theil-Sen method has been used on the data obtained from 16 meteorological stations. The stations cover the provinces of Kayseri, Sivas, Yozgat, and Nevşehir in the Central Anatolia region of Turkey. Changes in land-use affect local climate. Dams are structures that cause major changes on the land. Yamula Dam is located 25 km northwest of Kayseri. The dam has huge water body which is approximately 85 km2. The mentioned tests have been used for detecting the presence of any positive or negative trend in meteorological data. The meteorological data in relation to the seasonal average, maximum, and minimum values of the relative humidity and seasonal average wind speed have been organized as time series and the tests have been conducted accordingly. As a result of these tests, the following have been identified: increase was observed in minimum relative humidity values in the spring, summer, and autumn seasons. As for the seasonal average wind speed, decrease was detected for nine stations in all seasons, whereas increase was observed in four stations. After the trend analysis, pre-dam mean relative humidity time series were modeled with Autoregressive Integrated Moving Averages (ARIMA) model which is statistical modeling tool. Post-dam relative humidity values were predicted by ARIMA models.

Modeling peripheral vision for moving target search and detection.

PubMed

Yang, Ji Hyun; Huston, Jesse; Day, Michael; Balogh, Imre

2012-06-01

Most target search and detection models focus on foveal vision. In reality, peripheral vision plays a significant role, especially in detecting moving objects. There were 23 subjects who participated in experiments simulating target detection tasks in urban and rural environments while their gaze parameters were tracked. Button responses associated with foveal object and peripheral object (PO) detection and recognition were recorded. In an urban scenario, pedestrians appearing in the periphery holding guns were threats and pedestrians with empty hands were non-threats. In a rural scenario, non-U.S. unmanned aerial vehicles (UAVs) were considered threats and U.S. UAVs non-threats. On average, subjects missed detecting 2.48 POs among 50 POs in the urban scenario and 5.39 POs in the rural scenario. Both saccade reaction time and button reaction time can be predicted by peripheral angle and entrance speed of POs. Fast moving objects were detected faster than slower objects and POs appearing at wider angles took longer to detect than those closer to the gaze center. A second-order mixed-effect model was applied to provide each subject's prediction model for peripheral target detection performance as a function of eccentricity angle and speed. About half the subjects used active search patterns while the other half used passive search patterns. An interactive 3-D visualization tool was developed to provide a representation of macro-scale head and gaze movement in the search and target detection task. An experimentally validated stochastic model of peripheral vision in realistic target detection scenarios was developed.

Measurement of greenhouse gas emissions from agricultural sites using open-path optical remote sensing method.

PubMed

Ro, Kyoung S; Johnson, Melvin H; Varma, Ravi M; Hashmonay, Ram A; Hunt, Patrick

2009-08-01

Improved characterization of distributed emission sources of greenhouse gases such as methane from concentrated animal feeding operations require more accurate methods. One promising method is recently used by the USEPA. It employs a vertical radial plume mapping (VRPM) algorithm using optical remote sensing techniques. We evaluated this method to estimate emission rates from simulated distributed methane sources. A scanning open-path tunable diode laser was used to collect path-integrated concentrations (PICs) along different optical paths on a vertical plane downwind of controlled methane releases. Each cycle consists of 3 ground-level PICs and 2 above ground PICs. Three- to 10-cycle moving averages were used to reconstruct mass equivalent concentration plum maps on the vertical plane. The VRPM algorithm estimated emission rates of methane along with meteorological and PIC data collected concomitantly under different atmospheric stability conditions. The derived emission rates compared well with actual released rates irrespective of atmospheric stability conditions. The maximum error was 22 percent when 3-cycle moving average PICs were used; however, it decreased to 11% when 10-cycle moving average PICs were used. Our validation results suggest that this new VRPM method may be used for improved estimations of greenhouse gas emission from a variety of agricultural sources.

A novel algorithm for Bluetooth ECG.

PubMed

Pandya, Utpal T; Desai, Uday B

2012-11-01

In wireless transmission of ECG, data latency will be significant when battery power level and data transmission distance are not maintained. In applications like home monitoring or personalized care, to overcome the joint effect of previous issues of wireless transmission and other ECG measurement noises, a novel filtering strategy is required. Here, a novel algorithm, identified as peak rejection adaptive sampling modified moving average (PRASMMA) algorithm for wireless ECG is introduced. This algorithm first removes error in bit pattern of received data if occurred in wireless transmission and then removes baseline drift. Afterward, a modified moving average is implemented except in the region of each QRS complexes. The algorithm also sets its filtering parameters according to different sampling rate selected for acquisition of signals. To demonstrate the work, a prototyped Bluetooth-based ECG module is used to capture ECG with different sampling rate and in different position of patient. This module transmits ECG wirelessly to Bluetooth-enabled devices where the PRASMMA algorithm is applied on captured ECG. The performance of PRASMMA algorithm is compared with moving average and S-Golay algorithms visually as well as numerically. The results show that the PRASMMA algorithm can significantly improve the ECG reconstruction by efficiently removing the noise and its use can be extended to any parameters where peaks are importance for diagnostic purpose.

Enhancement of the Comb Filtering Selectivity Using Iterative Moving Average for Periodic Waveform and Harmonic Elimination

PubMed Central

Wu, Yan; Aarts, Ronald M.

2018-01-01

A recurring problem regarding the use of conventional comb filter approaches for elimination of periodic waveforms is the degree of selectivity achieved by the filtering process. Some applications, such as the gradient artefact correction in EEG recordings during coregistered EEG-fMRI, require a highly selective comb filtering that provides effective attenuation in the stopbands and gain close to unity in the pass-bands. In this paper, we present a novel comb filtering implementation whereby the iterative filtering application of FIR moving average-based approaches is exploited in order to enhance the comb filtering selectivity. Our results indicate that the proposed approach can be used to effectively approximate the FIR moving average filter characteristics to those of an ideal filter. A cascaded implementation using the proposed approach shows to further increase the attenuation in the filter stopbands. Moreover, broadening of the bandwidth of the comb filtering stopbands around −3 dB according to the fundamental frequency of the stopband can be achieved by the novel method, which constitutes an important characteristic to account for broadening of the harmonic gradient artefact spectral lines. In parallel, the proposed filtering implementation can also be used to design a novel notch filtering approach with enhanced selectivity as well. PMID:29599955

Quasi-static motion of microparticles at the depinning contact line of an evaporating droplet on PDMS surface

NASA Astrophysics Data System (ADS)

Yu, Ying-Song; Xia, Xue-Lian; Zheng, Xu; Huang, Xianfu; Zhou, Jin-Zhi

2017-09-01

In this paper, evaporation of sessile water droplets containing fluorescent polystyrene (PS) microparticles on polydimethylsiloxane (PDMS) surfaces with different curing ratios was studied experimentally using laser confocal microscopy. At the beginning, there were some microparticles located at the contact line and some microparticles moved towards the line. Due to contact angle hysteresis, at first both the contact line and the microparticles were pinned. With the depinning contact line, the microparticles moved together spontaneously. Using the software ImageJ, the location of contact lines at different time were acquired and the circle centers and radii of the contact lines were obtained via the least square method. Then the average distance of two neighbor contact lines at a certain time interval was obtained to characterize the motion of the contact line. Fitting the distance-time curve at the depinning contact line stage with polynomials and differentiating the polynomials with time, we obtained the velocity and acceleration of both the contact line and the microparticles located at the line. The velocity and the maximum acceleration were, respectively, of the orders of 1 μm/s and 20-200 nm/s2, indicating that the motion of the microparticles located at the depinning contact line was quasi-static. Finally, we presented a theoretical model to describe the quasi-static process, which may help in understanding both self-pinning and depinning of microparticles.

FARMWORKERS, A REPRINT FROM THE 1966 MANPOWER REPORT.

ERIC Educational Resources Information Center

Manpower Administration (DOL), Washington, DC.

ALTHOUGH THE AVERAGE STANDARD OF LIVING OF FARM PEOPLE HAS BEEN RISING STEADILY, THEY CONTINUE TO FACE SEVERE PROBLEMS OF UNDEREMPLOYMENT AND POVERTY. THE AVERAGE PER CAPITA INCOME OF FARM RESIDENTS IS LESS THAN TWO-THIRDS THAT OF THE NONFARM POPULATION. MILLIONS HAVE MOVED TO CITIES, LEAVING STAGNATING RURAL COMMUNITIES, AND INCREASING THE CITY…

Non-equilibrium steady states in the Klein-Gordon theory

NASA Astrophysics Data System (ADS)

Doyon, Benjamin; Lucas, Andrew; Schalm, Koenraad; Bhaseen, M. J.

2015-03-01

We construct non-equilibrium steady states in the Klein-Gordon theory in arbitrary space dimension d following a local quench. We consider the approach where two independently thermalized semi-infinite systems, with temperatures {{T}L} and {{T}R}, are connected along a d-1-dimensional hypersurface. A current-carrying steady state, described by thermally distributed modes with temperatures {{T}L} and {{T}R} for left and right-moving modes, respectively, emerges at late times. The non-equilibrium density matrix is the exponential of a non-local conserved charge. We obtain exact results for the average energy current and the complete distribution of energy current fluctuations. The latter shows that the long-time energy transfer can be described by a continuum of independent Poisson processes, for which we provide the exact weights. We further describe the full time evolution of local observables following the quench. Averages of generic local observables, including the stress-energy tensor, approach the steady state with a power-law in time, where the exponent depends on the initial conditions at the connection hypersurface. We describe boundary conditions and special operators for which the steady state is reached instantaneously on the connection hypersurface. A semiclassical analysis of freely propagating modes yields the average energy current at large distances and late times. We conclude by comparing and contrasting our findings with results for interacting theories and provide an estimate for the timescale governing the crossover to hydrodynamics. As a modification of our Klein-Gordon analysis we also include exact results for free Dirac fermions.

Severe Weather Guide - Mediterranean Ports. 7. Marseille

DTIC Science & Technology

1988-03-01

the afternoon. Upper—level westerlies and the associated storm track is moved northward during summer, so extratropical cyclones and associated...autumn as the extratropical storm track moves southward. Precipitation amount is the highest of the year, with an average of 3 inches (76 mm) for the...18 SUBJECT TERMS (Continue on reverse if necessary and identify by block number) Storm haven Mediterranean meteorology Marseille port

Polymer Coatings Degradation Properties

DTIC Science & Technology

1985-02-01

undertaken 124). The Box-Jenkins approach first evaluates the partial auto -correlation function and determines the order of the moving average memory function...78 - Tables 15 and 16 show the resalit- f- a, the partial auto correlation plots. Second order moving .-. "ra ;;th -he appropriate lags were...coated films. Kaempf, Guenter; Papenroth, Wolfgang; Kunststoffe Date: 1982 Volume: 72 Number:7 Pages: 424-429 Parameters influencing the accelerated

Nonparametric Transfer Function Models

PubMed Central

Liu, Jun M.; Chen, Rong; Yao, Qiwei

2009-01-01

In this paper a class of nonparametric transfer function models is proposed to model nonlinear relationships between ‘input’ and ‘output’ time series. The transfer function is smooth with unknown functional forms, and the noise is assumed to be a stationary autoregressive-moving average (ARMA) process. The nonparametric transfer function is estimated jointly with the ARMA parameters. By modeling the correlation in the noise, the transfer function can be estimated more efficiently. The parsimonious ARMA structure improves the estimation efficiency in finite samples. The asymptotic properties of the estimators are investigated. The finite-sample properties are illustrated through simulations and one empirical example. PMID:20628584

Stochastic Flow Cascades

NASA Astrophysics Data System (ADS)

Eliazar, Iddo I.; Shlesinger, Michael F.

2012-01-01

We introduce and explore a Stochastic Flow Cascade (SFC) model: A general statistical model for the unidirectional flow through a tandem array of heterogeneous filters. Examples include the flow of: (i) liquid through heterogeneous porous layers; (ii) shocks through tandem shot noise systems; (iii) signals through tandem communication filters. The SFC model combines together the Langevin equation, convolution filters and moving averages, and Poissonian randomizations. A comprehensive analysis of the SFC model is carried out, yielding closed-form results. Lévy laws are shown to universally emerge from the SFC model, and characterize both heavy tailed retention times (Noah effect) and long-ranged correlations (Joseph effect).

How directional mobility affects coexistence in rock-paper-scissors models

NASA Astrophysics Data System (ADS)

Avelino, P. P.; Bazeia, D.; Losano, L.; Menezes, J.; de Oliveira, B. F.; Santos, M. A.

2018-03-01

This work deals with a system of three distinct species that changes in time under the presence of mobility, selection, and reproduction, as in the popular rock-paper-scissors game. The novelty of the current study is the modification of the mobility rule to the case of directional mobility, in which the species move following the direction associated to a larger (averaged) number density of selection targets in the surrounding neighborhood. Directional mobility can be used to simulate eyes that see or a nose that smells, and we show how it may contribute to reduce the probability of coexistence.

How directional mobility affects coexistence in rock-paper-scissors models.

PubMed

Avelino, P P; Bazeia, D; Losano, L; Menezes, J; de Oliveira, B F; Santos, M A

2018-03-01

This work deals with a system of three distinct species that changes in time under the presence of mobility, selection, and reproduction, as in the popular rock-paper-scissors game. The novelty of the current study is the modification of the mobility rule to the case of directional mobility, in which the species move following the direction associated to a larger (averaged) number density of selection targets in the surrounding neighborhood. Directional mobility can be used to simulate eyes that see or a nose that smells, and we show how it may contribute to reduce the probability of coexistence.

Evaluating Zeolite-Modified Sensors: towards a faster set of chemical sensors

NASA Astrophysics Data System (ADS)

Berna, A. Z.; Vergara, A.; Trincavelli, M.; Huerta, R.; Afonja, A.; Parkin, I. P.; Binions, R.; Trowell, S.

2011-09-01

The responses of zeolite-modified sensors, prepared by screen printing layers of chromium titanium oxide (CTO), were compared to unmodified tin oxide sensors using amplitude and transient responses. For transient responses we used a family of features, derived from the exponential moving average (EMA), to characterize chemo-resistive responses. All sensors were tested simultaneously against 20 individual volatile compounds from four chemical groups. The responses of the two types of sensors showed some independence. The zeolite-modified CTO sensors discriminated compounds better using either amplitude response or EMA features and CTO-modified sensors also responded three times faster.

Finding time over time: Longitudinal links between employed mothers' work-family conflict and time profiles.

PubMed

Lee, Soomi; McHale, Susan M; Crouter, Ann C; Hammer, Leslie B; Almeida, David M

2017-08-01

Drawing upon the Work-Home Resources model (ten Brummelhuis & Bakker, 2012), this study examined the links between work-family conflict and employed mothers' profiles of time resources for work and parenting roles. Using a person-centered latent profile approach, we identified 3 profiles of time use and perceived time adequacy in a sample of mothers employed in the extended-care industry (N = 440): a Work-Oriented profile, characterized by spending relatively more time at work, perceiving lower time adequacy for work, spending less time with children, and perceiving lower time adequacy for children; a Parenting-Oriented profile, characterized by the opposite pattern; and a Role-Balanced profile, characterized by average levels across the 4 dimensions. Mothers in the Work-Oriented profile reported greater work-to-family conflict and family to-work conflict than those in the Role-Balanced and Parenting-Oriented profiles. Greater work-to-family conflict was linked to membership in the Work-Oriented profile, net of personal, family, and work characteristics. Longitudinal latent profile transition analysis showed that increases in work-to-family conflict across 12 months were linked to greater odds of moving toward the Work-Oriented profile (relative to staying in the same profile), whereas decreases in work-to-family conflict were linked to greater odds of moving toward the Parenting-Oriented profile. Results illuminate the heterogeneity in how employed mothers perceive and allocate time in work and parenting roles and suggest that decreasing work-to-family conflict may preserve time resources for parenting. Intervention efforts should address ways of increasing employees' family time resources and decreasing work-family conflict. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

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.

The Dynamics and Correlates of Religious Service Attendance in Adolescence

PubMed Central

Hardie, Jessica Halliday; Pearce, Lisa D.; Denton, Melinda Lundquist

2013-01-01

This study examines changes in religious service attendance over time for a contemporary cohort of adolescents moving from middle to late adolescence. We use two waves of a nationally representative panel survey of youth from the National Study of Youth and Religion (NSYR) to examine the dynamics of religious involvement during adolescence. We then follow with an analysis of how demographic characteristics, family background, and life course transitions relate to changes in religious service attendance during adolescence. Our findings suggest that, on average, adolescent religious service attendance declines over time, related to major life course transitions such as becoming employed, leaving home, and initiating sexual activity. Parents’ affiliation and attendance, on the other hand, are protective factors against decreasing attendance. PMID:26900186

Thermoelectric integrated membrane evaporation water recovery technology

NASA Technical Reports Server (NTRS)

Roebelen, G. J., Jr.; Winkler, H. E.; Dehner, G. F.

1982-01-01

The recently developed Thermoelectric Integrated Membrane Evaporation Subsystem (TIMES) offers a highly competitive approach to water recovery from waste fluids for future on-orbit stations such as the Space Operations Center. Low power, compactness and gravity insensitive operation are featured in this vacuum distillation subsystem that combines a hollow fiber membrane evaporator with a thermoelectric heat pump. The hollow fiber elements provide positive liquid/gas phase control with no moving parts other than pumps and an accumulator, thus solving problems inherent in other reclamation subsystem designs. In an extensive test program, over 850 hours of operation were accumulated during which time high quality product water was recovered from both urine and wash water at an average steady state production rate of 2.2 pounds per hour.

Moving force identification based on modified preconditioned conjugate gradient method

NASA Astrophysics Data System (ADS)

Chen, Zhen; Chan, Tommy H. T.; Nguyen, Andy

2018-06-01

This paper develops a modified preconditioned conjugate gradient (M-PCG) method for moving force identification (MFI) by improving the conjugate gradient (CG) and preconditioned conjugate gradient (PCG) methods with a modified Gram-Schmidt algorithm. The method aims to obtain more accurate and more efficient identification results from the responses of bridge deck caused by vehicles passing by, which are known to be sensitive to ill-posed problems that exist in the inverse problem. A simply supported beam model with biaxial time-varying forces is used to generate numerical simulations with various analysis scenarios to assess the effectiveness of the method. Evaluation results show that regularization matrix L and number of iterations j are very important influence factors to identification accuracy and noise immunity of M-PCG. Compared with the conventional counterpart SVD embedded in the time domain method (TDM) and the standard form of CG, the M-PCG with proper regularization matrix has many advantages such as better adaptability and more robust to ill-posed problems. More importantly, it is shown that the average optimal numbers of iterations of M-PCG can be reduced by more than 70% compared with PCG and this apparently makes M-PCG a preferred choice for field MFI applications.

The Onset Time of the Ownership Sensation in the Moving Rubber Hand Illusion.

PubMed

Kalckert, Andreas; Ehrsson, H H

2017-01-01

The rubber hand illusion (RHI) is a perceptual illusion whereby a model hand is perceived as part of one's own body. This illusion has been extensively studied, but little is known about the temporal evolution of this perceptual phenomenon, i.e., how long it takes until participants start to experience ownership over the model hand. In the present study, we investigated a version of the rubber hand experiment based on finger movements and measured the average onset time in active and passive movement conditions. This comparison enabled us to further explore the possible role of intentions and motor control processes that are only present in the active movement condition. The results from a large group of healthy participants ( n = 117) showed that the illusion of ownership took approximately 23 s to emerge (active: 22.8; passive: 23.2). The 90th percentile occurs in both conditions within approximately 50 s (active: 50; passive: 50.6); therefore, most participants experience the illusion within the first minute. We found indirect evidence of a facilitatory effect of active movements compared to passive movements, and we discuss these results in the context of our current understanding of the processes underlying the moving RHI.

Collective cell migration without proliferation: density determines cell velocity and wave velocity

NASA Astrophysics Data System (ADS)

Tlili, Sham; Gauquelin, Estelle; Li, Brigitte; Cardoso, Olivier; Ladoux, Benoît; Delanoë-Ayari, Hélène; Graner, François

2018-05-01

Collective cell migration contributes to embryogenesis, wound healing and tumour metastasis. Cell monolayer migration experiments help in understanding what determines the movement of cells far from the leading edge. Inhibiting cell proliferation limits cell density increase and prevents jamming; we observe long-duration migration and quantify space-time characteristics of the velocity profile over large length scales and time scales. Velocity waves propagate backwards and their frequency depends only on cell density at the moving front. Both cell average velocity and wave velocity increase linearly with the cell effective radius regardless of the distance to the front. Inhibiting lamellipodia decreases cell velocity while waves either disappear or have a lower frequency. Our model combines conservation laws, monolayer mechanical properties and a phenomenological coupling between strain and polarity: advancing cells pull on their followers, which then become polarized. With reasonable values of parameters, this model agrees with several of our experimental observations. Together, our experiments and model disantangle the respective contributions of active velocity and of proliferation in monolayer migration, explain how cells maintain their polarity far from the moving front, and highlight the importance of strain-polarity coupling and density in long-range information propagation.

Quantum hydrodynamics: capturing a reactive scattering resonance.

PubMed

Derrickson, Sean W; Bittner, Eric R; Kendrick, Brian K

2005-08-01

The hydrodynamic equations of motion associated with the de Broglie-Bohm formulation of quantum mechanics are solved using a meshless method based upon a moving least-squares approach. An arbitrary Lagrangian-Eulerian frame of reference and a regridding algorithm which adds and deletes computational points are used to maintain a uniform and nearly constant interparticle spacing. The methodology also uses averaged fields to maintain unitary time evolution. The numerical instabilities associated with the formation of nodes in the reflected portion of the wave packet are avoided by adding artificial viscosity to the equations of motion. A new and more robust artificial viscosity algorithm is presented which gives accurate scattering results and is capable of capturing quantum resonances. The methodology is applied to a one-dimensional model chemical reaction that is known to exhibit a quantum resonance. The correlation function approach is used to compute the reactive scattering matrix, reaction probability, and time delay as a function of energy. Excellent agreement is obtained between the scattering results based upon the quantum hydrodynamic approach and those based upon standard quantum mechanics. This is the first clear demonstration of the ability of moving grid approaches to accurately and robustly reproduce resonance structures in a scattering system.

