Assessing the Efficacy of Adjustable Moving Averages Using ASEAN-5 Currencies.

Directory of Open Access Journals (Sweden)

Jacinta Chan Phooi M'ng

Full Text Available The objective of this research is to examine the trends in the exchange rate markets of the ASEAN-5 countries (Indonesia (IDR, Malaysia (MYR, the Philippines (PHP, Singapore (SGD, and Thailand (THB through the application of dynamic moving average trading systems. This research offers evidence of the usefulness of the time-varying volatility technical analysis indicator, Adjustable Moving Average (AMA' in deciphering trends in these ASEAN-5 exchange rate markets. This time-varying volatility factor, referred to as the Efficacy Ratio in this paper, is embedded in AMA'. The Efficacy Ratio adjusts the AMA' to the prevailing market conditions by avoiding whipsaws (losses due, in part, to acting on wrong trading signals, which generally occur when there is no general direction in the market in range trading and by entering early into new trends in trend trading. The efficacy of AMA' is assessed against other popular moving-average rules. Based on the January 2005 to December 2014 dataset, our findings show that the moving averages and AMA' are superior to the passive buy-and-hold strategy. Specifically, AMA' outperforms the other models for the United States Dollar against PHP (USD/PHP and USD/THB currency pairs. The results show that different length moving averages perform better in different periods for the five currencies. This is consistent with our hypothesis that a dynamic adjustable technical indicator is needed to cater for different periods in different markets.

Assessing the Efficacy of Adjustable Moving Averages Using ASEAN-5 Currencies.

Science.gov (United States)

Chan Phooi M'ng, Jacinta; Zainudin, Rozaimah

2016-01-01

The objective of this research is to examine the trends in the exchange rate markets of the ASEAN-5 countries (Indonesia (IDR), Malaysia (MYR), the Philippines (PHP), Singapore (SGD), and Thailand (THB)) through the application of dynamic moving average trading systems. This research offers evidence of the usefulness of the time-varying volatility technical analysis indicator, Adjustable Moving Average (AMA') in deciphering trends in these ASEAN-5 exchange rate markets. This time-varying volatility factor, referred to as the Efficacy Ratio in this paper, is embedded in AMA'. The Efficacy Ratio adjusts the AMA' to the prevailing market conditions by avoiding whipsaws (losses due, in part, to acting on wrong trading signals, which generally occur when there is no general direction in the market) in range trading and by entering early into new trends in trend trading. The efficacy of AMA' is assessed against other popular moving-average rules. Based on the January 2005 to December 2014 dataset, our findings show that the moving averages and AMA' are superior to the passive buy-and-hold strategy. Specifically, AMA' outperforms the other models for the United States Dollar against PHP (USD/PHP) and USD/THB currency pairs. The results show that different length moving averages perform better in different periods for the five currencies. This is consistent with our hypothesis that a dynamic adjustable technical indicator is needed to cater for different periods in different markets.

A note on moving average models for Gaussian random fields

DEFF Research Database (Denmark)

Hansen, Linda Vadgård; Thorarinsdottir, Thordis L.

The class of moving average models offers a flexible modeling framework for Gaussian random fields with many well known models such as the Matérn covariance family and the Gaussian covariance falling under this framework. Moving average models may also be viewed as a kernel smoothing of a Lévy...... basis, a general modeling framework which includes several types of non-Gaussian models. We propose a new one-parameter spatial correlation model which arises from a power kernel and show that the associated Hausdorff dimension of the sample paths can take any value between 2 and 3. As a result...

MARD—A moving average rose diagram application for the geosciences

Science.gov (United States)

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.

Capillary Electrophoresis Sensitivity Enhancement Based on Adaptive Moving Average Method.

Science.gov (United States)

Drevinskas, Tomas; Telksnys, Laimutis; Maruška, Audrius; Gorbatsova, Jelena; Kaljurand, Mihkel

2018-06-05

In the present work, we demonstrate a novel approach to improve the sensitivity of the "out of lab" portable capillary electrophoretic measurements. Nowadays, many signal enhancement methods are (i) underused (nonoptimal), (ii) overused (distorts the data), or (iii) inapplicable in field-portable instrumentation because of a lack of computational power. The described innovative migration velocity-adaptive moving average method uses an optimal averaging window size and can be easily implemented with a microcontroller. The contactless conductivity detection was used as a model for the development of a signal processing method and the demonstration of its impact on the sensitivity. The frequency characteristics of the recorded electropherograms and peaks were clarified. Higher electrophoretic mobility analytes exhibit higher-frequency peaks, whereas lower electrophoretic mobility analytes exhibit lower-frequency peaks. On the basis of the obtained data, a migration velocity-adaptive moving average algorithm was created, adapted, and programmed into capillary electrophoresis data-processing software. Employing the developed algorithm, each data point is processed depending on a certain migration time of the analyte. Because of the implemented migration velocity-adaptive moving average method, the signal-to-noise ratio improved up to 11 times for sampling frequency of 4.6 Hz and up to 22 times for sampling frequency of 25 Hz. This paper could potentially be used as a methodological guideline for the development of new smoothing algorithms that require adaptive conditions in capillary electrophoresis and other separation methods.

Moving average rules as a source of market instability

NARCIS (Netherlands)

Chiarella, C.; He, X.Z.; Hommes, C.H.

2006-01-01

Despite the pervasiveness of the efficient markets paradigm in the academic finance literature, the use of various moving average (MA) trading rules remains popular with financial market practitioners. This paper proposes a stochastic dynamic financial market model in which demand for traded assets

Prediction of South China sea level using seasonal ARIMA models

Science.gov (United States)

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.

Studying the effect of meteorological factors on the SO2 and PM10 pollution levels with refined versions of the SARIMA model

Energy Technology Data Exchange (ETDEWEB)

Voynikova, D. S., E-mail: desi-sl2000@yahoo.com; Gocheva-Ilieva, S. G., E-mail: snegocheva@yahoo.com; Ivanov, A. V., E-mail: aivanov-99@yahoo.com [Department of Applied Mathematics and Modeling, Faculty of Mathematics and Informatics, Paisii Hilendarski University of Plovdiv, 24 Tzar Assen str., 4000 Plovdiv (Bulgaria); Iliev, I. P., E-mail: iliev55@abv.bg [Department of Physics, Technical University – Plovdiv, 25 Tzanko Djusstabanov str., 4000 Plovdiv (Bulgaria)

2015-10-28

Numerous time series methods are used in environmental sciences allowing the detailed investigation of air pollution processes. The goal of this study is to present the empirical analysis of various aspects of stochastic modeling and in particular the ARIMA/SARIMA methods. The subject of investigation is air pollution in the town of Kardzhali, Bulgaria with 2 problematic pollutants – sulfur dioxide (SO2) and particulate matter (PM10). Various SARIMA Transfer Function models are built taking into account meteorological factors, data transformations and the use of different horizons selected to predict future levels of concentrations of the pollutants.

Quantified moving average strategy of crude oil futures market based on fuzzy logic rules and genetic algorithms

Science.gov (United States)

Liu, Xiaojia; An, Haizhong; Wang, Lijun; Guan, Qing

2017-09-01

The moving average strategy is a technical indicator that can generate trading signals to assist investment. While the trading signals tell the traders timing to buy or sell, the moving average cannot tell the trading volume, which is a crucial factor for investment. This paper proposes a fuzzy moving average strategy, in which the fuzzy logic rule is used to determine the strength of trading signals, i.e., the trading volume. To compose one fuzzy logic rule, we use four types of moving averages, the length of the moving average period, the fuzzy extent, and the recommend value. Ten fuzzy logic rules form a fuzzy set, which generates a rating level that decides the trading volume. In this process, we apply genetic algorithms to identify an optimal fuzzy logic rule set and utilize crude oil futures prices from the New York Mercantile Exchange (NYMEX) as the experiment data. Each experiment is repeated for 20 times. The results show that firstly the fuzzy moving average strategy can obtain a more stable rate of return than the moving average strategies. Secondly, holding amounts series is highly sensitive to price series. Thirdly, simple moving average methods are more efficient. Lastly, the fuzzy extents of extremely low, high, and very high are more popular. These results are helpful in investment decisions.

Kumaraswamy autoregressive moving average models for double bounded environmental data

Science.gov (United States)

Bayer, Fábio Mariano; Bayer, Débora Missio; Pumi, Guilherme

2017-12-01

In this paper we introduce the Kumaraswamy autoregressive moving average models (KARMA), which is a dynamic class of models for time series taking values in the double bounded interval (a,b) following the Kumaraswamy distribution. The Kumaraswamy family of distribution is widely applied in many areas, especially hydrology and related fields. Classical examples are time series representing rates and proportions observed over time. In the proposed KARMA model, the median is modeled by a dynamic structure containing autoregressive and moving average terms, time-varying regressors, unknown parameters and a link function. We introduce the new class of models and discuss conditional maximum likelihood estimation, hypothesis testing inference, diagnostic analysis and forecasting. In particular, we provide closed-form expressions for the conditional score vector and conditional Fisher information matrix. An application to environmental real data is presented and discussed.

Monthly streamflow forecasting with auto-regressive integrated moving average

Science.gov (United States)

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.

A RED modified weighted moving average for soft real-time application

Directory of Open Access Journals (Sweden)

Domanśka Joanna

2014-09-01

Full Text Available The popularity of TCP/IP has resulted in an increase in usage of best-effort networks for real-time communication. Much effort has been spent to ensure quality of service for soft real-time traffic over IP networks. The Internet Engineering Task Force has proposed some architecture components, such as Active Queue Management (AQM. The paper investigates the influence of the weighted moving average on packet waiting time reduction for an AQM mechanism: the RED algorithm. The proposed method for computing the average queue length is based on a difference equation (a recursive equation. Depending on a particular optimality criterion, proper parameters of the modified weighted moving average function can be chosen. This change will allow reducing the number of violations of timing constraints and better use of this mechanism for soft real-time transmissions. The optimization problem is solved through simulations performed in OMNeT++ and later verified experimentally on a Linux implementation

Modeling methane emission via the infinite moving average process

Czech Academy of Sciences Publication Activity Database

Jordanova, D.; Dušek, Jiří; Stehlík, M.

2013-01-01

Roč. 122, - (2013), s. 40-49 ISSN 0169-7439 R&D Projects: GA MŠk(CZ) ED1.1.00/02.0073; GA ČR(CZ) GAP504/11/1151 Institutional support: RVO:67179843 Keywords : Environmental chemistry * Pareto tails * t-Hill estimator * Weak consistency * Moving average process * Methane emission model Subject RIV: EH - Ecology, Behaviour Impact factor: 2.381, year: 2013

Bivariate copulas on the exponentially weighted moving average control chart

Directory of Open Access Journals (Sweden)

Sasigarn Kuvattana

2016-10-01

Full Text Available This paper proposes four types of copulas on the Exponentially Weighted Moving Average (EWMA control chart when observations are from an exponential distribution using a Monte Carlo simulation approach. The performance of the control chart is based on the Average Run Length (ARL which is compared for each copula. Copula functions for specifying dependence between random variables are used and measured by Kendall’s tau. The results show that the Normal copula can be used for almost all shifts.

Effect of parameters in moving average method for event detection enhancement using phase sensitive OTDR

Science.gov (United States)

Kwon, Yong-Seok; Naeem, Khurram; Jeon, Min Yong; Kwon, Il-bum

2017-04-01

We analyze the relations of parameters in moving average method to enhance the event detectability of phase sensitive optical time domain reflectometer (OTDR). If the external events have unique frequency of vibration, then the control parameters of moving average method should be optimized in order to detect these events efficiently. A phase sensitive OTDR was implemented by a pulsed light source, which is composed of a laser diode, a semiconductor optical amplifier, an erbium-doped fiber amplifier, a fiber Bragg grating filter, and a light receiving part, which has a photo-detector and high speed data acquisition system. The moving average method is operated with the control parameters: total number of raw traces, M, number of averaged traces, N, and step size of moving, n. The raw traces are obtained by the phase sensitive OTDR with sound signals generated by a speaker. Using these trace data, the relation of the control parameters is analyzed. In the result, if the event signal has one frequency, then the optimal values of N, n are existed to detect the event efficiently.

Image compression using moving average histogram and RBF network

International Nuclear Information System (INIS)

Khowaja, S.; Ismaili, I.A.

2015-01-01

Modernization and Globalization have made the multimedia technology as one of the fastest growing field in recent times but optimal use of bandwidth and storage has been one of the topics which attract the research community to work on. Considering that images have a lion share in multimedia communication, efficient image compression technique has become the basic need for optimal use of bandwidth and space. This paper proposes a novel method for image compression based on fusion of moving average histogram and RBF (Radial Basis Function). Proposed technique employs the concept of reducing color intensity levels using moving average histogram technique followed by the correction of color intensity levels using RBF networks at reconstruction phase. Existing methods have used low resolution images for the testing purpose but the proposed method has been tested on various image resolutions to have a clear assessment of the said technique. The proposed method have been tested on 35 images with varying resolution and have been compared with the existing algorithms in terms of CR (Compression Ratio), MSE (Mean Square Error), PSNR (Peak Signal to Noise Ratio), computational complexity. The outcome shows that the proposed methodology is a better trade off technique in terms of compression ratio, PSNR which determines the quality of the image and computational complexity. (author)

BOX & JENKINS METHODOLOGY: AN APLICATION IN RAW MILK DATA FROM THE STATE OF MINAS GERAIS

Directory of Open Access Journals (Sweden)

Eduardo Campana Barbosa

2014-04-01

Full Text Available The Box & Jenkins methodology was used to obtain a statistical model for estimate the production in liters of milk of the 6 first months of 2013 in Minas Gerais state, adjusting SARIMA (p, d, q x (P, D, Qs models, where d and D are the number of differences to remove the trend and seasonality of time series, p and q are the order of the autoregressive and moving average operators, P and Q are the order of the autoregressive and moving average seasonal operators and s is the seasonal periodicity. The Akaike Criterion Information (AIC procedure was used to select the 6 most parsimonious models and to find the best one the error indicators Mean Squared Error (EQM and Mean Absolute Percent Error (MAPE were analyzed, in addition to the assumptions of residues white noise. The Seasonal Autoregressive Integrated Moving Average SARIMA (3,1,2 x (0,1,212 was upper, view of the principle of parsimony and with more precise estimates. The forecast was more adjusted to the real values of milk production in Minas Gerais state and the model had smaller error indicators. The residues estimated were by this model white noise.

Spatial analysis based on variance of moving window averages

OpenAIRE

Wu, B M; Subbarao, K V; Ferrandino, F J; Hao, J J

2006-01-01

A new method for analysing spatial patterns was designed based on the variance of moving window averages (VMWA), which can be directly calculated in geographical information systems or a spreadsheet program (e.g. MS Excel). Different types of artificial data were generated to test the method. Regardless of data types, the VMWA method correctly determined the mean cluster sizes. This method was also employed to assess spatial patterns in historical plant disease survey data encompassing both a...

https://www.jcoeng.edu.iq/index.php/main/article/view/155/138

Directory of Open Access Journals (Sweden)

Awatif Soaded Alsaqqar

2016-08-01

Full Text Available The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC and mean squared error (MSE was found to be SARIMA (2, 0, 0 (0,1,1. The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlation coefficient between the actual and predicted values for fluoride concentration at the six locations, Al-Karakh, East Tigris, Al-Wathbah, AL-Karamah, Al-Rashid and Al-Wahda WTP intakes, was 0.93, 0.82, 0.86, 0.90, 0.83 and 0.89, respectively. Model verification results indicated that the model forecasting outputs rationally estimated the actual monthly fluoride content in the selected locations.

Journal of Earth System Science | Indian Academy of Sciences

Indian Academy of Sciences (India)

To overcome this shortcoming, monthly inflow is predicted in this study based on a combination of seasonal autoregressive integrated moving average (SARIMA) andgene expression programming (GEP) models, which is a new hybrid method (SARIMA–GEP). To this end, a four-step process is employed. First, the monthly ...

Using exponentially weighted moving average algorithm to defend against DDoS attacks

CSIR Research Space (South Africa)

Machaka, P

2016-11-01

Full Text Available This paper seeks to investigate the performance of the Exponentially Weighted Moving Average (EWMA) for mining big data and detection of DDoS attacks in Internet of Things (IoT) infrastructure. The paper will investigate the tradeoff between...

Generalized Heteroskedasticity ACF for Moving Average Models in Explicit Forms

Directory of Open Access Journals (Sweden)

Samir Khaled Safi

2014-02-01

Full Text Available Normal 0 false false false MicrosoftInternetExplorer4 The autocorrelation function (ACF measures the correlation between observations at different   distances apart. We derive explicit equations for generalized heteroskedasticity ACF for moving average of order q, MA(q. We consider two cases: Firstly: when the disturbance term follow the general covariance matrix structure Cov(wi, wj=S with si,j ¹ 0 " i¹j . Secondly: when the diagonal elements of S are not all identical but sij = 0 " i¹j, i.e. S=diag(s11, s22,…,stt. The forms of the explicit equations depend essentially on the moving average coefficients and covariance structure of the disturbance terms.   /* Style Definitions */ table.MsoNormalTable {mso-style-name:"جدول عادي"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman"; mso-ansi-language:#0400; mso-fareast-language:#0400; mso-bidi-language:#0400;}

Estimation and Forecasting in Vector Autoregressive Moving Average Models for Rich Datasets

DEFF Research Database (Denmark)

Dias, Gustavo Fruet; Kapetanios, George

We address the issue of modelling and forecasting macroeconomic variables using rich datasets, by adopting the class of Vector Autoregressive Moving Average (VARMA) models. We overcome the estimation issue that arises with this class of models by implementing an iterative ordinary least squares (...

Compact and accurate linear and nonlinear autoregressive moving average model parameter estimation using laguerre functions

DEFF Research Database (Denmark)

Chon, K H; Cohen, R J; Holstein-Rathlou, N H

1997-01-01

A linear and nonlinear autoregressive moving average (ARMA) identification algorithm is developed for modeling time series data. The algorithm uses Laguerre expansion of kernals (LEK) to estimate Volterra-Wiener kernals. However, instead of estimating linear and nonlinear system dynamics via moving...... average models, as is the case for the Volterra-Wiener analysis, we propose an ARMA model-based approach. The proposed algorithm is essentially the same as LEK, but this algorithm is extended to include past values of the output as well. Thus, all of the advantages associated with using the Laguerre...

Forcasting Philippine daily stock exchange index | Urrutia | Journal ...

African Journals Online (AJOL)

The purpose of the study is to produce a model that can estimate a three-year forecast of the Philippine Daily Stock Exchange Index. Seasonal Autoregressive Integrated Moving Average (SARIMA) model is applied ona total of 4,927 daily data observations from 1995 to 2014. By then, actual and predicted values was ...

Forecasting the number of zoonotic cutaneous leishmaniasis cases in south of Fars province, Iran using seasonal ARIMA time series method.

Science.gov (United States)

Sharafi, Mehdi; Ghaem, Haleh; Tabatabaee, Hamid Reza; Faramarzi, Hossein

2017-01-01

To predict the trend of cutaneous leishmaniasis and assess the relationship between the disease trend and weather variables in south of Fars province using Seasonal Autoregressive Integrated Moving Average (SARIMA) model. The trend of cutaneous leishmaniasis was predicted using Mini tab software and SARIMA model. Besides, information about the disease and weather conditions was collected monthly based on time series design during January 2010 to March 2016. Moreover, various SARIMA models were assessed and the best one was selected. Then, the model's fitness was evaluated based on normality of the residuals' distribution, correspondence between the fitted and real amounts, and calculation of Akaike Information Criteria (AIC) and Bayesian Information Criteria (BIC). The study results indicated that SARIMA model (4,1,4)(0,1,0) (12) in general and SARIMA model (4,1,4)(0,1,1) (12) in below and above 15 years age groups could appropriately predict the disease trend in the study area. Moreover, temperature with a three-month delay (lag3) increased the disease trend, rainfall with a four-month delay (lag4) decreased the disease trend, and rainfall with a nine-month delay (lag9) increased the disease trend. Based on the results, leishmaniasis follows a descending trend in the study area in case drought condition continues, SARIMA models can suitably measure the disease trend, and the disease follows a seasonal trend. Copyright © 2017 Hainan Medical University. Production and hosting by Elsevier B.V. All rights reserved.

Generalized Heteroskedasticity ACF for Moving Average Models in Explicit Forms

OpenAIRE

Samir Khaled Safi

2014-01-01

The autocorrelation function (ACF) measures the correlation between observations at different   distances apart. We derive explicit equations for generalized heteroskedasticity ACF for moving average of order q, MA(q). We consider two cases: Firstly: when the disturbance term follow the general covariance matrix structure Cov(wi, wj)=S with si,j ¹ 0 " i¹j . Secondly: when the diagonal elements of S are not all identical but sij = 0 " i¹j, i.e. S=diag(s11, s22,&hellip...

Experimental investigation of a moving averaging algorithm for motion perpendicular to the leaf travel direction in dynamic MLC target tracking

Energy Technology Data Exchange (ETDEWEB)

Yoon, Jai-Woong; Sawant, Amit; Suh, Yelin; Cho, Byung-Chul; Suh, Tae-Suk; Keall, Paul [Department of Biomedical Engineering, College of Medicine, Catholic University of Korea, Seoul, Korea 131-700 and Research Institute of Biomedical Engineering, Catholic University of Korea, Seoul, 131-700 (Korea, Republic of); Department of Radiation Oncology, Stanford University, Stanford, California 94305 (United States); Department of Radiation Oncology, Stanford University, Stanford, California 94305 (United States) and Department of Radiation Oncology, Asan Medical Center, Seoul, 138-736 (Korea, Republic of); Department of Biomedical Engineering, College of Medicine, Catholic University of Korea, Seoul, 131-700 and Research Institute of Biomedical Engineering, Catholic University of Korea, Seoul, 131-700 (Korea, Republic of); Department of Radiation Oncology, Stanford University, Stanford, California 94305 (United States) and Radiation Physics Laboratory, Sydney Medical School, University of Sydney, 2006 (Australia)

2011-07-15

Purpose: In dynamic multileaf collimator (MLC) motion tracking with complex intensity-modulated radiation therapy (IMRT) fields, target motion perpendicular to the MLC leaf travel direction can cause beam holds, which increase beam delivery time by up to a factor of 4. As a means to balance delivery efficiency and accuracy, a moving average algorithm was incorporated into a dynamic MLC motion tracking system (i.e., moving average tracking) to account for target motion perpendicular to the MLC leaf travel direction. The experimental investigation of the moving average algorithm compared with real-time tracking and no compensation beam delivery is described. Methods: The properties of the moving average algorithm were measured and compared with those of real-time tracking (dynamic MLC motion tracking accounting for both target motion parallel and perpendicular to the leaf travel direction) and no compensation beam delivery. The algorithm was investigated using a synthetic motion trace with a baseline drift and four patient-measured 3D tumor motion traces representing regular and irregular motions with varying baseline drifts. Each motion trace was reproduced by a moving platform. The delivery efficiency, geometric accuracy, and dosimetric accuracy were evaluated for conformal, step-and-shoot IMRT, and dynamic sliding window IMRT treatment plans using the synthetic and patient motion traces. The dosimetric accuracy was quantified via a {gamma}-test with a 3%/3 mm criterion. Results: The delivery efficiency ranged from 89 to 100% for moving average tracking, 26%-100% for real-time tracking, and 100% (by definition) for no compensation. The root-mean-square geometric error ranged from 3.2 to 4.0 mm for moving average tracking, 0.7-1.1 mm for real-time tracking, and 3.7-7.2 mm for no compensation. The percentage of dosimetric points failing the {gamma}-test ranged from 4 to 30% for moving average tracking, 0%-23% for real-time tracking, and 10%-47% for no compensation

Experimental investigation of a moving averaging algorithm for motion perpendicular to the leaf travel direction in dynamic MLC target tracking.

Science.gov (United States)

Yoon, Jai-Woong; Sawant, Amit; Suh, Yelin; Cho, Byung-Chul; Suh, Tae-Suk; Keall, Paul

2011-07-01

In dynamic multileaf collimator (MLC) motion tracking with complex intensity-modulated radiation therapy (IMRT) fields, target motion perpendicular to the MLC leaf travel direction can cause beam holds, which increase beam delivery time by up to a factor of 4. As a means to balance delivery efficiency and accuracy, a moving average algorithm was incorporated into a dynamic MLC motion tracking system (i.e., moving average tracking) to account for target motion perpendicular to the MLC leaf travel direction. The experimental investigation of the moving average algorithm compared with real-time tracking and no compensation beam delivery is described. The properties of the moving average algorithm were measured and compared with those of real-time tracking (dynamic MLC motion tracking accounting for both target motion parallel and perpendicular to the leaf travel direction) and no compensation beam delivery. The algorithm was investigated using a synthetic motion trace with a baseline drift and four patient-measured 3D tumor motion traces representing regular and irregular motions with varying baseline drifts. Each motion trace was reproduced by a moving platform. The delivery efficiency, geometric accuracy, and dosimetric accuracy were evaluated for conformal, step-and-shoot IMRT, and dynamic sliding window IMRT treatment plans using the synthetic and patient motion traces. The dosimetric accuracy was quantified via a tgamma-test with a 3%/3 mm criterion. The delivery efficiency ranged from 89 to 100% for moving average tracking, 26%-100% for real-time tracking, and 100% (by definition) for no compensation. The root-mean-square geometric error ranged from 3.2 to 4.0 mm for moving average tracking, 0.7-1.1 mm for real-time tracking, and 3.7-7.2 mm for no compensation. The percentage of dosimetric points failing the gamma-test ranged from 4 to 30% for moving average tracking, 0%-23% for real-time tracking, and 10%-47% for no compensation. The delivery efficiency of

Exponentially Weighted Moving Average Chart as a Suitable Tool for Nuchal Translucency Quality Review

Czech Academy of Sciences Publication Activity Database

Hynek, M.; Smetanová, D.; Stejskal, D.; Zvárová, Jana

2014-01-01

Roč. 34, č. 4 (2014), s. 367-376 ISSN 0197-3851 Institutional support: RVO:67985807 Keywords : nuchal translucency * exponentially weighted moving average model * statistics Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 3.268, year: 2014

Application of autoregressive moving average model in reactor noise analysis

International Nuclear Information System (INIS)

Tran Dinh Tri

1993-01-01

The application of an autoregressive (AR) model to estimating noise measurements has achieved many successes in reactor noise analysis in the last ten years. The physical processes that take place in the nuclear reactor, however, are described by an autoregressive moving average (ARMA) model rather than by an AR model. Consequently more correct results could be obtained by applying the ARMA model instead of the AR model to reactor noise analysis. In this paper the system of the generalised Yule-Walker equations is derived from the equation of an ARMA model, then a method for its solution is given. Numerical results show the applications of the method proposed. (author)

Optimization of seasonal ARIMA models using differential evolution - simulated annealing (DESA) algorithm in forecasting dengue cases in Baguio City

Science.gov (United States)

Addawe, Rizavel C.; Addawe, Joel M.; Magadia, Joselito C.

2016-10-01

Accurate forecasting of dengue cases would significantly improve epidemic prevention and control capabilities. This paper attempts to provide useful models in forecasting dengue epidemic specific to the young and adult population of Baguio City. To capture the seasonal variations in dengue incidence, this paper develops a robust modeling approach to identify and estimate seasonal autoregressive integrated moving average (SARIMA) models in the presence of additive outliers. Since the least squares estimators are not robust in the presence of outliers, we suggest a robust estimation based on winsorized and reweighted least squares estimators. A hybrid algorithm, Differential Evolution - Simulated Annealing (DESA), is used to identify and estimate the parameters of the optimal SARIMA model. The method is applied to the monthly reported dengue cases in Baguio City, Philippines.

Relationship research between meteorological disasters and stock markets based on a multifractal detrending moving average algorithm

Science.gov (United States)

Li, Qingchen; Cao, Guangxi; Xu, Wei

2018-01-01

Based on a multifractal detrending moving average algorithm (MFDMA), this study uses the fractionally autoregressive integrated moving average process (ARFIMA) to demonstrate the effectiveness of MFDMA in the detection of auto-correlation at different sample lengths and to simulate some artificial time series with the same length as the actual sample interval. We analyze the effect of predictable and unpredictable meteorological disasters on the US and Chinese stock markets and the degree of long memory in different sectors. Furthermore, we conduct a preliminary investigation to determine whether the fluctuations of financial markets caused by meteorological disasters are derived from the normal evolution of the financial system itself or not. We also propose several reasonable recommendations.

Analysis of nonlinear systems using ARMA [autoregressive moving average] models

International Nuclear Information System (INIS)

Hunter, N.F. Jr.

1990-01-01

While many vibration systems exhibit primarily linear behavior, a significant percentage of the systems encountered in vibration and model testing are mildly to severely nonlinear. Analysis methods for such nonlinear systems are not yet well developed and the response of such systems is not accurately predicted by linear models. Nonlinear ARMA (autoregressive moving average) models are one method for the analysis and response prediction of nonlinear vibratory systems. In this paper we review the background of linear and nonlinear ARMA models, and illustrate the application of these models to nonlinear vibration systems. We conclude by summarizing the advantages and disadvantages of ARMA models and emphasizing prospects for future development. 14 refs., 11 figs

Comparative study of four time series methods in forecasting typhoid fever incidence in China.

Science.gov (United States)

Zhang, Xingyu; Liu, Yuanyuan; Yang, Min; Zhang, Tao; Young, Alistair A; Li, Xiaosong

2013-01-01

Accurate incidence forecasting of infectious disease is critical for early prevention and for better government strategic planning. In this paper, we present a comprehensive study of different forecasting methods based on the monthly incidence of typhoid fever. The seasonal autoregressive integrated moving average (SARIMA) model and three different models inspired by neural networks, namely, back propagation neural networks (BPNN), radial basis function neural networks (RBFNN), and Elman recurrent neural networks (ERNN) were compared. The differences as well as the advantages and disadvantages, among the SARIMA model and the neural networks were summarized and discussed. The data obtained for 2005 to 2009 and for 2010 from the Chinese Center for Disease Control and Prevention were used as modeling and forecasting samples, respectively. The performances were evaluated based on three metrics: mean absolute error (MAE), mean absolute percentage error (MAPE), and mean square error (MSE). The results showed that RBFNN obtained the smallest MAE, MAPE and MSE in both the modeling and forecasting processes. The performances of the four models ranked in descending order were: RBFNN, ERNN, BPNN and the SARIMA model.

Comparative study of four time series methods in forecasting typhoid fever incidence in China.

Directory of Open Access Journals (Sweden)

Xingyu Zhang

Full Text Available Accurate incidence forecasting of infectious disease is critical for early prevention and for better government strategic planning. In this paper, we present a comprehensive study of different forecasting methods based on the monthly incidence of typhoid fever. The seasonal autoregressive integrated moving average (SARIMA model and three different models inspired by neural networks, namely, back propagation neural networks (BPNN, radial basis function neural networks (RBFNN, and Elman recurrent neural networks (ERNN were compared. The differences as well as the advantages and disadvantages, among the SARIMA model and the neural networks were summarized and discussed. The data obtained for 2005 to 2009 and for 2010 from the Chinese Center for Disease Control and Prevention were used as modeling and forecasting samples, respectively. The performances were evaluated based on three metrics: mean absolute error (MAE, mean absolute percentage error (MAPE, and mean square error (MSE. The results showed that RBFNN obtained the smallest MAE, MAPE and MSE in both the modeling and forecasting processes. The performances of the four models ranked in descending order were: RBFNN, ERNN, BPNN and the SARIMA model.

Short-term forecasting of the chloride content in the mineral waters of the Ustroń Health Resort using SARIMA and Holt-Winters models

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Dąbrowska Dominika

2015-12-01

Full Text Available The Ustroń S.A. Health Resort (southern Poland uses iodide-bromide mineral waters taken from Middle and Upper Devonian limestones and dolomites with a mineralisation range of 110-130 g/dm3 for curative purposes. Two boreholes - U-3 and U3-A drilled in the early 1970s were exploited. The aim of this paper is to estimate changes in mineral water quality of the Ustroń Health Resort by taking into consideration chloride content in the water from the U-3 borehole. The data has included the results of monthly analyses of chlorides from 2005 to 2015 during the tests carried out by the Mining Department of the Health Resort. The triple exponential smoothing (ETS function and the Seasonal Autoregressive Integrated Moving Average (SARIMA method of modelling time series were used for the calculations. The ability to properly forecast mineral water quality can result in a good status of the exploitation borehole and a limited number of failures in the exploitation system. Because of the good management of health resorts, it is possible to acquire more satisfied customers. The main goal of the article involves the real-time forecast accuracy, obtained results show that the proposed methods are effective for such situations. Presented methods made it possible to obtain a 24-month point and interval forecast. The results of these analyses indicate that the chloride content is forecast to be in the range of 72 to 83 g/l from 2015 to 2017. While comparing the two methods of analysis, a narrower range of forecast values and, therefore, greater accuracy were obtained for the ETS function. The good performance of the ETS model highlights its utility compared with complicated physically based numerical models.

Dosimetric consequences of planning lung treatments on 4DCT average reconstruction to represent a moving tumour

International Nuclear Information System (INIS)

Dunn, L.F.; Taylor, M.L.; Kron, T.; Franich, R.

2010-01-01

Full text: Anatomic motion during a radiotherapy treatment is one of the more significant challenges in contemporary radiation therapy. For tumours of the lung, motion due to patient respiration makes both accurate planning and dose delivery difficult. One approach is to use the maximum intensity projection (MIP) obtained from a 40 computed tomography (CT) scan and then use this to determine the treatment volume. The treatment is then planned on a 4DCT average reco struction, rather than assuming the entire ITY has a uniform tumour density. This raises the question: how well does planning on a 'blurred' distribution of density with CT values greater than lung density but less than tumour density match the true case of a tumour moving within lung tissue? The aim of this study was to answer this question, determining the dosimetric impact of using a 4D-CT average reconstruction as the basis for a radiotherapy treatment plan. To achieve this, Monte-Carlo sim ulations were undertaken using GEANT4. The geometry consisted of a tumour (diameter 30 mm) moving with a sinusoidal pattern of amplitude = 20 mm. The tumour's excursion occurs within a lung equivalent volume beyond a chest wall interface. Motion was defined parallel to a 6 MY beam. This was then compared to a single oblate tumour of a magnitude determined by the extremes of the tumour motion. The variable density of the 4DCT average tumour is simulated by a time-weighted average, to achieve the observed density gradient. The generic moving tumour geometry is illustrated in the Figure.

Burden of Disease Measured by Disability-Adjusted Life Years and a Disease Forecasting Time Series Model of Scrub Typhus in Laiwu, China

Science.gov (United States)

Yang, Li-Ping; Liang, Si-Yuan; Wang, Xian-Jun; Li, Xiu-Jun; Wu, Yan-Ling; Ma, Wei

2015-01-01

Background Laiwu District is recognized as a hyper-endemic region for scrub typhus in Shandong Province, but the seriousness of this problem has been neglected in public health circles. Methodology/Principal Findings A disability-adjusted life years (DALYs) approach was adopted to measure the burden of scrub typhus in Laiwu, China during the period 2006 to 2012. A multiple seasonal autoregressive integrated moving average model (SARIMA) was used to identify the most suitable forecasting model for scrub typhus in Laiwu. Results showed that the disease burden of scrub typhus is increasing yearly in Laiwu, and which is higher in females than males. For both females and males, DALY rates were highest for the 60–69 age group. Of all the SARIMA models tested, the SARIMA(2,1,0)(0,1,0)12 model was the best fit for scrub typhus cases in Laiwu. Human infections occurred mainly in autumn with peaks in October. Conclusions/Significance Females, especially those of 60 to 69 years of age, were at highest risk of developing scrub typhus in Laiwu, China. The SARIMA (2,1,0)(0,1,0)12 model was the best fit forecasting model for scrub typhus in Laiwu, China. These data are useful for developing public health education and intervention programs to reduce disease. PMID:25569248

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

Science.gov (United States)

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.

A generalization of the preset count moving average algorithm for digital rate meters

International Nuclear Information System (INIS)

Arandjelovic, Vojislav; Koturovic, Aleksandar; Vukanovic, Radomir

2002-01-01

A generalized definition of the preset count moving average algorithm for digital rate meters has been introduced. The algorithm is based on the knowledge of time intervals between successive pulses in random-pulse sequences. The steady state and transient regimes of the algorithm have been characterized. A measure for statistical fluctuations of the successive measurement results has been introduced. The versatility of the generalized algorithm makes it suitable for application in the design of the software of modern measuring/control digital systems

Quantifying walking and standing behaviour of dairy cows using a moving average based on output from an accelerometer

DEFF Research Database (Denmark)

Nielsen, Lars Relund; Pedersen, Asger Roer; Herskin, Mette S

2010-01-01

in sequences of approximately 20 s for the period of 10 min. Afterwards the cows were stimulated to move/lift the legs while standing in a cubicle. The behaviour was video recorded, and the recordings were analysed second by second for walking and standing behaviour as well as the number of steps taken....... Various algorithms for predicting walking/standing status were compared. The algorithms were all based on a limit of a moving average calculated by using one of two outputs of the accelerometer, either a motion index or a step count, and applied over periods of 3 or 5 s. Furthermore, we investigated...... the effect of additionally applying the rule: a walking period must last at least 5 s. The results indicate that the lowest misclassification rate (10%) of walking and standing was obtained based on the step count with a moving average of 3 s and with the rule applied. However, the rate of misclassification...

Forecasting incidence of dengue in Rajasthan, using time series analyses.

Science.gov (United States)

Bhatnagar, Sunil; Lal, Vivek; Gupta, Shiv D; Gupta, Om P

2012-01-01

To develop a prediction model for dengue fever/dengue haemorrhagic fever (DF/DHF) using time series data over the past decade in Rajasthan and to forecast monthly DF/DHF incidence for 2011. Seasonal autoregressive integrated moving average (SARIMA) model was used for statistical modeling. During January 2001 to December 2010, the reported DF/DHF cases showed a cyclical pattern with seasonal variation. SARIMA (0,0,1) (0,1,1) 12 model had the lowest normalized Bayesian information criteria (BIC) of 9.426 and mean absolute percentage error (MAPE) of 263.361 and appeared to be the best model. The proportion of variance explained by the model was 54.3%. Adequacy of the model was established through Ljung-Box test (Q statistic 4.910 and P-value 0.996), which showed no significant correlation between residuals at different lag times. The forecast for the year 2011 showed a seasonal peak in the month of October with an estimated 546 cases. Application of SARIMA model may be useful for forecast of cases and impending outbreaks of DF/DHF and other infectious diseases, which exhibit seasonal pattern.

An Exponentially Weighted Moving Average Control Chart for Bernoulli Data

DEFF Research Database (Denmark)

Spliid, Henrik

2010-01-01

of the transformation is given and its limit for small values of p is derived. Control of high yield processes is discussed and the chart is shown to perform very well in comparison with both the most common alternative EWMA chart and the CUSUM chart. The construction and the use of the proposed EWMA chart......We consider a production process in which units are produced in a sequential manner. The units can, for example, be manufactured items or services, provided to clients. Each unit produced can be a failure with probability p or a success (non-failure) with probability (1-p). A novel exponentially...... weighted moving average (EWMA) control chart intended for surveillance of the probability of failure, p, is described. The chart is based on counting the number of non-failures produced between failures in combination with a variance-stabilizing transformation. The distribution function...

An Invariance Property for the Maximum Likelihood Estimator of the Parameters of a Gaussian Moving Average Process

OpenAIRE

Godolphin, E. J.

1980-01-01

It is shown that the estimation procedure of Walker leads to estimates of the parameters of a Gaussian moving average process which are asymptotically equivalent to the maximum likelihood estimates proposed by Whittle and represented by Godolphin.

