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Sample records for regressive integrated moving

  1. 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.

  2. 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.

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

    Directory of Open Access Journals (Sweden)

    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

  4. 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.

  5. 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.

  6. [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.

  7. An integrated fuzzy regression algorithm for energy consumption estimation with non-stationary data: A case study of Iran

    Energy Technology Data Exchange (ETDEWEB)

    Azadeh, A; Seraj, O [Department of Industrial Engineering and Research Institute of Energy Management and Planning, Center of Excellence for Intelligent-Based Experimental Mechanics, College of Engineering, University of Tehran, P.O. Box 11365-4563 (Iran); Saberi, M [Department of Industrial Engineering, University of Tafresh (Iran); Institute for Digital Ecosystems and Business Intelligence, Curtin University of Technology, Perth (Australia)

    2010-06-15

    This study presents an integrated fuzzy regression and time series framework to estimate and predict electricity demand for seasonal and monthly changes in electricity consumption especially in developing countries such as China and Iran with non-stationary data. Furthermore, it is difficult to model uncertain behavior of energy consumption with only conventional fuzzy regression (FR) or time series and the integrated algorithm could be an ideal substitute for such cases. At First, preferred Time series model is selected from linear or nonlinear models. For this, after selecting preferred Auto Regression Moving Average (ARMA) model, Mcleod-Li test is applied to determine nonlinearity condition. When, nonlinearity condition is satisfied, the preferred nonlinear model is selected and defined as preferred time series model. At last, the preferred model from fuzzy regression and time series model is selected by the Granger-Newbold. Also, the impact of data preprocessing on the fuzzy regression performance is considered. Monthly electricity consumption of Iran from March 1994 to January 2005 is considered as the case of this study. The superiority of the proposed algorithm is shown by comparing its results with other intelligent tools such as Genetic Algorithm (GA) and Artificial Neural Network (ANN). (author)

  8. Extreme Learning Machine and Moving Least Square Regression Based Solar Panel Vision Inspection

    Directory of Open Access Journals (Sweden)

    Heng Liu

    2017-01-01

    Full Text Available In recent years, learning based machine intelligence has aroused a lot of attention across science and engineering. Particularly in the field of automatic industry inspection, the machine learning based vision inspection plays a more and more important role in defect identification and feature extraction. Through learning from image samples, many features of industry objects, such as shapes, positions, and orientations angles, can be obtained and then can be well utilized to determine whether there is defect or not. However, the robustness and the quickness are not easily achieved in such inspection way. In this work, for solar panel vision inspection, we present an extreme learning machine (ELM and moving least square regression based approach to identify solder joint defect and detect the panel position. Firstly, histogram peaks distribution (HPD and fractional calculus are applied for image preprocessing. Then an ELM-based defective solder joints identification is discussed in detail. Finally, moving least square regression (MLSR algorithm is introduced for solar panel position determination. Experimental results and comparisons show that the proposed ELM and MLSR based inspection method is efficient not only in detection accuracy but also in processing speed.

  9. Forecasting daily meteorological time series using ARIMA and regression models

    Science.gov (United States)

    Murat, Małgorzata; Malinowska, Iwona; Gos, Magdalena; Krzyszczak, Jaromir

    2018-04-01

    The daily air temperature and precipitation time series recorded between January 1, 1980 and December 31, 2010 in four European sites (Jokioinen, Dikopshof, Lleida and Lublin) from different climatic zones were modeled and forecasted. In our forecasting we used the methods of the Box-Jenkins and Holt- Winters seasonal auto regressive integrated moving-average, the autoregressive integrated moving-average with external regressors in the form of Fourier terms and the time series regression, including trend and seasonality components methodology with R software. It was demonstrated that obtained models are able to capture the dynamics of the time series data and to produce sensible forecasts.

  10. Moving energies as first integrals of nonholonomic systems with affine constraints

    Science.gov (United States)

    Fassò, Francesco; García-Naranjo, Luis C.; Sansonetto, Nicola

    2018-03-01

    In nonholonomic mechanical systems with constraints that are affine (linear nonhomogeneous) functions of the velocities, the energy is typically not a first integral. It was shown in Fassò and Sansonetto (2016 J. Nonlinear Sci. 26 519-44) that, nevertheless, there exist modifications of the energy, called there moving energies, which under suitable conditions are first integrals. The first goal of this paper is to study the properties of these functions and the conditions that lead to their conservation. In particular, we enlarge the class of moving energies considered in Fassò and Sansonetto (2016 J. Nonlinear Sci. 26 519-44). The second goal of the paper is to demonstrate the relevance of moving energies in nonholonomic mechanics. We show that certain first integrals of some well known systems (the affine Veselova and LR systems), which had been detected on a case-by-case way, are instances of moving energies. Moreover, we determine conserved moving energies for a class of affine systems on Lie groups that include the LR systems, for a heavy convex rigid body that rolls without slipping on a uniformly rotating plane, and for an n-dimensional generalization of the Chaplygin sphere problem to a uniformly rotating hyperplane.

  11. Shadowfax: Moving mesh hydrodynamical integration code

    Science.gov (United States)

    Vandenbroucke, Bert

    2016-05-01

    Shadowfax simulates galaxy evolution. Written in object-oriented modular C++, it evolves a mixture of gas, subject to the laws of hydrodynamics and gravity, and any collisionless fluid only subject to gravity, such as cold dark matter or stars. For the hydrodynamical integration, it makes use of a (co-) moving Lagrangian mesh. The code has a 2D and 3D version, contains utility programs to generate initial conditions and visualize simulation snapshots, and its input/output is compatible with a number of other simulation codes, e.g. Gadget2 (ascl:0003.001) and GIZMO (ascl:1410.003).

  12. Making the Move: A Mixed Research Integrative Review

    Directory of Open Access Journals (Sweden)

    Sarah Gilbert

    2015-08-01

    Full Text Available The purpose of this mixed research integrative review is to determine factors that influence relocation transitions for older adults who are considering a move from independent living to supervised housing, such as assisted living, using the Theory of Planned Behavior as a conceptual guide. PubMED, CINAHL, and PsychInfo databases were queried using key words: relocation, transition, older adults, and, elderly and time limited from 1992 to 2014. Sixteen articles were retained for review. The majority of articles, qualitative in design, reveal that older adults who comprehend the need to move and participate in the decision-making process of a relocation adjust to new living environments with fewer negative outcomes than older adults who experience a forced relocation. The few quantitative articles examined the elements of impending relocation using a variety of instruments but support the necessity for older adults to recognize the possibility of a future move and contribute to the relocation process. Additionally, the influence of family, friends, and health care providers provides the older adult with support and guidance throughout the process.

  13. 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)

  14. 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.

  15. 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.

  16. Wavelet regression model in forecasting crude oil price

    Science.gov (United States)

    Hamid, Mohd Helmie; Shabri, Ani

    2017-05-01

    This study presents the performance of wavelet multiple linear regression (WMLR) technique in daily crude oil forecasting. WMLR model was developed by integrating the discrete wavelet transform (DWT) and multiple linear regression (MLR) model. The original time series was decomposed to sub-time series with different scales by wavelet theory. Correlation analysis was conducted to assist in the selection of optimal decomposed components as inputs for the WMLR model. The daily WTI crude oil price series has been used in this study to test the prediction capability of the proposed model. The forecasting performance of WMLR model were also compared with regular multiple linear regression (MLR), Autoregressive Moving Average (ARIMA) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) using root mean square errors (RMSE) and mean absolute errors (MAE). Based on the experimental results, it appears that the WMLR model performs better than the other forecasting technique tested in this study.

  17. An integrated approach for visual analysis of a multisource moving objects knowledge base

    NARCIS (Netherlands)

    Willems, N.; van Hage, W.R.; de Vries, G.; Janssens, J.H.M.; Malaisé, V.

    2010-01-01

    We present an integrated and multidisciplinary approach for analyzing the behavior of moving objects. The results originate from an ongoing research of four different partners from the Dutch Poseidon project (Embedded Systems Institute (2007)), which aims to develop new methods for Maritime Safety

  18. Tracking integration in concentrating photovoltaics using laterally moving optics.

    Science.gov (United States)

    Duerr, Fabian; Meuret, Youri; Thienpont, Hugo

    2011-05-09

    In this work the concept of tracking-integrated concentrating photovoltaics is studied and its capabilities are quantitatively analyzed. The design strategy desists from ideal concentration performance to reduce the external mechanical solar tracking effort in favor of a compact installation, possibly resulting in lower overall cost. The proposed optical design is based on an extended Simultaneous Multiple Surface (SMS) algorithm and uses two laterally moving plano-convex lenses to achieve high concentration over a wide angular range of ±24°. It achieves 500× concentration, outperforming its conventional concentrating photovoltaic counterparts on a polar aligned single axis tracker.

  19. Adaptive Moving Object Tracking Integrating Neural Networks And Intelligent Processing

    Science.gov (United States)

    Lee, James S. J.; Nguyen, Dziem D.; Lin, C.

    1989-03-01

    A real-time adaptive scheme is introduced to detect and track moving objects under noisy, dynamic conditions including moving sensors. This approach integrates the adaptiveness and incremental learning characteristics of neural networks with intelligent reasoning and process control. Spatiotemporal filtering is used to detect and analyze motion, exploiting the speed and accuracy of multiresolution processing. A neural network algorithm constitutes the basic computational structure for classification. A recognition and learning controller guides the on-line training of the network, and invokes pattern recognition to determine processing parameters dynamically and to verify detection results. A tracking controller acts as the central control unit, so that tracking goals direct the over-all system. Performance is benchmarked against the Widrow-Hoff algorithm, for target detection scenarios presented in diverse FLIR image sequences. Efficient algorithm design ensures that this recognition and control scheme, implemented in software and commercially available image processing hardware, meets the real-time requirements of tracking applications.

  20. Integrated Multiscale Latent Variable Regression and Application to Distillation Columns

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    Muddu Madakyaru

    2013-01-01

    Full Text Available Proper control of distillation columns requires estimating some key variables that are challenging to measure online (such as compositions, which are usually estimated using inferential models. Commonly used inferential models include latent variable regression (LVR techniques, such as principal component regression (PCR, partial least squares (PLS, and regularized canonical correlation analysis (RCCA. Unfortunately, measured practical data are usually contaminated with errors, which degrade the prediction abilities of inferential models. Therefore, noisy measurements need to be filtered to enhance the prediction accuracy of these models. Multiscale filtering has been shown to be a powerful feature extraction tool. In this work, the advantages of multiscale filtering are utilized to enhance the prediction accuracy of LVR models by developing an integrated multiscale LVR (IMSLVR modeling algorithm that integrates modeling and feature extraction. The idea behind the IMSLVR modeling algorithm is to filter the process data at different decomposition levels, model the filtered data from each level, and then select the LVR model that optimizes a model selection criterion. The performance of the developed IMSLVR algorithm is illustrated using three examples, one using synthetic data, one using simulated distillation column data, and one using experimental packed bed distillation column data. All examples clearly demonstrate the effectiveness of the IMSLVR algorithm over the conventional methods.

  1. Integrating address geocoding, land use regression, and spatiotemporal geostatistical estimation for groundwater tetrachloroethylene.

    Science.gov (United States)

    Messier, Kyle P; Akita, Yasuyuki; Serre, Marc L

    2012-03-06

    Geographic information systems (GIS) based techniques are cost-effective and efficient methods used by state agencies and epidemiology researchers for estimating concentration and exposure. However, budget limitations have made statewide assessments of contamination difficult, especially in groundwater media. Many studies have implemented address geocoding, land use regression, and geostatistics independently, but this is the first to examine the benefits of integrating these GIS techniques to address the need of statewide exposure assessments. A novel framework for concentration exposure is introduced that integrates address geocoding, land use regression (LUR), below detect data modeling, and Bayesian Maximum Entropy (BME). A LUR model was developed for tetrachloroethylene that accounts for point sources and flow direction. We then integrate the LUR model into the BME method as a mean trend while also modeling below detects data as a truncated Gaussian probability distribution function. We increase available PCE data 4.7 times from previously available databases through multistage geocoding. The LUR model shows significant influence of dry cleaners at short ranges. The integration of the LUR model as mean trend in BME results in a 7.5% decrease in cross validation mean square error compared to BME with a constant mean trend.

  2. An Integrated Approach for Visual Analysis of a Multi-Source Moving Objects Knowledge Base

    NARCIS (Netherlands)

    Willems, C.M.E.; van Hage, W.R.; de Vries, G.K.D.; Janssens, J.; Malaisé, V.

    2010-01-01

    We present an integrated and multidisciplinary approach for analyzing the behavior of moving objects. The results originate from an ongoing research of four different partners from the Dutch Poseidon project (Embedded Systems Institute (2007)), which aims to develop new methods for Maritime Safety

  3. An integrated approach for visual analysis of a multi-source moving objects knowledge base

    NARCIS (Netherlands)

    Willems, N.; Hage, van W.R.; Vries, de G.; Janssens, J.H.M.; Malaisé, V.

    2010-01-01

    We present an integrated and multidisciplinary approach for analyzing the behavior of moving objects. The results originate from an ongoing research of four different partners from the Dutch Poseidon project (Embedded Systems Institute (2007)), which aims to develop new methods for Maritime Safety

  4. 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

  5. Estimating integrated variance in the presence of microstructure noise using linear regression

    Science.gov (United States)

    Holý, Vladimír

    2017-07-01

    Using financial high-frequency data for estimation of integrated variance of asset prices is beneficial but with increasing number of observations so-called microstructure noise occurs. This noise can significantly bias the realized variance estimator. We propose a method for estimation of the integrated variance robust to microstructure noise as well as for testing the presence of the noise. Our method utilizes linear regression in which realized variances estimated from different data subsamples act as dependent variable while the number of observations act as explanatory variable. We compare proposed estimator with other methods on simulated data for several microstructure noise structures.

  6. A unified framework for testing in the linear regression model under unknown order of fractional integration

    DEFF Research Database (Denmark)

    Christensen, Bent Jesper; Kruse, Robinson; Sibbertsen, Philipp

    We consider hypothesis testing in a general linear time series regression framework when the possibly fractional order of integration of the error term is unknown. We show that the approach suggested by Vogelsang (1998a) for the case of integer integration does not apply to the case of fractional...

  7. Depth extraction method with high accuracy in integral imaging based on moving array lenslet technique

    Science.gov (United States)

    Wang, Yao-yao; Zhang, Juan; Zhao, Xue-wei; Song, Li-pei; Zhang, Bo; Zhao, Xing

    2018-03-01

    In order to improve depth extraction accuracy, a method using moving array lenslet technique (MALT) in pickup stage is proposed, which can decrease the depth interval caused by pixelation. In this method, the lenslet array is moved along the horizontal and vertical directions simultaneously for N times in a pitch to get N sets of elemental images. Computational integral imaging reconstruction method for MALT is taken to obtain the slice images of the 3D scene, and the sum modulus (SMD) blur metric is taken on these slice images to achieve the depth information of the 3D scene. Simulation and optical experiments are carried out to verify the feasibility of this method.

  8. Assessing the Value of Moving More-The Integral Role of Qualified Health Professionals.

    Science.gov (United States)

    Arena, Ross; McNeil, Amy; Lavie, Carl J; Ozemek, Cemal; Forman, Daniel; Myers, Jonathan; Laddu, Deepika R; Popovic, Dejana; Rouleau, Codie R; Campbell, Tavis S; Hills, Andrew P

    2018-04-01

    Being physically active or, in a broader sense, simply moving more throughout each day is one of the most important components of an individual's health plan. In conjunction with regular exercise training, taking more steps in a day and sitting less are also important components of one's movement portfolio. Given this priority, health care professionals must develop enhanced skills for prescribing and guiding individualized movement programs for all their patients. An important component of a health care professional's ability to prescribe movement as medicine is competency in assessing an individual's risk for untoward events if physical exertion was increased. The ability to appropriately assess one's risk before advising an individual to move more is integral to clinical decision-making related to subsequent testing if needed, exercise prescription, and level of supervision with exercise training. At present, there is a lack of clarity pertaining to how a health care professional should go about assessing an individual's readiness to move more on a daily basis in a safe manner. Therefore, this perspectives article clarifies key issues related to prescribing movement as medicine and presents a new process for clinical assessment before prescribing an individualized movement program. Copyright © 2018 Elsevier B.V. All rights reserved.

  9. Deweyan integration: moving beyond place attachment in elderly migration theory.

    Science.gov (United States)

    Cutchin, M P

    2001-01-01

    The fact that aging-in-place and elderly migration are intricately linked has been overlooked by behavioral approaches to elderly migration. "Humanistic" inquiry has provided important insights into aging-in-place and elderly migration as well as the connection between the two. Humanistic approaches, however, do not encapsulate the full range of experience involved in elders' lives. To move beyond humanistic research and key concepts such as place attachment, the philosophy of John Dewey is introduced. Dewey's viewpoint is merged with the geographical concept of place into what is termed "place integration." This perspective is subsequently compared with humanistic perspectives on aging-in-place and elderly migration decision-making. Fundamental differences such as temporal orientation and substantive focus are illustrated and discussed. Conclusions address the utility of such a perspective.

  10. An Operator-Integration-Factor Splitting (OIFS) method for Incompressible Flows in Moving Domains

    Energy Technology Data Exchange (ETDEWEB)

    Patel, Saumil S. [Argonne National Lab. (ANL), Argonne, IL (United States); Fischer, Paul F. [Argonne National Lab. (ANL), Argonne, IL (United States); Univ. of Illinois, Urbana-Champaign, IL (United States); Min, Misun [Argonne National Lab. (ANL), Argonne, IL (United States); Tomboulides, Ananias G [Argonne National Lab. (ANL), Argonne, IL (United States); Aristotle Univ., Thessaloniki (Greece)

    2017-10-21

    In this paper, we present a characteristic-based numerical procedure for simulating incompressible flows in domains with moving boundaries. Our approach utilizes an operator-integration-factor splitting technique to help produce an effcient and stable numerical scheme. Using the spectral element method and an arbitrary Lagrangian-Eulerian formulation, we investigate flows where the convective acceleration effects are non-negligible. Several examples, ranging from laminar to turbulent flows, are considered. Comparisons with a standard, semi-implicit time-stepping procedure illustrate the improved performance of the scheme.

  11. Integration of least angle regression with empirical Bayes for multi-locus genome-wide association studies

    Science.gov (United States)

    Multi-locus genome-wide association studies has become the state-of-the-art procedure to identify quantitative trait loci (QTL) associated with traits simultaneously. However, implementation of multi-locus model is still difficult. In this study, we integrated least angle regression with empirical B...

  12. Integrable discretizations and self-adaptive moving mesh method for a coupled short pulse equation

    International Nuclear Information System (INIS)

    Feng, Bao-Feng; Chen, Junchao; Chen, Yong; Maruno, Ken-ichi; Ohta, Yasuhiro

    2015-01-01

    In the present paper, integrable semi-discrete and fully discrete analogues of a coupled short pulse (CSP) equation are constructed. The key to the construction are the bilinear forms and determinant structure of the solutions of the CSP equation. We also construct N-soliton solutions for the semi-discrete and fully discrete analogues of the CSP equations in the form of Casorati determinants. In the continuous limit, we show that the fully discrete CSP equation converges to the semi-discrete CSP equation, then further to the continuous CSP equation. Moreover, the integrable semi-discretization of the CSP equation is used as a self-adaptive moving mesh method for numerical simulations. The numerical results agree with the analytical results very well. (paper)

  13. 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....

  14. The Prediction of Exchange Rates with the Use of Auto-Regressive Integrated Moving-Average Models

    Directory of Open Access Journals (Sweden)

    Daniela Spiesová

    2014-10-01

    Full Text Available Currency market is recently the largest world market during the existence of which there have been many theories regarding the prediction of the development of exchange rates based on macroeconomic, microeconomic, statistic and other models. The aim of this paper is to identify the adequate model for the prediction of non-stationary time series of exchange rates and then use this model to predict the trend of the development of European currencies against Euro. The uniqueness of this paper is in the fact that there are many expert studies dealing with the prediction of the currency pairs rates of the American dollar with other currency but there is only a limited number of scientific studies concerned with the long-term prediction of European currencies with the help of the integrated ARMA models even though the development of exchange rates has a crucial impact on all levels of economy and its prediction is an important indicator for individual countries, banks, companies and businessmen as well as for investors. The results of this study confirm that to predict the conditional variance and then to estimate the future values of exchange rates, it is adequate to use the ARIMA (1,1,1 model without constant, or ARIMA [(1,7,1,(1,7] model, where in the long-term, the square root of the conditional variance inclines towards stable value.

  15. A Gaussian mixture copula model based localized Gaussian process regression approach for long-term wind speed prediction

    International Nuclear Information System (INIS)

    Yu, Jie; Chen, Kuilin; Mori, Junichi; Rashid, Mudassir M.

    2013-01-01

    Optimizing wind power generation and controlling the operation of wind turbines to efficiently harness the renewable wind energy is a challenging task due to the intermittency and unpredictable nature of wind speed, which has significant influence on wind power production. A new approach for long-term wind speed forecasting is developed in this study by integrating GMCM (Gaussian mixture copula model) and localized GPR (Gaussian process regression). The time series of wind speed is first classified into multiple non-Gaussian components through the Gaussian mixture copula model and then Bayesian inference strategy is employed to incorporate the various non-Gaussian components using the posterior probabilities. Further, the localized Gaussian process regression models corresponding to different non-Gaussian components are built to characterize the stochastic uncertainty and non-stationary seasonality of the wind speed data. The various localized GPR models are integrated through the posterior probabilities as the weightings so that a global predictive model is developed for the prediction of wind speed. The proposed GMCM–GPR approach is demonstrated using wind speed data from various wind farm locations and compared against the GMCM-based ARIMA (auto-regressive integrated moving average) and SVR (support vector regression) methods. In contrast to GMCM–ARIMA and GMCM–SVR methods, the proposed GMCM–GPR model is able to well characterize the multi-seasonality and uncertainty of wind speed series for accurate long-term prediction. - Highlights: • A novel predictive modeling method is proposed for long-term wind speed forecasting. • Gaussian mixture copula model is estimated to characterize the multi-seasonality. • Localized Gaussian process regression models can deal with the random uncertainty. • Multiple GPR models are integrated through Bayesian inference strategy. • The proposed approach shows higher prediction accuracy and reliability

  16. Reconstruction of missing daily streamflow data using dynamic regression models

    Science.gov (United States)

    Tencaliec, Patricia; Favre, Anne-Catherine; Prieur, Clémentine; Mathevet, Thibault

    2015-12-01

    River discharge is one of the most important quantities in hydrology. It provides fundamental records for water resources management and climate change monitoring. Even very short data-gaps in this information can cause extremely different analysis outputs. Therefore, reconstructing missing data of incomplete data sets is an important step regarding the performance of the environmental models, engineering, and research applications, thus it presents a great challenge. The objective of this paper is to introduce an effective technique for reconstructing missing daily discharge data when one has access to only daily streamflow data. The proposed procedure uses a combination of regression and autoregressive integrated moving average models (ARIMA) called dynamic regression model. This model uses the linear relationship between neighbor and correlated stations and then adjusts the residual term by fitting an ARIMA structure. Application of the model to eight daily streamflow data for the Durance river watershed showed that the model yields reliable estimates for the missing data in the time series. Simulation studies were also conducted to evaluate the performance of the procedure.

  17. Integration of motion energy from overlapping random background noise increases perceived speed of coherently moving stimuli.

    Science.gov (United States)

    Chuang, Jason; Ausloos, Emily C; Schwebach, Courtney A; Huang, Xin

    2016-12-01

    The perception of visual motion can be profoundly influenced by visual context. To gain insight into how the visual system represents motion speed, we investigated how a background stimulus that did not move in a net direction influenced the perceived speed of a center stimulus. Visual stimuli were two overlapping random-dot patterns. The center stimulus moved coherently in a fixed direction, whereas the background stimulus moved randomly. We found that human subjects perceived the speed of the center stimulus to be significantly faster than its veridical speed when the background contained motion noise. Interestingly, the perceived speed was tuned to the noise level of the background. When the speed of the center stimulus was low, the highest perceived speed was reached when the background had a low level of motion noise. As the center speed increased, the peak perceived speed was reached at a progressively higher background noise level. The effect of speed overestimation required the center stimulus to overlap with the background. Increasing the background size within a certain range enhanced the effect, suggesting spatial integration. The speed overestimation was significantly reduced or abolished when the center stimulus and the background stimulus had different colors, or when they were placed at different depths. When the center- and background-stimuli were perceptually separable, speed overestimation was correlated with perceptual similarity between the center- and background-stimuli. These results suggest that integration of motion energy from random motion noise has a significant impact on speed perception. Our findings put new constraints on models regarding the neural basis of speed perception. Copyright © 2016 the American Physiological Society.

  18. Abstract Expression Grammar Symbolic Regression

    Science.gov (United States)

    Korns, Michael F.

    This chapter examines the use of Abstract Expression Grammars to perform the entire Symbolic Regression process without the use of Genetic Programming per se. The techniques explored produce a symbolic regression engine which has absolutely no bloat, which allows total user control of the search space and output formulas, which is faster, and more accurate than the engines produced in our previous papers using Genetic Programming. The genome is an all vector structure with four chromosomes plus additional epigenetic and constraint vectors, allowing total user control of the search space and the final output formulas. A combination of specialized compiler techniques, genetic algorithms, particle swarm, aged layered populations, plus discrete and continuous differential evolution are used to produce an improved symbolic regression sytem. Nine base test cases, from the literature, are used to test the improvement in speed and accuracy. The improved results indicate that these techniques move us a big step closer toward future industrial strength symbolic regression systems.

  19. Time series regression model for infectious disease and weather.

    Science.gov (United States)

    Imai, Chisato; Armstrong, Ben; Chalabi, Zaid; Mangtani, Punam; Hashizume, Masahiro

    2015-10-01

    Time series regression has been developed and long used to evaluate the short-term associations of air pollution and weather with mortality or morbidity of non-infectious diseases. The application of the regression approaches from this tradition to infectious diseases, however, is less well explored and raises some new issues. We discuss and present potential solutions for five issues often arising in such analyses: changes in immune population, strong autocorrelations, a wide range of plausible lag structures and association patterns, seasonality adjustments, and large overdispersion. The potential approaches are illustrated with datasets of cholera cases and rainfall from Bangladesh and influenza and temperature in Tokyo. Though this article focuses on the application of the traditional time series regression to infectious diseases and weather factors, we also briefly introduce alternative approaches, including mathematical modeling, wavelet analysis, and autoregressive integrated moving average (ARIMA) models. Modifications proposed to standard time series regression practice include using sums of past cases as proxies for the immune population, and using the logarithm of lagged disease counts to control autocorrelation due to true contagion, both of which are motivated from "susceptible-infectious-recovered" (SIR) models. The complexity of lag structures and association patterns can often be informed by biological mechanisms and explored by using distributed lag non-linear models. For overdispersed models, alternative distribution models such as quasi-Poisson and negative binomial should be considered. Time series regression can be used to investigate dependence of infectious diseases on weather, but may need modifying to allow for features specific to this context. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  20. Failure and reliability prediction by support vector machines regression of time series data

    International Nuclear Information System (INIS)

    Chagas Moura, Marcio das; Zio, Enrico; Lins, Isis Didier; Droguett, Enrique

    2011-01-01

    Support Vector Machines (SVMs) are kernel-based learning methods, which have been successfully adopted for regression problems. However, their use in reliability applications has not been widely explored. In this paper, a comparative analysis is presented in order to evaluate the SVM effectiveness in forecasting time-to-failure and reliability of engineered components based on time series data. The performance on literature case studies of SVM regression is measured against other advanced learning methods such as the Radial Basis Function, the traditional MultiLayer Perceptron model, Box-Jenkins autoregressive-integrated-moving average and the Infinite Impulse Response Locally Recurrent Neural Networks. The comparison shows that in the analyzed cases, SVM outperforms or is comparable to other techniques. - Highlights: → Realistic modeling of reliability demands complex mathematical formulations. → SVM is proper when the relation input/output is unknown or very costly to be obtained. → Results indicate the potential of SVM for reliability time series prediction. → Reliability estimates support the establishment of adequate maintenance strategies.

  1. Classification and regression trees

    CERN Document Server

    Breiman, Leo; Olshen, Richard A; Stone, Charles J

    1984-01-01

    The methodology used to construct tree structured rules is the focus of this monograph. Unlike many other statistical procedures, which moved from pencil and paper to calculators, this text's use of trees was unthinkable before computers. Both the practical and theoretical sides have been developed in the authors' study of tree methods. Classification and Regression Trees reflects these two sides, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.

  2. Integrating travel behavior with land use regression to estimate dynamic air pollution exposure in Hong Kong.

    Science.gov (United States)

    Tang, Robert; Tian, Linwei; Thach, Thuan-Quoc; Tsui, Tsz Him; Brauer, Michael; Lee, Martha; Allen, Ryan; Yuchi, Weiran; Lai, Poh-Chin; Wong, Paulina; Barratt, Benjamin

    2018-04-01

    Epidemiological studies typically use subjects' residential address to estimate individuals' air pollution exposure. However, in reality this exposure is rarely static as people move from home to work/study locations and commute during the day. Integrating mobility and time-activity data may reduce errors and biases, thereby improving estimates of health risks. To incorporate land use regression with movement and building infiltration data to estimate time-weighted air pollution exposures stratified by age, sex, and employment status for population subgroups in Hong Kong. A large population-representative survey (N = 89,385) was used to characterize travel behavior, and derive time-activity pattern for each subject. Infiltration factors calculated from indoor/outdoor monitoring campaigns were used to estimate micro-environmental concentrations. We evaluated dynamic and static (residential location-only) exposures in a staged modeling approach to quantify effects of each component. Higher levels of exposures were found for working adults and students due to increased mobility. Compared to subjects aged 65 or older, exposures to PM 2.5 , BC, and NO 2 were 13%, 39% and 14% higher, respectively for subjects aged below 18, and 3%, 18% and 11% higher, respectively for working adults. Exposures of females were approximately 4% lower than those of males. Dynamic exposures were around 20% lower than ambient exposures at residential addresses. The incorporation of infiltration and mobility increased heterogeneity in population exposure and allowed identification of highly exposed groups. The use of ambient concentrations may lead to exposure misclassification which introduces bias, resulting in lower effect estimates than 'true' exposures. Copyright © 2018 Elsevier Ltd. All rights reserved.

  3. Semiparametric regression during 2003–2007

    KAUST Repository

    Ruppert, David; Wand, M.P.; Carroll, Raymond J.

    2009-01-01

    Semiparametric regression is a fusion between parametric regression and nonparametric regression that integrates low-rank penalized splines, mixed model and hierarchical Bayesian methodology – thus allowing more streamlined handling of longitudinal and spatial correlation. We review progress in the field over the five-year period between 2003 and 2007. We find semiparametric regression to be a vibrant field with substantial involvement and activity, continual enhancement and widespread application.

  4. 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.

  5. Sparse multivariate factor analysis regression models and its applications to integrative genomics analysis.

    Science.gov (United States)

    Zhou, Yan; Wang, Pei; Wang, Xianlong; Zhu, Ji; Song, Peter X-K

    2017-01-01

    The multivariate regression model is a useful tool to explore complex associations between two kinds of molecular markers, which enables the understanding of the biological pathways underlying disease etiology. For a set of correlated response variables, accounting for such dependency can increase statistical power. Motivated by integrative genomic data analyses, we propose a new methodology-sparse multivariate factor analysis regression model (smFARM), in which correlations of response variables are assumed to follow a factor analysis model with latent factors. This proposed method not only allows us to address the challenge that the number of association parameters is larger than the sample size, but also to adjust for unobserved genetic and/or nongenetic factors that potentially conceal the underlying response-predictor associations. The proposed smFARM is implemented by the EM algorithm and the blockwise coordinate descent algorithm. The proposed methodology is evaluated and compared to the existing methods through extensive simulation studies. Our results show that accounting for latent factors through the proposed smFARM can improve sensitivity of signal detection and accuracy of sparse association map estimation. We illustrate smFARM by two integrative genomics analysis examples, a breast cancer dataset, and an ovarian cancer dataset, to assess the relationship between DNA copy numbers and gene expression arrays to understand genetic regulatory patterns relevant to the disease. We identify two trans-hub regions: one in cytoband 17q12 whose amplification influences the RNA expression levels of important breast cancer genes, and the other in cytoband 9q21.32-33, which is associated with chemoresistance in ovarian cancer. © 2016 WILEY PERIODICALS, INC.

  6. 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...

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

    Directory of Open Access Journals (Sweden)

    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%.

  8. Marital status integration and suicide: A meta-analysis and meta-regression.

    Science.gov (United States)

    Kyung-Sook, Woo; SangSoo, Shin; Sangjin, Shin; Young-Jeon, Shin

    2018-01-01

    Marital status is an index of the phenomenon of social integration within social structures and has long been identified as an important predictor suicide. However, previous meta-analyses have focused only on a particular marital status, or not sufficiently explored moderators. A meta-analysis of observational studies was conducted to explore the relationships between marital status and suicide and to understand the important moderating factors in this association. Electronic databases were searched to identify studies conducted between January 1, 2000 and June 30, 2016. We performed a meta-analysis, subgroup analysis, and meta-regression of 170 suicide risk estimates from 36 publications. Using random effects model with adjustment for covariates, the study found that the suicide risk for non-married versus married was OR = 1.92 (95% CI: 1.75-2.12). The suicide risk was higher for non-married individuals aged analysis by gender, non-married men exhibited a greater risk of suicide than their married counterparts in all sub-analyses, but women aged 65 years or older showed no significant association between marital status and suicide. The suicide risk in divorced individuals was higher than for non-married individuals in both men and women. The meta-regression showed that gender, age, and sample size affected between-study variation. The results of the study indicated that non-married individuals have an aggregate higher suicide risk than married ones. In addition, gender and age were confirmed as important moderating factors in the relationship between marital status and suicide. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. 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

  10. 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.

  11. 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.

  12. Ethnicity at the individual and neighborhood level as an explanation for moving out of the neighborhood

    NARCIS (Netherlands)

    Schaake, K.; Burgers, J.; Mulder, C.H.

    2010-01-01

    We address the influence of both the ethnic composition of the neighborhood and the ethnicity of individual residents on moving out of neighborhoods in the Netherlands. Using the Housing Research Netherlands survey and multinomial logistic regression analyses of moving out versus not moving or

  13. Forecasting systems reliability based on support vector regression with genetic algorithms

    International Nuclear Information System (INIS)

    Chen, K.-Y.

    2007-01-01

    This study applies a novel neural-network technique, support vector regression (SVR), to forecast reliability in engine systems. The aim of this study is to examine the feasibility of SVR in systems reliability prediction by comparing it with the existing neural-network approaches and the autoregressive integrated moving average (ARIMA) model. To build an effective SVR model, SVR's parameters must be set carefully. This study proposes a novel approach, known as GA-SVR, which searches for SVR's optimal parameters using real-value genetic algorithms, and then adopts the optimal parameters to construct the SVR models. A real reliability data for 40 suits of turbochargers were employed as the data set. The experimental results demonstrate that SVR outperforms the existing neural-network approaches and the traditional ARIMA models based on the normalized root mean square error and mean absolute percentage error

  14. Nonlinear regression and ARIMA models for precipitation chemistry in East Central Florida from 1978 to 1997

    International Nuclear Information System (INIS)

    Nickerson, David M.; Madsen, Brooks C.

    2005-01-01

    Continuous monitoring of precipitation in East Central Florida has occurred since 1978 at a sampling site located on the University of Central Florida (UCF) campus. Monthly volume-weighted average (VWA) concentration for several major analytes that are present in precipitation samples was calculated from samples collected daily. Monthly VWA concentration and wet deposition of H + , NH 4 + , Ca 2+ , Mg 2+ , NO 3 - , Cl - and SO 4 2- were evaluated by a nonlinear regression (NLR) model that considered 10-year data (from 1978 to 1987) and 20-year data (from 1978 to 1997). Little change in the NLR parameter estimates was indicated among the 10-year and 20-year evaluations except for general decreases in the predicted trends from the 10-year to the 20-year fits. Box-Jenkins autoregressive integrated moving average (ARIMA) models with linear trend were considered as an alternative to the NLR models for these data. The NLR and ARIMA model forecasts for 1998 were compared to the actual 1998 data. For monthly VWA concentration values, the two models gave similar results. For the wet deposition values, the ARIMA models performed considerably better. - Autoregressive integrated moving average models of precipitation data are an improvement over nonlinear models for the prediction of precipitation chemistry composition

  15. Application of semi-empirical modeling and non-linear regression to unfolding fast neutron spectra from integral reaction rate data

    International Nuclear Information System (INIS)

    Harker, Y.D.