The Impact of Averaging Window Length on the “Desaturation” Indexes Obtained Via Overnight Pulse Oximetry at High Altitude

PubMed Central

Cross, Troy J.; Keller-Ross, Manda; Issa, Amine; Wentz, Robert; Taylor, Bryan; Johnson, Bruce

2015-01-01

Study Objectives: To determine the impact of averaging window-length on the “desaturation” indexes (DIs) obtained via overnight pulse oximetry (SpO2) at high altitude. Design: Overnight SpO2 data were collected during a 10-day sojourn at high altitude. SpO2 was obtained using a commercial wrist-worn finger oximeter whose firmware was modified to store unaveraged beat-to-beat data. Simple moving averages of window lengths spanning 2 to 20 cardiac beats were retrospectively applied to beat-to-beat SpO2 datasets. After SpO2 artifacts were removed, the following DIs were then calculated for each of the averaged datasets: oxygen desaturation index (ODI); total sleep time with SpO2 < 80% (TST < 80), and the lowest SpO2 observed during sleep (SpO2 low). Setting: South Base Camp, Mt. Everest (5,364 m elevation). Participants: Five healthy, adult males (35 ± 5 y; 180 ± 1 cm; 85 ± 4 kg). Interventions: N/A. Measurements and Results: 49 datasets were obtained from the 5 participants, totalling 239 hours of data. For all window lengths ≥ 2 beats, ODI and TST < 80 were lower, and SpO2 low was higher than those values obtained from the beat-to-beat SpO2 time series data (P < 0.05). Conclusions: Our findings indicate that increasing oximeter averaging window length progressively underestimates the frequency and magnitude of sleep disordered breathing events at high altitude, as indirectly assessed via the desaturation indexes. Citation: Cross TJ, Keller-Ross M, Issa A, Wentz R, Taylor B, Johnson B. The impact of averaging window length on the “desaturation” indexes obtained via overnight pulse oximetry at high altitude. SLEEP 2015;38(8):1331–1334. PMID:25581919

Propulsion by sinusoidal locomotion: A motion inspired by Caenorhabditis elegans

NASA Astrophysics Data System (ADS)

Ulrich, Xialing

Sinusoidal locomotion is commonly seen in snakes, fish, nematodes, or even the wings of some birds and insects. This doctoral thesis presents the study of sinusoidal locomotion of the nematode C. elegans in experiments and the application of the state-space airloads theory to the theoretical forces of sinusoidal motion. An original MATLAB program has been developed to analyze the video records of C. elegans' movement in different fluids, including Newtonian and non-Newtonian fluids. The experimental and numerical studies of swimming C. elegans has revealed three conclusions. First, though the amplitude and wavelength are varying with time, the motion of swimming C. elegans can still be viewed as sinusoidal locomotion with slips. The average normalized wavelength is a conserved character of the locomotion for both Newtonian and non-Newtonian fluids. Second, fluid viscosity affects the frequency but not the moving speed of C. elegans, while fluid elasticity affects the moving speed but not the frequency. Third, by the resistive force theory, for more elastic fluids the ratio of resistive coefficients becomes smaller. Inspired by the motion of C. elegans and other animals performing sinusoidal motion, we investigated the sinusoidal motion of a thin flexible wing in theory. Given the equation of the motion, we have derived the closed forms of propulsive force, lift and other generalized forces applying on the wing. We also calculated the power required to perform the motion, the power lost due to the shed vortices and the propulsive efficiency. These forces and powers are given as functions of reduced frequency k, dimensionless wavelength z, dimensionless amplitude A/b, and time. Our results show that a positive, time-averaged propulsive force is produced for all k>k0=pi/ z. At k=k0, which implies the moment when the moving speed of the wing is the same as the wave speed of its undulation, the motion reaches a steady state with all forces being zero. If there were no shed vorticity effects, the propulsive force would be zero at z = 0.569 and z = 1.3 for all k, and for a fixed k the wing would gain the optimal propulsive force when z = 0.82. With the effects of shed vorticity, the propulsive efficiency decreases from 1.0 to 0.5 as k goes to infinity, and the propulsive efficiency increases almost in a linear relationship with k0.

Random Process Simulation for stochastic fatigue analysis. Ph.D. Thesis - Rice Univ., Houston, Tex.

NASA Technical Reports Server (NTRS)

Larsen, Curtis E.

1988-01-01

A simulation technique is described which directly synthesizes the extrema of a random process and is more efficient than the Gaussian simulation method. Such a technique is particularly useful in stochastic fatigue analysis because the required stress range moment E(R sup m), is a function only of the extrema of the random stress process. The family of autoregressive moving average (ARMA) models is reviewed and an autoregressive model is presented for modeling the extrema of any random process which has a unimodal power spectral density (psd). The proposed autoregressive technique is found to produce rainflow stress range moments which compare favorably with those computed by the Gaussian technique and to average 11.7 times faster than the Gaussian technique. The autoregressive technique is also adapted for processes having bimodal psd's. The adaptation involves using two autoregressive processes to simulate the extrema due to each mode and the superposition of these two extrema sequences. The proposed autoregressive superposition technique is 9 to 13 times faster than the Gaussian technique and produces comparable values for E(R sup m) for bimodal psd's having the frequency of one mode at least 2.5 times that of the other mode.

Traction force and tension fluctuations in growing axons

NASA Astrophysics Data System (ADS)

Urbach, Jeffrey; Polackwich, Jamie; Koch, Daniel; McAllister, Ryan; Geller, Herbert

Actively generated mechanical forces play a central role in axon growth and guidance during nervous system development. We describe the dynamics of traction stresses from growth cones of actively advancing axons from postnatal rat DRG neurons. By tracking the movement of the growth cone and analyzing the traction stresses in a co-moving reference frame, we show that there is a clear and consistent average stress field underlying the complex spatial stresses present at any one time. The average stress field has strong maxima on the sides of the growth cone, directed inward toward the growth cone neck. This pattern represents a Contractile stress contained within the growth cone, and a net force that is balanced by the axon tension. In addition, using high time-resolution measurements, we show that the stress field is composed of fluctuating local stress peaks, with a population of peaks whose lifetime distribution follows an exponential decay, and a small number of very long-lived peaks. We also find that the tension appears to vary randomly over short time scales, roughly consistent with the lifetime of the stress peaks, suggesting that the tension fluctuations originate from stochastic adhesion dynamics.

Spectral narrowing and spin echo for localized carriers with heavy-tailed L evy distribution of hopping times

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

Yue, Z.; Mkhitaryan, Vagharsh; Raikh, M. E.

2016-02-02

We study analytically the free induction decay and the spin echo decay originating from the localized carriers moving between the sites which host random magnetic fields. Due to disorder in the site positions and energies, the on-site residence times, , are widely spread according to the L evy distribution. The power-law tail ∝ τ -1-∝ in the distribution of does not affect the conventional spectral narrowing for α > 2, but leads to a dramatic acceleration of the free induction decay in the domain 2 > α > 1. The next abrupt acceleration of the decay takes place as becomesmore » smaller than 1. In the latter domain the decay does not follow a simple-exponent law. To capture the behavior of the average spin in this domain, we solve the evolution equation for the average spin using the approach different from the conventional approach based on the Laplace transform. Unlike the free induction decay, the tail in the distribution of the residence times leads to the slow decay of the spin echo. The echo is dominated by realizations of the carrier motion for which the number of sites, visited by the carrier, is minimal.« less

Prediction Methods in Solar Sunspots Cycles

PubMed Central

Ng, Kim Kwee

2016-01-01

An understanding of the Ohl’s Precursor Method, which is used to predict the upcoming sunspots activity, is presented by employing a simplified movable divided-blocks diagram. Using a new approach, the total number of sunspots in a solar cycle and the maximum averaged monthly sunspots number Rz(max) are both shown to be statistically related to the geomagnetic activity index in the prior solar cycle. The correlation factors are significant and they are respectively found to be 0.91 ± 0.13 and 0.85 ± 0.17. The projected result is consistent with the current observation of solar cycle 24 which appears to have attained at least Rz(max) at 78.7 ± 11.7 in March 2014. Moreover, in a statistical study of the time-delayed solar events, the average time between the peak in the monthly geomagnetic index and the peak in the monthly sunspots numbers in the succeeding ascending phase of the sunspot activity is found to be 57.6 ± 3.1 months. The statistically determined time-delayed interval confirms earlier observational results by others that the Sun’s electromagnetic dipole is moving toward the Sun’s Equator during a solar cycle. PMID:26868269

Locomotion of microorganisms near a no-slip boundary in a viscoelastic fluid

NASA Astrophysics Data System (ADS)

Yazdi, Shahrzad; Ardekani, Arezoo M.; Borhan, Ali

2014-10-01

Locomotion of microorganisms plays a vital role in most of their biological processes. In many of these processes, microorganisms are exposed to complex fluids while swimming in confined domains, such as spermatozoa in mucus of mammalian reproduction tracts or bacteria in extracellular polymeric matrices during biofilm formation. Thus, it is important to understand the kinematics of propulsion in a viscoelastic fluid near a no-slip boundary. We use a squirmer model with a time-reversible body motion to analytically investigate the swimming kinematics in an Oldroyd-B fluid near a wall. Analysis of the time-averaged motion of the swimmer shows that both pullers and pushers in a viscoelastic fluid swim towards the no-slip boundary if they are initially located within a small domain of "attraction" in the vicinity of the wall. In contrast, neutral swimmers always move towards the wall regardless of their initial distance from the wall. Outside the domain of attraction, pullers and pushers are both repelled from the no-slip boundary. Time-averaged locomotion is most pronounced at a Deborah number of unity. We examine the swimming trajectories of different types of swimmers as a function of their initial orientation and distance from the no-slip boundary.

Response of Bighead Carp and Silver Carp to repeated water gun operation in an enclosed shallow pond

USGS Publications Warehouse

Romine, Jason G.; Jensen, Nathan; Parsley, Michael J.; Gaugush, Robert F.; Severson, Todd J.; Hatton, Tyson W.; Adams, Ryan F.; Gaikowski, Mark P.

2015-01-01

The Bighead Carp Hypophthalmichthys nobilis and Silver Carp H. molitrix are nonnative species that pose a threat to Great Lakes ecosystems should they advance into those areas. Thus, technologies to impede Asian carp movement into the Great Lakes are needed; one potential technology is the seismic water gun. We evaluated the efficacy of a water gun array as a behavioral deterrent to the movement of acoustic-tagged Bighead Carp and Silver Carp in an experimental pond. Behavioral responses were evaluated by using four metrics: (1) fish distance from the water guns (D); (2) spatial area of the fish's utilization distribution (UD); (3) persistence velocity (Vp); and (4) number of times a fish transited the water gun array. For both species, average D increased by 10 m during the firing period relative to the pre-firing period. During the firing period, the spatial area of use within the pond decreased. Carp were located throughout the pond during the pre-firing period but were concentrated in the north end of the pond during the firing period, thus reducing their UDs by roughly 50%. Overall, Vp decreased during the firing period relative to the pre-firing period, as fish movement became more tortuous and confined, suggesting that the firing of the guns elicited a change in carp behavior. The water gun array was partially successful at impeding carp movement, but some fish did transit the array. Bighead Carp moved past the guns a total of 78 times during the pre-firing period and 15 times during the firing period; Silver Carp moved past the guns 96 times during the pre-firing period and 13 times during the firing period. Although the water guns did alter carp behavior, causing the fish to move away from the guns, this method was not 100% effective as a passage deterrent.

Variability of runoff-based drought conditions in the conterminous United States

USGS Publications Warehouse

McCabe, Gregory J.; Wolock, David M.; Austin, Samuel H.

2017-01-01

In this study, a monthly water-balance model is used to simulate monthly runoff for 2109 hydrologic units (HUs) in the conterminous United States (CONUS) for water-years 1901 through 2014. The monthly runoff time series for each HU were smoothed with a 3-month moving average, and then the 3-month moving-average runoff values were converted to percentiles. For each HU, a drought was considered to occur when the HU runoff percentile dropped to the 20th percentile or lower. A drought was considered to end when the HU runoff percentile exceeded the 20th percentile. After identifying drought events for each HU, the frequency and length of drought events were examined. Results indicated that (1) the longest mean drought lengths occur in the eastern CONUS and parts of the Rocky Mountain region and the northwestern CONUS, (2) the frequency of drought is highest in the southwestern and central CONUS, and lowest in the eastern CONUS, the Rocky Mountain region, and the northwestern CONUS, (3) droughts have occurred during all months of the year and there does not appear to be a seasonal pattern to drought occurrence, (4) the variability of precipitation appears to have been the principal climatic factor determining drought, and (5) for most of the CONUS, drought frequency appears to have decreased during the 1901 through 2014 period.

Development of a fuel cell plug-in hybrid electric vehicle and vehicle simulator for energy management assessment

NASA Astrophysics Data System (ADS)

Meintz, Andrew Lee

This dissertation offers a description of the development of a fuel cell plug-in hybrid electric vehicle focusing on the propulsion architecture selection, propulsion system control, and high-level energy management. Two energy management techniques have been developed and implemented for real-time control of the vehicle. The first method is a heuristic method that relies on a short-term moving average of the vehicle power requirements. The second method utilizes an affine function of the short-term and long-term moving average vehicle power requirements. The development process of these methods has required the creation of a vehicle simulator capable of estimating the effect of changes to the energy management control techniques on the overall vehicle energy efficiency. Furthermore, the simulator has allowed for the refinement of the energy management methods and for the stability of the method to be analyzed prior to on-road testing. This simulator has been verified through on-road testing of a constructed prototype vehicle under both highway and city driving schedules for each energy management method. The results of the finalized vehicle control strategies are compared with the simulator predictions and an assessment of the effectiveness of both strategies is discussed. The methods have been evaluated for energy consumption in the form of both hydrogen fuel and stored electricity from grid charging.

Granger causality for state-space models

NASA Astrophysics Data System (ADS)

Barnett, Lionel; Seth, Anil K.

2015-04-01

Granger causality has long been a prominent method for inferring causal interactions between stochastic variables for a broad range of complex physical systems. However, it has been recognized that a moving average (MA) component in the data presents a serious confound to Granger causal analysis, as routinely performed via autoregressive (AR) modeling. We solve this problem by demonstrating that Granger causality may be calculated simply and efficiently from the parameters of a state-space (SS) model. Since SS models are equivalent to autoregressive moving average models, Granger causality estimated in this fashion is not degraded by the presence of a MA component. This is of particular significance when the data has been filtered, downsampled, observed with noise, or is a subprocess of a higher dimensional process, since all of these operations—commonplace in application domains as diverse as climate science, econometrics, and the neurosciences—induce a MA component. We show how Granger causality, conditional and unconditional, in both time and frequency domains, may be calculated directly from SS model parameters via solution of a discrete algebraic Riccati equation. Numerical simulations demonstrate that Granger causality estimators thus derived have greater statistical power and smaller bias than AR estimators. We also discuss how the SS approach facilitates relaxation of the assumptions of linearity, stationarity, and homoscedasticity underlying current AR methods, thus opening up potentially significant new areas of research in Granger causal analysis.

Weather Variability, Tides, and Barmah Forest Virus Disease in the Gladstone Region, Australia

PubMed Central

Naish, Suchithra; Hu, Wenbiao; Nicholls, Neville; Mackenzie, John S.; McMichael, Anthony J.; Dale, Pat; Tong, Shilu

2006-01-01

In this study we examined the impact of weather variability and tides on the transmission of Barmah Forest virus (BFV) disease and developed a weather-based forecasting model for BFV disease in the Gladstone region, Australia. We used seasonal autoregressive integrated moving-average (SARIMA) models to determine the contribution of weather variables to BFV transmission after the time-series data of response and explanatory variables were made stationary through seasonal differencing. We obtained data on the monthly counts of BFV cases, weather variables (e.g., mean minimum and maximum temperature, total rainfall, and mean relative humidity), high and low tides, and the population size in the Gladstone region between January 1992 and December 2001 from the Queensland Department of Health, Australian Bureau of Meteorology, Queensland Department of Transport, and Australian Bureau of Statistics, respectively. The SARIMA model shows that the 5-month moving average of minimum temperature (β = 0.15, p-value < 0.001) was statistically significantly and positively associated with BFV disease, whereas high tide in the current month (β = −1.03, p-value = 0.04) was statistically significantly and inversely associated with it. However, no significant association was found for other variables. These results may be applied to forecast the occurrence of BFV disease and to use public health resources in BFV control and prevention. PMID:16675420

Online tracking of instantaneous frequency and amplitude of dynamical system response

NASA Astrophysics Data System (ADS)

Frank Pai, P.

2010-05-01

This paper presents a sliding-window tracking (SWT) method for accurate tracking of the instantaneous frequency and amplitude of arbitrary dynamic response by processing only three (or more) most recent data points. Teager-Kaiser algorithm (TKA) is a well-known four-point method for online tracking of frequency and amplitude. Because finite difference is used in TKA, its accuracy is easily destroyed by measurement and/or signal-processing noise. Moreover, because TKA assumes the processed signal to be a pure harmonic, any moving average in the signal can destroy the accuracy of TKA. On the other hand, because SWT uses a constant and a pair of windowed regular harmonics to fit the data and estimate the instantaneous frequency and amplitude, the influence of any moving average is eliminated. Moreover, noise filtering is an implicit capability of SWT when more than three data points are used, and this capability increases with the number of processed data points. To compare the accuracy of SWT and TKA, Hilbert-Huang transform is used to extract accurate time-varying frequencies and amplitudes by processing the whole data set without assuming the signal to be harmonic. Frequency and amplitude trackings of different amplitude- and frequency-modulated signals, vibrato in music, and nonlinear stationary and non-stationary dynamic signals are studied. Results show that SWT is more accurate, robust, and versatile than TKA for online tracking of frequency and amplitude.

Modeling of Particle Agglomeration in Nanofluids

NASA Astrophysics Data System (ADS)

Kanagala, Hari Krishna

Nanofluids are colloidal dispersions of nano sized particles (<100nm in diameter) in dispersion mediums. They are of great interest in industrial applications as heat transfer fluids owing to their enhanced thermal conductivities. Stability of nanofluids is a major problem hindering their industrial application. Agglomeration and then sedimentation are some reasons, which drastically decrease the shelf life of these nanofluids. Current research addresses the agglomeration effect and how it can affect the shelf life of a nanofluid. The reasons for agglomeration in nanofluids are attributable to the interparticle interactions which are quantified by the various theories. By altering the governing properties like volume fraction, pH and electrolyte concentration different nanofluids with instant agglomeration, slow agglomeration and no agglomeration can be produced. A numerical model is created based on the discretized population balance equations which analyses the particle size distribution at different times. Agglomeration effects have been analyzed for alumina nanoparticles with average particle size of 150nm dispersed in de-ionized water. As the pH was moved towards the isoelectric point of alumina nanofluids, the particle size distribution became broader and moved to bigger sizes rapidly with time. Particle size distributions became broader and moved to bigger sizes more quickly with time with increase in the electrolyte concentration. The two effects together can be used to create different temporal trends in the particle size distributions. Faster agglomeration is attributed to the decrease in the electrostatic double layer repulsion forces which is due to decrease in the induced charge and the double layer thickness around the particle. Bigger particle clusters show lesser agglomeration due to reaching the equilibrium size. The procedures and processes described in this work can be used to generate more stable nanofluids.

Methylmercury production in and export from agricultural wetlands in California, USA: the need to account for physical transport processes into and out of the root zone

USGS Publications Warehouse

Bachand, Philip A.M.; Bachand, Sandra M.; Fleck, Jacob A.; Alpers, Charles N.; Stephenson, Mark; Windham-Myers, Lisamarie

2014-01-01

Concentration and mass balance analyses were used to quantify methylmercury (MeHg) loads from conventional (white) rice, wild rice, and fallowed fields in northern California's Yolo Bypass. These analyses were standardized against chloride to distinguish transport pathways and net ecosystem production (NEP). During summer, chloride loads were both exported with surface water and moved into the root zone at a 2:1 ratio. MeHg and dissolved organic carbon (DOC) behaved similarly with surface water and root zone exports at ~ 3:1 ratio. These trends reversed in winter with DOC, MeHg, and chloride moving from the root zone to surface waters at rates opposite and exceeding summertime root zone fluxes. These trends suggest that summer transpiration advectively moves constituents from surface water into the root zone, and winter diffusion, driven by concentration gradients, subsequently releases those constituents into surface waters. The results challenge a number of paradigms regarding MeHg. Specifically, biogeochemical conditions favoring microbial MeHg production do not necessarily translate to synchronous surface water exports; MeHg may be preserved in the soils allowing for release at a later time; and plants play a role in both biogeochemistry and transport. Our calculations show that NEP of MeHg occurred during both summer irrigation and winter flooding. Wild rice wet harvesting and winter flooding of white rice fields were specific practices that increased MeHg export, both presumably related to increased labile organic carbon and disturbance. Outflow management during these times could reduce MeHg exports. Standardizing MeHg outflow:inflow concentration ratios against natural tracers (e.g. chloride, EC) provides a simple tool to identify NEP periods. Summer MeHg exports averaged 0.2 to 1 μg m− 2 for the different agricultural wetland fields, depending upon flood duration. Average winter MeHg exports were estimated at 0.3 μg m− 2. These exports are within the range reported for other shallow aquatic systems.

Methylmercury production in and export from agricultural wetlands in California, USA: the need to account for physical transport processes into and out of the root zone.