Forecasting Rice Productivity and Production of Odisha, India, Using Autoregressive Integrated Moving Average Models

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Rahul Tripathi

2014-01-01

Full Text Available Forecasting of rice area, production, and productivity of Odisha was made from the historical data of 1950-51 to 2008-09 by using univariate autoregressive integrated moving average (ARIMA models and was compared with the forecasted all Indian data. The autoregressive (p and moving average (q parameters were identified based on the significant spikes in the plots of partial autocorrelation function (PACF and autocorrelation function (ACF of the different time series. ARIMA (2, 1, 0 model was found suitable for all Indian rice productivity and production, whereas ARIMA (1, 1, 1 was best fitted for forecasting of rice productivity and production in Odisha. Prediction was made for the immediate next three years, that is, 2007-08, 2008-09, and 2009-10, using the best fitted ARIMA models based on minimum value of the selection criterion, that is, Akaike information criteria (AIC and Schwarz-Bayesian information criteria (SBC. The performances of models were validated by comparing with percentage deviation from the actual values and mean absolute percent error (MAPE, which was found to be 0.61 and 2.99% for the area under rice in Odisha and India, respectively. Similarly for prediction of rice production and productivity in Odisha and India, the MAPE was found to be less than 6%.

A Pareto-optimal moving average multigene genetic programming model for daily streamflow prediction

Science.gov (United States)

Danandeh Mehr, Ali; Kahya, Ercan

2017-06-01

Genetic programming (GP) is able to systematically explore alternative model structures of different accuracy and complexity from observed input and output data. The effectiveness of GP in hydrological system identification has been recognized in recent studies. However, selecting a parsimonious (accurate and simple) model from such alternatives still remains a question. This paper proposes a Pareto-optimal moving average multigene genetic programming (MA-MGGP) approach to develop a parsimonious model for single-station streamflow prediction. The three main components of the approach that take us from observed data to a validated model are: (1) data pre-processing, (2) system identification and (3) system simplification. The data pre-processing ingredient uses a simple moving average filter to diminish the lagged prediction effect of stand-alone data-driven models. The multigene ingredient of the model tends to identify the underlying nonlinear system with expressions simpler than classical monolithic GP and, eventually simplification component exploits Pareto front plot to select a parsimonious model through an interactive complexity-efficiency trade-off. The approach was tested using the daily streamflow records from a station on Senoz Stream, Turkey. Comparing to the efficiency results of stand-alone GP, MGGP, and conventional multi linear regression prediction models as benchmarks, the proposed Pareto-optimal MA-MGGP model put forward a parsimonious solution, which has a noteworthy importance of being applied in practice. In addition, the approach allows the user to enter human insight into the problem to examine evolved models and pick the best performing programs out for further analysis.

Predicting the outbreak of hand, foot, and mouth disease in Nanjing, China: a time-series model based on weather variability

Science.gov (United States)

Liu, Sijun; Chen, Jiaping; Wang, Jianming; Wu, Zhuchao; Wu, Weihua; Xu, Zhiwei; Hu, Wenbiao; Xu, Fei; Tong, Shilu; Shen, Hongbing

2017-10-01

Hand, foot, and mouth disease (HFMD) is a significant public health issue in China and an accurate prediction of epidemic can improve the effectiveness of HFMD control. This study aims to develop a weather-based forecasting model for HFMD using the information on climatic variables and HFMD surveillance in Nanjing, China. Daily data on HFMD cases and meteorological variables between 2010 and 2015 were acquired from the Nanjing Center for Disease Control and Prevention, and China Meteorological Data Sharing Service System, respectively. A multivariate seasonal autoregressive integrated moving average (SARIMA) model was developed and validated by dividing HFMD infection data into two datasets: the data from 2010 to 2013 were used to construct a model and those from 2014 to 2015 were used to validate it. Moreover, we used weekly prediction for the data between 1 January 2014 and 31 December 2015 and leave-1-week-out prediction was used to validate the performance of model prediction. SARIMA (2,0,0)52 associated with the average temperature at lag of 1 week appeared to be the best model (R 2 = 0.936, BIC = 8.465), which also showed non-significant autocorrelations in the residuals of the model. In the validation of the constructed model, the predicted values matched the observed values reasonably well between 2014 and 2015. There was a high agreement rate between the predicted values and the observed values (sensitivity 80%, specificity 96.63%). This study suggests that the SARIMA model with average temperature could be used as an important tool for early detection and prediction of HFMD outbreaks in Nanjing, China.

A Two-Factor Autoregressive Moving Average Model Based on Fuzzy Fluctuation Logical Relationships

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Shuang Guan

2017-10-01

Full Text Available Many of the existing autoregressive moving average (ARMA forecast models are based on one main factor. In this paper, we proposed a new two-factor first-order ARMA forecast model based on fuzzy fluctuation logical relationships of both a main factor and a secondary factor of a historical training time series. Firstly, we generated a fluctuation time series (FTS for two factors by calculating the difference of each data point with its previous day, then finding the absolute means of the two FTSs. We then constructed a fuzzy fluctuation time series (FFTS according to the defined linguistic sets. The next step was establishing fuzzy fluctuation logical relation groups (FFLRGs for a two-factor first-order autoregressive (AR(1 model and forecasting the training data with the AR(1 model. Then we built FFLRGs for a two-factor first-order autoregressive moving average (ARMA(1,m model. Lastly, we forecasted test data with the ARMA(1,m model. To illustrate the performance of our model, we used real Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX and Dow Jones datasets as a secondary factor to forecast TAIEX. The experiment results indicate that the proposed two-factor fluctuation ARMA method outperformed the one-factor method based on real historic data. The secondary factor may have some effects on the main factor and thereby impact the forecasting results. Using fuzzified fluctuations rather than fuzzified real data could avoid the influence of extreme values in historic data, which performs negatively while forecasting. To verify the accuracy and effectiveness of the model, we also employed our method to forecast the Shanghai Stock Exchange Composite Index (SHSECI from 2001 to 2015 and the international gold price from 2000 to 2010.

Forecasting dengue hemorrhagic fever cases using ARIMA model: a case study in Asahan district

Science.gov (United States)

Siregar, Fazidah A.; Makmur, Tri; Saprin, S.

2018-01-01

Time series analysis had been increasingly used to forecast the number of dengue hemorrhagic fever in many studies. Since no vaccine exist and poor public health infrastructure, predicting the occurrence of dengue hemorrhagic fever (DHF) is crucial. This study was conducted to determine trend and forecasting the occurrence of DHF in Asahan district, North Sumatera Province. Monthly reported dengue cases for the years 2012-2016 were obtained from the district health offices. A time series analysis was conducted by Autoregressive integrated moving average (ARIMA) modeling to forecast the occurrence of DHF. The results demonstrated that the reported DHF cases showed a seasonal variation. The SARIMA (1,0,0)(0,1,1)12 model was the best model and adequate for the data. The SARIMA model for DHF is necessary and could applied to predict the incidence of DHF in Asahan district and assist with design public health maesures to prevent and control the diseases.

Linear Algorithms for Radioelectric Spectrum Forecast

Directory of Open Access Journals (Sweden)

Luis F. Pedraza

2016-12-01

Full Text Available This paper presents the development and evaluation of two linear algorithms for forecasting reception power for different channels at an assigned spectrum band of global systems for mobile communications (GSM, in order to analyze the spatial opportunity for reuse of frequencies by secondary users (SUs in a cognitive radio (CR network. The algorithms employed correspond to seasonal autoregressive integrated moving average (SARIMA and generalized autoregressive conditional heteroskedasticity (GARCH, which allow for a forecast of channel occupancy status. Results are evaluated using the following criteria: availability and occupancy time for channels, different types of mean absolute error, and observation time. The contributions of this work include a more integral forecast as the algorithm not only forecasts reception power but also the occupancy and availability time of a channel to determine its precision percentage during the use by primary users (PUs and SUs within a CR system. Algorithm analyses demonstrate a better performance for SARIMA over GARCH algorithm in most of the evaluated variables.

O Moving Average Convergence Convergence-Divergence como Ferramenta para a Decisão de Investimentos no Mercado de Ações

Directory of Open Access Journals (Sweden)

Rodrigo Silva Vidotto

2009-04-01

Full Text Available The increase in the number of investors at Bovespa since 2000 is due to stabilized inflation and falling interest rates. The use of tools that assist investors in selling and buying stocks is very important in a competitive and risky market. The technical analysis of stocks is used to search for trends in the movements of share prices and therefore indicate a suitable moment to buy or sell stocks. Among these technical indicators is the Moving Average Convergence-Divergence [MACD], which uses the concept of moving average in its equation and is considered by financial analysts as a simple tool to operate and analyze. This article aims to assess the effectiveness of the use of the MACD to indicate the moment to purchase and sell stocks in five companies – selected at random – a total of ninety companies in the Bovespa New Market and analyze the profitability gained during 2006, taking as a reference the valorization of the Ibovespa exchange in that year. The results show that the cumulative average return of the five companies was of 26.7% against a cumulative average return of 0.90% for Ibovespa.

Statistical aspects of autoregressive-moving average models in the assessment of radon mitigation

International Nuclear Information System (INIS)

Dunn, J.E.; Henschel, D.B.

1989-01-01

Radon values, as reflected by hourly scintillation counts, seem dominated by major, pseudo-periodic, random fluctuations. This methodological paper reports a moderate degree of success in modeling these data using relatively simple autoregressive-moving average models to assess the effectiveness of radon mitigation techniques in existing housing. While accounting for the natural correlation of successive observations, familiar summary statistics such as steady state estimates, standard errors, confidence limits, and tests of hypothesis are produced. The Box-Jenkins approach is used throughout. In particular, intervention analysis provides an objective means of assessing the effectiveness of an active mitigation measure, such as a fan off/on cycle. Occasionally, failure to declare a significant intervention has suggested a means of remedial action in the data collection procedure

Electricity demand loads modeling using AutoRegressive Moving Average (ARMA) models

Energy Technology Data Exchange (ETDEWEB)

Pappas, S.S. [Department of Information and Communication Systems Engineering, University of the Aegean, Karlovassi, 83 200 Samos (Greece); Ekonomou, L.; Chatzarakis, G.E. [Department of Electrical Engineering Educators, ASPETE - School of Pedagogical and Technological Education, N. Heraklion, 141 21 Athens (Greece); Karamousantas, D.C. [Technological Educational Institute of Kalamata, Antikalamos, 24100 Kalamata (Greece); Katsikas, S.K. [Department of Technology Education and Digital Systems, University of Piraeus, 150 Androutsou Srt., 18 532 Piraeus (Greece); Liatsis, P. [Division of Electrical Electronic and Information Engineering, School of Engineering and Mathematical Sciences, Information and Biomedical Engineering Centre, City University, Northampton Square, London EC1V 0HB (United Kingdom)

2008-09-15

This study addresses the problem of modeling the electricity demand loads in Greece. The provided actual load data is deseasonilized and an AutoRegressive Moving Average (ARMA) model is fitted on the data off-line, using the Akaike Corrected Information Criterion (AICC). The developed model fits the data in a successful manner. Difficulties occur when the provided data includes noise or errors and also when an on-line/adaptive modeling is required. In both cases and under the assumption that the provided data can be represented by an ARMA model, simultaneous order and parameter estimation of ARMA models under the presence of noise are performed. The produced results indicate that the proposed method, which is based on the multi-model partitioning theory, tackles successfully the studied problem. For validation purposes the produced results are compared with three other established order selection criteria, namely AICC, Akaike's Information Criterion (AIC) and Schwarz's Bayesian Information Criterion (BIC). The developed model could be useful in the studies that concern electricity consumption and electricity prices forecasts. (author)

Autoregressive moving average fitting for real standard deviation in Monte Carlo power distribution calculation

International Nuclear Information System (INIS)

Ueki, Taro

2010-01-01

The noise propagation of tallies in the Monte Carlo power method can be represented by the autoregressive moving average process of orders p and p-1 (ARMA(p,p-1)], where p is an integer larger than or equal to two. The formula of the autocorrelation of ARMA(p,q), p≥q+1, indicates that ARMA(3,2) fitting is equivalent to lumping the eigenmodes of fluctuation propagation in three modes such as the slow, intermediate and fast attenuation modes. Therefore, ARMA(3,2) fitting was applied to the real standard deviation estimation of fuel assemblies at particular heights. The numerical results show that straightforward ARMA(3,2) fitting is promising but a stability issue must be resolved toward the incorporation in the distributed version of production Monte Carlo codes. The same numerical results reveal that the average performance of ARMA(3,2) fitting is equivalent to that of the batch method in MCNP with a batch size larger than one hundred and smaller than two hundred cycles for a 1100 MWe pressurized water reactor. The bias correction of low lag autocovariances in MVP/GMVP is demonstrated to have the potential of improving the average performance of ARMA(3,2) fitting. (author)

Evaluation of Seasonal, ANN, and Hybrid Models in Modeling Urban Water Consumption A Case Study of Rash City

Directory of Open Access Journals (Sweden)

Seyed Nematollah Mousavi

2016-09-01

Full Text Available Forecasting future water consumption in cities to plan for the required capacities in urban water supply systems (including water transmission networks and water treatment facilities depends on the application of behavioral models of uban water consumption. Being located in the North-South corridor, Rasht City is assuming a new role to play in the national economy as a foreign trade center. It will, thus, be necessary to review its present urban infrastructure in order to draft the required infrastructural development plans for meeting the city’s future water demands. The three Seasonal Autoregressive Integrated Moving Average (SARIMA, Artificial Neural Network (ANN, and SARIMABP approaches were employed in present study to model and forecast Rasht urban water consumption using monthly time series for the period 2001‒2008 of urban water consumption in Rasht. The seasonal unit root test was applied to develop the relevant SARIMA model. Results showed that all the seasonal and non-seasonal unit roots are present in all the frequencies in the monthly time series for Rasht urban water consumption. Using a proper filter, the SAIMA patterns were estimated. In a second stage the SARIMA output was used to determine the ANN output and the hybrid SARIMABP structure was accordingly constructed. The values for Rasht urban water consumption predicted by the three models indicated the superiority of the SARIMABP hybrid model as evidenced by the forecast error index of 0.41% obtained for this model. The other two models of SARIMA and ANN were, however, found to yield acceptable results for urban water managers since the forecasting error recorded for them was below 1%.

Assessment and prediction of road accident injuries trend using time-series models in Kurdistan.

Science.gov (United States)

Parvareh, Maryam; Karimi, Asrin; Rezaei, Satar; Woldemichael, Abraha; Nili, Sairan; Nouri, Bijan; Nasab, Nader Esmail

2018-01-01

Road traffic accidents are commonly encountered incidents that can cause high-intensity injuries to the victims and have direct impacts on the members of the society. Iran has one of the highest incident rates of road traffic accidents. The objective of this study was to model the patterns of road traffic accidents leading to injury in Kurdistan province, Iran. A time-series analysis was conducted to characterize and predict the frequency of road traffic accidents that lead to injury in Kurdistan province. The injuries were categorized into three separate groups which were related to the car occupants, motorcyclists and pedestrian road traffic accident injuries. The Box-Jenkins time-series analysis was used to model the injury observations applying autoregressive integrated moving average (ARIMA) and seasonal autoregressive integrated moving average (SARIMA) from March 2009 to February 2015 and to predict the accidents up to 24 months later (February 2017). The analysis was carried out using R-3.4.2 statistical software package. A total of 5199 pedestrians, 9015 motorcyclists, and 28,906 car occupants' accidents were observed. The mean (SD) number of car occupant, motorcyclist and pedestrian accident injuries observed were 401.01 (SD 32.78), 123.70 (SD 30.18) and 71.19 (SD 17.92) per year, respectively. The best models for the pattern of car occupant, motorcyclist, and pedestrian injuries were the ARIMA (1, 0, 0), SARIMA (1, 0, 2) (1, 0, 0) 12 , and SARIMA (1, 1, 1) (0, 0, 1) 12 , respectively. The motorcyclist and pedestrian injuries showed a seasonal pattern and the peak was during summer (August). The minimum frequency for the motorcyclist and pedestrian injuries were observed during the late autumn and early winter (December and January). Our findings revealed that the observed motorcyclist and pedestrian injuries had a seasonal pattern that was explained by air temperature changes overtime. These findings call the need for close monitoring of the

Medium term municipal solid waste generation prediction by autoregressive integrated moving average

International Nuclear Information System (INIS)

Younes, Mohammad K.; Nopiah, Z. M.; Basri, Noor Ezlin A.; Basri, Hassan

2014-01-01

Generally, solid waste handling and management are performed by municipality or local authority. In most of developing countries, local authorities suffer from serious solid waste management (SWM) problems and insufficient data and strategic planning. Thus it is important to develop robust solid waste generation forecasting model. It helps to proper manage the generated solid waste and to develop future plan based on relatively accurate figures. In Malaysia, solid waste generation rate increases rapidly due to the population growth and new consumption trends that characterize the modern life style. This paper aims to develop monthly solid waste forecasting model using Autoregressive Integrated Moving Average (ARIMA), such model is applicable even though there is lack of data and will help the municipality properly establish the annual service plan. The results show that ARIMA (6,1,0) model predicts monthly municipal solid waste generation with root mean square error equals to 0.0952 and the model forecast residuals are within accepted 95% confident interval

Medium term municipal solid waste generation prediction by autoregressive integrated moving average

Science.gov (United States)

Younes, Mohammad K.; Nopiah, Z. M.; Basri, Noor Ezlin A.; Basri, Hassan

2014-09-01

Generally, solid waste handling and management are performed by municipality or local authority. In most of developing countries, local authorities suffer from serious solid waste management (SWM) problems and insufficient data and strategic planning. Thus it is important to develop robust solid waste generation forecasting model. It helps to proper manage the generated solid waste and to develop future plan based on relatively accurate figures. In Malaysia, solid waste generation rate increases rapidly due to the population growth and new consumption trends that characterize the modern life style. This paper aims to develop monthly solid waste forecasting model using Autoregressive Integrated Moving Average (ARIMA), such model is applicable even though there is lack of data and will help the municipality properly establish the annual service plan. The results show that ARIMA (6,1,0) model predicts monthly municipal solid waste generation with root mean square error equals to 0.0952 and the model forecast residuals are within accepted 95% confident interval.

Shape and depth determinations from second moving average residual self-potential anomalies

International Nuclear Information System (INIS)

Abdelrahman, E M; El-Araby, T M; Essa, K S

2009-01-01

We have developed a semi-automatic method to determine the depth and shape (shape factor) of a buried structure from second moving average residual self-potential anomalies obtained from observed data using filters of successive window lengths. The method involves using a relationship between the depth and the shape to source and a combination of windowed observations. The relationship represents a parametric family of curves (window curves). For a fixed window length, the depth is determined for each shape factor. The computed depths are plotted against the shape factors, representing a continuous monotonically increasing curve. The solution for the shape and depth is read at the common intersection of the window curves. The validity of the method is tested on a synthetic example with and without random errors and on two field examples from Turkey and Germany. In all cases examined, the depth and the shape solutions obtained are in very good agreement with the true ones

Moving Average Filter-Based Phase-Locked Loops: Performance Analysis and Design Guidelines

DEFF Research Database (Denmark)

Golestan, Saeed; Ramezani, Malek; Guerrero, Josep M.

2014-01-01

this challenge, incorporating moving average filter(s) (MAF) into the PLL structure has been proposed in some recent literature. A MAF is a linear-phase finite impulse response filter which can act as an ideal low-pass filter, if certain conditions hold. The main aim of this paper is to present the control...... design guidelines for a typical MAF-based PLL. The paper starts with the general description of MAFs. The main challenge associated with using the MAFs is then explained, and its possible solutions are discussed. The paper then proceeds with a brief overview of the different MAF-based PLLs. In each case......, the PLL block diagram description is shown, the advantages and limitations are briefly discussed, and the tuning approach (if available) is evaluated. The paper then presents two systematic methods to design the control parameters of a typical MAF-based PLL: one for the case of using a proportional...

Medium term municipal solid waste generation prediction by autoregressive integrated moving average

Energy Technology Data Exchange (ETDEWEB)

Younes, Mohammad K.; Nopiah, Z. M.; Basri, Noor Ezlin A.; Basri, Hassan [Department of Civil and Structural Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor (Malaysia)

2014-09-12

Generally, solid waste handling and management are performed by municipality or local authority. In most of developing countries, local authorities suffer from serious solid waste management (SWM) problems and insufficient data and strategic planning. Thus it is important to develop robust solid waste generation forecasting model. It helps to proper manage the generated solid waste and to develop future plan based on relatively accurate figures. In Malaysia, solid waste generation rate increases rapidly due to the population growth and new consumption trends that characterize the modern life style. This paper aims to develop monthly solid waste forecasting model using Autoregressive Integrated Moving Average (ARIMA), such model is applicable even though there is lack of data and will help the municipality properly establish the annual service plan. The results show that ARIMA (6,1,0) model predicts monthly municipal solid waste generation with root mean square error equals to 0.0952 and the model forecast residuals are within accepted 95% confident interval.

PERAMALAN PERSEDIAAN INFUS MENGGUNAKAN METODE AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) PADA RUMAH SAKIT UMUM PUSAT SANGLAH

OpenAIRE

I PUTU YUDI PRABHADIKA; NI KETUT TARI TASTRAWATI; LUH PUTU IDA HARINI

2018-01-01

Infusion supplies are an important thing that must be considered by the hospital in meeting the needs of patients. This study aims to predict the need for infusion of 0.9% 500 ml of NaCl and 5% 500 ml glucose infusion at Sanglah General Hospital (RSUP) Sanglah so that the hospital can estimate the many infusions needed for the next six months. The forecasting method used in this research is the autoregressive integrated moving average (ARIMA) time series method. The results of this study indi...

On the speed towards the mean for continuous time autoregressive moving average processes with applications to energy markets

International Nuclear Information System (INIS)

Benth, Fred Espen; Taib, Che Mohd Imran Che

2013-01-01

We extend the concept of half life of an Ornstein–Uhlenbeck process to Lévy-driven continuous-time autoregressive moving average processes with stochastic volatility. The half life becomes state dependent, and we analyze its properties in terms of the characteristics of the process. An empirical example based on daily temperatures observed in Petaling Jaya, Malaysia, is presented, where the proposed model is estimated and the distribution of the half life is simulated. The stationarity of the dynamics yield futures prices which asymptotically tend to constant at an exponential rate when time to maturity goes to infinity. The rate is characterized by the eigenvalues of the dynamics. An alternative description of this convergence can be given in terms of our concept of half life. - Highlights: • The concept of half life is extended to Levy-driven continuous time autoregressive moving average processes • The dynamics of Malaysian temperatures are modeled using a continuous time autoregressive model with stochastic volatility • Forward prices on temperature become constant when time to maturity tends to infinity • Convergence in time to maturity is at an exponential rate given by the eigenvalues of the model temperature model

Dual-component model of respiratory motion based on the periodic autoregressive moving average (periodic ARMA) method

International Nuclear Information System (INIS)

McCall, K C; Jeraj, R

2007-01-01

A new approach to the problem of modelling and predicting respiration motion has been implemented. This is a dual-component model, which describes the respiration motion as a non-periodic time series superimposed onto a periodic waveform. A periodic autoregressive moving average algorithm has been used to define a mathematical model of the periodic and non-periodic components of the respiration motion. The periodic components of the motion were found by projecting multiple inhale-exhale cycles onto a common subspace. The component of the respiration signal that is left after removing this periodicity is a partially autocorrelated time series and was modelled as an autoregressive moving average (ARMA) process. The accuracy of the periodic ARMA model with respect to fluctuation in amplitude and variation in length of cycles has been assessed. A respiration phantom was developed to simulate the inter-cycle variations seen in free-breathing and coached respiration patterns. At ±14% variability in cycle length and maximum amplitude of motion, the prediction errors were 4.8% of the total motion extent for a 0.5 s ahead prediction, and 9.4% at 1.0 s lag. The prediction errors increased to 11.6% at 0.5 s and 21.6% at 1.0 s when the respiration pattern had ±34% variations in both these parameters. Our results have shown that the accuracy of the periodic ARMA model is more strongly dependent on the variations in cycle length than the amplitude of the respiration cycles

Average equilibrium charge state of 278113 ions moving in a helium gas

International Nuclear Information System (INIS)

Kaji, D.; Morita, K.; Morimoto, K.

2005-01-01

Difficulty to identify a new heavy element comes from the small production cross section. For example, the production cross section was about 0.5 pb in the case of searching for the 112th element produced by the cold fusion reaction of 208 Pb( 70 Zn,n) 277 ll2. In order to identify heavier elements than element 112, the experimental apparatus with a sensitivity of sub-pico barn level is essentially needed. A gas-filled recoil separator, in general, has a large collection efficiency compared with other recoil separators as seen from the operation principle of a gas-filled recoil separator. One of the most important parameters for a gas-filled recoil separator is the average equilibrium charge state q ave of ions moving in a used gas. This is because the recoil ion can not be properly transported to the focal plane of the separator, if the q ave of an element of interest in a gas is unknown. We have systematically measured equilibrium charge state distributions of heavy ions ( 169 Tm, 208 Pb, 193,209 Bi, 196 Po, 200 At, 203,204 Fr, 212 Ac, 234 Bk, 245 Fm, 254 No, 255 Lr, and 265 Hs) moving in a helium gas by using the gas-filled recoil separator GARIS at RIKEN. Ana then, the empirical formula on q ave of heavy ions in a helium gas was derived as a function of the velocity and the atomic number of an ion on the basis of the Tomas-Fermi model of the atom. The formula was found to be applicable to search for transactinide nuclides of 271 Ds, 272 Rg, and 277 112 produced by cold fusion reactions. Using the formula on q ave , we searched for a new isotope of element 113 produced by the cold fusion reaction of 209 Bi( 70 Zn,n) 278 113. As a result, a decay chain due to an evaporation residue of 278 113 was observed. Recently, we have successfully observed the 2nd decay chain due to an evaporation residue of 278 113. In this report, we will present experimental results in detail, and will also discuss the average equilibrium charge sate of 278 113 in a helium gas by

A time series analysis of environmental and metrological factors impact on cutaneous leishmaniasis incidence in an endemic area of Dehloran, Iran.

Science.gov (United States)

Nikonahad, Ali; Khorshidi, Ali; Ghaffari, Hamid Reza; Aval, Hamideh Ebrahimi; Miri, Mohammad; Amarloei, Ali; Nourmoradi, Heshmatollah; Mohammadi, Amir

2017-06-01

The aim of this study was to investigate the relationship between the environmental and metrological variables and cutaneous leishmaniasis (CL) transmission and its prediction in a region susceptible to this disease prevalence using a time series model. The accurate locations of 4437 CL diagnosed from 2011 to 2015 were obtained to be used in the time series model. Temperature, number of days with temperature over 30 °C, and number of earthquake were related to CL incidence using the Seasonal Auto-correlated Integrated Moving Average (SARIMA) model according to the Box-Jenkins method. In addition, the relationship between land use and surface soil type in 500- and 1000-m radius around the CL patients were investigated. The SARIMA models showed significant associations between environmental and meteorological variables and CL incidence adjusted for seasonality and auto-correlation. The result indicated that there are need more robust preventive programs in earthquake-prone areas with high temperature and inceptisol soil type than other areas. In addition, the region with these characteristics should be considered as high-risk areas for CL prevalence.

Robust nonlinear autoregressive moving average model parameter estimation using stochastic recurrent artificial neural networks

DEFF Research Database (Denmark)

Chon, K H; Hoyer, D; Armoundas, A A

1999-01-01

In this study, we introduce a new approach for estimating linear and nonlinear stochastic autoregressive moving average (ARMA) model parameters, given a corrupt signal, using artificial recurrent neural networks. This new approach is a two-step approach in which the parameters of the deterministic...... part of the stochastic ARMA model are first estimated via a three-layer artificial neural network (deterministic estimation step) and then reestimated using the prediction error as one of the inputs to the artificial neural networks in an iterative algorithm (stochastic estimation step). The prediction...... error is obtained by subtracting the corrupt signal of the estimated ARMA model obtained via the deterministic estimation step from the system output response. We present computer simulation examples to show the efficacy of the proposed stochastic recurrent neural network approach in obtaining accurate...

Time series modelling to forecast prehospital EMS demand for diabetic emergencies.

Science.gov (United States)

Villani, Melanie; Earnest, Arul; Nanayakkara, Natalie; Smith, Karen; de Courten, Barbora; Zoungas, Sophia

2017-05-05

Acute diabetic emergencies are often managed by prehospital Emergency Medical Services (EMS). The projected growth in prevalence of diabetes is likely to result in rising demand for prehospital EMS that are already under pressure. The aims of this study were to model the temporal trends and provide forecasts of prehospital attendances for diabetic emergencies. A time series analysis on monthly cases of hypoglycemia and hyperglycemia was conducted using data from the Ambulance Victoria (AV) electronic database between 2009 and 2015. Using the seasonal autoregressive integrated moving average (SARIMA) modelling process, different models were evaluated. The most parsimonious model with the highest accuracy was selected. Forty-one thousand four hundred fifty-four prehospital diabetic emergencies were attended over a seven-year period with an increase in the annual median monthly caseload between 2009 (484.5) and 2015 (549.5). Hypoglycemia (70%) and people with type 1 diabetes (48%) accounted for most attendances. The SARIMA (0,1,0,12) model provided the best fit, with a MAPE of 4.2% and predicts a monthly caseload of approximately 740 by the end of 2017. Prehospital EMS demand for diabetic emergencies is increasing. SARIMA time series models are a valuable tool to allow forecasting of future caseload with high accuracy and predict increasing cases of prehospital diabetic emergencies into the future. The model generated by this study may be used by service providers to allow appropriate planning and resource allocation of EMS for diabetic emergencies.

Synchronized moving aperture radiation therapy (SMART): average tumour trajectory for lung patients

International Nuclear Information System (INIS)

Neicu, Toni; Shirato, Hiroki; Seppenwoolde, Yvette; Jiang, Steve B

2003-01-01

Synchronized moving aperture radiation therapy (SMART) is a new technique for treating mobile tumours under development at Massachusetts General Hospital (MGH). The basic idea of SMART is to synchronize the moving radiation beam aperture formed by a dynamic multileaf collimator (DMLC) with the tumour motion induced by respiration. SMART is based on the concept of the average tumour trajectory (ATT) exhibited by a tumour during respiration. During the treatment simulation stage, tumour motion is measured and the ATT is derived. Then, the original IMRT MLC leaf sequence is modified using the ATT to compensate for tumour motion. During treatment, the tumour motion is monitored. The treatment starts when leaf motion and tumour motion are synchronized at a specific breathing phase. The treatment will halt when the tumour drifts away from the ATT and will resume when the synchronization between tumour motion and radiation beam is re-established. In this paper, we present a method to derive the ATT from measured tumour trajectory data. We also investigate the validity of the ATT concept for lung tumours during normal breathing. The lung tumour trajectory data were acquired during actual radiotherapy sessions using a real-time tumour-tracking system. SMART treatment is simulated by assuming that the radiation beam follows the derived ATT and the tumour follows the measured trajectory. In simulation, the treatment starts at exhale phase. The duty cycle of SMART delivery was calculated for various treatment times and gating thresholds, as well as for various exhale phases where the treatment begins. The simulation results show that in the case of free breathing, for 4 out of 11 lung datasets with tumour motion greater than 1 cm from peak to peak, the error in tumour tracking can be controlled to within a couple of millimetres while maintaining a reasonable delivery efficiency. That is to say, without any breath coaching/control, the ATT is a valid concept for some lung

Statistical Modeling and Prediction for Tourism Economy Using Dendritic Neural Network.

Science.gov (United States)

Yu, Ying; Wang, Yirui; Gao, Shangce; Tang, Zheng

2017-01-01

With the impact of global internationalization, tourism economy has also been a rapid development. The increasing interest aroused by more advanced forecasting methods leads us to innovate forecasting methods. In this paper, the seasonal trend autoregressive integrated moving averages with dendritic neural network model (SA-D model) is proposed to perform the tourism demand forecasting. First, we use the seasonal trend autoregressive integrated moving averages model (SARIMA model) to exclude the long-term linear trend and then train the residual data by the dendritic neural network model and make a short-term prediction. As the result showed in this paper, the SA-D model can achieve considerably better predictive performances. In order to demonstrate the effectiveness of the SA-D model, we also use the data that other authors used in the other models and compare the results. It also proved that the SA-D model achieved good predictive performances in terms of the normalized mean square error, absolute percentage of error, and correlation coefficient.

Strengthening economy through tourism sector by tourist arrival prediction

Science.gov (United States)

Supriatna, A.; Subartini, B.; Hertini, E.; Sukono; Rumaisha; Istiqamah, N.

2018-03-01

Tourism sector has a tendency to be proposed as a support for national economy to many countries with various of natural resources, such as Indonesia. The number of tourist is very related with the success rate of a tourist attraction, since it is also related with planning and strategy. Hence, it is important to predict the climate of tourism in Indonesia, especially the number of domestic or international tourist in the future. This study uses Seasonal Autoregressive Integrated Moving Average (SARIMA) time series method to predict the number of tourist arrival to tourism strategic areas in Nusa Tenggara Barat. The prediction was done using the international and domestic tourist arrival to Nusa Tenggara Barat data from January 2008 to June 2016. The established SARIMA method was (0,1,1)(0,0,2)12 with MAPE error of 15.76. The prediction for the next six time periods showed that the highest number of tourist arrival is during September 2016 with 330,516 tourist arrivals. Prediction of tourist arrival hopefully might be used as reference for local and national government to make policies to strengthen national economy for a long period of time

Forecasting typhoid fever incidence in the Cordillera administrative region in the Philippines using seasonal ARIMA models

Science.gov (United States)

Cawiding, Olive R.; Natividad, Gina May R.; Bato, Crisostomo V.; Addawe, Rizavel C.

2017-11-01

The prevalence of typhoid fever in developing countries such as the Philippines calls for a need for accurate forecasting of the disease. This will be of great assistance in strategic disease prevention. This paper presents a development of useful models that predict the behavior of typhoid fever incidence based on the monthly incidence in the provinces of the Cordillera Administrative Region from 2010 to 2015 using univariate time series analysis. The data used was obtained from the Cordillera Office of the Department of Health (DOH-CAR). Seasonal autoregressive moving average (SARIMA) models were used to incorporate the seasonality of the data. A comparison of the results of the obtained models revealed that the SARIMA (1,1,7)(0,0,1)12 with a fixed coefficient at the seventh lag produces the smallest root mean square error (RMSE), mean absolute error (MAE), Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC). The model suggested that for the year 2016, the number of cases would increase from the months of July to September and have a drop in December. This was then validated using the data collected from January 2016 to December 2016.

Swarm Intelligence-Based Hybrid Models for Short-Term Power Load Prediction

Directory of Open Access Journals (Sweden)

Jianzhou Wang

2014-01-01

Full Text Available Swarm intelligence (SI is widely and successfully applied in the engineering field to solve practical optimization problems because various hybrid models, which are based on the SI algorithm and statistical models, are developed to further improve the predictive abilities. In this paper, hybrid intelligent forecasting models based on the cuckoo search (CS as well as the singular spectrum analysis (SSA, time series, and machine learning methods are proposed to conduct short-term power load prediction. The forecasting performance of the proposed models is augmented by a rolling multistep strategy over the prediction horizon. The test results are representative of the out-performance of the SSA and CS in tuning the seasonal autoregressive integrated moving average (SARIMA and support vector regression (SVR in improving load forecasting, which indicates that both the SSA-based data denoising and SI-based intelligent optimization strategy can effectively improve the model’s predictive performance. Additionally, the proposed CS-SSA-SARIMA and CS-SSA-SVR models provide very impressive forecasting results, demonstrating their strong robustness and universal forecasting capacities in terms of short-term power load prediction 24 hours in advance.

The application of moving average control charts for evaluating magnetic field quality on an individual magnet basis

International Nuclear Information System (INIS)

Pollock, D.A.; Gunst, R.F.; Schucany, W.R.

1994-01-01

SSC Collider Dipole Magnet field quality specifications define limits of variation for the population mean (Systematic) and standard deviation (RMS deviation) of allowed and unallowed multipole coefficients generated by the full collection of dipole magnets throughout the Collider operating cycle. A fundamental Quality Control issue is how to determine the acceptability of individual magnets during production, in other words taken one at a time and compared to the population parameters. Provided that the normal distribution assumptions hold, the random variation of multipoles for individual magnets may be evaluated by comparing the measured results to ± 3 x RMS tolerance, centered on the design nominal. To evaluate the local and cumulative systematic variation of the magnets against the distribution tolerance, individual magnet results need to be combined with others that come before it. This paper demonstrates a Statistical Quality Control method (the Unweighted Moving Average control chart) to evaluate individual magnet performance and process stability against population tolerances. The DESY/HERA Dipole cold skew quadrupole measurements for magnets in production order are used to evaluate non-stationarity of the mean over time for the cumulative set of magnets, as well as for a moving sample

Assessing air quality in Aksaray with time series analysis

Science.gov (United States)

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.

Modelling and analysis of turbulent datasets using Auto Regressive Moving Average processes

International Nuclear Information System (INIS)

Faranda, Davide; Dubrulle, Bérengère; Daviaud, François; Pons, Flavio Maria Emanuele; Saint-Michel, Brice; Herbert, Éric; Cortet, Pierre-Philippe

2014-01-01

We introduce a novel way to extract information from turbulent datasets by applying an Auto Regressive Moving Average (ARMA) statistical analysis. Such analysis goes well beyond the analysis of the mean flow and of the fluctuations and links the behavior of the recorded time series to a discrete version of a stochastic differential equation which is able to describe the correlation structure in the dataset. We introduce a new index Υ that measures the difference between the resulting analysis and the Obukhov model of turbulence, the simplest stochastic model reproducing both Richardson law and the Kolmogorov spectrum. We test the method on datasets measured in a von Kármán swirling flow experiment. We found that the ARMA analysis is well correlated with spatial structures of the flow, and can discriminate between two different flows with comparable mean velocities, obtained by changing the forcing. Moreover, we show that the Υ is highest in regions where shear layer vortices are present, thereby establishing a link between deviations from the Kolmogorov model and coherent structures. These deviations are consistent with the ones observed by computing the Hurst exponents for the same time series. We show that some salient features of the analysis are preserved when considering global instead of local observables. Finally, we analyze flow configurations with multistability features where the ARMA technique is efficient in discriminating different stability branches of the system

Comparing a recursive digital filter with the moving-average and sequential probability-ratio detection methods for SNM portal monitors

International Nuclear Information System (INIS)

Fehlau, P.E.

1993-01-01

The author compared a recursive digital filter proposed as a detection method for French special nuclear material monitors with the author's detection methods, which employ a moving-average scaler or a sequential probability-ratio test. Each of these nine test subjects repeatedly carried a test source through a walk-through portal monitor that had the same nuisance-alarm rate with each method. He found that the average detection probability for the test source is also the same for each method. However, the recursive digital filter may have on drawback: its exponentially decreasing response to past radiation intensity prolongs the impact of any interference from radiation sources of radiation-producing machinery. He also examined the influence of each test subject on the monitor's operation by measuring individual attenuation factors for background and source radiation, then ranked the subjects' attenuation factors against their individual probabilities for detecting the test source. The one inconsistent ranking was probably caused by that subject's unusually long stride when passing through the portal

Power Based Phase-Locked Loop Under Adverse Conditions with Moving Average Filter for Single-Phase System

Directory of Open Access Journals (Sweden)

Menxi Xie

2017-06-01

Full Text Available High performance synchronization methord is citical for grid connected power converter. For single-phase system, power based phase-locked loop(pPLL uses a multiplier as phase detector(PD. As single-phase grid voltage is distorted, the phase error information contains ac disturbances oscillating at integer multiples of fundamental frequency which lead to detection error. This paper presents a new scheme based on moving average filter(MAF applied in-loop of pPLL. The signal characteristic of phase error is dissussed in detail. A predictive rule is adopted to compensate the delay induced by MAF, thus achieving fast dynamic response. In the case of frequency deviate from nomimal, estimated frequency is fed back to adjust the filter window length of MAF and buffer size of predictive rule. Simulation and experimental results show that proposed PLL achieves good performance under adverse grid conditions.