    1976-01-01

    A semi-empirical analytical expression representing a fast reactor neutron spectrum has been developed. This expression was used in a non-linear regression computer routine to obtain from measured multiple foil integral reaction data the neutron spectrum inside the Coupled Fast Reactivity Measurement Facility. In this application six parameters in the analytical expression for neutron spectrum were adjusted in the non-linear fitting process to maximize consistency between calculated and measured integral reaction rates for a set of 15 dosimetry detector foils. In two-thirds of the observations the calculated integral agreed with its respective measured value to within the experimental standard deviation, and in all but one case agreement within two standard deviations was obtained. Based on this quality of fit the estimated 70 to 75 percent confidence intervals for the derived spectrum are 10 to 20 percent for the energy range 100 eV to 1 MeV, 10 to 50 percent for 1 MeV to 10 MeV and 50 to 90 percent for 10 MeV to 18 MeV. The analytical model has demonstrated a flexibility to describe salient features of neutron spectra of the fast reactor type. The use of regression analysis with this model has produced a stable method to derive neutron spectra from a limited amount of integral data

  16. Logistic Regression Modeling of Diminishing Manufacturing Sources for Integrated Circuits

    National Research Council Canada - National Science Library

    Gravier, Michael

    1999-01-01

    .... The research identified logistic regression as a powerful tool for analysis of DMSMS and further developed twenty models attempting to identify the "best" way to model and predict DMSMS using logistic regression...

  17. Precision Interval Estimation of the Response Surface by Means of an Integrated Algorithm of Neural Network and Linear Regression

    Science.gov (United States)

    Lo, Ching F.

    1999-01-01

    The integration of Radial Basis Function Networks and Back Propagation Neural Networks with the Multiple Linear Regression has been accomplished to map nonlinear response surfaces over a wide range of independent variables in the process of the Modem Design of Experiments. The integrated method is capable to estimate the precision intervals including confidence and predicted intervals. The power of the innovative method has been demonstrated by applying to a set of wind tunnel test data in construction of response surface and estimation of precision interval.

  18. DO DYNAMIC NEURAL NETWORKS STAND A BETTER CHANCE IN FRACTIONALLY INTEGRATED PROCESS FORECASTING?

    Directory of Open Access Journals (Sweden)

    Majid Delavari

    2013-04-01

    Full Text Available The main purpose of the present study was to investigate the capabilities of two generations of models such as those based on dynamic neural network (e.g., Nonlinear Neural network Auto Regressive or NNAR model and a regressive (Auto Regressive Fractionally Integrated Moving Average model which is based on Fractional Integration Approach in forecasting daily data related to the return index of Tehran Stock Exchange (TSE. In order to compare these models under similar conditions, Mean Square Error (MSE and also Root Mean Square Error (RMSE were selected as criteria for the models’ simulated out-of-sample forecasting performance. Besides, fractal markets hypothesis was examined and according to the findings, fractal structure was confirmed to exist in the time series under investigation. Another finding of the study was that dynamic artificial neural network model had the best performance in out-of-sample forecasting based on the criteria introduced for calculating forecasting error in comparison with the ARFIMA model.

  19. Ridge Regression Signal Processing

    Science.gov (United States)

    Kuhl, Mark R.

    1990-01-01

    The introduction of the Global Positioning System (GPS) into the National Airspace System (NAS) necessitates the development of Receiver Autonomous Integrity Monitoring (RAIM) techniques. In order to guarantee a certain level of integrity, a thorough understanding of modern estimation techniques applied to navigational problems is required. The extended Kalman filter (EKF) is derived and analyzed under poor geometry conditions. It was found that the performance of the EKF is difficult to predict, since the EKF is designed for a Gaussian environment. A novel approach is implemented which incorporates ridge regression to explain the behavior of an EKF in the presence of dynamics under poor geometry conditions. The basic principles of ridge regression theory are presented, followed by the derivation of a linearized recursive ridge estimator. Computer simulations are performed to confirm the underlying theory and to provide a comparative analysis of the EKF and the recursive ridge estimator.

  20. Current control by a homopolar machine with moving brushes

    International Nuclear Information System (INIS)

    Vogel, H.

    1978-01-01

    The equation for TNS Doublet's E-coil circuit with moving brush homopolar machine is integrated in the flux of the homopolar for a monotonically increasing current function extending beyond the current reversal into the burn period. The results show that the moving brush feature is not useful for controlling the burn

  1. Integrative analysis of multiple diverse omics datasets by sparse group multitask regression

    Directory of Open Access Journals (Sweden)

    Dongdong eLin

    2014-10-01

    Full Text Available A variety of high throughput genome-wide assays enable the exploration of genetic risk factors underlying complex traits. Although these studies have remarkable impact on identifying susceptible biomarkers, they suffer from issues such as limited sample size and low reproducibility. Combining individual studies of different genetic levels/platforms has the promise to improve the power and consistency of biomarker identification. In this paper, we propose a novel integrative method, namely sparse group multitask regression, for integrating diverse omics datasets, platforms and populations to identify risk genes/factors of complex diseases. This method combines multitask learning with sparse group regularization, which will: 1 treat the biomarker identification in each single study as a task and then combine them by multitask learning; 2 group variables from all studies for identifying significant genes; 3 enforce sparse constraint on groups of variables to overcome the ‘small sample, but large variables’ problem. We introduce two sparse group penalties: sparse group lasso and sparse group ridge in our multitask model, and provide an effective algorithm for each model. In addition, we propose a significance test for the identification of potential risk genes. Two simulation studies are performed to evaluate the performance of our integrative method by comparing it with conventional meta-analysis method. The results show that our sparse group multitask method outperforms meta-analysis method significantly. In an application to our osteoporosis studies, 7 genes are identified as significant genes by our method and are found to have significant effects in other three independent studies for validation. The most significant gene SOD2 has been identified in our previous osteoporosis study involving the same expression dataset. Several other genes such as TREML2, HTR1E and GLO1 are shown to be novel susceptible genes for osteoporosis, as confirmed

  2. Bayesian logistic regression analysis

    NARCIS (Netherlands)

    Van Erp, H.R.N.; Van Gelder, P.H.A.J.M.

    2012-01-01

    In this paper we present a Bayesian logistic regression analysis. It is found that if one wishes to derive the posterior distribution of the probability of some event, then, together with the traditional Bayes Theorem and the integrating out of nuissance parameters, the Jacobian transformation is an

  3. An analytical boundary element integral approach to track the boundary of a moving cavity using electrical impedance tomography

    International Nuclear Information System (INIS)

    Khambampati, Anil Kumar; Kim, Sin; Lee, Bo An; Kim, Kyung Youn

    2012-01-01

    This paper is about locating the boundary of a moving cavity within a homogeneous background from the voltage measurements recorded on the outer boundary. An inverse boundary problem of a moving cavity is formulated by considering a two-phase vapor–liquid flow in a pipe. The conductivity of the flow components (vapor and liquid) is assumed to be constant and known a priori while the location and shape of the inclusion (vapor) are the unknowns to be estimated. The forward problem is solved using the boundary element method (BEM) with the integral equations solved analytically. A special situation is considered such that the cavity changes its location and shape during the time taken to acquire a full set of independent measurement data. The boundary of a cavity is assumed to be elliptic and is parameterized with Fourier series. The inverse problem is treated as a state estimation problem with the Fourier coefficients that represent the center and radii of the cavity as the unknowns to be estimated. An extended Kalman filter (EKF) is used as an inverse algorithm to estimate the time varying Fourier coefficients. Numerical experiments are shown to evaluate the performance of the proposed method. Through the results, it can be noticed that the proposed BEM with EKF method is successful in estimating the boundary of a moving cavity. (paper)

  4. Experimental Verification of a Vehicle Localization based on Moving Horizon Estimation Integrating LRS and Odometry

    International Nuclear Information System (INIS)

    Sakaeta, Kuniyuki; Nonaka, Kenichiro; Sekiguchi, Kazuma

    2016-01-01

    Localization is an important function for the robots to complete various tasks. For localization, both internal and external sensors are used generally. The odometry is widely used as the method based on the internal sensors, but it suffers from cumulative errors. In the method using the laser range sensor (LRS) which is a kind of external sensor, the estimation accuracy is affected by the number of available measurement data. In our previous study, we applied moving horizon estimation (MHE) to the vehicle localization for integrating the LRS measurement data and the odometry information where the weightings of them are balanced relatively adapting to the number of the available LRS measurement data. In this paper, the effectiveness of the proposed localization method is verified through both numerical simulations and experiments using a 1/10 scale vehicle. The verification is conducted in the situations where the vehicle position cannot be localized uniquely on a certain direction using the LRS measurement data only. We achieve accurate localization even in such a situation by integrating the odometry and LRS based on MHE. We also show the superiority of the method through comparisons with a method using extended Kalman filter (EKF). (paper)

  5. A robust combination approach for short-term wind speed forecasting and analysis – Combination of the ARIMA (Autoregressive Integrated Moving Average), ELM (Extreme Learning Machine), SVM (Support Vector Machine) and LSSVM (Least Square SVM) forecasts using a GPR (Gaussian Process Regression) model

    International Nuclear Information System (INIS)

    Wang, Jianzhou; Hu, Jianming

    2015-01-01

    With the increasing importance of wind power as a component of power systems, the problems induced by the stochastic and intermittent nature of wind speed have compelled system operators and researchers to search for more reliable techniques to forecast wind speed. This paper proposes a combination model for probabilistic short-term wind speed forecasting. In this proposed hybrid approach, EWT (Empirical Wavelet Transform) is employed to extract meaningful information from a wind speed series by designing an appropriate wavelet filter bank. The GPR (Gaussian Process Regression) model is utilized to combine independent forecasts generated by various forecasting engines (ARIMA (Autoregressive Integrated Moving Average), ELM (Extreme Learning Machine), SVM (Support Vector Machine) and LSSVM (Least Square SVM)) in a nonlinear way rather than the commonly used linear way. The proposed approach provides more probabilistic information for wind speed predictions besides improving the forecasting accuracy for single-value predictions. The effectiveness of the proposed approach is demonstrated with wind speed data from two wind farms in China. The results indicate that the individual forecasting engines do not consistently forecast short-term wind speed for the two sites, and the proposed combination method can generate a more reliable and accurate forecast. - Highlights: • The proposed approach can make probabilistic modeling for wind speed series. • The proposed approach adapts to the time-varying characteristic of the wind speed. • The hybrid approach can extract the meaningful components from the wind speed series. • The proposed method can generate adaptive, reliable and more accurate forecasting results. • The proposed model combines four independent forecasting engines in a nonlinear way.

  6. Moving the boundary between wavelength resources in optical packet and circuit integrated ring network.

    Science.gov (United States)

    Furukawa, Hideaki; Miyazawa, Takaya; Wada, Naoya; Harai, Hiroaki

    2014-01-13

    Optical packet and circuit integrated (OPCI) networks provide both optical packet switching (OPS) and optical circuit switching (OCS) links on the same physical infrastructure using a wavelength multiplexing technique in order to deal with best-effort services and quality-guaranteed services. To immediately respond to changes in user demand for OPS and OCS links, OPCI networks should dynamically adjust the amount of wavelength resources for each link. We propose a resource-adjustable hybrid optical packet/circuit switch and transponder. We also verify that distributed control of resource adjustments can be applied to the OPCI ring network testbed we developed. In cooperation with the resource adjustment mechanism and the hybrid switch and transponder, we demonstrate that automatically allocating a shared resource and moving the wavelength resource boundary between OPS and OCS links can be successfully executed, depending on the number of optical paths in use.

  7. Dynamic Regression Intervention Modeling for the Malaysian Daily Load

    Directory of Open Access Journals (Sweden)

    Fadhilah Abdrazak

    2014-05-01

    Full Text Available Malaysia is a unique country due to having both fixed and moving holidays.  These moving holidays may overlap with other fixed holidays and therefore, increase the complexity of the load forecasting activities. The errors due to holidays’ effects in the load forecasting are known to be higher than other factors.  If these effects can be estimated and removed, the behavior of the series could be better viewed.  Thus, the aim of this paper is to improve the forecasting errors by using a dynamic regression model with intervention analysis.   Based on the linear transfer function method, a daily load model consists of either peak or average is developed.  The developed model outperformed the seasonal ARIMA model in estimating the fixed and moving holidays’ effects and achieved a smaller Mean Absolute Percentage Error (MAPE in load forecast.

  8. Time-localized wavelet multiple regression and correlation

    Science.gov (United States)

    Fernández-Macho, Javier

    2018-02-01

    This paper extends wavelet methodology to handle comovement dynamics of multivariate time series via moving weighted regression on wavelet coefficients. The concept of wavelet local multiple correlation is used to produce one single set of multiscale correlations along time, in contrast with the large number of wavelet correlation maps that need to be compared when using standard pairwise wavelet correlations with rolling windows. Also, the spectral properties of weight functions are investigated and it is argued that some common time windows, such as the usual rectangular rolling window, are not satisfactory on these grounds. The method is illustrated with a multiscale analysis of the comovements of Eurozone stock markets during this century. It is shown how the evolution of the correlation structure in these markets has been far from homogeneous both along time and across timescales featuring an acute divide across timescales at about the quarterly scale. At longer scales, evidence from the long-term correlation structure can be interpreted as stable perfect integration among Euro stock markets. On the other hand, at intramonth and intraweek scales, the short-term correlation structure has been clearly evolving along time, experiencing a sharp increase during financial crises which may be interpreted as evidence of financial 'contagion'.

  9. Retrospective feasibility study of simultaneous integrated boost in cervical cancer using Tomotherapy: the impact of organ motion and tumor regression.

    Science.gov (United States)

    Herrera, Fernanda G; Callaway, Sharon; Delikgoz-Soykut, Ela; Coskun, Mehtap; Porta, Laetitia; Meuwly, Jean-Yves; Soares-Rodrigues, Joao; Heym, Leonie; Moeckli, Raphael; Ozsahin, Mahmut

    2013-01-03

    Whole pelvis intensity modulated radiotherapy (IMRT) is increasingly being used to treat cervical cancer aiming to reduce side effects. Encouraged by this, some groups have proposed the use of simultaneous integrated boost (SIB) to target the tumor, either to get a higher tumoricidal effect or to replace brachytherapy. Nevertheless, physiological organ movement and rapid tumor regression throughout treatment might substantially reduce any benefit of this approach. To evaluate the clinical target volume - simultaneous integrated boost (CTV-SIB) regression and motion during chemo-radiotherapy (CRT) for cervical cancer, and to monitor treatment progress dosimetrically and volumetrically to ensure treatment goals are met. Ten patients treated with standard doses of CRT and brachytherapy were retrospectively re-planned using a helical Tomotherapy - SIB technique for the hypothetical scenario of this feasibility study. Target and organs at risk (OAR) were contoured on deformable fused planning-computed tomography and megavoltage computed tomography images. The CTV-SIB volume regression was determined. The center of mass (CM) was used to evaluate the degree of motion. The Dice's similarity coefficient (DSC) was used to assess the spatial overlap of CTV-SIBs between scans. A cumulative dose-volume histogram modeled estimated delivered doses. The CTV-SIB relative reduction was between 31 and 70%. The mean maximum CM change was 12.5, 9, and 3 mm in the superior-inferior, antero-posterior, and right-left dimensions, respectively. The CTV-SIB-DSC approached 1 in the first week of treatment, indicating almost perfect overlap. CTV-SIB-DSC regressed linearly during therapy, and by the end of treatment was 0.5, indicating 50% discordance. Two patients received less than 95% of the prescribed dose. Much higher doses to the OAR were observed. A multiple regression analysis showed a significant interaction between CTV-SIB reduction and OAR dose increase. The CTV-SIB had important

  10. Retrospective feasibility study of simultaneous integrated boost in cervical cancer using tomotherapy: the impact of organ motion and tumor regression

    International Nuclear Information System (INIS)

    Herrera, Fernanda G; Ozsahin, Mahmut; Callaway, Sharon; Delikgoz-Soykut, Ela; Coskun, Mehtap; Porta, Laetitia; Meuwly, Jean-Yves; Soares-Rodrigues, Joao; Heym, Leonie; Moeckli, Raphael

    2013-01-01

    Whole pelvis intensity modulated radiotherapy (IMRT) is increasingly being used to treat cervical cancer aiming to reduce side effects. Encouraged by this, some groups have proposed the use of simultaneous integrated boost (SIB) to target the tumor, either to get a higher tumoricidal effect or to replace brachytherapy. Nevertheless, physiological organ movement and rapid tumor regression throughout treatment might substantially reduce any benefit of this approach. To evaluate the clinical target volume - simultaneous integrated boost (CTV-SIB) regression and motion during chemo-radiotherapy (CRT) for cervical cancer, and to monitor treatment progress dosimetrically and volumetrically to ensure treatment goals are met. Ten patients treated with standard doses of CRT and brachytherapy were retrospectively re-planned using a helical Tomotherapy - SIB technique for the hypothetical scenario of this feasibility study. Target and organs at risk (OAR) were contoured on deformable fused planning-computed tomography and megavoltage computed tomography images. The CTV-SIB volume regression was determined. The center of mass (CM) was used to evaluate the degree of motion. The Dice’s similarity coefficient (DSC) was used to assess the spatial overlap of CTV-SIBs between scans. A cumulative dose-volume histogram modeled estimated delivered doses. The CTV-SIB relative reduction was between 31 and 70%. The mean maximum CM change was 12.5, 9, and 3 mm in the superior-inferior, antero-posterior, and right-left dimensions, respectively. The CTV-SIB-DSC approached 1 in the first week of treatment, indicating almost perfect overlap. CTV-SIB-DSC regressed linearly during therapy, and by the end of treatment was 0.5, indicating 50% discordance. Two patients received less than 95% of the prescribed dose. Much higher doses to the OAR were observed. A multiple regression analysis showed a significant interaction between CTV-SIB reduction and OAR dose increase. The CTV-SIB had important

  11. Retrospective feasibility study of simultaneous integrated boost in cervical cancer using tomotherapy: the impact of organ motion and tumor regression

    Directory of Open Access Journals (Sweden)

    Herrera Fernanda G

    2013-01-01

    Full Text Available Abstract Background Whole pelvis intensity modulated radiotherapy (IMRT is increasingly being used to treat cervical cancer aiming to reduce side effects. Encouraged by this, some groups have proposed the use of simultaneous integrated boost (SIB to target the tumor, either to get a higher tumoricidal effect or to replace brachytherapy. Nevertheless, physiological organ movement and rapid tumor regression throughout treatment might substantially reduce any benefit of this approach. Purpose To evaluate the clinical target volume - simultaneous integrated boost (CTV-SIB regression and motion during chemo-radiotherapy (CRT for cervical cancer, and to monitor treatment progress dosimetrically and volumetrically to ensure treatment goals are met. Methods and materials Ten patients treated with standard doses of CRT and brachytherapy were retrospectively re-planned using a helical Tomotherapy - SIB technique for the hypothetical scenario of this feasibility study. Target and organs at risk (OAR were contoured on deformable fused planning-computed tomography and megavoltage computed tomography images. The CTV-SIB volume regression was determined. The center of mass (CM was used to evaluate the degree of motion. The Dice’s similarity coefficient (DSC was used to assess the spatial overlap of CTV-SIBs between scans. A cumulative dose-volume histogram modeled estimated delivered doses. Results The CTV-SIB relative reduction was between 31 and 70%. The mean maximum CM change was 12.5, 9, and 3 mm in the superior-inferior, antero-posterior, and right-left dimensions, respectively. The CTV-SIB-DSC approached 1 in the first week of treatment, indicating almost perfect overlap. CTV-SIB-DSC regressed linearly during therapy, and by the end of treatment was 0.5, indicating 50% discordance. Two patients received less than 95% of the prescribed dose. Much higher doses to the OAR were observed. A multiple regression analysis showed a significant interaction

  12. Modeling Fire Occurrence at the City Scale: A Comparison between Geographically Weighted Regression and Global Linear Regression.

    Science.gov (United States)

    Song, Chao; Kwan, Mei-Po; Zhu, Jiping

    2017-04-08

    An increasing number of fires are occurring with the rapid development of cities, resulting in increased risk for human beings and the environment. This study compares geographically weighted regression-based models, including geographically weighted regression (GWR) and geographically and temporally weighted regression (GTWR), which integrates spatial and temporal effects and global linear regression models (LM) for modeling fire risk at the city scale. The results show that the road density and the spatial distribution of enterprises have the strongest influences on fire risk, which implies that we should focus on areas where roads and enterprises are densely clustered. In addition, locations with a large number of enterprises have fewer fire ignition records, probably because of strict management and prevention measures. A changing number of significant variables across space indicate that heterogeneity mainly exists in the northern and eastern rural and suburban areas of Hefei city, where human-related facilities or road construction are only clustered in the city sub-centers. GTWR can capture small changes in the spatiotemporal heterogeneity of the variables while GWR and LM cannot. An approach that integrates space and time enables us to better understand the dynamic changes in fire risk. Thus governments can use the results to manage fire safety at the city scale.

  13. Inflation, Forecast Intervals and Long Memory Regression Models

    NARCIS (Netherlands)

    C.S. Bos (Charles); Ph.H.B.F. Franses (Philip Hans); M. Ooms (Marius)

    2001-01-01

    textabstractWe examine recursive out-of-sample forecasting of monthly postwar U.S. core inflation and log price levels. We use the autoregressive fractionally integrated moving average model with explanatory variables (ARFIMAX). Our analysis suggests a significant explanatory power of leading

  14. Inflation, Forecast Intervals and Long Memory Regression Models

    NARCIS (Netherlands)

    Ooms, M.; Bos, C.S.; Franses, P.H.

    2003-01-01

    We examine recursive out-of-sample forecasting of monthly postwar US core inflation and log price levels. We use the autoregressive fractionally integrated moving average model with explanatory variables (ARFIMAX). Our analysis suggests a significant explanatory power of leading indicators

  15. Integration of association statistics over genomic regions using Bayesian adaptive regression splines

    Directory of Open Access Journals (Sweden)

    Zhang Xiaohua

    2003-11-01

    Full Text Available Abstract In the search for genetic determinants of complex disease, two approaches to association analysis are most often employed, testing single loci or testing a small group of loci jointly via haplotypes for their relationship to disease status. It is still debatable which of these approaches is more favourable, and under what conditions. The former has the advantage of simplicity but suffers severely when alleles at the tested loci are not in linkage disequilibrium (LD with liability alleles; the latter should capture more of the signal encoded in LD, but is far from simple. The complexity of haplotype analysis could be especially troublesome for association scans over large genomic regions, which, in fact, is becoming the standard design. For these reasons, the authors have been evaluating statistical methods that bridge the gap between single-locus and haplotype-based tests. In this article, they present one such method, which uses non-parametric regression techniques embodied by Bayesian adaptive regression splines (BARS. For a set of markers falling within a common genomic region and a corresponding set of single-locus association statistics, the BARS procedure integrates these results into a single test by examining the class of smooth curves consistent with the data. The non-parametric BARS procedure generally finds no signal when no liability allele exists in the tested region (ie it achieves the specified size of the test and it is sensitive enough to pick up signals when a liability allele is present. The BARS procedure provides a robust and potentially powerful alternative to classical tests of association, diminishes the multiple testing problem inherent in those tests and can be applied to a wide range of data types, including genotype frequencies estimated from pooled samples.

  16. Direct integral linear least square regression method for kinetic evaluation of hepatobiliary scintigraphy

    International Nuclear Information System (INIS)

    Shuke, Noriyuki

    1991-01-01

    In hepatobiliary scintigraphy, kinetic model analysis, which provides kinetic parameters like hepatic extraction or excretion rate, have been done for quantitative evaluation of liver function. In this analysis, unknown model parameters are usually determined using nonlinear least square regression method (NLS method) where iterative calculation and initial estimate for unknown parameters are required. As a simple alternative to NLS method, direct integral linear least square regression method (DILS method), which can determine model parameters by a simple calculation without initial estimate, is proposed, and tested the applicability to analysis of hepatobiliary scintigraphy. In order to see whether DILS method could determine model parameters as good as NLS method, or to determine appropriate weight for DILS method, simulated theoretical data based on prefixed parameters were fitted to 1 compartment model using both DILS method with various weightings and NLS method. The parameter values obtained were then compared with prefixed values which were used for data generation. The effect of various weights on the error of parameter estimate was examined, and inverse of time was found to be the best weight to make the error minimum. When using this weight, DILS method could give parameter values close to those obtained by NLS method and both parameter values were very close to prefixed values. With appropriate weighting, the DILS method could provide reliable parameter estimate which is relatively insensitive to the data noise. In conclusion, the DILS method could be used as a simple alternative to NLS method, providing reliable parameter estimate. (author)

  17. Integrated knowledge translation: digging deeper, moving forward.

    Science.gov (United States)

    Kothari, Anita; Wathen, C Nadine

    2017-06-01

    Integrated knowledge translation has risen in popularity as a solution to the underuse of research in policy and practice settings. It engages knowledge users-policymakers, practitioners, patients/consumers or their advocates, and members of the wider public-in mutually beneficial research that can involve the joint development of research questions, data collection, analysis and dissemination of findings. Knowledge that is co-produced has a better chance of being implemented. The purpose of this paper is to update developments in the field of integrated knowledge translation through a deeper analysis of the approach in practice-oriented and policy-oriented health research. We present collaborative models that fall outside the scope of integrated knowledge translation, but then explore consensus-based approaches and networks as alternate sites of knowledge co-production. We discuss the need to advance the field through the development, or use, of data collection and interpretation tools that creatively engage knowledge users in the research process. Most importantly, conceptually relevant outcomes need to be identified, including ones that focus on team transformation through the co-production of knowledge. We explore some of these challenges and benefits in detail to help researchers understand what integrated knowledge translation means, and whether the approach's potential added value is worth the investment of time, energy and other resources. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

  18. Unbalanced Regressions and the Predictive Equation

    DEFF Research Database (Denmark)

    Osterrieder, Daniela; Ventosa-Santaulària, Daniel; Vera-Valdés, J. Eduardo

    Predictive return regressions with persistent regressors are typically plagued by (asymptotically) biased/inconsistent estimates of the slope, non-standard or potentially even spurious statistical inference, and regression unbalancedness. We alleviate the problem of unbalancedness in the theoreti......Predictive return regressions with persistent regressors are typically plagued by (asymptotically) biased/inconsistent estimates of the slope, non-standard or potentially even spurious statistical inference, and regression unbalancedness. We alleviate the problem of unbalancedness...... in the theoretical predictive equation by suggesting a data generating process, where returns are generated as linear functions of a lagged latent I(0) risk process. The observed predictor is a function of this latent I(0) process, but it is corrupted by a fractionally integrated noise. Such a process may arise due...... to aggregation or unexpected level shifts. In this setup, the practitioner estimates a misspecified, unbalanced, and endogenous predictive regression. We show that the OLS estimate of this regression is inconsistent, but standard inference is possible. To obtain a consistent slope estimate, we then suggest...

  19. Towards Slow-Moving Landslide Monitoring by Integrating Multi-Sensor InSAR Time Series Datasets: The Zhouqu Case Study, China

    Directory of Open Access Journals (Sweden)

    Qian Sun

    2016-11-01

    Full Text Available Although the past few decades have witnessed the great development of Synthetic Aperture Radar Interferometry (InSAR technology in the monitoring of landslides, such applications are limited by geometric distortions and ambiguity of 1D Line-Of-Sight (LOS measurements, both of which are the fundamental weakness of InSAR. Integration of multi-sensor InSAR datasets has recently shown its great potential in breaking through the two limits. In this study, 16 ascending images from the Advanced Land Observing Satellite (ALOS and 18 descending images from the Environmental Satellite (ENVISAT have been integrated to characterize and to detect the slow-moving landslides in Zhouqu, China between 2008 and 2010. Geometric distortions are first mapped by using the imaging geometric parameters of the used SAR data and public Digital Elevation Model (DEM data of Zhouqu, which allow the determination of the most appropriate data assembly for a particular slope. Subsequently, deformation rates along respective LOS directions of ALOS ascending and ENVISAT descending tracks are estimated by conducting InSAR time series analysis with a Temporarily Coherent Point (TCP-InSAR algorithm. As indicated by the geometric distortion results, 3D deformation rates of the Xieliupo slope at the east bank of the Pai-lung River are finally reconstructed by joint exploiting of the LOS deformation rates from cross-heading datasets based on the surface–parallel flow assumption. It is revealed that the synergistic results of ALOS and ENVISAT datasets provide a more comprehensive understanding and monitoring of the slow-moving landslides in Zhouqu.

  20. Performance of the Analog Moving Window Detector

    DEFF Research Database (Denmark)

    Hansen, V. Gregers

    1970-01-01

    A type of analog integrating moving window detector for use with a scanning pulse radar is examined. A performance analysis is carried out, which takes into account both the radiation pattern of the antenna and the dynamic character of the detection process due to the angular scanning...

  1. Integrating principal component analysis and vector quantization with support vector regression for sulfur content prediction in HDS process

    Directory of Open Access Journals (Sweden)

    Shokri Saeid

    2015-01-01

    Full Text Available An accurate prediction of sulfur content is very important for the proper operation and product quality control in hydrodesulfurization (HDS process. For this purpose, a reliable data- driven soft sensors utilizing Support Vector Regression (SVR was developed and the effects of integrating Vector Quantization (VQ with Principle Component Analysis (PCA were studied on the assessment of this soft sensor. First, in pre-processing step the PCA and VQ techniques were used to reduce dimensions of the original input datasets. Then, the compressed datasets were used as input variables for the SVR model. Experimental data from the HDS setup were employed to validate the proposed integrated model. The integration of VQ/PCA techniques with SVR model was able to increase the prediction accuracy of SVR. The obtained results show that integrated technique (VQ-SVR was better than (PCA-SVR in prediction accuracy. Also, VQ decreased the sum of the training and test time of SVR model in comparison with PCA. For further evaluation, the performance of VQ-SVR model was also compared to that of SVR. The obtained results indicated that VQ-SVR model delivered the best satisfactory predicting performance (AARE= 0.0668 and R2= 0.995 in comparison with investigated models.

  2. Short-term load forecasting with increment regression tree

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Jingfei; Stenzel, Juergen [Darmstadt University of Techonology, Darmstadt 64283 (Germany)

    2006-06-15

    This paper presents a new regression tree method for short-term load forecasting. Both increment and non-increment tree are built according to the historical data to provide the data space partition and input variable selection. Support vector machine is employed to the samples of regression tree nodes for further fine regression. Results of different tree nodes are integrated through weighted average method to obtain the comprehensive forecasting result. The effectiveness of the proposed method is demonstrated through its application to an actual system. (author)

  3. Enterprise Architecture Integration in E-government

    NARCIS (Netherlands)

    Janssen, M.F.W.H.A.; Cresswell, A.

    2005-01-01

    Achieving goals of better integrated and responsive government services requires moving away from stand alone applications toward more comprehensive, integrated architectures. As a result there is mounting pressure to move from disparate systems operating in parallel toward a shared architecture

  4. Recursive and non-linear logistic regression: moving on from the original EuroSCORE and EuroSCORE II methodologies.

    Science.gov (United States)

    Poullis, Michael

    2014-11-01

    EuroSCORE II, despite improving on the original EuroSCORE system, has not solved all the calibration and predictability issues. Recursive, non-linear and mixed recursive and non-linear regression analysis were assessed with regard to sensitivity, specificity and predictability of the original EuroSCORE and EuroSCORE II systems. The original logistic EuroSCORE, EuroSCORE II and recursive, non-linear and mixed recursive and non-linear regression analyses of these risk models were assessed via receiver operator characteristic curves (ROC) and Hosmer-Lemeshow statistic analysis with regard to the accuracy of predicting in-hospital mortality. Analysis was performed for isolated coronary artery bypass grafts (CABGs) (n = 2913), aortic valve replacement (AVR) (n = 814), mitral valve surgery (n = 340), combined AVR and CABG (n = 517), aortic (n = 350), miscellaneous cases (n = 642), and combinations of the above cases (n = 5576). The original EuroSCORE had an ROC below 0.7 for isolated AVR and combined AVR and CABG. None of the methods described increased the ROC above 0.7. The EuroSCORE II risk model had an ROC below 0.7 for isolated AVR only. Recursive regression, non-linear regression, and mixed recursive and non-linear regression all increased the ROC above 0.7 for isolated AVR. The original EuroSCORE had a Hosmer-Lemeshow statistic that was above 0.05 for all patients and the subgroups analysed. All of the techniques markedly increased the Hosmer-Lemeshow statistic. The EuroSCORE II risk model had a Hosmer-Lemeshow statistic that was significant for all patients (P linear regression failed to improve on the original Hosmer-Lemeshow statistic. The mixed recursive and non-linear regression using the EuroSCORE II risk model was the only model that produced an ROC of 0.7 or above for all patients and procedures and had a Hosmer-Lemeshow statistic that was highly non-significant. The original EuroSCORE and the EuroSCORE II risk models do not have adequate ROC and Hosmer

  5. Improving ISD Agility in Fast-Moving Software Organizations

    DEFF Research Database (Denmark)

    Persson, John Stouby; Nørbjerg, Jacob; Nielsen, Peter Axel

    2016-01-01

    Fast-moving software organizations must respond quickly to changing technological options and market trends while delivering high-quality services at competitive prices. Improving agility of information systems development (ISD) may reconcile these inherent tensions, but previous research...... study on how to improve ISD agility in a fast-moving software organization. The study maps central problems in the ISD management to direct improvements of agility. Our following intervention addressed method improvements in defining types of ISD by customer relations and integrating the method...... with the task management tool used by the organization. The paper discusses how the action research contributes to our understanding of ISD agility in fast-moving software organizations with a framework for mapping and evaluating improvements of agility. The action research specifically points out that project...

  6. FBH1 Catalyzes Regression of Stalled Replication Forks

    Directory of Open Access Journals (Sweden)

    Kasper Fugger

    2015-03-01

    Full Text Available DNA replication fork perturbation is a major challenge to the maintenance of genome integrity. It has been suggested that processing of stalled forks might involve fork regression, in which the fork reverses and the two nascent DNA strands anneal. Here, we show that FBH1 catalyzes regression of a model replication fork in vitro and promotes fork regression in vivo in response to replication perturbation. Cells respond to fork stalling by activating checkpoint responses requiring signaling through stress-activated protein kinases. Importantly, we show that FBH1, through its helicase activity, is required for early phosphorylation of ATM substrates such as CHK2 and CtIP as well as hyperphosphorylation of RPA. These phosphorylations occur prior to apparent DNA double-strand break formation. Furthermore, FBH1-dependent signaling promotes checkpoint control and preserves genome integrity. We propose a model whereby FBH1 promotes early checkpoint signaling by remodeling of stalled DNA replication forks.

  7. 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

  8. Thermal Analysis of a Cracked Half-plane under Moving Point Heat Source

    Directory of Open Access Journals (Sweden)

    He Kuanfang

    2017-09-01

    Full Text Available The heat conduction in half-plane with an insulated crack subjected to moving point heat source is investigated. The analytical solution and the numerical means are combined to analyze the transient temperature distribution of a cracked half-plane under moving point heat source. The transient temperature distribution of the half plane structure under moving point heat source is obtained by the moving coordinate method firstly, then the heat conduction equation with thermal boundary of an insulated crack face is changed to singular integral equation by applying Fourier transforms and solved by the numerical method. The numerical examples of the temperature distribution on the cracked half-plane structure under moving point heat source are presented and discussed in detail.

  9. Projected regression method for solving Fredholm integral equations arising in the analytic continuation problem of quantum physics

    International Nuclear Information System (INIS)

    Arsenault, Louis-François; Millis, Andrew J; Neuberg, Richard; Hannah, Lauren A

    2017-01-01

    We present a supervised machine learning approach to the inversion of Fredholm integrals of the first kind as they arise, for example, in the analytic continuation problem of quantum many-body physics. The approach provides a natural regularization for the ill-conditioned inverse of the Fredholm kernel, as well as an efficient and stable treatment of constraints. The key observation is that the stability of the forward problem permits the construction of a large database of outputs for physically meaningful inputs. Applying machine learning to this database generates a regression function of controlled complexity, which returns approximate solutions for previously unseen inputs; the approximate solutions are then projected onto the subspace of functions satisfying relevant constraints. Under standard error metrics the method performs as well or better than the Maximum Entropy method for low input noise and is substantially more robust to increased input noise. We suggest that the methodology will be similarly effective for other problems involving a formally ill-conditioned inversion of an integral operator, provided that the forward problem can be efficiently solved. (paper)

  10. Moving Target Detection With Compact Laser Doppler Radar

    Science.gov (United States)

    Sepp, G.; Breining, A.; Eisfeld, W.; Knopp, R.; Lill, E.; Wagner, D.