PubMed

Bachand, P A M; Bachand, S M; Fleck, J A; Alpers, C N; Stephenson, M; Windham-Myers, L

2014-02-15

Concentration and mass balance analyses were used to quantify methylmercury (MeHg) loads from conventional (white) rice, wild rice, and fallowed fields in northern California's Yolo Bypass. These analyses were standardized against chloride to distinguish transport pathways and net ecosystem production (NEP). During summer, chloride loads were both exported with surface water and moved into the root zone at a 2:1 ratio. MeHg and dissolved organic carbon (DOC) behaved similarly with surface water and root zone exports at ~3:1 ratio. These trends reversed in winter with DOC, MeHg, and chloride moving from the root zone to surface waters at rates opposite and exceeding summertime root zone fluxes. These trends suggest that summer transpiration advectively moves constituents from surface water into the root zone, and winter diffusion, driven by concentration gradients, subsequently releases those constituents into surface waters. The results challenge a number of paradigms regarding MeHg. Specifically, biogeochemical conditions favoring microbial MeHg production do not necessarily translate to synchronous surface water exports; MeHg may be preserved in the soils allowing for release at a later time; and plants play a role in both biogeochemistry and transport. Our calculations show that NEP of MeHg occurred during both summer irrigation and winter flooding. Wild rice wet harvesting and winter flooding of white rice fields were specific practices that increased MeHg export, both presumably related to increased labile organic carbon and disturbance. Outflow management during these times could reduce MeHg exports. Standardizing MeHg outflow:inflow concentration ratios against natural tracers (e.g. chloride, EC) provides a simple tool to identify NEP periods. Summer MeHg exports averaged 0.2 to 1 μg m(-2) for the different agricultural wetland fields, depending upon flood duration. Average winter MeHg exports were estimated at 0.3 μg m(-2). These exports are within the range reported for other shallow aquatic systems. Copyright © 2013 Elsevier B.V. All rights reserved.

Application of image processing to calculate the number of fish seeds using raspberry-pi

NASA Astrophysics Data System (ADS)

Rahmadiansah, A.; Kusumawardhani, A.; Duanto, F. N.; Qoonita, F.

2018-03-01

Many fish cultivator in Indonesia who suffered losses due to the sale and purchase of fish seeds did not match the agreed amount. The loss is due to the calculation of fish seed still using manual method. To overcome these problems, then in this study designed fish counting system automatically and real-time fish using the image processing based on Raspberry Pi. Used image processing because it can calculate moving objects and eliminate noise. Image processing method used to calculate moving object is virtual loop detector or virtual detector method and the approach used is “double difference image”. The “double difference” approach uses information from the previous frame and the next frame to estimate the shape and position of the object. Using these methods and approaches, the results obtained were quite good with an average error of 1.0% for 300 individuals in a test with a virtual detector width of 96 pixels and a slope of 1 degree test plane.

Towards an optimal flow: Density-of-states-informed replica-exchange simulations

DOE PAGES

Vogel, Thomas; Perez, Danny

2015-11-05

Here we learn that replica exchange (RE) is one of the most popular enhanced-sampling simulations technique in use today. Despite widespread successes, RE simulations can sometimes fail to converge in practical amounts of time, e.g., when sampling around phase transitions, or when a few hard-to-find configurations dominate the statistical averages. We introduce a generalized RE scheme, density-of-states-informed RE, that addresses some of these challenges. The key feature of our approach is to inform the simulation with readily available, but commonly unused, information on the density of states of the system as the RE simulation proceeds. This enables two improvements, namely,more » the introduction of resampling moves that actively move the system towards equilibrium and the continual adaptation of the optimal temperature set. As a consequence of these two innovations, we show that the configuration flow in temperature space is optimized and that the overall convergence of RE simulations can be dramatically accelerated.« less

Food price seasonality in Africa: Measurement and extent.

PubMed

Gilbert, Christopher L; Christiaensen, Luc; Kaminski, Jonathan

2017-02-01

Everyone knows about seasonality. But what exactly do we know? This study systematically measures seasonal price gaps at 193 markets for 13 food commodities in seven African countries. It shows that the commonly used dummy variable or moving average deviation methods to estimate the seasonal gap can yield substantial upward bias. This can be partially circumvented using trigonometric and sawtooth models, which are more parsimonious. Among staple crops, seasonality is highest for maize (33 percent on average) and lowest for rice (16½ percent). This is two and a half to three times larger than in the international reference markets. Seasonality varies substantially across market places but maize is the only crop in which there are important systematic country effects. Malawi, where maize is the main staple, emerges as exhibiting the most acute seasonal differences. Reaching the Sustainable Development Goal of Zero Hunger requires renewed policy attention to seasonality in food prices and consumption.

Phase transformation of mixed-phase clouds

NASA Astrophysics Data System (ADS)

Korolev, Alexei; Isaac, George

2003-01-01

The glaciation time of a mixed-phase cloud due to the Wegener-Bergeron-Findeisen mechanism is calculated using an adiabatic one-dimensional numerical model for the cases of zero, ascending, descending and oscillating vertical velocities. The characteristic values of the glaciation time are obtained for different concentrations of ice particles and liquid-water content. Steady state is not possible for the ice-water content/total water content ratio in a uniformly vertically moving mixed-phase parcel. The vertical oscillation of a cloud parcel may result in a periodic evaporation and activation of liquid droplets in the presence of ice particles during infinite time. After a certain time, the average ice-water content and liquid-water content reach a steady state. This phenomenon may explain the existence of long-lived mixed-phase stratiform layers. The obtained results are important for understanding the mechanisms of formation and life cycle of mixed-phase clouds.

Ambient noise correlations on a mobile, deformable array.

PubMed

Naughton, Perry; Roux, Philippe; Yeakle, Riley; Schurgers, Curt; Kastner, Ryan; Jaffe, Jules S; Roberts, Paul L D

2016-12-01

This paper presents a demonstration of ambient acoustic noise processing on a set of free floating oceanic receivers whose relative positions vary with time. It is shown that it is possible to retrieve information that is relevant to the travel time between the receivers. With thousands of short time cross-correlations (10 s) of varying distance, it is shown that on average, the decrease in amplitude of the noise correlation function with increased separation follows a power law. This suggests that there may be amplitude information that is embedded in the noise correlation function. An incoherent beamformer is developed, which shows that it is possible to determine a source direction using an array with moving elements and large element separation. This incoherent beamformer is used to verify cases when the distribution of noise sources in the ocean allows one to recover travel time information between pairs of mobile receivers.

Video enhancement workbench: an operational real-time video image processing system

NASA Astrophysics Data System (ADS)

Yool, Stephen R.; Van Vactor, David L.; Smedley, Kirk G.

1993-01-01

Video image sequences can be exploited in real-time, giving analysts rapid access to information for military or criminal investigations. Video-rate dynamic range adjustment subdues fluctuations in image intensity, thereby assisting discrimination of small or low- contrast objects. Contrast-regulated unsharp masking enhances differentially shadowed or otherwise low-contrast image regions. Real-time removal of localized hotspots, when combined with automatic histogram equalization, may enhance resolution of objects directly adjacent. In video imagery corrupted by zero-mean noise, real-time frame averaging can assist resolution and location of small or low-contrast objects. To maximize analyst efficiency, lengthy video sequences can be screened automatically for low-frequency, high-magnitude events. Combined zoom, roam, and automatic dynamic range adjustment permit rapid analysis of facial features captured by video cameras recording crimes in progress. When trying to resolve small objects in murky seawater, stereo video places the moving imagery in an optimal setting for human interpretation.

Non-intrusive parameter identification procedure user's guide

NASA Technical Reports Server (NTRS)

Hanson, G. D.; Jewell, W. F.

1983-01-01

Written in standard FORTRAN, NAS is capable of identifying linear as well as nonlinear relations between input and output parameters; the only restriction is that the input/output relation be linear with respect to the unknown coefficients of the estimation equations. The output of the identification algorithm can be specified to be in either the time domain (i.e., the estimation equation coefficients) or in the frequency domain (i.e., a frequency response of the estimation equation). The frame length ("window") over which the identification procedure is to take place can be specified to be any portion of the input time history, thereby allowing the freedom to start and stop the identification procedure within a time history. There also is an option which allows a sliding window, which gives a moving average over the time history. The NAS software also includes the ability to identify several assumed solutions simultaneously for the same or different input data.

Spectral analysis based on fast Fourier transformation (FFT) of surveillance data: the case of scarlet fever in China.

PubMed

Zhang, T; Yang, M; Xiao, X; Feng, Z; Li, C; Zhou, Z; Ren, Q; Li, X

2014-03-01

Many infectious diseases exhibit repetitive or regular behaviour over time. Time-domain approaches, such as the seasonal autoregressive integrated moving average model, are often utilized to examine the cyclical behaviour of such diseases. The limitations for time-domain approaches include over-differencing and over-fitting; furthermore, the use of these approaches is inappropriate when the assumption of linearity may not hold. In this study, we implemented a simple and efficient procedure based on the fast Fourier transformation (FFT) approach to evaluate the epidemic dynamic of scarlet fever incidence (2004-2010) in China. This method demonstrated good internal and external validities and overcame some shortcomings of time-domain approaches. The procedure also elucidated the cycling behaviour in terms of environmental factors. We concluded that, under appropriate circumstances of data structure, spectral analysis based on the FFT approach may be applicable for the study of oscillating diseases.

Mean first passage time of active Brownian particle in one dimension

NASA Astrophysics Data System (ADS)

Scacchi, A.; Sharma, A.

2018-02-01

We investigate the mean first passage time of an active Brownian particle in one dimension using numerical simulations. The activity in one dimension is modelled as a two state model; the particle moves with a constant propulsion strength but its orientation switches from one state to other as in a random telegraphic process. We study the influence of a finite resetting rate r on the mean first passage time to a fixed target of a single free active Brownian particle and map this result using an effective diffusion process. As in the case of a passive Brownian particle, we can find an optimal resetting rate r* for an active Brownian particle for which the target is found with the minimum average time. In the case of the presence of an external potential, we find good agreement between the theory and numerical simulations using an effective potential approach.

ARMA models for earthquake ground motions. Seismic safety margins research program

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

Chang, M. K.; Kwiatkowski, J. W.; Nau, R. F.

1981-02-01

Four major California earthquake records were analyzed by use of a class of discrete linear time-domain processes commonly referred to as ARMA (Autoregressive/Moving-Average) models. It was possible to analyze these different earthquakes, identify the order of the appropriate ARMA model(s), estimate parameters, and test the residuals generated by these models. It was also possible to show the connections, similarities, and differences between the traditional continuous models (with parameter estimates based on spectral analyses) and the discrete models with parameters estimated by various maximum-likelihood techniques applied to digitized acceleration data in the time domain. The methodology proposed is suitable for simulatingmore » earthquake ground motions in the time domain, and appears to be easily adapted to serve as inputs for nonlinear discrete time models of structural motions. 60 references, 19 figures, 9 tables.« less

Temporal and long-term trend analysis of class C notifiable diseases in China from 2009 to 2014

PubMed Central

Zhang, Xingyu; Hou, Fengsu; Qiao, Zhijiao; Li, Xiaosong; Zhou, Lijun; Liu, Yuanyuan; Zhang, Tao

2016-01-01

Objectives Time series models are effective tools for disease forecasting. This study aims to explore the time series behaviour of 11 notifiable diseases in China and to predict their incidence through effective models. Settings and participants The Chinese Ministry of Health started to publish class C notifiable diseases in 2009. The monthly reported case time series of 11 infectious diseases from the surveillance system between 2009 and 2014 was collected. Methods We performed a descriptive and a time series study using the surveillance data. Decomposition methods were used to explore (1) their seasonality expressed in the form of seasonal indices and (2) their long-term trend in the form of a linear regression model. Autoregressive integrated moving average (ARIMA) models have been established for each disease. Results The number of cases and deaths caused by hand, foot and mouth disease ranks number 1 among the detected diseases. It occurred most often in May and July and increased, on average, by 0.14126/100 000 per month. The remaining incidence models show good fit except the influenza and hydatid disease models. Both the hydatid disease and influenza series become white noise after differencing, so no available ARIMA model can be fitted for these two diseases. Conclusion Time series analysis of effective surveillance time series is useful for better understanding the occurrence of the 11 types of infectious disease. PMID:27797981

Human Kinematics of Cochlear Implant Surgery: An Investigation of Insertion Micro-Motions and Speed Limitations.

PubMed

Kesler, Kyle; Dillon, Neal P; Fichera, Loris; Labadie, Robert F

2017-09-01

Objectives Document human motions associated with cochlear implant electrode insertion at different speeds and determine the lower limit of continuous insertion speed by a human. Study Design Observational. Setting Academic medical center. Subjects and Methods Cochlear implant forceps were coupled to a frame containing reflective fiducials, which enabled optical tracking of the forceps' tip position in real time. Otolaryngologists (n = 14) performed mock electrode insertions at different speeds based on recommendations from the literature: "fast" (96 mm/min), "stable" (as slow as possible without stopping), and "slow" (15 mm/min). For each insertion, the following metrics were calculated from the tracked position data: percentage of time at prescribed speed, percentage of time the surgeon stopped moving forward, and number of direction reversals (ie, going from forward to backward motion). Results Fast insertion trials resulted in better adherence to the prescribed speed (45.4% of the overall time), no motion interruptions, and no reversals, as compared with slow insertions (18.6% of time at prescribed speed, 15.7% stopped time, and an average of 18.6 reversals per trial). These differences were statistically significant for all metrics ( P < .01). The metrics for the fast and stable insertions were comparable; however, stable insertions were performed 44% slower on average. The mean stable insertion speed was 52 ± 19.3 mm/min. Conclusion Results indicate that continuous insertion of a cochlear implant electrode at 15 mm/min is not feasible for human operators. The lower limit of continuous forward insertion is 52 mm/min on average. Guidelines on manual insertion kinematics should consider this practical limit of human motion.

Suitability of a structured Fundamental Movement Skills program for long day care centres: a process evaluation.

PubMed

Petrunoff, Nick; Lloyd, Beverley; Watson, Natalie; Morrisey, David

2009-04-01

Early childhood presents an opportunity to encourage development of Fundamental Movement Skills (FMS). Implementation of a structured program in the Long Day Care (LDC) setting presents challenges. Implementation of a structured FMS program FunMoves was assessed in LDC in metropolitan New South Wales. LDC staff attended a training session conducted by trained Health Promotion Officers (HPOs) and completed an evaluation. During implementation HPOs completed lesson observations. De-identified attendance data was collected and director and staff feedback on the program including barriers to implementation was obtained via questionnaire. Qualitative information relevant to process evaluation was obtained via open questions on questionnaires, and a de-brief diary recording feedback from directors and staff. Knowledge of FMS and FunMoves and staff confidence to deliver the program were high after training. On average, staff stated they ran lessons more than the suggested twice weekly and the majority of children attended 1-3 lessons per week. However, lesson delivery was not as designed, and staff found FunMoves disruptive and time consuming. Six directors and the majority of staff thought that FunMoves could be improved. Structured program delivery was hampered by contextual issues including significant staff turnover and program length and structure being at odds with the setting. Implementation could be enhanced by guidelines for more flexible delivery options including less structured approaches, shorter and simpler lessons, ongoing conversations with the early childhood sector, in-centre engagement of staff and post-training support.

Tracking Movements of Individual Anoplophora glabripennis (Coleoptera: Cerambycidae) Adults: Application of Harmonic Radar

Treesearch

David W. Williams; Guohong Li; Ruitong Gao

2004-01-01

Movements of 55 Anoplophora glabripennis (Motschulsky) adults were monitored on 200 willow trees, Salix babylonica L., at a site appx. 80 km southeast of Beijing, China, for 9-14 d in an individual mark-recapture study using harmonic radar. The average movement distance was appx. 14 m, with many beetles not moving at all and others moving >90 m. The rate of movement...

Rootless shield and perched lava pond collapses at Kīlauea Volcano, Hawai'i

USGS Publications Warehouse

Patrick, Matthew R.; Orr, Tim R.

2012-01-01

Effusion rate is a primary measurement used to judge the expected advance rate, length, and hazard potential of lava flows. At basaltic volcanoes, the rapid draining of lava stored in rootless shields and perched ponds can produce lava flows with much higher local effusion rates and advance velocities than would be expected based on the effusion rate at the vent. For several months in 2007–2008, lava stored in a series of perched ponds and rootless shields on Kīlauea Volcano, Hawai'i, was released episodically to produce fast-moving 'a'ā lava flows. Several of these lava flows approached Royal Gardens subdivision and threatened the safety of remaining residents. Using time-lapse image measurements, we show that the initial time-averaged discharge rate for one collapse-triggered lava flow was approximately eight times greater than the effusion rate at the vent. Though short-lived, the collapse-triggered 'a'ā lava flows had average advance rates approximately 45 times greater than that of the pāhoehoe flow field from which they were sourced. The high advance rates of the collapse-triggered lava flows demonstrates that recognition of lava accumulating in ponds and shields, which may be stored in a cryptic manner, is vital for accurately assessing short-term hazards at basaltic volcanoes.

Movements and bioenergetics of canvasbacks wintering in the upper Chesapeake Bay

USGS Publications Warehouse

Howerter, D.W.

1990-01-01

The movement patterns, range areas and energetics of canvasbacks (Aythya valisineria) wintering in the upper Chesapeake Bay, Maryland, were investigated. Eighty-seven juvenile female canvasbacks were radio-tracked between 30 December 1988 and 25 March 1989. Diurnal time and energy budgets were constructed for a time of day-season matrix for canvasbacks using riverine and main bay habitats. Canvasbacks were very active at night, making regular and often lengthy crepuscular movements (x = 11.7 km) from near shore habitats during the day to off shore habitats at night. Movement patterns were similar for birds using habitats on the eastern and western shores of the Bay. Canvasbacks had extensive home ranges averaging 14,286 ha, and used an average of 1.97 core areas. Sleeping was the predominant diurnal behavior. Telemetry indicated that canvasbacks actively fed at night. Canvasbacks spent more time in active behaviors (e.g. swimming, alert) on the eastern shore than on the western shore. Similarly, canvasbacks were more active during daytime hours at locations where artificial feeding occurred. Behavioral patterns were only weakly correlated with weather patterns. Canvasbacks appeared to reduce energy expenditure in mid-winter by reducing distances moved, reducing feeding activities and increasing the amount of time spent sleeping. This pattern was observed even though 1988-89 mid-winter weather conditions were very mild.

Beyond Horse Race Comparisons of National Performance Averages: Math Performance Variation within and between Classrooms in 38 Countries

ERIC Educational Resources Information Center

Huang, Min-Hsiung

2009-01-01

Reports of international studies of student achievement often receive public attention worldwide. However, this attention overly focuses on the national rankings of average student performance. To move beyond the simplistic comparison of national mean scores, this study investigates (a) country differences in the measures of variability as well as…

Impact of smoking on in-vehicle fine particle exposure during driving

NASA Astrophysics Data System (ADS)

Sohn, Hongji; Lee, Kiyoung

2010-09-01

Indoor smoking ban in public places can reduce secondhand smoke (SHS) exposure. However, smoking in cars and homes has continued. The purpose of this study was to assess particulate matter less than 2.5 μm (PM 2.5) concentration in moving cars with different window opening conditions. The PM 2.5 level was measured by an aerosol spectrometer inside and outside moving cars simultaneously, along with ultrafine particle (UFP) number concentration, speed, temperature and humidity inside cars. Two sport utility vehicles were used. Three different ventilation conditions were evaluated by up to 20 repeated experiments. In the pre-smoking phase, average in-vehicle PM 2.5 concentrations were 16-17 μg m -3. Regardless of different window opening conditions, the PM 2.5 levels promptly increased when smoking occurred and decreased after cigarette was extinguished. Although only a single cigarette was smoked, the average PM 2.5 levels were 506-1307 μg m -3 with different window opening conditions. When smoking was ceased, the average PM 2.5 levels for 15 min were several times higher than the US National Ambient Air Quality Standard of 35 μg m -3. It took longer than 10 min to reach the level of the pre-smoking phase. Although UFP levels had a similar temporal profile of PM 2.5, the increased levels during the smoking phase were relatively small. This study demonstrated that the SHS exposure in cars with just a single cigarette being smoked could exceed the US EPA NAAQS under realistic window opening conditions. Therefore, the findings support the need for public education against smoking in cars and advocacy for a smoke-free car policy.

Fluvial sediments a summary of source, transportation, deposition, and measurement of sediment discharge

USGS Publications Warehouse

Colby, B.R.