Statistical Modeling and Prediction for Tourism Economy Using Dendritic Neural Network

Directory of Open Access Journals (Sweden)

Ying Yu

2017-01-01

Full Text Available With the impact of global internationalization, tourism economy has also been a rapid development. The increasing interest aroused by more advanced forecasting methods leads us to innovate forecasting methods. In this paper, the seasonal trend autoregressive integrated moving averages with dendritic neural network model (SA-D model is proposed to perform the tourism demand forecasting. First, we use the seasonal trend autoregressive integrated moving averages model (SARIMA model to exclude the long-term linear trend and then train the residual data by the dendritic neural network model and make a short-term prediction. As the result showed in this paper, the SA-D model can achieve considerably better predictive performances. In order to demonstrate the effectiveness of the SA-D model, we also use the data that other authors used in the other models and compare the results. It also proved that the SA-D model achieved good predictive performances in terms of the normalized mean square error, absolute percentage of error, and correlation coefficient.

Time series analysis of dengue incidence in Guadeloupe, French West Indies: Forecasting models using climate variables as predictors

Directory of Open Access Journals (Sweden)

Ruche Guy

2011-06-01

Full Text Available Abstract Background During the last decades, dengue viruses have spread throughout the Americas region, with an increase in the number of severe forms of dengue. The surveillance system in Guadeloupe (French West Indies is currently operational for the detection of early outbreaks of dengue. The goal of the study was to improve this surveillance system by assessing a modelling tool to predict the occurrence of dengue epidemics few months ahead and thus to help an efficient dengue control. Methods The Box-Jenkins approach allowed us to fit a Seasonal Autoregressive Integrated Moving Average (SARIMA model of dengue incidence from 2000 to 2006 using clinical suspected cases. Then, this model was used for calculating dengue incidence for the year 2007 compared with observed data, using three different approaches: 1 year-ahead, 3 months-ahead and 1 month-ahead. Finally, we assessed the impact of meteorological variables (rainfall, temperature and relative humidity on the prediction of dengue incidence and outbreaks, incorporating them in the model fitting the best. Results The 3 months-ahead approach was the most appropriate for an effective and operational public health response, and the most accurate (Root Mean Square Error, RMSE = 0.85. Relative humidity at lag-7 weeks, minimum temperature at lag-5 weeks and average temperature at lag-11 weeks were variables the most positively correlated to dengue incidence in Guadeloupe, meanwhile rainfall was not. The predictive power of SARIMA models was enhanced by the inclusion of climatic variables as external regressors to forecast the year 2007. Temperature significantly affected the model for better dengue incidence forecasting (p-value = 0.03 for minimum temperature lag-5, p-value = 0.02 for average temperature lag-11 but not humidity. Minimum temperature at lag-5 weeks was the best climatic variable for predicting dengue outbreaks (RMSE = 0.72. Conclusion Temperature improves dengue outbreaks forecasts

Nonlinear Autoregressive Network with the Use of a Moving Average Method for Forecasting Typhoon Tracks

OpenAIRE

Tienfuan Kerh; Shin-Hung Wu

2017-01-01

Forecasting of a typhoon moving path may help to evaluate the potential negative impacts in the neighbourhood areas along the moving path. This study proposed a work of using both static and dynamic neural network models to link a time series of typhoon track parameters including longitude and latitude of the typhoon central location, cyclonic radius, central wind speed, and typhoon moving speed. Based on the historical records of 100 typhoons, the performances of neural network models are ev...

Forecast of sea surface temperature off the Peruvian coast using an autoregressive integrated moving average model

Directory of Open Access Journals (Sweden)

Carlos Quispe

2013-04-01

Full Text Available El Niño connects globally climate, ecosystems and socio-economic activities. Since 1980 this event has been tried to be predicted, but until now the statistical and dynamical models are insuffi cient. Thus, the objective of the present work was to explore using an autoregressive moving average model the effect of El Niño over the sea surface temperature (TSM off the Peruvian coast. The work involved 5 stages: identifi cation, estimation, diagnostic checking, forecasting and validation. Simple and partial autocorrelation functions (FAC and FACP were used to identify and reformulate the orders of the model parameters, as well as Akaike information criterium (AIC and Schwarz criterium (SC for the selection of the best models during the diagnostic checking. Among the main results the models ARIMA(12,0,11 were proposed, which simulated monthly conditions in agreement with the observed conditions off the Peruvian coast: cold conditions at the end of 2004, and neutral conditions at the beginning of 2005.

Experimental validation of heterogeneity-corrected dose-volume prescription on respiratory-averaged CT images in stereotactic body radiotherapy for moving tumors

International Nuclear Information System (INIS)

Nakamura, Mitsuhiro; Miyabe, Yuki; Matsuo, Yukinori; Kamomae, Takeshi; Nakata, Manabu; Yano, Shinsuke; Sawada, Akira; Mizowaki, Takashi; Hiraoka, Masahiro

2012-01-01

The purpose of this study was to experimentally assess the validity of heterogeneity-corrected dose-volume prescription on respiratory-averaged computed tomography (RACT) images in stereotactic body radiotherapy (SBRT) for moving tumors. Four-dimensional computed tomography (CT) data were acquired while a dynamic anthropomorphic thorax phantom with a solitary target moved. Motion pattern was based on cos (t) with a constant respiration period of 4.0 sec along the longitudinal axis of the CT couch. The extent of motion (A 1 ) was set in the range of 0.0–12.0 mm at 3.0-mm intervals. Treatment planning with the heterogeneity-corrected dose-volume prescription was designed on RACT images. A new commercially available Monte Carlo algorithm of well-commissioned 6-MV photon beam was used for dose calculation. Dosimetric effects of intrafractional tumor motion were then investigated experimentally under the same conditions as 4D CT simulation using the dynamic anthropomorphic thorax phantom, films, and an ionization chamber. The passing rate of γ index was 98.18%, with the criteria of 3 mm/3%. The dose error between the planned and the measured isocenter dose in moving condition was within ± 0.7%. From the dose area histograms on the film, the mean ± standard deviation of the dose covering 100% of the cross section of the target was 102.32 ± 1.20% (range, 100.59–103.49%). By contrast, the irradiated areas receiving more than 95% dose for A 1 = 12 mm were 1.46 and 1.33 times larger than those for A 1 = 0 mm in the coronal and sagittal planes, respectively. This phantom study demonstrated that the cross section of the target received 100% dose under moving conditions in both the coronal and sagittal planes, suggesting that the heterogeneity-corrected dose-volume prescription on RACT images is acceptable in SBRT for moving tumors.

Treatment on outliers in UBJ-SARIMA models for forecasting dengue cases on age groups not eligible for vaccination in Baguio City, Philippines

Science.gov (United States)

Magsakay, Clarenz B.; De Vera, Nora U.; Libatique, Criselda P.; Addawe, Rizavel C.; Addawe, Joel M.

2017-11-01

Dengue vaccination has become a breakthrough in the fight against dengue infection. This is however not applicable to all ages. Individuals from 0 to 8 years old and adults older than 45 years old remain susceptible to the vector-borne disease dengue. Forecasting future dengue cases accurately from susceptible age groups would aid in the efforts to prevent further increase in dengue infections. For the age groups of individuals not eligible for vaccination, the presence of outliers was observed and was treated using winsorization, square root, and logarithmic transformations to create a SARIMA model. The best model for the age group 0 to 8 years old was found to be ARIMA(13,1,0)(1,0,0)12 with 10 fixed variables using square root transformation with a 95% winsorization, and the best model for the age group older than 45 years old is ARIMA(7,1,0)(1,0,0)12 with 5 fixed variables using logarithmic transformation with 90% winsorization. These models are then used to forecast the monthly dengue cases for Baguio City for the age groups considered.

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

Science.gov (United States)

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%.

Simple Moving Voltage Average Incremental Conductance MPPT Technique with Direct Control Method under Nonuniform Solar Irradiance Conditions

Directory of Open Access Journals (Sweden)

Amjad Ali

2015-01-01

Full Text Available A new simple moving voltage average (SMVA technique with fixed step direct control incremental conductance method is introduced to reduce solar photovoltaic voltage (VPV oscillation under nonuniform solar irradiation conditions. To evaluate and validate the performance of the proposed SMVA method in comparison with the conventional fixed step direct control incremental conductance method under extreme conditions, different scenarios were simulated. Simulation results show that in most cases SMVA gives better results with more stability as compared to traditional fixed step direct control INC with faster tracking system along with reduction in sustained oscillations and possesses fast steady state response and robustness. The steady state oscillations are almost eliminated because of extremely small dP/dV around maximum power (MP, which verify that the proposed method is suitable for standalone PV system under extreme weather conditions not only in terms of bus voltage stability but also in overall system efficiency.

PERAMALAN DERET WAKTU MENGGUNAKAN MODEL FUNGSI BASIS RADIAL (RBF DAN AUTO REGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA

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DT Wiyanti

2013-07-01

Full Text Available Salah satu metode peramalan yang paling dikembangkan saat ini adalah time series, yakni menggunakan pendekatan kuantitatif dengan data masa lampau yang dijadikan acuan untuk peramalan masa depan. Berbagai penelitian telah mengusulkan metode-metode untuk menyelesaikan time series, di antaranya statistik, jaringan syaraf, wavelet, dan sistem fuzzy. Metode-metode tersebut memiliki kekurangan dan keunggulan yang berbeda. Namun permasalahan yang ada dalam dunia nyata merupakan masalah yang kompleks. Satu metode saja mungkin tidak mampu mengatasi masalah tersebut dengan baik. Dalam artikel ini dibahas penggabungan dua buah metode yaitu Auto Regressive Integrated Moving Average (ARIMA dan Radial Basis Function (RBF. Alasan penggabungan kedua metode ini adalah karena adanya asumsi bahwa metode tunggal tidak dapat secara total mengidentifikasi semua karakteristik time series. Pada artikel ini dibahas peramalan terhadap data Indeks Harga Perdagangan Besar (IHPB dan data inflasi komoditi Indonesia; kedua data berada pada rentang tahun 2006 hingga beberapa bulan di tahun 2012. Kedua data tersebut masing-masing memiliki enam variabel. Hasil peramalan metode ARIMA-RBF dibandingkan dengan metode ARIMA dan metode RBF secara individual. Hasil analisa menunjukkan bahwa dengan metode penggabungan ARIMA dan RBF, model yang diberikan memiliki hasil yang lebih akurat dibandingkan dengan penggunaan salah satu metode saja. Hal ini terlihat dalam visual plot, MAPE, dan RMSE dari semua variabel pada dua data uji coba. The accuracy of time series forecasting is the subject of many decision-making processes. Time series use a quantitative approach to employ data from the past to make forecast for the future. Many researches have proposed several methods to solve time series, such as using statistics, neural networks, wavelets, and fuzzy systems. These methods have different advantages and disadvantages. But often the problem in the real world is just too complex that a

Books average previous decade of economic misery.

Science.gov (United States)

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.

Books Average Previous Decade of Economic Misery

Science.gov (United States)

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

A hybrid procedure for MSW generation forecasting at multiple time scales in Xiamen City, China

International Nuclear Information System (INIS)

Xu, Lilai; Gao, Peiqing; Cui, Shenghui; Liu, Chun

2013-01-01

Highlights: ► We propose a hybrid model that combines seasonal SARIMA model and grey system theory. ► The model is robust at multiple time scales with the anticipated accuracy. ► At month-scale, the SARIMA model shows good representation for monthly MSW generation. ► At medium-term time scale, grey relational analysis could yield the MSW generation. ► At long-term time scale, GM (1, 1) provides a basic scenario of MSW generation. - Abstract: Accurate forecasting of municipal solid waste (MSW) generation is crucial and fundamental for the planning, operation and optimization of any MSW management system. Comprehensive information on waste generation for month-scale, medium-term and long-term time scales is especially needed, considering the necessity of MSW management upgrade facing many developing countries. Several existing models are available but of little use in forecasting MSW generation at multiple time scales. The goal of this study is to propose a hybrid model that combines the seasonal autoregressive integrated moving average (SARIMA) model and grey system theory to forecast MSW generation at multiple time scales without needing to consider other variables such as demographics and socioeconomic factors. To demonstrate its applicability, a case study of Xiamen City, China was performed. Results show that the model is robust enough to fit and forecast seasonal and annual dynamics of MSW generation at month-scale, medium- and long-term time scales with the desired accuracy. In the month-scale, MSW generation in Xiamen City will peak at 132.2 thousand tonnes in July 2015 – 1.5 times the volume in July 2010. In the medium term, annual MSW generation will increase to 1518.1 thousand tonnes by 2015 at an average growth rate of 10%. In the long term, a large volume of MSW will be output annually and will increase to 2486.3 thousand tonnes by 2020 – 2.5 times the value for 2010. The hybrid model proposed in this paper can enable decision makers to

A hybrid procedure for MSW generation forecasting at multiple time scales in Xiamen City, China

Energy Technology Data Exchange (ETDEWEB)

Xu, Lilai, E-mail: llxu@iue.ac.cn [Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, 1799 Jimei Road, Xiamen 361021 (China); Xiamen Key Lab of Urban Metabolism, Xiamen 361021 (China); Gao, Peiqing, E-mail: peiqing15@yahoo.com.cn [Xiamen City Appearance and Environmental Sanitation Management Office, 51 Hexiangxi Road, Xiamen 361004 (China); Cui, Shenghui, E-mail: shcui@iue.ac.cn [Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, 1799 Jimei Road, Xiamen 361021 (China); Xiamen Key Lab of Urban Metabolism, Xiamen 361021 (China); Liu, Chun, E-mail: xmhwlc@yahoo.com.cn [Xiamen City Appearance and Environmental Sanitation Management Office, 51 Hexiangxi Road, Xiamen 361004 (China)

2013-06-15

Highlights: ► We propose a hybrid model that combines seasonal SARIMA model and grey system theory. ► The model is robust at multiple time scales with the anticipated accuracy. ► At month-scale, the SARIMA model shows good representation for monthly MSW generation. ► At medium-term time scale, grey relational analysis could yield the MSW generation. ► At long-term time scale, GM (1, 1) provides a basic scenario of MSW generation. - Abstract: Accurate forecasting of municipal solid waste (MSW) generation is crucial and fundamental for the planning, operation and optimization of any MSW management system. Comprehensive information on waste generation for month-scale, medium-term and long-term time scales is especially needed, considering the necessity of MSW management upgrade facing many developing countries. Several existing models are available but of little use in forecasting MSW generation at multiple time scales. The goal of this study is to propose a hybrid model that combines the seasonal autoregressive integrated moving average (SARIMA) model and grey system theory to forecast MSW generation at multiple time scales without needing to consider other variables such as demographics and socioeconomic factors. To demonstrate its applicability, a case study of Xiamen City, China was performed. Results show that the model is robust enough to fit and forecast seasonal and annual dynamics of MSW generation at month-scale, medium- and long-term time scales with the desired accuracy. In the month-scale, MSW generation in Xiamen City will peak at 132.2 thousand tonnes in July 2015 – 1.5 times the volume in July 2010. In the medium term, annual MSW generation will increase to 1518.1 thousand tonnes by 2015 at an average growth rate of 10%. In the long term, a large volume of MSW will be output annually and will increase to 2486.3 thousand tonnes by 2020 – 2.5 times the value for 2010. The hybrid model proposed in this paper can enable decision makers to

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

Science.gov (United States)

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.

Short-term electricity prices forecasting based on support vector regression and Auto-regressive integrated moving average modeling

International Nuclear Information System (INIS)

Che Jinxing; Wang Jianzhou

2010-01-01

In this paper, we present the use of different mathematical models to forecast electricity price under deregulated power. A successful prediction tool of electricity price can help both power producers and consumers plan their bidding strategies. Inspired by that the support vector regression (SVR) model, with the ε-insensitive loss function, admits of the residual within the boundary values of ε-tube, we propose a hybrid model that combines both SVR and Auto-regressive integrated moving average (ARIMA) models to take advantage of the unique strength of SVR and ARIMA models in nonlinear and linear modeling, which is called SVRARIMA. A nonlinear analysis of the time-series indicates the convenience of nonlinear modeling, the SVR is applied to capture the nonlinear patterns. ARIMA models have been successfully applied in solving the residuals regression estimation problems. The experimental results demonstrate that the model proposed outperforms the existing neural-network approaches, the traditional ARIMA models and other hybrid models based on the root mean square error and mean absolute percentage error.

Forecasting Construction Tender Price Index in Ghana using Autoregressive Integrated Moving Average with Exogenous Variables Model

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Ernest Kissi

2018-03-01

Full Text Available Prices of construction resources keep on fluctuating due to unstable economic situations that have been experienced over the years. Clients knowledge of their financial commitments toward their intended project remains the basis for their final decision. The use of construction tender price index provides a realistic estimate at the early stage of the project. Tender price index (TPI is influenced by various economic factors, hence there are several statistical techniques that have been employed in forecasting. Some of these include regression, time series, vector error correction among others. However, in recent times the integrated modelling approach is gaining popularity due to its ability to give powerful predictive accuracy. Thus, in line with this assumption, the aim of this study is to apply autoregressive integrated moving average with exogenous variables (ARIMAX in modelling TPI. The results showed that ARIMAX model has a better predictive ability than the use of the single approach. The study further confirms the earlier position of previous research of the need to use the integrated model technique in forecasting TPI. This model will assist practitioners to forecast the future values of tender price index. Although the study focuses on the Ghanaian economy, the findings can be broadly applicable to other developing countries which share similar economic characteristics.

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

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Chieh-Fan Chen

2011-01-01

Full Text Available 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.

MOTION ARTIFACT REDUCTION IN FUNCTIONAL NEAR INFRARED SPECTROSCOPY SIGNALS BY AUTOREGRESSIVE MOVING AVERAGE MODELING BASED KALMAN FILTERING

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MEHDI AMIAN

2013-10-01

Full Text Available Functional near infrared spectroscopy (fNIRS is a technique that is used for noninvasive measurement of the oxyhemoglobin (HbO2 and deoxyhemoglobin (HHb concentrations in the brain tissue. Since the ratio of the concentration of these two agents is correlated with the neuronal activity, fNIRS can be used for the monitoring and quantifying the cortical activity. The portability of fNIRS makes it a good candidate for studies involving subject's movement. The fNIRS measurements, however, are sensitive to artifacts generated by subject's head motion. This makes fNIRS signals less effective in such applications. In this paper, the autoregressive moving average (ARMA modeling of the fNIRS signal is proposed for state-space representation of the signal which is then fed to the Kalman filter for estimating the motionless signal from motion corrupted signal. Results are compared to the autoregressive model (AR based approach, which has been done previously, and show that the ARMA models outperform AR models. We attribute it to the richer structure, containing more terms indeed, of ARMA than AR. We show that the signal to noise ratio (SNR is about 2 dB higher for ARMA based method.

Neural networks prediction and fault diagnosis applied to stationary and non stationary ARMA (Autoregressive moving average) modeled time series

International Nuclear Information System (INIS)

Marseguerra, M.; Minoggio, S.; Rossi, A.; Zio, E.

1992-01-01

The correlated noise affecting many industrial plants under stationary or cyclo-stationary conditions - nuclear reactors included -has been successfully modeled by autoregressive moving average (ARMA) due to the versatility of this technique. The relatively recent neural network methods have similar features and much effort is being devoted to exploring their usefulness in forecasting and control. Identifying a signal by means of an ARMA model gives rise to the problem of selecting its correct order. Similar difficulties must be faced when applying neural network methods and, specifically, particular care must be given to the setting up of the appropriate network topology, the data normalization procedure and the learning code. In the present paper the capability of some neural networks of learning ARMA and seasonal ARMA processes is investigated. The results of the tested cases look promising since they indicate that the neural networks learn the underlying process with relative ease so that their forecasting capability may represent a convenient fault diagnosis tool. (Author)

Forecasting of energy and diesel consumption and the cost of energy production in isolated electrical systems in the Amazon using a fuzzification process in time series models

Energy Technology Data Exchange (ETDEWEB)

Neto, Joao C. do L, E-mail: jcaldas@ufam.edu.br [Group of Optimization and Fuzzy Systems, Federal University of Amazonas, General Rodrigo Octavio Jordao Ramos Avenue, 3000, Academic Campus, 69077-000 Manaus, Amazonas (Brazil); Costa Junior, Carlos T. da [Postgraduate Program in Electrical Engineering, Institute of Technology, Federal University of Para, Augusto Correa Street, 1, Guama, 66075-900 Belem, Para (Brazil); Bitar, Sandro D.B. [Group of Optimization and Fuzzy Systems, Federal University of Amazonas, General Rodrigo Octavio Jordao Ramos Avenue, 3000, Academic Campus, 69077-000 Manaus, Amazonas (Brazil); Junior, Walter B. [Postgraduate Program in Electrical Engineering, Institute of Technology, Federal University of Para, Augusto Correa Street, 1, Guama, 66075-900 Belem, Para (Brazil)

2011-09-15

Understanding the uncertainty inherent in the analysis of diesel fuel consumption and its impact on the generation of electricity is an important topic for planning the expansion of isolated thermoelectric systems in the state of Amazonas. In light of this, a decision support system has been developed to forecast the cost of electricity production using non-stationary data by integrating the methodology of time series models with fuzzy systems and optimization tools. The method presented herein combines the potential of the Autoregressive Integrated Moving Average (ARIMA) and the Seasonal ARIMA (SARIMA) models, such as the forecasting tool, with the advantages of fuzzy set theory to compensate for the uncertainties and errors encountered in the observed data, which would degrade the validity of forecasted values. The results show that incorporation of the {alpha}-cut concept facilitated the evaluation of risks while allowing simultaneous consideration of intervals for the unitary cost of energy production. This provides the analyst with the ability to make decisions using various predicted intervals with different membership values instead of the common practice of simply using the specific costs. - Highlights: > A decision support system has been developed using SARIMA with fuzzy systems and optimizations tools. > It assists the decision-making process for planning the expansion in isolated thermoelectric systems. > The {alpha}-cut concept facilitated the evaluation of risks for the cost of electricity production. > Provides decisions using various forecasted interval for this cost with different membership values.

Forecasting of energy and diesel consumption and the cost of energy production in isolated electrical systems in the Amazon using a fuzzification process in time series models

International Nuclear Information System (INIS)

Neto, Joao C. do L; Costa Junior, Carlos T. da; Bitar, Sandro D.B.; Junior, Walter B.

2011-01-01

Understanding the uncertainty inherent in the analysis of diesel fuel consumption and its impact on the generation of electricity is an important topic for planning the expansion of isolated thermoelectric systems in the state of Amazonas. In light of this, a decision support system has been developed to forecast the cost of electricity production using non-stationary data by integrating the methodology of time series models with fuzzy systems and optimization tools. The method presented herein combines the potential of the Autoregressive Integrated Moving Average (ARIMA) and the Seasonal ARIMA (SARIMA) models, such as the forecasting tool, with the advantages of fuzzy set theory to compensate for the uncertainties and errors encountered in the observed data, which would degrade the validity of forecasted values. The results show that incorporation of the α-cut concept facilitated the evaluation of risks while allowing simultaneous consideration of intervals for the unitary cost of energy production. This provides the analyst with the ability to make decisions using various predicted intervals with different membership values instead of the common practice of simply using the specific costs. - Highlights: → A decision support system has been developed using SARIMA with fuzzy systems and optimizations tools. → It assists the decision-making process for planning the expansion in isolated thermoelectric systems. → The α-cut concept facilitated the evaluation of risks for the cost of electricity production. → Provides decisions using various forecasted interval for this cost with different membership values.

Time series analytics using sliding window metaheuristic optimization-based machine learning system for identifying building energy consumption patterns

International Nuclear Information System (INIS)

Chou, Jui-Sheng; Ngo, Ngoc-Tri

2016-01-01

Highlights: • This study develops a novel time-series sliding window forecast system. • The system integrates metaheuristics, machine learning and time-series models. • Site experiment of smart grid infrastructure is installed to retrieve real-time data. • The proposed system accurately predicts energy consumption in residential buildings. • The forecasting system can help users minimize their electricity usage. - Abstract: Smart grids are a promising solution to the rapidly growing power demand because they can considerably increase building energy efficiency. This study developed a novel time-series sliding window metaheuristic optimization-based machine learning system for predicting real-time building energy consumption data collected by a smart grid. The proposed system integrates a seasonal autoregressive integrated moving average (SARIMA) model and metaheuristic firefly algorithm-based least squares support vector regression (MetaFA-LSSVR) model. Specifically, the proposed system fits the SARIMA model to linear data components in the first stage, and the MetaFA-LSSVR model captures nonlinear data components in the second stage. Real-time data retrieved from an experimental smart grid installed in a building were used to evaluate the efficacy and effectiveness of the proposed system. A k-week sliding window approach is proposed for employing historical data as input for the novel time-series forecasting system. The prediction system yielded high and reliable accuracy rates in 1-day-ahead predictions of building energy consumption, with a total error rate of 1.181% and mean absolute error of 0.026 kW h. Notably, the system demonstrates an improved accuracy rate in the range of 36.8–113.2% relative to those of the linear forecasting model (i.e., SARIMA) and nonlinear forecasting models (i.e., LSSVR and MetaFA-LSSVR). Therefore, end users can further apply the forecasted information to enhance efficiency of energy usage in their buildings, especially

ELECTRICITY DEMAND FORECASTING USING A SARIMAMULTIPLICATIVE SINGLE NEURON HYBRID MODEL

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JUAN DAVID VELÁSQUEZ HENAO

2013-01-01

Full Text Available La combinación de modelos SARIMA y redes neuronales son una aproximación común para pronosticar series de tiempo no lineales. Mientras la metodología SARIMA es usada para capturar las componentes lineales en la serie de tiempo, las redes neuronales artifi ciales son aplicadas para pronosticar las no-linealidades remanentes en los residuos del modelo SARIMA. En este artículo, se propone un modelo simple no lineal para el pronóstico de series de tiempo obtenido por la combinación de un modelo SARIMA y una neurona simple multiplicativa que usa las mismas entradas del modelo SARIMA. Para evaluar la capacidad de la nueva aproximación, la demanda mensual de electricidad en el mercado de energía de Colombia es pronosticada y comparada con los modelos SARIMA y la neurona simple multiplicativa.

Time series analysis of cholera in Matlab, Bangladesh, during 1988-2001.

Science.gov (United States)

Ali, Mohammad; Kim, Deok Ryun; Yunus, Mohammad; Emch, Michael

2013-03-01

The study examined the impact of in-situ climatic and marine environmental variability on cholera incidence in an endemic area of Bangladesh and developed a forecasting model for understanding the magnitude of incidence. Diarrhoea surveillance data collected between 1988 and 2001 were obtained from a field research site in Matlab, Bangladesh. Cholera cases were defined as Vibrio cholerae O1 isolated from faecal specimens of patients who sought care at treatment centres serving the Matlab population. Cholera incidence for 168 months was correlated with remotely-sensed sea-surface temperature (SST) and in-situ environmental data, including rainfall and ambient temperature. A seasonal autoregressive integrated moving average (SARIMA) model was used for determining the impact of climatic and environmental variability on cholera incidence and evaluating the ability of the model to forecast the magnitude of cholera. There were 4,157 cholera cases during the study period, with an average of 1.4 cases per 1,000 people. Since monthly cholera cases varied significantly by month, it was necessary to stabilize the variance of cholera incidence by computing the natural logarithm to conduct the analysis. The SARIMA model shows temporal clustering of cholera at one- and 12-month lags. There was a 6% increase in cholera incidence with a minimum temperature increase of one degree celsius in the current month. For increase of SST by one degree celsius, there was a 25% increase in the cholera incidence at currrent month and 18% increase in the cholera incidence at two months. Rainfall did not influenc to cause variation in cholera incidence during the study period. The model forecast the fluctuation of cholera incidence in Matlab reasonably well (Root mean square error, RMSE: 0.108). Thus, the ambient and sea-surface temperature-based model could be used in forecasting cholera outbreaks in Matlab.

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

Science.gov (United States)

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

Consensus in averager-copier-voter networks of moving dynamical agents

Science.gov (United States)

Shang, Yilun

2017-02-01

This paper deals with a hybrid opinion dynamics comprising averager, copier, and voter agents, which ramble as random walkers on a spatial network. Agents exchange information following some deterministic and stochastic protocols if they reside at the same site in the same time. Based on stochastic stability of Markov chains, sufficient conditions guaranteeing consensus in the sense of almost sure convergence have been obtained. The ultimate consensus state is identified in the form of an ergodicity result. Simulation studies are performed to validate the effectiveness and availability of our theoretical results. The existence/non-existence of voters and the proportion of them are unveiled to play key roles during the consensus-reaching process.

The application of seasonal latent variable in forecasting electricity demand as an alternative method

International Nuclear Information System (INIS)

Sumer, Kutluk Kagan; Goktas, Ozlem; Hepsag, Aycan

2009-01-01

In this study, we used ARIMA, seasonal ARIMA (SARIMA) and alternatively the regression model with seasonal latent variable in forecasting electricity demand by using data that belongs to 'Kayseri and Vicinity Electricity Joint-Stock Company' over the 1997:1-2005:12 periods. This study tries to examine the advantages of forecasting with ARIMA, SARIMA methods and with the model has seasonal latent variable to each other. The results support that ARIMA and SARIMA models are unsuccessful in forecasting electricity demand. The regression model with seasonal latent variable used in this study gives more successful results than ARIMA and SARIMA models because also this model can consider seasonal fluctuations and structural breaks

FPGA based computation of average neutron flux and e-folding period for start-up range of reactors

International Nuclear Information System (INIS)

Ram, Rajit; Borkar, S.P.; Dixit, M.Y.; Das, Debashis

2013-01-01

Pulse processing instrumentation channels used for reactor applications, play a vital role to ensure nuclear safety in startup range of reactor operation and also during fuel loading and first approach to criticality. These channels are intended for continuous run time computation of equivalent reactor core neutron flux and e-folding period. This paper focuses only the computational part of these instrumentation channels which is implemented in single FPGA using 32-bit floating point arithmetic engine. The computations of average count rate, log of average count rate, log rate and reactor period are done in VHDL using digital circuit realization approach. The computation of average count rate is done using fully adaptive window size moving average method, while Taylor series expansion for logarithms is implemented in FPGA to compute log of count rate, log rate and reactor e-folding period. This paper describes the block diagrams of digital logic realization in FPGA and advantage of fully adaptive window size moving average technique over conventional fixed size moving average technique for pulse processing of reactor instrumentations. (author)

Improved Multiscale Entropy Technique with Nearest-Neighbor Moving-Average Kernel for Nonlinear and Nonstationary Short-Time Biomedical Signal Analysis

Directory of Open Access Journals (Sweden)

S. P. Arunachalam

2018-01-01

Full Text Available Analysis of biomedical signals can yield invaluable information for prognosis, diagnosis, therapy evaluation, risk assessment, and disease prevention which is often recorded as short time series data that challenges existing complexity classification algorithms such as Shannon entropy (SE and other techniques. The purpose of this study was to improve previously developed multiscale entropy (MSE technique by incorporating nearest-neighbor moving-average kernel, which can be used for analysis of nonlinear and non-stationary short time series physiological data. The approach was tested for robustness with respect to noise analysis using simulated sinusoidal and ECG waveforms. Feasibility of MSE to discriminate between normal sinus rhythm (NSR and atrial fibrillation (AF was tested on a single-lead ECG. In addition, the MSE algorithm was applied to identify pivot points of rotors that were induced in ex vivo isolated rabbit hearts. The improved MSE technique robustly estimated the complexity of the signal compared to that of SE with various noises, discriminated NSR and AF on single-lead ECG, and precisely identified the pivot points of ex vivo rotors by providing better contrast between the rotor core and the peripheral region. The improved MSE technique can provide efficient complexity analysis of variety of nonlinear and nonstationary short-time biomedical signals.

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

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Haroldo V Ribeiro

Full Text Available 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.

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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.

Multi-pulse orbits and chaotic dynamics in motion of parametrically excited viscoelastic moving belt

International Nuclear Information System (INIS)

Zhang Wei; Yao Minghui

2006-01-01

In this paper, the Shilnikov type multi-pulse orbits and chaotic dynamics of parametrically excited viscoelastic moving belt are studied in detail. Using Kelvin-type viscoelastic constitutive law, the equations of motion for viscoelastic moving belt with the external damping and parametric excitation are given. The four-dimensional averaged equation under the case of primary parametric resonance is obtained by directly using the method of multiple scales and Galerkin's approach to the partial differential governing equation of viscoelastic moving belt. From the averaged equations obtained here, the theory of normal form is used to give the explicit expressions of normal form with a double zero and a pair of pure imaginary eigenvalues. Based on normal form, the energy-phrase method is employed to analyze the global bifurcations and chaotic dynamics in parametrically excited viscoelastic moving belt. The global bifurcation analysis indicates that there exist the heteroclinic bifurcations and the Silnikov type multi-pulse homoclinic orbits in the averaged equation. The results obtained above mean the existence of the chaos for the Smale horseshoe sense in parametrically excited viscoelastic moving belt. The chaotic motions of viscoelastic moving belts are also found by using numerical simulation. A new phenomenon on the multi-pulse jumping orbits is observed from three-dimensional phase space

Time Series ARIMA Models of Undergraduate Grade Point Average.

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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…

The Effect of Direction on Cursor Moving Kinematics

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Chiu-Ping Lu

2012-02-01

Full Text Available There have been only few studies to substantiate the kinematic characteristics of cursor movement. In this study, a quantitative experimental research method was used to explore the effect of moving direction on the kinematics of cursor movement in 24 typical young persons using our previously developed computerized measuring program. The results of multiple one way repeated measures ANOVAs and post hoc LSD tests demonstrated that the moving direction had effects on average velocity, movement time, movement unit and peak velocity. Moving leftward showed better efficiency than moving rightward, upward and downward from the kinematic evidences such as velocity, movement unit and time. Moreover, the unique pattern of the power spectral density (PSD of velocity (strategy for power application explained why the smoothness was still maintained while moving leftward even under an unstable situation with larger momentum. Moreover, the information from this cursor moving study can guide us to relocate the toolbars and icons in the window interface, especially for individuals with physical disabilities whose performances are easily interrupted while controlling the cursor in specific directions.

A landslide-quake detection algorithm with STA/LTA and diagnostic functions of moving average and scintillation index: A preliminary case study of the 2009 Typhoon Morakot in Taiwan

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Wu, Yu-Jie; Lin, Guan-Wei

2017-04-01

Since 1999, Taiwan has experienced a rapid rise in the number of landslides, and the number even reached a peak after the 2009 Typhoon Morakot. Although it is proved that the ground-motion signals induced by slope processes could be recorded by seismograph, it is difficult to be distinguished from continuous seismic records due to the lack of distinct P and S waves. In this study, we combine three common seismic detectors including the short-term average/long-term average (STA/LTA) approach, and two diagnostic functions of moving average and scintillation index. Based on these detectors, we have established an auto-detection algorithm of landslide-quakes and the detection thresholds are defined to distinguish landslide-quake from earthquakes and background noises. To further improve the proposed detection algorithm, we apply it to seismic archives recorded by Broadband Array in Taiwan for Seismology (BATS) during the 2009 Typhoon Morakots and consequently the discrete landslide-quakes detected by the automatic algorithm are located. The detection algorithm show that the landslide-detection results are consistent with that of visual inspection and hence can be used to automatically monitor landslide-quakes.

Heterogeneous CPU-GPU moving targets detection for UAV video

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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.

Transport of the moving barrier driven by chiral active particles

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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.

The moving-window Bayesian maximum entropy framework: estimation of PM(2.5) yearly average concentration across the contiguous United States.

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Akita, Yasuyuki; Chen, Jiu-Chiuan; Serre, Marc L

2012-09-01

Geostatistical methods are widely used in estimating long-term exposures for epidemiological studies on air pollution, despite their limited capabilities to handle spatial non-stationarity over large geographic domains and the uncertainty associated with missing monitoring data. We developed a moving-window (MW) Bayesian maximum entropy (BME) method and applied this framework to estimate fine particulate matter (PM(2.5)) yearly average concentrations over the contiguous US. The MW approach accounts for the spatial non-stationarity, while the BME method rigorously processes the uncertainty associated with data missingness in the air-monitoring system. In the cross-validation analyses conducted on a set of randomly selected complete PM(2.5) data in 2003 and on simulated data with different degrees of missing data, we demonstrate that the MW approach alone leads to at least 17.8% reduction in mean square error (MSE) in estimating the yearly PM(2.5). Moreover, the MWBME method further reduces the MSE by 8.4-43.7%, with the proportion of incomplete data increased from 18.3% to 82.0%. The MWBME approach leads to significant reductions in estimation error and thus is recommended for epidemiological studies investigating the effect of long-term exposure to PM(2.5) across large geographical domains with expected spatial non-stationarity.

The moving-window Bayesian Maximum Entropy framework: Estimation of PM2.5 yearly average concentration across the contiguous United States

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Akita, Yasuyuki; Chen, Jiu-Chiuan; Serre, Marc L.