    1989-12-01

    This paper describes an experimental integrated optronic system for detection and tracking of moving objects. The system is based on a CO2 waveguide laser Doppler ra-dar with homodyne receiver and galvanometer mirror beam scanner. A "hot spot" seeker consisting of a thermal imager with image processor transmits the coordinates of IR-emitting, i.e. potentially powered, objects to the laser radar scanner. The scanner addresses these "hot" locations operating in a large field-of-view (FOV) random ac-cess mode. Hot spots exhibiting a Doppler shifted laser signal are indicated in the thermal image by velocity-to-colour encoded markers. After switching to a small FOV scanning mode, the laser Doppler radar is used to track fast moving objects. Labora-tory and field experiments with moving objects including rotating discs, automobiles and missiles are described.

  11. Differentiating regressed melanoma from regressed lichenoid keratosis.

    Science.gov (United States)

    Chan, Aegean H; Shulman, Kenneth J; Lee, Bonnie A

    2017-04-01

    Distinguishing regressed lichen planus-like keratosis (LPLK) from regressed melanoma can be difficult on histopathologic examination, potentially resulting in mismanagement of patients. We aimed to identify histopathologic features by which regressed melanoma can be differentiated from regressed LPLK. Twenty actively inflamed LPLK, 12 LPLK with regression and 15 melanomas with regression were compared and evaluated by hematoxylin and eosin staining as well as Melan-A, microphthalmia transcription factor (MiTF) and cytokeratin (AE1/AE3) immunostaining. (1) A total of 40% of regressed melanomas showed complete or near complete loss of melanocytes within the epidermis with Melan-A and MiTF immunostaining, while 8% of regressed LPLK exhibited this finding. (2) Necrotic keratinocytes were seen in the epidermis in 33% regressed melanomas as opposed to all of the regressed LPLK. (3) A dense infiltrate of melanophages in the papillary dermis was seen in 40% of regressed melanomas, a feature not seen in regressed LPLK. In summary, our findings suggest that a complete or near complete loss of melanocytes within the epidermis strongly favors a regressed melanoma over a regressed LPLK. In addition, necrotic epidermal keratinocytes and the presence of a dense band-like distribution of dermal melanophages can be helpful in differentiating these lesions. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  12. Integrated wireless fast-scan cyclic voltammetry recording and electrical stimulation for reward-predictive learning in awake, freely moving rats

    Science.gov (United States)

    Li, Yu-Ting; Wickens, Jeffery R.; Huang, Yi-Ling; Pan, Wynn H. T.; Chen, Fu-Yu Beverly; Chen, Jia-Jin Jason

    2013-08-01

    Objective. Fast-scan cyclic voltammetry (FSCV) is commonly used to monitor phasic dopamine release, which is usually performed using tethered recording and for limited types of animal behavior. It is necessary to design a wireless dopamine sensing system for animal behavior experiments. Approach. This study integrates a wireless FSCV system for monitoring the dopamine signal in the ventral striatum with an electrical stimulator that induces biphasic current to excite dopaminergic neurons in awake freely moving rats. The measured dopamine signals are unidirectionally transmitted from the wireless FSCV module to the host unit. To reduce electrical artifacts, an optocoupler and a separate power are applied to isolate the FSCV system and electrical stimulator, which can be activated by an infrared controller. Main results. In the validation test, the wireless backpack system has similar performance in comparison with a conventional wired system and it does not significantly affect the locomotor activity of the rat. In the cocaine administration test, the maximum electrically elicited dopamine signals increased to around 230% of the initial value 20 min after the injection of 10 mg kg-1 cocaine. In a classical conditioning test, the dopamine signal in response to a cue increased to around 60 nM over 50 successive trials while the electrically evoked dopamine concentration decreased from about 90 to 50 nM in the maintenance phase. In contrast, the cue-evoked dopamine concentration progressively decreased and the electrically evoked dopamine was eliminated during the extinction phase. In the histological evaluation, there was little damage to brain tissue after five months chronic implantation of the stimulating electrode. Significance. We have developed an integrated wireless voltammetry system for measuring dopamine concentration and providing electrical stimulation. The developed wireless FSCV system is proven to be a useful experimental tool for the continuous

  13. Research on refugees and immigrants social integration in Yunnan Border Area: An empirical analysis on the multivariable linear regression model

    Directory of Open Access Journals (Sweden)

    Peng Nai

    2016-03-01

    Full Text Available A great number of immigration populations resident permanently in Yunnan Border Area of China. To some extent, these people belong to refugees or immigrants in accordance with International Rules, which significantly features the social diversity of this area. However, this kind of social diversity always impairs the social order. Therefore, there will be a positive influence to the local society governance by a research on local immigration integration. This essay hereby attempts to acquire the data of the living situation of these border area immigration and refugees. The analysis of the social integration of refugees and immigration in Yunnan border area in China will be deployed through the modeling of multivariable linear regression based on these data in order to propose some more achievable resolutions.

  14. 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…

  15. Moving Low-Carbon Transportation in Xinjiang: Evidence from STIRPAT and Rigid Regression Models

    Directory of Open Access Journals (Sweden)

    Jiefang Dong

    2016-12-01

    Full Text Available With the rapid economic development of the Xinjiang Uygur Autonomous Region, the area’s transport sector has witnessed significant growth, which in turn has led to a large increase in carbon dioxide emissions. As such, calculating of the carbon footprint of Xinjiang’s transportation sector and probing the driving factors of carbon dioxide emissions are of great significance to the region’s energy conservation and environmental protection. This paper provides an account of the growth in the carbon emissions of Xinjiang’s transportation sector during the period from 1989 to 2012. We also analyze the transportation sector’s trends and historical evolution. Combined with the STIRPAT (Stochastic Impacts by Regression on Population, Affluence and Technology model and ridge regression, this study further quantitatively analyzes the factors that influence the carbon emissions of Xinjiang’s transportation sector. The results indicate the following: (1 the total carbon emissions and per capita carbon emissions of Xinjiang’s transportation sector both continued to rise rapidly during this period; their average annual growth rates were 10.8% and 9.1%, respectively; (2 the carbon emissions of the transportation sector come mainly from the consumption of diesel and gasoline, which accounted for an average of 36.2% and 2.6% of carbon emissions, respectively; in addition, the overall carbon emission intensity of the transportation sector showed an “S”-pattern trend within the study period; (3 population density plays a dominant role in increasing carbon dioxide emissions. Population is then followed by per capita GDP and, finally, energy intensity. Cargo turnover has a more significant potential impact on and role in emission reduction than do private vehicles. This is because road freight is the primary form of transportation used across Xinjiang, and this form of transportation has low energy efficiency. These findings have important

  16. Effect of contact angle hysteresis on moving liquid film integrity.

    Science.gov (United States)

    Simon, F. F.; Hsu, Y. Y.

    1972-01-01

    A study was made of the formation and breakdown of a water film moving over solid surfaces (teflon, lucite, stainless steel, and copper). The flow rate associated with film formation was found to be higher than the flow rate at which film breakdown occurred. The difference in the flow rates for film formation and film breakdown was attributed to contact angle hysteresis. Analysis and experiment, which are in good agreement, indicated that film formation and film breakdown are functions of the advancing and receding angles, respectively.

  17. Moving interfacial crack between two dissimilar soft ferromagnetic materials in uniform magnetic field

    International Nuclear Information System (INIS)

    Zhao, She Xu; Lee, Kang Yong

    2007-01-01

    This paper presents the dynamic magnetoelastic stress intensity factors of a Yoffe-type moving crack at the interface between two dissimilar soft ferromagnetic elastic half-planes. The solids are subjected to a uniform in-plane magnetic field and the crack is opened by internal normal and shear tractions. The problem is considered within the framework of linear magnetoelasticity. By application of the Fourier integral transform, the mixed boundary problem is reduced to a pair of integral equations of the second kind with Cauchy-type singularities. The singular integral equations are solved by means of a Jacobi polynomial expansion method. For a particular case, closed-form solutions are obtained. It is shown that the magnetoelastic stress intensity factors depend on the moving velocity of the crack, the magnetic field and the magnetoelastic properties of the materials

  18. Visual SLAM and Moving-object Detection for a Small-size Humanoid Robot

    Directory of Open Access Journals (Sweden)

    Yin-Tien Wang

    2010-09-01

    Full Text Available In the paper, a novel moving object detection (MOD algorithm is developed and integrated with robot visual Simultaneous Localization and Mapping (vSLAM. The moving object is assumed to be a rigid body and its coordinate system in space is represented by a position vector and a rotation matrix. The MOD algorithm is composed of detection of image features, initialization of image features, and calculation of object coordinates. Experimentation is implemented on a small-size humanoid robot and the results show that the performance of the proposed algorithm is efficient for robot visual SLAM and moving object detection.

  19. An integrated mathematical model for chemical oxygen demand (COD) removal in moving bed biofilm reactors (MBBR) including predation and hydrolysis.

    Science.gov (United States)

    Revilla, Marta; Galán, Berta; Viguri, Javier R

    2016-07-01

    An integrated mathematical model is proposed for modelling a moving bed biofilm reactor (MBBR) for removal of chemical oxygen demand (COD) under aerobic conditions. The composite model combines the following: (i) a one-dimensional biofilm model, (ii) a bulk liquid model, and (iii) biological processes in the bulk liquid and biofilm considering the interactions among autotrophic, heterotrophic and predator microorganisms. Depending on the values for the soluble biodegradable COD loading rate (SCLR), the model takes into account a) the hydrolysis of slowly biodegradable compounds in the bulk liquid, and b) the growth of predator microorganisms in the bulk liquid and in the biofilm. The integration of the model and the SCLR allows a general description of the behaviour of COD removal by the MBBR under various conditions. The model is applied for two in-series MBBR wastewater plant from an integrated cellulose and viscose production and accurately describes the experimental concentrations of COD, total suspended solids (TSS), nitrogen and phosphorous obtained during 14 months working at different SCLRs and nutrient dosages. The representation of the microorganism group distribution in the biofilm and in the bulk liquid allow for verification of the presence of predator microorganisms in the second reactor under some operational conditions. Copyright © 2016 Elsevier Ltd. All rights reserved.

  20. 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)

  1. Ethics and integrative medicine: moving beyond the biomedical model.

    Science.gov (United States)

    Guinn, D E

    2001-01-01

    For the most part, those who have written on the ethics of complementary and alternative medicine (CAM) and integrative medicine have attempted simply to apply traditional bioethics (in the form of principles of autonomy, beneficence, nonmaleficence, and justice) to this new area of healthcare. In this article I argue that adopting the practices of CAM requires a new ethical understanding that incorporates the values implicit in those practices. The characteristics of CAM and conventional medicine can be translated into the language of healthcare values in a variety of ways. I suggest that they support 5 core values: integrated humanity, ecological integrity, naturalism, relationalism, and spiritualism. Characteristics of both CAM and conventional medicine are present in value. What is now thought of as principlism is, in this understanding, simply a subset within these values.

  2. The APT model as reduced-rank regression

    NARCIS (Netherlands)

    Bekker, P.A.; Dobbelstein, P.; Wansbeek, T.J.

    Integrating the two steps of an arbitrage pricing theory (APT) model leads to a reduced-rank regression (RRR) model. So the results on RRR can be used to estimate APT models, making estimation very simple. We give a succinct derivation of estimation of RRR, derive the asymptotic variance of RRR

  3. Retro-regression--another important multivariate regression improvement.

    Science.gov (United States)

    Randić, M

    2001-01-01

    We review the serious problem associated with instabilities of the coefficients of regression equations, referred to as the MRA (multivariate regression analysis) "nightmare of the first kind". This is manifested when in a stepwise regression a descriptor is included or excluded from a regression. The consequence is an unpredictable change of the coefficients of the descriptors that remain in the regression equation. We follow with consideration of an even more serious problem, referred to as the MRA "nightmare of the second kind", arising when optimal descriptors are selected from a large pool of descriptors. This process typically causes at different steps of the stepwise regression a replacement of several previously used descriptors by new ones. We describe a procedure that resolves these difficulties. The approach is illustrated on boiling points of nonanes which are considered (1) by using an ordered connectivity basis; (2) by using an ordering resulting from application of greedy algorithm; and (3) by using an ordering derived from an exhaustive search for optimal descriptors. A novel variant of multiple regression analysis, called retro-regression (RR), is outlined showing how it resolves the ambiguities associated with both "nightmares" of the first and the second kind of MRA.

  4. Modified Regression Correlation Coefficient for Poisson Regression Model

    Science.gov (United States)

    Kaengthong, Nattacha; Domthong, Uthumporn

    2017-09-01

    This study gives attention to indicators in predictive power of the Generalized Linear Model (GLM) which are widely used; however, often having some restrictions. We are interested in regression correlation coefficient for a Poisson regression model. This is a measure of predictive power, and defined by the relationship between the dependent variable (Y) and the expected value of the dependent variable given the independent variables [E(Y|X)] for the Poisson regression model. The dependent variable is distributed as Poisson. The purpose of this research was modifying regression correlation coefficient for Poisson regression model. We also compare the proposed modified regression correlation coefficient with the traditional regression correlation coefficient in the case of two or more independent variables, and having multicollinearity in independent variables. The result shows that the proposed regression correlation coefficient is better than the traditional regression correlation coefficient based on Bias and the Root Mean Square Error (RMSE).

  5. Moving beyond regression techniques in cardiovascular risk prediction: applying machine learning to address analytic challenges.

    Science.gov (United States)

    Goldstein, Benjamin A; Navar, Ann Marie; Carter, Rickey E

    2017-06-14

    Risk prediction plays an important role in clinical cardiology research. Traditionally, most risk models have been based on regression models. While useful and robust, these statistical methods are limited to using a small number of predictors which operate in the same way on everyone, and uniformly throughout their range. The purpose of this review is to illustrate the use of machine-learning methods for development of risk prediction models. Typically presented as black box approaches, most machine-learning methods are aimed at solving particular challenges that arise in data analysis that are not well addressed by typical regression approaches. To illustrate these challenges, as well as how different methods can address them, we consider trying to predicting mortality after diagnosis of acute myocardial infarction. We use data derived from our institution's electronic health record and abstract data on 13 regularly measured laboratory markers. We walk through different challenges that arise in modelling these data and then introduce different machine-learning approaches. Finally, we discuss general issues in the application of machine-learning methods including tuning parameters, loss functions, variable importance, and missing data. Overall, this review serves as an introduction for those working on risk modelling to approach the diffuse field of machine learning. © The Author 2016. Published by Oxford University Press on behalf of the European Society of Cardiology.

  6. Switching moving boundary models for two-phase flow evaporators and condensers

    Science.gov (United States)

    Bonilla, Javier; Dormido, Sebastián; Cellier, François E.

    2015-03-01

    The moving boundary method is an appealing approach for the design, testing and validation of advanced control schemes for evaporators and condensers. When it comes to advanced control strategies, not only accurate but fast dynamic models are required. Moving boundary models are fast low-order dynamic models, and they can describe the dynamic behavior with high accuracy. This paper presents a mathematical formulation based on physical principles for two-phase flow moving boundary evaporator and condenser models which support dynamic switching between all possible flow configurations. The models were implemented in a library using the equation-based object-oriented Modelica language. Several integrity tests in steady-state and transient predictions together with stability tests verified the models. Experimental data from a direct steam generation parabolic-trough solar thermal power plant is used to validate and compare the developed moving boundary models against finite volume models.

  7. IPF-LASSO: Integrative L1-Penalized Regression with Penalty Factors for Prediction Based on Multi-Omics Data

    Directory of Open Access Journals (Sweden)

    Anne-Laure Boulesteix

    2017-01-01

    Full Text Available As modern biotechnologies advance, it has become increasingly frequent that different modalities of high-dimensional molecular data (termed “omics” data in this paper, such as gene expression, methylation, and copy number, are collected from the same patient cohort to predict the clinical outcome. While prediction based on omics data has been widely studied in the last fifteen years, little has been done in the statistical literature on the integration of multiple omics modalities to select a subset of variables for prediction, which is a critical task in personalized medicine. In this paper, we propose a simple penalized regression method to address this problem by assigning different penalty factors to different data modalities for feature selection and prediction. The penalty factors can be chosen in a fully data-driven fashion by cross-validation or by taking practical considerations into account. In simulation studies, we compare the prediction performance of our approach, called IPF-LASSO (Integrative LASSO with Penalty Factors and implemented in the R package ipflasso, with the standard LASSO and sparse group LASSO. The use of IPF-LASSO is also illustrated through applications to two real-life cancer datasets. All data and codes are available on the companion website to ensure reproducibility.

  8. Recent Development of an Earth Science App - FieldMove Clino

    Science.gov (United States)

    Vaughan, Alan; Collins, Nathan; Krus, Mike; Rourke, Peter

    2014-05-01

    As geological modelling and analysis move into 3D digital space, it becomes increasingly important to be able to rapidly integrate new data with existing databases, without the potential degradation caused by repeated manual transcription of numeric, graphical and meta-data. Digital field mapping offers significant benefits when compared with traditional paper mapping techniques, in that it can directly and interactively feed and be guided by downstream geological modelling and analysis. One of the most important pieces of equipment used by the field geologists is the compass clinometer. Midland Valley's development team have recently release their highly anticipated FieldMove Clino App. FieldMove Clino is a digital compass-clinometer for data capture on a smartphone. The app allows the user to use their phone as a traditional hand-held bearing compass, as well as a digital compass-clinometer for rapidly measuring and capturing the georeferenced location and orientation of planar and linear features in the field. The user can also capture and store digital photographs and text notes. FieldMove Clino supports online Google Maps as well as offline maps, so that the user can import their own georeferenced basemaps. Data can be exported as comma-separated values (.csv) or Move™ (.mve) files and then imported directly into FieldMove™, Move™ or other applications. Midland Valley is currently pioneering tablet-based mapping and, along with its industrial and academic partners, will be using the application in field based projects throughout this year and will be integrating feedback in further developments of this technology.

  9. Development of an integrated method for long-term water quality prediction using seasonal climate forecast

    Directory of Open Access Journals (Sweden)

    J. Cho

    2016-10-01

    Full Text Available The APEC Climate Center (APCC produces climate prediction information utilizing a multi-climate model ensemble (MME technique. In this study, four different downscaling methods, in accordance with the degree of utilizing the seasonal climate prediction information, were developed in order to improve predictability and to refine the spatial scale. These methods include: (1 the Simple Bias Correction (SBC method, which directly uses APCC's dynamic prediction data with a 3 to 6 month lead time; (2 the Moving Window Regression (MWR method, which indirectly utilizes dynamic prediction data; (3 the Climate Index Regression (CIR method, which predominantly uses observation-based climate indices; and (4 the Integrated Time Regression (ITR method, which uses predictors selected from both CIR and MWR. Then, a sampling-based temporal downscaling was conducted using the Mahalanobis distance method in order to create daily weather inputs to the Soil and Water Assessment Tool (SWAT model. Long-term predictability of water quality within the Wecheon watershed of the Nakdong River Basin was evaluated. According to the Korean Ministry of Environment's Provisions of Water Quality Prediction and Response Measures, modeling-based predictability was evaluated by using 3-month lead prediction data issued in February, May, August, and November as model input of SWAT. Finally, an integrated approach, which takes into account various climate information and downscaling methods for water quality prediction, was presented. This integrated approach can be used to prevent potential problems caused by extreme climate in advance.

  10. Moving finite element method aided by computerized symbolic manipulation and its application to dynamic fracture simulation

    International Nuclear Information System (INIS)

    Nishioka, Toshihisa; Takemoto, Yutaka

    1988-01-01

    Recently, the authors have shown that the combined method of the path-independent J' integral (dynamic J integral) and a moving isoparametric element procedure is an effective tool for the calculation of dynamic stress intensity factors. In the moving element procedure, the nodal pattern of the elements near a crack tip moves according to the motion of the crack-tip. An iterative numerical technique was used in the previous procedure to find the natural coordinates (ξ, η) at the newly created nodes. This technique requires additional computing time because of the nature of iteration. In the present paper, algebraic expressions for the transformation of the global coordinates (x, y) to the natural coordinates (ξ, η) were obtained by using a computerized symbolic manipulation system (REDUCE 3.2). These algebraic expressions are also very useful for remeshing or zooming techniques often used in finite element analysis. The present moving finite element method demonstrates its effectiveness for the simulation of a fast fracture. (author)

  11. 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

  12. An integrated study of surface roughness in EDM process using regression analysis and GSO algorithm

    Science.gov (United States)

    Zainal, Nurezayana; Zain, Azlan Mohd; Sharif, Safian; Nuzly Abdull Hamed, Haza; Mohamad Yusuf, Suhaila

    2017-09-01

    The aim of this study is to develop an integrated study of surface roughness (Ra) in the die-sinking electrical discharge machining (EDM) process of Ti-6AL-4V titanium alloy with positive polarity of copper-tungsten (Cu-W) electrode. Regression analysis and glowworm swarm optimization (GSO) algorithm were considered for modelling and optimization process. Pulse on time (A), pulse off time (B), peak current (C) and servo voltage (D) were selected as the machining parameters with various levels. The experiments have been conducted based on the two levels of full factorial design with an added center point design of experiments (DOE). Moreover, mathematical models with linear and 2 factor interaction (2FI) effects of the parameters chosen were developed. The validity test of the fit and the adequacy of the developed mathematical models have been carried out by using analysis of variance (ANOVA) and F-test. The statistical analysis showed that the 2FI model outperformed with the most minimal value of Ra compared to the linear model and experimental result.

  13. Nonparametric instrumental regression with non-convex constraints

    International Nuclear Information System (INIS)

    Grasmair, M; Scherzer, O; Vanhems, A

    2013-01-01

    This paper considers the nonparametric regression model with an additive error that is dependent on the explanatory variables. As is common in empirical studies in epidemiology and economics, it also supposes that valid instrumental variables are observed. A classical example in microeconomics considers the consumer demand function as a function of the price of goods and the income, both variables often considered as endogenous. In this framework, the economic theory also imposes shape restrictions on the demand function, such as integrability conditions. Motivated by this illustration in microeconomics, we study an estimator of a nonparametric constrained regression function using instrumental variables by means of Tikhonov regularization. We derive rates of convergence for the regularized model both in a deterministic and stochastic setting under the assumption that the true regression function satisfies a projected source condition including, because of the non-convexity of the imposed constraints, an additional smallness condition. (paper)

  14. Nonparametric instrumental regression with non-convex constraints

    Science.gov (United States)

    Grasmair, M.; Scherzer, O.; Vanhems, A.

    2013-03-01

    This paper considers the nonparametric regression model with an additive error that is dependent on the explanatory variables. As is common in empirical studies in epidemiology and economics, it also supposes that valid instrumental variables are observed. A classical example in microeconomics considers the consumer demand function as a function of the price of goods and the income, both variables often considered as endogenous. In this framework, the economic theory also imposes shape restrictions on the demand function, such as integrability conditions. Motivated by this illustration in microeconomics, we study an estimator of a nonparametric constrained regression function using instrumental variables by means of Tikhonov regularization. We derive rates of convergence for the regularized model both in a deterministic and stochastic setting under the assumption that the true regression function satisfies a projected source condition including, because of the non-convexity of the imposed constraints, an additional smallness condition.

  15. GSMNet: A Hierarchical Graph Model for Moving Objects in Networks

    Directory of Open Access Journals (Sweden)

    Hengcai Zhang

    2017-03-01

    Full Text Available Existing data models for moving objects in networks are often limited by flexibly controlling the granularity of representing networks and the cost of location updates and do not encompass semantic information, such as traffic states, traffic restrictions and social relationships. In this paper, we aim to fill the gap of traditional network-constrained models and propose a hierarchical graph model called the Geo-Social-Moving model for moving objects in Networks (GSMNet that adopts four graph structures, RouteGraph, SegmentGraph, ObjectGraph and MoveGraph, to represent the underlying networks, trajectories and semantic information in an integrated manner. The bulk of user-defined data types and corresponding operators is proposed to handle moving objects and answer a new class of queries supporting three kinds of conditions: spatial, temporal and semantic information. Then, we develop a prototype system with the native graph database system Neo4Jto implement the proposed GSMNet model. In the experiment, we conduct the performance evaluation using simulated trajectories generated from the BerlinMOD (Berlin Moving Objects Database benchmark and compare with the mature MOD system Secondo. The results of 17 benchmark queries demonstrate that our proposed GSMNet model has strong potential to reduce time-consuming table join operations an d shows remarkable advantages with regard to representing semantic information and controlling the cost of location updates.

  16. Optimization of Game Formats in U-10 Soccer Using Logistic Regression Analysis

    Directory of Open Access Journals (Sweden)

    Amatria Mario

    2016-12-01

    Full Text Available Small-sided games provide young soccer players with better opportunities to develop their skills and progress as individual and team players. There is, however, little evidence on the effectiveness of different game formats in different age groups, and furthermore, these formats can vary between and even within countries. The Royal Spanish Soccer Association replaced the traditional grassroots 7-a-side format (F-7 with the 8-a-side format (F-8 in the 2011-12 season and the country’s regional federations gradually followed suit. The aim of this observational methodology study was to investigate which of these formats best suited the learning needs of U-10 players transitioning from 5-aside futsal. We built a multiple logistic regression model to predict the success of offensive moves depending on the game format and the area of the pitch in which the move was initiated. Success was defined as a shot at the goal. We also built two simple logistic regression models to evaluate how the game format influenced the acquisition of technicaltactical skills. It was found that the probability of a shot at the goal was higher in F-7 than in F-8 for moves initiated in the Creation Sector-Own Half (0.08 vs 0.07 and the Creation Sector-Opponent's Half (0.18 vs 0.16. The probability was the same (0.04 in the Safety Sector. Children also had more opportunities to control the ball and pass or take a shot in the F-7 format (0.24 vs 0.20, and these were also more likely to be successful in this format (0.28 vs 0.19.

  17. 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.

  18. Optimal regression for reasoning about knowledge and actions

    NARCIS (Netherlands)

    Ditmarsch, van H.; Herzig, Andreas; Lima, de Tiago

    2007-01-01

    We show how in the propositional case both Reiter’s and Scherl & Levesque’s solutions to the frame problem can be modelled in dynamic epistemic logic (DEL), and provide an optimal regression algorithm for the latter. Our method is as follows: we extend Reiter’s framework by integrating observation

  19. Dual Regression

    OpenAIRE

    Spady, Richard; Stouli, Sami

    2012-01-01

    We propose dual regression as an alternative to the quantile regression process for the global estimation of conditional distribution functions under minimal assumptions. Dual regression provides all the interpretational power of the quantile regression process while avoiding the need for repairing the intersecting conditional quantile surfaces that quantile regression often produces in practice. Our approach introduces a mathematical programming characterization of conditional distribution f...

  20. Least square regression based integrated multi-parameteric demand modeling for short term load forecasting

    International Nuclear Information System (INIS)

    Halepoto, I.A.; Uqaili, M.A.

    2014-01-01

    Nowadays, due to power crisis, electricity demand forecasting is deemed an important area for socioeconomic development and proper anticipation of the load forecasting is considered essential step towards efficient power system operation, scheduling and planning. In this paper, we present STLF (Short Term Load Forecasting) using multiple regression techniques (i.e. linear, multiple linear, quadratic and exponential) by considering hour by hour load model based on specific targeted day approach with temperature variant parameter. The proposed work forecasts the future load demand correlation with linear and non-linear parameters (i.e. considering temperature in our case) through different regression approaches. The overall load forecasting error is 2.98% which is very much acceptable. From proposed regression techniques, Quadratic Regression technique performs better compared to than other techniques because it can optimally fit broad range of functions and data sets. The work proposed in this paper, will pave a path to effectively forecast the specific day load with multiple variance factors in a way that optimal accuracy can be maintained. (author)

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. Integrating classification trees with local logistic regression in Intensive Care prognosis.

    Science.gov (United States)

    Abu-Hanna, Ameen; de Keizer, Nicolette

    2003-01-01

    Health care effectiveness and efficiency are under constant scrutiny especially when treatment is quite costly as in the Intensive Care (IC). Currently there are various international quality of care programs for the evaluation of IC. At the heart of such quality of care programs lie prognostic models whose prediction of patient mortality can be used as a norm to which actual mortality is compared. The current generation of prognostic models in IC are statistical parametric models based on logistic regression. Given a description of a patient at admission, these models predict the probability of his or her survival. Typically, this patient description relies on an aggregate variable, called a score, that quantifies the severity of illness of the patient. The use of a parametric model and an aggregate score form adequate means to develop models when data is relatively scarce but it introduces the risk of bias. This paper motivates and suggests a method for studying and improving the performance behavior of current state-of-the-art IC prognostic models. Our method is based on machine learning and statistical ideas and relies on exploiting information that underlies a score variable. In particular, this underlying information is used to construct a classification tree whose nodes denote patient sub-populations. For these sub-populations, local models, most notably logistic regression ones, are developed using only the total score variable. We compare the performance of this hybrid model to that of a traditional global logistic regression model. We show that the hybrid model not only provides more insight into the data but also has a better performance. We pay special attention to the precision aspect of model performance and argue why precision is more important than discrimination ability.

  6. Output-Only Modal Parameter Recursive Estimation of Time-Varying Structures via a Kernel Ridge Regression FS-TARMA Approach

    Directory of Open Access Journals (Sweden)

    Zhi-Sai Ma

    2017-01-01

    Full Text Available Modal parameter estimation plays an important role in vibration-based damage detection and is worth more attention and investigation, as changes in modal parameters are usually being used as damage indicators. This paper focuses on the problem of output-only modal parameter recursive estimation of time-varying structures based upon parameterized representations of the time-dependent autoregressive moving average (TARMA. A kernel ridge regression functional series TARMA (FS-TARMA recursive identification scheme is proposed and subsequently employed for the modal parameter estimation of a numerical three-degree-of-freedom time-varying structural system and a laboratory time-varying structure consisting of a simply supported beam and a moving mass sliding on it. The proposed method is comparatively assessed against an existing recursive pseudolinear regression FS-TARMA approach via Monte Carlo experiments and shown to be capable of accurately tracking the time-varying dynamics in a recursive manner.

  7. Evaluation of a multiple linear regression model and SARIMA model in forecasting heat demand for district heating system

    International Nuclear Information System (INIS)

    Fang, Tingting; Lahdelma, Risto

    2016-01-01

    Highlights: • Social factor is considered for the linear regression models besides weather file. • Simultaneously optimize all the coefficients for linear regression models. • SARIMA combined with linear regression is used to forecast the heat demand. • The accuracy for both linear regression and time series models are evaluated. - Abstract: Forecasting heat demand is necessary for production and operation planning of district heating (DH) systems. In this study we first propose a simple regression model where the hourly outdoor temperature and wind speed forecast the heat demand. Weekly rhythm of heat consumption as a social component is added to the model to significantly improve the accuracy. The other type of model is the seasonal autoregressive integrated moving average (SARIMA) model with exogenous variables as a combination to take weather factors, and the historical heat consumption data as depending variables. One outstanding advantage of the model is that it peruses the high accuracy for both long-term and short-term forecast by considering both exogenous factors and time series. The forecasting performance of both linear regression models and time series model are evaluated based on real-life heat demand data for the city of Espoo in Finland by out-of-sample tests for the last 20 full weeks of the year. The results indicate that the proposed linear regression model (T168h) using 168-h demand pattern with midweek holidays classified as Saturdays or Sundays gives the highest accuracy and strong robustness among all the tested models based on the tested forecasting horizon and corresponding data. Considering the parsimony of the input, the ease of use and the high accuracy, the proposed T168h model is the best in practice. The heat demand forecasting model can also be developed for individual buildings if automated meter reading customer measurements are available. This would allow forecasting the heat demand based on more accurate heat consumption

  8. Learning a Nonnegative Sparse Graph for Linear Regression.

    Science.gov (United States)

    Fang, Xiaozhao; Xu, Yong; Li, Xuelong; Lai, Zhihui; Wong, Wai Keung

    2015-09-01

    Previous graph-based semisupervised learning (G-SSL) methods have the following drawbacks: 1) they usually predefine the graph structure and then use it to perform label prediction, which cannot guarantee an overall optimum and 2) they only focus on the label prediction or the graph structure construction but are not competent in handling new samples. To this end, a novel nonnegative sparse graph (NNSG) learning method was first proposed. Then, both the label prediction and projection learning were integrated into linear regression. Finally, the linear regression and graph structure learning were unified within the same framework to overcome these two drawbacks. Therefore, a novel method, named learning a NNSG for linear regression was presented, in which the linear regression and graph learning were simultaneously performed to guarantee an overall optimum. In the learning process, the label information can be accurately propagated via the graph structure so that the linear regression can learn a discriminative projection to better fit sample labels and accurately classify new samples. An effective algorithm was designed to solve the corresponding optimization problem with fast convergence. Furthermore, NNSG provides a unified perceptiveness for a number of graph-based learning methods and linear regression methods. The experimental results showed that NNSG can obtain very high classification accuracy and greatly outperforms conventional G-SSL methods, especially some conventional graph construction methods.

  9. Viscous dissipation effects on heat transfer in flow past a continuous moving plate

    Digital Repository Service at National Institute of Oceanography (India)

    Soundalgekar, V.M.; Murty, T.V.R.

    The study of thermal boundary layer on taking into account the viscous dissipative heat, on a continuously moving semi-infinite flat plate is presented here.Similarity solutions are derived and the resulting equations are integrated numerically...

  10. Regression: A Bibliography.

    Science.gov (United States)

    Pedrini, D. T.; Pedrini, Bonnie C.

    Regression, another mechanism studied by Sigmund Freud, has had much research, e.g., hypnotic regression, frustration regression, schizophrenic regression, and infra-human-animal regression (often directly related to fixation). Many investigators worked with hypnotic age regression, which has a long history, going back to Russian reflexologists.…

  11. Cab technology integration laboratory demonstration with moving map technology

    Science.gov (United States)

    2013-03-31

    A human performance study was conducted at the John A. Volpe National Transportation Systems Center (Volpe Center) using a locomotive research simulatorthe Cab Technology Integration Laboratory (CTIL)that was acquired by the Federal Railroad Ad...

  12. 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.

  13. Advanced statistics: linear regression, part I: simple linear regression.

    Science.gov (United States)

    Marill, Keith A

    2004-01-01

    Simple linear regression is a mathematical technique used to model the relationship between a single independent predictor variable and a single dependent outcome variable. In this, the first of a two-part series exploring concepts in linear regression analysis, the four fundamental assumptions and the mechanics of simple linear regression are reviewed. The most common technique used to derive the regression line, the method of least squares, is described. The reader will be acquainted with other important concepts in simple linear regression, including: variable transformations, dummy variables, relationship to inference testing, and leverage. Simplified clinical examples with small datasets and graphic models are used to illustrate the points. This will provide a foundation for the second article in this series: a discussion of multiple linear regression, in which there are multiple predictor variables.

  14. Coulomb's Law in a Moving Medium--A Review Exercise in Advanced Undergraduate Electromagnetism

    Science.gov (United States)

    Sastry, G. P.

    1978-01-01

    The electromagnetic field of a static charge in a moving medium is evaluated using elements of special relativity, residue calculus, and Fourier integration. Some of the concepts in electrodynamics that are of current research value are discussed. (BB)

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

    Directory of Open Access Journals (Sweden)

    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.

  16. Logistic Regression Modeling of Diminishing Manufacturing Sources for Integrated Circuits

    National Research Council Canada - National Science Library

    Gravier, Michael

    1999-01-01

    .... This thesis draws on available data from the electronics integrated circuit industry to attempt to assess whether statistical modeling offers a viable method for predicting the presence of DMSMS...

  17. Methodology for the AutoRegressive Planet Search (ARPS) Project

    Science.gov (United States)

    Feigelson, Eric; Caceres, Gabriel; ARPS Collaboration

    2018-01-01

    The detection of periodic signals of transiting exoplanets is often impeded by the presence of aperiodic photometric variations. This variability is intrinsic to the host star in space-based observations (typically arising from magnetic activity) and from observational conditions in ground-based observations. The most common statistical procedures to remove stellar variations are nonparametric, such as wavelet decomposition or Gaussian Processes regression. However, many stars display variability with autoregressive properties, wherein later flux values are correlated with previous ones. Providing the time series is evenly spaced, parametric autoregressive models can prove very effective. Here we present the methodology of the Autoregessive Planet Search (ARPS) project which uses Autoregressive Integrated Moving Average (ARIMA) models to treat a wide variety of stochastic short-memory processes, as well as nonstationarity. Additionally, we introduce a planet-search algorithm to detect periodic transits in the time-series residuals after application of ARIMA models. Our matched-filter algorithm, the Transit Comb Filter (TCF), replaces the traditional box-fitting step. We construct a periodogram based on the TCF to concentrate the signal of these periodic spikes. Various features of the original light curves, the ARIMA fits, the TCF periodograms, and folded light curves at peaks of the TCF periodogram can then be collected to provide constraints for planet detection. These features provide input into a multivariate classifier when a training set is available. The ARPS procedure has been applied NASA's Kepler mission observations of ~200,000 stars (Caceres, Dissertation Talk, this meeting) and will be applied in the future to other datasets.