1963-01-01

This paper presents a broad but undetailed picture of fluvial sediments in streams, reservoirs, and lakes and includes a discussion of the processes involved in the movement of sediment by flowing water. Sediment is fragmental material that originates from the chemical or physical disintegration of rocks. The disintegration products may have many different shapes and may range in size from large boulders to colloidal particles. In general, they retain about the same mineral composition as the parent rocks. Rock fragments become fluvial sediment when they are entrained in a stream of water. The entrainment may occur as sheet erosion from land surfaces, particularly for the fine particles, or as channel erosion after the surface runoff has accumulated in streams. Fluvial sediments move in streams as bedload (particles moving within a few particle diameters of the streambed) or as suspended sediment in the turbulent flow. The discharge of bedload varies with several factors, which may include particle size and a type of effective shear on the surface of the streambed. The discharge of suspended sediment depends partly on concentration of moving sediment near the streambed and hence on discharge of bedload. However, the concentration of fine sediment near the streambed varies widely, even for equal flows, and, therefore, the discharge of fine sediment normally cannot be computed theoretically. The discharge of suspended sediment also depends on velocity, turbulence, depth of flow, and fall velocity of the particles. In general, the coarse sediment transported by a stream moves intermittently and is discharged at a rate that depends on properties of the flow and of the sediment. If an ample supply of coarse sediment is available at the surface of the streambed, the discharge of the coarse sediment, such as sand, can be roughly computed from properties of the available sediment and of the flow. On the other hand, much of the fine sediment in a stream usually moves nearly continuously at about the velocity of the flow, and even low flows can transport large amounts of fine sediment. Hence, the discharge of fine sediments, being largely dependent on the availability of fine sediment upstream rather than on the properties of the sediment and of the flow at a cross section, can seldom be computed from properties, other than concentrations based directly on samples, that can be observed at the cross section. Sediment particles continually change their positions in the flow; some fall to the streambed, and others are removed from the bed. Sediment deposits form locally or over large areas if the volume rate at which particles settle to the bed exceeds the volume rate at which particles are removed from the bed. In general, large particles are deposited more readily than small particles, whether the point of deposition is behind a rock, on a flood plain, within a stream channel, or at the entrance to a reservoir, a lake, or the ocean. Most samplers used for sediment observations collect a water-sediment mixture from the water surface to within a few tenths of a foot of the streambed. They thus sample most of the suspended sediment, especially if the flow is deep or if the sediment is mostly fine; but they exclude the bedload and some of the suspended sediment in a layer near the streambed where the suspended-sediment concentrations are highest. Measured sediment discharges are usually based on concentrations that are averages of several individual sediment samples for a cross section. If enough average concentrations for a cross section have been determined, the measured sediment discharge can be computed by interpolating sediment concentrations between sampling times. If only occasional samples were collected, an average relation between sediment discharge and flow can be used with a flow-duration curve to compute roughly the average or the total sediment discharges for any periods of time for which the flow-duration c

Short-Term Mortality Rates during a Decade of Improved Air Quality in Erfurt, Germany

PubMed Central

Breitner, Susanne; Stölzel, Matthias; Cyrys, Josef; Pitz, Mike; Wölke, Gabriele; Kreyling, Wolfgang; Küchenhoff, Helmut; Heinrich, Joachim; Wichmann, H.-Erich; Peters, Annette

2009-01-01

Background Numerous studies have shown associations between ambient air pollution and daily mortality. Objectives Our goal was to investigate the association of ambient air pollution and daily mortality in Erfurt, Germany, over a 10.5-year period after the German unification, when air quality improved. Methods We obtained daily mortality counts and data on mass concentrations of particulate matter (PM) < 10 μm in aerodynamic diameter (PM10), gaseous pollutants, and meteorology in Erfurt between October 1991 and March 2002. We obtained ultrafine particle number concentrations (UFP) and mass concentrations of PM < 2.5 μm in aerodynamic diameter (PM2.5) from September 1995 to March 2002. We analyzed the data using semiparametric Poisson regression models adjusting for trend, seasonality, influenza epidemics, day of the week, and meteorology. We evaluated cumulative associations between air pollution and mortality using polynomial distributed lag (PDL) models and multiday moving averages of air pollutants. We evaluated changes in the associations over time in time-varying coefficient models. Results Air pollution concentrations decreased over the study period. Cumulative exposure to UFP was associated with increased mortality. An interquartile range (IQR) increase in the 15-day cumulative mean UFP of 7,649 cm−3 was associated with a relative risk (RR) of 1.060 [95% confidence interval (CI), 1.008–1.114] for PDL models and an RR/IQR of 1.055 (95% CI, 1.011–1.101) for moving averages. RRs decreased from the mid-1990s to the late 1990s. Conclusion Results indicate an elevated mortality risk from short-term exposure to UFP. They further suggest that RRs for short-term associations of air pollution decreased as pollution control measures were implemented in Eastern Germany. PMID:19337521

Effect of environmental factors on Internet searches related to sinusitis.

PubMed

Willson, Thomas J; Lospinoso, Joshua; Weitzel, Erik K; McMains, Kevin C

2015-11-01

Sinusitis significantly affects the population of the United States, exacting direct cost and lost productivity. Patients are likely to search the Internet for information related to their health before seeking care by a healthcare professional. Utilizing data generated from these searches may serve as an epidemiologic surrogate. A retrospective time series analysis was performed. Google search trend data from the Dallas-Fort Worth metro region for the years 2012 and 2013 were collected from www.google.com/trends for terms related to sinusitis based on literature outlining the most important symptoms for diagnosis. Additional terms were selected based on common English language terms used to describe the disease. Twelve months of data from the same time period and location for common pollutants (nitrogen dioxide, ozone, sulfur dioxide, and particulates), pollen and mold counts, and influenza-like illness were also collected. Statistical analysis was performed using Pearson correlation coefficients, and potential search activity predictors were assessed using autoregressive integrated moving average. Pearson correlation was strongest between the terms congestion and influenza-like illness (r=0.615), and sinus and influenza-like illness (r=0.534) and nitrogen dioxide (r=0.487). Autoregressive integrated moving average analysis revealed ozone, influenza-like illness, and nitrogen dioxide levels to be potential predictors for sinus pressure searches, with estimates of 0.118, 0.349, and 0.438, respectively. Nitrogen dioxide was also a potential predictor for the terms congestion and sinus, with estimates of 0.191 and 0.272, respectively. Google search activity for related terms follow the pattern of seasonal influenza-like illness and nitrogen dioxide. These data highlight the epidemiologic potential of this novel surveillance method. NA. © 2015 The American Laryngological, Rhinological and Otological Society, Inc.

Performance evaluation of ionospheric time delay forecasting models using GPS observations at a low-latitude station

NASA Astrophysics Data System (ADS)

Sivavaraprasad, G.; Venkata Ratnam, D.

2017-07-01

Ionospheric delay is one of the major atmospheric effects on the performance of satellite-based radio navigation systems. It limits the accuracy and availability of Global Positioning System (GPS) measurements, related to critical societal and safety applications. The temporal and spatial gradients of ionospheric total electron content (TEC) are driven by several unknown priori geophysical conditions and solar-terrestrial phenomena. Thereby, the prediction of ionospheric delay is challenging especially over Indian sub-continent. Therefore, an appropriate short/long-term ionospheric delay forecasting model is necessary. Hence, the intent of this paper is to forecast ionospheric delays by considering day to day, monthly and seasonal ionospheric TEC variations. GPS-TEC data (January 2013-December 2013) is extracted from a multi frequency GPS receiver established at K L University, Vaddeswaram, Guntur station (geographic: 16.37°N, 80.37°E; geomagnetic: 7.44°N, 153.75°E), India. An evaluation, in terms of forecasting capabilities, of three ionospheric time delay models - an Auto Regressive Moving Average (ARMA) model, Auto Regressive Integrated Moving Average (ARIMA) model, and a Holt-Winter's model is presented. The performances of these models are evaluated through error measurement analysis during both geomagnetic quiet and disturbed days. It is found that, ARMA model is effectively forecasting the ionospheric delay with an accuracy of 82-94%, which is 10% more superior to ARIMA and Holt-Winter's models. Moreover, the modeled VTEC derived from International Reference Ionosphere, IRI (IRI-2012) model and new global TEC model, Neustrelitz TEC Model (NTCM-GL) have compared with forecasted VTEC values of ARMA, ARIMA and Holt-Winter's models during geomagnetic quiet days. The forecast results are indicating that ARMA model would be useful to set up an early warning system for ionospheric disturbances at low latitude regions.

Statistical properties of the yuan exchange rate index

NASA Astrophysics Data System (ADS)

Wang, Dong-Hua; Yu, Xiao-Wen; Suo, Yuan-Yuan

2012-06-01

We choice the yuan exchange rate index based on a basket of currencies as the effective exchange rate of the yuan and investigate the statistical properties of the yuan exchange rate index after China's exchange rate system reform on the 21st July 2005. After dividing the time series into two parts according to the change in the yuan exchange rate regime in July 2008, we compare the statistical properties of the yuan exchange rate index during these two periods. We find that the distribution of the two return series has the exponential form. We also perform the detrending moving average analysis (DMA) and the multifractal detrending moving average analysis (MFDMA). The two periods possess different degrees of long-range correlations, and the multifractal nature is also unveiled in these two time series. Significant difference is found in the scaling exponents τ(q) and singularity spectra f(α) of the two periods obtained from the MFDMA analysis. Besides, in order to detect the sources of multifractality, shuffling and phase randomization procedures are applied to destroy the long-range temporal correlation and fat-tailed distribution of the yuan exchange rate index respectively. We find that the fat-tailedness plays a critical role in the sources of multifractality in the first period, while the long memory is the major cause in the second period. The results suggest that the change in China's exchange rate regime in July 2008 gives rise to the different multifractal properties of the yuan exchange rate index in these two periods, and thus has an effect on the effective exchange rate of the yuan after the exchange rate reform on the 21st July 2005.

Application of seasonal auto-regressive integrated moving average model in forecasting the incidence of hand-foot-mouth disease in Wuhan, China.

PubMed

Peng, Ying; Yu, Bin; Wang, Peng; Kong, De-Guang; Chen, Bang-Hua; Yang, Xiao-Bing

2017-12-01

Outbreaks of hand-foot-mouth disease (HFMD) have occurred many times and caused serious health burden in China since 2008. Application of modern information technology to prediction and early response can be helpful for efficient HFMD prevention and control. A seasonal auto-regressive integrated moving average (ARIMA) model for time series analysis was designed in this study. Eighty-four-month (from January 2009 to December 2015) retrospective data obtained from the Chinese Information System for Disease Prevention and Control were subjected to ARIMA modeling. The coefficient of determination (R 2 ), normalized Bayesian Information Criterion (BIC) and Q-test P value were used to evaluate the goodness-of-fit of constructed models. Subsequently, the best-fitted ARIMA model was applied to predict the expected incidence of HFMD from January 2016 to December 2016. The best-fitted seasonal ARIMA model was identified as (1,0,1)(0,1,1) 12 , with the largest coefficient of determination (R 2 =0.743) and lowest normalized BIC (BIC=3.645) value. The residuals of the model also showed non-significant autocorrelations (P Box-Ljung (Q) =0.299). The predictions by the optimum ARIMA model adequately captured the pattern in the data and exhibited two peaks of activity over the forecast interval, including a major peak during April to June, and again a light peak for September to November. The ARIMA model proposed in this study can forecast HFMD incidence trend effectively, which could provide useful support for future HFMD prevention and control in the study area. Besides, further observations should be added continually into the modeling data set, and parameters of the models should be adjusted accordingly.

Statistical process control of mortality series in the Australian and New Zealand Intensive Care Society (ANZICS) adult patient database: implications of the data generating process

PubMed Central

2013-01-01

Background Statistical process control (SPC), an industrial sphere initiative, has recently been applied in health care and public health surveillance. SPC methods assume independent observations and process autocorrelation has been associated with increase in false alarm frequency. Methods Monthly mean raw mortality (at hospital discharge) time series, 1995–2009, at the individual Intensive Care unit (ICU) level, were generated from the Australia and New Zealand Intensive Care Society adult patient database. Evidence for series (i) autocorrelation and seasonality was demonstrated using (partial)-autocorrelation ((P)ACF) function displays and classical series decomposition and (ii) “in-control” status was sought using risk-adjusted (RA) exponentially weighted moving average (EWMA) control limits (3 sigma). Risk adjustment was achieved using a random coefficient (intercept as ICU site and slope as APACHE III score) logistic regression model, generating an expected mortality series. Application of time-series to an exemplar complete ICU series (1995-(end)2009) was via Box-Jenkins methodology: autoregressive moving average (ARMA) and (G)ARCH ((Generalised) Autoregressive Conditional Heteroscedasticity) models, the latter addressing volatility of the series variance. Results The overall data set, 1995-2009, consisted of 491324 records from 137 ICU sites; average raw mortality was 14.07%; average(SD) raw and expected mortalities ranged from 0.012(0.113) and 0.013(0.045) to 0.296(0.457) and 0.278(0.247) respectively. For the raw mortality series: 71 sites had continuous data for assessment up to or beyond lag40 and 35% had autocorrelation through to lag40; and of 36 sites with continuous data for ≥ 72 months, all demonstrated marked seasonality. Similar numbers and percentages were seen with the expected series. Out-of-control signalling was evident for the raw mortality series with respect to RA-EWMA control limits; a seasonal ARMA model, with GARCH effects, displayed white-noise residuals which were in-control with respect to EWMA control limits and one-step prediction error limits (3SE). The expected series was modelled with a multiplicative seasonal autoregressive model. Conclusions The data generating process of monthly raw mortality series at the ICU level displayed autocorrelation, seasonality and volatility. False-positive signalling of the raw mortality series was evident with respect to RA-EWMA control limits. A time series approach using residual control charts resolved these issues. PMID:23705957

Simulations of moving effect of coastal vegetation on tsunami damping

NASA Astrophysics Data System (ADS)

Tsai, Ching-Piao; Chen, Ying-Chi; Octaviani Sihombing, Tri; Lin, Chang

2017-05-01

A coupled wave-vegetation simulation is presented for the moving effect of the coastal vegetation on tsunami wave height damping. The problem is idealized by solitary wave propagation on a group of emergent cylinders. The numerical model is based on general Reynolds-averaged Navier-Stokes equations with renormalization group turbulent closure model by using volume of fluid technique. The general moving object (GMO) model developed in computational fluid dynamics (CFD) code Flow-3D is applied to simulate the coupled motion of vegetation with wave dynamically. The damping of wave height and the turbulent kinetic energy along moving and stationary cylinders are discussed. The simulated results show that the damping of wave height and the turbulent kinetic energy by the moving cylinders are clearly less than by the stationary cylinders. The result implies that the wave decay by the coastal vegetation may be overestimated if the vegetation was represented as stationary state.

SU-E-T-755: Timing Characteristics of Proton and Carbon Ion Treatments Using a Synchrotron and Modulated Scanning

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

Zhao, J; Li, Y; Huang, Z

2015-06-15

Purpose: The time required to deliver a treatment impacts not only the number of patients that can be treated each day but also the accuracy of delivery due to potential movements of patient tissues. Both macroscopic and microscopic timing characteristics of a beam delivery system were studied to examine their impacts on patient treatments. Methods: 35 patients were treated during a clinical trial to demonstrate safety and efficacy of a Siemens Iontris system prior to receiving approval from the Chinese Food and Drug Administration. The system has a variable cycle time and can provide proton beams from 48 to 221more » MeV/n and carbon ions from 86 to 430 MeV/n. A modulated scanning beam delivery technique is used where the beam remains stationary at each spot aiming location and is not turned off while the spot quickly moves from one aiming location to the next. The treatment log files for 28 of the trial patients were analyzed to determine several timing characteristics. Results: The average portal time per target dose was 172.5 s/Gy for protons and 150.7 s/Gy for carbon ions. The maximum delivery time for any portal was less than 300 s. The average dwell time per spot was 12 ms for protons and 3.0 ms for carbon ions. The number of aiming positions per energy layer varied from 1 to 258 for protons and 1 to 621 for carbon ions. The average spill time and cycle time per energy layer were 1.20 and 2.68 s for protons and 0.95 and 4.73 s for carbon ions respectively. For 3 of the patients, the beam was gated on and off to reduce the effects of respiration. Conclusion: For a typical target volume of 153 cc as used in this clinical trial, the portal delivery times were acceptable.« less

On the rationality of cycling in the Theory of Moves framework

NASA Astrophysics Data System (ADS)

Olsen, Jolie; Sen, Sandip

2014-04-01

Theory of Moves (TOM) is a novel approach to game theory for determining rational strategies during the play of dynamic games [Brams, S J. (1994). Theory of moves. Cambridge, UK: Cambridge University Press]. While alternate models such as normal form games exist, players of these games are limited to single shot interactions with each other, but within TOM, sequences of moves and counter moves are allowed. As a consequence of this framework potential cyclic behaviour may arise. Unfortunately, standard TOM framework suggests that players do not move from the initial state if the possibility of cyclic behaviour is detected. However, in a plethora of real life scenarios, cycling can benefit a player over time. We first extend the TOM framework by allowing players to choose how much time to stay in each state while specifying time limits for moves. This generalisation allows for cycling behaviour in addition to normal, acyclic TOM play. We present additional rationality rules to handle the choice of move time and cyclic play and identify conditions for the existence of solutions that involve cycles. Moreover, if solutions do exist, equilibrium are determined so a player can predict the rational outcome upon engaging a cycle. A variety of time constraints on move times are investigated and the effects of these contrasts on the solution space and equilibrium are analysed.

Moving through time: the role of personality in three real-life contexts.

PubMed

Duffy, Sarah E; Feist, Michele I; McCarthy, Steven

2014-01-01

In English, two deictic space-time metaphors are in common usage: the Moving Ego metaphor conceptualizes the ego as moving forward through time and the Moving Time metaphor conceptualizes time as moving forward toward the ego (Clark, 1973). Although earlier research investigating the psychological reality of these metaphors has typically examined spatial influences on temporal reasoning (e.g., Boroditsky & Ramscar, 2002), recent lines of research have extended beyond this, providing initial evidence that personality differences and emotional experiences may also influence how people reason about events in time (Duffy & Feist, 2014; Hauser, Carter, & Meier, 2009; Richmond, Wilson, & Zinken, 2012). In this article, we investigate whether these relationships have force in real life. Building on the effects of individual differences in self-reported conscientiousness and procrastination found by Duffy and Feist (2014), we examined whether, in addition to self-reported conscientiousness and procrastination, there is a relationship between conscientious and procrastinating behaviors and temporal perspective. We found that participants who adopted the Moving Time perspective were more likely to exhibit conscientious behaviors, while those who adopted the Moving Ego perspective were more likely to procrastinate, suggesting that the earlier effects reach beyond the laboratory. Copyright © 2014 Cognitive Science Society, Inc.

Detached eddy simulation for turbulent fluid-structure interaction of moving bodies using the constraint-based immersed boundary method

NASA Astrophysics Data System (ADS)

Nangia, Nishant; Bhalla, Amneet P. S.; Griffith, Boyce E.; Patankar, Neelesh A.

2016-11-01

Flows over bodies of industrial importance often contain both an attached boundary layer region near the structure and a region of massively separated flow near its trailing edge. When simulating these flows with turbulence modeling, the Reynolds-averaged Navier-Stokes (RANS) approach is more efficient in the former, whereas large-eddy simulation (LES) is more accurate in the latter. Detached-eddy simulation (DES), based on the Spalart-Allmaras model, is a hybrid method that switches from RANS mode of solution in attached boundary layers to LES in detached flow regions. Simulations of turbulent flows over moving structures on a body-fitted mesh incur an enormous remeshing cost every time step. The constraint-based immersed boundary (cIB) method eliminates this operation by placing the structure on a Cartesian mesh and enforcing a rigidity constraint as an additional forcing in the Navier-Stokes momentum equation. We outline the formulation and development of a parallel DES-cIB method using adaptive mesh refinement. We show preliminary validation results for flows past stationary bodies with both attached and separated boundary layers along with results for turbulent flows past moving bodies. This work is supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE-1324585.

The forward undulatory locomotion of Ceanorhabditis elegans in viscoelastic fluids

NASA Astrophysics Data System (ADS)

Shen, Amy; Ulrich, Xialing

2013-11-01

Caenorhabditis elegans is a soil dwelling roundworm that has served as model organisms for studying a multitude of biological and engineering phenomena. We study the undulatory locomotion of nematode in viscoelastic fluids with zero-shear viscosity varying from 0.03-75 Pa .s and relaxation times ranging from 0-350 s. We observe that the averaged normalized wavelength of swimming worm is essentially the same as that in Newtonian fluids. The undulatory frequency f shows the same reduction rate with respect to zero-shear viscosity in viscoelastic fluids as that found in the Newtonian fluids, meaning that the undulatory frequency is mainly controlled by the fluid viscosity. However, the moving speed Vm of the worm shows more distinct dependence on the elasticity of the fluid and exhibits a 4% drop with each 10-fold increase of the Deborah number De, a dimensionless number characterizing the elasticity of a fluid. To estimate the swimming efficiency coefficient and the ratio K =CN /CL of resistive coefficients of the worm in various viscoelastic fluids, we show that whereas it would take the worm around 7 periods to move a body length in a Newtonian fluid, it would take 27 periods to move a body length in a highly viscoelastic fluid.

Mallard brood movements, wetland use, and duckling survival during and following a prairie drought

USGS Publications Warehouse

Krapu, G.L.; Pietz, P.J.; Brandt, D.A.; Cox, R.R.

2006-01-01

We used radiotelemetry to study mallard (Anas platyrhynchos) brood movements, wetland use, and duckling survival during a major drought (1988-1992) and during the first 2 years of the subsequent wet period (1993-1994) at 4 51-km2 sites in prairie pothole landscapes in eastern North Dakota, USA. About two-thirds of 69 radiomarked mallard broods initiated moves from the nest to water before noon, and all left the nest during daylight. On average, broods used fewer wetlands, but moved greater distances during the dry period than the wet period. Broods of all ages were more likely to make inter-wetland moves during the wet period and probabilities of inter-wetland moves decreased as duckling age increased, especially during the dry period. Brood use of seasonal wetlands nearly doubled from 22% to 43% and use of semi-permanent wetlands declined from 73% to 50% from the dry to the wet period. Eighty-one of 150 radiomarked ducklings died during 1,604 exposure days. We evaluated survival models containing variables related to water conditions, weather, duckling age, and hatch date. Model-averaged risk ratios indicated that, on any given date, radiomarked ducklings were 1.5 (95% CI = 0.8-2.8) times more likely to die when the percentage of seasonal basins containing water (WETSEAS) was ???18% than when WETSEAS was >40%. An interaction between duckling age and occurrence of rain on the current or 2 previous days indicated that rain effects were pronounced when ducklings were 0-7 days old but negligible when they were 8-30 days old. The TMIN (mean daily minimum temperature on the current and 2 previous days) effects generally were consistent between duckling age classes, and the risk of duckling death increased 9.3% for each 1??C decrease in TMIN across both age classes. Overall, the 30-day survival rate of ducklings equipped with radiotransmitters was about 0.23 lower than the survival rate of those without radiotransmitiers. Unmarked ducklings were 7.6 (95% CI = 2.7-21.3) times more likely to die on any given day when WETSEAS was ???18% than when WETSEAS was >40%. Higher duckling survival and increased use of seasonal wetlands during the wet period suggest that mallard production will benefit from programs that conserve and restore seasonal wetland habitat. Given adverse effects of low temperatures on duckling survival, managers may want to include this stochastic variable in models used to predict annual production of mallards in the Prairie Pothole Region.

Spatial and temporal distribution of airborne Bacillus thuringiensis var. kurstaki during an aerial spray program for gypsy moth eradication.