2013-01-01

Geostatistical methods are widely used in estimating long-term exposures for air pollution epidemiological studies, despite their limited capabilities to handle spatial non-stationarity over large geographic domains and uncertainty associated with missing monitoring data. We developed a moving-window (MW) Bayesian Maximum Entropy (BME) method and applied this framework to estimate fine particulate matter (PM2.5) yearly average concentrations over the contiguous U.S. The MW approach accounts for the spatial non-stationarity, while the BME method rigorously processes the uncertainty associated with data missingnees in the air monitoring system. In the cross-validation analyses conducted on a set of randomly selected complete PM2.5 data in 2003 and on simulated data with different degrees of missing data, we demonstrate that the MW approach alone leads to at least 17.8% reduction in mean square error (MSE) in estimating the yearly PM2.5. Moreover, the MWBME method further reduces the MSE by 8.4% to 43.7% with the proportion of incomplete data increased from 18.3% to 82.0%. The MWBME approach leads to significant reductions in estimation error and thus is recommended for epidemiological studies investigating the effect of long-term exposure to PM2.5 across large geographical domains with expected spatial non-stationarity. PMID:22739679

Simulation And Forecasting of Daily Pm10 Concentrations Using Autoregressive Models In Kagithane Creek Valley, Istanbul

Science.gov (United States)

Ağaç, Kübra; Koçak, Kasım; Deniz, Ali

2015-04-01

A time series approach using autoregressive model (AR), moving average model (MA) and seasonal autoregressive integrated moving average model (SARIMA) were used in this study to simulate and forecast daily PM10 concentrations in Kagithane Creek Valley, Istanbul. Hourly PM10 concentrations have been measured in Kagithane Creek Valley between 2010 and 2014 periods. Bosphorus divides the city in two parts as European and Asian parts. The historical part of the city takes place in Golden Horn. Our study area Kagithane Creek Valley is connected with this historical part. The study area is highly polluted because of its topographical structure and industrial activities. Also population density is extremely high in this site. The dispersion conditions are highly poor in this creek valley so it is necessary to calculate PM10 levels for air quality and human health. For given period there were some missing PM10 concentration values so to make an accurate calculations and to obtain exact results gap filling method was applied by Singular Spectrum Analysis (SSA). SSA is a new and efficient method for gap filling and it is an state-of-art modeling. SSA-MTM Toolkit was used for our study. SSA is considered as a noise reduction algorithm because it decomposes an original time series to trend (if exists), oscillatory and noise components by way of a singular value decomposition. The basic SSA algorithm has stages of decomposition and reconstruction. For given period daily and monthly PM10 concentrations were calculated and episodic periods are determined. Long term and short term PM10 concentrations were analyzed according to European Union (EU) standards. For simulation and forecasting of high level PM10 concentrations, meteorological data (wind speed, pressure and temperature) were used to see the relationship between daily PM10 concentrations. Fast Fourier Transformation (FFT) was also applied to the data to see the periodicity and according to these periods models were built

Autoregressive moving average (ARMA) model applied to quantification of cerebral blood flow using dynamic susceptibility contrast-enhanced magnetic resonance imaging

International Nuclear Information System (INIS)

Murase, Kenya; Yamazaki, Youichi; Shinohara, Masaaki

2003-01-01

The purpose of this study was to investigate the feasibility of the autoregressive moving average (ARMA) model for quantification of cerebral blood flow (CBF) with dynamic susceptibility contrast-enhanced magnetic resonance imaging (DSC-MRI) in comparison with deconvolution analysis based on singular value decomposition (DA-SVD). Using computer simulations, we generated a time-dependent concentration of the contrast agent in the volume of interest (VOI) from the arterial input function (AIF) modeled as a gamma-variate function under various CBFs, cerebral blood volumes and signal-to-noise ratios (SNRs) for three different types of residue function (exponential, triangular, and box-shaped). We also considered the effects of delay and dispersion in AIF. The ARMA model and DA-SVD were used to estimate CBF values from the simulated concentration-time curves in the VOI and AIFs, and the estimated values were compared with the assumed values. We found that the CBF value estimated by the ARMA model was more sensitive to the SNR and the delay in AIF than that obtained by DA-SVD. Although the ARMA model considerably overestimated CBF at low SNRs, it estimated the CBF more accurately than did DA-SVD at high SNRs for the exponential or triangular residue function. We believe this study will contribute to an understanding of the usefulness and limitations of the ARMA model when applied to quantification of CBF with DSC-MRI. (author)

Middle and long-term prediction of UT1-UTC based on combination of Gray Model and Autoregressive Integrated Moving Average

Science.gov (United States)

Jia, Song; Xu, Tian-he; Sun, Zhang-zhen; Li, Jia-jing

2017-02-01

UT1-UTC is an important part of the Earth Orientation Parameters (EOP). The high-precision predictions of UT1-UTC play a key role in practical applications of deep space exploration, spacecraft tracking and satellite navigation and positioning. In this paper, a new prediction method with combination of Gray Model (GM(1, 1)) and Autoregressive Integrated Moving Average (ARIMA) is developed. The main idea is as following. Firstly, the UT1-UTC data are preprocessed by removing the leap second and Earth's zonal harmonic tidal to get UT1R-TAI data. Periodic terms are estimated and removed by the least square to get UT2R-TAI. Then the linear terms of UT2R-TAI data are modeled by the GM(1, 1), and the residual terms are modeled by the ARIMA. Finally, the UT2R-TAI prediction can be performed based on the combined model of GM(1, 1) and ARIMA, and the UT1-UTC predictions are obtained by adding the corresponding periodic terms, leap second correction and the Earth's zonal harmonic tidal correction. The results show that the proposed model can be used to predict UT1-UTC effectively with higher middle and long-term (from 32 to 360 days) accuracy than those of LS + AR, LS + MAR and WLS + MAR.

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

Science.gov (United States)

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.

Dog days of summer: Influences on decision of wolves to move pups

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Ausband, David E.; Mitchell, Michael S.; Bassing, Sarah B.; Nordhagen, Matthew; Smith, Douglas W.; Stahler, Daniel R.

2016-01-01

For animals that forage widely, protecting young from predation can span relatively long time periods due to the inability of young to travel with and be protected by their parents. Moving relatively immobile young to improve access to important resources, limit detection of concentrated scent by predators, and decrease infestations by ectoparasites can be advantageous. Moving young, however, can also expose them to increased mortality risks (e.g., accidents, getting lost, predation). For group-living animals that live in variable environments and care for young over extended time periods, the influence of biotic factors (e.g., group size, predation risk) and abiotic factors (e.g., temperature and precipitation) on the decision to move young is unknown. We used data from 25 satellite-collared wolves ( Canis lupus ) in Idaho, Montana, and Yellowstone National Park to evaluate how these factors could influence the decision to move pups during the pup-rearing season. We hypothesized that litter size, the number of adults in a group, and perceived predation risk would positively affect the number of times gray wolves moved pups. We further hypothesized that wolves would move their pups more often when it was hot and dry to ensure sufficient access to water. Contrary to our hypothesis, monthly temperature above the 30-year average was negatively related to the number of times wolves moved their pups. Monthly precipitation above the 30-year average, however, was positively related to the amount of time wolves spent at pup-rearing sites after leaving the natal den. We found little relationship between risk of predation (by grizzly bears, humans, or conspecifics) or group and litter sizes and number of times wolves moved their pups. Our findings suggest that abiotic factors most strongly influence the decision of wolves to move pups, although responses to unpredictable biotic events (e.g., a predator encountering pups) cannot be ruled out.

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

International Nuclear Information System (INIS)

Bovy, Jo; Hogg, David W.

2010-01-01

The velocity distribution of nearby stars (∼<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 eponymous 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.

CHARCOAL PRICE ANALYSIS IN FOUR REGIONS OF MINAS GERAIS STATE-BRAZIL

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José Luiz Pereira de Rezende

2005-09-01

Full Text Available The State of Minas Gerais is the largest producer and consumer of charcoal, that is used as term-reducer of iron ore,for producing pig iron. This study analyzed the time series of charcoal prices in four regions of Minas Gerais State. For the analysisof the price series, the SARIMA model was used, for finding a model that better forecasts prices for the four studied areas. The mostappropriate models were chosen using graphical analyses of the standardized residues, autocorrelation functions and partialautocorrelations, stochastic tests and criteria of evaluation of the order of the model. It concluded that: the differences of charcoalprices occur, basically, due to the geographical location; the analyses of domain of the time and domain of the frequency showed thatthere is difference in the price series of the four studied areas; the areas of Sete Lagoas and Belo Horizonte, giving that they are closelylocated, possess similar prices and they generated similar model; the studied areas presented differentiated models and supplied goodadjustments for the observed series. The best models were SARIMA (2,1,1x(1,0,012, for Belo Horizonte; SARIMA (2,0,0x(2,1,212,for Divinópolis; SARIMA (2,1,1x(1,0,012, for Sete Lagoas and SARIMA (1,1,1x(1,1,112, for Vertentes. Such models presented in aparsimonious way, containing a small number of parameters. All models SARIMA (p,d,q (P,D,Qs, for the four studied areas,presented white noise and supplied adequate price forecast.

Remote sensing-based time series models for malaria early warning in the highlands of Ethiopia

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Midekisa Alemayehu

2012-05-01

Full Text Available Abstract Background Malaria is one of the leading public health problems in most of sub-Saharan Africa, particularly in Ethiopia. Almost all demographic groups are at risk of malaria because of seasonal and unstable transmission of the disease. Therefore, there is a need to develop malaria early-warning systems to enhance public health decision making for control and prevention of malaria epidemics. Data from orbiting earth-observing sensors can monitor environmental risk factors that trigger malaria epidemics. Remotely sensed environmental indicators were used to examine the influences of climatic and environmental variability on temporal patterns of malaria cases in the Amhara region of Ethiopia. Methods In this study seasonal autoregressive integrated moving average (SARIMA models were used to quantify the relationship between malaria cases and remotely sensed environmental variables, including rainfall, land-surface temperature (LST, vegetation indices (NDVI and EVI, and actual evapotranspiration (ETa with lags ranging from one to three months. Predictions from the best model with environmental variables were compared to the actual observations from the last 12 months of the time series. Results Malaria cases exhibited positive associations with LST at a lag of one month and positive associations with indicators of moisture (rainfall, EVI and ETa at lags from one to three months. SARIMA models that included these environmental covariates had better fits and more accurate predictions, as evidenced by lower AIC and RMSE values, than models without environmental covariates. Conclusions Malaria risk indicators such as satellite-based rainfall estimates, LST, EVI, and ETa exhibited significant lagged associations with malaria cases in the Amhara region and improved model fit and prediction accuracy. These variables can be monitored frequently and extensively across large geographic areas using data from earth-observing sensors to support public

ANALISIS CURAH HUJAN DAN DEBIT MODEL SWAT DENGAN METODE MOVING AVERAGE DI DAS CILIWUNG HULU

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Defri Satiya Zuma

2017-09-01

Full Text Available Watershed can be regarded as a hydrological system that has a function in transforming rainwater as an input into outputs such as flow and sediment. The transformation of inputs into outputs has specific forms and properties. The transformation involves many processes, including processes occurred on the surface of the land, river basins, in soil and aquifer. This study aimed to apply the SWAT model  in  Ciliwung Hulu Watershed, asses the effect of average rainfall  on 3 days, 5 days, 7 days and 10 days of the hydrological characteristics in Ciliwung Hulu Watershed. The correlation coefficient (r between rainfall and discharge was positive, it indicated that there was an unidirectional relationship between rainfall and discharge in the upstream, midstream and downstream of the watershed. The upper limit ratio of discharge had a downward trend from upstream to downstream, while the lower limit ratio of  discharge had an upward trend from upstream to downstream. It showed that the discharge peak in Ciliwung  Hulu Watershed from upstream to downstream had a downward trend while the baseflow from upstream to downstream had an upward trend. It showed that the upstream of Ciliwung Hulu Watershed had the highest ratio of discharge peak  and baseflow so it needs the soil and water conservations and technical civil measures. The discussion concluded that the SWAT model could be well applied in Ciliwung Hulu Watershed, the most affecting average rainfall on the hydrological characteristics was the average rainfall of 10 days. On average  rainfall of 10 days, all components had contributed maximally for river discharge.

On critical cases in limit theory for stationary increments Lévy driven moving averages

DEFF Research Database (Denmark)

Basse-O'Connor, Andreas; Podolskij, Mark

averages. The limit theory heavily depends on the interplay between the given order of the increments, the considered power, the Blumenthal-Getoor index of the driving pure jump Lévy process L and the behavior of the kernel function g at 0. In this work we will study the critical cases, which were...

Combined influence of multiple climatic factors on the incidence of bacterial foodborne diseases.

Science.gov (United States)

Park, Myoung Su; Park, Ki Hwan; Bahk, Gyung Jin

2018-01-01

Information regarding the relationship between the incidence of foodborne diseases (FBD) and climatic factors is useful in designing preventive strategies for FBD based on anticipated future climate change. To better predict the effect of climate change on foodborne pathogens, the present study investigated the combined influence of multiple climatic factors on bacterial FBD incidence in South Korea. During 2011-2015, the relationships between 8 climatic factors and the incidences of 13 bacterial FBD, were determined based on inpatient stays, on a monthly basis using the Pearson correlation analyses, multicollinearity tests, principal component analysis (PCA), and the seasonal autoregressive integrated moving average (SARIMA) modeling. Of the 8 climatic variables, the combination of temperature, relative humidity, precipitation, insolation, and cloudiness was significantly associated with salmonellosis (Pclimatic factors. These findings indicate that the relationships between multiple climatic factors and bacterial FBD incidence can be valuable for the development of prediction models for future patterns of diseases in response to changes in climate. Copyright © 2017 Elsevier B.V. All rights reserved.

Canada’s 2010 Tax Competitiveness Ranking: Moving to the Average but Biased Against Services

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Duanjie Chen

2011-02-01

Full Text Available For the first time since 1975 (the year Canada’s marginal effective tax rates were first measured, Canada has become the most tax-competitive country among G-7 states with respect to taxation of capital investment. Even more remarkably, Canada accomplished this feat within a mere six years, having previously been the least taxcompetitive G-7 member. Even in comparison to strongly growing emerging economies, Canada’s 2010 marginal effective tax rate on capital is still above average. The planned reductions in federal and provincial corporate taxes by 2013 will reduce Canada’s effective tax rate on new investments to 18.4 percent, below the Organization for Economic Co-operation and Development (OECD 2010 average and close to the average of the 50 non-OECD countries studied. This remarkable change in Canada’s tax competitiveness must be maintained in the coming years, as countries are continually reducing their business taxation despite the recent fiscal pressures arising from the 2008-9 downturn in the world economy. Many countries have forged ahead with significant reforms designed to increase tax competitiveness and improve tax neutrality including Greece, Israel, Japan, New Zealand, Taiwan and the United Kingdom. The continuing bias in Canada’s corporate income tax structure favouring manufacturing and processing business warrants close scrutiny. Measured by the difference between the marginal effective tax rate on capital between manufacturing and the broad range of service sectors, Canada has the greatest gap in tax burdens between manufacturing and services among OECD countries. Surprisingly, preferential tax treatment (such as fast write-off and investment tax credits favouring only manufacturing and processing activities has become the norm in Canada, although it does not exist in most developed economies.

Plans, Patterns, and Move Categories Guiding a Highly Selective Search

Science.gov (United States)

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.

Optimization of Moving Coil Actuators for Digital Displacement Machines

DEFF Research Database (Denmark)

Nørgård, Christian; Bech, Michael Møller; Roemer, Daniel Beck

2016-01-01

This paper focuses on deriving an optimal moving coil actuator design, used as force pro-ducing element in hydraulic on/off valves for Digital Displacement machines. Different moving coil actuator geometry topologies (permanent magnet placement and magnetiza-tion direction) are optimized for actu......This paper focuses on deriving an optimal moving coil actuator design, used as force pro-ducing element in hydraulic on/off valves for Digital Displacement machines. Different moving coil actuator geometry topologies (permanent magnet placement and magnetiza-tion direction) are optimized...... for actuating annular seat valves in a digital displacement machine. The optimization objectives are to the minimize the actuator power, the valve flow losses and the height of the actuator. Evaluation of the objective function involves static finite element simulation and simulation of an entire operation...... designs requires approximately 20 W on average and may be realized in 20 mm × Ø 22.5 mm (height × diameter) for a 20 kW pressure chamber. The optimization is carried out using the multi-objective Generalized Differential Evolu-tion optimization algorithm GDE3 which successfully handles constrained multi-objective...

Comparison of wintertime CO to NOx ratios to MOVES and MOBILE6.2 on-road emissions inventories

Science.gov (United States)

Wallace, H. W.; Jobson, B. T.; Erickson, M. H.; McCoskey, J. K.; VanReken, T. M.; Lamb, B. K.; Vaughan, J. K.; Hardy, R. J.; Cole, J. L.; Strachan, S. M.; Zhang, W.

2012-12-01

The CO-to-NOx molar emission ratios from the US EPA vehicle emissions models MOVES and MOBILE6.2 were compared to urban wintertime measurements of CO and NOx. Measurements of CO, NOx, and volatile organic compounds were made at a regional air monitoring site in Boise, Idaho for 2 months from December 2008 to January 2009. The site is impacted by roadway emissions from a nearby busy urban arterial roads and highway. The measured CO-to-NOx ratio for morning rush hour periods was 4.2 ± 0.6. The average CO-to-NOx ratio during weekdays between the hours of 08:00 and 18:00 when vehicle miles travelled were highest was 5.2 ± 0.5. For this time period, MOVES yields an average hourly CO-to-NOx ratio of 9.1 compared to 20.2 for MOBILE6.2. Off-network emissions are a significant fraction of the CO and NOx emissions in MOVES, accounting for 65% of total CO emissions, and significantly increase the CO-to-NOx molar ratio. Observed ratios were more similar to the average hourly running emissions for urban roads determined by MOVES to be 4.3.

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

Razana Alwee

2013-01-01

Full Text Available 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.

Moving In, Moving Through, and Moving Out: The Transitional Experiences of Foster Youth College Students

Science.gov (United States)

Gamez, Sara I.

2017-01-01

The purpose of this qualitative study was to explore the transitional experiences of foster youth college students. The study explored how foster youth experienced moving into, moving through, and moving out of the college environment and what resources and strategies they used to thrive during their college transitions. In addition, this study…

Developing a comprehensive measure of mobility: mobility over varied environments scale (MOVES).

Science.gov (United States)

Hirsch, Jana A; Winters, Meghan; Sims-Gould, Joanie; Clarke, Philippa J; Ste-Marie, Nathalie; Ashe, Maureen; McKay, Heather A

2017-05-25

While recent work emphasizes the multi-dimensionality of mobility, no current measure incorporates multiple domains of mobility. Using existing conceptual frameworks we identified four domains of mobility (physical, cognitive, social, transportation) to create a "Mobility Over Varied Environments Scale" (MOVES). We then assessed expected patterns of MOVES in the Canadian population. An expert panel identified survey items within each MOVES domain from the Canadian Community Health Survey- Healthy Aging Cycle (2008-2009) for 28,555 (weighted population n = 12,805,067) adults (≥45 years). We refined MOVES using principal components analysis and Cronbach's alpha and weighted items so each domain was 10 points. Expected mobility trends, as assessed by average MOVES, were examined by sociodemographic and health factors, and by province, using Analysis of Variance (ANOVA). MOVES ranged from 0 to 40, where 0 represents individuals who are immobile and 40 those who are fully mobile. Mean MOVES was 29.58 (95% confidence interval (CI) 29.49, 29.67) (10th percentile: 24.17 (95% CI 23.96, 24.38), 90th percentile: 34.70 (CI 34.55, 34.85)). MOVES scores were lower for older, female, and non-white Canadians with worse health and lower socioeconomic status. MOVES was also lower for those who live in less urban areas. MOVES is a holistic measure of mobility for characterizing older adult mobility across populations. Future work should examine individual or neighborhood predictors of MOVES and its relationship to broader health outcomes. MOVES holds utility for research, surveillance, evaluation, and interventions around the broad factors influencing mobility in older adults.

Random walk of passive tracers among randomly moving obstacles.

Science.gov (United States)

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.

Óbitos por desnutrição em idosos, São Paulo e Rio de Janeiro: análise de séries temporais. 1980-1996 Deaths due to malnutrition in the elderly, São Paulo e Rio de Janeiro: time series analyse. 1980-1996

Directory of Open Access Journals (Sweden)

Ubirani Barros Otero

2001-11-01

Full Text Available OBJETIVOS: Descrever a evolução da mortalidade por desnutrição em idosos nas Regiões Metropolitanas dos Estados do Rio de Janeiro (RMRJ e São Paulo (RMSP, verificar as suas tendências, entre 1980 e 1996, e propor um modelo que permita prever a ocorrência de casos. METODOLOGIA: Trata-se de um estudo ecológico, de séries temporais, baseado em dados secundários. Foram incluídos no estudo indivíduos com 60 anos de idade ou mais, de ambos os sexos, das RMRJ e RMSP. A fonte de dados utilizada foi o Sistema de Informações sobre Mortalidade (SIM. Analisou-se a série de casos mensais, no período de janeiro de 1980 a dezembro de 1996. Para modelagem da série e predição de casos por desnutrição em idosos, utilizou-se o método Box and Jenkins, SARIMA (Sazonal Autoregressive Integrated Moving Average. RESULTADOS: Os resultados apontam a existência de sazonalidade, com maior número de óbitos nos meses de junho e julho na RMSP, no mês de janeiro na RMRJ, provavelmente, decorrente do clima frio, nestes meses, em São Paulo e do calor intenso no Rio de Janeiro. Este resultado pode ser explicado pela possibilidade de idosos, com estado nutricional comprometido, terem dificuldades em manter a temperatura corporal normal durante os meses de inverno, representando um estresse adicional a um organismo sem reservas. CONCLUSÕES: As séries apresentaram tendência de aumento e revelaram um padrão sazonal no inverno na RMSP e no verão na RMRJ. Ao estimar os modelos SARIMA para as Regiões para o ano de 1996, os resultados reforçaram a hipótese de que este método pode ser eficiente para fazer previsões futuras. Provavelmente um estudo que leve em consideração causas múltiplas de morte permitirá verificar a real contribuição da desnutrição como causa básica ou contributiva para a morte. Infelizmente, até este momento, esses dados não estão disponíveis para análise.OBJECTIVES: To describe mortality evolution of malnutrition in

Job Surfing: Move On to Move Up.

Science.gov (United States)

Martin, Justin

1997-01-01

Looks at the process of switching jobs and changing careers. Discusses when to consider options and make the move as well as the need to be flexible and open minded. Provides a test for determining the chances of promotion and when to move on. (JOW)

Moving standard deviation and moving sum of outliers as quality tools for monitoring analytical precision.

Science.gov (United States)

Liu, Jiakai; Tan, Chin Hon; Badrick, Tony; Loh, Tze Ping

2018-02-01

An increase in analytical imprecision (expressed as CV a ) can introduce additional variability (i.e. noise) to the patient results, which poses a challenge to the optimal management of patients. Relatively little work has been done to address the need for continuous monitoring of analytical imprecision. Through numerical simulations, we describe the use of moving standard deviation (movSD) and a recently described moving sum of outlier (movSO) patient results as means for detecting increased analytical imprecision, and compare their performances against internal quality control (QC) and the average of normal (AoN) approaches. The power of detecting an increase in CV a is suboptimal under routine internal QC procedures. The AoN technique almost always had the highest average number of patient results affected before error detection (ANPed), indicating that it had generally the worst capability for detecting an increased CV a . On the other hand, the movSD and movSO approaches were able to detect an increased CV a at significantly lower ANPed, particularly for measurands that displayed a relatively small ratio of biological variation to CV a. CONCLUSION: The movSD and movSO approaches are effective in detecting an increase in CV a for high-risk measurands with small biological variation. Their performance is relatively poor when the biological variation is large. However, the clinical risks of an increase in analytical imprecision is attenuated for these measurands as an increased analytical imprecision will only add marginally to the total variation and less likely to impact on the clinical care. Copyright © 2017 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Human Capital Theory and Internal Migration: Do Average Outcomes Distort Our View of Migrant Motives?

Science.gov (United States)

Korpi, Martin; Clark, William A W

2017-05-01

By modelling the distribution of percentage income gains for movers in Sweden, using multinomial logistic regression, this paper shows that those receiving large pecuniary returns from migration are primarily those moving to the larger metropolitan areas and those with higher education, and that there is much more variability in income gains than what is often assumed in models of average gains to migration. This suggests that human capital models of internal migration often overemphasize the job and income motive for moving, and fail to explore where and when human capital motivated migration occurs.

Anticipatory Cyber Security Research: An Ultimate Technique for the First-Move Advantage

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Bharat S.Rawal

2016-02-01

Full Text Available Across all industry segments, 96 percent of systems could be breached on average. In the game of cyber security, every moment a new player (attacker is entering the game with new skill sets. An attacker only needs to be effective once while defenders of cyberspace have to be successful all of the time. There will be a first-mover advantage in such a chasing game, which means that the first move often wins. In this paper, in order to face the security challenges brought in by attacker’s first move advantage, we analyzed the past ten years of cyber-attacks, studied the immediate attack’s pattern and offer the tools to predict the next move of the cyber attacker.

Application of semi parametric modelling to times series forecasting: case of the electricity consumption

International Nuclear Information System (INIS)

Lefieux, V.

2007-10-01

Reseau de Transport d'Electricite (RTE), in charge of operating the French electric transportation grid, needs an accurate forecast of the power consumption in order to operate it correctly. The forecasts used everyday result from a model combining a nonlinear parametric regression and a SARIMA model. In order to obtain an adaptive forecasting model, nonparametric forecasting methods have already been tested without real success. In particular, it is known that a nonparametric predictor behaves badly with a great number of explanatory variables, what is commonly called the curse of dimensionality. Recently, semi parametric methods which improve the pure nonparametric approach have been proposed to estimate a regression function. Based on the concept of 'dimension reduction', one those methods (called MAVE : Moving Average -conditional- Variance Estimate) can apply to time series. We study empirically its effectiveness to predict the future values of an autoregressive time series. We then adapt this method, from a practical point of view, to forecast power consumption. We propose a partially linear semi parametric model, based on the MAVE method, which allows to take into account simultaneously the autoregressive aspect of the problem and the exogenous variables. The proposed estimation procedure is practically efficient. (author)

Projecting the Water and Electric Consumption of Polytechnic University of the Philippines

Science.gov (United States)

Urrutia, Jackie D.; Mercado, Joseph; Bautista, Lincoln A.; Baccay, Edcon B.

2017-03-01

This study investigates water and electric consumption in Polytechnic University of the Philippines - Sta. Mesa using a time series analysis. The researchers analyzed the water and electric usage separately. Electric consumption was examined in terms of pesos and kilowatt-hour, while water consumption was analyzed in pesos and cubic meter. The data are gathered from the university limited only from January 2009 to July 2015 in a monthly based record. The aim is to forecast the water and electric usage of the university for the years 2016 and 2017. There are two main statistical treatments that the researchers conducted to be able to formulate mathematical models that can estimate the water and electric consumption of the said school. Using Seasonal Autoregressive Integrated Moving Average (SARIMA), electric usage was forecasted in peso and kilowatt-hour, and water usage in peso and cubic meter. Moreover, the predicted values of the consumptions are compared to the actual values using Paired T-test to examine whether there is a significant difference. Forecasting accurately the water and electric consumption would be helpful to manage the budget allotted for the water and electric consumption of PUP - Sta. Mesa for the next two years.

Moving related to separation : who moves and to what distance

NARCIS (Netherlands)

Mulder, Clara H.; Malmberg, Gunnar

We address the issue of moving from the joint home on the occasion of separation. Our research question is: To what extent can the occurrence of moves related to separation, and the distance moved, be explained by ties to the location, resources, and other factors influencing the likelihood of

Drought Forecasting with Vegetation Temperature Condition Index Using ARIMA Models in the Guanzhong Plain

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Miao Tian

2016-08-01

Full Text Available This paper works on the agricultural drought forecasting in the Guanzhong Plain of China using Autoregressive Integrated Moving Average (ARIMA models based on the time series of drought monitoring results of Vegetation Temperature Condition Index (VTCI. About 90 VTCI images derived from Advanced Very High Resolution Radiometer (AVHRR data were selected to develop the ARIMA models from the erecting stage to the maturity stage of winter wheat (early March to late May in each year at a ten-day interval of the years from 2000 to 2009. We take the study area overlying on the administration map around the study area, and divide the study area into 17 parts where at least one weather station is located in each part. The pixels where the 17 weather stations are located are firstly chosen and studied for their fitting models, and then the best models for all pixels of the whole area are determined. According to the procedures for the models’ development, the selected best models for the 17 pixels are identified and the forecast is done with three steps. The forecasting results of the ARIMA models were compared with the monitoring ones. The results show that with reference to the categorized VTCI drought monitoring results, the categorized forecasting results of the ARIMA models are in good agreement with the monitoring ones. The categorized drought forecasting results of the ARIMA models are more severity in the northeast of the Plain in April 2009, which are in good agreements with the monitoring ones. The absolute errors of the AR(1 models are lower than the SARIMA models, both in the frequency distributions and in the statistic results. However, the ability of SARIMA models to detect the changes of the drought situation is better than the AR(1 models. These results indicate that the ARIMA models can better forecast the category and extent of droughts and can be applied to forecast droughts in the Plain.

An empirical investigation on the forecasting ability of mallows model averaging in a macro economic environment

Science.gov (United States)

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.

Move up,Move out

Institute of Scientific and Technical Information of China (English)

Guo Yan

2007-01-01

@@ China has already become the world's largest manufacturer of cement,copper and steel.Chinese producers have moved onto the world stage and dominated the global consumer market from textiles to electronics with amazing speed and efficiency.

Role of moving planes and moving spheres following Dupin cyclides

KAUST Repository

Jia, Xiaohong

2014-03-01

We provide explicit representations of three moving planes that form a μ-basis for a standard Dupin cyclide. We also show how to compute μ-bases for Dupin cyclides in general position and orientation from their implicit equations. In addition, we describe the role of moving planes and moving spheres in bridging between the implicit and rational parametric representations of these cyclides. © 2014 Elsevier B.V.

Role of moving planes and moving spheres following Dupin cyclides

KAUST Repository

Jia, Xiaohong

2014-01-01

We provide explicit representations of three moving planes that form a μ-basis for a standard Dupin cyclide. We also show how to compute μ-bases for Dupin cyclides in general position and orientation from their implicit equations. In addition, we describe the role of moving planes and moving spheres in bridging between the implicit and rational parametric representations of these cyclides. © 2014 Elsevier B.V.

Automatic Moving Object Segmentation for Freely Moving Cameras

Directory of Open Access Journals (Sweden)

Yanli Wan

2014-01-01

Full Text Available This paper proposes a new moving object segmentation algorithm for freely moving cameras which is very common for the outdoor surveillance system, the car build-in surveillance system, and the robot navigation system. A two-layer based affine transformation model optimization method is proposed for camera compensation purpose, where the outer layer iteration is used to filter the non-background feature points, and the inner layer iteration is used to estimate a refined affine model based on the RANSAC method. Then the feature points are classified into foreground and background according to the detected motion information. A geodesic based graph cut algorithm is then employed to extract the moving foreground based on the classified features. Unlike the existing global optimization or the long term feature point tracking based method, our algorithm only performs on two successive frames to segment the moving foreground, which makes it suitable for the online video processing applications. The experiment results demonstrate the effectiveness of our algorithm in both of the high accuracy and the fast speed.

Moving event and moving participant in aspectual conceptions

Directory of Open Access Journals (Sweden)

Izutsu Katsunobu

2016-06-01

Full Text Available This study advances an analysis of the event conception of aspectual forms in four East Asian languages: Ainu, Japanese, Korean, and Ryukyuan. As earlier studies point out, event conceptions can be divided into two major types: the moving-event type and the moving-participant type, respectively. All aspectual forms in Ainu and Korean, and most forms in Japanese and Ryukyuan are based on that type of event conception. Moving-participant oriented Ainu and movingevent oriented Japanese occupy two extremes, between which Korean and Ryukyuan stand. Notwithstanding the geographical relationships among the four languages, Ryukyuan is closer to Ainu than to Korean, whereas Korean is closer to Ainu than to Japanese.

Hybrid Heat Capacity - Moving Slab Laser Concept

International Nuclear Information System (INIS)

Stappaerts, E A

2002-01-01

A hybrid configuration of a heat capacity laser (HCL) and a moving slab laser (MSL) has been studied. Multiple volumes of solid-state laser material are sequentially diode-pumped and their energy extracted. When a volume reaches a maximum temperature after a ''sub-magazine depth'', it is moved out of the pumping region into a cooling region, and a new volume is introduced. The total magazine depth equals the submagazine depth times the number of volumes. The design parameters are chosen to provide high duty factor operation, resulting in effective use of the diode arrays. The concept significantly reduces diode array cost over conventional heat capacity lasers, and it is considered enabling for many potential applications. A conceptual design study of the hybrid configuration has been carried out. Three concepts were evaluated using CAD tools. The concepts are described and their relative merits discussed. Because of reduced disk size and diode cost, the hybrid concept may allow scaling to average powers on the order of 0.5 MW/module

One-dimensional quantum walk with a moving boundary

International Nuclear Information System (INIS)

Kwek, Leong Chuan; Setiawan

2011-01-01

Quantum walks are interesting models with potential applications to quantum algorithms and physical processes such as photosynthesis. In this paper, we study two models of one-dimensional quantum walks, namely, quantum walks with a moving absorbing wall and quantum walks with one stationary and one moving absorbing wall. For the former, we calculate numerically the survival probability, the rate of change of average position, and the rate of change of standard deviation of the particle's position in the long time limit for different wall velocities. Moreover, we also study the asymptotic behavior and the dependence of the survival probability on the initial particle's state. While for the latter, we compute the absorption probability of the right stationary wall for different velocities and initial positions of the left wall boundary. The results for these two models are compared with those obtained for the classical model. The difference between the results obtained for the quantum and classical models can be attributed to the difference in the probability distributions.

Pronosticando la inflación mensual en Colombia un paso hacia delante: una aproximación "de abajo hacia arriba" || Forecasting the Colombian Monthly Inflation One Step Ahead: A "Bottom to Top" Approach

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Alonso, Julio César

2017-06-01

Full Text Available La estructura jerárquica del Índice de Precios al Consumidor (IPC de Colombia permite calcular la inflación como una combinación lineal de sus subcomponentes. Nuestra aproximación implica emplear modelos SARIMA para pronosticar cada componente del IPC y crear un pronóstico de la inflación como una combinación lineal de los pronósticos individuales; es decir, una aproximación "de abajo hacia arriba". Se evalúa el desempeño fuera de muestra de los pronósticos para el siguiente mes de 12 métodos que emplean una aproximación "de abajo hacia arriba". Estos métodos son comparados con un pronóstico agregado de la inflación empleando un modelo SARIMA para el IPC total. Nuestros resultados muestran que emplear un método "de abajo hacia arriba" para pronosticar la inflación del siguiente mes tiene un mejor comportamiento que emplear un modelo SARIMA agregado. || The hierarchical structure of the Colombian Consumer Price Index (CPI makes possible to calculate inflation as a linear combination of its subcomponents. We use SARIMA models to forecast each component of CPI and construct an forecast of inflation using a lineal combination of the forecasts of these components, i.e. a "bottom to top" approach. In this paper, we asses the out-of-sample performance of the one-step ahead forecast of 12 "bottom to top" methodologies. These methods are compared with an aggregate forecast using a SARIMA model. Our results show that a "bottom to top" method to forecast inflation outperforms an aggregate approach for the case of monthly inflation in Colombia.

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

Science.gov (United States)

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.

Climatic Variables and Malaria Morbidity in Mutale Local Municipality, South Africa: A 19-Year Data Analysis.

Science.gov (United States)

Adeola, Abiodun M; Botai, Joel O; Rautenbach, Hannes; Adisa, Omolola M; Ncongwane, Katlego P; Botai, Christina M; Adebayo-Ojo, Temitope C

2017-11-08

The north-eastern parts of South Africa, comprising the Limpopo Province, have recorded a sudden rise in the rate of malaria morbidity and mortality in the 2017 malaria season. The epidemiological profiles of malaria, as well as other vector-borne diseases, are strongly associated with climate and environmental conditions. A retrospective understanding of the relationship between climate and the occurrence of malaria may provide insight into the dynamics of the disease's transmission and its persistence in the north-eastern region. In this paper, the association between climatic variables and the occurrence of malaria was studied in the Mutale local municipality in South Africa over a period of 19-year. Time series analysis was conducted on monthly climatic variables and monthly malaria cases in the Mutale municipality for the period of 1998-2017. Spearman correlation analysis was performed and the Seasonal Autoregressive Integrated Moving Average (SARIMA) model was developed. Microsoft Excel was used for data cleaning, and statistical software R was used to analyse the data and develop the model. Results show that both climatic variables' and malaria cases' time series exhibited seasonal patterns, showing a number of peaks and fluctuations. Spearman correlation analysis indicated that monthly total rainfall, mean minimum temperature, mean maximum temperature, mean average temperature, and mean relative humidity were significantly and positively correlated with monthly malaria cases in the study area. Regression analysis showed that monthly total rainfall and monthly mean minimum temperature ( R ² = 0.65), at a two-month lagged effect, are the most significant climatic predictors of malaria transmission in Mutale local municipality. A SARIMA (2,1,2) (1,1,1) model fitted with only malaria cases has a prediction performance of about 51%, and the SARIMAX (2,1,2) (1,1,1) model with climatic variables as exogenous factors has a prediction performance of about 72% in

Research on measurement method of optical camouflage effect of moving object

Science.gov (United States)

Wang, Juntang; Xu, Weidong; Qu, Yang; Cui, Guangzhen

2016-10-01

Camouflage effectiveness measurement as an important part of the camouflage technology, which testing and measuring the camouflage effect of the target and the performance of the camouflage equipment according to the tactical and technical requirements. The camouflage effectiveness measurement of current optical band is mainly aimed at the static target which could not objectively reflect the dynamic camouflage effect of the moving target. This paper synthetical used technology of dynamic object detection and camouflage effect detection, the digital camouflage of the moving object as the research object, the adaptive background update algorithm of Surendra was improved, a method of optical camouflage effect detection using Lab-color space in the detection of moving-object was presented. The binary image of moving object is extracted by this measurement technology, in the sequence diagram, the characteristic parameters such as the degree of dispersion, eccentricity, complexity and moment invariants are constructed to construct the feature vector space. The Euclidean distance of moving target which through digital camouflage was calculated, the results show that the average Euclidean distance of 375 frames was 189.45, which indicated that the degree of dispersion, eccentricity, complexity and moment invariants of the digital camouflage graphics has a great difference with the moving target which not spray digital camouflage. The measurement results showed that the camouflage effect was good. Meanwhile with the performance evaluation module, the correlation coefficient of the dynamic target image range 0.1275 from 0.0035, and presented some ups and down. Under the dynamic condition, the adaptability of target and background was reflected. In view of the existing infrared camouflage technology, the next step, we want to carry out the camouflage effect measurement technology of the moving target based on infrared band.

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

Science.gov (United States)

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.

SAR Ground Moving Target Indication Based on Relative Residue of DPCA Processing

Directory of Open Access Journals (Sweden)

Jia Xu

2016-10-01

Full Text Available For modern synthetic aperture radar (SAR, it has much more urgent demands on ground moving target indication (GMTI, which includes not only the point moving targets like cars, truck or tanks but also the distributed moving targets like river or ocean surfaces. Among the existing GMTI methods, displaced phase center antenna (DPCA can effectively cancel the strong ground clutter and has been widely used. However, its detection performance is closely related to the target’s signal-to-clutter ratio (SCR as well as radial velocity, and it cannot effectively detect the weak large-sized river surfaces in strong ground clutter due to their low SCR caused by specular scattering. This paper proposes a novel method called relative residue of DPCA (RR-DPCA, which jointly utilizes the DPCA cancellation outputs and the multi-look images to improve the detection performance of weak river surfaces. Furthermore, based on the statistics analysis of the RR-DPCA outputs on the homogenous background, the cell average (CA method can be well applied for subsequent constant false alarm rate (CFAR detection. The proposed RR-DPCA method can well detect the point moving targets and distributed moving targets simultaneously. Finally, the results of both simulated and real data are provided to demonstrate the effectiveness of the proposed SAR/GMTI method.

Embodied affectivity: On moving and being moved

Directory of Open Access Journals (Sweden)

Thomas eFuchs

2014-06-01

Full Text Available There is a growing body of research indicating that bodily sensation and behaviour strongly influences one’s emotional reaction towards certain situations or objects. On this background, a framework model of embodied affectivity is suggested: we regard emotions as resulting from the circular interaction between affective qualities or affordances in the environment and the subject’s bodily resonance, be it in the form of sensations, postures, expressive movements or movement tendencies. Motion and emotion are thus intrinsically connected: one is moved by movement (perception; impression; affection and moved to move (action; expression; e-motion. Through its resonance, the body functions as a medium of emotional perception: it colours or charges self-experience and the environment with affective valences while it remains itself in the background of one’s own awareness. This model is then applied to emotional social understanding or interaffectivity which is regarded as an intertwinement of two cycles of embodied affectivity, thus continuously modifying each partner’s affective affordances and bodily resonance. We conclude with considerations of how embodied affectivity is altered in psychopathology and can be addressed in psychotherapy of the embodied self.

Time series trends of the safety effects of pavement resurfacing.