  18. Mathematical Modeling of a Moving Planar Payload Pendulum on Flexible Portal Framework

    Directory of Open Access Journals (Sweden)

    Edwar Yazid

    2012-03-01

    Full Text Available Mathematical modeling of a moving planar payload pendulum on elastic portal framework is presented in this paper. The equations of motion of such a system are obtained by modeling the portal frame using finite element in conjunction with moving finite element method and moving planar payload pendulum by using Lagrange’s equations. The generated equations indicate the presence of nonlinear coupling between dynamics of portal framework and the payload pendulum. The combinational direct numerical integration technique, namely Newmarkand fourth-order Runge-Kutta method, is then proposed to solve the coupled equations of motion. Several numerical simulations are performed and the results are verified with several benchmarks. The results indicate that the amplitude and frequency of the payload pendulum swing angle are greatly affected by flexibility of structure and the cable in term of carriage speed. 

  19. Ordinary least square regression, orthogonal regression, geometric mean regression and their applications in aerosol science

    International Nuclear Information System (INIS)

    Leng Ling; Zhang Tianyi; Kleinman, Lawrence; Zhu Wei

    2007-01-01

    Regression analysis, especially the ordinary least squares method which assumes that errors are confined to the dependent variable, has seen a fair share of its applications in aerosol science. The ordinary least squares approach, however, could be problematic due to the fact that atmospheric data often does not lend itself to calling one variable independent and the other dependent. Errors often exist for both measurements. In this work, we examine two regression approaches available to accommodate this situation. They are orthogonal regression and geometric mean regression. Comparisons are made theoretically as well as numerically through an aerosol study examining whether the ratio of organic aerosol to CO would change with age

  20. Moving-part-free microfluidic systems for lab-on-a-chip

    International Nuclear Information System (INIS)

    Luo, J K; Fu, Y Q; Du, X Y; Flewitt, A J; Milne, W I; Li, Y; Walton, A J

    2009-01-01

    Microfluidic systems are part of an emerging technology which deals with minute amounts of liquids (biological samples and reagents) on a small scale. They are fast, compact and can be made into a highly integrated system to deliver sample purification, separation, reaction, immobilization, labelling, as well as detection, thus are promising for applications such as lab-on-a-chip and handheld healthcare devices. Miniaturized micropumps typically consist of a moving-part component, such as a membrane structure, to deliver liquids, and are often unreliable, complicated in structure and difficult to be integrated with other control electronics circuits. The trend of new-generation micropumps is moving-part-free micropumps operated by advanced techniques, such as electrokinetic force, surface tension/energy, acoustic waves. This paper reviews the development and advances of relevant technologies, and introduces electrowetting-on-dielectrics and acoustic wave-based microfluidics. The programmable electrowetting micropump has been realized to dispense and manipulate droplets in 2D with up to 1000 addressable electrodes and electronics built underneath. The acoustic wave-based microfluidics can be used not only for pumping, mixing and droplet generation but also for biosensors, suitable for single-mechanism-based lab-on-a-chip applications

  1. Polynomial regression analysis and significance test of the regression function

    International Nuclear Information System (INIS)

    Gao Zhengming; Zhao Juan; He Shengping

    2012-01-01

    In order to analyze the decay heating power of a certain radioactive isotope per kilogram with polynomial regression method, the paper firstly demonstrated the broad usage of polynomial function and deduced its parameters with ordinary least squares estimate. Then significance test method of polynomial regression function is derived considering the similarity between the polynomial regression model and the multivariable linear regression model. Finally, polynomial regression analysis and significance test of the polynomial function are done to the decay heating power of the iso tope per kilogram in accord with the authors' real work. (authors)

  2. Moving Green Chemistry Forward: Networks as a Foundation

    Science.gov (United States)

    Carter, T.; Lough, G.

    2014-12-01

    Green chemistry is a growing discipline, but for a variety of reasons, it has not yet become integrated into science curriculum and the greater societal conscience. With its increasing economic benefits to many sectors including business, industry, and academia and its potential to make science more accessible not only to science students but also to the general citizenry, we suggested answers to the questions: Why has greater success not been realized? What are the particular barriers to wider implementation? And what are incentives and ways to move green chemistry forward? We suggest some strategies and options to both increase the use of green chemistry principles and to also increase stakeholders' understanding of the importance and utility of green chemistry in their daily lives. For example, our main suggestions are that an inclusive, multidisciplinary network would aid in coordinating data and in translating the science into user friendly tools, and that an educational component embedded in this greater effort would also serve to move green chemistry forward.

  3. Theory of Regression Apple Professional Cooperation Organization Research

    OpenAIRE

    Ouyang Bin

    2013-01-01

    In view of the enterprise ecological apple manor a variety of problems of existence, put forward to the enterprise management transformation, achieve enterprise, collective, individual integrated operation management and the use of regression mathematical model on apple professional cooperation organization analysis. Through the example, Apple professional economic cooperation organization innovation model of the input output ratio than the rural economic cooperation organization is much high...

  4. 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.

  5. Reduced Rank Regression

    DEFF Research Database (Denmark)

    Johansen, Søren

    2008-01-01

    The reduced rank regression model is a multivariate regression model with a coefficient matrix with reduced rank. The reduced rank regression algorithm is an estimation procedure, which estimates the reduced rank regression model. It is related to canonical correlations and involves calculating...

  6. 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.

  7. What is new about covered interest parity condition in the European Union? Evidence from fractal cross-correlation regressions

    Science.gov (United States)

    Ferreira, Paulo; Kristoufek, Ladislav

    2017-11-01

    We analyse the covered interest parity (CIP) using two novel regression frameworks based on cross-correlation analysis (detrended cross-correlation analysis and detrending moving-average cross-correlation analysis), which allow for studying the relationships at different scales and work well under non-stationarity and heavy tails. CIP is a measure of capital mobility commonly used to analyse financial integration, which remains an interesting feature of study in the context of the European Union. The importance of this features is related to the fact that the adoption of a common currency is associated with some benefits for countries, but also involves some risks such as the loss of economic instruments to face possible asymmetric shocks. While studying the Eurozone members could explain some problems in the common currency, studying the non-Euro countries is important to analyse if they are fit to take the possible benefits. Our results point to the CIP verification mainly in the Central European countries while in the remaining countries, the verification of the parity is only residual.

  8. Heat transfer in flow past a continuously moving porous flat plate with heat flux

    Digital Repository Service at National Institute of Oceanography (India)

    Murty, T.V.R.; Sarma, Y.V.B.

    The analysis of the heat transfer in flow past a continuously moving semi-infinite plate in the presence of suction/ injection with heat flux has been presented. Similarity solutions have been derived and the resulting equations are integrated...

  9. HYBRID DATA APPROACH FOR SELECTING EFFECTIVE TEST CASES DURING THE REGRESSION TESTING

    OpenAIRE

    Mohan, M.; Shrimali, Tarun

    2017-01-01

    In the software industry, software testing becomes more important in the entire software development life cycle. Software testing is one of the fundamental components of software quality assurances. Software Testing Life Cycle (STLC)is a process involved in testing the complete software, which includes Regression Testing, Unit Testing, Smoke Testing, Integration Testing, Interface Testing, System Testing & etc. In the STLC of Regression testing, test case selection is one of the most importan...

  10. 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

  11. Quantile Regression Methods

    DEFF Research Database (Denmark)

    Fitzenberger, Bernd; Wilke, Ralf Andreas

    2015-01-01

    if the mean regression model does not. We provide a short informal introduction into the principle of quantile regression which includes an illustrative application from empirical labor market research. This is followed by briefly sketching the underlying statistical model for linear quantile regression based......Quantile regression is emerging as a popular statistical approach, which complements the estimation of conditional mean models. While the latter only focuses on one aspect of the conditional distribution of the dependent variable, the mean, quantile regression provides more detailed insights...... by modeling conditional quantiles. Quantile regression can therefore detect whether the partial effect of a regressor on the conditional quantiles is the same for all quantiles or differs across quantiles. Quantile regression can provide evidence for a statistical relationship between two variables even...

  12. Connecticut School Integration: Moving Forward as the Northeast Retreats

    Science.gov (United States)

    Orfield, Gary

    2015-01-01

    This report analyzes the data on changes in patterns of racial segregation and their education consequences over a quarter century, from l987 to 2012. It examines a major transition in the racial and ethnic composition of Connecticut and the changes in integration and segregation in the schools of the state and its urban communities and it…

  13. Comparing lagged linear correlation, lagged regression, Granger causality, and vector autoregression for uncovering associations in EHR data.

    Science.gov (United States)

    Levine, Matthew E; Albers, David J; Hripcsak, George

    2016-01-01

    Time series analysis methods have been shown to reveal clinical and biological associations in data collected in the electronic health record. We wish to develop reliable high-throughput methods for identifying adverse drug effects that are easy to implement and produce readily interpretable results. To move toward this goal, we used univariate and multivariate lagged regression models to investigate associations between twenty pairs of drug orders and laboratory measurements. Multivariate lagged regression models exhibited higher sensitivity and specificity than univariate lagged regression in the 20 examples, and incorporating autoregressive terms for labs and drugs produced more robust signals in cases of known associations among the 20 example pairings. Moreover, including inpatient admission terms in the model attenuated the signals for some cases of unlikely associations, demonstrating how multivariate lagged regression models' explicit handling of context-based variables can provide a simple way to probe for health-care processes that confound analyses of EHR data.

  14. Moving mesh generation with a sequential approach for solving PDEs

    DEFF Research Database (Denmark)

    In moving mesh methods, physical PDEs and a mesh equation derived from equidistribution of an error metrics (so-called the monitor function) are simultaneously solved and meshes are dynamically concentrated on steep regions (Lim et al., 2001). However, the simultaneous solution procedure...... a simple and robust moving mesh algorithm in one or multidimension. In this study, we propose a sequential solution procedure including two separate parts: prediction step to obtain an approximate solution to a next time level (integration of physical PDEs) and regriding step at the next time level (mesh...... generation and solution interpolation). Convection terms, which appear in physical PDEs and a mesh equation, are discretized by a WENO (Weighted Essentially Non-Oscillatory) scheme under the consrvative form. This sequential approach is to keep the advantages of robustness and simplicity for the static...

  15. Satellite rainfall retrieval by logistic regression

    Science.gov (United States)

    Chiu, Long S.

    1986-01-01

    The potential use of logistic regression in rainfall estimation from satellite measurements is investigated. Satellite measurements provide covariate information in terms of radiances from different remote sensors.The logistic regression technique can effectively accommodate many covariates and test their significance in the estimation. The outcome from the logistical model is the probability that the rainrate of a satellite pixel is above a certain threshold. By varying the thresholds, a rainrate histogram can be obtained, from which the mean and the variant can be estimated. A logistical model is developed and applied to rainfall data collected during GATE, using as covariates the fractional rain area and a radiance measurement which is deduced from a microwave temperature-rainrate relation. It is demonstrated that the fractional rain area is an important covariate in the model, consistent with the use of the so-called Area Time Integral in estimating total rain volume in other studies. To calibrate the logistical model, simulated rain fields generated by rainfield models with prescribed parameters are needed. A stringent test of the logistical model is its ability to recover the prescribed parameters of simulated rain fields. A rain field simulation model which preserves the fractional rain area and lognormality of rainrates as found in GATE is developed. A stochastic regression model of branching and immigration whose solutions are lognormally distributed in some asymptotic limits has also been developed.

  16. A Monte Carlo simulation study comparing linear regression, beta regression, variable-dispersion beta regression and fractional logit regression at recovering average difference measures in a two sample design.

    Science.gov (United States)

    Meaney, Christopher; Moineddin, Rahim

    2014-01-24

    In biomedical research, response variables are often encountered which have bounded support on the open unit interval--(0,1). Traditionally, researchers have attempted to estimate covariate effects on these types of response data using linear regression. Alternative modelling strategies may include: beta regression, variable-dispersion beta regression, and fractional logit regression models. This study employs a Monte Carlo simulation design to compare the statistical properties of the linear regression model to that of the more novel beta regression, variable-dispersion beta regression, and fractional logit regression models. In the Monte Carlo experiment we assume a simple two sample design. We assume observations are realizations of independent draws from their respective probability models. The randomly simulated draws from the various probability models are chosen to emulate average proportion/percentage/rate differences of pre-specified magnitudes. Following simulation of the experimental data we estimate average proportion/percentage/rate differences. We compare the estimators in terms of bias, variance, type-1 error and power. Estimates of Monte Carlo error associated with these quantities are provided. If response data are beta distributed with constant dispersion parameters across the two samples, then all models are unbiased and have reasonable type-1 error rates and power profiles. If the response data in the two samples have different dispersion parameters, then the simple beta regression model is biased. When the sample size is small (N0 = N1 = 25) linear regression has superior type-1 error rates compared to the other models. Small sample type-1 error rates can be improved in beta regression models using bias correction/reduction methods. In the power experiments, variable-dispersion beta regression and fractional logit regression models have slightly elevated power compared to linear regression models. Similar results were observed if the

  17. Variance of discharge estimates sampled using acoustic Doppler current profilers from moving boats

    Science.gov (United States)

    Garcia, Carlos M.; Tarrab, Leticia; Oberg, Kevin; Szupiany, Ricardo; Cantero, Mariano I.

    2012-01-01

    This paper presents a model for quantifying the random errors (i.e., variance) of acoustic Doppler current profiler (ADCP) discharge measurements from moving boats for different sampling times. The model focuses on the random processes in the sampled flow field and has been developed using statistical methods currently available for uncertainty analysis of velocity time series. Analysis of field data collected using ADCP from moving boats from three natural rivers of varying sizes and flow conditions shows that, even though the estimate of the integral time scale of the actual turbulent flow field is larger than the sampling interval, the integral time scale of the sampled flow field is on the order of the sampling interval. Thus, an equation for computing the variance error in discharge measurements associated with different sampling times, assuming uncorrelated flow fields is appropriate. The approach is used to help define optimal sampling strategies by choosing the exposure time required for ADCPs to accurately measure flow discharge.

  18. 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,

  19. A refined approach: Saudi Arabia moves beyond crude

    International Nuclear Information System (INIS)

    Krane, Jim

    2015-01-01

    Saudi Arabia's role in global energy markets is changing. The kingdom is reshaping itself as a supplier of refined petroleum products while moving beyond its long-held role as a simple exporter of crude oil. This change is commensurate with the typical development trajectory of a state progressing to a more advanced stage of global economic integration. Gains from increased refining include reducing fuel imports and capturing margins now bequeathed to competitors. Refining also allows the kingdom to export its heavy crude oil to a wider array of customers, beyond select importers configured to handle heavy crudes. However, the move also presents strategic complications. The world's 'swing supplier' of oil may grow less willing or able to adjust supply to suit market demands. In the process, Saudi Arabia may have to update the old “oil for security” relationship that links it with Washington, augmenting it with a more diverse set of economic and investment ties with individual companies and countries, including China. -- Highlights: •Saudi Arabia is diverting crude oil into an expanding refining sector. •In doing so, the kingdom is moving beyond its role as global “swing supplier” of crude oil. •The kingdom will benefit from increased refining, including enhanced demand for heavy crude. •Strategic complications may force it to seek security partners beyond Washington

  20. Transforming traditional Tai Ji Quan techniques into integrative movement therapy-Tai Ji Quan: Moving for Better Balance.

    Science.gov (United States)

    Li, Fuzhong

    2014-03-01

    Tai Ji Quan, developed as a martial art, has traditionally served multiple purposes, including self-defense, competition/performance, and health promotion. With respect to health, the benefits historically and anecdotally associated with Tai Ji Quan are now being supported by scientific and clinical research, with mounting evidence indicating its potential value in preventing and managing various diseases and improving well-being and quality of life in middle-aged and older adults. The research findings produced to date have both public health significance and clinical relevance. However, because of its roots in the martial arts, transforming traditional Tai Ji Quan movements and training approaches into contemporary therapeutic programs and functional applications is needed to maximize its ultimate utility. This paper addresses this issue by introducing Tai Ji Quan: Moving for Better Balance , a functional therapy that involves the use of Tai Ji Quan principles and Yang-style-based movements to form an innovative, contemporary therapeutic approach that integrates motor, sensory, and cognitive components to improve postural control, gait, and mobility for older adults and those who have neurodegenerative movement impairments. It provides a synergy of traditional and contemporary Tai Ji Quan practice with the ultimate goal of improving balance and gait, enhancing performance of daily functional tasks, and reducing incidence of falls among older adults.

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

    Science.gov (United States)

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

    2017-08-01

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

  2. Regression Phalanxes

    OpenAIRE

    Zhang, Hongyang; Welch, William J.; Zamar, Ruben H.

    2017-01-01

    Tomal et al. (2015) introduced the notion of "phalanxes" in the context of rare-class detection in two-class classification problems. A phalanx is a subset of features that work well for classification tasks. In this paper, we propose a different class of phalanxes for application in regression settings. We define a "Regression Phalanx" - a subset of features that work well together for prediction. We propose a novel algorithm which automatically chooses Regression Phalanxes from high-dimensi...

  3. The state-level approach: moving beyond integrated safeguards

    International Nuclear Information System (INIS)

    Tape, James W.

    2008-01-01

    The concept of a State-Level Approach (SLA) for international safeguards planning, implementation, and evaluation was contained in the Conceptual Framework for Integrated Safeguards (IS) agreed in 2002. This paper describes briefly the key elements of the SLA, including State-level factors and high-level safeguards objectives, and considers different cases in which application of the SLA methodology could address safeguards for 'suspect' States, 'good' States, and Nuclear Weapons States hosting fuel cycle centers. The continued use and further development of the SLA to customize safeguards for each State, including for States already under IS, is seen as central to effective and efficient safeguards for an expanding nuclear world.

  4. Predictors of Traditional Medical Practices in Illness Behavior in Northwestern Ethiopia: An Integrated Model of Behavioral Prediction Based Logistic Regression Analysis

    Directory of Open Access Journals (Sweden)

    Abenezer Yared

    2017-01-01

    Full Text Available This study aimed at investigating traditional medical beliefs and practices in illness behavior as well as predictors of the practices in Gondar city, northwestern Ethiopia, by using the integrated model of behavioral prediction. A cross-sectional quantitative survey was conducted to collect data through interviewer administered structured questionnaires from 496 individuals selected by probability proportional to size sampling technique. Unadjusted bivariate and adjusted multivariate logistic regression analyses were performed, and the results indicated that sociocultural predictors of normative response and attitude as well as psychosocial individual difference variables of traditional understanding of illness causation and perceived efficacy had statistically significant associations with traditional medical practices. Due to the influence of these factors, majority of the study population (85% thus relied on both herbal and spiritual varieties of traditional medicine to respond to their perceived illnesses, supporting the conclusion that characterized the illness behavior of the people as mainly involving traditional medical practices. The results implied two-way medicine needs to be developed with ongoing research, and health educations must take the traditional customs into consideration, for integrating interventions in the health care system in ways that the general public accepts yielding a better health outcome.

  5. Continuous processing of recombinant proteins: Integration of inclusion body solubilization and refolding using simulated moving bed size exclusion chromatography with buffer recycling.

    Science.gov (United States)

    Wellhoefer, Martin; Sprinzl, Wolfgang; Hahn, Rainer; Jungbauer, Alois

    2013-12-06

    An integrated process which combines continuous inclusion body dissolution with NaOH and continuous matrix-assisted refolding based on closed-loop simulated moving bed size exclusion chromatography was designed and experimentally evaluated at laboratory scale. Inclusion bodies from N(pro) fusion pep6His and N(pro) fusion MCP1 from high cell density fermentation were continuously dissolved with NaOH, filtered and mixed with concentrated refolding buffer prior to refolding by size exclusion chromatography (SEC). This process enabled an isocratic operation of the simulated moving bed (SMB) system with a closed-loop set-up with refolding buffer as the desorbent buffer and buffer recycling by concentrating the raffinate using tangential flow filtration. With this continuous refolding process, we increased the refolding and cleavage yield of both model proteins by 10% compared to batch dilution refolding. Furthermore, more than 99% of the refolding buffer of the raffinate could be recycled which reduced the buffer consumption significantly. Based on the actual refolding data, we compared throughput, productivity, and buffer consumption between two batch dilution refolding processes - one using urea for IB dissolution, the other one using NaOH for IB dissolution - and our continuous refolding process. The higher complexity of the continuous refolding process was rewarded with higher throughput and productivity as well as significantly lower buffer consumption compared to the batch dilution refolding processes. Copyright © 2013 Elsevier B.V. All rights reserved.

  6. Quasi-Stationary Temperature Field of Two-Layer Half-Space with Moving Boundary

    Directory of Open Access Journals (Sweden)

    P. A. Vlasov

    2015-01-01

    Full Text Available Due to intensive introduction of mathematical modeling methods into engineering practice, analytical methods for solving problems of heat conduction theory along with computational methods become increasingly important. Despite the well-known limitations of the analytical method applicability, this trend is caused by many reasons. In particular, solutions of the appropriate problems presented in analytically closed form can be used to test the new efficient computational algorithms, to carry out a parametric study of the temperature field of the analyzed system and to explore specific features of its formation, to formulate and solve optimization problems. In addition, these solutions allow us to explore the possibility for simplifying mathematical model with retaining its adequacy to the studied process.The main goal of the conducted research is to provide an analytically closed-form solution to the problem of finding the quasi-stationary temperature field of the system, which is simulated by isotropic half-space with isotropic coating of constant thickness. The outer boundary of this system is exposed to the Gaussian-type heat flux and uniformly moves in parallel with itself.A two-dimensional mathematical model that takes into account the axial symmetry of the studied process has been used. After the transition to a moving coordinate system rigidly associated with a moving boundary the Hankel integral transform of zero order (with respect to the radial variable and the Laplace transform (with respect to the temporal variable were used. Next, the image of the Hankel transform for the stationary temperature field of the system with respect to the moving coordinate system was found using a limit theorem of operational calculus. This allowed representing the required quasi-stationary field in the form of an improper integral of the first kind, which depends on the parameters. This result obtained can be used to conduct a parametric study and solve

  7. 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...

  8. Model Identification of Integrated ARMA Processes

    Science.gov (United States)

    Stadnytska, Tetiana; Braun, Simone; Werner, Joachim

    2008-01-01

    This article evaluates the Smallest Canonical Correlation Method (SCAN) and the Extended Sample Autocorrelation Function (ESACF), automated methods for the Autoregressive Integrated Moving-Average (ARIMA) model selection commonly available in current versions of SAS for Windows, as identification tools for integrated processes. SCAN and ESACF can…

  9. 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...

  10. The relative importance of imaging markers for the prediction of Alzheimer's disease dementia in mild cognitive impairment — Beyond classical regression

    Directory of Open Access Journals (Sweden)

    Stefan J. Teipel

    2015-01-01

    Penalized regression yielded more parsimonious models than unpenalized stepwise regression for the integration of multiregional and multimodal imaging information. The advantage of penalized regression was particularly strong with a high number of collinear predictors.

  11. Advanced statistics: linear regression, part II: multiple linear regression.

    Science.gov (United States)

    Marill, Keith A

    2004-01-01

    The applications of simple linear regression in medical research are limited, because in most situations, there are multiple relevant predictor variables. Univariate statistical techniques such as simple linear regression use a single predictor variable, and they often may be mathematically correct but clinically misleading. Multiple linear regression is a mathematical technique used to model the relationship between multiple independent predictor variables and a single dependent outcome variable. It is used in medical research to model observational data, as well as in diagnostic and therapeutic studies in which the outcome is dependent on more than one factor. Although the technique generally is limited to data that can be expressed with a linear function, it benefits from a well-developed mathematical framework that yields unique solutions and exact confidence intervals for regression coefficients. Building on Part I of this series, this article acquaints the reader with some of the important concepts in multiple regression analysis. These include multicollinearity, interaction effects, and an expansion of the discussion of inference testing, leverage, and variable transformations to multivariate models. Examples from the first article in this series are expanded on using a primarily graphic, rather than mathematical, approach. The importance of the relationships among the predictor variables and the dependence of the multivariate model coefficients on the choice of these variables are stressed. Finally, concepts in regression model building are discussed.

  12. Robust Face Recognition via Multi-Scale Patch-Based Matrix Regression.

    Directory of Open Access Journals (Sweden)

    Guangwei Gao

    Full Text Available In many real-world applications such as smart card solutions, law enforcement, surveillance and access control, the limited training sample size is the most fundamental problem. By making use of the low-rank structural information of the reconstructed error image, the so-called nuclear norm-based matrix regression has been demonstrated to be effective for robust face recognition with continuous occlusions. However, the recognition performance of nuclear norm-based matrix regression degrades greatly in the face of the small sample size problem. An alternative solution to tackle this problem is performing matrix regression on each patch and then integrating the outputs from all patches. However, it is difficult to set an optimal patch size across different databases. To fully utilize the complementary information from different patch scales for the final decision, we propose a multi-scale patch-based matrix regression scheme based on which the ensemble of multi-scale outputs can be achieved optimally. Extensive experiments on benchmark face databases validate the effectiveness and robustness of our method, which outperforms several state-of-the-art patch-based face recognition algorithms.

  13. Boosted beta regression.

    Directory of Open Access Journals (Sweden)

    Matthias Schmid

    Full Text Available Regression analysis with a bounded outcome is a common problem in applied statistics. Typical examples include regression models for percentage outcomes and the analysis of ratings that are measured on a bounded scale. In this paper, we consider beta regression, which is a generalization of logit models to situations where the response is continuous on the interval (0,1. Consequently, beta regression is a convenient tool for analyzing percentage responses. The classical approach to fit a beta regression model is to use maximum likelihood estimation with subsequent AIC-based variable selection. As an alternative to this established - yet unstable - approach, we propose a new estimation technique called boosted beta regression. With boosted beta regression estimation and variable selection can be carried out simultaneously in a highly efficient way. Additionally, both the mean and the variance of a percentage response can be modeled using flexible nonlinear covariate effects. As a consequence, the new method accounts for common problems such as overdispersion and non-binomial variance structures.

  14. Performance Analysis of Trans-Jakarta Bus Suburban Service Move-Across Greater Jakarta

    Science.gov (United States)

    Tangkudung, ESW; Widyadayinta, C.

    2018-03-01

    Trans-Jakarta have developed their services scope as Suburban Service or Feeder move-across service that operate from greater Jakarta into Jakarta central vice versa. One of the route is Ciputat – Bundaran Hotel Indonesia (Tosari) and integrated with corridor 1 (one) and 8 (eight). This service is not travel on the exclusive lane or bus-way. Objective of Government Jakarta to provide this service is to decrease private car to enter the central of Jakarta. The objective of this study is to find the performance of the service. Survey have conducted static and dynamic on work day to get variable of travel time and delay, waiting time of passenger at the bus stop, headway and ridership of the bus. Service Standard Minimum of Trans-Jakarta have compared with the result of variable headway, travel speed, and waiting time at bus stop as concern of all the passengers. Analysis use correlation test method and linear regression model have done. The performance of Trans-Jakarta bus suburban service, based on travel speed indicator is fairly bad, only 8.1% of trip could comply with Minimum Service Standard. Bus performance based on the indicator of density in the bus is good, where all points are below the maximum limit i.e. 8 people/m2 at peak hour and 5 people/m2 at off-peak hour.

  15. Regression to Causality : Regression-style presentation influences causal attribution

    DEFF Research Database (Denmark)

    Bordacconi, Mats Joe; Larsen, Martin Vinæs

    2014-01-01

    of equivalent results presented as either regression models or as a test of two sample means. Our experiment shows that the subjects who were presented with results as estimates from a regression model were more inclined to interpret these results causally. Our experiment implies that scholars using regression...... models – one of the primary vehicles for analyzing statistical results in political science – encourage causal interpretation. Specifically, we demonstrate that presenting observational results in a regression model, rather than as a simple comparison of means, makes causal interpretation of the results...... more likely. Our experiment drew on a sample of 235 university students from three different social science degree programs (political science, sociology and economics), all of whom had received substantial training in statistics. The subjects were asked to compare and evaluate the validity...

  16. 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.

  17. Adaptive kernel regression for freehand 3D ultrasound reconstruction

    Science.gov (United States)

    Alshalalfah, Abdel-Latif; Daoud, Mohammad I.; Al-Najar, Mahasen

    2017-03-01

    Freehand three-dimensional (3D) ultrasound imaging enables low-cost and flexible 3D scanning of arbitrary-shaped organs, where the operator can freely move a two-dimensional (2D) ultrasound probe to acquire a sequence of tracked cross-sectional images of the anatomy. Often, the acquired 2D ultrasound images are irregularly and sparsely distributed in the 3D space. Several 3D reconstruction algorithms have been proposed to synthesize 3D ultrasound volumes based on the acquired 2D images. A challenging task during the reconstruction process is to preserve the texture patterns in the synthesized volume and ensure that all gaps in the volume are correctly filled. This paper presents an adaptive kernel regression algorithm that can effectively reconstruct high-quality freehand 3D ultrasound volumes. The algorithm employs a kernel regression model that enables nonparametric interpolation of the voxel gray-level values. The kernel size of the regression model is adaptively adjusted based on the characteristics of the voxel that is being interpolated. In particular, when the algorithm is employed to interpolate a voxel located in a region with dense ultrasound data samples, the size of the kernel is reduced to preserve the texture patterns. On the other hand, the size of the kernel is increased in areas that include large gaps to enable effective gap filling. The performance of the proposed algorithm was compared with seven previous interpolation approaches by synthesizing freehand 3D ultrasound volumes of a benign breast tumor. The experimental results show that the proposed algorithm outperforms the other interpolation approaches.

  18. A Simple and Robust Sliding Mode Velocity Observer for Moving Coil Actuators in Digital Hydraulic Valves

    DEFF Research Database (Denmark)

    Nørgård, Christian; Schmidt, Lasse; Bech, Michael Møller

    2016-01-01

    This paper focuses on estimating the velocity and position of fast switching digital hydraulic valves actuated by electromagnetic moving coil actuators, based on measurements of the coil current and voltage. The velocity is estimated by a simple first-order sliding mode observer architecture...... and the position is estimated by integrating the estimated velocity. The binary operation of digi-valves enables limiting and resetting the position estimate since the moving member is switched between the mechanical end-stops of the valve. This enables accurate tracking since drifting effects due to measurement...... noise and integration of errors in the velocity estimate may be circumvented. The proposed observer architecture is presented along with stability proofs and initial experimental results. To reveal the optimal observer performance, an optimization of the observer parameters is carried out. Subsequently...

  19. An Integrated Approach to Battery Health Monitoring using Bayesian Regression, Classification and State Estimation

    Data.gov (United States)

    National Aeronautics and Space Administration — The application of the Bayesian theory of managing uncertainty and complexity to regression and classification in the form of Relevance Vector Machine (RVM), and to...

  20. A method for nonlinear exponential regression analysis

    Science.gov (United States)

    Junkin, B. G.

    1971-01-01

    A computer-oriented technique is presented for performing a nonlinear exponential regression analysis on decay-type experimental data. The technique involves the least squares procedure wherein the nonlinear problem is linearized by expansion in a Taylor series. A linear curve fitting procedure for determining the initial nominal estimates for the unknown exponential model parameters is included as an integral part of the technique. A correction matrix was derived and then applied to the nominal estimate to produce an improved set of model parameters. The solution cycle is repeated until some predetermined criterion is satisfied.

  1. Schema generation in recurrent neural nets for intercepting a moving target.

    Science.gov (United States)

    Fleischer, Andreas G

    2010-06-01

    The grasping of a moving object requires the development of a motor strategy to anticipate the trajectory of the target and to compute an optimal course of interception. During the performance of perception-action cycles, a preprogrammed prototypical movement trajectory, a motor schema, may highly reduce the control load. Subjects were asked to hit a target that was moving along a circular path by means of a cursor. Randomized initial target positions and velocities were detected in the periphery of the eyes, resulting in a saccade toward the target. Even when the target disappeared, the eyes followed the target's anticipated course. The Gestalt of the trajectories was dependent on target velocity. The prediction capability of the motor schema was investigated by varying the visibility range of cursor and target. Motor schemata were determined to be of limited precision, and therefore visual feedback was continuously required to intercept the moving target. To intercept a target, the motor schema caused the hand to aim ahead and to adapt to the target trajectory. The control of cursor velocity determined the point of interception. From a modeling point of view, a neural network was developed that allowed the implementation of a motor schema interacting with feedback control in an iterative manner. The neural net of the Wilson type consists of an excitation-diffusion layer allowing the generation of a moving bubble. This activation bubble runs down an eye-centered motor schema and causes a planar arm model to move toward the target. A bubble provides local integration and straightening of the trajectory during repetitive moves. The schema adapts to task demands by learning and serves as forward controller. On the basis of these model considerations the principal problem of embedding motor schemata in generalized control strategies is discussed.

  2. Copy-Move Forgery Detection Technique for Forensic Analysis in Digital Images

    Directory of Open Access Journals (Sweden)

    Toqeer Mahmood

    2016-01-01

    Full Text Available Due to the powerful image editing tools images are open to several manipulations; therefore, their authenticity is becoming questionable especially when images have influential power, for example, in a court of law, news reports, and insurance claims. Image forensic techniques determine the integrity of images by applying various high-tech mechanisms developed in the literature. In this paper, the images are analyzed for a particular type of forgery where a region of an image is copied and pasted onto the same image to create a duplication or to conceal some existing objects. To detect the copy-move forgery attack, images are first divided into overlapping square blocks and DCT components are adopted as the block representations. Due to the high dimensional nature of the feature space, Gaussian RBF kernel PCA is applied to achieve the reduced dimensional feature vector representation that also improved the efficiency during the feature matching. Extensive experiments are performed to evaluate the proposed method in comparison to state of the art. The experimental results reveal that the proposed technique precisely determines the copy-move forgery even when the images are contaminated with blurring, noise, and compression and can effectively detect multiple copy-move forgeries. Hence, the proposed technique provides a computationally efficient and reliable way of copy-move forgery detection that increases the credibility of images in evidence centered applications.

  3. Regression analysis for the social sciences

    CERN Document Server

    Gordon, Rachel A

    2010-01-01

    The book provides graduate students in the social sciences with the basic skills that they need to estimate, interpret, present, and publish basic regression models using contemporary standards. Key features of the book include: interweaving the teaching of statistical concepts with examples developed for the course from publicly-available social science data or drawn from the literature. thorough integration of teaching statistical theory with teaching data processing and analysis. teaching of both SAS and Stata "side-by-side" and use of chapter exercises in which students practice programming and interpretation on the same data set and course exercises in which students can choose their own research questions and data set.

  4. Transforming traditional Tai Ji Quan techniques into integrative movement therapy—Tai Ji Quan: Moving for Better Balance

    Directory of Open Access Journals (Sweden)

    Fuzhong Li

    2014-03-01

    Full Text Available Tai Ji Quan, developed as a martial art, has traditionally served multiple purposes, including self-defense, competition/performance, and health promotion. With respect to health, the benefits historically and anecdotally associated with Tai Ji Quan are now being supported by scientific and clinical research, with mounting evidence indicating its potential value in preventing and managing various diseases and improving well-being and quality of life in middle-aged and older adults. The research findings produced to date have both public health significance and clinical relevance. However, because of its roots in the martial arts, transforming traditional Tai Ji Quan movements and training approaches into contemporary therapeutic programs and functional applications is needed to maximize its ultimate utility. This paper addresses this issue by introducing Tai Ji Quan: Moving for Better Balance, a functional therapy that involves the use of Tai Ji Quan principles and Yang-style-based movements to form an innovative, contemporary therapeutic approach that integrates motor, sensory, and cognitive components to improve postural control, gait, and mobility for older adults and those who have neurodegenerative movement impairments. It provides a synergy of traditional and contemporary Tai Ji Quan practice with the ultimate goal of improving balance and gait, enhancing performance of daily functional tasks, and reducing incidence of falls among older adults.