PubMed

Teschke, K; Chow, Y; Bartlett, K; Ross, A; van Netten, C

2001-01-01

We measured airborne exposures to the biological insecticide Bacillus thuringiensis var. kurstaki (Btk) during an aerial spray program to eradicate gypsy moths on the west coast of Canada. We aimed to determine whether staying indoors during spraying reduced exposures, to determine the rate of temporal decay of airborne concentrations, and to determine whether drift occurred outside the spray zone. During spraying, the average culturable airborne Btk concentration measured outdoors within the spray zone was 739 colony-forming units (CFU)/m3 of air. Outdoor air concentrations decreased over time, quickly in an initial phase with a half time of 3.3 hr, and then more slowly over the following 9 days, with an overall half-time of about 2.4 days. Inside residences during spraying, average concentrations were initially 2-5 times lower than outdoors, but at 5-6 hr after spraying began, indoor concentrations exceeded those outdoors, with an average of 244 CFU/m3 vs. 77 CFU/m3 outdoors, suggesting that the initial benefits of remaining indoors during spraying may not persist as outside air moves indoors with normal daily activities. There was drift of culturable Btk throughout a 125- to 1,000-meter band outside the spray zone where measurements were made, a consequence of the fine aerosol sizes that remained airborne (count median diameters of 4.3 to 7.2 microm). Btk concentrations outside the spray zone were related to wind speed and direction, but not to distance from the spray zone.

Three Least-Squares Minimization Approaches to Interpret Gravity Data Due to Dipping Faults

NASA Astrophysics Data System (ADS)

Abdelrahman, E. M.; Essa, K. S.

2015-02-01

We have developed three different least-squares minimization approaches to determine, successively, the depth, dip angle, and amplitude coefficient related to the thickness and density contrast of a buried dipping fault from first moving average residual gravity anomalies. By defining the zero-anomaly distance and the anomaly value at the origin of the moving average residual profile, the problem of depth determination is transformed into a constrained nonlinear gravity inversion. After estimating the depth of the fault, the dip angle is estimated by solving a nonlinear inverse problem. Finally, after estimating the depth and dip angle, the amplitude coefficient is determined using a linear equation. This method can be applied to residuals as well as to measured gravity data because it uses the moving average residual gravity anomalies to estimate the model parameters of the faulted structure. The proposed method was tested on noise-corrupted synthetic and real gravity data. In the case of the synthetic data, good results are obtained when errors are given in the zero-anomaly distance and the anomaly value at the origin, and even when the origin is determined approximately. In the case of practical data (Bouguer anomaly over Gazal fault, south Aswan, Egypt), the fault parameters obtained are in good agreement with the actual ones and with those given in the published literature.

Optimization and validation of moving average quality control procedures using bias detection curves and moving average validation charts.

PubMed

van Rossum, Huub H; Kemperman, Hans

2017-02-01

To date, no practical tools are available to obtain optimal settings for moving average (MA) as a continuous analytical quality control instrument. Also, there is no knowledge of the true bias detection properties of applied MA. We describe the use of bias detection curves for MA optimization and MA validation charts for validation of MA. MA optimization was performed on a data set of previously obtained consecutive assay results. Bias introduction and MA bias detection were simulated for multiple MA procedures (combination of truncation limits, calculation algorithms and control limits) and performed for various biases. Bias detection curves were generated by plotting the median number of test results needed for bias detection against the simulated introduced bias. In MA validation charts the minimum, median, and maximum numbers of assay results required for MA bias detection are shown for various bias. Their use was demonstrated for sodium, potassium, and albumin. Bias detection curves allowed optimization of MA settings by graphical comparison of bias detection properties of multiple MA. The optimal MA was selected based on the bias detection characteristics obtained. MA validation charts were generated for selected optimal MA and provided insight into the range of results required for MA bias detection. Bias detection curves and MA validation charts are useful tools for optimization and validation of MA procedures.

Pre-Drinking and the Temporal Gradient of Intoxication in a New Zealand Nightlife Environment.

PubMed

Cameron, Michael P; Roskruge, Matthew J; Droste, Nic; Miller, Peter G

2018-01-01

We measured changes in the average level of intoxication over time in the nighttime economy and identified the factors associated with intoxication, including pre-drinking. A random intercept sample of 320 pedestrians (105 women; 215 men) was interviewed and received breath alcohol analysis in the nighttime economy of Hamilton, New Zealand. Data were collected over a five-night period, between 7 P.M. and 2:30 A.M. Data were analyzed by plotting the moving average breath alcohol concentration (BrAC) over time and using linear regression models to identify the factors associated with BrAC. Mean BrAC was 241.5 mcg/L for the full sample; 179.7 for women and 271.7 for men, which is a statistically significant difference. Mean BrAC was also significantly higher among those who engaged in pre-drinking than those who did not. In the regression models, time of night and pre-drinking were significantly associated with higher BrAC. The effect of pre-drinking on BrAC was larger for women than for men. The average level of intoxication increases throughout the night. However, this masks a potentially important gender difference, in that women's intoxication levels stop increasing after midnight, whereas men's increase continuously through the night. Similarly, intoxication of pre-drinkers stops increasing from 11 P.M., although remaining higher than non-pre-drinkers throughout the night. Analysis of BrAC provides a more nuanced understanding of intoxication levels in the nighttime economy.

Association of Heart Rate Variability in Taxi Drivers with Marked Changes in Particulate Air Pollution in Beijing in 2008

PubMed Central

Wu, Shaowei; Deng, Furong; Niu, Jie; Huang, Qinsheng; Liu, Youcheng; Guo, Xinbiao

2010-01-01

Background Heart rate variability (HRV), a marker of cardiac autonomic function, has been associated with particulate matter (PM) air pollution, especially in older patients and those with cardiovascular diseases. However, the effect of PM exposure on cardiac autonomic function in young, healthy adults has received less attention. Objectives We evaluated the relationship between exposure to traffic-related PM with an aerodynamic diameter ≤ 2.5 μm (PM2.5) and HRV in a highly exposed panel of taxi drivers. Methods Continuous measurements of personal exposure to PM2.5 and ambulatory electrocardiogram monitoring were conducted on 11 young healthy taxi drivers for a 12-hr work shift during their work time (0900–2100 hr) before, during, and after the Beijing 2008 Olympic Games. Mixed-effects regression models were used to estimate associations between PM2.5 exposure and percent changes in 5-min HRV indices after combining data from the three time periods and controlling for potentially confounding variables. Results Personal exposures of taxi drivers to PM2.5 changed markedly across the three time periods. The standard deviation of normal-to-normal (SDNN) intervals decreased by 2.2% [95% confidence interval (CI), −3.8% to −0.6%] with an interquartile range (IQR; 69.5 μg/m3) increase in the 30-min PM2.5 moving average, whereas the low-frequency and high-frequency powers decreased by 4.2% (95% CI, −9.0% to 0.8%) and 6.2% (95% CI, −10.7% to −1.5%), respectively, in association with an IQR increase in the 2-hr PM2.5 moving average. Conclusions Marked changes in traffic-related PM2.5 exposure were associated with altered cardiac autonomic function in young healthy adults. PMID:20056565

Amplitude gating for a coached breathing approach in respiratory gated 10 MV flattening filter‐free VMAT delivery

PubMed Central

Lee, Richard; Gete, Ermias; Duzenli, Cheryl

2015-01-01

The purpose of this study was to investigate amplitude gating combined with a coached breathing strategy for 10 MV flattening filter‐free (FFF) volumetric‐modulated arc therapy (VMAT) on the Varian TrueBeam linac. Ten patient plans for VMAT SABR liver were created using the Eclipse treatment planning system (TPS). The verification plans were then transferred to a CT‐scanned Quasar phantom and delivered on a TrueBeam linac using a 10 MV FFF beam and Varian's real‐time position management (RPM) system for respiratory gating based on breathing amplitude. Breathing traces were acquired from ten patients using two kinds of breathing patterns: free breathing and an interrupted (~5 s pause) end of exhale coached breathing pattern. Ion chamber and Gafchromic film measurements were acquired for a gated delivery while the phantom moved under the described breathing patterns, as well as for a nongated stationary phantom delivery. The gate window was set to obtain a range of residual target motion from 2–5 mm. All gated deliveries on a moving phantom have been shown to be dosimetrically equivalent to the nongated deliveries on a static phantom, with differences in point dose measurements under 1% and average gamma 2%/2 mm agreement above 98.7%. Comparison with the treatment planning system also resulted in good agreement, with differences in point‐dose measurements under 2.5% and average gamma 3%/3 mm agreement of 97%. The use of a coached breathing pattern significantly increases the duty cycle, compared with free breathing, and allows for shorter treatment times. Patients' free‐breathing patterns contain considerable variability and, although dosimetric results for gated delivery may be acceptable, it is difficult to achieve efficient treatment delivery. A coached breathing pattern combined with a 5 mm amplitude gate, resulted in both high‐quality dose distributions and overall shortest gated beam delivery times. PACS number: 87.55.Qr PMID:26219000

Understanding the source of multifractality in financial markets

NASA Astrophysics Data System (ADS)

Barunik, Jozef; Aste, Tomaso; Di Matteo, T.; Liu, Ruipeng

2012-09-01

In this paper, we use the generalized Hurst exponent approach to study the multi-scaling behavior of different financial time series. We show that this approach is robust and powerful in detecting different types of multi-scaling. We observe a puzzling phenomenon where an apparent increase in multifractality is measured in time series generated from shuffled returns, where all time-correlations are destroyed, while the return distributions are conserved. This effect is robust and it is reproduced in several real financial data including stock market indices, exchange rates and interest rates. In order to understand the origin of this effect we investigate different simulated time series by means of the Markov switching multifractal model, autoregressive fractionally integrated moving average processes with stable innovations, fractional Brownian motion and Levy flights. Overall we conclude that the multifractality observed in financial time series is mainly a consequence of the characteristic fat-tailed distribution of the returns and time-correlations have the effect to decrease the measured multifractality.

Deep Downhole Seismic Testing at the Waste Treatment Plant Site, Hanford, WA. Volume IV S-Wave Measurements in Borehole C4993 Seismic Records, Wave-Arrival Identifications and Interpreted S-Wave Velocity Profile.

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

Stokoe, Kenneth H.; Li, Song Cheng; Cox, Brady R.

2007-06-06

In this volume (IV), all S-wave measurements are presented that were performed in Borehole C4993 at the Waste Treatment Plant (WTP) with T-Rex as the seismic source and the Lawrence Berkeley National Laboratory (LBNL) 3-D wireline geophone as the at-depth borehole receiver. S-wave measurements were performed over the depth range of 370 to 1300 ft, typically in 10-ft intervals. However, in some interbeds, 5-ft depth intervals were used, while below about 1200 ft, depth intervals of 20 ft were used. Shear (S) waves were generated by moving the base plate of T-Rex for a given number of cycles at amore » fixed frequency as discussed in Section 2. This process was repeated so that signal averaging in the time domain was performed using 3 to about 15 averages, with 5 averages typically used. In addition, a second average shear wave record was recorded by reversing the polarity of the motion of the T-Rex base plate. In this sense, all the signals recorded in the field were averaged signals. In all cases, the base plate was moving perpendicular to a radial line between the base plate and the borehole which is in and out of the plane of the figure shown in Figure 1.1. The definition of “in-line”, “cross-line”, “forward”, and “reversed” directions in items 2 and 3 of Section 2 was based on the moving direction of the base plate. In addition to the LBNL 3-D geophone, called the lower receiver herein, a 3-D geophone from Redpath Geophysics was fixed at a depth of 22 ft in Borehole C4993, and a 3-D geophone from the University of Texas (UT) was embedded near the borehole at about 1.5 ft below the ground surface. The Redpath geophone and the UT geophone were properly aligned so that one of the horizontal components in each geophone was aligned with the direction of horizontal shaking of the T-Rex base plate. This volume is organized into 12 sections as follows. Section 1: Introduction, Section 2: Explanation of Terminology, Section 3: Vs Profile at Borehole C4993, Sections 4 to 6: Unfiltered S-wave records of lower horizontal receiver, reaction mass, and reference receiver, respectively, Sections 7 to 9: Filtered S-wave signals of lower horizontal receiver, reaction mass and reference receiver, respectively, Section 10: Expanded and filtered S-wave signals of lower horizontal receiver, and Sections 11 and 12: Waterfall plots of unfiltered and filtered lower horizontal receiver signals, respectively.« less

Predicting long-term catchment nutrient export: the use of nonlinear time series models

NASA Astrophysics Data System (ADS)

Valent, Peter; Howden, Nicholas J. K.; Szolgay, Jan; Komornikova, Magda

2010-05-01

After the Second World War the nitrate concentrations in European water bodies changed significantly as the result of increased nitrogen fertilizer use and changes in land use. However, in the last decades, as a consequence of the implementation of nitrate-reducing measures in Europe, the nitrate concentrations in water bodies slowly decrease. This causes that the mean and variance of the observed time series also changes with time (nonstationarity and heteroscedascity). In order to detect changes and properly describe the behaviour of such time series by time series analysis, linear models (such as autoregressive (AR), moving average (MA) and autoregressive moving average models (ARMA)), are no more suitable. Time series with sudden changes in statistical characteristics can cause various problems in the calibration of traditional water quality models and thus give biased predictions. Proper statistical analysis of these non-stationary and heteroscedastic time series with the aim of detecting and subsequently explaining the variations in their statistical characteristics requires the use of nonlinear time series models. This information can be then used to improve the model building and calibration of conceptual water quality model or to select right calibration periods in order to produce reliable predictions. The objective of this contribution is to analyze two long time series of nitrate concentrations of the rivers Ouse and Stour with advanced nonlinear statistical modelling techniques and compare their performance with traditional linear models of the ARMA class in order to identify changes in the time series characteristics. The time series were analysed with nonlinear models with multiple regimes represented by self-exciting threshold autoregressive (SETAR) and Markov-switching models (MSW). The analysis showed that, based on the value of residual sum of squares (RSS) in both datasets, SETAR and MSW models described the time-series better than models of the ARMA class. In most cases the relative improvement of SETAR models against AR models of first order was low ranging between 1% and 4% with the exception of the three-regime model for the River Stour time-series where the improvement was 48.9%. In comparison, the relative improvement of MSW models was between 44.6% and 52.5 for two-regime and from 60.4% to 75% for three-regime models. However, the visual assessment of models plotted against original datasets showed that despite a high value of RSS, some ARMA models could describe the analyzed time-series better than AR, MA and SETAR models with lower values of RSS. In both datasets MSW models provided a very good visual fit describing most of the extreme values.

Stock market context of the Lévy walks with varying velocity

NASA Astrophysics Data System (ADS)

Kutner, Ryszard

2002-11-01

We developed the most general Lévy walks with varying velocity, shorter called the Weierstrass walks (WW) model, by which one can describe both stationary and non-stationary stochastic time series. We considered a non-Brownian random walk where the walker moves, in general, with a velocity that assumes a different constant value between the successive turning points, i.e., the velocity is a piecewise constant function. This model is a kind of Lévy walks where we assume a hierarchical, self-similar in a stochastic sense, spatio-temporal representation of the main quantities such as waiting-time distribution and sojourn probability density (which are principal quantities in the continuous-time random walk formalism). The WW model makes possible to analyze both the structure of the Hurst exponent and the power-law behavior of kurtosis. This structure results from the hierarchical, spatio-temporal coupling between the walker displacement and the corresponding time of the walks. The analysis uses both the fractional diffusion and the super Burnett coefficients. We constructed the diffusion phase diagram which distinguishes regions occupied by classes of different universality. We study only such classes which are characteristic for stationary situations. We thus have a model ready for describing the data presented, e.g., in the form of moving averages; the operation is often used for stochastic time series, especially financial ones. The model was inspired by properties of financial time series and tested for empirical data extracted from the Warsaw stock exchange since it offers an opportunity to study in an unbiased way several features of stock exchange in its early stage.

Behavior and Frequency Analysis of Aurelia aurita by Using in situ Target Strength at a Port in Southwestern Korea

NASA Astrophysics Data System (ADS)

Yoon, Eun-A.; Hwang, Doo-Jin; Chae, Jinho; Yoon, Won Duk; Lee, Kyounghoon

2018-03-01

This study was carried out to determine the in situ target strength and behavioral characteristics of moon jellyfish ( Aurelia aurita) using two frequencies (38 and 120 kHz) that present a 2- frequency-difference method for distinguishing A. aurita from other marine planktonic organisms. The average TS was shown as -71.9 -67.9 dB at 38 kHz and -75.5 -66.0 dB at 120 kHz and the average ΔMVBS120-38 kHz was similar at -1.5 3.5 dB. The TS values varied in a range of about 14 dB from -83.3 and -69.0 dB depending on the pulsation of A. aurita. The species moved in a range of -0.1 1.0 m and they mostly moved horizontally with moving speeds of 0.3 0.6 m·s-1. The TS and behavioral characteristics of A. aurita can distinguish the species from others. The acoustic technology can also contribute to understanding the distribution and abundance of the species.

Environmental Assessment: Installation Development at Sheppard Air Force Base, Texas

DTIC Science & Technology

2007-05-01

column, or in topographic depressions. Water is then utilized by plants and is respired, or it moves slowly into groundwater and/or eventually to surface...water bodies where it slowly moves through the hydrologic cycle. Removal of vegetation decreases infiltration into the soil column and thereby...School District JP-4 jet propulsion fuel 4 kts knots Ldn Day- Night Average Sound Level Leq equivalent noise level Lmax maximum sound level lb pound

Power strain imaging based on vibro-elastography techniques

NASA Astrophysics Data System (ADS)

Wen, Xu; Salcudean, S. E.

2007-03-01

This paper describes a new ultrasound elastography technique, power strain imaging, based on vibro-elastography (VE) techniques. With this method, tissue is compressed by a vibrating actuator driven by low-pass or band-pass filtered white noise, typically in the 0-20 Hz range. Tissue displacements at different spatial locations are estimated by correlation-based approaches on the raw ultrasound radio frequency signals and recorded in time sequences. The power spectra of these time sequences are computed by Fourier spectral analysis techniques. As the average of the power spectrum is proportional to the squared amplitude of the tissue motion, the square root of the average power over the range of excitation frequencies is used as a measure of the tissue displacement. Then tissue strain is determined by the least squares estimation of the gradient of the displacement field. The computation of the power spectra of the time sequences can be implemented efficiently by using Welch's periodogram method with moving windows or with accumulative windows with a forgetting factor. Compared to the transfer function estimation originally used in VE, the computation of cross spectral densities is not needed, which saves both the memory and computational times. Phantom experiments demonstrate that the proposed method produces stable and operator-independent strain images with high signal-to-noise ratio in real time. This approach has been also tested on a few patient data of the prostate region, and the results are encouraging.

Walking, running, and resting under time, distance, and average speed constraints: optimality of walk-run-rest mixtures.

PubMed

Long, Leroy L; Srinivasan, Manoj

2013-04-06

On a treadmill, humans switch from walking to running beyond a characteristic transition speed. Here, we study human choice between walking and running in a more ecological (non-treadmill) setting. We asked subjects to travel a given distance overground in a given allowed time duration. During this task, the subjects carried, and could look at, a stopwatch that counted down to zero. As expected, if the total time available were large, humans walk the whole distance. If the time available were small, humans mostly run. For an intermediate total time, humans often use a mixture of walking at a slow speed and running at a higher speed. With analytical and computational optimization, we show that using a walk-run mixture at intermediate speeds and a walk-rest mixture at the lowest average speeds is predicted by metabolic energy minimization, even with costs for transients-a consequence of non-convex energy curves. Thus, sometimes, steady locomotion may not be energy optimal, and not preferred, even in the absence of fatigue. Assuming similar non-convex energy curves, we conjecture that similar walk-run mixtures may be energetically beneficial to children following a parent and animals on long leashes. Humans and other animals might also benefit energetically from alternating between moving forward and standing still on a slow and sufficiently long treadmill.

Walking, running, and resting under time, distance, and average speed constraints: optimality of walk–run–rest mixtures

PubMed Central

Long, Leroy L.; Srinivasan, Manoj

2013-01-01

On a treadmill, humans switch from walking to running beyond a characteristic transition speed. Here, we study human choice between walking and running in a more ecological (non-treadmill) setting. We asked subjects to travel a given distance overground in a given allowed time duration. During this task, the subjects carried, and could look at, a stopwatch that counted down to zero. As expected, if the total time available were large, humans walk the whole distance. If the time available were small, humans mostly run. For an intermediate total time, humans often use a mixture of walking at a slow speed and running at a higher speed. With analytical and computational optimization, we show that using a walk–run mixture at intermediate speeds and a walk–rest mixture at the lowest average speeds is predicted by metabolic energy minimization, even with costs for transients—a consequence of non-convex energy curves. Thus, sometimes, steady locomotion may not be energy optimal, and not preferred, even in the absence of fatigue. Assuming similar non-convex energy curves, we conjecture that similar walk–run mixtures may be energetically beneficial to children following a parent and animals on long leashes. Humans and other animals might also benefit energetically from alternating between moving forward and standing still on a slow and sufficiently long treadmill. PMID:23365192

An empirical investigation on the forecasting ability of mallows model averaging in a macro economic environment

NASA Astrophysics Data System (ADS)

Yin, Yip Chee; Hock-Eam, Lim

2012-09-01

This paper investigates the forecasting ability of Mallows Model Averaging (MMA) by conducting an empirical analysis of five Asia countries, Malaysia, Thailand, Philippines, Indonesia and China's GDP growth rate. Results reveal that MMA has no noticeable differences in predictive ability compared to the general autoregressive fractional integrated moving average model (ARFIMA) and its predictive ability is sensitive to the effect of financial crisis. MMA could be an alternative forecasting method for samples without recent outliers such as financial crisis.

Effects of coarse-graining on the scaling behavior of long-range correlated and anti-correlated signals.