Science.gov (United States)

Park, Juneyoung; Abdel-Aty, Mohamed; Wang, Jung-Han

2017-04-01

This study evaluated the safety performance of pavement resurfacing projects on urban arterials in Florida using the observational before and after approaches. The safety effects of pavement resurfacing were quantified in the crash modification factors (CMFs) and estimated based on different ranges of heavy vehicle traffic volume and time changes for different severity levels. In order to evaluate the variation of CMFs over time, crash modification functions (CMFunctions) were developed using nonlinear regression and time series models. The results showed that pavement resurfacing projects decrease crash frequency and are found to be more safety effective to reduce severe crashes in general. Moreover, the results of the general relationship between the safety effects and time changes indicated that the CMFs increase over time after the resurfacing treatment. It was also found that pavement resurfacing projects for the urban roadways with higher heavy vehicle volume rate are more safety effective than the roadways with lower heavy vehicle volume rate. Based on the exploration and comparison of the developed CMFucntions, the seasonal autoregressive integrated moving average (SARIMA) and exponential functional form of the nonlinear regression models can be utilized to identify the trend of CMFs over time. Copyright © 2017 Elsevier Ltd. All rights reserved.

An application of seasonal ARIMA models on group commodities to forecast Philippine merchandise exports performance

Science.gov (United States)

Natividad, Gina May R.; Cawiding, Olive R.; Addawe, Rizavel C.

2017-11-01

The increase in the merchandise exports of the country offers information about the Philippines' trading role within the global economy. Merchandise exports statistics are used to monitor the country's overall production that is consumed overseas. This paper investigates the comparison between two models obtained by a) clustering the commodity groups into two based on its proportional contribution to the total exports, and b) treating only the total exports. Different seasonal autoregressive integrated moving average (SARIMA) models were then developed for the clustered commodities and for the total exports based on the monthly merchandise exports of the Philippines from 2011 to 2016. The data set used in this study was retrieved from the Philippine Statistics Authority (PSA) which is the central statistical authority in the country responsible for primary data collection. A test for significance of the difference between means at 0.05 level of significance was then performed on the forecasts produced. The result indicates that there is a significant difference between the mean of the forecasts of the two models. Moreover, upon a comparison of the root mean square error (RMSE) and mean absolute error (MAE) of the models, it was found that the models used for the clustered groups outperform the model for the total exports.

Application of semi parametric modelling to times series forecasting: case of the electricity consumption; Modeles semi-parametriques appliques a la prevision des series temporelles. Cas de la consommation d'electricite

Energy Technology Data Exchange (ETDEWEB)

Lefieux, V

2007-10-15

Reseau de Transport d'Electricite (RTE), in charge of operating the French electric transportation grid, needs an accurate forecast of the power consumption in order to operate it correctly. The forecasts used everyday result from a model combining a nonlinear parametric regression and a SARIMA model. In order to obtain an adaptive forecasting model, nonparametric forecasting methods have already been tested without real success. In particular, it is known that a nonparametric predictor behaves badly with a great number of explanatory variables, what is commonly called the curse of dimensionality. Recently, semi parametric methods which improve the pure nonparametric approach have been proposed to estimate a regression function. Based on the concept of 'dimension reduction', one those methods (called MAVE : Moving Average -conditional- Variance Estimate) can apply to time series. We study empirically its effectiveness to predict the future values of an autoregressive time series. We then adapt this method, from a practical point of view, to forecast power consumption. We propose a partially linear semi parametric model, based on the MAVE method, which allows to take into account simultaneously the autoregressive aspect of the problem and the exogenous variables. The proposed estimation procedure is practically efficient. (author)

Method and apparatus for a combination moving bed thermal treatment reactor and moving bed filter

Energy Technology Data Exchange (ETDEWEB)

Badger, Phillip C.; Dunn, Jr., Kenneth J.

2015-09-01

A moving bed gasification/thermal treatment reactor includes a geometry in which moving bed reactor particles serve as both a moving bed filter and a heat carrier to provide thermal energy for thermal treatment reactions, such that the moving bed filter and the heat carrier are one and the same to remove solid particulates or droplets generated by thermal treatment processes or injected into the moving bed filter from other sources.

Analysis of the Dose Distribution of Moving Organ using a Moving Phantom System

International Nuclear Information System (INIS)

Kim, Yon Lae; Park, Byung Moon; Bae, Yong Ki; Kang, Min Young; Bang, Dong Wan; Lee, Gui Won

2006-01-01

Few researches have been performed on the dose distribution of the moving organ for radiotherapy so far. In order to simulate the organ motion caused by respiratory function, multipurpose phantom and moving device was used and dosimetric measurements for dose distribution of the moving organs were conducted in this study. The purpose of our study was to evaluate how dose distributions are changed due to respiratory motion. A multipurpose phantom and a moving device were developed for the measurement of the dose distribution of the moving organ due to respiratory function. Acryl chosen design of the phantom was considered the most obvious choice for phantom material. For construction of the phantom, we used acryl and cork with density of 1.14 g/cm 3 , 0.32 g/cm 3 respectively. Acryl and cork slab in the phantom were used to simulate the normal organ and lung respectively. The moving phantom system was composed of moving device, moving control system, and acryl and cork phantom. Gafchromic film and EDR2 film were used to measure dose distributions. The moving device system may be driven by two directional step motors and able to perform 2 dimensional movements (x, z axis), but only 1 dimensional movement(z axis) was used for this study. Larger penumbra was shown in the cork phantom than in the acryl phantom. The dose profile and isodose curve of Gafchromic EBT film were not uniform since the film has small optical density responding to the dose. As the organ motion was increased, the blurrings in penumbra, flatness, and symmetry were increased. Most of measurements of dose distributions, Gafchromic EBT film has poor flatness and symmetry than EDR2 film, but both penumbra distributions were more or less comparable. The Gafchromic EBT film is more useful as it does not need development and more radiation dose could be exposed than EDR2 film without losing film characteristics. But as response of the optical density of Gafchromic EBT film to dose is low, beam profiles

Detection of moving objects from a moving platform in urban scenes

NARCIS (Netherlands)

Haar, F.B. ter; Hollander, R.J.M. den; Dijk, J.

2010-01-01

Moving object detection in urban scenes is important for the guidance of autonomous vehicles, robot navigation, and monitoring. In this paper moving objects are automatically detected using three sequential frames and tracked over a longer period. To this extend we modify the plane+parallax,

Low-resolution Airborne Radar Air/ground Moving Target Classification and Recognition

Directory of Open Access Journals (Sweden)

Wang Fu-you

2014-10-01

Full Text Available Radar Target Recognition (RTR is one of the most important needs of modern and future airborne surveillance radars, and it is still one of the key technologies of radar. The majority of present algorithms are based on wide-band radar signal, which not only needs high performance radar system and high target Signal-to-Noise Ratio (SNR, but also is sensitive to angle between radar and target. Low-Resolution Airborne Surveillance Radar (LRASR in downward-looking mode, slow flying aircraft and ground moving truck have similar Doppler velocity and Radar Cross Section (RCS, leading to the problem that LRASR air/ground moving targets can not be distinguished, which also disturbs detection, tracking, and classification of low altitude slow flying aircraft to solve these issues, an algorithm based on narrowband fractal feature and phase modulation feature is presented for LRASR air/ground moving targets classification. Real measured data is applied to verify the algorithm, the classification results validate the proposed method, helicopters and truck can be well classified, the average discrimination rate is more than 89% when SNR ≥ 15 dB.

Modeling an Application's Theoretical Minimum and Average Transactional Response Times

Energy Technology Data Exchange (ETDEWEB)

Paiz, Mary Rose [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-04-01

The theoretical minimum transactional response time of an application serves as a ba- sis for the expected response time. The lower threshold for the minimum response time represents the minimum amount of time that the application should take to complete a transaction. Knowing the lower threshold is beneficial in detecting anomalies that are re- sults of unsuccessful transactions. On the converse, when an application's response time falls above an upper threshold, there is likely an anomaly in the application that is causing unusual performance issues in the transaction. This report explains how the non-stationary Generalized Extreme Value distribution is used to estimate the lower threshold of an ap- plication's daily minimum transactional response time. It also explains how the seasonal Autoregressive Integrated Moving Average time series model is used to estimate the upper threshold for an application's average transactional response time.

MOVES regional level sensitivity analysis

Science.gov (United States)

2012-01-01

The MOVES Regional Level Sensitivity Analysis was conducted to increase understanding of the operations of the MOVES Model in regional emissions analysis and to highlight the following: : the relative sensitivity of selected MOVES Model input paramet...

Moving Field Guides

Science.gov (United States)

Cassie Meador; Mark Twery; Meagan. Leatherbury

2011-01-01

The Moving Field Guides (MFG) project is a creative take on site interpretation. Moving Field Guides provide an example of how scientific and artistic endeavors work in parallel. Both begin with keen observations that produce information that must be analyzed, understood, and interpreted. That interpretation then needs to be communicated to others to complete the...

Effect of 3 Key Factors on Average End to End Delay and Jitter in MANET

Directory of Open Access Journals (Sweden)

Saqib Hakak

2015-01-01

Full Text Available A mobile ad-hoc network (MANET is a self-configuring infrastructure-less network of mobile devices connected by wireless links where each node or mobile device is independent to move in any desired direction and thus the links keep moving from one node to another. In such a network, the mobile nodes are equipped with CSMA/CA (carrier sense multiple access with collision avoidance transceivers and communicate with each other via radio. In MANETs, routing is considered one of the most difficult and challenging tasks. Because of this, most studies on MANETs have focused on comparing protocols under varying network conditions. But to the best of our knowledge no one has studied the effect of other factors on network performance indicators like throughput, jitter and so on, revealing how much influence a particular factor or group of factors has on each network performance indicator. Thus, in this study the effects of three key factors, i.e. routing protocol, packet size and DSSS rate, were evaluated on key network performance metrics, i.e. average delay and average jitter, as these parameters are crucial for network performance and directly affect the buffering requirements for all video devices and downstream networks.

Estimation of pure moving average vector models | Usoro ...

African Journals Online (AJOL)

International Journal of Natural and Applied Sciences. Journal Home · ABOUT THIS JOURNAL · Advanced Search · Current Issue · Archives · Journal Home > Vol 3, No 3 (2007) >. Log in or Register to get access to full text downloads. Username, Password, Remember me, or Register. DOWNLOAD FULL TEXT ...

on the performance of Autoregressive Moving Average Polynomial

African Journals Online (AJOL)

Timothy Ademakinwa

estimated using least squares and Newton Raphson iterative methods. To determine the order of the ... r is the degree of polynomial while j is the number of lag of the ..... use a real time series dataset, monthly rainfall and temperature series ...

Cellular automaton model in the fundamental diagram approach reproducing the synchronized outflow of wide moving jams

International Nuclear Information System (INIS)

Tian, Jun-fang; Yuan, Zhen-zhou; Jia, Bin; Fan, Hong-qiang; Wang, Tao

2012-01-01

Velocity effect and critical velocity are incorporated into the average space gap cellular automaton model [J.F. Tian, et al., Phys. A 391 (2012) 3129], which was able to reproduce many spatiotemporal dynamics reported by the three-phase theory except the synchronized outflow of wide moving jams. The physics of traffic breakdown has been explained. Various congested patterns induced by the on-ramp are reproduced. It is shown that the occurrence of synchronized outflow, free outflow of wide moving jams is closely related with drivers time delay in acceleration at the downstream jam front and the critical velocity, respectively. -- Highlights: ► Velocity effect is added into average space gap cellular automaton model. ► The physics of traffic breakdown has been explained. ► The probabilistic nature of traffic breakdown is simulated. ► Various congested patterns induced by the on-ramp are reproduced. ► The occurrence of synchronized outflow of jams depends on drivers time delay.

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

Science.gov (United States)

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.

State Averages

Data.gov (United States)

U.S. Department of Health & Human Services — A list of a variety of averages for each state or territory as well as the national average, including each quality measure, staffing, fine amount and number of...

An Indoor Continuous Positioning Algorithm on the Move by Fusing Sensors and Wi-Fi on Smartphones.

Science.gov (United States)

Li, Huaiyu; Chen, Xiuwan; Jing, Guifei; Wang, Yuan; Cao, Yanfeng; Li, Fei; Zhang, Xinlong; Xiao, Han

2015-12-11

Wi-Fi indoor positioning algorithms experience large positioning error and low stability when continuously positioning terminals that are on the move. This paper proposes a novel indoor continuous positioning algorithm that is on the move, fusing sensors and Wi-Fi on smartphones. The main innovative points include an improved Wi-Fi positioning algorithm and a novel positioning fusion algorithm named the Trust Chain Positioning Fusion (TCPF) algorithm. The improved Wi-Fi positioning algorithm was designed based on the properties of Wi-Fi signals on the move, which are found in a novel "quasi-dynamic" Wi-Fi signal experiment. The TCPF algorithm is proposed to realize the "process-level" fusion of Wi-Fi and Pedestrians Dead Reckoning (PDR) positioning, including three parts: trusted point determination, trust state and positioning fusion algorithm. An experiment is carried out for verification in a typical indoor environment, and the average positioning error on the move is 1.36 m, a decrease of 28.8% compared to an existing algorithm. The results show that the proposed algorithm can effectively reduce the influence caused by the unstable Wi-Fi signals, and improve the accuracy and stability of indoor continuous positioning on the move.

Moving Magnetic Features Around a Pore

Energy Technology Data Exchange (ETDEWEB)

Kaithakkal, A. J.; Riethmüller, T. L.; Solanki, S. K.; Lagg, A.; Barthol, P.; Gandorfer, A.; Gizon, L.; Hirzberger, J.; VanNoort, M. [Max Planck Institute for Solar System Research, Justus-von-Liebig-Weg 3, Göttingen D-37077 (Germany); Rodríguez, J. Blanco [Grupo de Astronomía y Ciencias del Espacio, Universidad de Valencia, E-46980 Paterna, Valencia (Spain); Iniesta, J. C. Del Toro; Suárez, D. Orozco [Instituto de Astrofísica de Andalucía (CSIC), Apartado de Correos 3004, E-18080 Granada (Spain); Schmidt, W. [Kiepenheuer-Institut für Sonnenphysik, Schöneckstr. 6, D-79104 Freiburg (Germany); Pillet, V. Martínez [National Solar Observatory, 3665 Discovery Drive, Boulder, CO 80303 (United States); Knölker, M., E-mail: anjali@mps.mpg.de [High Altitude Observatory, National Center for Atmospheric Research, P.O. Box 3000, Boulder, CO 80307-3000 (United States)

2017-03-01

Spectropolarimetric observations from Sunrise/IMaX, obtained in 2013 June, are used for a statistical analysis to determine the physical properties of moving magnetic features (MMFs) observed near a pore. MMFs of the same and opposite polarity, with respect to the pore, are found to stream from its border at an average speed of 1.3 km s{sup −1} and 1.2 km s{sup −1}, respectively, with mainly same-polarity MMFs found further away from the pore. MMFs of both polarities are found to harbor rather weak, inclined magnetic fields. Opposite-polarity MMFs are blueshifted, whereas same-polarity MMFs do not show any preference for up- or downflows. Most of the MMFs are found to be of sub-arcsecond size and carry a mean flux of ∼1.2 × 10{sup 17} Mx.

Moving toroidal limiter

International Nuclear Information System (INIS)

Ikuta, Kazunari; Miyahara, Akira.

1983-06-01

The concept of the limiter-divertor proposed by Mirnov is extended to a toroidal limiter-divertor (which we call moving toroidal limiter) using the stream of ferromagnetic balls coated with a low Z materials such as plastics, graphite and ceramics. An important advantage of the use of the ferromagnetic materials would be possible soft landing of the balls on a catcher, provided that the temperature of the balls is below Curie point. Moreover, moving toroidal limiter would work as a protector of the first wall not only against the vertical movement of plasma ring but also against the violent inward motion driven by major disruption because the orbit of the ball in the case of moving toroidal limiter distributes over the small major radius side of the toroidal plasma. (author)

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

Science.gov (United States)

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.

Application of a Combined Model with Autoregressive Integrated Moving Average (ARIMA and Generalized Regression Neural Network (GRNN in Forecasting Hepatitis Incidence in Heng County, China.

Directory of Open Access Journals (Sweden)

Wudi Wei

Full Text Available Hepatitis is a serious public health problem with increasing cases and property damage in Heng County. It is necessary to develop a model to predict the hepatitis epidemic that could be useful for preventing this disease.The autoregressive integrated moving average (ARIMA model and the generalized regression neural network (GRNN model were used to fit the incidence data from the Heng County CDC (Center for Disease Control and Prevention from January 2005 to December 2012. Then, the ARIMA-GRNN hybrid model was developed. The incidence data from January 2013 to December 2013 were used to validate the models. Several parameters, including mean absolute error (MAE, root mean square error (RMSE, mean absolute percentage error (MAPE and mean square error (MSE, were used to compare the performance among the three models.The morbidity of hepatitis from Jan 2005 to Dec 2012 has seasonal variation and slightly rising trend. The ARIMA(0,1,2(1,1,112 model was the most appropriate one with the residual test showing a white noise sequence. The smoothing factor of the basic GRNN model and the combined model was 1.8 and 0.07, respectively. The four parameters of the hybrid model were lower than those of the two single models in the validation. The parameters values of the GRNN model were the lowest in the fitting of the three models.The hybrid ARIMA-GRNN model showed better hepatitis incidence forecasting in Heng County than the single ARIMA model and the basic GRNN model. It is a potential decision-supportive tool for controlling hepatitis in Heng County.

Moving Matters: The Causal Effect of Moving Schools on Student Performance. Working Paper #01-15

Science.gov (United States)

Schwartz, Amy Ellen; Stiefel, Leanna; Cordes, Sarah A.

2015-01-01

The majority of existing research on mobility indicates that students do worse in the year of a school move. This research, however, has been unsuccessful in isolating the causal effects of mobility and often fails to distinguish the heterogeneous impacts of moves, conflating structural moves (mandated by a school's terminal grade) and…

Percentiles of the run-length distribution of the Exponentially Weighted Moving Average (EWMA) median chart

Science.gov (United States)

Tan, K. L.; Chong, Z. L.; Khoo, M. B. C.; Teoh, W. L.; Teh, S. Y.

2017-09-01

Quality control is crucial in a wide variety of fields, as it can help to satisfy customers’ needs and requirements by enhancing and improving the products and services to a superior quality level. The EWMA median chart was proposed as a useful alternative to the EWMA \\bar{X} chart because the median-type chart is robust against contamination, outliers or small deviation from the normality assumption compared to the traditional \\bar{X}-type chart. To provide a complete understanding of the run-length distribution, the percentiles of the run-length distribution should be investigated rather than depending solely on the average run length (ARL) performance measure. This is because interpretation depending on the ARL alone can be misleading, as the process mean shifts change according to the skewness and shape of the run-length distribution, varying from almost symmetric when the magnitude of the mean shift is large, to highly right-skewed when the process is in-control (IC) or slightly out-of-control (OOC). Before computing the percentiles of the run-length distribution, optimal parameters of the EWMA median chart will be obtained by minimizing the OOC ARL, while retaining the IC ARL at a desired value.

Numerical analysis of droplet impingement using the moving particle semi-implicit method

International Nuclear Information System (INIS)

Xiong, Jinbiao; Koshizuka, Seiichi; Sakai, Mikio

2010-01-01

Droplet impingement onto a rigid wall is simulated in two and three dimensions using the moving particle semi-implicit method. In two-dimensional calculations, the convergence is achieved and the propagation of a shockwave in a droplet is captured. The average pressure on the contact area decreases gradually after the maximum value. The numerically obtained maximum average impact pressure agrees with the Heymann correlation. A large shear stress appears at the contact edge due to jetting. A parametric study shows that the droplet diameter has only a minor effect on the pressure load due to droplet impingement. When the impingement takes place from an impact angle of π/4 rad, the pressure load and shear stress show a dependence only on the normal velocity to the wall. A comparison between the three-dimensional and two-dimensional results shows that consideration of the three-dimensional effect can decrease the average impact pressure by about 12%. (author)

Application of Geostatistical Methods and Wavelets to the Analysis of Hyperspectral Imagery and the Testing of a Moving Variogram

National Research Council Canada - National Science Library

2000-01-01

This is a first report of the project. It incorporates the report on an analysis completed in the previous project on moving averages, variances and variograms for NIR from a SPOT image of part of Fort A. P. Hill...

PARALLEL MOVING MECHANICAL SYSTEMS

Directory of Open Access Journals (Sweden)

Florian Ion Tiberius Petrescu

2014-09-01

Full Text Available Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 Moving mechanical systems parallel structures are solid, fast, and accurate. Between parallel systems it is to be noticed Stewart platforms, as the oldest systems, fast, solid and precise. The work outlines a few main elements of Stewart platforms. Begin with the geometry platform, kinematic elements of it, and presented then and a few items of dynamics. Dynamic primary element on it means the determination mechanism kinetic energy of the entire Stewart platforms. It is then in a record tail cinematic mobile by a method dot matrix of rotation. If a structural mottoelement consists of two moving elements which translates relative, drive train and especially dynamic it is more convenient to represent the mottoelement as a single moving components. We have thus seven moving parts (the six motoelements or feet to which is added mobile platform 7 and one fixed.

An Indoor Continuous Positioning Algorithm on the Move by Fusing Sensors and Wi-Fi on Smartphones

Directory of Open Access Journals (Sweden)

Huaiyu Li

2015-12-01

Full Text Available Wi-Fi indoor positioning algorithms experience large positioning error and low stability when continuously positioning terminals that are on the move. This paper proposes a novel indoor continuous positioning algorithm that is on the move, fusing sensors and Wi-Fi on smartphones. The main innovative points include an improved Wi-Fi positioning algorithm and a novel positioning fusion algorithm named the Trust Chain Positioning Fusion (TCPF algorithm. The improved Wi-Fi positioning algorithm was designed based on the properties of Wi-Fi signals on the move, which are found in a novel “quasi-dynamic” Wi-Fi signal experiment. The TCPF algorithm is proposed to realize the “process-level” fusion of Wi-Fi and Pedestrians Dead Reckoning (PDR positioning, including three parts: trusted point determination, trust state and positioning fusion algorithm. An experiment is carried out for verification in a typical indoor environment, and the average positioning error on the move is 1.36 m, a decrease of 28.8% compared to an existing algorithm. The results show that the proposed algorithm can effectively reduce the influence caused by the unstable Wi-Fi signals, and improve the accuracy and stability of indoor continuous positioning on the move.

The importance of the sampling frequency in determining short-time-averaged irradiance and illuminance for rapidly changing cloud cover

International Nuclear Information System (INIS)

Delaunay, J.J.; Rommel, M.; Geisler, J.

1994-01-01

The sampling interval is an important parameter which must be chosen carefully, if measurements of the direct, global, and diffuse irradiance or illuminance are carried out to determine their averages over a given period. Using measurements from a day with rapidly moving clouds, we investigated the influence of the sampling interval on the uncertainly of the calculated 15-min averages. We conclude, for this averaging period, that the sampling interval should not exceed 60 s and 10 s for measurement of the diffuse and global components respectively, to reduce the influence of the sampling interval below 2%. For the direct component, even a 5 s sampling interval is too long to reach this influence level for days with extremely quickly changing insolation conditions. (author)

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

Science.gov (United States)

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 Moving image

DEFF Research Database (Denmark)

Hansen, Lennard Højbjerg

2014-01-01

Every day we are presented with bodily expressions in audiovisual media – by anchors, journalists and characters in films for instance. This article explores how body language in the moving image has been and can be approached in a scholarly manner.......Every day we are presented with bodily expressions in audiovisual media – by anchors, journalists and characters in films for instance. This article explores how body language in the moving image has been and can be approached in a scholarly manner....

Moving to Jobs?

OpenAIRE

Dave Maré; Jason Timmins

2003-01-01

This paper examines whether New Zealand residents move from low-growth to high-growth regions, using New Zealand census data from the past three inter-censal periods (covering 1986-2001). We focus on the relationship between employment growth and migration flows to gauge the strength of the relationship and the stability of the relationship over the business cycle. We find that people move to areas of high employment growth, but that the probability of leaving a region is less strongly relate...

Isolating and moving single atoms using silicon nanocrystals

Science.gov (United States)

Carroll, Malcolm S.

2010-09-07

A method is disclosed for isolating single atoms of an atomic species of interest by locating the atoms within silicon nanocrystals. This can be done by implanting, on the average, a single atom of the atomic species of interest into each nanocrystal, and then measuring an electrical charge distribution on the nanocrystals with scanning capacitance microscopy (SCM) or electrostatic force microscopy (EFM) to identify and select those nanocrystals having exactly one atom of the atomic species of interest therein. The nanocrystals with the single atom of the atomic species of interest therein can be sorted and moved using an atomic force microscope (AFM) tip. The method is useful for forming nanoscale electronic and optical devices including quantum computers and single-photon light sources.

Modeling malaria control intervention effect in KwaZulu-Natal, South Africa using intervention time series analysis.

Science.gov (United States)

Ebhuoma, Osadolor; Gebreslasie, Michael; Magubane, Lethumusa

The change of the malaria control intervention policy in South Africa (SA), re-introduction of dichlorodiphenyltrichloroethane (DDT), may be responsible for the low and sustained malaria transmission in KwaZulu-Natal (KZN). We evaluated the effect of the re-introduction of DDT on malaria in KZN and suggested practical ways the province can strengthen her already existing malaria control and elimination efforts, to achieve zero malaria transmission. We obtained confirmed monthly malaria cases in KZN from the malaria control program of KZN from 1998 to 2014. The seasonal autoregressive integrated moving average (SARIMA) intervention time series analysis (ITSA) was employed to model the effect of the re-introduction of DDT on confirmed monthly malaria cases. The result is an abrupt and permanent decline of monthly malaria cases (w 0 =-1174.781, p-value=0.003) following the implementation of the intervention policy. The sustained low malaria cases observed over a long period suggests that the continued usage of DDT did not result in insecticide resistance as earlier anticipated. It may be due to exophagic malaria vectors, which renders the indoor residual spraying not totally effective. Therefore, the feasibility of reducing malaria transmission to zero in KZN requires other reliable and complementary intervention resources to optimize the existing ones. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Averaging models: parameters estimation with the R-Average procedure

Directory of Open Access Journals (Sweden)

S. Noventa

2010-01-01

Full Text Available The Functional Measurement approach, proposed within the theoretical framework of Information Integration Theory (Anderson, 1981, 1982, can be a useful multi-attribute analysis tool. Compared to the majority of statistical models, the averaging model can account for interaction effects without adding complexity. The R-Average method (Vidotto & Vicentini, 2007 can be used to estimate the parameters of these models. By the use of multiple information criteria in the model selection procedure, R-Average allows for the identification of the best subset of parameters that account for the data. After a review of the general method, we present an implementation of the procedure in the framework of R-project, followed by some experiments using a Monte Carlo method.

Minimum Delay Moving Object Detection

KAUST Repository

Lao, Dong

2017-11-09

We present a general framework and method for detection of an object in a video based on apparent motion. The object moves relative to background motion at some unknown time in the video, and the goal is to detect and segment the object as soon it moves in an online manner. Due to unreliability of motion between frames, more than two frames are needed to reliably detect the object. Our method is designed to detect the object(s) with minimum delay, i.e., frames after the object moves, constraining the false alarms. Experiments on a new extensive dataset for moving object detection show that our method achieves less delay for all false alarm constraints than existing state-of-the-art.

Minimum Delay Moving Object Detection

KAUST Repository

Lao, Dong

2017-01-08

We present a general framework and method for detection of an object in a video based on apparent motion. The object moves relative to background motion at some unknown time in the video, and the goal is to detect and segment the object as soon it moves in an online manner. Due to unreliability of motion between frames, more than two frames are needed to reliably detect the object. Our method is designed to detect the object(s) with minimum delay, i.e., frames after the object moves, constraining the false alarms. Experiments on a new extensive dataset for moving object detection show that our method achieves less delay for all false alarm constraints than existing state-of-the-art.

Minimum Delay Moving Object Detection

KAUST Repository

Lao, Dong; Sundaramoorthi, Ganesh

2017-01-01

We present a general framework and method for detection of an object in a video based on apparent motion. The object moves relative to background motion at some unknown time in the video, and the goal is to detect and segment the object as soon it moves in an online manner. Due to unreliability of motion between frames, more than two frames are needed to reliably detect the object. Our method is designed to detect the object(s) with minimum delay, i.e., frames after the object moves, constraining the false alarms. Experiments on a new extensive dataset for moving object detection show that our method achieves less delay for all false alarm constraints than existing state-of-the-art.

Stochastic approaches for time series forecasting of boron: a case study of Western Turkey.

Science.gov (United States)

Durdu, Omer Faruk

2010-10-01

In the present study, a seasonal and non-seasonal prediction of boron concentrations time series data for the period of 1996-2004 from Büyük Menderes river in western Turkey are addressed by means of linear stochastic models. The methodology presented here is to develop adequate linear stochastic models known as autoregressive integrated moving average (ARIMA) and multiplicative seasonal autoregressive integrated moving average (SARIMA) to predict boron content in the Büyük Menderes catchment. Initially, the Box-Whisker plots and Kendall's tau test are used to identify the trends during the study period. The measurements locations do not show significant overall trend in boron concentrations, though marginal increasing and decreasing trends are observed for certain periods at some locations. ARIMA modeling approach involves the following three steps: model identification, parameter estimation, and diagnostic checking. In the model identification step, considering the autocorrelation function (ACF) and partial autocorrelation function (PACF) results of boron data series, different ARIMA models are identified. The model gives the minimum Akaike information criterion (AIC) is selected as the best-fit model. The parameter estimation step indicates that the estimated model parameters are significantly different from zero. The diagnostic check step is applied to the residuals of the selected ARIMA models and the results indicate that the residuals are independent, normally distributed, and homoscadastic. For the model validation purposes, the predicted results using the best ARIMA models are compared to the observed data. The predicted data show reasonably good agreement with the actual data. The comparison of the mean and variance of 3-year (2002-2004) observed data vs predicted data from the selected best models show that the boron model from ARIMA modeling approaches could be used in a safe manner since the predicted values from these models preserve the basic

Minimum Delay Moving Object Detection

KAUST Repository

Lao, Dong

2017-05-14

This thesis presents a general framework and method for detection of an object in a video based on apparent motion. The object moves, at some unknown time, differently than the “background” motion, which can be induced from camera motion. The goal of proposed method is to detect and segment the object as soon it moves in an online manner. Since motion estimation can be unreliable between frames, more than two frames are needed to reliably detect the object. Observing more frames before declaring a detection may lead to a more accurate detection and segmentation, since more motion may be observed leading to a stronger motion cue. However, this leads to greater delay. The proposed method is designed to detect the object(s) with minimum delay, i.e., frames after the object moves, constraining the false alarms, defined as declarations of detection before the object moves or incorrect or inaccurate segmentation at the detection time. Experiments on a new extensive dataset for moving object detection show that our method achieves less delay for all false alarm constraints than existing state-of-the-art.

Non-sky-averaged sensitivity curves for space-based gravitational-wave observatories

International Nuclear Information System (INIS)

Vallisneri, Michele; Galley, Chad R

2012-01-01

for the isotropic population remains the same whether or not the LISA orbits are included in the computation. However, detector motion tightens the distribution of sensitivities, so for 50% of sources the sensitivity is within 30% of its average. For the Galactic-disk population, the average and the distribution of the sensitivity for a moving detector turn out to be similar to the isotropic case. (paper)

Study of the average charge states of 188Pb and 252,254No ions at the gas-filled separator TASCA

International Nuclear Information System (INIS)

Khuyagbaatar, J.; Ackermann, D.; Andersson, L.-L.; Ballof, J.; Brüchle, W.; Düllmann, Ch.E.; Dvorak, J.; Eberhardt, K.; Even, J.; Gorshkov, A.; Graeger, R.; Heßberger, F.-P.; Hild, D.; Hoischen, R.; Jäger, E.; Kindler, B.

2012-01-01

The average charge states of 188 Pb and 252,254 No ions in dilute helium gas were measured at the gas-filled recoil separator TASCA. Hydrogen gas was also used as a filling gas for measurements of the average charge state of 254 No. Helium and hydrogen gases at pressures from 0.2 mbar to 2.0 mbar were used. A strong dependence of the average charge state on the pressure of the filling gases was observed for both, helium and hydrogen. The influence of this dependence, classically attributed to the so-called “density effect”, on the performance of TASCA was investigated. The average charge states of 254 No ions were also measured in mixtures of helium and hydrogen gases at low gas pressures around 1.0 mbar. From the experimental results simple expressions for the prediction of average charge states of heavy ions moving in rarefied helium gas, hydrogen gas, and in their mixture were derived.

Error Analysis of Fast Moving Target Geo-location in Wide Area Surveillance Ground Moving Target Indication Mode

Directory of Open Access Journals (Sweden)

Zheng Shi-chao

2013-12-01

Full Text Available As an important mode in airborne radar systems, Wide Area Surveillance Ground Moving Target Indication (WAS-GMTI mode has the ability of monitoring a large area in a short time, and then the detected moving targets can be located quickly. However, in real environment, many factors introduce considerable errors into the location of moving targets. In this paper, a fast location method based on the characteristics of the moving targets in WAS-GMTI mode is utilized. And in order to improve the location performance, those factors that introduce location errors are analyzed and moving targets are relocated. Finally, the analysis of those factors is proved to be reasonable by simulation and real data experiments.

30 CFR 56.14107 - Moving machine parts.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Moving machine parts. 56.14107 Section 56.14107... Safety Devices and Maintenance Requirements § 56.14107 Moving machine parts. (a) Moving machine parts... takeup pulleys, flywheels, couplings, shafts, fan blades, and similar moving parts that can cause injury...

People on the Move

Science.gov (United States)

Mohan, Audrey

2018-01-01

The purpose of this 2-3 day lesson is to introduce students in Grades 2-4 to the idea that people move around the world for a variety of reasons. In this activity, students explore why people move through class discussion, a guided reading, and interviews. The teacher elicits student ideas using the compelling question (Dimension 1 of the C3…

P1-25: Filling-in the Blind Spot with the Average Direction

Directory of Open Access Journals (Sweden)

Sang-Ah Yoo

2012-10-01

Full Text Available Previous studies have shown that the visual system integrates local motions and perceives the average direction (Watamaniuk & Duchon, 1992 Vision Research 32 931–941. We investigated whether the surface of the blind spot is filled in with the average direction of the surrounding local motions. To test this, we varied the direction of a random-dot kinematogram (RDK both in adaptation and test. Motion aftereffects (MAE were defined as the difference of motion coherence thresholds between with and without adaptation. The participants were initially adapted to an annular RDK surrounding the blind spot for 30 s in their dominant eyes. The direction of each dot in this RDK was selected equally and randomly from either a normal distribution with the mean of 15° clockwise from vertical, 15° counterclockwise from vertical, or from the mixture of them. Immediately after the adaptation, a disk-shaped test RDK was presented for 1 s to the corresponding blind-spot location in the opposite eye. This RDK moved either 15° clockwise, 15° counterclockwise, or vertically (the average of the two directions. The participants' task was to discriminate the direction of the test RDK across different coherence levels. We found significant MAE when the test RDK had the same directions as the adaptor. More importantly, equally strong MAE was observed even when the direction of the test RDK was vertical, which was not physically present during adaptation. The result demonstrates that the visual system uses the average direction of the local surrounding motions to fill in the blind spot.

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

Science.gov (United States)

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.

Moving and Being Moved: Implications for Practice.

Science.gov (United States)

Kretchmar, R. Scott

2000-01-01

Uses philosophical writings, a novel about baseball, and a nonfiction work on rowing to analyze levels of meaning in physical activity, showing why three popular methods for enhancing meaning have not succeeded and may have moved some students away from deeper levels of meaning. The paper suggests that using hints taken from the three books could…

Rearrangement moves on rooted phylogenetic networks.

Science.gov (United States)

Gambette, Philippe; van Iersel, Leo; Jones, Mark; Lafond, Manuel; Pardi, Fabio; Scornavacca, Celine

2017-08-01

Phylogenetic tree reconstruction is usually done by local search heuristics that explore the space of the possible tree topologies via simple rearrangements of their structure. Tree rearrangement heuristics have been used in combination with practically all optimization criteria in use, from maximum likelihood and parsimony to distance-based principles, and in a Bayesian context. Their basic components are rearrangement moves that specify all possible ways of generating alternative phylogenies from a given one, and whose fundamental property is to be able to transform, by repeated application, any phylogeny into any other phylogeny. Despite their long tradition in tree-based phylogenetics, very little research has gone into studying similar rearrangement operations for phylogenetic network-that is, phylogenies explicitly representing scenarios that include reticulate events such as hybridization, horizontal gene transfer, population admixture, and recombination. To fill this gap, we propose "horizontal" moves that ensure that every network of a certain complexity can be reached from any other network of the same complexity, and "vertical" moves that ensure reachability between networks of different complexities. When applied to phylogenetic trees, our horizontal moves-named rNNI and rSPR-reduce to the best-known moves on rooted phylogenetic trees, nearest-neighbor interchange and rooted subtree pruning and regrafting. Besides a number of reachability results-separating the contributions of horizontal and vertical moves-we prove that rNNI moves are local versions of rSPR moves, and provide bounds on the sizes of the rNNI neighborhoods. The paper focuses on the most biologically meaningful versions of phylogenetic networks, where edges are oriented and reticulation events clearly identified. Moreover, our rearrangement moves are robust to the fact that networks with higher complexity usually allow a better fit with the data. Our goal is to provide a solid basis for

Rearrangement moves on rooted phylogenetic networks.

Directory of Open Access Journals (Sweden)

Philippe Gambette

2017-08-01

Full Text Available Phylogenetic tree reconstruction is usually done by local search heuristics that explore the space of the possible tree topologies via simple rearrangements of their structure. Tree rearrangement heuristics have been used in combination with practically all optimization criteria in use, from maximum likelihood and parsimony to distance-based principles, and in a Bayesian context. Their basic components are rearrangement moves that specify all possible ways of generating alternative phylogenies from a given one, and whose fundamental property is to be able to transform, by repeated application, any phylogeny into any other phylogeny. Despite their long tradition in tree-based phylogenetics, very little research has gone into studying similar rearrangement operations for phylogenetic network-that is, phylogenies explicitly representing scenarios that include reticulate events such as hybridization, horizontal gene transfer, population admixture, and recombination. To fill this gap, we propose "horizontal" moves that ensure that every network of a certain complexity can be reached from any other network of the same complexity, and "vertical" moves that ensure reachability between networks of different complexities. When applied to phylogenetic trees, our horizontal moves-named rNNI and rSPR-reduce to the best-known moves on rooted phylogenetic trees, nearest-neighbor interchange and rooted subtree pruning and regrafting. Besides a number of reachability results-separating the contributions of horizontal and vertical moves-we prove that rNNI moves are local versions of rSPR moves, and provide bounds on the sizes of the rNNI neighborhoods. The paper focuses on the most biologically meaningful versions of phylogenetic networks, where edges are oriented and reticulation events clearly identified. Moreover, our rearrangement moves are robust to the fact that networks with higher complexity usually allow a better fit with the data. Our goal is to provide

Reasons for Moving in Nonmetro Iowa

OpenAIRE

Burke, Sandra Charvat; Edelman, Mark

2007-01-01

This study highlights the experiences of people who have recently moved to or from 19 selected nonmetropolitan counties of Iowa. This report highlights work, family, community, and housing reasons for moving. The purpose is to increase understanding about why people move so community leaders and citizens can develop actionable strategies for attracting and retaining population.

Neutron resonance averaging

International Nuclear Information System (INIS)

Chrien, R.E.

1986-10-01

The principles of resonance averaging as applied to neutron capture reactions are described. Several illustrations of resonance averaging to problems of nuclear structure and the distribution of radiative strength in nuclei are provided. 30 refs., 12 figs

Slow light in moving media

Science.gov (United States)

Leonhardt, U.; Piwnicki, P.

2001-06-01

We review the theory of light propagation in moving media with extremely low group velocity. We intend to clarify the most elementary features of monochromatic slow light in a moving medium and, whenever possible, to give an instructive simplified picture.