  5. Market and organizational factors associated with hospital vertical integration into sub-acute care.

    Science.gov (United States)

    Hogan, Tory H; Lemak, Christy Harris; Hearld, Larry R; Sen, Bisakha P; Wheeler, Jack R C; Menachemi, Nir

    2018-04-11

    Changes in payment models incentivize hospitals to vertically integrate into sub-acute care (SAC) services. Through vertical integration into SAC, hospitals have the potential to reduce the transaction costs associated with moving patients throughout the care continuum and reduce the likelihood that patients will be readmitted. The purpose of this study is to examine the correlates of hospital vertical integration into SAC. Using panel data of U.S. acute care hospitals (2008-2012), we conducted logit regression models to examine environmental and organizational factors associated with hospital vertical integration. Results are reported as average marginal effects. Among 3,775 unique hospitals (16,269 hospital-year observations), 25.7% vertically integrated into skilled nursing facilities during at least 1 year of the study period. One measure of complexity, the availability of skilled nursing facilities in a county (ME = -1.780, p integration into SAC. Measures of munificence, percentage of the county population eligible for Medicare (ME = 0.018, p integration into SAC. Dynamism, when measured as the change county population between 2008 and 2011 (ME = 1.19e-06, p integration into SAC. Organizational resources, when measured as swing beds (ME = 0.069, p integration into SAC. Organizational resources, when measured as investor owned (ME = -0.052, p integration into SAC. Hospital adaption to the changing health care landscape through vertical integration varies across market and organizational conditions. Current Centers for Medicare and Medicaid reimbursement programs do not take these factors into consideration. Vertical integration strategy into SAC may be more appropriate under certain market conditions. Hospital leaders may consider how to best align their organization's SAC strategy with their operating environment.

  6. 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)

  7. 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…

  8. TESS: A RELATIVISTIC HYDRODYNAMICS CODE ON A MOVING VORONOI MESH

    International Nuclear Information System (INIS)

    Duffell, Paul C.; MacFadyen, Andrew I.

    2011-01-01

    We have generalized a method for the numerical solution of hyperbolic systems of equations using a dynamic Voronoi tessellation of the computational domain. The Voronoi tessellation is used to generate moving computational meshes for the solution of multidimensional systems of conservation laws in finite-volume form. The mesh-generating points are free to move with arbitrary velocity, with the choice of zero velocity resulting in an Eulerian formulation. Moving the points at the local fluid velocity makes the formulation effectively Lagrangian. We have written the TESS code to solve the equations of compressible hydrodynamics and magnetohydrodynamics for both relativistic and non-relativistic fluids on a dynamic Voronoi mesh. When run in Lagrangian mode, TESS is significantly less diffusive than fixed mesh codes and thus preserves contact discontinuities to high precision while also accurately capturing strong shock waves. TESS is written for Cartesian, spherical, and cylindrical coordinates and is modular so that auxiliary physics solvers are readily integrated into the TESS framework and so that this can be readily adapted to solve general systems of equations. We present results from a series of test problems to demonstrate the performance of TESS and to highlight some of the advantages of the dynamic tessellation method for solving challenging problems in astrophysical fluid dynamics.

  9. Movements of a Sphere Moving Over Smooth and Rough Inclines

    Science.gov (United States)

    Jan, Chyan-Deng

    1992-01-01

    The steady movements of a sphere over a rough incline in air, and over smooth and rough inclines in a liquid were studied theoretically and experimentally. The principle of energy conservation was used to analyze the translation velocities, rolling resistances, and drag coefficients of a sphere moving over the inclines. The rolling resistance to the movement of a sphere from the rough incline was presumed to be caused by collisions and frictional slidings. A varnished wooden board was placed on the bottom of an experimental tilting flume to form a smooth incline and a layer of spheres identical to the sphere moving over them was placed on the smooth wooden board to form a rough incline. Spheres used in the experiments were glass spheres, steel spheres, and golf balls. Experiments show that a sphere moving over a rough incline with negligible fluid drag in air can reach a constant translation velocity. This constant velocity was found to be proportional to the bed inclination (between 11 ^circ and 21^circ) and the square root of the sphere's diameter, but seemingly independent of the sphere's specific gravity. Two empirical coefficients in the theoretical expression of the sphere's translation velocity were determined by experiments. The collision and friction parts of the shear stress exerted on the interface between the moving sphere and rough incline were determined. The ratio of collision to friction parts appears to increase with increase in the bed inclination. These two parts seem to be of the same order of magnitude. The rolling resistances and the relations between the drag coefficient and Reynolds number for a sphere moving over smooth and rough inclines in a liquid, such as water or salad oil, were determined by a regression analysis based on experimental data. It was found that the drag coefficient for a sphere over the rough incline is larger than that for a sphere over the smooth incline, and both of which are much larger than that for a sphere in free

  10. Regression analysis with categorized regression calibrated exposure: some interesting findings

    Directory of Open Access Journals (Sweden)

    Hjartåker Anette

    2006-07-01

    Full Text Available Abstract Background Regression calibration as a method for handling measurement error is becoming increasingly well-known and used in epidemiologic research. However, the standard version of the method is not appropriate for exposure analyzed on a categorical (e.g. quintile scale, an approach commonly used in epidemiologic studies. A tempting solution could then be to use the predicted continuous exposure obtained through the regression calibration method and treat it as an approximation to the true exposure, that is, include the categorized calibrated exposure in the main regression analysis. Methods We use semi-analytical calculations and simulations to evaluate the performance of the proposed approach compared to the naive approach of not correcting for measurement error, in situations where analyses are performed on quintile scale and when incorporating the original scale into the categorical variables, respectively. We also present analyses of real data, containing measures of folate intake and depression, from the Norwegian Women and Cancer study (NOWAC. Results In cases where extra information is available through replicated measurements and not validation data, regression calibration does not maintain important qualities of the true exposure distribution, thus estimates of variance and percentiles can be severely biased. We show that the outlined approach maintains much, in some cases all, of the misclassification found in the observed exposure. For that reason, regression analysis with the corrected variable included on a categorical scale is still biased. In some cases the corrected estimates are analytically equal to those obtained by the naive approach. Regression calibration is however vastly superior to the naive method when applying the medians of each category in the analysis. Conclusion Regression calibration in its most well-known form is not appropriate for measurement error correction when the exposure is analyzed on a

  11. Minefield overwatch using moving target indicator radar

    Science.gov (United States)

    Donadio, Anthony; Ewing, Robert; Kenneally, William J.; Santapietro, John J.

    1999-07-01

    Traditional antipersonnel land mines are an effective military tool, but they are unable to distinguish friend from foe, or civilian from military personnel. The concept described here uses an advanced moving target indicator (MTI) radar to scan the minefield in order to detect movement towards or within the minefield, coupled with visual identification by a human operator and a communication link for command and control. Selected mines in the minefield can then be activated by means of the command link. In order to demonstrate this concept, a 3D, interactive simulation has been developed. This simulation builds on previous work by integrating a detailed analytical model of an MTI radar. This model has been tailored to the specific application of detection of slowly moving dismounted entities immersed in ground clutter. The model incorporates the effects of internal scatterer motion and antenna scanning modulation in order to provide a realistic representation of the detection problem in this environment. The angle information on the MTI target detection is then passed to a virtual 3D sight which cues a human operator to the target location. In addition, radar propagation effects and an experimental design in which the radar itself is used as a command link are explored.

  12. A lifelong journey of moving beyond wartime trauma for survivors from Hiroshima and Pearl Harbor.

    Science.gov (United States)

    Liehr, Patricia; Nishimura, Chie; Ito, Mio; Wands, Lisa Marie; Takahashi, Ryutaro

    2011-01-01

    This study examines 51 stories of health, shared by people who survived the wartime trauma of Hiroshima and Pearl Harbor, seeking to identify turning points that moved participants along over their lifetime. The central turning point for Hiroshima survivors was "becoming Hibabusha (A-bomb survivor)" and for Pearl Harbor survivors was "honoring the memory and setting it aside." Wartime trauma was permanently integrated into survivors' histories, surfacing steadily over decades for Hiroshima survivors and intermittently over decades for Pearl Harbor survivors. Regardless of experience or nationality, participants moved through wartime trauma by connecting with others, pursuing personal and global peace.

  13. Comparison of stochastic and regression based methods for quantification of predictive uncertainty of model-simulated wellhead protection zones in heterogeneous aquifers

    DEFF Research Database (Denmark)

    Christensen, Steen; Moore, C.; Doherty, J.

    2006-01-01

    accurate and required a few hundred model calls to be computed. (b) The linearized regression-based interval (Cooley, 2004) required just over a hundred model calls and also appeared to be nearly correct. (c) The calibration-constrained Monte-Carlo interval (Doherty, 2003) was found to be narrower than......For a synthetic case we computed three types of individual prediction intervals for the location of the aquifer entry point of a particle that moves through a heterogeneous aquifer and ends up in a pumping well. (a) The nonlinear regression-based interval (Cooley, 2004) was found to be nearly...... the regression-based intervals but required about half a million model calls. It is unclear whether or not this type of prediction interval is accurate....

  14. 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.

  15. Moving Griffith crack in an orthotropic strip with punches at boundary faces

    Directory of Open Access Journals (Sweden)

    S. Mukherjee

    2005-01-01

    Full Text Available Integral transform technique is employed to solve the elastodynamic problem of steady-state propagation of a Griffith crack centrally situated along the midplane of orthotropic strip of finite thickness 2h and subjected to point loading with centrally situated moving punches under constant pressure along the boundaries of the layer. The problem is reduced to the solution of a pair of simultaneous singular integral equations with Cauchy-type singularities which have finally been solved through the finite Hilbert transform technique. For large h, analytical expression for the stress intensity factor at the crack tip is obtained. Graphical plots of the numerical results are also presented.

  16. Regression analysis for the social sciences

    CERN Document Server

    Gordon, Rachel A

    2015-01-01

    Provides graduate students in the social sciences with the basic skills they need to estimate, interpret, present, and publish basic regression models using contemporary standards. Key features of the book include: interweaving the teaching of statistical concepts with examples developed for the course from publicly-available social science data or drawn from the literature. thorough integration of teaching statistical theory with teaching data processing and analysis. teaching of Stata and use of chapter exercises in which students practice programming and interpretation on the same data set. A separate set of exercises allows students to select a data set to apply the concepts learned in each chapter to a research question of interest to them, all updated for this edition.

  17. 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....

  18. 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...

  19. Time-adaptive quantile regression

    DEFF Research Database (Denmark)

    Møller, Jan Kloppenborg; Nielsen, Henrik Aalborg; Madsen, Henrik

    2008-01-01

    and an updating procedure are combined into a new algorithm for time-adaptive quantile regression, which generates new solutions on the basis of the old solution, leading to savings in computation time. The suggested algorithm is tested against a static quantile regression model on a data set with wind power......An algorithm for time-adaptive quantile regression is presented. The algorithm is based on the simplex algorithm, and the linear optimization formulation of the quantile regression problem is given. The observations have been split to allow a direct use of the simplex algorithm. The simplex method...... production, where the models combine splines and quantile regression. The comparison indicates superior performance for the time-adaptive quantile regression in all the performance parameters considered....

  20. Classical radiation theory of charged particles moving in electromagnetic fields in nonabsorbable isotropic media

    International Nuclear Information System (INIS)

    Konstantinovich, A.V.; Melnychuk, S.V.; Konstantinovich, I.A.

    2002-01-01

    The integral expressions for spectral-angular and spectral distributions of the radiation power of heterogeneous charged particles system moving on arbitrary trajectory in nonabsorbable isotropic media media with ε≠1 , μ≠1 are obtained using the Lorentz's self-interaction method. In this method a proper electromagnetic field, acting on electron, is defined as a semi difference between retarded and advanced potentials (Dirac, 1938). The power spectrum of Cherenkov radiation for the linear uniformly moving heterogeneous system of charged particles are obtained. It is found that the expression for the radiation power of heterogeneous system of charged particles becomes simplified when a system of charged particles is homogeneous. In this case the radiation power includes the coherent factor. It is shown what the redistribution effects in energy of the radiation spectrum of the studied system are caused by the coherent factor. The radiation spectrum of the system of electrons moving in a circle in this medium is discrete. The Doppler effect causes the appearance of the new harmonics for the system of electrons moving in a spiral. These harmonics form the region of continuous radiation spectrum. (authors)

  1. [A SAS marco program for batch processing of univariate Cox regression analysis for great database].

    Science.gov (United States)

    Yang, Rendong; Xiong, Jie; Peng, Yangqin; Peng, Xiaoning; Zeng, Xiaomin

    2015-02-01

    To realize batch processing of univariate Cox regression analysis for great database by SAS marco program. We wrote a SAS macro program, which can filter, integrate, and export P values to Excel by SAS9.2. The program was used for screening survival correlated RNA molecules of ovarian cancer. A SAS marco program could finish the batch processing of univariate Cox regression analysis, the selection and export of the results. The SAS macro program has potential applications in reducing the workload of statistical analysis and providing a basis for batch processing of univariate Cox regression analysis.

  2. Frequency modulation at a moving material interface and a conservation law for wave number. [acoustic wave reflection and transmission

    Science.gov (United States)

    Kleinstein, G. G.; Gunzburger, M. D.

    1976-01-01

    An integral conservation law for wave numbers is considered. In order to test the validity of the proposed conservation law, a complete solution for the reflection and transmission of an acoustic wave impinging normally on a material interface moving at a constant speed is derived. The agreement between the frequency condition thus deduced from the dynamic equations of motion and the frequency condition derived from the jump condition associated with the integral equation supports the proposed law as a true conservation law. Additional comparisons such as amplitude discontinuities and Snells' law in a moving media further confirm the stated proposition. Results are stated concerning frequency and wave number relations across a shock front as predicted by the proposed conservation law.

  3. The Integration of Extrarational and Rational Learning Processes: Moving Towards the Whole Learner.

    Science.gov (United States)

    Puk, Tom

    1996-01-01

    Discusses the dichotomy between rational and nonrational learning processes, arguing for an integration of both. Reviews information processing theory and related learning strategies. Presents a model instructional strategy that fully integrates rational and nonrational processes. Describes implications for teaching and learning of the learning…

  4. Moving ERP Systems to the Cloud - Data Security Issues

    Directory of Open Access Journals (Sweden)

    Pablo Saa

    2017-08-01

    Full Text Available This paper brings to light data security issues and concerns for organizations by moving their Enterprise Resource Planning (ERP systems to the cloud. Cloud computing has become the new trend of how organizations conduct business and has enabled them to innovate and compete in a dynamic environment through new and innovative business models. The growing popularity and success of the cloud has led to the emergence of cloud-based Software-as-a-Service (SaaS ERP systems, a new alternative approach to traditional on-premise ERP systems. Cloud-based ERP has a myriad of benefits for organizations. However, infrastructure engineers need to address data security issues before moving their enterprise applications to the cloud. Cloud-based ERP raises specific concerns about the confidentiality and integrity of the data stored in the cloud. Such concerns that affect the adoption of cloud-based ERP are based on the size of the organization. Small to medium enterprises (SMEs gain the maximum benefits from cloud-based ERP as many of the concerns around data security are not relevant to them. On the contrary, larger organizations are more cautious in moving their mission critical enterprise applications to the cloud. A hybrid solution where organizations can choose to keep their sensitive applications on-premise while leveraging the benefits of the cloud is proposed in this paper as an effective solution that is gaining momentum and popularity for large organizations.

  5. Screening of a moving charge in a nonequilibrium plasma

    International Nuclear Information System (INIS)

    Filippov, A. V.; Zagorodny, A. G.; Momot, A. I.; Pal', A. F.; Starostin, A. N.

    2009-01-01

    Based on the model of point sinks, we consider the problem on the screening of the charge of a moving macroparticle in a nonequilibrium plasma. The characteristic formation times of the polarization cloud around such a macroparticle have been determined by the method of a three-dimensional integral Fourier transformation in spatial variables and a Laplace transformation in time. The screening effect is shown to be enhanced with increasing macroparticle velocity. We consider the applicability conditions for the model of point sinks and establish that the domain of applicability of the results obtained expands with decreasing gas ionization rate and macroparticle size. We consider the problem of charge screening at low velocities and establish that the stationary potential of the moving charge has a dipole component that becomes dominant at large distances. We show that the direction of the force exerted on the dust particle by the induced charges generally depends on the relationship between the transport and loss coefficients of the plasma particles in a plasma. When the Langevin ion recombination coefficient β iL = 4πeμ i exceeds the electron-ion recombination coefficient β ei , this force will accelerate the dust particles in the presence of sinks. In the absence of sinks or when β ei > β iL , this force will be opposite in direction to the dust particle velocity. We also consider the problem on the energy and force of interaction between a moving charged macroparticle and the induced charges

  6. 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.

  7. 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.

  8. 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.

  9. Continuous processing of recombinant proteins: integration of refolding and purification using simulated moving bed size-exclusion chromatography with buffer recycling.

    Science.gov (United States)

    Wellhoefer, Martin; Sprinzl, Wolfgang; Hahn, Rainer; Jungbauer, Alois

    2014-04-11

    Continuous processing of recombinant proteins was accomplished by combining continuous matrix-assisted refolding and purification by tandem simulated moving bed (SMB) size-exclusion chromatography (SEC). Recombinant proteins, N(pro) fusion proteins from inclusion bodies were dissolved with NaOH and refolded in the SMB system with a closed-loop set-up with refolding buffer as the desorbent buffer and buffer recycling of the refolding buffer of the raffinate by tangential flow filtration. For further purification of the refolded proteins, a second SMB operation also based on SEC was added. The whole system could be operated isocratically with refolding buffer as the desorbent buffer, and buffer recycling could also be applied in the purification step. Thus, a significant reduction in buffer consumption was achieved. The system was evaluated with two proteins, the N(pro) fusion pep6His and N(pro) fusion MCP-1. Refolding solution, which contained residual N(pro) fusion peptide, the cleaved autoprotease N(pro), and the cleaved target peptide was used as feed solution. Full separation of the cleaved target peptide from residual proteins was achieved at a purity and recovery in the raffinate and extract, respectively, of approximately 100%. In addition, more than 99% of the refolding buffer of the raffinate was recycled. A comparison of throughput, productivity, and buffer consumption of the integrated continuous process with two batch processes demonstrated that up to 60-fold higher throughput, up to 180-fold higher productivity, and at least 28-fold lower buffer consumption can be obtained by the integrated continuous process, which compensates for the higher complexity. Copyright © 2014 Elsevier B.V. All rights reserved.

  10. Seemingly Unrelated Regression Approach for GSTARIMA Model to Forecast Rain Fall Data in Malang Southern Region Districts

    Directory of Open Access Journals (Sweden)

    Siti Choirun Nisak

    2016-06-01

    Full Text Available Time series forecasting models can be used to predict phenomena that occur in nature. Generalized Space Time Autoregressive (GSTAR is one of time series model used to forecast the data consisting the elements of time and space. This model is limited to the stationary and non-seasonal data. Generalized Space Time Autoregressive Integrated Moving Average (GSTARIMA is GSTAR development model that accommodates the non-stationary and seasonal data. Ordinary Least Squares (OLS is method used to estimate parameter of GSTARIMA model. Estimation parameter of GSTARIMA model using OLS will not produce efficiently estimator if there is an error correlation between spaces. Ordinary Least Square (OLS assumes the variance-covariance matrix has a constant error ~(, but in fact, the observatory spaces are correlated so that variance-covariance matrix of the error is not constant. Therefore, Seemingly Unrelated Regression (SUR approach is used to accommodate the weakness of the OLS. SUR assumption is ~(, for estimating parameters GSTARIMA model. The method to estimate parameter of SUR is Generalized Least Square (GLS. Applications GSTARIMA-SUR models for rainfall data in the region Malang obtained GSTARIMA models ((1(1,12,36,(0,(1-SUR with determination coefficient generated with the average of 57.726%.

  11. Appropriate assessment of neighborhood effects on individual health: integrating random and fixed effects in multilevel logistic regression

    DEFF Research Database (Denmark)

    Larsen, Klaus; Merlo, Juan

    2005-01-01

    The logistic regression model is frequently used in epidemiologic studies, yielding odds ratio or relative risk interpretations. Inspired by the theory of linear normal models, the logistic regression model has been extended to allow for correlated responses by introducing random effects. However......, the model does not inherit the interpretational features of the normal model. In this paper, the authors argue that the existing measures are unsatisfactory (and some of them are even improper) when quantifying results from multilevel logistic regression analyses. The authors suggest a measure...... of heterogeneity, the median odds ratio, that quantifies cluster heterogeneity and facilitates a direct comparison between covariate effects and the magnitude of heterogeneity in terms of well-known odds ratios. Quantifying cluster-level covariates in a meaningful way is a challenge in multilevel logistic...

  12. 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.

  13. Integration of thermal insulation coating and moving-air-cavity in a cool roof system for attic temperature reduction

    International Nuclear Information System (INIS)

    Yew, M.C.; Ramli Sulong, N.H.; Chong, W.T.; Poh, S.C.; Ang, B.C.; Tan, K.H.

    2013-01-01

    Highlights: • A novel integrated cool roof system for attic temperature reduction is introduced. • 13 °C temperature reduction achieved due to its efficient heat transfer mechanism. • Aluminium tube cavity of the roof is able to reduce the attic temperature. • This positive result is due to its efficient heat reflection and hot air rejection. • Thermal insulation coating incorporates the usage of eggshell waste as bio-filler. - Abstract: Cool roof systems play a significant role in enhancing the comfort level of occupants by reducing the attic temperature of the building. Heat transmission through the roof can be reduced by applying thermal insulation coating (TIC) on the roof and/or installing insulation under the roof of the attic. This paper focuses on a TIC integrated with a series of aluminium tubes that are installed on the underside of the metal roof. In this study, the recycled aluminium cans were arranged into tubes that act as a moving-air-cavity (MAC). The TIC was formulated using titanium dioxide pigment with chicken eggshell (CES) waste as bio-filler bound together by a polyurethane resin binder. The thermal conductivity of the thermal insulation paint was measured using KD2 Pro Thermal Properties Analyzer. Four types of cool roof systems were designed and the performances were evaluated. The experimental works were carried out indoors by using halogen light bulbs followed by comparison of the roof and attic temperatures. The temperature of the surrounding air during testing was approximately 27.5 °C. The cool roof that incorporated both TIC and MAC with opened attic inlet showed a significant improvement with a reduction of up to 13 °C (from 42.4 °C to 29.6 °C) in the attic temperature compared to the conventional roof system. The significant difference in the results is due to the low thermal conductivity of the thermal insulation paint (0.107 W/mK) as well as the usage of aluminium tubes in the roof cavity that was able to transfer

  14. Regression analysis by example

    CERN Document Server

    Chatterjee, Samprit

    2012-01-01

    Praise for the Fourth Edition: ""This book is . . . an excellent source of examples for regression analysis. It has been and still is readily readable and understandable."" -Journal of the American Statistical Association Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. Regression Analysis by Example, Fifth Edition has been expanded

  15. Applied logistic regression

    CERN Document Server

    Hosmer, David W; Sturdivant, Rodney X

    2013-01-01

     A new edition of the definitive guide to logistic regression modeling for health science and other applications This thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables. Applied Logistic Regression, Third Edition emphasizes applications in the health sciences and handpicks topics that best suit the use of modern statistical software. The book provides readers with state-of-

  16. 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.

  17. Normalization Ridge Regression in Practice I: Comparisons Between Ordinary Least Squares, Ridge Regression and Normalization Ridge Regression.

    Science.gov (United States)

    Bulcock, J. W.

    The problem of model estimation when the data are collinear was examined. Though the ridge regression (RR) outperforms ordinary least squares (OLS) regression in the presence of acute multicollinearity, it is not a problem free technique for reducing the variance of the estimates. It is a stochastic procedure when it should be nonstochastic and it…

  18. 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...

  19. Vector regression introduced

    Directory of Open Access Journals (Sweden)

    Mok Tik

    2014-06-01

    Full Text Available This study formulates regression of vector data that will enable statistical analysis of various geodetic phenomena such as, polar motion, ocean currents, typhoon/hurricane tracking, crustal deformations, and precursory earthquake signals. The observed vector variable of an event (dependent vector variable is expressed as a function of a number of hypothesized phenomena realized also as vector variables (independent vector variables and/or scalar variables that are likely to impact the dependent vector variable. The proposed representation has the unique property of solving the coefficients of independent vector variables (explanatory variables also as vectors, hence it supersedes multivariate multiple regression models, in which the unknown coefficients are scalar quantities. For the solution, complex numbers are used to rep- resent vector information, and the method of least squares is deployed to estimate the vector model parameters after transforming the complex vector regression model into a real vector regression model through isomorphism. Various operational statistics for testing the predictive significance of the estimated vector parameter coefficients are also derived. A simple numerical example demonstrates the use of the proposed vector regression analysis in modeling typhoon paths.

  20. What Happens to Young People Moving to Germany, Norway and the UK to Find Work?

    DEFF Research Database (Denmark)

    Leschke, Janine; Seeleib-Kaiser, Martin; Spreckelsen, Thees

    2017-01-01

    One of the most distinctive characteristics of youth employment in recent years has been the large proportion of young people who move abroad to find work (O’Reilly et al. 2015). But how well integrated are these young EU migrants? Are they offered new opportunities by these jobs or are they part...

  1. 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…

  2. Applied linear regression

    CERN Document Server

    Weisberg, Sanford

    2013-01-01

    Praise for the Third Edition ""...this is an excellent book which could easily be used as a course text...""-International Statistical Institute The Fourth Edition of Applied Linear Regression provides a thorough update of the basic theory and methodology of linear regression modeling. Demonstrating the practical applications of linear regression analysis techniques, the Fourth Edition uses interesting, real-world exercises and examples. Stressing central concepts such as model building, understanding parameters, assessing fit and reliability, and drawing conclusions, the new edition illus

  3. Automatic detection, tracking and sensor integration

    Science.gov (United States)

    Trunk, G. V.

    1988-06-01

    This report surveys the state of the art of automatic detection, tracking, and sensor integration. In the area of detection, various noncoherent integrators such as the moving window integrator, feedback integrator, two-pole filter, binary integrator, and batch processor are discussed. Next, the three techniques for controlling false alarms, adapting thresholds, nonparametric detectors, and clutter maps are presented. In the area of tracking, a general outline is given of a track-while-scan system, and then a discussion is presented of the file system, contact-entry logic, coordinate systems, tracking filters, maneuver-following logic, tracking initiating, track-drop logic, and correlation procedures. Finally, in the area of multisensor integration the problems of colocated-radar integration, multisite-radar integration, radar-IFF integration, and radar-DF bearing strobe integration are treated.

  4. Mortality at older ages and moves in residential and sheltered housing: evidence from the UK

    Science.gov (United States)

    Robards, James; Evandrou, Maria; Falkingham, Jane; Vlachantoni, Athina

    2014-01-01

    Background The study examines the relationship between transitions to residential and sheltered housing and mortality. Past research has focused on housing moves over extended time periods and subsequent mortality. In this paper, annual housing transitions allow the identification of the patterning of housing moves, the duration of stay in each sector and the assessment of the relationship of preceding moves to a heightened risk of dying. Methods The study uses longitudinal data constructed from pooled observations from the British Household Panel Survey (waves 1993–2008). Records were pooled for all cases where the survey member is 65 years or over and living in private housing at baseline and observed at three consecutive time points, including baseline (N=23 727). Binary logistic regression (death as outcome three waves after baseline) explored the relative strength of different housing transitions, controlling for sociodemographic predictors. Results (1) Transition to residential housing within the previous 12 months was associated with the highest mortality risk. (2) Results support existing findings showing an interaction between marital status and mortality, whereby unmarried persons were more likely to die. (3) Higher male mortality was observed across all housing transitions. Conclusions An older person's move to residential housing is associated with a higher risk of mortality within 12 months of the move. Survivors living in residential housing for more than a year, show a similar probability of dying to those living in sheltered housing. Results highlight that it is the type of accommodation that affects an older person's mortality risk, and the length of time they spend there. PMID:24638058

  5. Moving On: Farmer Education in Integrated Insect Pest and Disease Management

    NARCIS (Netherlands)

    Jiggins, J.L.S.; Mancini, F.

    2009-01-01

    This chapter explores intensive hands-on occupational education for farmers in selected European, African, Latin American countries and in south India. An Indian case study of Farmer Field Schools for Integrated Pest and Production Management (IPPM) to ensure food security and livelihood improvement

  6. Heat transfer from the moving heat source of arbitrary shape

    International Nuclear Information System (INIS)

    Fomin, Sergei A.

    2000-01-01

    The present research is related to contact melting by a moving heat source of arbitrary shape. Heat conduction in the melting material is governed by 3D differential equation, where the thermal conductivity of the surrounding material is assumed to be strongly temperature dependent. By using the Green's formula, the boundary-value problem is converted to the boundary integral equation. This non-linear equation is solved numerically by interactions utilizing the boundary element method. Different shapes of heat sources are investigated. Since the obtained integral equation is the Fredholm type equation of the first kind and belongs to the family of so-called ill-posed problems, therefore, supplementary computations, that verify the stability of numerical algorithm, are provided. For the special cases associated with thermodrilling technology, some analytical estimations and solutions are obtained. Particularly, if the melting velocity is high (Pe>10), asymptotic solutions are found. In this case the integral equation is significantly reduced, that simplifies the computations. Numerical results are in good agreement with the closed-form solutions available for the elliptical shape of a solid-liquid interface. (author)

  7. 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…

  8. Influence of foundation mass and surface roughness on dynamic response of beam on dynamic foundation subjected to the moving load

    Science.gov (United States)

    Tran Quoc, Tinh; Khong Trong, Toan; Luong Van, Hai

    2018-04-01

    In this paper, Improved Moving Element Method (IMEM) is used to analyze the dynamic response of Euler-Bernoulli beam structures on the dynamic foundation model subjected to the moving load. The effects of characteristic foundation model parameters such as Winkler stiffness, shear layer based on the Pasternak model, viscoelastic dashpot and characteristic parameter of mass on foundation. Beams are modeled by moving elements while the load is fixed. Based on the principle of the publicly virtual balancing and the theory of moving element method, the motion differential equation of the system is established and solved by means of the numerical integration based on the Newmark algorithm. The influence of mass on foundation and the roughness of the beam surface on the dynamic response of beam are examined in details.

  9. 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

  10. 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

  11. 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.

  12. Understanding poisson regression.

    Science.gov (United States)

    Hayat, Matthew J; Higgins, Melinda

    2014-04-01

    Nurse investigators often collect study data in the form of counts. Traditional methods of data analysis have historically approached analysis of count data either as if the count data were continuous and normally distributed or with dichotomization of the counts into the categories of occurred or did not occur. These outdated methods for analyzing count data have been replaced with more appropriate statistical methods that make use of the Poisson probability distribution, which is useful for analyzing count data. The purpose of this article is to provide an overview of the Poisson distribution and its use in Poisson regression. Assumption violations for the standard Poisson regression model are addressed with alternative approaches, including addition of an overdispersion parameter or negative binomial regression. An illustrative example is presented with an application from the ENSPIRE study, and regression modeling of comorbidity data is included for illustrative purposes. Copyright 2014, SLACK Incorporated.

  13. Alternative Methods of Regression

    CERN Document Server

    Birkes, David

    2011-01-01

    Of related interest. Nonlinear Regression Analysis and its Applications Douglas M. Bates and Donald G. Watts ".an extraordinary presentation of concepts and methods concerning the use and analysis of nonlinear regression models.highly recommend[ed].for anyone needing to use and/or understand issues concerning the analysis of nonlinear regression models." --Technometrics This book provides a balance between theory and practice supported by extensive displays of instructive geometrical constructs. Numerous in-depth case studies illustrate the use of nonlinear regression analysis--with all data s

  14. Time Series ARIMA Models of Undergraduate Grade Point Average.

    Science.gov (United States)

    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…

  15. Study on moving target detection to passive radar based on FM broadcast transmitter

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Target detection by a noncooperative illuminator is a topic of general interest in the electronic warfare field.First of all,direct-path interference(DPI)suppression which is the technique of bottleneck of moving target detection by a noncooperative frequency modulation(FM) broadcast transmitter is analyzed in this article;Secondly,a space-time-frequency domain synthetic solution to this problem is introduced:Adaptive nulling array processing is considered in the space domain,DPI cancellation based on adaptive fractional delay interpolation(AFDI)technique is used in planned time domain,and long-time coherent integration is utilized in the frequency domain;Finally,an experimental system is planned by considering FM broadcast transmitter as a noncooperative illuminator,Simulation results by real collected data show that the proposed method has a better performance of moving target detection.

  16. Path planning for first responders in the presence of moving obstacles

    Directory of Open Access Journals (Sweden)

    Zhiyong Wang

    2015-06-01

    Full Text Available Navigation services have gained much importance for all kinds of human activities ranging from tourist navigation to support of rescue teams in disaster management. However, despite the considerable amount of route guidance research that has been performed, many issues that are related to navigation for first responders still need to be addressed. During disasters, emergencies can result in different types of moving obstacles (e.g., fires, plumes, floods, which make some parts of the road network temporarily unavailable. After such incidents occur, responders have to go to different destinations to perform their tasks in the environment affected by the disaster. Therefore they need a path planner that is capable of dealing with such moving obstacles, as well as generating and coordinating their routes quickly and efficiently. During the past decades, more and more hazard simulations, which can modify the models with incorporation of dynamic data from the field, have been developed. These hazard simulations use methods such as data assimilation, stochastic estimation, and adaptive measurement techniques, and are able to generate more reliable results of hazards. This would allow the hazard simulation models to provide valuable information regarding the state of road networks affected by hazards, which supports path planning for first responders among the moving obstacles. The objective of this research is to develop an integrated navigation system for first responders in the presence of moving obstacles. Such system should be able to navigate one or more responders to one or multiple destinations avoiding the moving obstacles, using the predicted information of the moving obstacles generated from by hazard simulations. In this dissertation, the objective we have is expressed as the following research question: How do we safely and efficiently navigate one or more first responders to one or more destinations avoiding moving obstacles? To address

  17. Introduction to regression graphics

    CERN Document Server

    Cook, R Dennis

    2009-01-01

    Covers the use of dynamic and interactive computer graphics in linear regression analysis, focusing on analytical graphics. Features new techniques like plot rotation. The authors have composed their own regression code, using Xlisp-Stat language called R-code, which is a nearly complete system for linear regression analysis and can be utilized as the main computer program in a linear regression course. The accompanying disks, for both Macintosh and Windows computers, contain the R-code and Xlisp-Stat. An Instructor's Manual presenting detailed solutions to all the problems in the book is ava

  18. 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.

  19. Heat transfer in flow past a continuously moving semi-infinite flat plate in transverse magnetic field with heat flux

    Digital Repository Service at National Institute of Oceanography (India)

    Murty, T.V.R.

    Thermal boundary layer on a continuously moving semi-infinite flat plate in the presence of transverse magnetic field with heat flux has been examined. Similarity solutions have been derived and the resulting equations are integrated numerically...

  20. 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...

  1. Dynamic analysis of an axially moving beam subject to inner pressure using finite element method

    Energy Technology Data Exchange (ETDEWEB)

    Hua, Hongliang; Qiu, Ming; Liao, Zhenqiang [Nanjing University of Science and Technology, Nanjing (China)

    2017-06-15

    A dynamic model of an axially moving flexible beam subject to an inner pressure is present. The coupling principle between a flexible beam and inner pressure is analyzed first, and the potential energy of the inner pressure due to the beam bending is derived using the principle of virtual work. A 1D hollow beam element contain inner pressure is established. The finite element method and Lagrange’s equation are used to derive the motion equations of the axially moving system. The dynamic responses are analyzed by Newmark-β time integration method. Based on the computed dynamic responses, the effects of inner pressure on beam dynamics are discussed. Some interesting phenomenon is observed.

  2. Data-Driven Jump Detection Thresholds for Application in Jump Regressions

    Directory of Open Access Journals (Sweden)

    Robert Davies

    2018-03-01

    Full Text Available This paper develops a method to select the threshold in threshold-based jump detection methods. The method is motivated by an analysis of threshold-based jump detection methods in the context of jump-diffusion models. We show that over the range of sampling frequencies a researcher is most likely to encounter that the usual in-fill asymptotics provide a poor guide for selecting the jump threshold. Because of this we develop a sample-based method. Our method estimates the number of jumps over a grid of thresholds and selects the optimal threshold at what we term the ‘take-off’ point in the estimated number of jumps. We show that this method consistently estimates the jumps and their indices as the sampling interval goes to zero. In several Monte Carlo studies we evaluate the performance of our method based on its ability to accurately locate jumps and its ability to distinguish between true jumps and large diffusive moves. In one of these Monte Carlo studies we evaluate the performance of our method in a jump regression context. Finally, we apply our method in two empirical studies. In one we estimate the number of jumps and report the jump threshold our method selects for three commonly used market indices. In the other empirical application we perform a series of jump regressions using our method to select the jump threshold.

  3. 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.

  4. 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.