PubMed

Xu, Yinlin; Ma, Qianli D Y; Schmitt, Daniel T; Bernaola-Galván, Pedro; Ivanov, Plamen Ch

2011-11-01

We investigate how various coarse-graining (signal quantization) methods affect the scaling properties of long-range power-law correlated and anti-correlated signals, quantified by the detrended fluctuation analysis. Specifically, for coarse-graining in the magnitude of a signal, we consider (i) the Floor, (ii) the Symmetry and (iii) the Centro-Symmetry coarse-graining methods. We find that for anti-correlated signals coarse-graining in the magnitude leads to a crossover to random behavior at large scales, and that with increasing the width of the coarse-graining partition interval Δ, this crossover moves to intermediate and small scales. In contrast, the scaling of positively correlated signals is less affected by the coarse-graining, with no observable changes when Δ < 1, while for Δ > 1 a crossover appears at small scales and moves to intermediate and large scales with increasing Δ. For very rough coarse-graining (Δ > 3) based on the Floor and Symmetry methods, the position of the crossover stabilizes, in contrast to the Centro-Symmetry method where the crossover continuously moves across scales and leads to a random behavior at all scales; thus indicating a much stronger effect of the Centro-Symmetry compared to the Floor and the Symmetry method. For coarse-graining in time, where data points are averaged in non-overlapping time windows, we find that the scaling for both anti-correlated and positively correlated signals is practically preserved. The results of our simulations are useful for the correct interpretation of the correlation and scaling properties of symbolic sequences.

Effects of coarse-graining on the scaling behavior of long-range correlated and anti-correlated signals

PubMed Central

Xu, Yinlin; Ma, Qianli D.Y.; Schmitt, Daniel T.; Bernaola-Galván, Pedro; Ivanov, Plamen Ch.

2014-01-01

We investigate how various coarse-graining (signal quantization) methods affect the scaling properties of long-range power-law correlated and anti-correlated signals, quantified by the detrended fluctuation analysis. Specifically, for coarse-graining in the magnitude of a signal, we consider (i) the Floor, (ii) the Symmetry and (iii) the Centro-Symmetry coarse-graining methods. We find that for anti-correlated signals coarse-graining in the magnitude leads to a crossover to random behavior at large scales, and that with increasing the width of the coarse-graining partition interval Δ, this crossover moves to intermediate and small scales. In contrast, the scaling of positively correlated signals is less affected by the coarse-graining, with no observable changes when Δ < 1, while for Δ > 1 a crossover appears at small scales and moves to intermediate and large scales with increasing Δ. For very rough coarse-graining (Δ > 3) based on the Floor and Symmetry methods, the position of the crossover stabilizes, in contrast to the Centro-Symmetry method where the crossover continuously moves across scales and leads to a random behavior at all scales; thus indicating a much stronger effect of the Centro-Symmetry compared to the Floor and the Symmetry method. For coarse-graining in time, where data points are averaged in non-overlapping time windows, we find that the scaling for both anti-correlated and positively correlated signals is practically preserved. The results of our simulations are useful for the correct interpretation of the correlation and scaling properties of symbolic sequences. PMID:25392599

Efficiency and multifractality analysis of CSI 300 based on multifractal detrending moving average algorithm

NASA Astrophysics Data System (ADS)

Zhou, Weijie; Dang, Yaoguo; Gu, Rongbao

2013-03-01

We apply the multifractal detrending moving average (MFDMA) to investigate and compare the efficiency and multifractality of 5-min high-frequency China Securities Index 300 (CSI 300). The results show that the CSI 300 market becomes closer to weak-form efficiency after the introduction of CSI 300 future. We find that the CSI 300 is featured by multifractality and there are less complexity and risk after the CSI 300 index future was introduced. With the shuffling, surrogating and removing extreme values procedures, we unveil that extreme events and fat-distribution are the main origin of multifractality. Besides, we discuss the knotting phenomena in multifractality, and find that the scaling range and the irregular fluctuations for large scales in the Fq(s) vs s plot can cause a knot.

Gauging the Nearness and Size of Cycle Maximum

NASA Technical Reports Server (NTRS)

Wilson, Robert M.; Hathaway, David H.

2003-01-01

A simple method for monitoring the nearness and size of conventional cycle maximum for an ongoing sunspot cycle is examined. The method uses the observed maximum daily value and the maximum monthly mean value of international sunspot number and the maximum value of the 2-mo moving average of monthly mean sunspot number to effect the estimation. For cycle 23, a maximum daily value of 246, a maximum monthly mean of 170.1, and a maximum 2-mo moving average of 148.9 were each observed in July 2000. Taken together, these values strongly suggest that conventional maximum amplitude for cycle 23 would be approx. 124.5, occurring near July 2002 +/-5 mo, very close to the now well-established conventional maximum amplitude and occurrence date for cycle 23-120.8 in April 2000.

An algorithm for testing the efficient market hypothesis.

PubMed

Boboc, Ioana-Andreea; Dinică, Mihai-Cristian

2013-01-01

The objective of this research is to examine the efficiency of EUR/USD market through the application of a trading system. The system uses a genetic algorithm based on technical analysis indicators such as Exponential Moving Average (EMA), Moving Average Convergence Divergence (MACD), Relative Strength Index (RSI) and Filter that gives buying and selling recommendations to investors. The algorithm optimizes the strategies by dynamically searching for parameters that improve profitability in the training period. The best sets of rules are then applied on the testing period. The results show inconsistency in finding a set of trading rules that performs well in both periods. Strategies that achieve very good returns in the training period show difficulty in returning positive results in the testing period, this being consistent with the efficient market hypothesis (EMH).

An Algorithm for Testing the Efficient Market Hypothesis

PubMed Central

Boboc, Ioana-Andreea; Dinică, Mihai-Cristian

2013-01-01

The objective of this research is to examine the efficiency of EUR/USD market through the application of a trading system. The system uses a genetic algorithm based on technical analysis indicators such as Exponential Moving Average (EMA), Moving Average Convergence Divergence (MACD), Relative Strength Index (RSI) and Filter that gives buying and selling recommendations to investors. The algorithm optimizes the strategies by dynamically searching for parameters that improve profitability in the training period. The best sets of rules are then applied on the testing period. The results show inconsistency in finding a set of trading rules that performs well in both periods. Strategies that achieve very good returns in the training period show difficulty in returning positive results in the testing period, this being consistent with the efficient market hypothesis (EMH). PMID:24205148

Air quality at night markets in Taiwan.

PubMed

Zhao, Ping; Lin, Chi-Chi

2010-03-01

In Taiwan, there are more than 300 night markets and they have attracted more and more visitors in recent years. Air quality in night markets has become a public concern. To characterize the current air quality in night markets, four major night markets in Kaohsiung were selected for this study. The results of this study showed that the mean carbon dioxide (CO2) concentrations at fixed and moving sites in night markets ranged from 326 to 427 parts per million (ppm) during non-open hours and from 433 to 916 ppm during open hours. The average carbon monoxide (CO) concentrations at fixed and moving sites in night markets ranged from 0.2 to 2.8 ppm during non-open hours and from 2.1 to 14.1 ppm during open hours. The average 1-hr levels of particulate matter with aerodynamic diameters less than 10 microm (PM10) and less than 2.5 microm (PM2.5) at fixed and moving sites in night markets were high, ranging from 186 to 451 microg/m3 and from 175 to 418 microg/m3, respectively. The levels of PM2.5 accounted for 80-97% of their respective PM10 concentrations. The average formaldehyde (HCHO) concentrations at fixed and moving sites in night markets ranged from 0 to 0.05 ppm during non-open hours and from 0.02 to 0.27 ppm during open hours. The average concentration of individual polycyclic aromatic hydrocarbons (PAHs) was found in the range of 0.09 x 10(4) to 1.8 x 10(4) ng/m3. The total identified PAHs (TIPs) ranged from 7.8 x 10(1) to 20 x 10(1) ng/m3 during non-open hours and from 1.5 x 10(4) to 4.0 x 10(4) ng/m3 during open hours. Of the total analyzed PAHs, the low-molecular-weight PAHs (two to three rings) were the dominant species, corresponding to an average of 97% during non-open hours and 88% during open hours, whereas high-molecular-weight PAHs (four to six rings) represented 3 and 12% of the total detected PAHs in the gas phase during non-open and open hours, respectively.

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.

Statistical analysis of low level atmospheric turbulence

NASA Technical Reports Server (NTRS)

Tieleman, H. W.; Chen, W. W. L.

1974-01-01

The statistical properties of low-level wind-turbulence data were obtained with the model 1080 total vector anemometer and the model 1296 dual split-film anemometer, both manufactured by Thermo Systems Incorporated. The data obtained from the above fast-response probes were compared with the results obtained from a pair of Gill propeller anemometers. The digitized time series representing the three velocity components and the temperature were each divided into a number of blocks, the length of which depended on the lowest frequency of interest and also on the storage capacity of the available computer. A moving-average and differencing high-pass filter was used to remove the trend and the low frequency components in the time series. The calculated results for each of the anemometers used are represented in graphical or tabulated form.

Solute transport and storage mechanisms in wetlands of the Everglades, south Florida

USGS Publications Warehouse

Harvey, Judson W.; Saiers, James E.; Newlin, Jessica T.

2005-01-01

Solute transport and storage processes in wetlands play an important role in biogeochemical cycling and in wetland water quality functions. In the wetlands of the Everglades, there are few data or guidelines to characterize transport through the heterogeneous flow environment. Our goal was to conduct a tracer study to help quantify solute exchange between the relatively fast flowing water in the open part of the water column and much more slowly moving water in thick floating vegetation and in the pore water of the underlying peat. We performed a tracer experiment that consisted of a constant‐rate injection of a sodium bromide (NaBr) solution for 22 hours into a 3 m wide, open‐ended flume channel in Everglades National Park. Arrival of the bromide tracer was monitored at an array of surface water and subsurface samplers for 48 hours at a distance of 6.8 m downstream of the injection. A one‐dimensional transport model was used in combination with an optimization code to identify the values of transport parameters that best explained the tracer observations. Parameters included dimensions and mass transfer coefficients describing exchange with both short (hours) and longer (tens of hours) storage zones as well as the average rates of advection and longitudinal dispersion in the open part of the water column (referred to as the “main flow zone”). Comparison with a more detailed set of tracer measurements tested how well the model's storage zones approximated the average characteristics of tracer movement into and out of the layer of thick floating vegetation and the pore water in the underlying peat. The rate at which the relatively fast moving water in the open water column was exchanged with slowly moving water in the layer of floating vegetation and in sediment pore water amounted to 50 and 3% h−1, respectively. Storage processes decreased the depth‐averaged velocity of surface water by 50% relative to the water velocity in the open part of the water column. As a result, flow measurements made with other methods that only work in the open part of the water column (e.g., acoustic Doppler) would have overestimated the true depth‐averaged velocity by a factor of 2. We hypothesize that solute exchange and storage in zones of floating vegetation and peat pore water increase contact time of solutes with biogeochemically active surfaces in this heterogeneous wetland environment.

Noise suppressing capillary separation system

DOEpatents

Yeung, Edward S.; Xue, Yongjun

1996-07-30

A noise-suppressing capillary separation system for detecting the real-time presence or concentration of an analyte in a sample is provided. The system contains a capillary separation means through which the analyte is moved, a coherent light source that generates a beam which is split into a reference beam and a sample beam that irradiate the capillary, and a detector for detecting the reference beam and the sample beam light that transmits through the capillary. The laser beam is of a wavelength effective to be absorbed by a chromophore in the capillary. The system includes a noise suppressing system to improve performance and accuracy without signal averaging or multiple scans.

Assessing air quality in Aksaray with time series analysis

NASA Astrophysics Data System (ADS)

Kadilar, Gamze Özel; Kadilar, Cem

2017-04-01

Sulphur dioxide (SO2) is a major air pollutant caused by the dominant usage of diesel, petrol and fuels by vehicles and industries. One of the most air-polluted city in Turkey is Aksaray. Hence, in this study, the level of SO2 is analyzed in Aksaray based on the database monitored at air quality monitoring station of Turkey. Seasonal Autoregressive Integrated Moving Average (SARIMA) approach is used to forecast the level of SO2 air quality parameter. The results indicate that the seasonal ARIMA model provides reliable and satisfactory predictions for the air quality parameters and expected to be an alternative tool for practical assessment and justification.

Noise suppressing capillary separation system

DOEpatents

Yeung, E.S.; Xue, Y.

1996-07-30

A noise-suppressing capillary separation system for detecting the real-time presence or concentration of an analyte in a sample is provided. The system contains a capillary separation means through which the analyte is moved, a coherent light source that generates a beam which is split into a reference beam and a sample beam that irradiate the capillary, and a detector for detecting the reference beam and the sample beam light that transmits through the capillary. The laser beam is of a wavelength effective to be absorbed by a chromophore in the capillary. The system includes a noise suppressing system to improve performance and accuracy without signal averaging or multiple scans. 13 figs.

Nonlinear dynamics and rheology of active fluids: simulations in two dimensions.

PubMed

Fielding, S M; Marenduzzo, D; Cates, M E

2011-04-01

We report simulations of a continuum model for (apolar, flow aligning) active fluids in two dimensions. Both free and anchored boundary conditions are considered, at parallel confining walls that are either static or moving at fixed relative velocity. We focus on extensile materials and find that steady shear bands, previously shown to arise ubiquitously in one dimension for the active nematic phase at small (or indeed zero) shear rate, are generally replaced in two dimensions by more complex flow patterns that can be stationary, oscillatory, or apparently chaotic. The consequences of these flow patterns for time-averaged steady-state rheology are examined. ©2011 American Physical Society

Episodic sediment delivery and landscape connectivity in the Mancos Shale badlands and Fremont River system, Utah, USA

NASA Astrophysics Data System (ADS)

Godfrey, Andrew E.; Everitt, Benjamin L.; Duque, José F. Martín

2008-12-01

The Fremont River drains about 1000 km 2 of Mancos Shale badlands, which provide a large percentage of the total sediment load of its middle and lower reaches. Factors controlling sediment movement include: weathering that produces thin paralithic soils, mass movement events that move the soil onto locations susceptible to fluvial transport, intense precipitation events that move the sediment along rills and across local pediments, and finally Fremont River floods that move the sediment to the main-stem Colorado River. A forty-year erosion-pin study has shown that down-slope creep moves the weathered shale crust an average of 5.9 cm/yr. Weather records and our monitoring show that wet winters add large slab failures and mudflows. Recent sediment-trap studies show that about 95% of sediment movement across pediments is accomplished by high-intensity summer convective storms. Between 1890 and 1910, a series of large autumn floods swept down the Fremont River, eroding its floodplain and transforming it from a narrow and meandering channel to a broad, braided one. Beginning about 1940, the Fremont's channel began to narrow. Sequential aerial photos and cross-sections suggest that floodplain construction since about 1966 has stored about 4000 to 8000 m 3 of sediment per kilometer per year. These data suggest that it will take two centuries to restore the floodplain to its pre-1890 condition, which is in line with geologic studies elsewhere on the Colorado Plateau. The various landscape elements of slope, pediment, and floodplain are semi-independent actors in sediment delivery, each with its own style. Accelerated mass movement on the slopes has an approximate 20-year recurrence. Sediment movement from slope across pediments to master stream is episodic and recurs more frequently. The slope-to-pediment portion of the system appears well connected. However, sediment transport through the floodplain is not well connected in the decadal time scale, but increases in the century and millennial time scales, and changes over time depending on the cycle of arroyo cutting and filling.

Hemorrhage Near Fetal Rat Bone: Preliminary Results

NASA Astrophysics Data System (ADS)

Bigelow, Timothy A.; Miller, Rita J.; Blue, James P.; O'Brien, William D.

2006-05-01

High-intensity ultrasound has shown potential in treating many ailments requiring noninvasive tissue necrosis. However, little work has been done on using ultrasound to ablate pathologies on or near the developing fetus. For example, Congenital Cystic Adenomatoid Malformation (cyst on lungs), Sacrococcygeal Teratoma (benign tumor on tail bone), and Twin-Twin Transfusion Syndrome (one twin pumps blood to other twin) are selected problems that will potentially benefit from noninvasive ultrasound treatments. Before these applications can be explored, potential ultrasound-induced bioeffects should be understood. Specifically, ultrasound-induced hemorrhage near the fetal rat skull was investigated. An f/1 spherically focused transducer (5.1-cm focal length) was used to expose the skull of 18- to 19-day-gestation exteriorized rat fetuses. The ultrasound pulse had a center frequency of 0.92 MHz and pulse duration of 9.6 μs. The fetuses were exposed to 1 of 4 exposure conditions (denoted A, B, C, and D) in addition to a sham exposure. Three of the exposures consisted of a peak compressional pressure of 10 MPa, a peak rarefactional pressure of 6.7 MPa, and pulse repetition frequencies of 100 Hz (A), 250 Hz (B), and 500 Hz (C), corresponding to time-average intensities of 1.9 W/cm2, 4.7 W/cm2, and 9.4 W/cm2, respectively. Exposure D consisted of a peak compressional pressure of 6.7 MPa, a peak rarefactional pressure of 5.0 MPa, and a PRF of 500 Hz corresponding to a time-average intensity of 4.6 W/cm2. Hemorrhage occurrence increased slightly with increasing time-average intensity (i.e., 11% for A, 28% for B, 31% for C, and 19% for D with a 9% occurrence when the fetuses were not exposed). The low overall occurrence of hemorrhaging may be attributed to fetal motion (observed in over half of the fetuses from the backscattered echo during the exposure). The mean hemorrhage sizes were 3.1 mm2 for A, 2.5 mm2 for B, 2.7 mm2 for C, and 5.1 mm2 for D. The larger lesions at D may be related to these fetuses moving less as only 40% of the fetuses were observed moving for this exposure condition.

Relevance analysis and short-term prediction of PM2.5 concentrations in Beijing based on multi-source data

NASA Astrophysics Data System (ADS)

Ni, X. Y.; Huang, H.; Du, W. P.

2017-02-01

The PM2.5 problem is proving to be a major public crisis and is of great public-concern requiring an urgent response. Information about, and prediction of PM2.5 from the perspective of atmospheric dynamic theory is still limited due to the complexity of the formation and development of PM2.5. In this paper, we attempted to realize the relevance analysis and short-term prediction of PM2.5 concentrations in Beijing, China, using multi-source data mining. A correlation analysis model of PM2.5 to physical data (meteorological data, including regional average rainfall, daily mean temperature, average relative humidity, average wind speed, maximum wind speed, and other pollutant concentration data, including CO, NO2, SO2, PM10) and social media data (microblog data) was proposed, based on the Multivariate Statistical Analysis method. The study found that during these factors, the value of average wind speed, the concentrations of CO, NO2, PM10, and the daily number of microblog entries with key words 'Beijing; Air pollution' show high mathematical correlation with PM2.5 concentrations. The correlation analysis was further studied based on a big data's machine learning model- Back Propagation Neural Network (hereinafter referred to as BPNN) model. It was found that the BPNN method performs better in correlation mining. Finally, an Autoregressive Integrated Moving Average (hereinafter referred to as ARIMA) Time Series model was applied in this paper to explore the prediction of PM2.5 in the short-term time series. The predicted results were in good agreement with the observed data. This study is useful for helping realize real-time monitoring, analysis and pre-warning of PM2.5 and it also helps to broaden the application of big data and the multi-source data mining methods.

Determinants of mobile phone output power in a multinational study: implications for exposure assessment.

PubMed

Vrijheid, M; Mann, S; Vecchia, P; Wiart, J; Taki, M; Ardoino, L; Armstrong, B K; Auvinen, A; Bédard, D; Berg-Beckhoff, G; Brown, J; Chetrit, A; Collatz-Christensen, H; Combalot, E; Cook, A; Deltour, I; Feychting, M; Giles, G G; Hepworth, S J; Hours, M; Iavarone, I; Johansen, C; Krewski, D; Kurttio, P; Lagorio, S; Lönn, S; McBride, M; Montestrucq, L; Parslow, R C; Sadetzki, S; Schüz, J; Tynes, T; Woodward, A; Cardis, E

2009-10-01

The output power of a mobile phone is directly related to its radiofrequency (RF) electromagnetic field strength, and may theoretically vary substantially in different networks and phone use circumstances due to power control technologies. To improve indices of RF exposure for epidemiological studies, we assessed determinants of mobile phone output power in a multinational study. More than 500 volunteers in 12 countries used Global System for Mobile communications software-modified phones (GSM SMPs) for approximately 1 month each. The SMPs recorded date, time, and duration of each call, and the frequency band and output power at fixed sampling intervals throughout each call. Questionnaires provided information on the typical circumstances of an individual's phone use. Linear regression models were used to analyse the influence of possible explanatory variables on the average output power and the percentage call time at maximum power for each call. Measurements of over 60,000 phone calls showed that the average output power was approximately 50% of the maximum, and that output power varied by a factor of up to 2 to 3 between study centres and network operators. Maximum power was used during a considerable proportion of call time (39% on average). Output power decreased with increasing call duration, but showed little variation in relation to reported frequency of use while in a moving vehicle or inside buildings. Higher output powers for rural compared with urban use of the SMP were observed principally in Sweden where the study covered very sparsely populated areas. Average power levels are substantially higher than the minimum levels theoretically achievable in GSM networks. Exposure indices could be improved by accounting for average power levels of different telecommunications systems. There appears to be little value in gathering information on circumstances of phone use other than use in very sparsely populated regions.

"It was five years of hell": Parental experiences of navigating and processing the slow and arduous time to pediatric resective epilepsy surgery.