Nitrification in moving bed and fixed bed biofilters treating effluent water from a large commercial outdoor rainbow trout RAS

DEFF Research Database (Denmark)

Suhr, Karin; Pedersen, Per Bovbjerg

2010-01-01

The nitrification performance of two fixed bed (FB) biofilters and two moving bed (MB) biofilters was evaluated. They received the same cold (8 degrees C) influent water from a commercial outdoor RAS facility producing rainbow trout (average density 32 kg m(-3)). The filters were constructed as f...

Nordic Seniors on the Move

DEFF Research Database (Denmark)

”I believe that all people need to move about. Actually, some have difficulties in doing so. They stay in their home neighbourhoods where they’ve grown up and feel safe. I can understand that, but my wife and I, we didn’t want that. We are more open to new ideas.” This anthology is about seniors...... on the move. In seven chapters, Nordic researchers from various disciplines, by means of ethnographic methods, attempt to comprehend the phenomenon of Nordic seniors who move to leisure areas in their own or in other countries. The number of people involved in this kind of migratory movement has grown...... above gives voice to one of these seniors, stressing the necessity of moving. The anthology contributes to the international body of literature about later life migration, specifically representing experiences made by Nordic seniors. As shown here, mobility and migration in later life have implications...

Slow collisions between identical atoms in a laser field: Application of the Born and Markov approximations to the system of moving atoms

International Nuclear Information System (INIS)

Trippenbach, M.; Gao, B.; Cooper, J.; Burnett, K.

1992-01-01

We have derived reduced-density-matrix equations of motion for a pair of two identical atoms moving in the radiation field as the first step in establishing a theory of collisional redistribution of light from neutral-atom traps. We use the Zwanzig projection-operator technique to average over spontaneous field modes and establish the conditions under which Born and Markov approximations can be applied to the system of moving atoms. It follows from these considerations that when these conditions hold, the reduced-density-matrix equation for moving atoms has the same form as that for the stationary case: time dependence is introduced into the decay rates and interaction potentials by making the substitution R=R(t)

A moving experience !

CERN Document Server

2005-01-01

The Transport Service pulled out all the stops and, more specifically, its fleet of moving and lifting equipment for the Discovery Monday on 6 June - a truly moving experience for all the visitors who took part ! Visitors could play at being machine operator, twiddling the controls of a lift truck fitted with a jib to lift a dummy magnet into a wooden mock-up of a beam-line.They had to show even greater dexterity for this game of lucky dip...CERN-style.Those with a head for heights took to the skies 20 m above ground in a telescopic boom lift.Children were allowed to climb up into the operator's cabin - this is one of the cranes used to move the LHC magnets around. Warm thanks to all members of the Transport Service for their participation, especially B. Goicoechea, T. Ilkei, R. Bihery, S. Prodon, S. Pelletier, Y. Bernard, A.  Sallot, B. Pigeard, S. Guinchard, B. Bulot, J. Berrez, Y. Grandjean, A. Bouakkaz, M. Bois, F. Stach, T. Mazzarino and S. Fumey.

Adaptive moving mesh methods for simulating one-dimensional groundwater problems with sharp moving fronts

Science.gov (United States)

Huang, W.; Zheng, Lingyun; Zhan, X.

2002-01-01

Accurate modelling of groundwater flow and transport with sharp moving fronts often involves high computational cost, when a fixed/uniform mesh is used. In this paper, we investigate the modelling of groundwater problems using a particular adaptive mesh method called the moving mesh partial differential equation approach. With this approach, the mesh is dynamically relocated through a partial differential equation to capture the evolving sharp fronts with a relatively small number of grid points. The mesh movement and physical system modelling are realized by solving the mesh movement and physical partial differential equations alternately. The method is applied to the modelling of a range of groundwater problems, including advection dominated chemical transport and reaction, non-linear infiltration in soil, and the coupling of density dependent flow and transport. Numerical results demonstrate that sharp moving fronts can be accurately and efficiently captured by the moving mesh approach. Also addressed are important implementation strategies, e.g. the construction of the monitor function based on the interpolation error, control of mesh concentration, and two-layer mesh movement. Copyright ?? 2002 John Wiley and Sons, Ltd.

Estimation of direction of arrival of a moving target using subspace based approaches

Science.gov (United States)

Ghosh, Ripul; Das, Utpal; Akula, Aparna; Kumar, Satish; Sardana, H. K.

2016-05-01

In this work, array processing techniques based on subspace decomposition of signal have been evaluated for estimation of direction of arrival of moving targets using acoustic signatures. Three subspace based approaches - Incoherent Wideband Multiple Signal Classification (IWM), Least Square-Estimation of Signal Parameters via Rotation Invariance Techniques (LS-ESPRIT) and Total Least Square- ESPIRIT (TLS-ESPRIT) are considered. Their performance is compared with conventional time delay estimation (TDE) approaches such as Generalized Cross Correlation (GCC) and Average Square Difference Function (ASDF). Performance evaluation has been conducted on experimentally generated data consisting of acoustic signatures of four different types of civilian vehicles moving in defined geometrical trajectories. Mean absolute error and standard deviation of the DOA estimates w.r.t. ground truth are used as performance evaluation metrics. Lower statistical values of mean error confirm the superiority of subspace based approaches over TDE based techniques. Amongst the compared methods, LS-ESPRIT indicated better performance.

Averaging, not internal noise, limits the development of coherent motion processing

Directory of Open Access Journals (Sweden)

Catherine Manning

2014-10-01

Full Text Available The development of motion processing is a critical part of visual development, allowing children to interact with moving objects and navigate within a dynamic environment. However, global motion processing, which requires pooling motion information across space, develops late, reaching adult-like levels only by mid-to-late childhood. The reasons underlying this protracted development are not yet fully understood. In this study, we sought to determine whether the development of motion coherence sensitivity is limited by internal noise (i.e., imprecision in estimating the directions of individual elements and/or global pooling across local estimates. To this end, we presented equivalent noise direction discrimination tasks and motion coherence tasks at both slow (1.5°/s and fast (6°/s speeds to children aged 5, 7, 9 and 11 years, and adults. We show that, as children get older, their levels of internal noise reduce, and they are able to average across more local motion estimates. Regression analyses indicated, however, that age-related improvements in coherent motion perception are driven solely by improvements in averaging and not by reductions in internal noise. Our results suggest that the development of coherent motion sensitivity is primarily limited by developmental changes within brain regions involved in integrating motion signals (e.g., MT/V5.

Move of ground water

International Nuclear Information System (INIS)

Kimura, Shigehiko

1983-01-01

As a ground water flow which is difficult to explain by Darcy's theory, there is stagnant water in strata, which moves by pumping and leads to land subsidence. This is now a major problem in Japan. Such move on an extensive scale has been investigated in detail by means of 3 H such as from rainfall in addition to ordinary measurement. The move of ground water is divided broadly into that in an unsaturated stratum from ground surface to water-table and that in a saturated stratum below the water-table. The course of the analyses made so far by 3 H contained in water, and the future trend of its usage are described. A flow model of regarding water as plastic fluid and its flow as channel assembly may be available for some flow mechanism which is not possible to explain with Darcy's theory. (Mori, K.)

A hybrid procedure for MSW generation forecasting at multiple time scales in Xiamen City, China.

Science.gov (United States)

Xu, Lilai; Gao, Peiqing; Cui, Shenghui; Liu, Chun

2013-06-01

Accurate forecasting of municipal solid waste (MSW) generation is crucial and fundamental for the planning, operation and optimization of any MSW management system. Comprehensive information on waste generation for month-scale, medium-term and long-term time scales is especially needed, considering the necessity of MSW management upgrade facing many developing countries. Several existing models are available but of little use in forecasting MSW generation at multiple time scales. The goal of this study is to propose a hybrid model that combines the seasonal autoregressive integrated moving average (SARIMA) model and grey system theory to forecast MSW generation at multiple time scales without needing to consider other variables such as demographics and socioeconomic factors. To demonstrate its applicability, a case study of Xiamen City, China was performed. Results show that the model is robust enough to fit and forecast seasonal and annual dynamics of MSW generation at month-scale, medium- and long-term time scales with the desired accuracy. In the month-scale, MSW generation in Xiamen City will peak at 132.2 thousand tonnes in July 2015 - 1.5 times the volume in July 2010. In the medium term, annual MSW generation will increase to 1518.1 thousand tonnes by 2015 at an average growth rate of 10%. In the long term, a large volume of MSW will be output annually and will increase to 2486.3 thousand tonnes by 2020 - 2.5 times the value for 2010. The hybrid model proposed in this paper can enable decision makers to develop integrated policies and measures for waste management over the long term. Copyright © 2013 Elsevier Ltd. All rights reserved.

Student-Centered Coaching: The Moves

Science.gov (United States)

Sweeney, Diane; Harris, Leanna S.

2017-01-01

Student-centered coaching is a highly-effective, evidence-based coaching model that shifts the focus from "fixing" teachers to collaborating with them to design instruction that targets student outcomes. But what does this look like in practice? "Student-Centered Coaching: The Moves" shows you the day-to-day coaching moves that…

Mixed convection from a discrete heat source in enclosures with two adjacent moving walls and filled with micropolar nanofluids

Directory of Open Access Journals (Sweden)

Sameh E. Ahmed

2016-03-01

Full Text Available This paper examines numerically the thermal and flow field characteristics of the laminar steady mixed convection flow in a square lid-driven enclosure filled with water-based micropolar nanofluids by using the finite volume method. While a uniform heat source is located on a part of the bottom of the enclosure, both the right and left sidewalls are considered adiabatic together with the remaining parts of the bottom wall. The upper wall is maintained at a relatively low temperature. Both the upper and left sidewalls move at a uniform lid-driven velocity and four different cases of the moving lid ordinations are considered. The fluid inside the enclosure is a water based micropolar nanofluid containing different types of solid spherical nanoparticles: Cu, Ag, Al2O3, and TiO2. Based on the numerical results, the effects of the dominant parameters such as Richardson number, nanofluid type, length and location of the heat source, solid volume fractions, moving lid orientations and dimensionless viscosity are examined. Comparisons with previously numerical works are performed and good agreements between the results are observed. It is found that the average Nusselt number along the heat source decreases as the heat source length increases while it increases when the solid volume fraction increases. Also, the results of the present study indicate that both the local and the average Nusselt numbers along the heat source have the highest value for the fourth case (C4. Moreover, it is observed that both the Richardson number and moving lid ordinations have a significant effect on the flow and thermal fields in the enclosure.

Moving Target Photometry Using WISE and NEOWISE

Science.gov (United States)

Wright, Edward L.

2015-01-01

WISE band 1 observations have a significant noise contribution from confusion. The image subtraction done on W0855-0714 by Wright et al. (2014) shows that this noise source can be eliminated for sources that move by much more than the beamsize. This paper describes an analysis that includes a pattern of celestially fixed flux plus a source moving with a known trajectory. This technique allows the confusion noise to be modeled with nuisance parameters and removed even for sources that have not moved by many beamwidths. However, the detector noise is magnified if the motion is too small. Examples of the method applied to fast moving Y dwarfs and slow moving planets will be shown.

Concentration Sensing by the Moving Nucleus in Cell Fate Determination: A Computational Analysis.

Directory of Open Access Journals (Sweden)

Varun Aggarwal

Full Text Available During development of the vertebrate neuroepithelium, the nucleus in neural progenitor cells (NPCs moves from the apex toward the base and returns to the apex (called interkinetic nuclear migration at which point the cell divides. The fate of the resulting daughter cells is thought to depend on the sampling by the moving nucleus of a spatial concentration profile of the cytoplasmic Notch intracellular domain (NICD. However, the nucleus executes complex stochastic motions including random waiting and back and forth motions, which can expose the nucleus to randomly varying levels of cytoplasmic NICD. How nuclear position can determine daughter cell fate despite the stochastic nature of nuclear migration is not clear. Here we derived a mathematical model for reaction, diffusion, and nuclear accumulation of NICD in NPCs during interkinetic nuclear migration (INM. Using experimentally measured trajectory-dependent probabilities of nuclear turning, nuclear waiting times and average nuclear speeds in NPCs in the developing zebrafish retina, we performed stochastic simulations to compute the nuclear trajectory-dependent probabilities of NPC differentiation. Comparison with experimentally measured nuclear NICD concentrations and trajectory-dependent probabilities of differentiation allowed estimation of the NICD cytoplasmic gradient. Spatially polarized production of NICD, rapid NICD cytoplasmic consumption and the time-averaging effect of nuclear import/export kinetics are sufficient to explain the experimentally observed differentiation probabilities. Our computational studies lend quantitative support to the feasibility of the nuclear concentration-sensing mechanism for NPC fate determination in zebrafish retina.

Daily air quality index forecasting with hybrid models: A case in China

International Nuclear Information System (INIS)

Zhu, Suling; Lian, Xiuyuan; Liu, Haixia; Hu, Jianming; Wang, Yuanyuan; Che, Jinxing

2017-01-01

Air quality is closely related to quality of life. Air pollution forecasting plays a vital role in air pollution warnings and controlling. However, it is difficult to attain accurate forecasts for air pollution indexes because the original data are non-stationary and chaotic. The existing forecasting methods, such as multiple linear models, autoregressive integrated moving average (ARIMA) and support vector regression (SVR), cannot fully capture the information from series of pollution indexes. Therefore, new effective techniques need to be proposed to forecast air pollution indexes. The main purpose of this research is to develop effective forecasting models for regional air quality indexes (AQI) to address the problems above and enhance forecasting accuracy. Therefore, two hybrid models (EMD-SVR-Hybrid and EMD-IMFs-Hybrid) are proposed to forecast AQI data. The main steps of the EMD-SVR-Hybrid model are as follows: the data preprocessing technique EMD (empirical mode decomposition) is utilized to sift the original AQI data to obtain one group of smoother IMFs (intrinsic mode functions) and a noise series, where the IMFs contain the important information (level, fluctuations and others) from the original AQI series. LS-SVR is applied to forecast the sum of the IMFs, and then, S-ARIMA (seasonal ARIMA) is employed to forecast the residual sequence of LS-SVR. In addition, EMD-IMFs-Hybrid first separately forecasts the IMFs via statistical models and sums the forecasting results of the IMFs as EMD-IMFs. Then, S-ARIMA is employed to forecast the residuals of EMD-IMFs. To certify the proposed hybrid model, AQI data from June 2014 to August 2015 collected from Xingtai in China are utilized as a test case to investigate the empirical research. In terms of some of the forecasting assessment measures, the AQI forecasting results of Xingtai show that the two proposed hybrid models are superior to ARIMA, SVR, GRNN, EMD-GRNN, Wavelet-GRNN and Wavelet-SVR. Therefore, the

On the energy flux of a signal in a moving magnetized plasma

International Nuclear Information System (INIS)

Gavrilenko, V.G.; Zelekson, L.A.

1980-01-01

Energy exchange of an electromagnetic signal with a homogeneous plasma moving along a strong magnetic field, provided that the initial signal is given in a plane parallel or normal to the drift velocity, has been analyzed. In the first case expressions for the fields excited in the long-range zone are obtained by the stationary phase method. It follows from the expressions that starting from some moment of time the direction of the energy flux and the sign of the energy density change into opposite. This is caused by the fact that the fast harmonic components (with a phase velocity exceeding the drift velocity) of the initial signal reach first the point of observation, and then the slow ones do, the energy density of the show waves being negative. On longitudinal propagation of perturbations excited by a quasimonochromatic source, the averaged flux and energy density in the weakly relativistic approximation have been shown to be zero. In conclusion electromagnetic waves moving with a superlight velocity in a non-dispersive medium are studied, the energy of the waves changing the sign with time [ru

Trading Fees and Slow-Moving Capital

OpenAIRE

Buss, Adrian; Dumas, Bernard J

2015-01-01

In some situations, investment capital seems to move slowly towards profitable trades. We develop a model of a financial market in which capital moves slowly simply because there is a proportional cost to moving capital. We incorporate trading fees in an infinite-horizon dynamic general-equilibrium model in which investors optimally and endogenously decide when and how much to trade. We determine the steady-state equilibrium no-trade zone, study the dynamics of equilibrium trades and prices a...

30 CFR 57.14107 - Moving machine parts.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Moving machine parts. 57.14107 Section 57.14107... Equipment Safety Devices and Maintenance Requirements § 57.14107 Moving machine parts. (a) Moving machine parts shall be guarded to protect persons from contacting gears, sprockets, chains, drive, head, tail...

Lattice Boltzmann methods for moving boundary flows

International Nuclear Information System (INIS)

Inamuro, Takaji

2012-01-01

The lattice Boltzmann methods (LBMs) for moving boundary flows are presented. The LBM for two-phase fluid flows with the same density and the LBM combined with the immersed boundary method are described. In addition, the LBM on a moving multi-block grid is explained. Three numerical examples (a droplet moving in a constricted tube, the lift generation of a flapping wing and the sedimentation of an elliptical cylinder) are shown in order to demonstrate the applicability of the LBMs to moving boundary problems. (invited review)

Lattice Boltzmann methods for moving boundary flows

Energy Technology Data Exchange (ETDEWEB)

Inamuro, Takaji, E-mail: inamuro@kuaero.kyoto-u.ac.jp [Department of Aeronautics and Astronautics, and Advanced Research Institute of Fluid Science and Engineering, Graduate School of Engineering, Kyoto University, Kyoto 606-8501 (Japan)

2012-04-01

The lattice Boltzmann methods (LBMs) for moving boundary flows are presented. The LBM for two-phase fluid flows with the same density and the LBM combined with the immersed boundary method are described. In addition, the LBM on a moving multi-block grid is explained. Three numerical examples (a droplet moving in a constricted tube, the lift generation of a flapping wing and the sedimentation of an elliptical cylinder) are shown in order to demonstrate the applicability of the LBMs to moving boundary problems. (invited review)

MODELLING THE INTERACTION IN GAME SPORTS - RELATIVE PHASE AND MOVING CORRELATIONS

Directory of Open Access Journals (Sweden)

Martin Lames

2006-12-01

Full Text Available Model building in game sports should maintain the constitutive feature of this group of sports, the dynamic interaction process between the two parties. For single net/wall games relative phase is suggested to describe the positional interaction between the two players. 30 baseline rallies in tennis were examined and relative phase was calculated by Hilbert transform from the two time-series of lateral displacement and trajectory in the court respectively. Results showed that relative phase indicates some aspects of the tactical interaction in tennis. At a more abstract level the interaction between two teams in handball was studied by examining the relationship of the two scoring processes. Each process can be conceived as a random walk. Moving averages of the scoring probabilities indicate something like a momentary strength. A moving correlation (length = 20 ball possessions describes the momentary relationship between the teams' strength. Evidence was found that this correlation is heavily time-dependent, in almost every single game among the 40 examined ones we found phases with a significant positive as well as significant negative relationship. This underlines the importance of a dynamic view on the interaction in these games.

77 FR 16566 - Submission for OMB Review, Comment Request, Proposed Collection: Let's Move Museums, Let's Move...

Science.gov (United States)

2012-03-21

..., Proposed Collection: Let's Move Museums, Let's Move Gardens AGENCY: Institute of Museum and Library..., comment request. SUMMARY: The Institute of Museum and Library Services announces that the following... functions of the agency, including whether the information will have practical utility; Evaluate the...

On Averaging Rotations

DEFF Research Database (Denmark)

Gramkow, Claus

1999-01-01

In this article two common approaches to averaging rotations are compared to a more advanced approach based on a Riemannian metric. Very offten the barycenter of the quaternions or matrices that represent the rotations are used as an estimate of the mean. These methods neglect that rotations belo...... approximations to the Riemannian metric, and that the subsequent corrections are inherient in the least squares estimation. Keywords: averaging rotations, Riemannian metric, matrix, quaternion......In this article two common approaches to averaging rotations are compared to a more advanced approach based on a Riemannian metric. Very offten the barycenter of the quaternions or matrices that represent the rotations are used as an estimate of the mean. These methods neglect that rotations belong...

Average-energy games

Directory of Open Access Journals (Sweden)

Patricia Bouyer

2015-09-01

Full Text Available Two-player quantitative zero-sum games provide a natural framework to synthesize controllers with performance guarantees for reactive systems within an uncontrollable environment. Classical settings include mean-payoff games, where the objective is to optimize the long-run average gain per action, and energy games, where the system has to avoid running out of energy. We study average-energy games, where the goal is to optimize the long-run average of the accumulated energy. We show that this objective arises naturally in several applications, and that it yields interesting connections with previous concepts in the literature. We prove that deciding the winner in such games is in NP inter coNP and at least as hard as solving mean-payoff games, and we establish that memoryless strategies suffice to win. We also consider the case where the system has to minimize the average-energy while maintaining the accumulated energy within predefined bounds at all times: this corresponds to operating with a finite-capacity storage for energy. We give results for one-player and two-player games, and establish complexity bounds and memory requirements.

FOCUS FORECASTING IN SUPPLY CHAIN: THE CASE STUDY OF FAST MOVING CONSUMER GOODS COMPANY IN SERBIA

Directory of Open Access Journals (Sweden)

Zoran Rakićević

2015-04-01

Full Text Available This paper presents an application of focus forecasting in a fast moving consumer goods (FMCG supply chain. Focus forecasting is tested in a real business case in a Serbian enterprise. The data used in the simulation refers to the historical sales of two types of FMCG with several different products. The data were collected and summarized across the whole distribution channel in the Serbian market from January 2012 to December 2013. We applied several well-known time series forecasting models using the focus forecasting approach, where for the future time period we used the method which had the best performances in the past. The focus forecasting approach mixes different standard forecasting methods on the data sets in order to find the one that was the most accurate during the past period. The accuracy of forecasting methods is defined through different measures of errors. In this paper we implemented the following forecasting models in Microsoft Excel: last period, all average, moving average, exponential smoothing with constant and variable parameter α, exponential smoothing with trend, exponential smoothing with trend and seasonality. The main purpose was not to evaluate different forecasting methods but to show a practical application of the focus forecasting approach in a real business case.

Moving Horizon Estimation and Control

DEFF Research Database (Denmark)

Jørgensen, John Bagterp

successful and applied methodology beyond PID-control for control of industrial processes. The main contribution of this thesis is introduction and definition of the extended linear quadratic optimal control problem for solution of numerical problems arising in moving horizon estimation and control...... problems. Chapter 1 motivates moving horizon estimation and control as a paradigm for control of industrial processes. It introduces the extended linear quadratic control problem and discusses its central role in moving horizon estimation and control. Introduction, application and efficient solution....... It provides an algorithm for computation of the maximal output admissible set for linear model predictive control. Appendix D provides results concerning linear regression. Appendix E discuss prediction error methods for identification of linear models tailored for model predictive control....

One-dimensional Fermi accelerator model with moving wall described by a nonlinear van der Pol oscillator.

Science.gov (United States)

Botari, Tiago; Leonel, Edson D

2013-01-01

A modification of the one-dimensional Fermi accelerator model is considered in this work. The dynamics of a classical particle of mass m, confined to bounce elastically between two rigid walls where one is described by a nonlinear van der Pol type oscillator while the other one is fixed, working as a reinjection mechanism of the particle for a next collision, is carefully made by the use of a two-dimensional nonlinear mapping. Two cases are considered: (i) the situation where the particle has mass negligible as compared to the mass of the moving wall and does not affect the motion of it; and (ii) the case where collisions of the particle do affect the movement of the moving wall. For case (i) the phase space is of mixed type leading us to observe a scaling of the average velocity as a function of the parameter (χ) controlling the nonlinearity of the moving wall. For large χ, a diffusion on the velocity is observed leading to the conclusion that Fermi acceleration is taking place. On the other hand, for case (ii), the motion of the moving wall is affected by collisions with the particle. However, due to the properties of the van der Pol oscillator, the moving wall relaxes again to a limit cycle. Such kind of motion absorbs part of the energy of the particle leading to a suppression of the unlimited energy gain as observed in case (i). The phase space shows a set of attractors of different periods whose basin of attraction has a complicated organization.

Moving carbonation fronts in concrete: a moving-sharp-interface approach

NARCIS (Netherlands)

Muntean, A.; Böhm, M.; Kropp, J.

2011-01-01

We present a new modeling strategy for predicting the penetration of carbonation reaction fronts in concrete. The approach relies on the assumption that carbonation reaction concentrates macroscopically on an a priori unknown narrow strip (called reaction front) moving into concrete gradually

Averaging of nonlinearity-managed pulses

International Nuclear Information System (INIS)

Zharnitsky, Vadim; Pelinovsky, Dmitry

2005-01-01

We consider the nonlinear Schroedinger equation with the nonlinearity management which describes Bose-Einstein condensates under Feshbach resonance. By using an averaging theory, we derive the Hamiltonian averaged equation and compare it with other averaging methods developed for this problem. The averaged equation is used for analytical approximations of nonlinearity-managed solitons

Ultrasound image based visual servoing for moving target ablation by high intensity focused ultrasound.

Science.gov (United States)

Seo, Joonho; Koizumi, Norihiro; Mitsuishi, Mamoru; Sugita, Naohiko

2017-12-01

Although high intensity focused ultrasound (HIFU) is a promising technology for tumor treatment, a moving abdominal target is still a challenge in current HIFU systems. In particular, respiratory-induced organ motion can reduce the treatment efficiency and negatively influence the treatment result. In this research, we present: (1) a methodology for integration of ultrasound (US) image based visual servoing in a HIFU system; and (2) the experimental results obtained using the developed system. In the visual servoing system, target motion is monitored by biplane US imaging and tracked in real time (40 Hz) by registration with a preoperative 3D model. The distance between the target and the current HIFU focal position is calculated in every US frame and a three-axis robot physically compensates for differences. Because simultaneous HIFU irradiation disturbs US target imaging, a sophisticated interlacing strategy was constructed. In the experiments, respiratory-induced organ motion was simulated in a water tank with a linear actuator and kidney-shaped phantom model. Motion compensation with HIFU irradiation was applied to the moving phantom model. Based on the experimental results, visual servoing exhibited a motion compensation accuracy of 1.7 mm (RMS) on average. Moreover, the integrated system could make a spherical HIFU-ablated lesion in the desired position of the respiratory-moving phantom model. We have demonstrated the feasibility of our US image based visual servoing technique in a HIFU system for moving target treatment. © 2016 The Authors The International Journal of Medical Robotics and Computer Assisted Surgery Published by John Wiley & Sons Ltd.

A new active portfolio risk management for an electricity retailer based on a drawdown risk preference

International Nuclear Information System (INIS)

Charwand, Mansour; Gitizadeh, Mohsen; Siano, Pierluigi

2017-01-01

This paper addresses the deciding under uncertainty of an electricity retailer in order to maximise its total expected rate of return. The developed methodology is based on the modelling of the stochastic evolution of zonal prices that seeks to manage a portfolio of different contracts. Retailer's load and the price at each zone are forecasted using the seasonal autoregressive integrated moving average (SARIMA) model and a clustering technique is used for scenario reduction. Supply sources include the pool, self-production facilities, forward and bilateral contracts. The risk of cost fluctuation due to uncertainties is explicitly modelled using the multi-scenario drawdown methodology. This risk function quantifies in aggregated format the frequency and magnitude of the portfolio drawdowns over planning horizon. In-sample and out-of-sample runs are performed for a portfolio allocation problem. Carried out experimental results on the basis of realistic data, show that imposing risk constraints improve the “real” performance of a portfolio management in out-of-sample runs. - Highlights: • A new drawdown-based method is introduced to retailer deciding under uncertainty. • This tool is used to assess the risk levels regarding retailer midterm strategies. • The methodology is based on the modeling of the stochastic evolution of zonal prices. • The risk function quantifies the frequency and magnitude of the portfolio drawdowns. • In-sample and out-of-sample runs are performed for a portfolio allocation problem.

Using autoregressive integrated moving average (ARIMA models to predict and monitor the number of beds occupied during a SARS outbreak in a tertiary hospital in Singapore

Directory of Open Access Journals (Sweden)

Earnest Arul

2005-05-01

Full Text Available Abstract Background The main objective of this study is to apply autoregressive integrated moving average (ARIMA models to make real-time predictions on the number of beds occupied in Tan Tock Seng Hospital, during the recent SARS outbreak. Methods This is a retrospective study design. Hospital admission and occupancy data for isolation beds was collected from Tan Tock Seng hospital for the period 14th March 2003 to 31st May 2003. The main outcome measure was daily number of isolation beds occupied by SARS patients. Among the covariates considered were daily number of people screened, daily number of people admitted (including observation, suspect and probable cases and days from the most recent significant event discovery. We utilized the following strategy for the analysis. Firstly, we split the outbreak data into two. Data from 14th March to 21st April 2003 was used for model development. We used structural ARIMA models in an attempt to model the number of beds occupied. Estimation is via the maximum likelihood method using the Kalman filter. For the ARIMA model parameters, we considered the simplest parsimonious lowest order model. Results We found that the ARIMA (1,0,3 model was able to describe and predict the number of beds occupied during the SARS outbreak well. The mean absolute percentage error (MAPE for the training set and validation set were 5.7% and 8.6% respectively, which we found was reasonable for use in the hospital setting. Furthermore, the model also provided three-day forecasts of the number of beds required. Total number of admissions and probable cases admitted on the previous day were also found to be independent prognostic factors of bed occupancy. Conclusion ARIMA models provide useful tools for administrators and clinicians in planning for real-time bed capacity during an outbreak of an infectious disease such as SARS. The model could well be used in planning for bed-capacity during outbreaks of other infectious

Using autoregressive integrated moving average (ARIMA) models to predict and monitor the number of beds occupied during a SARS outbreak in a tertiary hospital in Singapore.

Science.gov (United States)

Earnest, Arul; Chen, Mark I; Ng, Donald; Sin, Leo Yee

2005-05-11

The main objective of this study is to apply autoregressive integrated moving average (ARIMA) models to make real-time predictions on the number of beds occupied in Tan Tock Seng Hospital, during the recent SARS outbreak. This is a retrospective study design. Hospital admission and occupancy data for isolation beds was collected from Tan Tock Seng hospital for the period 14th March 2003 to 31st May 2003. The main outcome measure was daily number of isolation beds occupied by SARS patients. Among the covariates considered were daily number of people screened, daily number of people admitted (including observation, suspect and probable cases) and days from the most recent significant event discovery. We utilized the following strategy for the analysis. Firstly, we split the outbreak data into two. Data from 14th March to 21st April 2003 was used for model development. We used structural ARIMA models in an attempt to model the number of beds occupied. Estimation is via the maximum likelihood method using the Kalman filter. For the ARIMA model parameters, we considered the simplest parsimonious lowest order model. We found that the ARIMA (1,0,3) model was able to describe and predict the number of beds occupied during the SARS outbreak well. The mean absolute percentage error (MAPE) for the training set and validation set were 5.7% and 8.6% respectively, which we found was reasonable for use in the hospital setting. Furthermore, the model also provided three-day forecasts of the number of beds required. Total number of admissions and probable cases admitted on the previous day were also found to be independent prognostic factors of bed occupancy. ARIMA models provide useful tools for administrators and clinicians in planning for real-time bed capacity during an outbreak of an infectious disease such as SARS. The model could well be used in planning for bed-capacity during outbreaks of other infectious diseases as well.

Spatio-Temporal Queries for moving objects Data warehousing

OpenAIRE

Esheiba, Leila; Mokhtar, Hoda M. O.; El-Sharkawi, Mohamed

2013-01-01

In the last decade, Moving Object Databases (MODs) have attracted a lot of attention from researchers. Several research works were conducted to extend traditional database techniques to accommodate the new requirements imposed by the continuous change in location information of moving objects. Managing, querying, storing, and mining moving objects were the key research directions. This extensive interest in moving objects is a natural consequence of the recent ubiquitous location-aware device...

Energy flux correlations and moving mirrors

International Nuclear Information System (INIS)

Ford, L.H.; Roman, Thomas A.

2004-01-01

We study the quantum stress tensor correlation function for a massless scalar field in a flat two-dimensional spacetime containing a moving mirror. We construct the correlation functions for right-moving and left-moving fluxes for an arbitrary trajectory, and then specialize them to the case of a mirror trajectory for which the expectation value of the stress tensor describes a pair of delta-function pulses, one of negative energy and one of positive energy. The flux correlation function describes the fluctuations around this mean stress tensor, and reveals subtle changes in the correlations between regions where the mean flux vanishes

The difference between alternative averages

Directory of Open Access Journals (Sweden)

James Vaupel

2012-09-01

Full Text Available BACKGROUND Demographers have long been interested in how compositional change, e.g., change in age structure, affects population averages. OBJECTIVE We want to deepen understanding of how compositional change affects population averages. RESULTS The difference between two averages of a variable, calculated using alternative weighting functions, equals the covariance between the variable and the ratio of the weighting functions, divided by the average of the ratio. We compare weighted and unweighted averages and also provide examples of use of the relationship in analyses of fertility and mortality. COMMENTS Other uses of covariances in formal demography are worth exploring.

Reliable classification of moving waste materials with LIBS in concrete recycling.

Science.gov (United States)

Xia, Han; Bakker, M C M

2014-03-01

Effective discrimination between different waste materials is of paramount importance for inline quality inspection of recycle concrete aggregates from demolished buildings. The moving targeted materials in the concrete waste stream are wood, PVC, gypsum block, glass, brick, steel rebar, aggregate and cement paste. For each material, up to three different types were considered, while thirty particles of each material were selected. Proposed is a reliable classification methodology based on integration of the LIBS spectral emissions in a fixed time window, starting from the deployment of the laser shot. PLS-DA (multi class) and the hybrid combination PCA-Adaboost (binary class) were investigated as efficient classifiers. In addition, mean centre and auto scaling approaches were compared for both classifiers. Using 72 training spectra and 18 test spectra per material, each averaged by ten shots, only PLS-DA achieved full discrimination, and the mean centre approach made it slightly more robust. Continuing with PLS-DA, the relation between data averaging and convergence to 0.3% average error was investigated using 9-fold cross-validations. Single-shot PLS-DA presented the highest challenge and most desirable methodology, which converged with 59 PC. The degree of success in practical testing will depend on the quality of the training set and the implications of the possibly remaining false positives. © 2013 Published by Elsevier B.V.

A theory of traffic congestion at moving bottlenecks

Energy Technology Data Exchange (ETDEWEB)

Kerner, Boris S [Daimler AG, GR/PTF, HPC: G021, 71059 Sindelfingen (Germany); Klenov, Sergey L, E-mail: boris.kerner@daimler.co [Department of Physics, Moscow Institute of Physics and Technology, 141700 Dolgoprudny, Moscow Region (Russian Federation)

2010-10-22

The physics of traffic congestion occurring at a moving bottleneck on a multi-lane road is revealed based on the numerical analyses of vehicular traffic with a discrete stochastic traffic flow model in the framework of three-phase traffic theory. We find that there is a critical speed of a moving bottleneck at which traffic breakdown, i.e. a first-order phase transition from free flow to synchronized flow, occurs spontaneously at the moving bottleneck, if the flow rate upstream of the bottleneck is great enough. The greater the flow rate, the higher the critical speed of the moving bottleneck. A diagram of congested traffic patterns at the moving bottleneck is found, which shows regions in the flow-rate-moving-bottleneck-speed plane in which congested patterns emerge spontaneously or can be induced through large enough disturbances in an initial free flow. A comparison of features of traffic breakdown and resulting congested patterns at the moving bottleneck with known ones at an on-ramp (and other motionless) bottleneck is made. Nonlinear features of complex interactions and transformations of congested traffic patterns occurring at on- and off-ramp bottlenecks due to the existence of the moving bottleneck are found. The physics of the phenomenon of traffic congestion due to 'elephant racing' on a multi-lane road is revealed.

A theory of traffic congestion at moving bottlenecks

International Nuclear Information System (INIS)

Kerner, Boris S; Klenov, Sergey L

2010-01-01

The physics of traffic congestion occurring at a moving bottleneck on a multi-lane road is revealed based on the numerical analyses of vehicular traffic with a discrete stochastic traffic flow model in the framework of three-phase traffic theory. We find that there is a critical speed of a moving bottleneck at which traffic breakdown, i.e. a first-order phase transition from free flow to synchronized flow, occurs spontaneously at the moving bottleneck, if the flow rate upstream of the bottleneck is great enough. The greater the flow rate, the higher the critical speed of the moving bottleneck. A diagram of congested traffic patterns at the moving bottleneck is found, which shows regions in the flow-rate-moving-bottleneck-speed plane in which congested patterns emerge spontaneously or can be induced through large enough disturbances in an initial free flow. A comparison of features of traffic breakdown and resulting congested patterns at the moving bottleneck with known ones at an on-ramp (and other motionless) bottleneck is made. Nonlinear features of complex interactions and transformations of congested traffic patterns occurring at on- and off-ramp bottlenecks due to the existence of the moving bottleneck are found. The physics of the phenomenon of traffic congestion due to 'elephant racing' on a multi-lane road is revealed.

Moving in Circles

DEFF Research Database (Denmark)

Simonsen, Gunvor

2008-01-01

The article examines the development of African diaspora history during the last fifty years. It outlines the move from a focus on African survivals to a focus on deep rooted cultural principles and back again to a revived interest in concrete cultural transfers from Africa to the Americas....... This circular movement can be explained by a combination of elements characterizing African Atlantic and black Atlantic history. Among them is a lack of attention to questions of periodisation and change. Likewise, it has proven difficult to conceptualize Africa and America at one and the same time...... as characterized by cultural diversity and variation. Moreover, the field has been haunted by a tendency of moving to easily from descriptive evidence to conclusions about African identity in the Americas. A promising way to overcome these problems, it is suggested, is to develop research that focuses on single...

Codimension-two bifurcation of axial loaded beam bridge subjected to an infinite series of moving loads

International Nuclear Information System (INIS)

Yang Xin-Wei; Tian Rui-Lan; Li Hai-Tao

2013-01-01

A novel model is proposed which comprises of a beam bridge subjected to an axial load and an infinite series of moving loads. The moving loads, whose distance between the neighbouring ones is the length of the beam bridge, coupled with the axial force can lead the vibration of the beam bridge to codimension-two bifurcation. Of particular concern is a parameter regime where non-persistence set regions undergo a transition to persistence regions. The boundary of each stripe represents a bifurcation which can drive the system off a kind of dynamics and jump to another one, causing damage due to the resulting amplitude jumps. The Galerkin method, averaging method, invertible linear transformation, and near identity nonlinear transformations are used to obtain the universal unfolding for the codimension-two bifurcation of the mid-span deflection. The efficiency of the theoretical analysis obtained in this paper is verified via numerical simulations. (general)

On the XFEL Schrödinger Equation: Highly Oscillatory Magnetic Potentials and Time Averaging

KAUST Repository

Antonelli, Paolo

2014-01-14

We analyse a nonlinear Schrödinger equation for the time-evolution of the wave function of an electron beam, interacting selfconsistently through a Hartree-Fock nonlinearity and through the repulsive Coulomb interaction of an atomic nucleus. The electrons are supposed to move under the action of a time dependent, rapidly periodically oscillating electromagnetic potential. This can be considered a simplified effective single particle model for an X-ray free electron laser. We prove the existence and uniqueness for the Cauchy problem and the convergence of wave-functions to corresponding solutions of a Schrödinger equation with a time-averaged Coulomb potential in the high frequency limit for the oscillations of the electromagnetic potential. © 2014 Springer-Verlag Berlin Heidelberg.