  5. Flexible meta-regression to assess the shape of the benzene-leukemia exposure-response curve.

    NARCIS (Netherlands)

    Vlaanderen, J.J.|info:eu-repo/dai/nl/31403160X; Portengen, L.|info:eu-repo/dai/nl/269224742; Rothman, N.; Lan, Q.; Kromhout, H.|info:eu-repo/dai/nl/074385224; Vermeulen, R.|info:eu-repo/dai/nl/216532620

    2010-01-01

    BACKGROUND: Previous evaluations of the shape of the benzene-leukemia exposure-response curve (ERC) were based on a single set or on small sets of human occupational studies. Integrating evidence from all available studies that are of sufficient quality combined with flexible meta-regression models

  6. Prospective in-patient cohort study of moves between levels of therapeutic security: the DUNDRUM-1 triage security, DUNDRUM-3 programme completion and DUNDRUM-4 recovery scales and the HCR-20

    Directory of Open Access Journals (Sweden)

    Davoren Mary

    2012-07-01

    Full Text Available Abstract Background We examined whether new structured professional judgment instruments for assessing need for therapeutic security, treatment completion and recovery in forensic settings were related to moves from higher to lower levels of therapeutic security and added anything to assessment of risk. Methods This was a prospective naturalistic twelve month observational study of a cohort of patients in a forensic hospital placed according to their need for therapeutic security along a pathway of moves from high to progressively less secure units in preparation for discharge. Patients were assessed using the DUNDRUM-1 triage security scale, the DUNDRUM-3 programme completion scale and the DUNDRUM-4 recovery scale and assessments of risk of violence, self harm and suicide, symptom severity and global function. Patients were subsequently observed for positive moves to less secure units and negative moves to more secure units. Results There were 86 male patients at baseline with mean follow-up 0.9 years, 11 positive and 9 negative moves. For positive moves, logistic regression indicated that along with location at baseline, the DUNDRUM-1, HCR-20 dynamic and PANSS general symptom scores were associated with subsequent positive moves. The receiver operating characteristic was significant for the DUNDRUM-1 while ANOVA co-varying for both location at baseline and HCR-20 dynamic score was significant for DUNDRUM-1. For negative moves, logistic regression showed DUNDRUM-1 and HCR-20 dynamic scores were associated with subsequent negative moves, along with DUNDRUM-3 and PANSS negative symptoms in some models. The receiver operating characteristic was significant for the DUNDRUM-4 recovery and HCR-20 dynamic scores with DUNDRUM-1, DUNDRUM-3, PANSS general and GAF marginal. ANOVA co-varying for both location at baseline and HCR-20 dynamic scores showed only DUNDRUM-1 and PANSS negative symptoms associated with subsequent negative moves. Conclusions

  7. Prospective in-patient cohort study of moves between levels of therapeutic security: the DUNDRUM-1 triage security, DUNDRUM-3 programme completion and DUNDRUM-4 recovery scales and the HCR-20.

    Science.gov (United States)

    Davoren, Mary; O'Dwyer, Sarah; Abidin, Zareena; Naughton, Leena; Gibbons, Olivia; Doyle, Elaine; McDonnell, Kim; Monks, Stephen; Kennedy, Harry G

    2012-07-13

    We examined whether new structured professional judgment instruments for assessing need for therapeutic security, treatment completion and recovery in forensic settings were related to moves from higher to lower levels of therapeutic security and added anything to assessment of risk. This was a prospective naturalistic twelve month observational study of a cohort of patients in a forensic hospital placed according to their need for therapeutic security along a pathway of moves from high to progressively less secure units in preparation for discharge. Patients were assessed using the DUNDRUM-1 triage security scale, the DUNDRUM-3 programme completion scale and the DUNDRUM-4 recovery scale and assessments of risk of violence, self harm and suicide, symptom severity and global function. Patients were subsequently observed for positive moves to less secure units and negative moves to more secure units. There were 86 male patients at baseline with mean follow-up 0.9 years, 11 positive and 9 negative moves. For positive moves, logistic regression indicated that along with location at baseline, the DUNDRUM-1, HCR-20 dynamic and PANSS general symptom scores were associated with subsequent positive moves. The receiver operating characteristic was significant for the DUNDRUM-1 while ANOVA co-varying for both location at baseline and HCR-20 dynamic score was significant for DUNDRUM-1. For negative moves, logistic regression showed DUNDRUM-1 and HCR-20 dynamic scores were associated with subsequent negative moves, along with DUNDRUM-3 and PANSS negative symptoms in some models. The receiver operating characteristic was significant for the DUNDRUM-4 recovery and HCR-20 dynamic scores with DUNDRUM-1, DUNDRUM-3, PANSS general and GAF marginal. ANOVA co-varying for both location at baseline and HCR-20 dynamic scores showed only DUNDRUM-1 and PANSS negative symptoms associated with subsequent negative moves. Clinicians appear to decide moves based on combinations of current and

  8. Canonical variate regression.

    Science.gov (United States)

    Luo, Chongliang; Liu, Jin; Dey, Dipak K; Chen, Kun

    2016-07-01

    In many fields, multi-view datasets, measuring multiple distinct but interrelated sets of characteristics on the same set of subjects, together with data on certain outcomes or phenotypes, are routinely collected. The objective in such a problem is often two-fold: both to explore the association structures of multiple sets of measurements and to develop a parsimonious model for predicting the future outcomes. We study a unified canonical variate regression framework to tackle the two problems simultaneously. The proposed criterion integrates multiple canonical correlation analysis with predictive modeling, balancing between the association strength of the canonical variates and their joint predictive power on the outcomes. Moreover, the proposed criterion seeks multiple sets of canonical variates simultaneously to enable the examination of their joint effects on the outcomes, and is able to handle multivariate and non-Gaussian outcomes. An efficient algorithm based on variable splitting and Lagrangian multipliers is proposed. Simulation studies show the superior performance of the proposed approach. We demonstrate the effectiveness of the proposed approach in an [Formula: see text] intercross mice study and an alcohol dependence study. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  9. Prediction of unwanted pregnancies using logistic regression, probit regression and discriminant analysis.

    Science.gov (United States)

    Ebrahimzadeh, Farzad; Hajizadeh, Ebrahim; Vahabi, Nasim; Almasian, Mohammad; Bakhteyar, Katayoon

    2015-01-01

    Unwanted pregnancy not intended by at least one of the parents has undesirable consequences for the family and the society. In the present study, three classification models were used and compared to predict unwanted pregnancies in an urban population. In this cross-sectional study, 887 pregnant mothers referring to health centers in Khorramabad, Iran, in 2012 were selected by the stratified and cluster sampling; relevant variables were measured and for prediction of unwanted pregnancy, logistic regression, discriminant analysis, and probit regression models and SPSS software version 21 were used. To compare these models, indicators such as sensitivity, specificity, the area under the ROC curve, and the percentage of correct predictions were used. The prevalence of unwanted pregnancies was 25.3%. The logistic and probit regression models indicated that parity and pregnancy spacing, contraceptive methods, household income and number of living male children were related to unwanted pregnancy. The performance of the models based on the area under the ROC curve was 0.735, 0.733, and 0.680 for logistic regression, probit regression, and linear discriminant analysis, respectively. Given the relatively high prevalence of unwanted pregnancies in Khorramabad, it seems necessary to revise family planning programs. Despite the similar accuracy of the models, if the researcher is interested in the interpretability of the results, the use of the logistic regression model is recommended.

  10. Dynamical scene analysis with a moving camera: mobile targets detection system

    International Nuclear Information System (INIS)

    Hennebert, Christine

    1996-01-01

    This thesis work deals with the detection of moving objects in monocular image sequences acquired with a mobile camera. We propose a method able to detect small moving objects in visible or infrared images of real outdoor scenes. In order to detect objects of very low apparent motion, we consider an analysis on a large temporal interval. We have chosen to compensate for the dominant motion due to the camera displacement for several consecutive images in order to form a sub-sequence of images for which the camera seems virtually static. We have also developed a new approach allowing to extract the different layers of a real scene in order to deal with cases where the 2D motion due to the camera displacement cannot be globally compensated for. To this end, we use a hierarchical model with two levels: the local merging step and the global merging one. Then, an appropriate temporal filtering is applied to registered image sub-sequence to enhance signals corresponding to moving objects. The detection issue is stated as a labeling problem within a statistical regularization based on Markov Random Fields. Our method has been validated on numerous real image sequences depicting complex outdoor scenes. Finally, the feasibility of an integrated circuit for mobile object detection has been proved. This circuit could lead to an ASIC creation. (author) [fr

  11. Detection of Cutting Tool Wear using Statistical Analysis and Regression Model

    Science.gov (United States)

    Ghani, Jaharah A.; Rizal, Muhammad; Nuawi, Mohd Zaki; Haron, Che Hassan Che; Ramli, Rizauddin

    2010-10-01

    This study presents a new method for detecting the cutting tool wear based on the measured cutting force signals. A statistical-based method called Integrated Kurtosis-based Algorithm for Z-Filter technique, called I-kaz was used for developing a regression model and 3D graphic presentation of I-kaz 3D coefficient during machining process. The machining tests were carried out using a CNC turning machine Colchester Master Tornado T4 in dry cutting condition. A Kistler 9255B dynamometer was used to measure the cutting force signals, which were transmitted, analyzed, and displayed in the DasyLab software. Various force signals from machining operation were analyzed, and each has its own I-kaz 3D coefficient. This coefficient was examined and its relationship with flank wear lands (VB) was determined. A regression model was developed due to this relationship, and results of the regression model shows that the I-kaz 3D coefficient value decreases as tool wear increases. The result then is used for real time tool wear monitoring.

  12. Taking interim actions: Integrating CERCLA and NEPA to move ahead with site cleanup

    International Nuclear Information System (INIS)

    MacDonell, M.M.; Peterson, J.M.; Valett, G.L.; McCracken, S.H.

    1991-01-01

    The cleanup of contaminated sites can be expedited by using interim response actions in accordance with the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA), as amended, and the National Oil and Hazardous Substances Pollution Contingency Plan (NCP). In fact, a major portion of some Superfund sites can be cleaned up using interim actions. For CERCLA sites being remediated by the US Department of Energy (DOE), such actions must also comply with the National Environmental Policy Act (NEPA) because the DOE has established a policy for integrating CERCLA and NEPA requirements. A strategy for the integrated documentation with implementation of interim actions has been applied successfully at the Weldon Spring site, and major cleanup projects are currently underway. This paper discusses some of the issues associated with integrating CERCLA and NEPA for interim actions and summarizes those actions that have been identified for the Weldon Spring site

  13. Taking interim actions: Integrating CERCLA and NEPA to move ahead with site cleanup

    International Nuclear Information System (INIS)

    MacDonell, M.M.; Peterson, J.M.; Valett, G.L.; McCracken, S.H.

    1991-01-01

    The cleanup of contaminated sites can be expedited by using interim response actions in accordance with the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA), as amended, and the National Oil and Hazardous Substances Pollution Contingency Plan (NCP). In fact, a major portion of some Superfund sites can be cleaned up using interim actions. For CERCLA sites being remediated by the US Department of Energy (DOE), such actions must also comply with the National Environmental Policy Act (NEPA) because the DOE has established a policy for integrating CERCLA and NEPA requirements. A strategy for the integrated documentation and implementation of interim actions has been applied successfully at the Weldon Spring site, and major cleanup projects are currently underway. This paper discusses some of the issues associated with integrating CERCLA and NEPA for interim actions and summarizes those actions that have been identified for the Weldon Spring site

  14. 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.)

  15. Online Sentence Comprehension in PPA: Verb-Based Integration and Prediction

    Directory of Open Access Journals (Sweden)

    Jennifer E Mack

    2015-05-01

    Full Text Available Introduction. Impaired language comprehension is frequently observed in primary progressive aphasia (PPA. Word comprehension deficits are characteristic of the semantic variant (PPA-S whereas sentence comprehension deficits are more prevalent in the agrammatic (PPA-G and logopenic (PPA-L variants (Amici et al., 2007; Gorno-Tempini et al., 2011; Thompson et al., 2013. Word and sentence comprehension deficits have also been shown to have distinct neural substrates in PPA (Mesulam, Thompson, Weintraub, & Rogalski, in press. However, little is known about the relationship between word and sentence comprehension processes in PPA, specifically how words are accessed, combined, and used to predict upcoming elements within a sentence. A previous study demonstrated that listeners with stroke-induced agrammatic aphasia rapidly access verb meanings and use them to semantically integrate verb-arguments; however, they show deficits in using verb meanings predictively (Mack, Ji, & Thompson, 2013. The present study tested whether listeners with PPA are able to access verb meanings and to use this information to integrate and predict verb-arguments. Methods. Fifteen adults with PPA (8 with PPA-G, 3 with PPA-L, and 4 with PPA-S and ten age-matched controls participated in two eyetracking experiments. In both experiments, participants heard sentences with restrictive verbs that were semantically compatible with only one object in a four-picture visual array (e.g., eat when the array included a cake and three non-edible objects and unrestrictive verbs (e.g., move that were compatible with all four objects. The verb-based integration experiment tested access to verb meaning and its effects on integration of the direct object (e.g., Susan will eat/move the cake; the verb-based prediction experiment examined prediction of the direct object (e.g., Susan will eat/move the …. The dependent variable was the rate of fixations on the target picture (e.g., the cake in the

  16. 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…

  17. Sensorimotor integration in dyslexic children under different sensory stimulations.

    Directory of Open Access Journals (Sweden)

    André R Viana

    Full Text Available Dyslexic children, besides difficulties in mastering literacy, also show poor postural control that might be related to how sensory cues coming from different sensory channels are integrated into proper motor activity. Therefore, the aim of this study was to examine the relationship between sensory information and body sway, with visual and somatosensory information manipulated independent and concurrently, in dyslexic children. Thirty dyslexic and 30 non-dyslexic children were asked to stand as still as possible inside of a moving room either with eyes closed or open and either lightly touching a moveable surface or not for 60 seconds under five experimental conditions: (1 no vision and no touch; (2 moving room; (3 moving bar; (4 moving room and stationary touch; and (5 stationary room and moving bar. Body sway magnitude and the relationship between room/bar movement and body sway were examined. Results showed that dyslexic children swayed more than non-dyslexic children in all sensory condition. Moreover, in those trials with conflicting vision and touch manipulation, dyslexic children swayed less coherent with the stimulus manipulation compared to non-dyslexic children. Finally, dyslexic children showed higher body sway variability and applied higher force while touching the bar compared to non-dyslexic children. Based upon these results, we can suggest that dyslexic children are able to use visual and somatosensory information to control their posture and use the same underlying neural control processes as non-dyslexic children. However, dyslexic children show poorer performance and more variability while relating visual and somatosensory information and motor action even during a task that does not require an active cognitive and motor involvement. Further, in sensory conflict conditions, dyslexic children showed less coherent and more variable body sway. These results suggest that dyslexic children have difficulties in multisensory

  18. 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.

  19. Regression and regression analysis time series prediction modeling on climate data of quetta, pakistan

    International Nuclear Information System (INIS)

    Jafri, Y.Z.; Kamal, L.

    2007-01-01

    Various statistical techniques was used on five-year data from 1998-2002 of average humidity, rainfall, maximum and minimum temperatures, respectively. The relationships to regression analysis time series (RATS) were developed for determining the overall trend of these climate parameters on the basis of which forecast models can be corrected and modified. We computed the coefficient of determination as a measure of goodness of fit, to our polynomial regression analysis time series (PRATS). The correlation to multiple linear regression (MLR) and multiple linear regression analysis time series (MLRATS) were also developed for deciphering the interdependence of weather parameters. Spearman's rand correlation and Goldfeld-Quandt test were used to check the uniformity or non-uniformity of variances in our fit to polynomial regression (PR). The Breusch-Pagan test was applied to MLR and MLRATS, respectively which yielded homoscedasticity. We also employed Bartlett's test for homogeneity of variances on a five-year data of rainfall and humidity, respectively which showed that the variances in rainfall data were not homogenous while in case of humidity, were homogenous. Our results on regression and regression analysis time series show the best fit to prediction modeling on climatic data of Quetta, Pakistan. (author)

  20. Linear regression in astronomy. I

    Science.gov (United States)

    Isobe, Takashi; Feigelson, Eric D.; Akritas, Michael G.; Babu, Gutti Jogesh

    1990-01-01

    Five methods for obtaining linear regression fits to bivariate data with unknown or insignificant measurement errors are discussed: ordinary least-squares (OLS) regression of Y on X, OLS regression of X on Y, the bisector of the two OLS lines, orthogonal regression, and 'reduced major-axis' regression. These methods have been used by various researchers in observational astronomy, most importantly in cosmic distance scale applications. Formulas for calculating the slope and intercept coefficients and their uncertainties are given for all the methods, including a new general form of the OLS variance estimates. The accuracy of the formulas was confirmed using numerical simulations. The applicability of the procedures is discussed with respect to their mathematical properties, the nature of the astronomical data under consideration, and the scientific purpose of the regression. It is found that, for problems needing symmetrical treatment of the variables, the OLS bisector performs significantly better than orthogonal or reduced major-axis regression.

  1. Logic regression and its extensions.

    Science.gov (United States)

    Schwender, Holger; Ruczinski, Ingo

    2010-01-01

    Logic regression is an adaptive classification and regression procedure, initially developed to reveal interacting single nucleotide polymorphisms (SNPs) in genetic association studies. In general, this approach can be used in any setting with binary predictors, when the interaction of these covariates is of primary interest. Logic regression searches for Boolean (logic) combinations of binary variables that best explain the variability in the outcome variable, and thus, reveals variables and interactions that are associated with the response and/or have predictive capabilities. The logic expressions are embedded in a generalized linear regression framework, and thus, logic regression can handle a variety of outcome types, such as binary responses in case-control studies, numeric responses, and time-to-event data. In this chapter, we provide an introduction to the logic regression methodology, list some applications in public health and medicine, and summarize some of the direct extensions and modifications of logic regression that have been proposed in the literature. Copyright © 2010 Elsevier Inc. All rights reserved.

  2. Tumor regression patterns in retinoblastoma

    International Nuclear Information System (INIS)

    Zafar, S.N.; Siddique, S.N.; Zaheer, N.

    2016-01-01

    To observe the types of tumor regression after treatment, and identify the common pattern of regression in our patients. Study Design: Descriptive study. Place and Duration of Study: Department of Pediatric Ophthalmology and Strabismus, Al-Shifa Trust Eye Hospital, Rawalpindi, Pakistan, from October 2011 to October 2014. Methodology: Children with unilateral and bilateral retinoblastoma were included in the study. Patients were referred to Pakistan Institute of Medical Sciences, Islamabad, for chemotherapy. After every cycle of chemotherapy, dilated funds examination under anesthesia was performed to record response of the treatment. Regression patterns were recorded on RetCam II. Results: Seventy-four tumors were included in the study. Out of 74 tumors, 3 were ICRB group A tumors, 43 were ICRB group B tumors, 14 tumors belonged to ICRB group C, and remaining 14 were ICRB group D tumors. Type IV regression was seen in 39.1% (n=29) tumors, type II in 29.7% (n=22), type III in 25.6% (n=19), and type I in 5.4% (n=4). All group A tumors (100%) showed type IV regression. Seventeen (39.5%) group B tumors showed type IV regression. In group C, 5 tumors (35.7%) showed type II regression and 5 tumors (35.7%) showed type IV regression. In group D, 6 tumors (42.9%) regressed to type II non-calcified remnants. Conclusion: The response and success of the focal and systemic treatment, as judged by the appearance of different patterns of tumor regression, varies with the ICRB grouping of the tumor. (author)

  3. Is Pan-Asian Economic Integration Moving Forward?: Evidence from Pan-Asian Trade Statistics

    OpenAIRE

    Sapkota, Jeet Bahadur; Shuto, Motoko

    2016-01-01

    Asia is growing economically faster than any other region in the world; this led to the shift of the center of gravity of the global economy from the West to the East. However, it is not clear whether the Asian economy is integrating regionally or globally. In the context of the growing efforts of regional or sub-regional pan-Asian integration, it is worthwhile to explore the pan-Asian trade flows regionally as well as globally. Thus, this paper examines the trend and determinants of economic...

  4. 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...

  5. Combining Alphas via Bounded Regression

    Directory of Open Access Journals (Sweden)

    Zura Kakushadze

    2015-11-01

    Full Text Available We give an explicit algorithm and source code for combining alpha streams via bounded regression. In practical applications, typically, there is insufficient history to compute a sample covariance matrix (SCM for a large number of alphas. To compute alpha allocation weights, one then resorts to (weighted regression over SCM principal components. Regression often produces alpha weights with insufficient diversification and/or skewed distribution against, e.g., turnover. This can be rectified by imposing bounds on alpha weights within the regression procedure. Bounded regression can also be applied to stock and other asset portfolio construction. We discuss illustrative examples.

  6. 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...

  7. 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)

  8. 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)

  9. The use of outcome and process indicators to incentivize integrated care for frail older people: a case study of primary care services in Sweden

    Directory of Open Access Journals (Sweden)

    Anders Lars Anell

    2014-12-01

    Full Text Available Background: A number of reforms have been implemented in Swedish health care to support integrated care for frail older people and to reduce utilization of hospital care by this group. Outcomes and process indicators have been used in pay-for-performance (P4P schemes by both national and local governments to support developments.Objective: To analyse limitations in the use of outcome and process indicators to incentivize integrated care for elderly patients with significant health care needs in the context of primary care.Method: Data were collected from the Region Skåne county council. Eight primary care providers and associated community services were compared in a ranking exercise based on information from interviews and registered data. Registered data from 150 primary care providers were analysed in regression models.Results and conclusion: Both the ranking exercise and regression models revealed important problems related to risk-adjustment, attribution, randomness and measurement fixation when using indicators in P4P schemes and for external accountability purposes. Instead of using indicators in incentive schemes targeting individual providers, indicators may be used for diagnostic purposes and to support development of new knowledge, targeting local systems that move beyond organizational boundaries.

  10. riskRegression

    DEFF Research Database (Denmark)

    Ozenne, Brice; Sørensen, Anne Lyngholm; Scheike, Thomas

    2017-01-01

    In the presence of competing risks a prediction of the time-dynamic absolute risk of an event can be based on cause-specific Cox regression models for the event and the competing risks (Benichou and Gail, 1990). We present computationally fast and memory optimized C++ functions with an R interface...... for predicting the covariate specific absolute risks, their confidence intervals, and their confidence bands based on right censored time to event data. We provide explicit formulas for our implementation of the estimator of the (stratified) baseline hazard function in the presence of tied event times. As a by...... functionals. The software presented here is implemented in the riskRegression package....

  11. 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.

  12. Electricity consumption forecasting in Italy using linear regression models

    Energy Technology Data Exchange (ETDEWEB)

    Bianco, Vincenzo; Manca, Oronzio; Nardini, Sergio [DIAM, Seconda Universita degli Studi di Napoli, Via Roma 29, 81031 Aversa (CE) (Italy)

    2009-09-15

    The influence of economic and demographic variables on the annual electricity consumption in Italy has been investigated with the intention to develop a long-term consumption forecasting model. The time period considered for the historical data is from 1970 to 2007. Different regression models were developed, using historical electricity consumption, gross domestic product (GDP), gross domestic product per capita (GDP per capita) and population. A first part of the paper considers the estimation of GDP, price and GDP per capita elasticities of domestic and non-domestic electricity consumption. The domestic and non-domestic short run price elasticities are found to be both approximately equal to -0.06, while long run elasticities are equal to -0.24 and -0.09, respectively. On the contrary, the elasticities of GDP and GDP per capita present higher values. In the second part of the paper, different regression models, based on co-integrated or stationary data, are presented. Different statistical tests are employed to check the validity of the proposed models. A comparison with national forecasts, based on complex econometric models, such as Markal-Time, was performed, showing that the developed regressions are congruent with the official projections, with deviations of {+-}1% for the best case and {+-}11% for the worst. These deviations are to be considered acceptable in relation to the time span taken into account. (author)

  13. Electricity consumption forecasting in Italy using linear regression models

    International Nuclear Information System (INIS)

    Bianco, Vincenzo; Manca, Oronzio; Nardini, Sergio

    2009-01-01

    The influence of economic and demographic variables on the annual electricity consumption in Italy has been investigated with the intention to develop a long-term consumption forecasting model. The time period considered for the historical data is from 1970 to 2007. Different regression models were developed, using historical electricity consumption, gross domestic product (GDP), gross domestic product per capita (GDP per capita) and population. A first part of the paper considers the estimation of GDP, price and GDP per capita elasticities of domestic and non-domestic electricity consumption. The domestic and non-domestic short run price elasticities are found to be both approximately equal to -0.06, while long run elasticities are equal to -0.24 and -0.09, respectively. On the contrary, the elasticities of GDP and GDP per capita present higher values. In the second part of the paper, different regression models, based on co-integrated or stationary data, are presented. Different statistical tests are employed to check the validity of the proposed models. A comparison with national forecasts, based on complex econometric models, such as Markal-Time, was performed, showing that the developed regressions are congruent with the official projections, with deviations of ±1% for the best case and ±11% for the worst. These deviations are to be considered acceptable in relation to the time span taken into account. (author)

  14. 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...

  15. Environment, safety, and health information technology systems integration.

    Energy Technology Data Exchange (ETDEWEB)

    Hendrickson, David A.; Bayer, Gregory W.

    2006-02-01

    The ES&H Information Systems department, motivated by the numerous isolated information technology systems under its control, undertook a significant integration effort. This effort was planned and executed over the course of several years and parts of it still continue today. The effect was to help move the ES&H Information Systems department toward integration with the corporate Information Solutions and Services center.

  16. Regression in autistic spectrum disorders.

    Science.gov (United States)

    Stefanatos, Gerry A

    2008-12-01

    A significant proportion of children diagnosed with Autistic Spectrum Disorder experience a developmental regression characterized by a loss of previously-acquired skills. This may involve a loss of speech or social responsitivity, but often entails both. This paper critically reviews the phenomena of regression in autistic spectrum disorders, highlighting the characteristics of regression, age of onset, temporal course, and long-term outcome. Important considerations for diagnosis are discussed and multiple etiological factors currently hypothesized to underlie the phenomenon are reviewed. It is argued that regressive autistic spectrum disorders can be conceptualized on a spectrum with other regressive disorders that may share common pathophysiological features. The implications of this viewpoint are discussed.

  17. Designing Integrated Product- Service System Solutions in Manufacturing Industries

    DEFF Research Database (Denmark)

    Costa, Nina; Patrício, Lia; Morelli, Nicola

    2015-01-01

    Manufacturing firms are increasingly evolving towards the design of integrated product-service solutions but servitization literature does not provide specific guidance on how to design these integrated solutions. Building upon ProductService System (PSS) and Service Design (SD) approaches...... how it brings new insights to manufacturing companies moving to a service, value cocreation perspective....

  18. Understanding logistic regression analysis

    OpenAIRE

    Sperandei, Sandro

    2014-01-01

    Logistic regression is used to obtain odds ratio in the presence of more than one explanatory variable. The procedure is quite similar to multiple linear regression, with the exception that the response variable is binomial. The result is the impact of each variable on the odds ratio of the observed event of interest. The main advantage is to avoid confounding effects by analyzing the association of all variables together. In this article, we explain the logistic regression procedure using ex...

  19. Pentaho data integration cookbook

    CERN Document Server

    Meadows, Alex

    2013-01-01

    Pentaho Data Integration Cookbook Second Edition is written in a cookbook format, presenting examples in the style of recipes.This allows you to go directly to your topic of interest, or follow topics throughout a chapter to gain a thorough in-depth knowledge.Pentaho Data Integration Cookbook Second Edition is designed for developers who are familiar with the basics of Kettle but who wish to move up to the next level.It is also aimed at advanced users that want to learn how to use the new features of PDI as well as and best practices for working with Kettle.

  20. Strategies to Move From Conceptual Models to Quantifying Resilience in FEW Systems

    Science.gov (United States)

    Padowski, J.; Adam, J. C.; Boll, J.; Barber, M. E.; Cosens, B.; Goldsby, M.; Fortenbery, R.; Fowler, A.; Givens, J.; Guzman, C. D.; Hampton, S. E.; Harrison, J.; Huang, M.; Katz, S. L.; Kraucunas, I.; Kruger, C. E.; Liu, M.; Luri, M.; Malek, K.; Mills, A.; McLarty, D.; Pickering, N. B.; Rajagopalan, K.; Stockle, C.; Richey, A.; Voisin, N.; Witinok-Huber, B.; Yoder, J.; Yorgey, G.; Zhao, M.

    2017-12-01

    Understanding interdependencies within Food-Energy-Water (FEW) systems is critical to maintain FEW security. This project examines how coordinated management of physical (e.g., reservoirs, aquifers, and batteries) and non-physical (e.g., water markets, social capital, and insurance markets) storage systems across the three sectors promotes resilience. Coordination increases effective storage within the overall system and enhances buffering against shocks at multiple scales. System-wide resilience can be increased with innovations in technology (e.g., smart systems and energy storage) and institutions (e.g., economic systems and water law). Using the Columbia River Basin as our geographical study region, we use an integrated approach that includes a continuum of science disciplines, moving from theory to practice. In order to understand FEW linkages, we started with detailed, connected conceptual models of the food, energy, water, and social systems to identify where key interdependencies (i.e., overlaps, stocks, and flows) exist within and between systems. These are used to identify stress and opportunity points, develop innovation solutions across FEW sectors, remove barriers to the adoption of solutions, and quantify increases in system-wide resilience to regional and global change. The conceptual models act as a foundation from which we can identify key drivers, parameters, time steps, and variables of importance to build and improve existing systems dynamic and biophysical models. Our process of developing conceptual models and moving to integrated modeling is critical and serves as a foundation for coupling quantitative components with economic and social domain components and analyses of how these interact through time and space. This poster provides a description of this process that pulls together conceptual maps and integrated modeling output to quantify resilience across all three of the FEW sectors (a.k.a. "The Resilience Calculator"). Companion posters

  1. Developing and testing a global-scale regression model to quantify mean annual streamflow

    Science.gov (United States)

    Barbarossa, Valerio; Huijbregts, Mark A. J.; Hendriks, A. Jan; Beusen, Arthur H. W.; Clavreul, Julie; King, Henry; Schipper, Aafke M.

    2017-01-01

    Quantifying mean annual flow of rivers (MAF) at ungauged sites is essential for assessments of global water supply, ecosystem integrity and water footprints. MAF can be quantified with spatially explicit process-based models, which might be overly time-consuming and data-intensive for this purpose, or with empirical regression models that predict MAF based on climate and catchment characteristics. Yet, regression models have mostly been developed at a regional scale and the extent to which they can be extrapolated to other regions is not known. In this study, we developed a global-scale regression model for MAF based on a dataset unprecedented in size, using observations of discharge and catchment characteristics from 1885 catchments worldwide, measuring between 2 and 106 km2. In addition, we compared the performance of the regression model with the predictive ability of the spatially explicit global hydrological model PCR-GLOBWB by comparing results from both models to independent measurements. We obtained a regression model explaining 89% of the variance in MAF based on catchment area and catchment averaged mean annual precipitation and air temperature, slope and elevation. The regression model performed better than PCR-GLOBWB for the prediction of MAF, as root-mean-square error (RMSE) values were lower (0.29-0.38 compared to 0.49-0.57) and the modified index of agreement (d) was higher (0.80-0.83 compared to 0.72-0.75). Our regression model can be applied globally to estimate MAF at any point of the river network, thus providing a feasible alternative to spatially explicit process-based global hydrological models.

  2. Linear regression in astronomy. II

    Science.gov (United States)

    Feigelson, Eric D.; Babu, Gutti J.

    1992-01-01

    A wide variety of least-squares linear regression procedures used in observational astronomy, particularly investigations of the cosmic distance scale, are presented and discussed. The classes of linear models considered are (1) unweighted regression lines, with bootstrap and jackknife resampling; (2) regression solutions when measurement error, in one or both variables, dominates the scatter; (3) methods to apply a calibration line to new data; (4) truncated regression models, which apply to flux-limited data sets; and (5) censored regression models, which apply when nondetections are present. For the calibration problem we develop two new procedures: a formula for the intercept offset between two parallel data sets, which propagates slope errors from one regression to the other; and a generalization of the Working-Hotelling confidence bands to nonstandard least-squares lines. They can provide improved error analysis for Faber-Jackson, Tully-Fisher, and similar cosmic distance scale relations.

  3. A Matlab program for stepwise regression

    Directory of Open Access Journals (Sweden)

    Yanhong Qi

    2016-03-01

    Full Text Available The stepwise linear regression is a multi-variable regression for identifying statistically significant variables in the linear regression equation. In present study, we presented the Matlab program of stepwise regression.

  4. Helicopter Control Energy Reduction Using Moving Horizontal Tail

    Science.gov (United States)

    Oktay, Tugrul; Sal, Firat

    2015-01-01

    Helicopter moving horizontal tail (i.e., MHT) strategy is applied in order to save helicopter flight control system (i.e., FCS) energy. For this intention complex, physics-based, control-oriented nonlinear helicopter models are used. Equations of MHT are integrated into these models and they are together linearized around straight level flight condition. A specific variance constrained control strategy, namely, output variance constrained Control (i.e., OVC) is utilized for helicopter FCS. Control energy savings due to this MHT idea with respect to a conventional helicopter are calculated. Parameters of helicopter FCS and dimensions of MHT are simultaneously optimized using a stochastic optimization method, namely, simultaneous perturbation stochastic approximation (i.e., SPSA). In order to observe improvement in behaviors of classical controls closed loop analyses are done. PMID:26180841

  5. Helicopter Control Energy Reduction Using Moving Horizontal Tail

    Directory of Open Access Journals (Sweden)

    Tugrul Oktay

    2015-01-01

    Full Text Available Helicopter moving horizontal tail (i.e., MHT strategy is applied in order to save helicopter flight control system (i.e., FCS energy. For this intention complex, physics-based, control-oriented nonlinear helicopter models are used. Equations of MHT are integrated into these models and they are together linearized around straight level flight condition. A specific variance constrained control strategy, namely, output variance constrained Control (i.e., OVC is utilized for helicopter FCS. Control energy savings due to this MHT idea with respect to a conventional helicopter are calculated. Parameters of helicopter FCS and dimensions of MHT are simultaneously optimized using a stochastic optimization method, namely, simultaneous perturbation stochastic approximation (i.e., SPSA. In order to observe improvement in behaviors of classical controls closed loop analyses are done.

  6. Integrated Personal Health Records: Transformative Tools for Consumer-Centric Care

    Directory of Open Access Journals (Sweden)

    Raymond Brian

    2008-10-01

    Full Text Available Abstract Background Integrated personal health records (PHRs offer significant potential to stimulate transformational changes in health care delivery and self-care by patients. In 2006, an invitational roundtable sponsored by Kaiser Permanente Institute, the American Medical Informatics Association, and the Agency for Healthcare Research and Quality was held to identify the transformative potential of PHRs, as well as barriers to realizing this potential and a framework for action to move them closer to the health care mainstream. This paper highlights and builds on the insights shared during the roundtable. Discussion While there is a spectrum of dominant PHR models, (standalone, tethered, integrated, the authors state that only the integrated model has true transformative potential to strengthen consumers' ability to manage their own health care. Integrated PHRs improve the quality, completeness, depth, and accessibility of health information provided by patients; enable facile communication between patients and providers; provide access to health knowledge for patients; ensure portability of medical records and other personal health information; and incorporate auto-population of content. Numerous factors impede widespread adoption of integrated PHRs: obstacles in the health care system/culture; issues of consumer confidence and trust; lack of technical standards for interoperability; lack of HIT infrastructure; the digital divide; uncertain value realization/ROI; and uncertain market demand. Recent efforts have led to progress on standards for integrated PHRs, and government agencies and private companies are offering different models to consumers, but substantial obstacles remain to be addressed. Immediate steps to advance integrated PHRs should include sharing existing knowledge and expanding knowledge about them, building on existing efforts, and continuing dialogue among public and private sector stakeholders. Summary Integrated PHRs

  7. 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

  8. Building interpretable predictive models for pediatric hospital readmission using Tree-Lasso logistic regression.

    Science.gov (United States)

    Jovanovic, Milos; Radovanovic, Sandro; Vukicevic, Milan; Van Poucke, Sven; Delibasic, Boris

    2016-09-01

    Quantification and early identification of unplanned readmission risk have the potential to improve the quality of care during hospitalization and after discharge. However, high dimensionality, sparsity, and class imbalance of electronic health data and the complexity of risk quantification, challenge the development of accurate predictive models. Predictive models require a certain level of interpretability in order to be applicable in real settings and create actionable insights. This paper aims to develop accurate and interpretable predictive models for readmission in a general pediatric patient population, by integrating a data-driven model (sparse logistic regression) and domain knowledge based on the international classification of diseases 9th-revision clinical modification (ICD-9-CM) hierarchy of diseases. Additionally, we propose a way to quantify the interpretability of a model and inspect the stability of alternative solutions. The analysis was conducted on >66,000 pediatric hospital discharge records from California, State Inpatient Databases, Healthcare Cost and Utilization Project between 2009 and 2011. We incorporated domain knowledge based on the ICD-9-CM hierarchy in a data driven, Tree-Lasso regularized logistic regression model, providing the framework for model interpretation. This approach was compared with traditional Lasso logistic regression resulting in models that are easier to interpret by fewer high-level diagnoses, with comparable prediction accuracy. The results revealed that the use of a Tree-Lasso model was as competitive in terms of accuracy (measured by area under the receiver operating characteristic curve-AUC) as the traditional Lasso logistic regression, but integration with the ICD-9-CM hierarchy of diseases provided more interpretable models in terms of high-level diagnoses. Additionally, interpretations of models are in accordance with existing medical understanding of pediatric readmission. Best performing models have

  9. Tracking 3D Moving Objects Based on GPS/IMU Navigation Solution, Laser Scanner Point Cloud and GIS Data

    Directory of Open Access Journals (Sweden)

    Siavash Hosseinyalamdary

    2015-07-01

    Full Text Available Monitoring vehicular road traffic is a key component of any autonomous driving platform. Detecting moving objects, and tracking them, is crucial to navigating around objects and predicting their locations and trajectories. Laser sensors provide an excellent observation of the area around vehicles, but the point cloud of objects may be noisy, occluded, and prone to different errors. Consequently, object tracking is an open problem, especially for low-quality point clouds. This paper describes a pipeline to integrate various sensor data and prior information, such as a Geospatial Information System (GIS map, to segment and track moving objects in a scene. We show that even a low-quality GIS map, such as OpenStreetMap (OSM, can improve the tracking accuracy, as well as decrease processing time. A bank of Kalman filters is used to track moving objects in a scene. In addition, we apply non-holonomic constraint to provide a better orientation estimation of moving objects. The results show that moving objects can be correctly detected, and accurately tracked, over time, based on modest quality Light Detection And Ranging (LiDAR data, a coarse GIS map, and a fairly accurate Global Positioning System (GPS and Inertial Measurement Unit (IMU navigation solution.