PubMed

Pieters, Huibrie C; Iwaki, Tomoko; Vickrey, Barbara G; Mathern, Gary W; Baca, Christine B

2016-09-01

Children with medically refractory epilepsy stand to benefit from surgery and live a life free of seizures. However, a large proportion of potentially eligible children do not receive a timely referral for a surgical evaluation. We aimed to describe experiences during the arduous time before the referral and the parent-reported facilitators that helped them move forward through this slow time. Individual semi-structured interviews with 37 parents of children who had previously undergone epilepsy surgery at UCLA (2006-2011) were recorded, transcribed, and systematically analyzed by two independent coders using thematic analysis. Clinical data were extracted from medical records. Parents, 41.3years of age on average, were mostly Caucasian, English-speaking, mothers, married, and employed. The mean age at surgery for children was 8.2years with a mean time from epilepsy onset to surgery of 5.4years. Parental decision-making was facilitated when parents eventually received a presurgical referral and navigated to a multidisciplinary team that they trusted to care for their child with medically refractory epilepsy. Four themes described the experiences that parents used to feel a sense of moving forward. The first theme, processing, involved working through feelings and was mostly done alone. The second theme, navigating the complex unknowns of the health-care system, was more active and purposeful. Processing co-occurred with navigating in a fluid intersection, the third theme, which was evidenced by deliberate actions. The fourth theme, facilitators, explained helpful ways of processing and navigating; parents utilized these mechanisms to turn vulnerable times following the distress of their child's diagnosis into an experience of productivity. To limit parental distress and remediate the slow and arduous journey to multidisciplinary care at a comprehensive epilepsy center for a surgical evaluation, we suggest multi-pronged interventions to modify barriers associated with parents, providers, and health-care systems. Based on the facilitators that moved parents of our sample forward, we provide practical suggestions such as increased peer support, developing the role of patient navigators and communication strategies with parents before, during, and after referral to a comprehensive epilepsy center and presurgical evaluation. Published by Elsevier Inc.

Understanding the past to interpret the future: Comparison of simulated groundwater recharge in the upper Colorado River basin (USA) using observed and general-circulation-model historical climate data

USGS Publications Warehouse

Tillman, Fred D.; Gangopadhyay, Subhrendu; Pruitt, Tom

2017-01-01

In evaluating potential impacts of climate change on water resources, water managers seek to understand how future conditions may differ from the recent past. Studies of climate impacts on groundwater recharge often compare simulated recharge from future and historical time periods on an average monthly or overall average annual basis, or compare average recharge from future decades to that from a single recent decade. Baseline historical recharge estimates, which are compared with future conditions, are often from simulations using observed historical climate data. Comparison of average monthly results, average annual results, or even averaging over selected historical decades, may mask the true variability in historical results and lead to misinterpretation of future conditions. Comparison of future recharge results simulated using general circulation model (GCM) climate data to recharge results simulated using actual historical climate data may also result in an incomplete understanding of the likelihood of future changes. In this study, groundwater recharge is estimated in the upper Colorado River basin, USA, using a distributed-parameter soil-water balance groundwater recharge model for the period 1951–2010. Recharge simulations are performed using precipitation, maximum temperature, and minimum temperature data from observed climate data and from 97 CMIP5 (Coupled Model Intercomparison Project, phase 5) projections. Results indicate that average monthly and average annual simulated recharge are similar using observed and GCM climate data. However, 10-year moving-average recharge results show substantial differences between observed and simulated climate data, particularly during period 1970–2000, with much greater variability seen for results using observed climate data.

Studies in astronomical time series analysis. IV - Modeling chaotic and random processes with linear filters

NASA Technical Reports Server (NTRS)

Scargle, Jeffrey D.

1990-01-01

While chaos arises only in nonlinear systems, standard linear time series models are nevertheless useful for analyzing data from chaotic processes. This paper introduces such a model, the chaotic moving average. This time-domain model is based on the theorem that any chaotic process can be represented as the convolution of a linear filter with an uncorrelated process called the chaotic innovation. A technique, minimum phase-volume deconvolution, is introduced to estimate the filter and innovation. The algorithm measures the quality of a model using the volume covered by the phase-portrait of the innovation process. Experiments on synthetic data demonstrate that the algorithm accurately recovers the parameters of simple chaotic processes. Though tailored for chaos, the algorithm can detect both chaos and randomness, distinguish them from each other, and separate them if both are present. It can also recover nonminimum-delay pulse shapes in non-Gaussian processes, both random and chaotic.

Techniques used for the analysis of oculometer eye-scanning data obtained from an air traffic control display

NASA Technical Reports Server (NTRS)

Crawford, Daniel J.; Burdette, Daniel W.; Capron, William R.

1993-01-01

The methodology and techniques used to collect and analyze look-point position data from a real-time ATC display-format comparison experiment are documented. That study compared the delivery precision and controller workload of three final approach spacing aid display formats. Using an oculometer, controller lookpoint position data were collected, associated with gaze objects (e.g., moving aircraft) on the ATC display, and analyzed to determine eye-scan behavior. The equipment involved and algorithms for saving, synchronizing with the ATC simulation output, and filtering the data are described. Target (gaze object) and cross-check scanning identification algorithms are also presented. Data tables are provided of total dwell times, average dwell times, and cross-check scans. Flow charts, block diagrams, file record descriptors, and source code are included. The techniques and data presented are intended to benefit researchers in other studies that incorporate non-stationary gaze objects and oculometer equipment.

Nonparametric autocovariance estimation from censored time series by Gaussian imputation.

PubMed

Park, Jung Wook; Genton, Marc G; Ghosh, Sujit K

2009-02-01

One of the most frequently used methods to model the autocovariance function of a second-order stationary time series is to use the parametric framework of autoregressive and moving average models developed by Box and Jenkins. However, such parametric models, though very flexible, may not always be adequate to model autocovariance functions with sharp changes. Furthermore, if the data do not follow the parametric model and are censored at a certain value, the estimation results may not be reliable. We develop a Gaussian imputation method to estimate an autocovariance structure via nonparametric estimation of the autocovariance function in order to address both censoring and incorrect model specification. We demonstrate the effectiveness of the technique in terms of bias and efficiency with simulations under various rates of censoring and underlying models. We describe its application to a time series of silicon concentrations in the Arctic.

Compton cooling and the signature of Quasi Periodic Oscillations for the transient black hole candidate H 1743-322

NASA Astrophysics Data System (ADS)

Mondal, S.; Chakrabarti, S. K.; Debnath, D.; Jana, A.; Molla, A. A.

In black hole accretion cooling of the Compton cloud has an enormous effect on the dynamics of post-shock flow. We demonstrate that the Compton cooling is highly responsible for the origin of Quasi Periodic Oscillations (QPOs) during the outburst time of the galactic black hole candidates (BHCs). Our study shows that the disk oscillation will take place when infall time from the shock roughly agrees with cooling time in the post-shock region i.e., the resonance condition. We believe that this oscillation is responsible for the origin of QPOs and will occur only when a particular disk condition (disk rate, halo rate and shock strength) satisfies. We also confirm that shock moves with an average velocity of a few meters/sec for the transient BHC H1743-322 due to the presence of Compton cooling.

Techniques for obtaining regional radiation budgets from satellite radiometer observations, phase 4 and phase 5. Ph.D. Thesis. Final Report

NASA Technical Reports Server (NTRS)

Pina, J. F.; House, F. B.

1976-01-01

A scheme was developed which divides the earth-atmosphere system into 2060 elemental areas. The regions previously described are defined in terms of these elemental areas which are fixed in size and position as the satellite moves. One method, termed the instantaneous technique, yields values of the radiant emittance (We) and the radiant reflectance (Wr) which the regions have during the time interval of a single satellite pass. The number of observations matches the number of regions under study and a unique solution is obtained using matrix inversion. The other method (termed the best fit technique), yields time averages of We and Wr for large time intervals (e.g., months, seasons). The number of observations in this technique is much greater than the number of regions considered, and an approximate solution is obtained by the method of least squares.

Predictive time-series modeling using artificial neural networks for Linac beam symmetry: an empirical study.

PubMed

Li, Qiongge; Chan, Maria F

2017-01-01

Over half of cancer patients receive radiotherapy (RT) as partial or full cancer treatment. Daily quality assurance (QA) of RT in cancer treatment closely monitors the performance of the medical linear accelerator (Linac) and is critical for continuous improvement of patient safety and quality of care. Cumulative longitudinal QA measurements are valuable for understanding the behavior of the Linac and allow physicists to identify trends in the output and take preventive actions. In this study, artificial neural networks (ANNs) and autoregressive moving average (ARMA) time-series prediction modeling techniques were both applied to 5-year daily Linac QA data. Verification tests and other evaluations were then performed for all models. Preliminary results showed that ANN time-series predictive modeling has more advantages over ARMA techniques for accurate and effective applicability in the dosimetry and QA field. © 2016 New York Academy of Sciences.

A real-time robot arm collision avoidance system

NASA Technical Reports Server (NTRS)

Shaffer, Clifford A.; Herb, Gregory M.

1992-01-01

A data structure and update algorithm are presented for a prototype real-time collision avoidance safety system simulating a multirobot workspace. The data structure is a variant of the octree, which serves as a spatial index. An octree recursively decomposes 3D space into eight equal cubic octants until each octant meets some decomposition criteria. The N-objects octree, which indexes a collection of 3D primitive solids is used. These primitives make up the two (seven-degrees-of-freedom) robot arms and workspace modeled by the system. As robot arms move, the octree is updated to reflect their changed positions. During most update cycles, any given primitive does not change which octree nodes it is in. Thus, modification to the octree is rarely required. Cycle time for interpreting current arm joint angles, updating the octree to reflect new positions, and detecting/reporting imminent collisions averages 30 ms on an Intel 80386 processor running at 20 MHz.

Joint Seasonal ARMA Approach for Modeling of Load Forecast Errors in Planning Studies

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

Hafen, Ryan P.; Samaan, Nader A.; Makarov, Yuri V.

2014-04-14

To make informed and robust decisions in the probabilistic power system operation and planning process, it is critical to conduct multiple simulations of the generated combinations of wind and load parameters and their forecast errors to handle the variability and uncertainty of these time series. In order for the simulation results to be trustworthy, the simulated series must preserve the salient statistical characteristics of the real series. In this paper, we analyze day-ahead load forecast error data from multiple balancing authority locations and characterize statistical properties such as mean, standard deviation, autocorrelation, correlation between series, time-of-day bias, and time-of-day autocorrelation.more » We then construct and validate a seasonal autoregressive moving average (ARMA) model to model these characteristics, and use the model to jointly simulate day-ahead load forecast error series for all BAs.« less

Artificially intelligent recognition of Arabic speaker using voice print-based local features

NASA Astrophysics Data System (ADS)

Mahmood, Awais; Alsulaiman, Mansour; Muhammad, Ghulam; Akram, Sheeraz

2016-11-01

Local features for any pattern recognition system are based on the information extracted locally. In this paper, a local feature extraction technique was developed. This feature was extracted in the time-frequency plain by taking the moving average on the diagonal directions of the time-frequency plane. This feature captured the time-frequency events producing a unique pattern for each speaker that can be viewed as a voice print of the speaker. Hence, we referred to this technique as voice print-based local feature. The proposed feature was compared to other features including mel-frequency cepstral coefficient (MFCC) for speaker recognition using two different databases. One of the databases used in the comparison is a subset of an LDC database that consisted of two short sentences uttered by 182 speakers. The proposed feature attained 98.35% recognition rate compared to 96.7% for MFCC using the LDC subset.

Developmental changes in children's comprehension and explanation of spatial metaphors for time.

PubMed

Stites, Lauren J; Özçalişkan, Şeyda

2013-11-01

Time is frequently expressed with spatial motion, using one of three different metaphor types: moving-time, moving-ego, and sequence-as-position. Previous work shows that children can understand and explain moving-time metaphors by age five (Özçalışkan, 2005). In this study, we focus on all three metaphor types for time, and ask whether metaphor type has an effect on children's metaphor comprehension and explanation abilities. Analysis of the responses of three- to six-year-old children and adults showed that comprehension and explanation of all three metaphor types emerge at an early age. Moreover, children's metaphor comprehension and explanation vary by metaphor type: children perform better in understanding and explaining metaphors that structure time in relation to the observer of time (moving-ego, moving-time) than metaphors that structure time without any relation to the observer of time (sequence-as-position-on-a-path). Our findings suggest that children's bodily experiences might play a role in their developing understanding of the abstract concept of time.

RADON CONCENTRATION TIME SERIES MODELING AND APPLICATION DISCUSSION.

PubMed

Stránský, V; Thinová, L

2017-11-01

In the year 2010 a continual radon measurement was established at Mladeč Caves in the Czech Republic using a continual radon monitor RADIM3A. In order to model radon time series in the years 2010-15, the Box-Jenkins Methodology, often used in econometrics, was applied. Because of the behavior of radon concentrations (RCs), a seasonal integrated, autoregressive moving averages model with exogenous variables (SARIMAX) has been chosen to model the measured time series. This model uses the time series seasonality, previously acquired values and delayed atmospheric parameters, to forecast RC. The developed model for RC time series is called regARIMA(5,1,3). Model residuals could be retrospectively compared with seismic evidence of local or global earthquakes, which occurred during the RCs measurement. This technique enables us to asses if continuously measured RC could serve an earthquake precursor. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Rate of Oviposition by Culex Quinquefasciatus in San Antonio, Texas, During Three Years

DTIC Science & Technology

1988-09-01

autoregression and zero orders of integration and moving average ( ARIMA (l,O,O)). This model was chosen initially because rainfall ap- peared to...have no trend requiring integration and no obvious requirement for a moving aver- age component (i.e., no regular periodicity). This ARIMA model was...Say in both the northern and southern hem- ispheres exposes this species to a variety of climatic challenges to its survival. It is able to adjust

Seminar Proceedings Implementation of Nonstructural Measures Held at Ft. Belvoir, Virginia on 15, 16 and 17 November 1983

DTIC Science & Technology

1983-11-01

S-Approximate Household inventory item average chance of being moved (%) High Electric toaster Vacuum cleaner 80 Colour television Medium Record...most rtadily moved are small items of electrical. I equipment and valuable items such as colour televisions. However, many respondents reported that...WESSEX WATER AUTHORITY, "Somerset Land Drainage District, land drainage sur ey report", Wessex Water Authority, Bridgwater, England, 1979. .34 "* • I.U

Modeling of particle agglomeration in nanofluids

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

Krishna, K. Hari; Neti, S.; Oztekin, A.

2015-03-07

Agglomeration strongly influences the stability or shelf life of nanofluid. The present computational and experimental study investigates the rate of agglomeration quantitatively. Agglomeration in nanofluids is attributed to the net effect of various inter-particle interaction forces. For the nanofluid considered here, a net inter-particle force depends on the particle size, volume fraction, pH, and electrolyte concentration. A solution of the discretized and coupled population balance equations can yield particle sizes as a function of time. Nanofluid prepared here consists of alumina nanoparticles with the average particle size of 150 nm dispersed in de-ionized water. As the pH of the colloid wasmore » moved towards the isoelectric point of alumina nanofluids, the rate of increase of average particle size increased with time due to lower net positive charge on particles. The rate at which the average particle size is increased is predicted and measured for different electrolyte concentration and volume fraction. The higher rate of agglomeration is attributed to the decrease in the electrostatic double layer repulsion forces. The rate of agglomeration decreases due to increase in the size of nano-particle clusters thus approaching zero rate of agglomeration when all the clusters are nearly uniform in size. Predicted rates of agglomeration agree adequate enough with the measured values; validating the mathematical model and numerical approach is employed.« less

Congruity Effects in Time and Space: Behavioral and ERP Measures

ERIC Educational Resources Information Center

Teuscher, Ursina; McQuire, Marguerite; Collins, Jennifer; Coulson, Seana

2008-01-01

Two experiments investigated whether motion metaphors for time affected the perception of spatial motion. Participants read sentences either about literal motion through space or metaphorical motion through time written from either the ego-moving or object-moving perspective. Each sentence was followed by a cartoon clip. Smiley-moving clips showed…

Personal carbon monoxide exposure in Helsinki, Finland

NASA Astrophysics Data System (ADS)

Scotto di Marco, Greta; Kephalopoulos, Stylianos; Ruuskanen, Juhani; Jantunen, Matti

Personal exposure concentrations of carbon monoxide (CO) were measured for the adult urban population of Helsinki, Finland, as part of the multi-centre European EXPOLIS study. The arithmetic mean of the 48 h average personal CO exposure concentration was 1.3 mg m -3 for participants not exposed to environmental tobacco smoke (ETS) and 1.6 mg m -3 for those exposed to ETS at any time and in any microenvironment. The maximum 8 and 1 h exposure values were 2.0 and 2.6 mg m -3, and 4.3 and 5.7 mg m -3, respectively. As tobacco smoke is one of the major sources of CO, therefore the personal mean exposures of ETS participants were higher than the non-ETS participants for all averaging times. The long- and short-term personal exposures were higher in winter than in summer for all participants. In order to analyse in more detail the correlation between the time-activity patterns and exposure levels, cluster analysis was performed using 24 h personal exposure profiles of 1 h moving averages. The results showed clearly that the major source of CO for non-ETS exposed participants are traffic emissions. The majority of the diurnal exposure profiles showed two notable exposure peaks corresponding to the morning and evening traffic rush hours. The time spent in street traffic was the most relevant factor for describing the short-term personal exposures. The more time was spent commuting by car the higher were the exposures. The long-term exposure levels were linked both to the time spent commuting and home location. People living in low-traffic suburban areas and working in downtown spent more time commuting and ended up experiencing similar long-term exposure levels than people who lived in heavy-traffic downtown areas, but spent little time commuting. For ETS exposed participants the personal exposure profiles were dominated by both tobacco smoke and traffic emissions.

Plans, Patterns, and Move Categories Guiding a Highly Selective Search

NASA Astrophysics Data System (ADS)

Trippen, Gerhard

In this paper we present our ideas for an Arimaa-playing program (also called a bot) that uses plans and pattern matching to guide a highly selective search. We restrict move generation to moves in certain move categories to reduce the number of moves considered by the bot significantly. Arimaa is a modern board game that can be played with a standard Chess set. However, the rules of the game are not at all like those of Chess. Furthermore, Arimaa was designed to be as simple and intuitive as possible for humans, yet challenging for computers. While all established Arimaa bots use alpha-beta search with a variety of pruning techniques and other heuristics ending in an extensive positional leaf node evaluation, our new bot, Rat, starts with a positional evaluation of the current position. Based on features found in the current position - supported by pattern matching using a directed position graph - our bot Rat decides which of a given set of plans to follow. The plan then dictates what types of moves can be chosen. This is another major difference from bots that generate "all" possible moves for a particular position. Rat is only allowed to generate moves that belong to certain categories. Leaf nodes are evaluated only by a straightforward material evaluation to help avoid moves that lose material. This highly selective search looks, on average, at only 5 moves out of 5,000 to over 40,000 possible moves in a middle game position.

Analysis of the learning curve for peroral endoscopic myotomy for esophageal achalasia: Single-center, two-operator experience.

PubMed

Lv, Houning; Zhao, Ningning; Zheng, Zhongqing; Wang, Tao; Yang, Fang; Jiang, Xihui; Lin, Lin; Sun, Chao; Wang, Bangmao

2017-05-01

Peroral endoscopic myotomy (POEM) has emerged as an advanced technique for the treatment of achalasia, and defining the learning curve is mandatory. From August 2011 to June 2014, two operators in our institution (A&B) carried out POEM on 35 and 33 consecutive patients, respectively. Moving average and cumulative sum (CUSUM) methods were used to analyze the POEM learning curve for corrected operative time (cOT), referring to duration of per centimeter myotomy. Additionally, perioperative outcomes were compared among distinct learning curve phases. Using the moving average method, cOT reached a plateau at the 29th case and at the 24th case for operators A and B, respectively. CUSUM analysis identified three phases: initial learning period (Phase 1), efficiency period (Phase 2) and mastery period (Phase 3). The relatively smooth state in the CUSUM graph occurred at the 26th case and at the 24th case for operators A and B, respectively. Mean cOT of distinct phases for operator A were 8.32, 5.20 and 3.97 min, whereas they were 5.99, 3.06 and 3.75 min for operator B, respectively. Eckardt score and lower esophageal sphincter pressure significantly decreased during the 1-year follow-up period. Data were comparable regarding patient characteristics and perioperative outcomes. This single-center study demonstrated that expert endoscopists with experience in esophageal endoscopic submucosal dissection reached a plateau in learning of POEM after approximately 25 cases. © 2016 Japan Gastroenterological Endoscopy Society.

Suppression of AC railway power-line interference in ECG signals recorded by public access defibrillators

PubMed Central

Dotsinsky, Ivan

2005-01-01

Background Public access defibrillators (PADs) are now available for more efficient and rapid treatment of out-of-hospital sudden cardiac arrest. PADs are used normally by untrained people on the streets and in sports centers, airports, and other public areas. Therefore, automated detection of ventricular fibrillation, or its exclusion, is of high importance. A special case exists at railway stations, where electric power-line frequency interference is significant. Many countries, especially in Europe, use 16.7 Hz AC power, which introduces high level frequency-varying interference that may compromise fibrillation detection. Method Moving signal averaging is often used for 50/60 Hz interference suppression if its effect on the ECG spectrum has little importance (no morphological analysis is performed). This approach may be also applied to the railway situation, if the interference frequency is continuously detected so as to synchronize the analog-to-digital conversion (ADC) for introducing variable inter-sample intervals. A better solution consists of rated ADC, software frequency measuring, internal irregular re-sampling according to the interference frequency, and a moving average over a constant sample number, followed by regular back re-sampling. Results The proposed method leads to a total railway interference cancellation, together with suppression of inherent noise, while the peak amplitudes of some sharp complexes are reduced. This reduction has negligible effect on accurate fibrillation detection. Conclusion The method is developed in the MATLAB environment and represents a useful tool for real time railway interference suppression. PMID:16309558

The relationship between climate change and wars waged between nomadic and farming groups from the Western Han Dynasty to the Tang Dynasty period

NASA Astrophysics Data System (ADS)

Su, Y.; Liu, L.; Fang, X. Q.; Ma, Y. N.