Moving ring reactor 'Karin-1'

International Nuclear Information System (INIS)

1983-12-01

The conceptual design of a moving ring reactor ''Karin-1'' has been carried out to advance fusion system design, to clarify the research and development problems, and to decide their priority. In order to attain these objectives, a D-T reactor with tritium breeding blanket is designed, a commercial reactor with net power output of 500 MWe is designed, the compatibility of plasma physics with fusion engineering is demonstrated, and some other guideline is indicated. A moving ring reactor is composed mainly of three parts. In the first formation section, a plasma ring is formed and heated up to ignition temperature. The plasma ring of compact torus is transported from the formation section through the next burning section to generate fusion power. Then the plasma ring moves into the last recovery section, and the energy and particles of the plasma ring are recovered. The outline of a moving ring reactor ''Karin-1'' is described. As a candidate material for the first wall, SiC was adopted to reduce the MHD effect and to minimize the interaction with neutrons and charged particles. The thin metal lining was applied to the SiC surface to solve the problem of the compatibility with lithium blanket. Plasma physics, the engineering aspect and the items of research and development are described. (Kako, I.)

Bayesian model averaging and weighted average least squares : Equivariance, stability, and numerical issues

NARCIS (Netherlands)

De Luca, G.; Magnus, J.R.

2011-01-01

In this article, we describe the estimation of linear regression models with uncertainty about the choice of the explanatory variables. We introduce the Stata commands bma and wals, which implement, respectively, the exact Bayesian model-averaging estimator and the weighted-average least-squares

Moving vertices to make drawings plane

NARCIS (Netherlands)

Goaoc, X.; Kratochvil, J.; Okamoto, Y.; Shin, C.S.; Wolff, A.; Hong, S.K.; Nishizeki, T.; Quan, W.

2008-01-01

In John Tantalo’s on-line game Planarity the player is given a non-plane straight-line drawing of a planar graph. The aim is to make the drawing plane as quickly as possible by moving vertices. In this paper we investigate the related problem MinMovedVertices which asks for the minimum number of

Autowaves in moving excitable media

Directory of Open Access Journals (Sweden)

V.A.Davydov

2004-01-01

Full Text Available Within the framework of kinematic theory of autowaves we suggest a method for analytic description of stationary autowave structures appearing at the boundary between the moving and fixed excitable media. The front breakdown phenomenon is predicted for such structures. Autowave refraction and, particulary, one-side "total reflection" at the boundary is considered. The obtained analytical results are confirmed by computer simulations. Prospects of the proposed method for further studies of autowave dynamics in the moving excitable media are discussed.

Infinite games with uncertain moves

Directory of Open Access Journals (Sweden)

Nicholas Asher

2013-03-01

Full Text Available We study infinite two-player games where one of the players is unsure about the set of moves available to the other player. In particular, the set of moves of the other player is a strict superset of what she assumes it to be. We explore what happens to sets in various levels of the Borel hierarchy under such a situation. We show that the sets at every alternate level of the hierarchy jump to the next higher level.

Can math beat gamers in Quantum Moves?

OpenAIRE

Sels, Dries

2017-01-01

Abstract: In a recent work on quantum state preparation, Sørensen and co-workers [Nature (London) 532, 210 (2016)] explore the possibility of using video games to help design quantum control protocols. The authors present a game called Quantum Moves (https://www.scienceathome.org/games/quantum-moves/) in which gamers have to move an atom from A to B by means of optical tweezers. They report that, players succeed where purely numerical optimization fails. Moreover, by harnessing the player str...

Limit theorems for stationary increments Lévy driven moving averages

DEFF Research Database (Denmark)

Basse-O'Connor, Andreas; Lachièze-Rey, Raphaël; Podolskij, Mark

of the kernel function g at 0. First order asymptotic theory essentially comprise three cases: stable convergence towards a certain infinitely divisible distribution, an ergodic type limit theorem and convergence in probability towards an integrated random process. We also prove the second order limit theorem...

Human-animal interactions and safety during dairy cattle handling--Comparing moving cows to milking and hoof trimming.

Science.gov (United States)

Lindahl, C; Pinzke, S; Herlin, A; Keeling, L J

2016-03-01

Cattle handling is a dangerous activity on dairy farms, and cows are a major cause of injuries to livestock handlers. Even if dairy cows are generally tranquil and docile, when situations occur that they perceive or remember as aversive, they may become agitated and hazardous to handle. This study aimed to compare human-animal interactions, cow behavior, and handler safety when moving cows to daily milking and moving cows to more rarely occurring and possibly aversive hoof trimming. These processes were observed on 12 Swedish commercial dairy farms. The study included behavioral observations of handler and cows and cow heart rate recordings, as well as recording frequencies of situations and incidents related to an increased injury risk to the handler. At milking, cows were quite easily moved using few interactions. As expected, the cows showed no behavioral signs of stress, fear, or resistance and their heart rate only rose slightly from the baseline (i.e., the average heart rate during an undisturbed period before handling). Moving cows to hoof trimming involved more forceful and gentle interactions compared with moving cows to milking. Furthermore, the cows showed much higher frequencies of behaviors indicative of aversion and fear (e.g., freezing, balking, and resistance), as well as a higher increase in heart rate. The risk of injury to which handlers were exposed also increased when moving cows to hoof trimming rather than to routine milking. Some interactions (such as forceful tactile interactions with an object and pulling a neck strap or halter) appeared to be related to potentially dangerous incidents where the handler was being kicked, head-butted, or run over by a cow. In conclusion, moving cows to hoof trimming resulted in higher frequencies of behaviors indicating fear, more forceful interactions, and increased injury risks to the handler than moving cows to milking. Improving potentially stressful handling procedures (e.g., by better animal handling

Ready, set, move!

CERN Multimedia

Anaïs Schaeffer

2012-01-01

This year, the CERN Medical Service is launching a new public health campaign. Advertised by the catchphrase “Move! & Eat Better”, the particular aim of the campaign is to encourage people at CERN to take more regular exercise, of whatever kind.   The CERN annual relay race is scheduled on 24 May this year. The CERN Medical Service will officially launch its “Move! & Eat Better” campaign at this popular sporting event. “We shall be on hand on the day of the race to strongly advocate regular physical activity,” explains Rachid Belkheir, one of the Medical Service doctors. "We really want to pitch our campaign and answer any questions people may have. Above all we want to set an example. So we are going to walk the same circuit as the runners to underline to people that they can easily incorporate movement into their daily routine.” An underlying concern has prompted this campaign: during their first few year...

Camouflage, detection and identification of moving targets.

Science.gov (United States)

Hall, Joanna R; Cuthill, Innes C; Baddeley, Roland; Shohet, Adam J; Scott-Samuel, Nicholas E

2013-05-07

Nearly all research on camouflage has investigated its effectiveness for concealing stationary objects. However, animals have to move, and patterns that only work when the subject is static will heavily constrain behaviour. We investigated the effects of different camouflages on the three stages of predation-detection, identification and capture-in a computer-based task with humans. An initial experiment tested seven camouflage strategies on static stimuli. In line with previous literature, background-matching and disruptive patterns were found to be most successful. Experiment 2 showed that if stimuli move, an isolated moving object on a stationary background cannot avoid detection or capture regardless of the type of camouflage. Experiment 3 used an identification task and showed that while camouflage is unable to slow detection or capture, camouflaged targets are harder to identify than uncamouflaged targets when similar background objects are present. The specific details of the camouflage patterns have little impact on this effect. If one has to move, camouflage cannot impede detection; but if one is surrounded by similar targets (e.g. other animals in a herd, or moving background distractors), then camouflage can slow identification. Despite previous assumptions, motion does not entirely 'break' camouflage.

Averaging in spherically symmetric cosmology

International Nuclear Information System (INIS)

Coley, A. A.; Pelavas, N.

2007-01-01

The averaging problem in cosmology is of fundamental importance. When applied to study cosmological evolution, the theory of macroscopic gravity (MG) can be regarded as a long-distance modification of general relativity. In the MG approach to the averaging problem in cosmology, the Einstein field equations on cosmological scales are modified by appropriate gravitational correlation terms. We study the averaging problem within the class of spherically symmetric cosmological models. That is, we shall take the microscopic equations and effect the averaging procedure to determine the precise form of the correlation tensor in this case. In particular, by working in volume-preserving coordinates, we calculate the form of the correlation tensor under some reasonable assumptions on the form for the inhomogeneous gravitational field and matter distribution. We find that the correlation tensor in a Friedmann-Lemaitre-Robertson-Walker (FLRW) background must be of the form of a spatial curvature. Inhomogeneities and spatial averaging, through this spatial curvature correction term, can have a very significant dynamical effect on the dynamics of the Universe and cosmological observations; in particular, we discuss whether spatial averaging might lead to a more conservative explanation of the observed acceleration of the Universe (without the introduction of exotic dark matter fields). We also find that the correlation tensor for a non-FLRW background can be interpreted as the sum of a spatial curvature and an anisotropic fluid. This may lead to interesting effects of averaging on astrophysical scales. We also discuss the results of averaging an inhomogeneous Lemaitre-Tolman-Bondi solution as well as calculations of linear perturbations (that is, the backreaction) in an FLRW background, which support the main conclusions of the analysis

Applying Moving Objects Patterns towards Estimating Future Stocks Direction

Directory of Open Access Journals (Sweden)

Galal Dahab

2016-01-01

Full Text Available Stock is gaining vast popularity as a strategic investment tool not just by investor bankers, but also by the average worker. Large capitals are being traded within the stock market all around the world, making its impact not only macro economically focused, but also greatly valued taking into consideration its direct social impact. As a result, almost 66% of all American citizens are striving in their respective fields every day, trying to come up with better ways to predict and find patterns in stocks that could enhance their estimation and visualization so as to have the opportunity to take better investment decisions. Given the amount of effort that has been put into enhancing stock prediction techniques, there is still a factor that is almost completely neglected when handling stocks. The factor that has been obsolete for so long is in fact the effect of a correlation existing between stocks of the same index or parent company. This paper proposes a distinct approach for studying the correlation between stocks that belong to the same index by modelling stocks as moving objects to be able to track their movements while considering their relationships. Furthermore, it studies one of the movement techniques applied to moving objects to predict stock movement. The results yielded that both the movement technique and correlation coefficient technique are consistent in directions, with minor variations in values. The variations are attributed to the fact that the movement technique takes into consideration the sibling relationship

Designing components using smartMOVE electroactive polymer technology

Science.gov (United States)

Rosenthal, Marcus; Weaber, Chris; Polyakov, Ilya; Zarrabi, Al; Gise, Peter

2008-03-01

Designing components using SmartMOVE TM electroactive polymer technology requires an understanding of the basic operation principles and the necessary design tools for integration into actuator, sensor and energy generation applications. Artificial Muscle, Inc. is collaborating with OEMs to develop customized solutions for their applications using smartMOVE. SmartMOVE is an advanced and elegant way to obtain almost any kind of movement using dielectric elastomer electroactive polymers. Integration of this technology offers the unique capability to create highly precise and customized motion for devices and systems that require actuation. Applications of SmartMOVE include linear actuators for medical, consumer and industrial applications, such as pumps, valves, optical or haptic devices. This paper will present design guidelines for selecting a smartMOVE actuator design to match the stroke, force, power, size, speed, environmental and reliability requirements for a range of applications. Power supply and controller design and selection will also be introduced. An overview of some of the most versatile configuration options will be presented with performance comparisons. A case example will include the selection, optimization, and performance overview of a smartMOVE actuator for the cell phone camera auto-focus and proportional valve applications.

Moving backwards, moving forward: the experiences of older Filipino migrants adjusting to life in New Zealand

OpenAIRE

Montayre, Jed; Neville, Stephen; Holroyd, Eleanor

2017-01-01

ABSTRACT Purpose: To explore the experiences of older Filipino migrants adjusting to living permanently in New Zealand. Method: The qualitative descriptive approach taken in this study involved 17 individual face-to-face interviews of older Filipino migrants in New Zealand. Results: Three main themes emerged from the data. The first theme was ?moving backwards and moving forward?, which described how these older Filipino migrants adjusted to challenges they experienced with migration. The sec...

How to average logarithmic retrievals?

Directory of Open Access Journals (Sweden)

B. Funke

2012-04-01

Full Text Available Calculation of mean trace gas contributions from profiles obtained by retrievals of the logarithm of the abundance rather than retrievals of the abundance itself are prone to biases. By means of a system simulator, biases of linear versus logarithmic averaging were evaluated for both maximum likelihood and maximum a priori retrievals, for various signal to noise ratios and atmospheric variabilities. These biases can easily reach ten percent or more. As a rule of thumb we found for maximum likelihood retrievals that linear averaging better represents the true mean value in cases of large local natural variability and high signal to noise ratios, while for small local natural variability logarithmic averaging often is superior. In the case of maximum a posteriori retrievals, the mean is dominated by the a priori information used in the retrievals and the method of averaging is of minor concern. For larger natural variabilities, the appropriateness of the one or the other method of averaging depends on the particular case because the various biasing mechanisms partly compensate in an unpredictable manner. This complication arises mainly because of the fact that in logarithmic retrievals the weight of the prior information depends on abundance of the gas itself. No simple rule was found on which kind of averaging is superior, and instead of suggesting simple recipes we cannot do much more than to create awareness of the traps related with averaging of mixing ratios obtained from logarithmic retrievals.

Capacity gains of buffer-aided moving relays

KAUST Repository

Zafar, Ammar

2017-03-14

This work investigates the gain due to reduction in path loss by deploying buffer-aided moving relaying. In particular, the increase in gain due to moving relays is studied for dual-hop broadcast channels and the bidirectional relay channel. It is shown that the exploited gains in these channels due to buffer-aided relaying can be enhanced by utilizing the fact that a moving relay can communicate with the terminal closest to it and store the data in the buffer and then forward the data to the intended destination when it comes in close proximity with the destination. Numerical results show that for both the considered channels the achievable rates are increased as compared to the case of stationary relays. Numerical results also show that more significant increase in performance is seen when the relay moves to-and-fro between the source and the relay.

Capacity gains of buffer-aided moving relays

KAUST Repository

Zafar, Ammar; Shaqfeh, Mohammad; Alnuweiri, Hussein; Alouini, Mohamed-Slim

2017-01-01

This work investigates the gain due to reduction in path loss by deploying buffer-aided moving relaying. In particular, the increase in gain due to moving relays is studied for dual-hop broadcast channels and the bidirectional relay channel. It is shown that the exploited gains in these channels due to buffer-aided relaying can be enhanced by utilizing the fact that a moving relay can communicate with the terminal closest to it and store the data in the buffer and then forward the data to the intended destination when it comes in close proximity with the destination. Numerical results show that for both the considered channels the achievable rates are increased as compared to the case of stationary relays. Numerical results also show that more significant increase in performance is seen when the relay moves to-and-fro between the source and the relay.

Previsão do preço dos principais grãos produzidos no Rio Grande do Sul Forcasting the price of major grains produced in Rio Grande do Sul

Directory of Open Access Journals (Sweden)

Analice Marchezan

2010-11-01

Full Text Available Objetivou-se realizar previsões para o ano de 2007, referente ao preço das principais culturas das lavouras temporárias desenvolvidas no Estado do Rio Grande do Sul. Os dados-base da quantidade produzida dos principais grãos analisados foram a média anual, de 1995 a 2006, as previsões de preços, de janeiro de 1995 a dezembro de 2006. Para realização das previsões do preço das culturas de soja, arroz e milho no Estado do Rio Grande do Sul foi utilizada Metodologia Box & Jenkins. Para as culturas destacadas, a metodologia captou vários modelos significativos, mas por meiodos Critérios Penalizadores, AIC, SBC e Erro Quadrado Médio, escolheu-se o melhor modelo para cada série, sendo ideal o modelo ARIMA (0,1,2(0,1,0 para a soja; o modelo SARIMA(1,1,0(1,0,1 para o arroz e o modelo ARIMA (2,1,1(0,1,0 para o milho.The aim of this research was to make predictions for 2007, referring to the price of temporary crops developed in the Rio Grande do Sul state. The data-base of the amout produced of the major grain analyzed were the annual average1995 to 2006 and price produced, from January 1995 to December 2006. To accomplish the forecasts in relation to prices of soybean, rice and sweetcorn in RS state, it was used the Box & Jenkins methodology. To such cultivations, the methodoly showed many significant models, however, through the penalizing criterias, AIC e SBC, in addition to the square average error, it was possible to choose the best model for each serie, being the model ARIMA (0,1,2(0,1,0 to soybean; the model SARIMA (1,1,0(1,0,1 to rice and the model ARIMA (2,1,1(0,1,0 to sweetcorn.

Development of deformable moving lung phantom to simulate respiratory motion in radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Kim, Jina [Department of Biomedical Engineering, College of Medicine, The Catholic University of Korea, Seoul 137-701 (Korea, Republic of); Lee, Youngkyu [Department of Radiation Oncology, Seoul St. Mary' s Hospital, College of Medicine, The Catholic University of Korea, 137-701, Seoul (Korea, Republic of); Shin, Hunjoo [Department of Radiation Oncology, Inchoen St. Mary' s Hospital College of Medicine, The Catholic University of Korea, Incheon 403-720 (Korea, Republic of); Ji, Sanghoon [Field Robot R& D Group, Korea Institute of Industrial Technology, Ansan 426-910 (Korea, Republic of); Park, Sungkwang [Department of Radiation Oncology, Busan Paik Hospital, Inje University, Busan 614-735 (Korea, Republic of); Kim, Jinyoung [Department of Radiation Oncology, Haeundae Paik Hospital, Inje University, Busan 612-896 (Korea, Republic of); Jang, Hongseok [Department of Radiation Oncology, Seoul St. Mary' s Hospital, College of Medicine, The Catholic University of Korea, 137-701, Seoul (Korea, Republic of); Kang, Youngnam, E-mail: ynkang33@gmail.com [Department of Radiation Oncology, Seoul St. Mary' s Hospital, College of Medicine, The Catholic University of Korea, 137-701, Seoul (Korea, Republic of)

2016-07-01

Radiation treatment requires high accuracy to protect healthy organs and destroy the tumor. However, tumors located near the diaphragm constantly move during treatment. Respiration-gated radiotherapy has significant potential for the improvement of the irradiation of tumor sites affected by respiratory motion, such as lung and liver tumors. To measure and minimize the effects of respiratory motion, a realistic deformable phantom is required for use as a gold standard. The purpose of this study was to develop and study the characteristics of a deformable moving lung (DML) phantom, such as simulation, tissue equivalence, and rate of deformation. The rate of change of the lung volume, target deformation, and respiratory signals were measured in this study; they were accurately measured using a realistic deformable phantom. The measured volume difference was 31%, which closely corresponds to the average difference in human respiration, and the target movement was − 30 to + 32 mm. The measured signals accurately described human respiratory signals. This DML phantom would be useful for the estimation of deformable image registration and in respiration-gated radiotherapy. This study shows that the developed DML phantom can exactly simulate the patient's respiratory signal and it acts as a deformable 4-dimensional simulation of a patient's lung with sufficient volume change.

Development of deformable moving lung phantom to simulate respiratory motion in radiotherapy

International Nuclear Information System (INIS)

Kim, Jina; Lee, Youngkyu; Shin, Hunjoo; Ji, Sanghoon; Park, Sungkwang; Kim, Jinyoung; Jang, Hongseok; Kang, Youngnam

2016-01-01

Radiation treatment requires high accuracy to protect healthy organs and destroy the tumor. However, tumors located near the diaphragm constantly move during treatment. Respiration-gated radiotherapy has significant potential for the improvement of the irradiation of tumor sites affected by respiratory motion, such as lung and liver tumors. To measure and minimize the effects of respiratory motion, a realistic deformable phantom is required for use as a gold standard. The purpose of this study was to develop and study the characteristics of a deformable moving lung (DML) phantom, such as simulation, tissue equivalence, and rate of deformation. The rate of change of the lung volume, target deformation, and respiratory signals were measured in this study; they were accurately measured using a realistic deformable phantom. The measured volume difference was 31%, which closely corresponds to the average difference in human respiration, and the target movement was − 30 to + 32 mm. The measured signals accurately described human respiratory signals. This DML phantom would be useful for the estimation of deformable image registration and in respiration-gated radiotherapy. This study shows that the developed DML phantom can exactly simulate the patient's respiratory signal and it acts as a deformable 4-dimensional simulation of a patient's lung with sufficient volume change.

Modeling and simulation of dust behaviors behind a moving vehicle

Science.gov (United States)

Wang, Jingfang

Simulation of physically realistic complex dust behaviors is a difficult and attractive problem in computer graphics. A fast, interactive and visually convincing model of dust behaviors behind moving vehicles is very useful in computer simulation, training, education, art, advertising, and entertainment. In my dissertation, an experimental interactive system has been implemented for the simulation of dust behaviors behind moving vehicles. The system includes physically-based models, particle systems, rendering engines and graphical user interface (GUI). I have employed several vehicle models including tanks, cars, and jeeps to test and simulate in different scenarios and conditions. Calm weather, winding condition, vehicle turning left or right, and vehicle simulation controlled by users from the GUI are all included. I have also tested the factors which play against the physical behaviors and graphics appearances of the dust particles through GUI or off-line scripts. The simulations are done on a Silicon Graphics Octane station. The animation of dust behaviors is achieved by physically-based modeling and simulation. The flow around a moving vehicle is modeled using computational fluid dynamics (CFD) techniques. I implement a primitive variable and pressure-correction approach to solve the three dimensional incompressible Navier Stokes equations in a volume covering the moving vehicle. An alternating- direction implicit (ADI) method is used for the solution of the momentum equations, with a successive-over- relaxation (SOR) method for the solution of the Poisson pressure equation. Boundary conditions are defined and simplified according to their dynamic properties. The dust particle dynamics is modeled using particle systems, statistics, and procedure modeling techniques. Graphics and real-time simulation techniques, such as dynamics synchronization, motion blur, blending, and clipping have been employed in the rendering to achieve realistic appearing dust

Sense of moving

DEFF Research Database (Denmark)

Christensen, Mark Schram; Grünbaum, Thor

2017-01-01

In this chapter, we assume the existence of a sense of “movement activity” that arises when a person actively moves a body part. This sense is usually supposed to be part of sense of agency (SoA). The purpose of the chapter is to determine whether the already existing experimental paradigms can...

Scattering characteristics of relativistically moving concentrically layered spheres

Science.gov (United States)

Garner, Timothy J.; Lakhtakia, Akhlesh; Breakall, James K.; Bohren, Craig F.

2018-02-01

The energy extinction cross section of a concentrically layered sphere varies with velocity as the Doppler shift moves the spectral content of the incident signal in the sphere's co-moving inertial reference frame toward or away from resonances of the sphere. Computations for hollow gold nanospheres show that the energy extinction cross section is high when the Doppler shift moves the incident signal's spectral content in the co-moving frame near the wavelength of the sphere's localized surface plasmon resonance. The energy extinction cross section of a three-layer sphere consisting of an olivine-silicate core surrounded by a porous and a magnetite layer, which is used to explain extinction caused by interstellar dust, also depends strongly on velocity. For this sphere, computations show that the energy extinction cross section is high when the Doppler shift moves the spectral content of the incident signal near either of olivine-silicate's two localized surface phonon resonances at 9.7 μm and 18 μm.

Lattice Boltzmann simulation of behaviour of particles moving in blood vessels under the rolling massage

International Nuclear Information System (INIS)

Hou-Hui, Yi; Cai-Feng, Wang; Xiao-Feng, Yang; Hua-Bing, Li

2009-01-01

The rolling massage is one of the most important manipulations in Chinese massage, which is expected to eliminate many diseases. Here, the effect of the rolling massage on a pair of particles moving in blood vessels under rolling massage manipulation is studied by the lattice Boltzmann simulation. The simulated results show that the motion of each particle is considerably modified by the rolling massage, and it depends on the relative rolling velocity, the rolling depth, and the distance between particle position and rolling position. Both particles' translational average velocities increase almost linearly as the rolling velocity increases, and obey the same law. The increment of the average relative angular velocity for the leading particle is smaller than that of the trailing one. The result is helpful for understanding the mechanism of the massage and to further develop the rolling techniques. (classical areas of phenomenology)

Why superconducting vortices follow to moving hot sport?

Science.gov (United States)

Sergeev, Andrei; Michael, Reizer

Recent experiments reported in Nature Comm. 7, 12801, 2016 show that superconducting vortices follow to the moving hot sport created by a focused laser beam, i.e. vortices move from the cold area to the moving hot area. This behavior is opposite to the vortex motion observed in numerous measurements of the vortex Nernst effect, where vortices always move against the temperature gradient. Taking into account that superconducting magnetization currents do not transfer entropy, we analyze the balance of forces acting on a vortex in stationary and dynamic temperature gradients. We show that the dynamic measurements may be described by a single vortex approximation, while in stationary measurements interaction between vortices is critical. Supported by NRC.

On Averaging Rotations

DEFF Research Database (Denmark)

Gramkow, Claus

2001-01-01

In this paper two common approaches to averaging rotations are compared to a more advanced approach based on a Riemannian metric. Very often the barycenter of the quaternions or matrices that represent the rotations are used as an estimate of the mean. These methods neglect that rotations belong ...... approximations to the Riemannian metric, and that the subsequent corrections are inherent in the least squares estimation.......In this paper two common approaches to averaging rotations are compared to a more advanced approach based on a Riemannian metric. Very often the barycenter of the quaternions or matrices that represent the rotations are used as an estimate of the mean. These methods neglect that rotations belong...

Flows around a moving flat plate simulated by the method of cellular automata. Seru outoman ho ni yoru ido heiban mawari no nagare

Energy Technology Data Exchange (ETDEWEB)

Tsutahara, M; Tomiyama, A; Kimura, T; Murata, H [Kobe University, Kobe (Japan). Faculty of Engineering

1993-08-25

In order to analyze the field of flow containing a moving boundary by the method of cellular automaton, the method of giving the boundary conditions in the case where a wall is moving at a constant velocity in the normal direction was examined. This method is used to simulate the movement of continuous fluid by statistically treating the movement of many discrete particles which repeat translation and collision. The collision law of particles at grid points is formulated so as to conserve mass(number of particles) and momentum for the purpose of satisfying the governing equation of flow. The object is the flow in the case where a flat plate moves in the normal direction inside the fluid enclosed by rectangular walls and the plate was assumed that it is first in a standing condition, then starts to move from left to right at a speed of V and stops in front of the right wall. Three boundary conditions, surrounding wall, plate in the standing condition and moving plate, were considered. Flow rates were calculated concerning the translation and collision and each divided mean-field-approximation region(space having a magnitude of capable of averaging operation of particles). Effectiveness of proposed boundary conditions was confirmed by a visualization experiment. 3 refs., 14 figs.

Being Moved: Linguistic Representation and Conceptual Structure

Directory of Open Access Journals (Sweden)

Milena eKuehnast

2014-11-01

Full Text Available This study explored the organisation of the semantic field and the conceptual structure of moving experiences by investigating German-language expressions referring to the emotional state of being moved. We used present and past participles of eight psychological verbs as primes in a free word-association task, as these grammatical forms place their conceptual focus on the eliciting situation and on the felt emotional state, respectively. By applying a taxonomy of basic knowledge types and computing the Cognitive Salience Index, we identified joy and sadness as key emotional ingredients of being moved, and significant life events and art experiences as main elicitors of this emotional state. Metric multidimensional scaling analyses of the semantic field revealed that the core terms designate a cluster of emotional states characterised by low degrees of arousal and slightly positive valence, the latter due to a nearly balanced representation of positive and negative elements in the conceptual structure of being moved.

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

Science.gov (United States)

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.

Simultaneous multifractal decompositions for the spectra of local entropies and ergodic averages

International Nuclear Information System (INIS)

Meson, Alejandro; Vericat, Fernando

2009-01-01

We consider different multifractal decompositions of the form K α i ={x:g i (x)=α i },i=1,2,...,d, and we study the dimension spectrum corresponding to the multiparameter decomposition K α = intersection i=1 d K α i ,α=(α 1 ,...,α d ). Then for an homeomorphism f : X → X and potentials φ, ψ : X → R we analyze the decompositions K α + ={x:lim n→∞ 1/n (S n + (φ))(x)=α},K β - ={x:lim n→∞ 1/n (S n - (ψ))(x)=β}, where 1/n (S n + (φ)),1/n (S n - (ψ)) are ergodic averages using forward and backward orbits of f respectively. We must emphasize that the analysis, in any case, is done without requiring conditions of hyperbolicity for the dynamical system or Hoelder continuity on the potentials. We illustrate with an application to galactic dynamics: a set of stars (which do not interact among them) moving in a galactic field.

Detection of Moving Targets Using Soliton Resonance Effect

Science.gov (United States)

Kulikov, Igor K.; Zak, Michail

2013-01-01

The objective of this research was to develop a fundamentally new method for detecting hidden moving targets within noisy and cluttered data-streams using a novel "soliton resonance" effect in nonlinear dynamical systems. The technique uses an inhomogeneous Korteweg de Vries (KdV) equation containing moving-target information. Solution of the KdV equation will describe a soliton propagating with the same kinematic characteristics as the target. The approach uses the time-dependent data stream obtained with a sensor in form of the "forcing function," which is incorporated in an inhomogeneous KdV equation. When a hidden moving target (which in many ways resembles a soliton) encounters the natural "probe" soliton solution of the KdV equation, a strong resonance phenomenon results that makes the location and motion of the target apparent. Soliton resonance method will amplify the moving target signal, suppressing the noise. The method will be a very effective tool for locating and identifying diverse, highly dynamic targets with ill-defined characteristics in a noisy environment. The soliton resonance method for the detection of moving targets was developed in one and two dimensions. Computer simulations proved that the method could be used for detection of singe point-like targets moving with constant velocities and accelerations in 1D and along straight lines or curved trajectories in 2D. The method also allows estimation of the kinematic characteristics of moving targets, and reconstruction of target trajectories in 2D. The method could be very effective for target detection in the presence of clutter and for the case of target obscurations.

Moving backwards, moving forward: the experiences of older Filipino migrants adjusting to life in New Zealand.

Science.gov (United States)

Montayre, Jed; Neville, Stephen; Holroyd, Eleanor

2017-12-01

To explore the experiences of older Filipino migrants adjusting to living permanently in New Zealand. The qualitative descriptive approach taken in this study involved 17 individual face-to-face interviews of older Filipino migrants in New Zealand. Three main themes emerged from the data. The first theme was "moving backwards and moving forward", which described how these older Filipino migrants adjusted to challenges they experienced with migration. The second theme was "engaging with health services" and presented challenges relating to the New Zealand healthcare system, including a lack of knowledge of the nature of health services, language barriers, and differences in cultural views. The third theme, "new-found home", highlighted establishing a Filipino identity in New Zealand and adjusting to the challenges of relocation. Adjustment to life in New Zealand for these older Filipino migrants meant starting over again by building new values through learning the basics and then moving forward from there.

Lagrangian averaging with geodesic mean.

Science.gov (United States)

Oliver, Marcel

2017-11-01

This paper revisits the derivation of the Lagrangian averaged Euler (LAE), or Euler- α equations in the light of an intrinsic definition of the averaged flow map as the geodesic mean on the volume-preserving diffeomorphism group. Under the additional assumption that first-order fluctuations are statistically isotropic and transported by the mean flow as a vector field, averaging of the kinetic energy Lagrangian of an ideal fluid yields the LAE Lagrangian. The derivation presented here assumes a Euclidean spatial domain without boundaries.

Online Risk Prediction for Indoor Moving Objects

DEFF Research Database (Denmark)

Ahmed, Tanvir; Pedersen, Torben Bach; Calders, Toon

2016-01-01

Technologies such as RFID and Bluetooth have received considerable attention for tracking indoor moving objects. In a time-critical indoor tracking scenario such as airport baggage handling, a bag has to move through a sequence of locations until it is loaded into the aircraft. Inefficiency or in...... reduce the operation cost....

Research Article Special Issue

African Journals Online (AJOL)

pc

2018-02-24

Feb 24, 2018 ... Dengue fever is one of the pressing public-health problems in ... historical data of both regions to identify the best model to represent the cases and the .... Ribeirao Preto, Sao Paulo State, Brazil, using a SARIMA model.

So, You Want to Move out?!--An Awareness Program of the Real Costs of Moving Away from Home

Science.gov (United States)

Hines, Steven L.; Hansen, Lyle; Falen, Christi

2011-01-01

The So, You Want To Move Out?! program was developed to help teens explore the financial realities of moving away from home. This 3-day camp program allows youth the opportunity to interview for a job, work, earn a paycheck, and pay financial obligations. After paying expenses and trying to put some money away in savings, the participants begin to…

Maintenance of order in a moving strong condensate

International Nuclear Information System (INIS)

Whitehouse, Justin; Costa, André; Blythe, Richard A; Evans, Martin R

2014-01-01

We investigate the conditions under which a moving condensate may exist in a driven mass transport system. Our paradigm is a minimal mass transport model in which n − 1 particles move simultaneously from a site containing n > 1 particles to the neighbouring site in a preferred direction. In the spirit of a zero-range process the rate u(n) of this move depends only on the occupation of the departure site. We study a hopping rate u(n) = 1 + b/n α numerically and find a moving strong condensate phase for b > b c (α) for all α > 0. This phase is characterised by a condensate that moves through the system and comprises a fraction of the system's mass that tends to unity. The mass lost by the condensate as it moves is constantly replenished from the trailing tail of low occupancy sites that collectively comprise a vanishing fraction of the mass. We formulate an approximate analytical treatment of the model that allows a reasonable estimate of b c (α) to be obtained. We show numerically (for α = 1) that the transition is of mixed order, exhibiting a discontinuity in the order parameter as well as a diverging length scale as b↘b c . (paper)

Developing a dengue early warning system using time series model: Case study in Tainan, Taiwan

Science.gov (United States)

Chen, Xiao-Wei; Jan, Chyan-Deng; Wang, Ji-Shang

2017-04-01

Dengue fever (DF) is a climate-sensitive disease that has been emerging in southern regions of Taiwan over the past few decades, causing a significant health burden to affected areas. This study aims to propose a predictive model to implement an early warning system so as to enhance dengue surveillance and control in Tainan, Taiwan. The Seasonal Autoregressive Integrated Moving Average (SARIMA) model was used herein to forecast dengue cases. Temporal correlation between dengue incidences and climate variables were examined by Pearson correlation analysis and Cross-correlation tests in order to identify key determinants to be included as predictors. The dengue surveillance data between 2000 and 2009, as well as their respective climate variables were then used as inputs for the model. We validated the model by forecasting the number of dengue cases expected to occur each week between January 1, 2010 and December 31, 2015. In addition, we analyzed historical dengue trends and found that 25 cases occurring in one week was a trigger point that often led to a dengue outbreak. This threshold point was combined with the season-based framework put forth by the World Health Organization to create a more accurate epidemic threshold for a Tainan-specific warning system. A Seasonal ARIMA model with the general form: (1,0,5)(1,1,1)52 is identified as the most appropriate model based on lowest AIC, and was proven significant in the prediction of observed dengue cases. Based on the correlation coefficient, Lag-11 maximum 1-hr rainfall (r=0.319, Pclimate variables. Comparing the four multivariate models(i.e.1, 4, 9 and 13 weeks ahead), we found that including the climate variables improves the prediction RMSE as high as 3.24%, 10.39%, 17.96%, 21.81% respectively, in contrast to univariate models. Furthermore, the ability of the four multivariate models to determine whether the epidemic threshold would be exceeded in any given week during the forecasting period of 2010-2015 was

Occupational injuries and sick leaves in household moving works.

Science.gov (United States)

Hwan Park, Myoung; Jeong, Byung Yong

2017-09-01

This study is concerned with household moving works and the characteristics of occupational injuries and sick leaves in each step of the moving process. Accident data for 392 occupational accidents were categorized by the moving processes in which the accidents occurred, and possible incidents and sick leaves were assessed for each moving process and hazard factor. Accidents occurring during specific moving processes showed different characteristics depending on the type of accident and agency of accidents. The most critical form in the level of risk management was falls from a height in the 'lifting by ladder truck' process. Incidents ranked as a 'High' level of risk management were in the forms of slips, being struck by objects and musculoskeletal disorders in the 'manual materials handling' process. Also, falls in 'loading/unloading', being struck by objects during 'lifting by ladder truck' and driving accidents in the process of 'transport' were ranked 'High'. The findings of this study can be used to develop more effective accident prevention policy reflecting different circumstances and conditions to reduce occupational accidents in household moving works.

25 CFR 700.157 - Actual reasonable moving and related expenses-nonresidential moves.

Science.gov (United States)

2010-04-01

... of § 700.151(c) a certified eligible business, farm operation or nonprofit organization is entitled...-moves his business, farm operation, or nonprofit organization, the Commission may approve a payment for... and modifications necessary to adapt such property to the replacement structure or to the utilities or...

Theses "Discussion" Sections: A Structural Move Analysis

Science.gov (United States)

Nodoushan, Mohammad Ali Salmani; Khakbaz, Nafiseh

2011-01-01

The current study aimed at finding the probable differences between the move structure of Iranian MA graduates' thesis discussion subgenres and those of their non-Iranian counterparts, on the one hand, and those of journal paper authors, on the other. It also aimed at identifying the moves that are considered obligatory, conventional, or optional…

Indexing Moving Points

DEFF Research Database (Denmark)

Agarwal, Pankaj K.; Arge, Lars Allan; Erickson, Jeff

2003-01-01

We propose three indexing schemes for storing a set S of N points in the plane, each moving along a linear trajectory, so that any query of the following form can be answered quickly: Given a rectangle R and a real value t, report all K points of S that lie inside R at time t. We first present an...

Moving House for Education in the Pre-School Years

Science.gov (United States)

Hansen, Kirstine

2014-01-01

This paper uses data from the Millennium Cohort Study (MCS) to examine house moves that take place in the pre-school years, focusing on families who move for the education of their children. We present results showing that education- related house moves do indeed occur in the pre-school years with particular types of parents making these…

A-Track: Detecting Moving Objects in FITS images

Science.gov (United States)

Atay, T.; Kaplan, M.; Kilic, Y.; Karapinar, N.

2017-04-01

A-Track is a fast, open-source, cross-platform pipeline for detecting moving objects (asteroids and comets) in sequential telescope images in FITS format. The moving objects are detected using a modified line detection algorithm.

Distributed Measurement Data Gathering about Moving Objects

Directory of Open Access Journals (Sweden)

Ivan Kholod

2017-01-01

Full Text Available This paper describes approaches to gathering measurement data about moving objects in networks with low bandwidth. The first approach uses Fog computing conception and suggests moving assessing the quality of the measurement data into measuring points. The second approach uses prediction of telemetry quality by mining models. In addition, the paper presents implementation of these approaches based on actor model. As a result, it became possible not only to load balancing among edge and cloud nodes, but also to significantly reduce the network traffic, which in turn brings the possibility of decreasing the requirements for communication channels bandwidth and of using wireless networks for gathering measurement data about moving objects.

Spacetime averaging of exotic singularity universes

International Nuclear Information System (INIS)

Dabrowski, Mariusz P.

2011-01-01

Taking a spacetime average as a measure of the strength of singularities we show that big-rips (type I) are stronger than big-bangs. The former have infinite spacetime averages while the latter have them equal to zero. The sudden future singularities (type II) and w-singularities (type V) have finite spacetime averages. The finite scale factor (type III) singularities for some values of the parameters may have an infinite average and in that sense they may be considered stronger than big-bangs.

How to Move in a Jostling Crowd

Indian Academy of Sciences (India)

For people living in big cities it is an ordeal to walk in a bus stand or a railway station. They get stuck helplessly in a crowd. They are simply pushed around and all their efforts to move forward appear futile. Only the most energetic can wade through the constantly moving sea of people. How about the weaker ones?

Controllability for a Wave Equation with Moving Boundary

Directory of Open Access Journals (Sweden)

Lizhi Cui

2014-01-01

Full Text Available We investigate the controllability for a one-dimensional wave equation in domains with moving boundary. This model characterizes small vibrations of a stretched elastic string when one of the two endpoints varies. When the speed of the moving endpoint is less than 1-1/e, by Hilbert uniqueness method, sidewise energy estimates method, and multiplier method, we get partial Dirichlet boundary controllability. Moreover, we will give a sharper estimate on controllability time that only depends on the speed of the moving endpoint.