  10. 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.

  11. Quantile regression theory and applications

    CERN Document Server

    Davino, Cristina; Vistocco, Domenico

    2013-01-01

    A guide to the implementation and interpretation of Quantile Regression models This book explores the theory and numerous applications of quantile regression, offering empirical data analysis as well as the software tools to implement the methods. The main focus of this book is to provide the reader with a comprehensivedescription of the main issues concerning quantile regression; these include basic modeling, geometrical interpretation, estimation and inference for quantile regression, as well as issues on validity of the model, diagnostic tools. Each methodological aspect is explored and

  12. Fungible weights in logistic regression.

    Science.gov (United States)

    Jones, Jeff A; Waller, Niels G

    2016-06-01

    In this article we develop methods for assessing parameter sensitivity in logistic regression models. To set the stage for this work, we first review Waller's (2008) equations for computing fungible weights in linear regression. Next, we describe 2 methods for computing fungible weights in logistic regression. To demonstrate the utility of these methods, we compute fungible logistic regression weights using data from the Centers for Disease Control and Prevention's (2010) Youth Risk Behavior Surveillance Survey, and we illustrate how these alternate weights can be used to evaluate parameter sensitivity. To make our work accessible to the research community, we provide R code (R Core Team, 2015) that will generate both kinds of fungible logistic regression weights. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  13. The Boundary Element Method Applied to the Two Dimensional Stefan Moving Boundary Problem

    Science.gov (United States)

    1991-03-15

    Unc), - ( UGt )t - (UG,,),,] - (UG), If we integrate this equation with respect to r from 0 to t - c and with respect to and ij on the region 11(r...and others. "Moving Boundary Problems in Phase Change Mod- els," SIGNUM Newsletter, 20: 8-12 (1985). 21. Stefan, J. "Ober einige Probleme der Theorie ...ier Wirmelcitung," S.-B. \\Vein. Akad. Mat. Natur., 98: 173-484 (1889). 22.-. "flber (lie Theorie der Eisbildung insbesondere fiber die lisbildung im

  14. A new moving boundary model for transient simulation of dry-expansion evaporators

    DEFF Research Database (Denmark)

    Jensen, Jakob Munch; Knudsen, Hans-Jørgen Høgaard

    2002-01-01

    A new moving boundary model is presented for describing the dynamics of dry-expansin evaporators. The model is derived from conservation equations for mass and energy integrated over the two-phase and the superheated region. The new model is numerical fast compared to discretized models and very...... robust to sudden changes in the system. The model is well suited for open loop simulation for system design and model based contol strategies as e.g. optimal LQG (linear quadratic gausian) control. Simulation results for a refrigeration system are shown for different changes in evaporator fan speed...

  15. 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...

  16. AIM: An Integrated Approach to Organizational Improvement

    Directory of Open Access Journals (Sweden)

    Ronald A. Styron, Jr.

    2016-02-01

    Full Text Available This concept paper is based on the new problem-solving model of Blended Leadership called Alloy Improvement Model (AIM. This model consists of an integration of change theory, leadership theory, and democratic principles and practices to form a comprehensive problem-solving strategy for organizational leaders. The utilization of AIM will assist leaders in moving from problems to solutions while engaging stakeholders in a comprehensive, efficient, inclusive, informative, integrated and transparent process.

  17. Application of Hybrid Quantum Tabu Search with Support Vector Regression (SVR for Load Forecasting

    Directory of Open Access Journals (Sweden)

    Cheng-Wen Lee

    2016-10-01

    Full Text Available Hybridizing chaotic evolutionary algorithms with support vector regression (SVR to improve forecasting accuracy is a hot topic in electricity load forecasting. Trapping at local optima and premature convergence are critical shortcomings of the tabu search (TS algorithm. This paper investigates potential improvements of the TS algorithm by applying quantum computing mechanics to enhance the search information sharing mechanism (tabu memory to improve the forecasting accuracy. This article presents an SVR-based load forecasting model that integrates quantum behaviors and the TS algorithm with the support vector regression model (namely SVRQTS to obtain a more satisfactory forecasting accuracy. Numerical examples demonstrate that the proposed model outperforms the alternatives.

  18. Bayesian Travel Time Inversion adopting Gaussian Process Regression

    Science.gov (United States)

    Mauerberger, S.; Holschneider, M.

    2017-12-01

    A major application in seismology is the determination of seismic velocity models. Travel time measurements are putting an integral constraint on the velocity between source and receiver. We provide insight into travel time inversion from a correlation-based Bayesian point of view. Therefore, the concept of Gaussian process regression is adopted to estimate a velocity model. The non-linear travel time integral is approximated by a 1st order Taylor expansion. A heuristic covariance describes correlations amongst observations and a priori model. That approach enables us to assess a proxy of the Bayesian posterior distribution at ordinary computational costs. No multi dimensional numeric integration nor excessive sampling is necessary. Instead of stacking the data, we suggest to progressively build the posterior distribution. Incorporating only a single evidence at a time accounts for the deficit of linearization. As a result, the most probable model is given by the posterior mean whereas uncertainties are described by the posterior covariance.As a proof of concept, a synthetic purely 1d model is addressed. Therefore a single source accompanied by multiple receivers is considered on top of a model comprising a discontinuity. We consider travel times of both phases - direct and reflected wave - corrupted by noise. Left and right of the interface are assumed independent where the squared exponential kernel serves as covariance.

  19. Crisis and Regional Integration

    DEFF Research Database (Denmark)

    Dosenrode, Søren

    , Tunisia, Egypt …. ), where the crisis referred to could be humanitarian, environmental, economic, political … Europe, too, has also according to mass media, been a victim of a crisis, the financial one. Could ‘crisis’ be a beginning of enhanced regional integration? This paper will try to look...... at the processes of regional integration in relation to ‘crisis’ in Africa and Europe. First, this paper will look at the concept of ‘crisis’, before it moves on to discuss ‘regional integration’ and the correlation between the two, emphasizing the approaches of neo-functionalism and federal theory....... This is the basis for two short case studies of African and European regional integration. The paper tentative answers to the question: will the crisis in Africa and Europe respectively further or block regional integration? With a ‘that depends’. But the use of Federalism theory and neo-functionalism is seen...

  20. Exploration of Team Integration in Spanish Multifamily Residential Building Construction

    OpenAIRE

    Pellicer, Eugenio; Sanz Benlloch, María Amalia; Esmaeili, B.; MOLENAAR, KEITH ROBERT

    2016-01-01

    Project delivery team integration generally involves early involvement of general contractors and key specialty contractors in the design process. Team integration has been found to improve an owner’s probability of success. However, during difficult economic times, owners can forego early team involvement and move toward low bid procurement to take advantage of competitive markets. This study explores the performance of integrated teams in the Spanish multifamily building constructi...

  1. Principal component regression analysis with SPSS.

    Science.gov (United States)

    Liu, R X; Kuang, J; Gong, Q; Hou, X L

    2003-06-01

    The paper introduces all indices of multicollinearity diagnoses, the basic principle of principal component regression and determination of 'best' equation method. The paper uses an example to describe how to do principal component regression analysis with SPSS 10.0: including all calculating processes of the principal component regression and all operations of linear regression, factor analysis, descriptives, compute variable and bivariate correlations procedures in SPSS 10.0. The principal component regression analysis can be used to overcome disturbance of the multicollinearity. The simplified, speeded up and accurate statistical effect is reached through the principal component regression analysis with SPSS.

  2. 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

  3. Regression Analysis of Combined Gene Expression Regulation in Acute Myeloid Leukemia

    Science.gov (United States)

    Li, Yue; Liang, Minggao; Zhang, Zhaolei

    2014-01-01

    Gene expression is a combinatorial function of genetic/epigenetic factors such as copy number variation (CNV), DNA methylation (DM), transcription factors (TF) occupancy, and microRNA (miRNA) post-transcriptional regulation. At the maturity of microarray/sequencing technologies, large amounts of data measuring the genome-wide signals of those factors became available from Encyclopedia of DNA Elements (ENCODE) and The Cancer Genome Atlas (TCGA). However, there is a lack of an integrative model to take full advantage of these rich yet heterogeneous data. To this end, we developed RACER (Regression Analysis of Combined Expression Regulation), which fits the mRNA expression as response using as explanatory variables, the TF data from ENCODE, and CNV, DM, miRNA expression signals from TCGA. Briefly, RACER first infers the sample-specific regulatory activities by TFs and miRNAs, which are then used as inputs to infer specific TF/miRNA-gene interactions. Such a two-stage regression framework circumvents a common difficulty in integrating ENCODE data measured in generic cell-line with the sample-specific TCGA measurements. As a case study, we integrated Acute Myeloid Leukemia (AML) data from TCGA and the related TF binding data measured in K562 from ENCODE. As a proof-of-concept, we first verified our model formalism by 10-fold cross-validation on predicting gene expression. We next evaluated RACER on recovering known regulatory interactions, and demonstrated its superior statistical power over existing methods in detecting known miRNA/TF targets. Additionally, we developed a feature selection procedure, which identified 18 regulators, whose activities clustered consistently with cytogenetic risk groups. One of the selected regulators is miR-548p, whose inferred targets were significantly enriched for leukemia-related pathway, implicating its novel role in AML pathogenesis. Moreover, survival analysis using the inferred activities identified C-Fos as a potential AML

  4. Dynamic temperature field in the ferromagnetic plate induced by moving high frequency inductor

    Directory of Open Access Journals (Sweden)

    Milošević-Mitić Vesna

    2014-01-01

    Full Text Available The subject of the paper is the temperature distribution in the thin metallic ferromagnetic plate influenced by moving linear high frequency induction heater. As a result of high frequency electromagnetic field, conducting currents appear in the part of the plate. Distribution of the eddy-current power across the plate thickness is obtained by use of complex analysis. The influences of the heater frequency, magnetic field intensity and plate thickness on the heat power density were discussed. By treating this power as a moving heat source, differential equations governing distribution of the temperature field are formulated. Temperature across the plate thickness is assumed to be in linear form. Differential equations are analytically solved by using integral-transform technique, Fourier finite-sine and finite-cosine transform and Laplace transform. The influence of the heater velocity to the plate temperature is presented on numerical examples based on theoretically obtained results. [Projekat Ministarstva nauke Republike Srbije, br. TR 35040 i br. TR 35011

  5. Self-similarity of higher-order moving averages

    Science.gov (United States)

    Arianos, Sergio; Carbone, Anna; Türk, Christian

    2011-10-01

    In this work, higher-order moving average polynomials are defined by straightforward generalization of the standard moving average. The self-similarity of the polynomials is analyzed for fractional Brownian series and quantified in terms of the Hurst exponent H by using the detrending moving average method. We prove that the exponent H of the fractional Brownian series and of the detrending moving average variance asymptotically agree for the first-order polynomial. Such asymptotic values are compared with the results obtained by the simulations. The higher-order polynomials correspond to trend estimates at shorter time scales as the degree of the polynomial increases. Importantly, the increase of polynomial degree does not require to change the moving average window. Thus trends at different time scales can be obtained on data sets with the same size. These polynomials could be interesting for those applications relying on trend estimates over different time horizons (financial markets) or on filtering at different frequencies (image analysis).

  6. Logistic regression models

    CERN Document Server

    Hilbe, Joseph M

    2009-01-01

    This book really does cover everything you ever wanted to know about logistic regression … with updates available on the author's website. Hilbe, a former national athletics champion, philosopher, and expert in astronomy, is a master at explaining statistical concepts and methods. Readers familiar with his other expository work will know what to expect-great clarity.The book provides considerable detail about all facets of logistic regression. No step of an argument is omitted so that the book will meet the needs of the reader who likes to see everything spelt out, while a person familiar with some of the topics has the option to skip "obvious" sections. The material has been thoroughly road-tested through classroom and web-based teaching. … The focus is on helping the reader to learn and understand logistic regression. The audience is not just students meeting the topic for the first time, but also experienced users. I believe the book really does meet the author's goal … .-Annette J. Dobson, Biometric...

  7. Logistic regression applied to natural hazards: rare event logistic regression with replications

    Science.gov (United States)

    Guns, M.; Vanacker, V.

    2012-06-01

    Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead to a robust detection of controlling factors, as the results can be strongly sample-dependent. In this paper, we introduce some concepts of Monte Carlo simulations in rare event logistic regression. This technique, so-called rare event logistic regression with replications, combines the strength of probabilistic and statistical methods, and allows overcoming some of the limitations of previous developments through robust variable selection. This technique was here developed for the analyses of landslide controlling factors, but the concept is widely applicable for statistical analyses of natural hazards.

  8. 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.

  9. 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.

  10. Understanding logistic regression analysis.

    Science.gov (United States)

    Sperandei, Sandro

    2014-01-01

    Logistic regression is used to obtain odds ratio in the presence of more than one explanatory variable. The procedure is quite similar to multiple linear regression, with the exception that the response variable is binomial. The result is the impact of each variable on the odds ratio of the observed event of interest. The main advantage is to avoid confounding effects by analyzing the association of all variables together. In this article, we explain the logistic regression procedure using examples to make it as simple as possible. After definition of the technique, the basic interpretation of the results is highlighted and then some special issues are discussed.

  11. Watershed regressions for pesticides (WARP) for predicting atrazine concentration in Corn Belt streams

    Science.gov (United States)

    Stone, Wesley W.; Gilliom, Robert J.

    2011-01-01

    Watershed Regressions for Pesticides (WARP) models, previously developed for atrazine at the national scale, can be improved for application to the U.S. Corn Belt region by developing region-specific models that include important watershed characteristics that are influential in predicting atrazine concentration statistics within the Corn Belt. WARP models for the Corn Belt (WARP-CB) were developed for predicting annual maximum moving-average (14-, 21-, 30-, 60-, and 90-day durations) and annual 95th-percentile atrazine concentrations in streams of the Corn Belt region. All streams used in development of WARP-CB models drain watersheds with atrazine use intensity greater than 17 kilograms per square kilometer (kg/km2). The WARP-CB models accounted for 53 to 62 percent of the variability in the various concentration statistics among the model-development sites.

  12. Controlled Wake of a Moving Axisymmetric Bluff Body

    Science.gov (United States)

    Lee, E.; Vukasinovic, B.; Glezer, A.

    2017-11-01

    The aerodynamic loads exerted on a wire-mounted axisymmetric bluff body in prescribed rigid motion are controlled by fluidic manipulation of its near wake. The body is supported by a six-degree of freedom eight-wire traverse and its motion is controlled using a dedicated servo actuator and inline load cell for each wire. The instantaneous aerodynamic forces and moments on the moving body are manipulated by controlled interactions of an azimuthal array of integrated synthetic jet actuators with the cross flow to induce localized flow attachment over the body's aft end and thereby alter the symmetry of the wake. The coupled interactions between the wake structure and the effected aerodynamic loads during prescribed time-periodic and transitory (gust like) motions are investigated with emphasis on enhancing or diminishing the loads for maneuver control, and decoupling the body's motion from its far wake.

  13. Heterogeneous CPU-GPU moving targets detection for UAV video

    Science.gov (United States)

    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.

  14. Generic global regression models for growth prediction of Salmonella in ground pork and pork cuts

    DEFF Research Database (Denmark)

    Buschhardt, Tasja; Hansen, Tina Beck; Bahl, Martin Iain

    2017-01-01

    Introduction and Objectives Models for the prediction of bacterial growth in fresh pork are primarily developed using two-step regression (i.e. primary models followed by secondary models). These models are also generally based on experiments in liquids or ground meat and neglect surface growth....... It has been shown that one-step global regressions can result in more accurate models and that bacterial growth on intact surfaces can substantially differ from growth in liquid culture. Material and Methods We used a global-regression approach to develop predictive models for the growth of Salmonella....... One part of obtained logtransformed cell counts was used for model development and another for model validation. The Ratkowsky square root model and the relative lag time (RLT) model were integrated into the logistic model with delay. Fitted parameter estimates were compared to investigate the effect...

  15. Minimax Regression Quantiles

    DEFF Research Database (Denmark)

    Bache, Stefan Holst

    A new and alternative quantile regression estimator is developed and it is shown that the estimator is root n-consistent and asymptotically normal. The estimator is based on a minimax ‘deviance function’ and has asymptotically equivalent properties to the usual quantile regression estimator. It is......, however, a different and therefore new estimator. It allows for both linear- and nonlinear model specifications. A simple algorithm for computing the estimates is proposed. It seems to work quite well in practice but whether it has theoretical justification is still an open question....

  16. Moving NASA Beyond Low Earth Orbit: Future Human-Automation-Robotic Integration Challenges

    Science.gov (United States)

    Marquez, Jessica

    2016-01-01

    This presentation will provide an overview of current human spaceflight operations. It will also describe how future exploration missions will have to adapt and evolve in order to deal with more complex missions and communication latencies. Additionally, there are many implications regarding advanced automation and robotics, and this presentation will outline future human-automation-robotic integration challenges.

  17. An integrated unscented kalman filter and relevance vector regression approach for lithium-ion battery remaining useful life and short-term capacity prediction

    International Nuclear Information System (INIS)

    Zheng, Xiujuan; Fang, Huajing

    2015-01-01

    The gradual decreasing capacity of lithium-ion batteries can serve as a health indicator for tracking the degradation of lithium-ion batteries. It is important to predict the capacity of a lithium-ion battery for future cycles to assess its health condition and remaining useful life (RUL). In this paper, a novel method is developed using unscented Kalman filter (UKF) with relevance vector regression (RVR) and applied to RUL and short-term capacity prediction of batteries. A RVR model is employed as a nonlinear time-series prediction model to predict the UKF future residuals which otherwise remain zero during the prediction period. Taking the prediction step into account, the predictive value through the RVR method and the latest real residual value constitute the future evolution of the residuals with a time-varying weighting scheme. Next, the future residuals are utilized by UKF to recursively estimate the battery parameters for predicting RUL and short-term capacity. Finally, the performance of the proposed method is validated and compared to other predictors with the experimental data. According to the experimental and analysis results, the proposed approach has high reliability and prediction accuracy, which can be applied to battery monitoring and prognostics, as well as generalized to other prognostic applications. - Highlights: • An integrated method is proposed for RUL prediction as well as short-term capacity prediction. • Relevance vector regression model is employed as a nonlinear time-series prediction model. • Unscented Kalman filter is used to recursively update the states for battery model parameters during the prediction. • A time-varying weighting scheme is utilized to improve the accuracy of the RUL prediction. • The proposed method demonstrates high reliability and prediction accuracy.

  18. Regression with Sparse Approximations of Data

    DEFF Research Database (Denmark)

    Noorzad, Pardis; Sturm, Bob L.

    2012-01-01

    We propose sparse approximation weighted regression (SPARROW), a method for local estimation of the regression function that uses sparse approximation with a dictionary of measurements. SPARROW estimates the regression function at a point with a linear combination of a few regressands selected...... by a sparse approximation of the point in terms of the regressors. We show SPARROW can be considered a variant of \\(k\\)-nearest neighbors regression (\\(k\\)-NNR), and more generally, local polynomial kernel regression. Unlike \\(k\\)-NNR, however, SPARROW can adapt the number of regressors to use based...

  19. Assessing Potential Air Pollutant Emissions from Agricultural Feedstock Production using MOVES

    Energy Technology Data Exchange (ETDEWEB)

    Eberle, Annika [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Warner, Ethan [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhang, Yi Min [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Inman, Daniel J [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Carpenter Petri, Alberta C [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Heath, Garvin A [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Hettinger, Dylan J [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Bhatt, Arpit H [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2018-03-29

    Biomass feedstock production is expected to grow as demand for biofuels and bioenergy increases. The change in air pollutant emissions that may result from large-scale biomass supply has implications for local air quality and human health. We developed spatially explicit emissions inventories for corn grain and six cellulosic feedstocks through the extension of the National Renewable Energy Laboratory's Feedstock Production Emissions to Air Model (FPEAM). These inventories include emissions of seven pollutants (nitrogen oxides, ammonia, volatile organic compounds, particulate matter, sulfur oxides, and carbon monoxide) generated from biomass establishment, maintenance, harvest, transportation, and biofuel preprocessing activities. By integrating the EPA's MOtor Vehicle Emissions Simulator (MOVES) into FPEAM, we created a scalable framework to execute county-level runs of the MOVES-Onroad model for representative counties (i.e., those counties with the largest amount of cellulosic feedstock production in each state) on a national scale. We used these results to estimate emissions from the on-road transportation of biomass and combined them with county-level runs of the MOVES-Nonroad model to estimate emissions from agricultural equipment. We also incorporated documented emission factors to estimate emissions from chemical application and the operation of drying equipment for feedstock processing, and used methods developed by the EPA and the California Air Resources Board to estimate fugitive dust emissions. The model developed here could be applied to custom equipment budgets and is extensible to accommodate additional feedstocks and pollutants. Future work will also extend this model to analyze spatial boundaries beyond the county-scale (e.g., regional or sub-county levels).

  20. Logistic regression applied to natural hazards: rare event logistic regression with replications

    Directory of Open Access Journals (Sweden)

    M. Guns

    2012-06-01

    Full Text Available Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead to a robust detection of controlling factors, as the results can be strongly sample-dependent. In this paper, we introduce some concepts of Monte Carlo simulations in rare event logistic regression. This technique, so-called rare event logistic regression with replications, combines the strength of probabilistic and statistical methods, and allows overcoming some of the limitations of previous developments through robust variable selection. This technique was here developed for the analyses of landslide controlling factors, but the concept is widely applicable for statistical analyses of natural hazards.

  1. A simple approach to power and sample size calculations in logistic regression and Cox regression models.

    Science.gov (United States)

    Vaeth, Michael; Skovlund, Eva

    2004-06-15

    For a given regression problem it is possible to identify a suitably defined equivalent two-sample problem such that the power or sample size obtained for the two-sample problem also applies to the regression problem. For a standard linear regression model the equivalent two-sample problem is easily identified, but for generalized linear models and for Cox regression models the situation is more complicated. An approximately equivalent two-sample problem may, however, also be identified here. In particular, we show that for logistic regression and Cox regression models the equivalent two-sample problem is obtained by selecting two equally sized samples for which the parameters differ by a value equal to the slope times twice the standard deviation of the independent variable and further requiring that the overall expected number of events is unchanged. In a simulation study we examine the validity of this approach to power calculations in logistic regression and Cox regression models. Several different covariate distributions are considered for selected values of the overall response probability and a range of alternatives. For the Cox regression model we consider both constant and non-constant hazard rates. The results show that in general the approach is remarkably accurate even in relatively small samples. Some discrepancies are, however, found in small samples with few events and a highly skewed covariate distribution. Comparison with results based on alternative methods for logistic regression models with a single continuous covariate indicates that the proposed method is at least as good as its competitors. The method is easy to implement and therefore provides a simple way to extend the range of problems that can be covered by the usual formulas for power and sample size determination. Copyright 2004 John Wiley & Sons, Ltd.

  2. Integrated imaging – the complementary roles of radiology and ...

    African Journals Online (AJOL)

    Imaging techniques are moving towards integrated diagnostic clinical imaging. J Warwick,1 .... the stomach lesion and a lymph node. ese are shown on CT with calci cation ... fractures are diagnosed using conventional radiographs, but bone.

  3. 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...

  4. 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.)

  5. 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

  6. 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.

  7. 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.

  8. Post-processing through linear regression

    Science.gov (United States)

    van Schaeybroeck, B.; Vannitsem, S.

    2011-03-01

    Various post-processing techniques are compared for both deterministic and ensemble forecasts, all based on linear regression between forecast data and observations. In order to evaluate the quality of the regression methods, three criteria are proposed, related to the effective correction of forecast error, the optimal variability of the corrected forecast and multicollinearity. The regression schemes under consideration include the ordinary least-square (OLS) method, a new time-dependent Tikhonov regularization (TDTR) method, the total least-square method, a new geometric-mean regression (GM), a recently introduced error-in-variables (EVMOS) method and, finally, a "best member" OLS method. The advantages and drawbacks of each method are clarified. These techniques are applied in the context of the 63 Lorenz system, whose model version is affected by both initial condition and model errors. For short forecast lead times, the number and choice of predictors plays an important role. Contrarily to the other techniques, GM degrades when the number of predictors increases. At intermediate lead times, linear regression is unable to provide corrections to the forecast and can sometimes degrade the performance (GM and the best member OLS with noise). At long lead times the regression schemes (EVMOS, TDTR) which yield the correct variability and the largest correlation between ensemble error and spread, should be preferred.

  9. 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...

  10. Regression modeling methods, theory, and computation with SAS

    CERN Document Server

    Panik, Michael

    2009-01-01

    Regression Modeling: Methods, Theory, and Computation with SAS provides an introduction to a diverse assortment of regression techniques using SAS to solve a wide variety of regression problems. The author fully documents the SAS programs and thoroughly explains the output produced by the programs.The text presents the popular ordinary least squares (OLS) approach before introducing many alternative regression methods. It covers nonparametric regression, logistic regression (including Poisson regression), Bayesian regression, robust regression, fuzzy regression, random coefficients regression,

  11. Better Autologistic Regression

    Directory of Open Access Journals (Sweden)

    Mark A. Wolters

    2017-11-01

    Full Text Available Autologistic regression is an important probability model for dichotomous random variables observed along with covariate information. It has been used in various fields for analyzing binary data possessing spatial or network structure. The model can be viewed as an extension of the autologistic model (also known as the Ising model, quadratic exponential binary distribution, or Boltzmann machine to include covariates. It can also be viewed as an extension of logistic regression to handle responses that are not independent. Not all authors use exactly the same form of the autologistic regression model. Variations of the model differ in two respects. First, the variable coding—the two numbers used to represent the two possible states of the variables—might differ. Common coding choices are (zero, one and (minus one, plus one. Second, the model might appear in either of two algebraic forms: a standard form, or a recently proposed centered form. Little attention has been paid to the effect of these differences, and the literature shows ambiguity about their importance. It is shown here that changes to either coding or centering in fact produce distinct, non-nested probability models. Theoretical results, numerical studies, and analysis of an ecological data set all show that the differences among the models can be large and practically significant. Understanding the nature of the differences and making appropriate modeling choices can lead to significantly improved autologistic regression analyses. The results strongly suggest that the standard model with plus/minus coding, which we call the symmetric autologistic model, is the most natural choice among the autologistic variants.

  12. I Move: systematic development of a web-based computer tailored physical activity intervention, based on motivational interviewing and self-determination theory

    Science.gov (United States)

    2014-01-01

    Background This article describes the systematic development of the I Move intervention: a web-based computer tailored physical activity promotion intervention, aimed at increasing and maintaining physical activity among adults. This intervention is based on the theoretical insights and practical applications of self-determination theory and motivational interviewing. Methods/design Since developing interventions in a systemically planned way increases the likelihood of effectiveness, we used the Intervention Mapping protocol to develop the I Move intervention. In this article, we first describe how we proceeded through each of the six steps of the Intervention Mapping protocol. After that, we describe the content of the I Move intervention and elaborate on the planned randomized controlled trial. Discussion By integrating self-determination theory and motivational interviewing in web-based computer tailoring, the I Move intervention introduces a more participant-centered approach than traditional tailored interventions. Adopting this approach might enhance computer tailored physical activity interventions both in terms of intervention effectiveness and user appreciation. We will evaluate this in an randomized controlled trial, by comparing the I Move intervention to a more traditional web-based computer tailored intervention. Trial registration NTR4129 PMID:24580802

  13. Soft sensor development and optimization of the commercial petrochemical plant integrating support vector regression and genetic algorithm

    Directory of Open Access Journals (Sweden)

    S.K. Lahiri

    2009-09-01

    Full Text Available Soft sensors have been widely used in the industrial process control to improve the quality of the product and assure safety in the production. The core of a soft sensor is to construct a soft sensing model. This paper introduces support vector regression (SVR, a new powerful machine learning methodbased on a statistical learning theory (SLT into soft sensor modeling and proposes a new soft sensing modeling method based on SVR. This paper presents an artificial intelligence based hybrid soft sensormodeling and optimization strategies, namely support vector regression – genetic algorithm (SVR-GA for modeling and optimization of mono ethylene glycol (MEG quality variable in a commercial glycol plant. In the SVR-GA approach, a support vector regression model is constructed for correlating the process data comprising values of operating and performance variables. Next, model inputs describing the process operating variables are optimized using genetic algorithm with a view to maximize the process performance. The SVR-GA is a new strategy for soft sensor modeling and optimization. The major advantage of the strategies is that modeling and optimization can be conducted exclusively from the historic process data wherein the detailed knowledge of process phenomenology (reaction mechanism, kinetics etc. is not required. Using SVR-GA strategy, a number of sets of optimized operating conditions were found. The optimized solutions, when verified in an actual plant, resulted in a significant improvement in the quality.

  14. The Effect of Direction on Cursor Moving Kinematics

    Directory of Open Access Journals (Sweden)

    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.

  15. Unbalanced Regressions and the Predictive Equation

    DEFF Research Database (Denmark)

    Osterrieder, Daniela; Ventosa-Santaulària, Daniel; Vera-Valdés, J. Eduardo

    Predictive return regressions with persistent regressors are typically plagued by (asymptotically) biased/inconsistent estimates of the slope, non-standard or potentially even spurious statistical inference, and regression unbalancedness. We alleviate the problem of unbalancedness in the theoreti......Predictive return regressions with persistent regressors are typically plagued by (asymptotically) biased/inconsistent estimates of the slope, non-standard or potentially even spurious statistical inference, and regression unbalancedness. We alleviate the problem of unbalancedness...

  16. Comparison of multinomial logistic regression and logistic regression: which is more efficient in allocating land use?

    Science.gov (United States)

    Lin, Yingzhi; Deng, Xiangzheng; Li, Xing; Ma, Enjun

    2014-12-01

    Spatially explicit simulation of land use change is the basis for estimating the effects of land use and cover change on energy fluxes, ecology and the environment. At the pixel level, logistic regression is one of the most common approaches used in spatially explicit land use allocation models to determine the relationship between land use and its causal factors in driving land use change, and thereby to evaluate land use suitability. However, these models have a drawback in that they do not determine/allocate land use based on the direct relationship between land use change and its driving factors. Consequently, a multinomial logistic regression method was introduced to address this flaw, and thereby, judge the suitability of a type of land use in any given pixel in a case study area of the Jiangxi Province, China. A comparison of the two regression methods indicated that the proportion of correctly allocated pixels using multinomial logistic regression was 92.98%, which was 8.47% higher than that obtained using logistic regression. Paired t-test results also showed that pixels were more clearly distinguished by multinomial logistic regression than by logistic regression. In conclusion, multinomial logistic regression is a more efficient and accurate method for the spatial allocation of land use changes. The application of this method in future land use change studies may improve the accuracy of predicting the effects of land use and cover change on energy fluxes, ecology, and environment.

  17. Interpretation of commonly used statistical regression models.

    Science.gov (United States)

    Kasza, Jessica; Wolfe, Rory

    2014-01-01

    A review of some regression models commonly used in respiratory health applications is provided in this article. Simple linear regression, multiple linear regression, logistic regression and ordinal logistic regression are considered. The focus of this article is on the interpretation of the regression coefficients of each model, which are illustrated through the application of these models to a respiratory health research study. © 2013 The Authors. Respirology © 2013 Asian Pacific Society of Respirology.

  18. Linear regression

    CERN Document Server

    Olive, David J

    2017-01-01

    This text covers both multiple linear regression and some experimental design models. The text uses the response plot to visualize the model and to detect outliers, does not assume that the error distribution has a known parametric distribution, develops prediction intervals that work when the error distribution is unknown, suggests bootstrap hypothesis tests that may be useful for inference after variable selection, and develops prediction regions and large sample theory for the multivariate linear regression model that has m response variables. A relationship between multivariate prediction regions and confidence regions provides a simple way to bootstrap confidence regions. These confidence regions often provide a practical method for testing hypotheses. There is also a chapter on generalized linear models and generalized additive models. There are many R functions to produce response and residual plots, to simulate prediction intervals and hypothesis tests, to detect outliers, and to choose response trans...

  19. Regression modeling of ground-water flow

    Science.gov (United States)

    Cooley, R.L.; Naff, R.L.

    1985-01-01

    Nonlinear multiple regression methods are developed to model and analyze groundwater flow systems. Complete descriptions of regression methodology as applied to groundwater flow models allow scientists and engineers engaged in flow modeling to apply the methods to a wide range of problems. Organization of the text proceeds from an introduction that discusses the general topic of groundwater flow modeling, to a review of basic statistics necessary to properly apply regression techniques, and then to the main topic: exposition and use of linear and nonlinear regression to model groundwater flow. Statistical procedures are given to analyze and use the regression models. A number of exercises and answers are included to exercise the student on nearly all the methods that are presented for modeling and statistical analysis. Three computer programs implement the more complex methods. These three are a general two-dimensional, steady-state regression model for flow in an anisotropic, heterogeneous porous medium, a program to calculate a measure of model nonlinearity with respect to the regression parameters, and a program to analyze model errors in computed dependent variables such as hydraulic head. (USGS)

  20. Quantum mechanics on the half-line using path integrals

    International Nuclear Information System (INIS)

    Clark, T.E.; Menikoff, R.; Sharp, D.H.

    1980-01-01

    We study the Feynman path-integral formalism for the constrained problem of a free particle moving on the half-line. It is shown that the effect of the boundary condition at the origin can be incorporated into the path integral by a simple modification of the action. The small-time behavior of the Green's function can be obtained from the stationary-phase evaluation of our expression for the path integral, which in this case includes contributions from both the direct and reflected classical paths

  1. Can We Use Regression Modeling to Quantify Mean Annual Streamflow at a Global-Scale?

    Science.gov (United States)

    Barbarossa, V.; Huijbregts, M. A. J.; Hendriks, J. A.; Beusen, A.; Clavreul, J.; King, H.; Schipper, A.

    2016-12-01

    Quantifying mean annual flow of rivers (MAF) at ungauged sites is essential for a number of applications, including assessments of global water supply, ecosystem integrity and water footprints. MAF can be quantified with spatially explicit process-based models, which might be overly time-consuming and data-intensive for this purpose, or with empirical regression models that predict MAF based on climate and catchment characteristics. Yet, regression models have mostly been developed at a regional scale and the extent to which they can be extrapolated to other regions is not known. In this study, we developed a global-scale regression model for MAF using observations of discharge and catchment characteristics from 1,885 catchments worldwide, ranging from 2 to 106 km2 in size. In addition, we compared the performance of the regression model with the predictive ability of the spatially explicit global hydrological model PCR-GLOBWB [van Beek et al., 2011] by comparing results from both models to independent measurements. We obtained a regression model explaining 89% of the variance in MAF based on catchment area, mean annual precipitation and air temperature, average slope and elevation. The regression model performed better than PCR-GLOBWB for the prediction of MAF, as root-mean-square error values were lower (0.29 - 0.38 compared to 0.49 - 0.57) and the modified index of agreement was higher (0.80 - 0.83 compared to 0.72 - 0.75). Our regression model can be applied globally at any point of the river network, provided that the input parameters are within the range of values employed in the calibration of the model. The performance is reduced for water scarce regions and further research should focus on improving such an aspect for regression-based global hydrological models.