2016-01-01

In ancient China, shifts in regional productivity of agriculture and animal husbandry, caused by climate change, either led to wars or peaceful relations between nomadic and farming groups. During the period spanning the Western Han Dynasty to the Tang Dynasty, 367 wars were waged between these groups. While 69 % of the wars were initiated by nomads, 62.4 % were won by the farming groups. On a centennial timescale, the battlegrounds were mostly in northern areas (at an average latitude of 38.92° N) during warm periods, moving southward (at an average latitude of 34.66° N) during cold periods. On a decadal timescale, warm climates corresponded to a high incidence of wars (a correlation coefficient of 0.293). While farming groups were inclined to initiate wars during dry and cold periods, their chances of achieving victory were reduced at such times. The main reasons for this are, first, that a warm climate provided a solid material foundation for nomadic and farming groups, contributing especially to enhanced productivity among the former. However, the overriding desire of nomadic groups to expand essential subsistence means led to wars. Second, during cold periods, farming groups moved to and settled in the south, while nomadic groups occupied the Central Plain. Thus, the locations of the battlefields also changed. While other factors also influenced these wars, climate change served as a backdrop, playing an indirect role in wars between these groups.

Suppression of AC railway power-line interference in ECG signals recorded by public access defibrillators.

PubMed

Dotsinsky, Ivan

2005-11-26

Public access defibrillators (PADs) are now available for more efficient and rapid treatment of out-of-hospital sudden cardiac arrest. PADs are used normally by untrained people on the streets and in sports centers, airports, and other public areas. Therefore, automated detection of ventricular fibrillation, or its exclusion, is of high importance. A special case exists at railway stations, where electric power-line frequency interference is significant. Many countries, especially in Europe, use 16.7 Hz AC power, which introduces high level frequency-varying interference that may compromise fibrillation detection. Moving signal averaging is often used for 50/60 Hz interference suppression if its effect on the ECG spectrum has little importance (no morphological analysis is performed). This approach may be also applied to the railway situation, if the interference frequency is continuously detected so as to synchronize the analog-to-digital conversion (ADC) for introducing variable inter-sample intervals. A better solution consists of rated ADC, software frequency measuring, internal irregular re-sampling according to the interference frequency, and a moving average over a constant sample number, followed by regular back re-sampling. The proposed method leads to a total railway interference cancellation, together with suppression of inherent noise, while the peak amplitudes of some sharp complexes are reduced. This reduction has negligible effect on accurate fibrillation detection. The method is developed in the MATLAB environment and represents a useful tool for real time railway interference suppression.

Predicting the Size and Timing of Sunspot Maximum for Cycle 24

NASA Technical Reports Server (NTRS)

Wilson, Robert M.

2010-01-01

For cycle 24, the minimum value of the 12-month moving average (12-mma) of the AA-geomagnetic index in the vicinity of sunspot minimum (AAm) appears to have occurred in September 2009, measuring about 8.4 nT and following sunspot minimum by 9 months. This is the lowest value of AAm ever recorded, falling below that of 8.9 nT, previously attributed to cycle 14, which also is the smallest maximum amplitude (RM) cycle of the modern era (RM = 64.2). Based on the method of Ohl (the preferential association between RM and AAm for an ongoing cycle), one expects cycle 24 to have RM = 55+/-17 (the +/-1 - sigma prediction interval). Instead, using a variation of Ohl's method, one based on using 2-cycle moving averages (2-cma), one expects cycle 23's 2-cma of RM to be about 115.5+/-8.7 (the +/-1 - sigma prediction interval), inferring an RM of about 62+/-35 for cycle 24. Hence, it seems clear that cycle 24 will be smaller in size than was seen in cycle 23 (RM = 120.8) and, likely, will be comparable in size to that of cycle 14. From the Waldmeier effect (the preferential association between the ascent duration (ASC) and RM for an ongoing cycle), one expects cycle 24 to be a slow-rising cycle (ASC > or equal to 48 months), having RM occurrence after December 2012, unless it turns out to be a statistical outlier.

Increases in Perspective Embedding Increase Reading Time Even with Typical Text Presentation: Implications for the Reading of Literature

PubMed Central

Whalen, D. H.; Zunshine, Lisa; Holquist, Michael

2015-01-01

Reading fiction is a major component of intellectual life, yet it has proven difficult to study experimentally. One aspect of literature that has recently come to light is perspective embedding (“she thought I left” embedding her perspective on “I left”), which seems to be a defining feature of fiction. Previous work (Whalen et al., 2012) has shown that increasing levels of embedment affects the time that it takes readers to read and understand short vignettes in a moving window paradigm. With increasing levels of embedment from 1 to 5, reading times in a moving window paradigm rose almost linearly. However, level 0 was as slow as 3–4. Accuracy on probe questions was relatively constant until dropping at the fifth level. Here, we assessed this effect in a more ecologically valid (“typical”) reading paradigm, in which the entire vignette was visible at once, either for as long as desired (Experiment 1) or a fixed time (Experiment 2). In Experiment 1, reading times followed a pattern similar to that of the previous experiment, with some differences in absolute speed. Accuracy matched previous results: fairly consistent accuracy until a decline at level 5, indicating that both presentation methods allowed understanding. In Experiment 2, accuracy was somewhat reduced, perhaps because participants were less successful at allocating their attention than they were during the earlier experiment; however, the pattern was the same. It seems that literature does not, on average, use easiest reading level but rather uses a middle ground that challenges the reader, but not too much. PMID:26635684

Precision measurement of electric organ discharge timing from freely moving weakly electric fish.

PubMed

Jun, James J; Longtin, André; Maler, Leonard

2012-04-01

Physiological measurements from an unrestrained, untethered, and freely moving animal permit analyses of neural states correlated to naturalistic behaviors of interest. Precise and reliable remote measurements remain technically challenging due to animal movement, which perturbs the relative geometries between the animal and sensors. Pulse-type electric fish generate a train of discrete and stereotyped electric organ discharges (EOD) to sense their surroundings actively, and rapid modulation of the discharge rate occurs while free swimming in Gymnotus sp. The modulation of EOD rates is a useful indicator of the fish's central state such as resting, alertness, and learning associated with exploration. However, the EOD pulse waveforms remotely observed at a pair of dipole electrodes continuously vary as the fish swims relative to the electrodes, which biases the judgment of the actual pulse timing. To measure the EOD pulse timing more accurately, reliably, and noninvasively from a free-swimming fish, we propose a novel method based on the principles of waveform reshaping and spatial averaging. Our method is implemented using envelope extraction and multichannel summation, which is more precise and reliable compared with other widely used threshold- or peak-based methods according to the tests performed under various source-detector geometries. Using the same method, we constructed a real-time electronic pulse detector performing an additional online pulse discrimination routine to enhance further the detection reliability. Our stand-alone pulse detector performed with high temporal precision (<10 μs) and reliability (error <1 per 10(6) pulses) and permits longer recording duration by storing only event time stamps (4 bytes/pulse).

A Generation at Risk: When the Baby Boomers Reach Golden Pond.

ERIC Educational Resources Information Center

Butler, Robert N.

The 20th century has seen average life expectancy in the United States move from under 50 years to over 70 years. Coupled with this increase in average life expectancy is the aging of the 76.4 million persons born between 1946 and 1964. As they approach retirement, these baby-boomers will have to balance their own needs with those of living…

A time-domain Kirchhoff formula for the convective acoustic wave equation

NASA Astrophysics Data System (ADS)

Ghorbaniasl, Ghader; Siozos-Rousoulis, Leonidas; Lacor, Chris

2016-03-01

Kirchhoff's integral method allows propagated sound to be predicted, based on the pressure and its derivatives in time and space obtained on a data surface located in the linear flow region. Kirchhoff's formula for noise prediction from high-speed rotors and propellers suffers from the limitation of the observer located in uniform flow, thus requiring an extension to arbitrarily moving media. This paper presents a Kirchhoff formulation for moving surfaces in a uniform moving medium of arbitrary configuration. First, the convective wave equation is derived in a moving frame, based on the generalized functions theory. The Kirchhoff formula is then obtained for moving surfaces in the time domain. The formula has a similar form to the Kirchhoff formulation for moving surfaces of Farassat and Myers, with the presence of additional terms owing to the moving medium effect. The equation explicitly accounts for the influence of mean flow and angle of attack on the radiated noise. The formula is verified by analytical cases of a monopole source located in a moving medium.

Comparison of 3-D Multi-Lag Cross-Correlation and Speckle Brightness Aberration Correction Algorithms on Static and Moving Targets

PubMed Central

Ivancevich, Nikolas M.; Dahl, Jeremy J.; Smith, Stephen W.

2010-01-01

Phase correction has the potential to increase the image quality of 3-D ultrasound, especially transcranial ultrasound. We implemented and compared 2 algorithms for aberration correction, multi-lag cross-correlation and speckle brightness, using static and moving targets. We corrected three 75-ns rms electronic aberrators with full-width at half-maximum (FWHM) auto-correlation lengths of 1.35, 2.7, and 5.4 mm. Cross-correlation proved the better algorithm at 2.7 and 5.4 mm correlation lengths (P < 0.05). Static cross-correlation performed better than moving-target cross-correlation at the 2.7 mm correlation length (P < 0.05). Finally, we compared the static and moving-target cross-correlation on a flow phantom with a skull casting aberrator. Using signal from static targets, the correction resulted in an average contrast increase of 22.2%, compared with 13.2% using signal from moving targets. The contrast-to-noise ratio (CNR) increased by 20.5% and 12.8% using static and moving targets, respectively. Doppler signal strength increased by 5.6% and 4.9% for the static and moving-targets methods, respectively. PMID:19942503

Comparison of 3-D multi-lag cross- correlation and speckle brightness aberration correction algorithms on static and moving targets.

PubMed

Ivancevich, Nikolas M; Dahl, Jeremy J; Smith, Stephen W

2009-10-01

Phase correction has the potential to increase the image quality of 3-D ultrasound, especially transcranial ultrasound. We implemented and compared 2 algorithms for aberration correction, multi-lag cross-correlation and speckle brightness, using static and moving targets. We corrected three 75-ns rms electronic aberrators with full-width at half-maximum (FWHM) auto-correlation lengths of 1.35, 2.7, and 5.4 mm. Cross-correlation proved the better algorithm at 2.7 and 5.4 mm correlation lengths (P < 0.05). Static cross-correlation performed better than moving-target cross-correlation at the 2.7 mm correlation length (P < 0.05). Finally, we compared the static and moving-target cross-correlation on a flow phantom with a skull casting aberrator. Using signal from static targets, the correction resulted in an average contrast increase of 22.2%, compared with 13.2% using signal from moving targets. The contrast-to-noise ratio (CNR) increased by 20.5% and 12.8% using static and moving targets, respectively. Doppler signal strength increased by 5.6% and 4.9% for the static and moving-targets methods, respectively.

Afocal optical flow sensor for reducing vertical height sensitivity in indoor robot localization and navigation.

PubMed

Yi, Dong-Hoon; Lee, Tae-Jae; Cho, Dong-Il Dan

2015-05-13

This paper introduces a novel afocal optical flow sensor (OFS) system for odometry estimation in indoor robotic navigation. The OFS used in computer optical mouse has been adopted for mobile robots because it is not affected by wheel slippage. Vertical height variance is thought to be a dominant factor in systematic error when estimating moving distances in mobile robots driving on uneven surfaces. We propose an approach to mitigate this error by using an afocal (infinite effective focal length) system. We conducted experiments in a linear guide on carpet and three other materials with varying sensor heights from 30 to 50 mm and a moving distance of 80 cm. The same experiments were repeated 10 times. For the proposed afocal OFS module, a 1 mm change in sensor height induces a 0.1% systematic error; for comparison, the error for a conventional fixed-focal-length OFS module is 14.7%. Finally, the proposed afocal OFS module was installed on a mobile robot and tested 10 times on a carpet for distances of 1 m. The average distance estimation error and standard deviation are 0.02% and 17.6%, respectively, whereas those for a conventional OFS module are 4.09% and 25.7%, respectively.

Derivation of simple rules for complex flow vector fields on the lower part of the human face for robot face design.

PubMed

Ishihara, Hisashi; Ota, Nobuyuki; Asada, Minoru

2017-11-27

It is quite difficult for android robots to replicate the numerous and various types of human facial expressions owing to limitations in terms of space, mechanisms, and materials. This situation could be improved with greater knowledge regarding these expressions and their deformation rules, i.e. by using the biomimetic approach. In a previous study, we investigated 16 facial deformation patterns and found that each facial point moves almost only in its own principal direction and different deformation patterns are created with different combinations of moving lengths. However, the replication errors caused by moving each control point of a face in only their principal direction were not evaluated for each deformation pattern at that time. Therefore, we calculated the replication errors in this study using the second principal component scores of the 16 sets of flow vectors at each point on the face. More than 60% of the errors were within 1 mm, and approximately 90% of them were within 3 mm. The average error was 1.1 mm. These results indicate that robots can replicate the 16 investigated facial expressions with errors within 3 mm and 1 mm for about 90% and 60% of the vectors, respectively, even if each point on the robot face moves in only its own principal direction. This finding seems promising for the development of robots capable of showing various facial expressions because significantly fewer types of movements than previously predicted are necessary.

Scaling of Average Weighted Receiving Time on Double-Weighted Koch Networks

NASA Astrophysics Data System (ADS)

Dai, Meifeng; Ye, Dandan; Hou, Jie; Li, Xingyi

2015-03-01

In this paper, we introduce a model of the double-weighted Koch networks based on actual road networks depending on the two weight factors w,r ∈ (0, 1]. The double weights represent the capacity-flowing weight and the cost-traveling weight, respectively. Denote by wFij the capacity-flowing weight connecting the nodes i and j, and denote by wCij the cost-traveling weight connecting the nodes i and j. Let wFij be related to the weight factor w, and let wCij be related to the weight factor r. This paper assumes that the walker, at each step, starting from its current node, moves to any of its neighbors with probability proportional to the capacity-flowing weight of edge linking them. The weighted time for two adjacency nodes is the cost-traveling weight connecting the two nodes. We define the average weighted receiving time (AWRT) on the double-weighted Koch networks. The obtained result displays that in the large network, the AWRT grows as power-law function of the network order with the exponent, represented by θ(w,r) = ½ log2(1 + 3wr). We show that the AWRT exhibits a sublinear or linear dependence on network order. Thus, the double-weighted Koch networks are more efficient than classic Koch networks in receiving information.

Turbulent motion of mass flows. Mathematical modeling

NASA Astrophysics Data System (ADS)

Eglit, Margarita; Yakubenko, Alexander; Yakubenko, Tatiana

2016-04-01

New mathematical models for unsteady turbulent mass flows, e.g., dense snow avalanches and landslides, are presented. Such models are important since most of large scale flows are turbulent. In addition to turbulence, the two other important points are taken into account: the entrainment of the underlying material by the flow and the nonlinear rheology of moving material. The majority of existing models are based on the depth-averaged equations and the turbulent character of the flow is accounted by inclusion of drag proportional to the velocity squared. In this paper full (not depth-averaged) equations are used. It is assumed that basal entrainment takes place if the bed friction equals the shear strength of the underlying layer (Issler D, M. Pastor Peréz. 2011). The turbulent characteristics of the flow are calculated using a three-parameter differential model (Lushchik et al., 1978). The rheological properties of moving material are modeled by one of the three types of equations: 1) Newtonian fluid with high viscosity, 2) power-law fluid and 3) Bingham fluid. Unsteady turbulent flows down long homogeneous slope are considered. The flow dynamical parameters and entrainment rate behavior in time as well as their dependence on properties of moving and underlying materials are studied numerically. REFERENCES M.E. Eglit and A.E. Yakubenko, 2014. Numerical modeling of slope flows entraining bottom material. Cold Reg. Sci. Technol., 108, 139-148 Margarita E. Eglit and Alexander E. Yakubenko, 2016. The effect of bed material entrainment and non-Newtonian rheology on dynamics of turbulent slope flows. Fluid Dynamics, 51(3) Issler D, M. Pastor Peréz. 2011. Interplay of entrainment and rheology in snow avalanches; a numerical study. Annals of Glaciology, 52(58), 143-147 Lushchik, V.G., Paveliev, A.A. , and Yakubenko, A.E., 1978. Three-parameter model of shear turbulence. Fluid Dynamics, 13, (3), 350-362

myMoves Program: Feasibility and Acceptability Study of a Remotely Delivered Self-Management Program for Increasing Physical Activity Among Adults With Acquired Brain Injury Living in the Community.

PubMed

Jones, Taryn M; Dear, Blake F; Hush, Julia M; Titov, Nickolai; Dean, Catherine M

2016-12-01

People living with acquired brain injury (ABI) are more likely to be physically inactive and highly sedentary and, therefore, to have increased risks of morbidity and mortality. However, many adults with ABI experience barriers to participation in effective physical activity interventions. Remotely delivered self-management programs focused on teaching patients how to improve and maintain their physical activity levels have the potential to improve the overall health of adults with ABI. The study objective was to evaluate the acceptability and feasibility of a remotely delivered self-management program aimed at increasing physical activity among adults who dwell in the community and have ABI. A single-group design involving comparison of baseline measures with those taken immediately after intervention and at a 3-month follow-up was used in this study. The myMoves Program comprises 6 modules delivered over 8 weeks via email. Participants were provided with regular weekly contact with an experienced physical therapist via email and telephone. The primary outcomes were the feasibility (participation, attrition, clinician time, accessibility, and adverse events) and acceptability (satisfaction, worthiness of time, and recommendation) of the myMoves Program. The secondary outcomes were objective physical activity data collected from accelerometers, physical activity self-efficacy, psychological distress, and participation. Twenty-four participants commenced the program (20 with stroke, 4 with traumatic injury), and outcomes were collected for 23 and 22 participants immediately after the program and at a 3-month follow-up, respectively. The program required very little clinician contact time, with an average of 32.8 minutes (SD=22.8) per participant during the 8-week program. Acceptability was very high, with more than 95% of participants being either very satisfied or satisfied with the myMoves Program and stating that it was worth their time. All participants stated that they would recommend the program to others with ABI. The results were obtained from a small sample; hence, the results may not be generalizable to a larger ABI population. A remotely delivered self-management program aimed at increasing physical activity is feasible and acceptable for adults with ABI. Further large-scale efficacy trials are warranted. © 2016 American Physical Therapy Association.

CROSS-DISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Effect of Rolling Massage on Particle Moving Behaviour in Blood Vessels

NASA Astrophysics Data System (ADS)

Yi, Hou-Hui; Fan, Li-Juan; Yang, Xiao-Feng; Chen, Yan-Yan

2008-09-01

The rolling massage manipulation is a classic Chinese massage, which is expected to eliminate many diseases. Here the effect of the rolling massage on the particle moving property in the blood vessels under the rolling massage manipulation is studied by the lattice Boltzmann simulation. The simulation results show that the particle moving behaviour depends on the rolling velocity, the distance between particle position and rolling position. The average values, including particle translational velocity and angular velocity, increase as the rolling velocity increases almost linearly. The result is helpful to understand the mechanism of the massage and develop the rolling techniques.

Experimental comparisons of hypothesis test and moving average based combustion phase controllers.

PubMed

Gao, Jinwu; Wu, Yuhu; Shen, Tielong

2016-11-01

For engine control, combustion phase is the most effective and direct parameter to improve fuel efficiency. In this paper, the statistical control strategy based on hypothesis test criterion is discussed. Taking location of peak pressure (LPP) as combustion phase indicator, the statistical model of LPP is first proposed, and then the controller design method is discussed on the basis of both Z and T tests. For comparison, moving average based control strategy is also presented and implemented in this study. The experiments on a spark ignition gasoline engine at various operating conditions show that the hypothesis test based controller is able to regulate LPP close to set point while maintaining the rapid transient response, and the variance of LPP is also well constrained. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Neonatal heart rate prediction.

PubMed

Abdel-Rahman, Yumna; Jeremic, Aleksander; Tan, Kenneth

2009-01-01

Technological advances have caused a decrease in the number of infant deaths. Pre-term infants now have a substantially increased chance of survival. One of the mechanisms that is vital to saving the lives of these infants is continuous monitoring and early diagnosis. With continuous monitoring huge amounts of data are collected with so much information embedded in them. By using statistical analysis this information can be extracted and used to aid diagnosis and to understand development. In this study we have a large dataset containing over 180 pre-term infants whose heart rates were recorded over the length of their stay in the Neonatal Intensive Care Unit (NICU). We test two types of models, empirical bayesian and autoregressive moving average. We then attempt to predict future values. The autoregressive moving average model showed better results but required more computation.

Structural equation modeling of the inflammatory response to traffic air pollution

PubMed Central

Baja, Emmanuel S.; Schwartz, Joel D.; Coull, Brent A.; Wellenius, Gregory A.; Vokonas, Pantel S.; Suh, Helen H.

2015-01-01

Several epidemiological studies have reported conflicting results on the effect of traffic-related pollutants on markers of inflammation. In a Bayesian framework, we examined the effect of traffic pollution on inflammation using structural equation models (SEMs). We studied measurements of C-reactive protein (CRP), soluble vascular cell adhesion molecule-1 (sVCAM-1), and soluble intracellular adhesion molecule-1 (sICAM-1) for 749 elderly men from the Normative Aging Study. Using repeated measures SEMs, we fit a latent variable for traffic pollution that is reflected by levels of black carbon, carbon monoxide, nitrogen monoxide and nitrogen dioxide to estimate its effect on a latent variable for inflammation that included sICAM-1, sVCAM-1 and CRP. Exposure periods were assessed using 1-, 2-, 3-, 7-, 14- and 30-day moving averages previsit. We compared our findings using SEMs with those obtained using linear mixed models. Traffic pollution was related to increased inflammation for 3-, 7-, 14- and 30-day exposure periods. An inter-quartile range increase in traffic pollution was associated with a 2.3% (95% posterior interval (PI): 0.0–4.7%) increase in inflammation for the 3-day moving average, with the most significant association observed for the 30-day moving average (23.9%; 95% PI: 13.9–36.7%). Traffic pollution adversely impacts inflammation in the elderly. SEMs in a Bayesian framework can comprehensively incorporate multiple pollutants and health outcomes simultaneously in air pollution–cardiovascular epidemiological studies. PMID:23232970