Clustering Moving Objects Using Segments Slopes

OpenAIRE

Mohamed E. El-Sharkawi; Hoda M. O. Mokhtar; Omnia Ossama

2011-01-01

Given a set of moving object trajectories, we show how to cluster them using k-meansclustering approach. Our proposed clustering algorithm is competitive with the k-means clusteringbecause it specifies the value of “k” based on the segment’s slope of the moving object trajectories. Theadvantage of this approach is that it overcomes the known drawbacks of the k-means algorithm, namely,the dependence on the number of clusters (k), and the dependence on the initial choice of the clusters’centroi...

Age differences in big five behavior averages and variabilities across the adult life span: moving beyond retrospective, global summary accounts of personality.

Science.gov (United States)

Noftle, Erik E; Fleeson, William

2010-03-01

In 3 intensive cross-sectional studies, age differences in behavior averages and variabilities were examined. Three questions were posed: Does variability differ among age groups? Does the sizable variability in young adulthood persist throughout the life span? Do past conclusions about trait development, based on trait questionnaires, hold up when actual behavior is examined? Three groups participated: young adults (18-23 years), middle-aged adults (35-55 years), and older adults (65-81 years). In 2 experience-sampling studies, participants reported their current behavior multiple times per day for 1- or 2-week spans. In a 3rd study, participants interacted in standardized laboratory activities on 8 occasions. First, results revealed a sizable amount of intraindividual variability in behavior for all adult groups, with average within-person standard deviations ranging from about half a point to well over 1 point on 6-point scales. Second, older adults were most variable in Openness, whereas young adults were most variable in Agreeableness and Emotional Stability. Third, most specific patterns of maturation-related age differences in actual behavior were more greatly pronounced and differently patterned than those revealed by the trait questionnaire method. When participants interacted in standardized situations, personality differences between young adults and middle-aged adults were larger, and older adults exhibited a more positive personality profile than they exhibited in their everyday lives.

Moving as a gift: relocation in older adulthood.

Science.gov (United States)

Perry, Tam E

2014-12-01

While discussions of accessibility, mobility and activities of daily living frame relocation studies, in older adulthood, the paper explores the emotional motivation of gift giving as a rationale for moving. This ethnographic study investigates the processes of household disbandment and decision-making of older adults in the Midwestern United States relocating in post-Global Financial Crisis contexts. In this study, relationships are created and sustained through the process of moving, linking older adults (n=81), their kin (n=49), and professionals (n=46) in the Midwestern United States. Using Marcel Mauss' The Gift (1925/1990) as a theoretical lens, relocation in older adulthood is conceptualized as a gift in two ways: to one's partner, and one's kin. Partners may consider gift-giving in terms of the act of moving to appease and honor their partner. Kin who were not moving themselves were also recipients of the gift of moving. These gifts enchain others in relationships of reciprocity. However these gifts, like all gifts, are not without costs or danger, so this paper examines some of the challenges that emerge along with gift-giving. Copyright © 2014 Elsevier Inc. All rights reserved.

Moving across boundaries: migration in South Africa, 1950-2000.

Science.gov (United States)

Reed, Holly E

2013-02-01

Existing knowledge about historical patterns of black internal migration in South Africa is incomplete, primarily because of the lack of good life course studies as well as the apartheid government's suppression and censoring of data. This article provides a comprehensive picture of historical internal migration patterns with an analysis of a unique individual retrospective life history data set. This sample of the black population, collected in 2000, is the only known nationally representative life history data for South Africa; it includes all residential moves for each individual during his/her lifetime. Various mobility outcomes are analyzed: moves within/across provinces, moves within/across rural and urban areas, forced moves, moves with a nuclear family, and individual moves. The results indicate that migration significantly increased among black South Africans during the last half of the twentieth century, and that this increase began before the Pass Laws were repealed in 1986 and well before the official end of apartheid in 1991 or the first free election in 1994. The timing of this increase in migration rates suggests that migration in defiance of the Pass Laws (albeit a dangerous and desperate proposition) was a way of life for many black South Africans.

Moving Manifolds in Electromagnetic Fields

Directory of Open Access Journals (Sweden)

David V. Svintradze

2017-08-01

Full Text Available We propose dynamic non-linear equations for moving surfaces in an electromagnetic field. The field is induced by a material body with a boundary of the surface. Correspondingly the potential energy, set by the field at the boundary can be written as an addition of four-potential times four-current to a contraction of the electromagnetic tensor. Proper application of the minimal action principle to the system Lagrangian yields dynamic non-linear equations for moving three dimensional manifolds in electromagnetic fields. The equations in different conditions simplify to Maxwell equations for massless three surfaces, to Euler equations for a dynamic fluid, to magneto-hydrodynamic equations and to the Poisson-Boltzmann equation.

Moving core beam energy absorber and converter

Science.gov (United States)

Degtiarenko, Pavel V.

2012-12-18

A method and apparatus for the prevention of overheating of laser or particle beam impact zones through the use of a moving-in-the-coolant-flow arrangement for the energy absorbing core of the device. Moving of the core spreads the energy deposition in it in 1, 2, or 3 dimensions, thus increasing the effective cooling area of the device.

Energy flow around a moving dislocation

International Nuclear Information System (INIS)

Koizumi, H; Kirchner, H O K

2009-01-01

A dislocation moving in a lattice emits lattice waves. We study the energy flow accompanying the lattice wave emission in a molecular dynamics situation. About two thirds of the static free energy are emitted as lattice waves from the moving dislocation. Work done by the region around the dislocation helps to initiate the motion from the unstable equilibrium state under a small applied stress, or to compensate the energy emitted as lattice waves when the dislocation makes a long distance motion under a larger stress.

Sedimentological regimes for turbidity currents: Depth-averaged theory

Science.gov (United States)

Halsey, Thomas C.; Kumar, Amit; Perillo, Mauricio M.

2017-07-01

Turbidity currents are one of the most significant means by which sediment is moved from the continents into the deep ocean; their properties are interesting both as elements of the global sediment cycle and due to their role in contributing to the formation of deep water oil and gas reservoirs. One of the simplest models of the dynamics of turbidity current flow was introduced three decades ago, and is based on depth-averaging of the fluid mechanical equations governing the turbulent gravity-driven flow of relatively dilute turbidity currents. We examine the sedimentological regimes of a simplified version of this model, focusing on the role of the Richardson number Ri [dimensionless inertia] and Rouse number Ro [dimensionless sedimentation velocity] in determining whether a current is net depositional or net erosional. We find that for large Rouse numbers, the currents are strongly net depositional due to the disappearance of local equilibria between erosion and deposition. At lower Rouse numbers, the Richardson number also plays a role in determining the degree of erosion versus deposition. The currents become more erosive at lower values of the product Ro × Ri, due to the effect of clear water entrainment. At higher values of this product, the turbulence becomes insufficient to maintain the sediment in suspension, as first pointed out by Knapp and Bagnold. We speculate on the potential for two-layer solutions in this insufficiently turbulent regime, which would comprise substantial bedload flow with an overlying turbidity current.

Libraries on the MOVE.

Science.gov (United States)

Edgar, Jim; And Others

1986-01-01

Presents papers from Illinois State Library and Shawnee Library System's "Libraries on the MOVE" conference focusing on how libraries can impact economic/cultural climate of an area. Topics addressed included information services of rural libraries; marketing; rural library development; library law; information access; interagency…

Aboard the "Moving School."

Science.gov (United States)

Ainscow, Mel; Hopkins, David

1992-01-01

In many countries, education legislation embodies contradictory pressures for centralization and decentralization. In the United Kingdom, there is growing government control over policy and direction of schools; schools are also being given more responsibility for resource management. "Moving" schools within Improving the Quality of…

Heterodyne laser Doppler distance sensor with phase coding measuring stationary as well as laterally and axially moving objects

International Nuclear Information System (INIS)

Pfister, T; Günther, P; Nöthen, M; Czarske, J

2010-01-01

Both in production engineering and process control, multidirectional displacements, deformations and vibrations of moving or rotating components have to be measured dynamically, contactlessly and with high precision. Optical sensors would be predestined for this task, but their measurement rate is often fundamentally limited. Furthermore, almost all conventional sensors measure only one measurand, i.e. either out-of-plane or in-plane distance or velocity. To solve this problem, we present a novel phase coded heterodyne laser Doppler distance sensor (PH-LDDS), which is able to determine out-of-plane (axial) position and in-plane (lateral) velocity of rough solid-state objects simultaneously and independently with a single sensor. Due to the applied heterodyne technique, stationary or purely axially moving objects can also be measured. In addition, it is shown theoretically as well as experimentally that this sensor offers concurrently high temporal resolution and high position resolution since its position uncertainty is in principle independent of the lateral object velocity in contrast to conventional distance sensors. This is a unique feature of the PH-LDDS enabling precise and dynamic position and shape measurements also of fast moving objects. With an optimized sensor setup, an average position resolution of 240 nm was obtained

Partner (dis)agreement on moving desires and the subsequent moving behaviour of couples

NARCIS (Netherlands)

Coulter, R.; Van Ham, M.; Feijten, P.

2011-01-01

Most studies of residential mobility decision-making focus on the housing and neighbourhood satisfaction and pre-move thoughts of individuals. This implicitly assumes that individual evaluations represent the wider household unit. However, if partners in a couple do not share evaluations of dwelling

Effectively Indexing Uncertain Moving Objects for Predictive Queries

DEFF Research Database (Denmark)

Zhang, Meihui; Chen, Su; Jensen, Christian Søndergaard

2009-01-01

in more complex and stochastic ways. This paper investigates the possibility of a marriage between moving-object indexing and probabilistic object modelling. Given the distributions of the current locations and velocities of moving objects, we devise an efficient inference method for the prediction...

Does the Brain Extrapolate the Position of a Transient Moving Target?

Science.gov (United States)

Quinet, Julie; Goffart, Laurent

2015-08-26

When an object moves in the visual field, its motion evokes a streak of activity on the retina and the incoming retinal signals lead to robust oculomotor commands because corrections are observed if the trajectory of the interceptive saccade is perturbed by a microstimulation in the superior colliculus. The present study complements a previous perturbation study by investigating, in the head-restrained monkey, the generation of saccades toward a transient moving target (100-200 ms). We tested whether the saccades land on the average of antecedent target positions or beyond the location where the target disappeared. Using target motions with different speed profiles, we also examined the sensitivity of the process that converts time-varying retinal signals into saccadic oculomotor commands. The results show that, for identical overall target displacements on the visual display, saccades toward a faster target land beyond the endpoint of saccades toward a target moving slower. The rate of change in speed matters in the visuomotor transformation. Indeed, in response to identical overall target displacements and durations, the saccades have smaller amplitude when they are made in response to an accelerating target than to a decelerating one. Moreover, the motion-related signals have different weights depending upon their timing relative to the target onset: early signals are more influential in the specification of saccade amplitude than later signals. We discuss the "predictive" properties of the visuo-saccadic system and the nature of this location where the saccades land, after providing some critical comments to the "hic-et-nunc" hypothesis (Fleuriet and Goffart, 2012). Complementing the work of Fleuriet and Goffart (2012), this study is a contribution to the more general scientific research aimed at understanding how ongoing action is dynamically and adaptively adjusted to the current spatiotemporal aspects of its goal. Using the saccadic eye movement as a probe

Short-term forecasting of meteorological time series using Nonparametric Functional Data Analysis (NPFDA)

Science.gov (United States)

Curceac, S.; Ternynck, C.; Ouarda, T.

2015-12-01

Over the past decades, a substantial amount of research has been conducted to model and forecast climatic variables. In this study, Nonparametric Functional Data Analysis (NPFDA) methods are applied to forecast air temperature and wind speed time series in Abu Dhabi, UAE. The dataset consists of hourly measurements recorded for a period of 29 years, 1982-2010. The novelty of the Functional Data Analysis approach is in expressing the data as curves. In the present work, the focus is on daily forecasting and the functional observations (curves) express the daily measurements of the above mentioned variables. We apply a non-linear regression model with a functional non-parametric kernel estimator. The computation of the estimator is performed using an asymmetrical quadratic kernel function for local weighting based on the bandwidth obtained by a cross validation procedure. The proximities between functional objects are calculated by families of semi-metrics based on derivatives and Functional Principal Component Analysis (FPCA). Additionally, functional conditional mode and functional conditional median estimators are applied and the advantages of combining their results are analysed. A different approach employs a SARIMA model selected according to the minimum Akaike (AIC) and Bayessian (BIC) Information Criteria and based on the residuals of the model. The performance of the models is assessed by calculating error indices such as the root mean square error (RMSE), relative RMSE, BIAS and relative BIAS. The results indicate that the NPFDA models provide more accurate forecasts than the SARIMA models. Key words: Nonparametric functional data analysis, SARIMA, time series forecast, air temperature, wind speed

Moving Another Big Desk.

Science.gov (United States)

Fawcett, Gay

1996-01-01

New ways of thinking about leadership require that leaders move their big desks and establish environments that encourage trust and open communication. Educational leaders must trust their colleagues to make wise choices. When teachers are treated democratically as leaders, classrooms will also become democratic learning organizations. (SM)

ELECTROMAGNETIC APPARATUS FOR MOVING A ROD

Science.gov (United States)

Young, J.N.

1958-04-22

An electromagnetic apparatus for moving a rod-like member in small steps in either direction is described. The invention has particular application in the reactor field where the reactor control rods must be moved only a small distance and where the use of mechanical couplings is impractical due to the high- pressure seals required. A neutron-absorbing rod is mounted in a housing with gripping uaits that engage the rod, and coils for magnetizing the gripping units to make them grip, shift, and release the rod are located outside the housing.

Operational overhead of moving to higher energies

CERN Document Server

Lamont, M

2011-01-01

The operational overheads of moving above 3.5 TeV are examined. The costs of performing such a move at the start, or during, the 2011 run are evaluated. The impact of operation with beams above 3.5 TeV on machine protection systems is briefly reviewed, and any potential limitations are enumerated. Finally the possible benefits of increasing the beam energy on the luminosity are discussed.

High-throughput machining using a high-average power ultrashort pulse laser and high-speed polygon scanner

Science.gov (United States)

Schille, Joerg; Schneider, Lutz; Streek, André; Kloetzer, Sascha; Loeschner, Udo

2016-09-01

High-throughput ultrashort pulse laser machining is investigated on various industrial grade metals (aluminum, copper, and stainless steel) and Al2O3 ceramic at unprecedented processing speeds. This is achieved by using a high-average power picosecond laser in conjunction with a unique, in-house developed polygon mirror-based biaxial scanning system. Therefore, different concepts of polygon scanners are engineered and tested to find the best architecture for high-speed and precision laser beam scanning. In order to identify the optimum conditions for efficient processing when using high-average laser powers, the depths of cavities made in the samples by varying the processing parameter settings are analyzed and, from the results obtained, the characteristic removal values are specified. For overlapping pulses of optimum fluence, the removal rate is as high as 27.8 mm3/min for aluminum, 21.4 mm3/min for copper, 15.3 mm3/min for stainless steel, and 129.1 mm3/min for Al2O3, when a laser beam of 187 W average laser powers irradiates. On stainless steel, it is demonstrated that the removal rate increases to 23.3 mm3/min when the laser beam is very fast moving. This is thanks to the low pulse overlap as achieved with 800 m/s beam deflection speed; thus, laser beam shielding can be avoided even when irradiating high-repetitive 20-MHz pulses.

Parents' Reactions to Finding Out That Their Children Have Average or above Average IQ Scores.

Science.gov (United States)

Dirks, Jean; And Others

1983-01-01

Parents of 41 children who had been given an individually-administered intelligence test were contacted 19 months after testing. Parents of average IQ children were less accurate in their memory of test results. Children with above average IQ experienced extremely low frequencies of sibling rivalry, conceit or pressure. (Author/HLM)

Evaluations of average level spacings

International Nuclear Information System (INIS)

Liou, H.I.

1980-01-01

The average level spacing for highly excited nuclei is a key parameter in cross section formulas based on statistical nuclear models, and also plays an important role in determining many physics quantities. Various methods to evaluate average level spacings are reviewed. Because of the finite experimental resolution, to detect a complete sequence of levels without mixing other parities is extremely difficult, if not totally impossible. Most methods derive the average level spacings by applying a fit, with different degrees of generality, to the truncated Porter-Thomas distribution for reduced neutron widths. A method that tests both distributions of level widths and positions is discussed extensivey with an example of 168 Er data. 19 figures, 2 tables

Predicting Moves-on-Stills for Comic Art Using Viewer Gaze Data.

Science.gov (United States)

Jain, Eakta; Sheikh, Yaser; Hodgins, Jessica

2016-01-01

Comic art consists of a sequence of panels of different shapes and sizes that visually communicate the narrative to the reader. The move-on-stills technique allows such still images to be retargeted for digital displays via camera moves. Today, moves-on-stills can be created by software applications given user-provided parameters for each desired camera move. The proposed algorithm uses viewer gaze as input to computationally predict camera move parameters. The authors demonstrate their algorithm on various comic book panels and evaluate its performance by comparing their results with a professional DVD.

Averaged RMHD equations

International Nuclear Information System (INIS)

Ichiguchi, Katsuji

1998-01-01

A new reduced set of resistive MHD equations is derived by averaging the full MHD equations on specified flux coordinates, which is consistent with 3D equilibria. It is confirmed that the total energy is conserved and the linearized equations for ideal modes are self-adjoint. (author)

Moving a House by Moved Participants

DEFF Research Database (Denmark)

Axel, Erik

himself in controlling every detail of the shape of the concrete slaps. He pushed all the other participants of the meetings, asking for details, information, the change of drawings etc. He explained the technical issues he was pursuing, was prepared for problems at the meetings, was well informed, always......? The participant observer believed it was a matter of changing coordinates, but the engineers immediately saw it was an issue of pipes in the ground, could they be moved and still function as planned? To decide the possibility of this suggestion the engineer was given the task of investigating the consequences...... they saw him as a bit pushy. On the other hand they understood why he was so since his firm would be fined if the concrete slabs did not meet specifications. The case will be the basis for a discussion of double motivation of the engineer, his evident interest in his professional work, and the wish...

Reproducing multi-model ensemble average with Ensemble-averaged Reconstructed Forcings (ERF) in regional climate modeling

Science.gov (United States)

Erfanian, A.; Fomenko, L.; Wang, G.

2016-12-01

Multi-model ensemble (MME) average is considered the most reliable for simulating both present-day and future climates. It has been a primary reference for making conclusions in major coordinated studies i.e. IPCC Assessment Reports and CORDEX. The biases of individual models cancel out each other in MME average, enabling the ensemble mean to outperform individual members in simulating the mean climate. This enhancement however comes with tremendous computational cost, which is especially inhibiting for regional climate modeling as model uncertainties can originate from both RCMs and the driving GCMs. Here we propose the Ensemble-based Reconstructed Forcings (ERF) approach to regional climate modeling that achieves a similar level of bias reduction at a fraction of cost compared with the conventional MME approach. The new method constructs a single set of initial and boundary conditions (IBCs) by averaging the IBCs of multiple GCMs, and drives the RCM with this ensemble average of IBCs to conduct a single run. Using a regional climate model (RegCM4.3.4-CLM4.5), we tested the method over West Africa for multiple combination of (up to six) GCMs. Our results indicate that the performance of the ERF method is comparable to that of the MME average in simulating the mean climate. The bias reduction seen in ERF simulations is achieved by using more realistic IBCs in solving the system of equations underlying the RCM physics and dynamics. This endows the new method with a theoretical advantage in addition to reducing computational cost. The ERF output is an unaltered solution of the RCM as opposed to a climate state that might not be physically plausible due to the averaging of multiple solutions with the conventional MME approach. The ERF approach should be considered for use in major international efforts such as CORDEX. Key words: Multi-model ensemble, ensemble analysis, ERF, regional climate modeling

Averaging for solitons with nonlinearity management

International Nuclear Information System (INIS)

Pelinovsky, D.E.; Kevrekidis, P.G.; Frantzeskakis, D.J.

2003-01-01

We develop an averaging method for solitons of the nonlinear Schroedinger equation with a periodically varying nonlinearity coefficient, which is used to effectively describe solitons in Bose-Einstein condensates, in the context of the recently proposed technique of Feshbach resonance management. Using the derived local averaged equation, we study matter-wave bright and dark solitons and demonstrate a very good agreement between solutions of the averaged and full equations

The Acceleration of Charged Particles at a Spherical Shock Moving through an Irregular Magnetic Field

Energy Technology Data Exchange (ETDEWEB)

Giacalone, J. [Department of Planetary Sciences, University of Arizona, Tucson, AZ (United States)

2017-10-20

We investigate the physics of charged-particle acceleration at spherical shocks moving into a uniform plasma containing a turbulent magnetic field with a uniform mean. This has applications to particle acceleration at astrophysical shocks, most notably, to supernovae blast waves. We numerically integrate the equations of motion of a large number of test protons moving under the influence of electric and magnetic fields determined from a kinematically defined plasma flow associated with a radially propagating blast wave. Distribution functions are determined from the positions and velocities of the protons. The unshocked plasma contains a magnetic field with a uniform mean and an irregular component having a Kolmogorov-like power spectrum. The field inside the blast wave is determined from Maxwell’s equations. The angle between the average magnetic field and unit normal to the shock varies with position along its surface. It is quasi-perpendicular to the unit normal near the sphere’s equator, and quasi-parallel to it near the poles. We find that the highest intensities of particles, accelerated by the shock, are at the poles of the blast wave. The particles “collect” at the poles as they approximately adhere to magnetic field lines that move poleward from their initial encounter with the shock at the equator, as the shock expands. The field lines at the poles have been connected to the shock the longest. We also find that the highest-energy protons are initially accelerated near the equator or near the quasi-perpendicular portion of the shock, where the acceleration is more rapid.

Score-driven exponentially weighted moving averages and Value-at-Risk forecasting

NARCIS (Netherlands)

Lucas, A.; Zhang, X.

2016-01-01

We present a simple methodology for modeling the time variation in volatilities and other higher-order moments using a recursive updating scheme that is similar to the familiar RiskMetrics approach. The parameters are updated using the score of the forecasting distribution, which allows the

Imaging of Moving Ground Vehicles

National Research Council Canada - National Science Library

Rihaczek, A

1996-01-01

... requires that use be made of the complex image. The yaw/pitch/roll/bounce/flex motion of a moving ground vehicle demands that different motion compensations be applied to different parts of the vehicle...

Moving up in industry.

Science.gov (United States)

Covell, Charlotte

2016-01-23

Charlotte Covell is commercial business manager at Virbac UK, a role that gives her responsibility for the company's sales to corporate practices, some buying groups and internet pharmacies. She began her career as a veterinary nurse, but moved into industry and now has a role in senior business management. British Veterinary Association.

time series modeling of daily abandoned calls in a call centre

African Journals Online (AJOL)

DJFLEX

Models for evaluating and predicting the short periodic time series in daily ... Ugwuowo (2006) proposed asymmetric angular- linear multivariate regression models, ..... Using the parameter estimates in Table 3, the fitted Fourier series model is ..... For the SARIMA model with the stochastic component also being white noise, ...

Making Images That Move

Science.gov (United States)

Rennie, Richard

2015-01-01

The history of the moving image (the cinema) is well documented in books and on the Internet. This article offers a number of activities that can easily be carried out in a science class. They make use of the phenomenon of "Persistence of Vision." The activities presented herein demonstrate the functionality of the phenakistoscope, the…

40 CFR 600.510-12 - Calculation of average fuel economy and average carbon-related exhaust emissions.

Science.gov (United States)

2010-07-01

... and average carbon-related exhaust emissions. 600.510-12 Section 600.510-12 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) ENERGY POLICY FUEL ECONOMY AND CARBON-RELATED EXHAUST EMISSIONS OF... Transportation. (iv) [Reserved] (2) Average carbon-related exhaust emissions will be calculated to the nearest...

Being moved: linguistic representation and conceptual structure

OpenAIRE

Kuehnast, Milena; Wagner, Valentin; Wassiliwizky, Eugen; Jacobsen, Thomas; Menninghaus, Winfried

2014-01-01

This study explored the organization of the semantic field and the conceptual structure of moving experiences by investigating German-language expressions referring to the emotional state of being moved. We used present and past participles of eight psychological verbs as primes in a free word-association task, as these grammatical forms place their conceptual focus on the eliciting situation and on the felt emotional state, respectively. By applying a taxonomy of basic knowledge types and co...

Faith Moves Mountains-Mountains Move Faith: Two Opposite Epidemiological Forces in Research on Religion and Health.

Science.gov (United States)

Hvidt, N C; Hvidtjørn, D; Christensen, K; Nielsen, J B; Søndergaard, J

2017-02-01

Research suggests opposite epidemiological forces in religion and health: (1). Faith seems to move mountains in the sense that religion is associated with positive health outcomes. (2). Mountains of bad health seem to move faith. We reflected on these forces in a population of 3000 young Danish twins in which all religiosity measures were associated with severe disease. We believe the reason for this novel finding is that the sample presents as a particularly secular population-based study and that the second epidemiological force has gained the upper hand in this sample. We suggest that all cross-sectional research on religion and health should be interpreted in light of such opposite epidemiological forces potentially diluting each other.

Improved averaging for non-null interferometry

Science.gov (United States)

Fleig, Jon F.; Murphy, Paul E.

2013-09-01

Arithmetic averaging of interferometric phase measurements is a well-established method for reducing the effects of time varying disturbances, such as air turbulence and vibration. Calculating a map of the standard deviation for each pixel in the average map can provide a useful estimate of its variability. However, phase maps of complex and/or high density fringe fields frequently contain defects that severely impair the effectiveness of simple phase averaging and bias the variability estimate. These defects include large or small-area phase unwrapping artifacts, large alignment components, and voids that change in number, location, or size. Inclusion of a single phase map with a large area defect into the average is usually sufficient to spoil the entire result. Small-area phase unwrapping and void defects may not render the average map metrologically useless, but they pessimistically bias the variance estimate for the overwhelming majority of the data. We present an algorithm that obtains phase average and variance estimates that are robust against both large and small-area phase defects. It identifies and rejects phase maps containing large area voids or unwrapping artifacts. It also identifies and prunes the unreliable areas of otherwise useful phase maps, and removes the effect of alignment drift from the variance estimate. The algorithm has several run-time adjustable parameters to adjust the rejection criteria for bad data. However, a single nominal setting has been effective over a wide range of conditions. This enhanced averaging algorithm can be efficiently integrated with the phase map acquisition process to minimize the number of phase samples required to approach the practical noise floor of the metrology environment.

Similitude study of a moving bed granular filter

Energy Technology Data Exchange (ETDEWEB)

Robert C. Brown; Huawei Shi; Gerald Colver; Saw-Choon Soo [Iowa State University, IA (United States)

2003-12-10

The goal of this study was to evaluate the performance of a moving bed granular filter designed for hot gas clean up. This study used similitude theory to devise experiments that were conducted at near-ambient conditions while simulating the performance of filters operated at elevated temperatures and pressures (850{sup o}C and 1000 kPa). These experiments revealed that the proposed moving bed granular filter can operate at high collection efficiencies, typically exceeding 99%, and low pressure drops without the need for periodic regeneration through the use of a continuous flow of fresh granular filter media in the filter. In addition, important design constraints were discovered for the successful operation of the proposed moving bed granular filter.

Simple, Yet Powerful English of MoveOns's Campaigns

Directory of Open Access Journals (Sweden)

Aris Munandar

2012-08-01

Full Text Available Getting messages across to a large audience of diverse backgrounds is a challenge. MoveOn.org is successful in responding to the challenge when writing its campaigns in a language intelligible to all members. This research studies the characteristics of English used in MoveOn’s campaigns during the periods of January 25, to March 30, 2011. It reveals that the campaigns choose ordinary words (neither politically charged nor hyperbolic to maintain neutrality and situation-problem-solution pattern for its rhetorical structure in order to convey an easy-to-follow argument. The research concludes that MoveOn designs its campaigns to produce persuasive effects that are more rational based than emotional-based.

Vibration of Bridges under the Passage of Vehicles Simulated as Moving Loads

International Nuclear Information System (INIS)

Ouchenane, M.; Lassoued, R.; Ouchenane, K.

2011-01-01

The dynamic behavior of bridges under the effect of moving loads simulating the vehicle moving along the bridge structure idealized by an Euler beam is analyzed. We will present the dynamic behavior of beams under the stress of moving loads (or masses) by the analytical and semi-analytical approaches. When the mass of the bridge structure is comparable to that of the vehicle, the mobile source requesting the bridge is simulated by a mass. In most practical cases, the mobile force used is due to the effects of the gravitational moving masses: . When the moving mass is small compared to the beam mass, the obtained solution under the effect of moving force is approximately correct for the solution obtained with the moving mass. Otherwise, the problem of the moving mass is imperative. To do this, we wrote a program in Matlab language which reflects the dynamic behavior of beams under the effect of moving charges, which gives the following results T he frequencies and modes of vibration, the dynamics deflection of the beam requested by moving force, the dynamic response (DAF: dynamic amplification factor) of the beam requested by a moving force, over the whole length of the beam, for all times and for different speeds. The numerical example that we look to see for study the dynamic behavior of this type of bridge under moving loads is that of a thin beam unamortised on simple support and length of 50m, under the solicitation of moving force and mass at a constant speed and varies from 0 to 100 m / s (M. A. Foda, 1997), depending on the relationship between the vehicle mass and the mass of the bridge that will allow us to see the contribution of the choice of modelling type on the total response and then the vibration of bridge, also we will study the effect of type of simulation of the load by moving force or mass on the dynamic amplification factor and comparing our results with those from the literature. (author)

A time-averaged cosmic ray propagation theory

International Nuclear Information System (INIS)

Klimas, A.J.

1975-01-01

An argument is presented, which casts doubt on our ability to choose an appropriate magnetic field ensemble for computing the average behavior of cosmic ray particles. An alternate procedure, using time-averages rather than ensemble-averages, is presented. (orig.) [de

Basal-topographic control of stationary ponds on a continuously moving landslide

Science.gov (United States)

Coe, J.A.; McKenna, J.P.; Godt, J.W.; Baum, R.L.

2009-01-01

analyses of translational landslides should attempt to incorporate irregular basal surface topography. Additional implications for moving landslides where basal topography controls surface morphology include the following: dateable sediments or organic material from basal layers of stationary ponds will yield ages that are younger than the date of landslide initiation, and it is probable that other landslide surface features such as faults, streams, springs and sinks are also controlled by basal topography. The longitudinal topographic profile indicated that the upper part of the Slumgullion landslide was depleted at a mean vertical lowering rate of 5.6 cm/yr between 1939 and 2000, while the toe advanced at an average rate of 1.5 m/yr during the same period. Therefore, during this 61-year period, neither the depletion of material at the head of the landslide nor continued growth of the landslide toe has decreased the overall movement rate of the landslide. Continued depletion of the upper part of the landslide, and growth of the toe, should eventually result in stabilization of the landslide. Copyright ?? 2008 John Wiley & Sons, Ltd.

Multiple Moving Obstacles Avoidance of Service Robot using Stereo Vision

Directory of Open Access Journals (Sweden)

Achmad Jazidie

2011-12-01

Full Text Available In this paper, we propose a multiple moving obstacles avoidance using stereo vision for service robots in indoor environments. We assume that this model of service robot is used to deliver a cup to the recognized customer from the starting point to the destination. The contribution of this research is a new method for multiple moving obstacle avoidance with Bayesian approach using stereo camera. We have developed and introduced 3 main modules to recognize faces, to identify multiple moving obstacles and to maneuver of robot. A group of people who is walking will be tracked as a multiple moving obstacle, and the speed, direction, and distance of the moving obstacles is estimated by a stereo camera in order that the robot can maneuver to avoid the collision. To overcome the inaccuracies of vision sensor, Bayesian approach is used for estimate the absense and direction of obstacles. We present the results of the experiment of the service robot called Srikandi III which uses our proposed method and we also evaluate its performance. Experiments shown that our proposed method working well, and Bayesian approach proved increasing the estimation perform for absence and direction of moving obstacle.

Capture of a quantum particle by a moving trapping potential

International Nuclear Information System (INIS)

Shegelski, Mark R A; Poole, Tyler; Thompson, Cole

2013-01-01

We investigate the capture of a quantum particle in free space by a moving trapping potential. The capture is investigated for various initial conditions. We examine the dependence of the probability of capture on the shape and depth of the trapping potential, initial speed and mass of the particle, and other parameters. We take the trapping potential to move with an initial speed v 0 and to decelerate with constant acceleration a c until the well stops moving. We study the motion during the time the well is moving and after the well has stopped. We compare the probability of capture to the probability that the particle is in a stationary state (while the well is moving) and the probability the particle is in a bound state (after the well's motion has stopped). Our work could be of interest to instructors and students in upper-year undergraduate quantum mechanics courses. (paper)

Moving charged particles in lattice Boltzmann-based electrokinetics

Science.gov (United States)

Kuron, Michael; Rempfer, Georg; Schornbaum, Florian; Bauer, Martin; Godenschwager, Christian; Holm, Christian; de Graaf, Joost

2016-12-01

The motion of ionic solutes and charged particles under the influence of an electric field and the ensuing hydrodynamic flow of the underlying solvent is ubiquitous in aqueous colloidal suspensions. The physics of such systems is described by a coupled set of differential equations, along with boundary conditions, collectively referred to as the electrokinetic equations. Capuani et al. [J. Chem. Phys. 121, 973 (2004)] introduced a lattice-based method for solving this system of equations, which builds upon the lattice Boltzmann algorithm for the simulation of hydrodynamic flow and exploits computational locality. However, thus far, a description of how to incorporate moving boundary conditions into the Capuani scheme has been lacking. Moving boundary conditions are needed to simulate multiple arbitrarily moving colloids. In this paper, we detail how to introduce such a particle coupling scheme, based on an analogue to the moving boundary method for the pure lattice Boltzmann solver. The key ingredients in our method are mass and charge conservation for the solute species and a partial-volume smoothing of the solute fluxes to minimize discretization artifacts. We demonstrate our algorithm's effectiveness by simulating the electrophoresis of charged spheres in an external field; for a single sphere we compare to the equivalent electro-osmotic (co-moving) problem. Our method's efficiency and ease of implementation should prove beneficial to future simulations of the dynamics in a wide range of complex nanoscopic and colloidal systems that were previously inaccessible to lattice-based continuum algorithms.

20007: Quantum particle displacement by a moving localized potential trap

Science.gov (United States)

Granot, E.; Marchewka, A.

2009-04-01

We describe the dynamics of a bound state of an attractive δ-well under displacement of the potential. Exact analytical results are presented for the suddenly moved potential. Since this is a quantum system, only a fraction of the initially confined wave function remains confined to the moving potential. However, it is shown that besides the probability to remain confined to the moving barrier and the probability to remain in the initial position, there is also a certain probability for the particle to move at double speed. A quasi-classical interpretation for this effect is suggested. The temporal and spectral dynamics of each one of the scenarios is investigated.

Improving consensus structure by eliminating averaging artifacts

Directory of Open Access Journals (Sweden)

KC Dukka B

2009-03-01

Full Text Available Abstract Background Common structural biology methods (i.e., NMR and molecular dynamics often produce ensembles of molecular structures. Consequently, averaging of 3D coordinates of molecular structures (proteins and RNA is a frequent approach to obtain a consensus structure that is representative of the ensemble. However, when the structures are averaged, artifacts can result in unrealistic local geometries, including unphysical bond lengths and angles. Results Herein, we describe a method to derive representative structures while limiting the number of artifacts. Our approach is based on a Monte Carlo simulation technique that drives a starting structure (an extended or a 'close-by' structure towards the 'averaged structure' using a harmonic pseudo energy function. To assess the performance of the algorithm, we applied our approach to Cα models of 1364 proteins generated by the TASSER structure prediction algorithm. The average RMSD of the refined model from the native structure for the set becomes worse by a mere 0.08 Å compared to the average RMSD of the averaged structures from the native structure (3.28 Å for refined structures and 3.36 A for the averaged structures. However, the percentage of atoms involved in clashes is greatly reduced (from 63% to 1%; in fact, the majority of the refined proteins had zero clashes. Moreover, a small number (38 of refined structures resulted in lower RMSD to the native protein versus the averaged structure. Finally, compared to PULCHRA 1, our approach produces representative structure of similar RMSD quality, but with much fewer clashes. Conclusion The benchmarking results demonstrate that our approach for removing averaging artifacts can be very beneficial for the structural biology community. Furthermore, the same approach can be applied to almost any problem where averaging of 3D coordinates is performed. Namely, structure averaging is also commonly performed in RNA secondary prediction 2, which

Optimal moving grids for time-dependent partial differential equations

Science.gov (United States)

Wathen, A. J.

1992-01-01

Various adaptive moving grid techniques for the numerical solution of time-dependent partial differential equations were proposed. The precise criterion for grid motion varies, but most techniques will attempt to give grids on which the solution of the partial differential equation can be well represented. Moving grids are investigated on which the solutions of the linear heat conduction and viscous Burgers' equation in one space dimension are optimally approximated. Precisely, the results of numerical calculations of optimal moving grids for piecewise linear finite element approximation of PDE solutions in the least-squares norm are reported.

Chromatic Shadow Detection and Tracking for Moving Foreground Segmentation

DEFF Research Database (Denmark)

Huerta, Ivan; Holte, Michael Boelstoft; Moeslund, Thomas B.

2015-01-01

are usually detected as part of moving objects, thus affecting the performance of the final detection. In this paper we address the detection of both penumbra and umbra shadow regions. First, a novel bottom-up approach is presented based on gradient and colour models, which successfully discriminates between...... chromatic moving cast shadow regions and those regions detected as moving objects. In essence, those regions corresponding to potential shadows are detected based on edge partitioning and colour statistics. Subsequently (i) temporal similarities between textures and (ii) spatial similarities between...

On the rationality of cycling in the Theory of Moves framework

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Temperature distribution in a uniformly moving medium

International Nuclear Information System (INIS)

Mitchell, Joseph D; Petrov, Nikola P

2009-01-01

We apply several physical ideas to determine the steady temperature distribution in a medium moving with uniform velocity between two infinite parallel plates. We compute it in the coordinate frame moving with the medium by integration over the 'past' to account for the influence of an infinite set of instantaneous point sources of heat in past moments as seen by an observer moving with the medium. The boundary heat flux is simulated by appropriately distributed point heat sources on the inner side of an adiabatically insulating boundary. We make an extensive use of the Green functions with an emphasis on their physical meaning. The methodology used in this paper is of great pedagogical value as it offers an opportunity for students to see the connection between powerful mathematical techniques and their physical interpretation in an intuitively clear physical problem. We suggest several problems and a challenging project that can be easily incorporated in undergraduate or graduate courses

Multiphase flow of immiscible fluids on unstructured moving meshes

DEFF Research Database (Denmark)

Misztal, Marek Krzysztof; Erleben, Kenny; Bargteil, Adam

2012-01-01

In this paper, we present a method for animating multiphase flow of immiscible fluids using unstructured moving meshes. Our underlying discretization is an unstructured tetrahedral mesh, the deformable simplicial complex (DSC), that moves with the flow in a Lagrangian manner. Mesh optimization op...

Multiphase Flow of Immiscible Fluids on Unstructured Moving Meshes

DEFF Research Database (Denmark)

Misztal, Marek Krzysztof; Erleben, Kenny; Bargteil, Adam

2013-01-01

In this paper, we present a method for animating multiphase flow of immiscible fluids using unstructured moving meshes. Our underlying discretization is an unstructured tetrahedral mesh, the deformable simplicial complex (DSC), that moves with the flow in a Lagrangian manner. Mesh optimization op...

Detection and Removal of Chromatic Moving Shadows in Surveillance Scenarios