  2. 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...

  3. 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.

  4. Bring in the social context: towards an integrated approach to health promotion and prevention.

    Science.gov (United States)

    Thorlindsson, Thorolfur

    2011-03-01

    In this paper I take up the quest for an integrated approach to health promotion and prevention that incorporates the social context. I suggest that an integrated theory of public health has to rethink the individual society relationships and move beyond the dominance of socialization theory and individual level analysis. A theoretical analysis of key issues in an integrated theory of public health. I maintain that we must shift the attention away from the individual to the social organization and the embeddedness of the social actor in the ongoing social networks and relationships; we must pay attention to the definition of levels of analysis and the relationships between them; we must emphasize the social mechanisms that influence people in social relationships and networks and connect various levels; we must reconsider some of the epistemological and methodological ideas that have been taken for granted and pay attention to issues of emergence and reductionism and the use of multiple methods. I conclude by suggesting that if public health is to move forward and develop better theories, and more efficient ways of prevention and health promotion, it needs to move beyond reductionist models of social behaviour and develop a transdisciplinary approach that integrates various elements from different disciplines and different levels of analysis.

  5. Post-processing through linear regression

    Directory of Open Access Journals (Sweden)

    B. Van Schaeybroeck

    2011-03-01

    Full Text Available Various post-processing techniques are compared for both deterministic and ensemble forecasts, all based on linear regression between forecast data and observations. In order to evaluate the quality of the regression methods, three criteria are proposed, related to the effective correction of forecast error, the optimal variability of the corrected forecast and multicollinearity. The regression schemes under consideration include the ordinary least-square (OLS method, a new time-dependent Tikhonov regularization (TDTR method, the total least-square method, a new geometric-mean regression (GM, a recently introduced error-in-variables (EVMOS method and, finally, a "best member" OLS method. The advantages and drawbacks of each method are clarified.

    These techniques are applied in the context of the 63 Lorenz system, whose model version is affected by both initial condition and model errors. For short forecast lead times, the number and choice of predictors plays an important role. Contrarily to the other techniques, GM degrades when the number of predictors increases. At intermediate lead times, linear regression is unable to provide corrections to the forecast and can sometimes degrade the performance (GM and the best member OLS with noise. At long lead times the regression schemes (EVMOS, TDTR which yield the correct variability and the largest correlation between ensemble error and spread, should be preferred.

  6. A comparison of random forest regression and multiple linear regression for prediction in neuroscience.

    Science.gov (United States)

    Smith, Paul F; Ganesh, Siva; Liu, Ping

    2013-10-30

    Regression is a common statistical tool for prediction in neuroscience. However, linear regression is by far the most common form of regression used, with regression trees receiving comparatively little attention. In this study, the results of conventional multiple linear regression (MLR) were compared with those of random forest regression (RFR), in the prediction of the concentrations of 9 neurochemicals in the vestibular nucleus complex and cerebellum that are part of the l-arginine biochemical pathway (agmatine, putrescine, spermidine, spermine, l-arginine, l-ornithine, l-citrulline, glutamate and γ-aminobutyric acid (GABA)). The R(2) values for the MLRs were higher than the proportion of variance explained values for the RFRs: 6/9 of them were ≥ 0.70 compared to 4/9 for RFRs. Even the variables that had the lowest R(2) values for the MLRs, e.g. ornithine (0.50) and glutamate (0.61), had much lower proportion of variance explained values for the RFRs (0.27 and 0.49, respectively). The RSE values for the MLRs were lower than those for the RFRs in all but two cases. In general, MLRs seemed to be superior to the RFRs in terms of predictive value and error. In the case of this data set, MLR appeared to be superior to RFR in terms of its explanatory value and error. This result suggests that MLR may have advantages over RFR for prediction in neuroscience with this kind of data set, but that RFR can still have good predictive value in some cases. Copyright © 2013 Elsevier B.V. All rights reserved.

  7. Logistic regression applied to natural hazards: rare event logistic regression with replications

    OpenAIRE

    Guns, M.; Vanacker, Veerle

    2012-01-01

    Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead to a robust detection of controlling factors, as the results can be strongly sample-dependent. In this paper, we introduce some concepts of Monte Carlo simulations in rare event logistic regression. This technique, so-called rare event logisti...

  8. The use of nonlinear regression analysis for integrating pollutant concentration measurements with atmospheric dispersion modeling for source term estimation

    International Nuclear Information System (INIS)

    Edwards, L.L.; Freis, R.P.; Peters, L.G.; Gudiksen, P.H.; Pitovranov, S.E.

    1993-01-01

    The accuracy associated with assessing the environmental consequences of an accidental release of radioactivity is highly dependent on the knowledge of the source term characteristics, which are generally poorly known. The development of an automated numerical technique that integrates the radiological measurements with atmospheric dispersion modeling for more accurate source term estimation is reported. Often, this process of parameter estimation is performed by an emergency response assessor, who takes an intelligent first guess at the model parameters, then, comparing the model results with whatever measurements are available, makes an intuitive, informed next guess of the model parameters. This process may be repeated any number of times until the assessor feels that the model results are reasonable in terms of the measured observations. A new approach, based on a nonlinear least-squares regression scheme coupled with the existing Atmospheric Release Advisory Capability three-dimensional atmospheric dispersion models, is to supplement the assessor's intuition with automated mathematical methods that do not significantly increase the response time of the existing predictive models. The viability of the approach is evaluated by estimation of the known SF 6 tracer release rates associated with the Mesoscale Atmospheric Transport Studies tracer experiments conducted at the Savannah River Laboratory during 1983. These 19 experiments resulted in 14 successful, separate tracer releases with sampling of the tracer plumes along the cross-plume arc situated ∼30 km from the release site

  9. ATLAS Solenoid Integration

    CERN Multimedia

    Ruber, R

    Last month the central solenoid was installed in the barrel cryostat, which it shares with the liquid argon calorimeter. Figure 1: Some members of the solenoid and liquid argon teams proudly pose in front of the barrel cryosat, complete with detector and magnet. Some two years ago the central solenoid arrived at CERN after being manufactured and tested in Japan. It was kept in storage until last October when it was finally moved to the barrel cryostat integration area. Here a position survey of the solenoid (with respect to the cryostat's inner warm vessel) was performed. Figure 2: The alignment survey by Dirk Mergelkuhl and Aude Wiart. (EST-SU) At the start of the New Year the solenoid was moved to the cryostat insertion stand. Figure 3: The solenoid on the insertion stand, with Akira Yamamoto the solenoid designer and project leader. Figure 4: Taka Kondo, ATLAS Japan spokesperson, and Shoichi Mizumaki, Toshiba project engineer for the ATLAS solenoid, celebrate the insertion. Aft...

  10. Toward an Integrative Model of Professional Practice.

    Science.gov (United States)

    Newman, Margaret A.

    1990-01-01

    The cycles of growth of the nursing profession depict subordination of nursing to hospital administration and medicine. Nursing is ready to move into an integrative, collaborative stage of development that places nurses directly responsible to patients, and this would facilitate nursing's response to clients' health concerns wherever they occur.…

  11. Get It Together: Integrating Data with XML.

    Science.gov (United States)

    Miller, Ron

    2003-01-01

    Discusses the use of XML for data integration to move data across different platforms, including across the Internet, from a variety of sources. Topics include flexibility; standards; organizing databases; unstructured data and the use of meta tags to encode it with XML information; cost effectiveness; and eliminating client software licenses.…

  12. A Seemingly Unrelated Poisson Regression Model

    OpenAIRE

    King, Gary

    1989-01-01

    This article introduces a new estimator for the analysis of two contemporaneously correlated endogenous event count variables. This seemingly unrelated Poisson regression model (SUPREME) estimator combines the efficiencies created by single equation Poisson regression model estimators and insights from "seemingly unrelated" linear regression models.

  13. Convergence diagnostics for Eigenvalue problems with linear regression model

    International Nuclear Information System (INIS)

    Shi, Bo; Petrovic, Bojan

    2011-01-01

    Although the Monte Carlo method has been extensively used for criticality/Eigenvalue problems, a reliable, robust, and efficient convergence diagnostics method is still desired. Most methods are based on integral parameters (multiplication factor, entropy) and either condense the local distribution information into a single value (e.g., entropy) or even disregard it. We propose to employ the detailed cycle-by-cycle local flux evolution obtained by using mesh tally mechanism to assess the source and flux convergence. By applying a linear regression model to each individual mesh in a mesh tally for convergence diagnostics, a global convergence criterion can be obtained. We exemplify this method on two problems and obtain promising diagnostics results. (author)

  14. 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...

  15. Effects of integration time on in-water radiometric profiles.

    Science.gov (United States)

    D'Alimonte, Davide; Zibordi, Giuseppe; Kajiyama, Tamito

    2018-03-05

    This work investigates the effects of integration time on in-water downward irradiance E d , upward irradiance E u and upwelling radiance L u profile data acquired with free-fall hyperspectral systems. Analyzed quantities are the subsurface value and the diffuse attenuation coefficient derived by applying linear and non-linear regression schemes. Case studies include oligotrophic waters (Case-1), as well as waters dominated by Colored Dissolved Organic Matter (CDOM) and Non-Algal Particles (NAP). Assuming a 24-bit digitization, measurements resulting from the accumulation of photons over integration times varying between 8 and 2048ms are evaluated at depths corresponding to: 1) the beginning of each integration interval (Fst); 2) the end of each integration interval (Lst); 3) the averages of Fst and Lst values (Avg); and finally 4) the values weighted accounting for the diffuse attenuation coefficient of water (Wgt). Statistical figures show that the effects of integration time can bias results well above 5% as a function of the depth definition. Results indicate the validity of the Wgt depth definition and the fair applicability of the Avg one. Instead, both the Fst and Lst depths should not be adopted since they may introduce pronounced biases in E u and L u regression products for highly absorbing waters. Finally, the study reconfirms the relevance of combining multiple radiometric casts into a single profile to increase precision of regression products.

  16. Recursive Algorithm For Linear Regression

    Science.gov (United States)

    Varanasi, S. V.

    1988-01-01

    Order of model determined easily. Linear-regression algorithhm includes recursive equations for coefficients of model of increased order. Algorithm eliminates duplicative calculations, facilitates search for minimum order of linear-regression model fitting set of data satisfactory.

  17. Applied regression analysis a research tool

    CERN Document Server

    Pantula, Sastry; Dickey, David

    1998-01-01

    Least squares estimation, when used appropriately, is a powerful research tool. A deeper understanding of the regression concepts is essential for achieving optimal benefits from a least squares analysis. This book builds on the fundamentals of statistical methods and provides appropriate concepts that will allow a scientist to use least squares as an effective research tool. Applied Regression Analysis is aimed at the scientist who wishes to gain a working knowledge of regression analysis. The basic purpose of this book is to develop an understanding of least squares and related statistical methods without becoming excessively mathematical. It is the outgrowth of more than 30 years of consulting experience with scientists and many years of teaching an applied regression course to graduate students. Applied Regression Analysis serves as an excellent text for a service course on regression for non-statisticians and as a reference for researchers. It also provides a bridge between a two-semester introduction to...

  18. 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.

  19. 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.

  20. A comprehensive method for evaluating precision of transfer alignment on a moving base

    Science.gov (United States)

    Yin, Hongliang; Xu, Bo; Liu, Dezheng

    2017-09-01

    In this study, we propose the use of the Degree of Alignment (DOA) in engineering applications for evaluating the precision of and identifying the transfer alignment on a moving base. First, we derive the statistical formula on the basis of estimations. Next, we design a scheme for evaluating the transfer alignment on a moving base, for which the attitude error cannot be directly measured. Then, we build a mathematic estimation model and discuss Fixed Point Smoothing (FPS), Returns to Scale (RTS), Inverted Sequence Recursive Estimation (ISRE), and Kalman filter estimation methods, which can be used when evaluating alignment accuracy. Our theoretical calculations and simulated analyses show that the DOA reflects not only the alignment time and accuracy but also differences in the maneuver schemes, and is suitable for use as an integrated evaluation index. Furthermore, all four of these algorithms can be used to identify the transfer alignment and evaluate its accuracy. We recommend RTS in particular for engineering applications. Generalized DOAs should be calculated according to the tactical requirements.

  1. Standards for Standardized Logistic Regression Coefficients

    Science.gov (United States)

    Menard, Scott

    2011-01-01

    Standardized coefficients in logistic regression analysis have the same utility as standardized coefficients in linear regression analysis. Although there has been no consensus on the best way to construct standardized logistic regression coefficients, there is now sufficient evidence to suggest a single best approach to the construction of a…

  2. [Application of negative binomial regression and modified Poisson regression in the research of risk factors for injury frequency].

    Science.gov (United States)

    Cao, Qingqing; Wu, Zhenqiang; Sun, Ying; Wang, Tiezhu; Han, Tengwei; Gu, Chaomei; Sun, Yehuan

    2011-11-01

    To Eexplore the application of negative binomial regression and modified Poisson regression analysis in analyzing the influential factors for injury frequency and the risk factors leading to the increase of injury frequency. 2917 primary and secondary school students were selected from Hefei by cluster random sampling method and surveyed by questionnaire. The data on the count event-based injuries used to fitted modified Poisson regression and negative binomial regression model. The risk factors incurring the increase of unintentional injury frequency for juvenile students was explored, so as to probe the efficiency of these two models in studying the influential factors for injury frequency. The Poisson model existed over-dispersion (P Poisson regression and negative binomial regression model, was fitted better. respectively. Both showed that male gender, younger age, father working outside of the hometown, the level of the guardian being above junior high school and smoking might be the results of higher injury frequencies. On a tendency of clustered frequency data on injury event, both the modified Poisson regression analysis and negative binomial regression analysis can be used. However, based on our data, the modified Poisson regression fitted better and this model could give a more accurate interpretation of relevant factors affecting the frequency of injury.

  3. Logistic regression for dichotomized counts.

    Science.gov (United States)

    Preisser, John S; Das, Kalyan; Benecha, Habtamu; Stamm, John W

    2016-12-01

    Sometimes there is interest in a dichotomized outcome indicating whether a count variable is positive or zero. Under this scenario, the application of ordinary logistic regression may result in efficiency loss, which is quantifiable under an assumed model for the counts. In such situations, a shared-parameter hurdle model is investigated for more efficient estimation of regression parameters relating to overall effects of covariates on the dichotomous outcome, while handling count data with many zeroes. One model part provides a logistic regression containing marginal log odds ratio effects of primary interest, while an ancillary model part describes the mean count of a Poisson or negative binomial process in terms of nuisance regression parameters. Asymptotic efficiency of the logistic model parameter estimators of the two-part models is evaluated with respect to ordinary logistic regression. Simulations are used to assess the properties of the models with respect to power and Type I error, the latter investigated under both misspecified and correctly specified models. The methods are applied to data from a randomized clinical trial of three toothpaste formulations to prevent incident dental caries in a large population of Scottish schoolchildren. © The Author(s) 2014.

  4. PENGARUH PENERAPAN SISTEM MOVING CLASS DAN MOTIVASI BELAJAR TERHADAP HASIL BELAJAR MATA PELAJARAN PENGANTAR ADMINISTRASI PERKANTORAN SISWA KELAS XI PROGRAM KEAHLIAN ADMINISTRASI PERKANTORAN DI SMK NEGERI 9 SEMARANG TAHUN AJARAN 2014/2015

    Directory of Open Access Journals (Sweden)

    Stefhani Tantra Sintara

    2015-11-01

    Full Text Available Tujuan penelitian ini yaitu untuk mengetahui adakah pengaruh penerapan sistem moving class dan motivasi belajar terhadap hasil belajar mata pelajaran pengantar administrasi perkantoran siswa kelas XI secara simultan maupun parsial. Populasi yang diteliti dalam penelitian ini adalah siswa kelas XI Program Keahlian Administrasi Perkantoran tahun ajaran 2014/2015 sebanyak 105 siswa. Peneliti mengambil teknik sensus, yaitu mengambil keseluruhan populasi sebagai objek penelitian. Variabel yang dikaji dalam penelitian ini adalah penerapan sistem moving class (X1, motivasi belajar (X2 dan hasil belajar (Y. Pengumpulan data dilakukan dengan cara kuesioner dan dokumentasi. Teknik analisis data menggunakan analisis deskriptif dan analisis regresi berganda. Hasil dari analisis regresi linear berganda diperoleh persamaan Y = 6,164+0,883X1+0,300X2+ e. Ada pengaruh secara simultan antara penerapan sistem moving class dan motivasi belajar terhadap hasil belajar sebesar 51,8%, sedangkan pengaruh secara parsial penerepan sistem moving class sebesar 28,84% dan motivasi belajar sebesar 10,63%. The problem that had been studied in this research is whether there is influence of moving class implementation and learning motivation toward eleventh grade students’ achievement of introductory office administration lesson simultaneously and partially. The population that had been studied in this research is eleventh grade students of office administration major in the academic year of 2014/2015, as many as 105 students. The researcher took a census technique which take the whole population as the object of the research. An investigated variable in this research is the implementation of moving class system (X1, learning motivation (X2, and the result of the study (Y. The data were collected using questionnaireand documentation. The analysis of the data is usingdescriptive analysis and bifiliar regression analysis. The result of the linear regression analysis obtained an

  5. Moving Beyond the “Lump-Sum”: A Case Study of Partnership for Positive Social Change

    Directory of Open Access Journals (Sweden)

    Anne Bunde-Birouste

    2010-08-01

    Full Text Available Based on a foundation of an integrated sport program for positive social change and health promotion, this paper presents a case study of the relationship between a corporate sponsor (JP Morgan, and a community-based health promotion/social change organization (Football United. The paper articulates the various issues that arise in management of such a program, and the involvement of sponsors in its operation. Illustrated through the JP Morgan - Football United case study, the paper explores: the difficulties of maintaining a program that remains faithful to the expectations and demands of each stakeholder group involved; the challenges involved in harnessing support for a program when moving beyond the one-dimensional transfer of funds; the different needs and expectations of/for volunteers this type of complex health promotion intervention. This case study has been written to propose that an “integrated partnership” between a corporate body and a social change organization can produce significant advantages beyond the scope of uncomplicated financial contribution The key feature documented is that corporate investment can move beyond abstract “lump-sum” social responsibility, towards targeted contributions to detailed outcomes through sustainable and meaningful involvement in a health promotion framework. This in turn equates to funding stability and a more empowering partnership for the health promotion/social change organization.

  6. 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...

  7. What is new about covered interest parity condition in the European Union? Evidence from fractal cross-correlation regressions

    Czech Academy of Sciences Publication Activity Database

    Krištoufek, Ladislav; Ferreira, P.

    2017-01-01

    Roč. 486, č. 1 (2017), s. 554-566 ISSN 0378-4371 R&D Projects: GA ČR(CZ) GA17-12408S Institutional support: RVO:67985556 Keywords : covered interest parity * detrended cross-correlation analysis * detrending moving cross-corrrelation analysis * financial integration Subject RIV: AH - Economics OBOR OECD: Applied Economics, Econometrics Impact factor: 2.243, year: 2016 http://library.utia.cas.cz/separaty/2017/E/kristoufek-0478811.pdf

  8. Bayesian ARTMAP for regression.

    Science.gov (United States)

    Sasu, L M; Andonie, R

    2013-10-01

    Bayesian ARTMAP (BA) is a recently introduced neural architecture which uses a combination of Fuzzy ARTMAP competitive learning and Bayesian learning. Training is generally performed online, in a single-epoch. During training, BA creates input data clusters as Gaussian categories, and also infers the conditional probabilities between input patterns and categories, and between categories and classes. During prediction, BA uses Bayesian posterior probability estimation. So far, BA was used only for classification. The goal of this paper is to analyze the efficiency of BA for regression problems. Our contributions are: (i) we generalize the BA algorithm using the clustering functionality of both ART modules, and name it BA for Regression (BAR); (ii) we prove that BAR is a universal approximator with the best approximation property. In other words, BAR approximates arbitrarily well any continuous function (universal approximation) and, for every given continuous function, there is one in the set of BAR approximators situated at minimum distance (best approximation); (iii) we experimentally compare the online trained BAR with several neural models, on the following standard regression benchmarks: CPU Computer Hardware, Boston Housing, Wisconsin Breast Cancer, and Communities and Crime. Our results show that BAR is an appropriate tool for regression tasks, both for theoretical and practical reasons. Copyright © 2013 Elsevier Ltd. All rights reserved.

  9. Mechanisms of neuroblastoma regression

    Science.gov (United States)

    Brodeur, Garrett M.; Bagatell, Rochelle

    2014-01-01

    Recent genomic and biological studies of neuroblastoma have shed light on the dramatic heterogeneity in the clinical behaviour of this disease, which spans from spontaneous regression or differentiation in some patients, to relentless disease progression in others, despite intensive multimodality therapy. This evidence also suggests several possible mechanisms to explain the phenomena of spontaneous regression in neuroblastomas, including neurotrophin deprivation, humoral or cellular immunity, loss of telomerase activity and alterations in epigenetic regulation. A better understanding of the mechanisms of spontaneous regression might help to identify optimal therapeutic approaches for patients with these tumours. Currently, the most druggable mechanism is the delayed activation of developmentally programmed cell death regulated by the tropomyosin receptor kinase A pathway. Indeed, targeted therapy aimed at inhibiting neurotrophin receptors might be used in lieu of conventional chemotherapy or radiation in infants with biologically favourable tumours that require treatment. Alternative approaches consist of breaking immune tolerance to tumour antigens or activating neurotrophin receptor pathways to induce neuronal differentiation. These approaches are likely to be most effective against biologically favourable tumours, but they might also provide insights into treatment of biologically unfavourable tumours. We describe the different mechanisms of spontaneous neuroblastoma regression and the consequent therapeutic approaches. PMID:25331179

  10. Information Technology Integration in Teacher Education: Supporting the Paradigm Shift in Hong Kong.

    Science.gov (United States)

    Lee, Kar Tin

    2001-01-01

    Examines the integration of information technology (IT) at the Hong Kong Institute of Education, presenting the rationale for this move, characteristics of IT integration, and program development issues for making IT application a critical component of contemporary teacher education. The paper presents a framework for program development and…

  11. 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.

  12. Bone marrow endothelial progenitors augment atherosclerotic plaque regression in a mouse model of plasma lipid lowering

    Science.gov (United States)

    Yao, Longbiao; Heuser-Baker, Janet; Herlea-Pana, Oana; Iida, Ryuji; Wang, Qilong; Zou, Ming-Hui; Barlic-Dicen, Jana

    2012-01-01

    The major event initiating atherosclerosis is hypercholesterolemia-induced disruption of vascular endothelium integrity. In settings of endothelial damage, endothelial progenitor cells (EPCs) are mobilized from bone marrow into circulation and home to sites of vascular injury where they aid endothelial regeneration. Given the beneficial effects of EPCs in vascular repair, we hypothesized that these cells play a pivotal role in atherosclerosis regression. We tested our hypothesis in the atherosclerosis-prone mouse model in which hypercholesterolemia, one of the main factors affecting EPC homeostasis, is reversible (Reversa mice). In these mice normalization of plasma lipids decreased atherosclerotic burden; however, plaque regression was incomplete. To explore whether endothelial progenitors contribute to atherosclerosis regression, bone marrow EPCs from a transgenic strain expressing green fluorescent protein under the control of endothelial cell-specific Tie2 promoter (Tie2-GFP+) were isolated. These cells were then adoptively transferred into atheroregressing Reversa recipients where they augmented plaque regression induced by reversal of hypercholesterolemia. Advanced plaque regression correlated with engraftment of Tie2-GFP+ EPCs into endothelium and resulted in an increase in atheroprotective nitric oxide and improved vascular relaxation. Similarly augmented plaque regression was also detected in regressing Reversa mice treated with the stem cell mobilizer AMD3100 which also mobilizes EPCs to peripheral blood. We conclude that correction of hypercholesterolemia in Reversa mice leads to partial plaque regression that can be augmented by AMD3100 treatment or by adoptive transfer of EPCs. This suggests that direct cell therapy or indirect progenitor cell mobilization therapy may be used in combination with statins to treat atherosclerosis. PMID:23081735

  13. Using the Ridge Regression Procedures to Estimate the Multiple Linear Regression Coefficients

    Science.gov (United States)

    Gorgees, HazimMansoor; Mahdi, FatimahAssim

    2018-05-01

    This article concerns with comparing the performance of different types of ordinary ridge regression estimators that have been already proposed to estimate the regression parameters when the near exact linear relationships among the explanatory variables is presented. For this situations we employ the data obtained from tagi gas filling company during the period (2008-2010). The main result we reached is that the method based on the condition number performs better than other methods since it has smaller mean square error (MSE) than the other stated methods.

  14. Multicollinearity and Regression Analysis

    Science.gov (United States)

    Daoud, Jamal I.

    2017-12-01

    In regression analysis it is obvious to have a correlation between the response and predictor(s), but having correlation among predictors is something undesired. The number of predictors included in the regression model depends on many factors among which, historical data, experience, etc. At the end selection of most important predictors is something objective due to the researcher. Multicollinearity is a phenomena when two or more predictors are correlated, if this happens, the standard error of the coefficients will increase [8]. Increased standard errors means that the coefficients for some or all independent variables may be found to be significantly different from In other words, by overinflating the standard errors, multicollinearity makes some variables statistically insignificant when they should be significant. In this paper we focus on the multicollinearity, reasons and consequences on the reliability of the regression model.

  15. Panel Smooth Transition Regression Models

    DEFF Research Database (Denmark)

    González, Andrés; Terasvirta, Timo; Dijk, Dick van

    We introduce the panel smooth transition regression model. This new model is intended for characterizing heterogeneous panels, allowing the regression coefficients to vary both across individuals and over time. Specifically, heterogeneity is allowed for by assuming that these coefficients are bou...

  16. On the Choice of Difference Sequence in a Unified Framework for Variance Estimation in Nonparametric Regression

    KAUST Repository

    Dai, Wenlin; Tong, Tiejun; Zhu, Lixing

    2017-01-01

    Difference-based methods do not require estimating the mean function in nonparametric regression and are therefore popular in practice. In this paper, we propose a unified framework for variance estimation that combines the linear regression method with the higher-order difference estimators systematically. The unified framework has greatly enriched the existing literature on variance estimation that includes most existing estimators as special cases. More importantly, the unified framework has also provided a smart way to solve the challenging difference sequence selection problem that remains a long-standing controversial issue in nonparametric regression for several decades. Using both theory and simulations, we recommend to use the ordinary difference sequence in the unified framework, no matter if the sample size is small or if the signal-to-noise ratio is large. Finally, to cater for the demands of the application, we have developed a unified R package, named VarED, that integrates the existing difference-based estimators and the unified estimators in nonparametric regression and have made it freely available in the R statistical program http://cran.r-project.org/web/packages/.

  17. On the Choice of Difference Sequence in a Unified Framework for Variance Estimation in Nonparametric Regression

    KAUST Repository

    Dai, Wenlin

    2017-09-01

    Difference-based methods do not require estimating the mean function in nonparametric regression and are therefore popular in practice. In this paper, we propose a unified framework for variance estimation that combines the linear regression method with the higher-order difference estimators systematically. The unified framework has greatly enriched the existing literature on variance estimation that includes most existing estimators as special cases. More importantly, the unified framework has also provided a smart way to solve the challenging difference sequence selection problem that remains a long-standing controversial issue in nonparametric regression for several decades. Using both theory and simulations, we recommend to use the ordinary difference sequence in the unified framework, no matter if the sample size is small or if the signal-to-noise ratio is large. Finally, to cater for the demands of the application, we have developed a unified R package, named VarED, that integrates the existing difference-based estimators and the unified estimators in nonparametric regression and have made it freely available in the R statistical program http://cran.r-project.org/web/packages/.

  18. Credit Scoring Problem Based on Regression Analysis

    OpenAIRE

    Khassawneh, Bashar Suhil Jad Allah

    2014-01-01

    ABSTRACT: This thesis provides an explanatory introduction to the regression models of data mining and contains basic definitions of key terms in the linear, multiple and logistic regression models. Meanwhile, the aim of this study is to illustrate fitting models for the credit scoring problem using simple linear, multiple linear and logistic regression models and also to analyze the found model functions by statistical tools. Keywords: Data mining, linear regression, logistic regression....

  19. A new irradiation unit constructed of self-moving gantry-CT and linac

    International Nuclear Information System (INIS)

    Kuriyama, Kengo; Onishi, Hiroshi; Sano, Naoki; Komiyama, Takafumi; Aikawa, Yoshihito; Tateda, Yoshihito; Araki, Tsutomu; Uematsu, Minoru

    2003-01-01

    Purpose: To improve reproducibility in stereotactic irradiation (STI) without using noninvasive immobilization devices or body frames, we have developed an integrated computed tomography (CT)-linac irradiation system connecting CT scanner and linac via a common treatment couch. Methods and Materials: This system consists of a linac, a CT scanner, and a common treatment couch. The linac and the CT gantry are positioned on opposite ends of the couch so that, by rotating the treatment couch, linac radiotherapy or CT scanning can be performed. The rotational axis of the linac gantry is coaxial with that of the CT gantry, and the position of the linac isocenter on the couch matches the origin of the coordinate system for CT scanning when the couch is rotated 180 degree sign toward the CT side. Instead of the couch moving into the gantry, as in conventional CT, in this case the table is fixed and scanning is accomplished by moving the gantry. We evaluated the rotational accuracy of the common couch and the scan-position accuracy of the self-moving gantry CT. Results: The positional accuracy of the common couch was 0.20, 0.18, and 0.39 mm in the lateral, longitudinal, and vertical directions, respectively. The scan-position accuracy of the CT gantry was less than 0.4 mm in the lateral, longitudinal, and vertical directions. Conclusion: This irradiation system has a high accuracy and is useful for noninvasive STI and for verification of the position of a target in three-dimensional conformal radiotherapy

  20. 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.

  1. 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.

  2. Iterative integral parameter identification of a respiratory mechanics model.

    Science.gov (United States)

    Schranz, Christoph; Docherty, Paul D; Chiew, Yeong Shiong; Möller, Knut; Chase, J Geoffrey

    2012-07-18

    Patient-specific respiratory mechanics models can support the evaluation of optimal lung protective ventilator settings during ventilation therapy. Clinical application requires that the individual's model parameter values must be identified with information available at the bedside. Multiple linear regression or gradient-based parameter identification methods are highly sensitive to noise and initial parameter estimates. Thus, they are difficult to apply at the bedside to support therapeutic decisions. An iterative integral parameter identification method is applied to a second order respiratory mechanics model. The method is compared to the commonly used regression methods and error-mapping approaches using simulated and clinical data. The clinical potential of the method was evaluated on data from 13 Acute Respiratory Distress Syndrome (ARDS) patients. The iterative integral method converged to error minima 350 times faster than the Simplex Search Method using simulation data sets and 50 times faster using clinical data sets. Established regression methods reported erroneous results due to sensitivity to noise. In contrast, the iterative integral method was effective independent of initial parameter estimations, and converged successfully in each case tested. These investigations reveal that the iterative integral method is beneficial with respect to computing time, operator independence and robustness, and thus applicable at the bedside for this clinical application.

  3. [From clinical judgment to linear regression model.

    Science.gov (United States)

    Palacios-Cruz, Lino; Pérez, Marcela; Rivas-Ruiz, Rodolfo; Talavera, Juan O

    2013-01-01

    When we think about mathematical models, such as linear regression model, we think that these terms are only used by those engaged in research, a notion that is far from the truth. Legendre described the first mathematical model in 1805, and Galton introduced the formal term in 1886. Linear regression is one of the most commonly used regression models in clinical practice. It is useful to predict or show the relationship between two or more variables as long as the dependent variable is quantitative and has normal distribution. Stated in another way, the regression is used to predict a measure based on the knowledge of at least one other variable. Linear regression has as it's first objective to determine the slope or inclination of the regression line: Y = a + bx, where "a" is the intercept or regression constant and it is equivalent to "Y" value when "X" equals 0 and "b" (also called slope) indicates the increase or decrease that occurs when the variable "x" increases or decreases in one unit. In the regression line, "b" is called regression coefficient. The coefficient of determination (R 2 ) indicates the importance of independent variables in the outcome.

  4. Autistic Regression

    Science.gov (United States)

    Matson, Johnny L.; Kozlowski, Alison M.

    2010-01-01

    Autistic regression is one of the many mysteries in the developmental course of autism and pervasive developmental disorders not otherwise specified (PDD-NOS). Various definitions of this phenomenon have been used, further clouding the study of the topic. Despite this problem, some efforts at establishing prevalence have been made. The purpose of…

  5. Ridge regression estimator: combining unbiased and ordinary ridge regression methods of estimation

    Directory of Open Access Journals (Sweden)

    Sharad Damodar Gore

    2009-10-01

    Full Text Available Statistical literature has several methods for coping with multicollinearity. This paper introduces a new shrinkage estimator, called modified unbiased ridge (MUR. This estimator is obtained from unbiased ridge regression (URR in the same way that ordinary ridge regression (ORR is obtained from ordinary least squares (OLS. Properties of MUR are derived. Results on its matrix mean squared error (MMSE are obtained. MUR is compared with ORR and URR in terms of MMSE. These results are illustrated with an example based on data generated by Hoerl and Kennard (1975.

  6. 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.

  7. Discriminative Elastic-Net Regularized Linear Regression.

    Science.gov (United States)

    Zhang, Zheng; Lai, Zhihui; Xu, Yong; Shao, Ling; Wu, Jian; Xie, Guo-Sen

    2017-03-01

    In this paper, we aim at learning compact and discriminative linear regression models. Linear regression has been widely used in different problems. However, most of the existing linear regression methods exploit the conventional zero-one matrix as the regression targets, which greatly narrows the flexibility of the regression model. Another major limitation of these methods is that the learned projection matrix fails to precisely project the image features to the target space due to their weak discriminative capability. To this end, we present an elastic-net regularized linear regression (ENLR) framework, and develop two robust linear regression models which possess the following special characteristics. First, our methods exploit two particular strategies to enlarge the margins of different classes by relaxing the strict binary targets into a more feasible variable matrix. Second, a robust elastic-net regularization of singular values is introduced to enhance the compactness and effectiveness of the learned projection matrix. Third, the resulting optimization problem of ENLR has a closed-form solution in each iteration, which can be solved efficiently. Finally, rather than directly exploiting the projection matrix for recognition, our methods employ the transformed features as the new discriminate representations to make final image classification. Compared with the traditional linear regression model and some of its variants, our method is much more accurate in image classification. Extensive experiments conducted on publicly available data sets well demonstrate that the proposed framework can outperform the state-of-the-art methods. The MATLAB codes of our methods can be available at http://www.yongxu.org/lunwen.html.

  8. STS-98 U.S. Lab Destiny is moved out of Atlantis' payload bay

    Science.gov (United States)

    2001-01-01

    KENNEDY SPACE CENTER, Fla. -- Workers in the Payload Changeout Room check the U.S. Lab Destiny as its moves from Atlantis''' payload bay into the PCR. Destiny will remain in the PCR while Atlantis rolls back to the Vehicle Assembly Building to allow workers to conduct inspections, continuity checks and X-ray analysis on the 36 solid rocket booster cables located inside each booster'''s system tunnel. An extensive evaluation of NASA'''s SRB cable inventory revealed conductor damage in four (of about 200) cables on the shelf. Shuttle managers decided to prove the integrity of the system tunnel cables already on Atlantis.

  9. Integration process and logistics results

    International Nuclear Information System (INIS)

    2004-01-01

    The Procurement and Logistics functions have gone through a process of integration since the beginning of integrated management of Asco and Vandellos II up to the present. These are functions that are likely to be designed for delivering a single product to the rest of the organization, defined from a high level of expectations, and that admit simplifications and materialization of synergy's as they are approached from an integrated perspective. The analyzed functions are as follows: Service and Material Purchasing, Warehouse and Material Management, and Documentation and General Services Management. In all case, to accomplish the integration, objectives, procedures and information systems were unified. As for the organization, a decision was made in each case on whether or not to out source. The decisive corporate strategy to integrate, resulting in actions such as moving corporate headquarters to Vandellos II, corporate consolidation, regulation of employment and implementation of the ENDESA Group Economic Information System (SIE) , has shaped this process, which at present can be considered as practically complete. (Author)

  10. Ten years integrated care for mental disorders in the Netherlands

    Directory of Open Access Journals (Sweden)

    Christina M van der Feltz-Cornelis

    2011-03-01

    Full Text Available Background and problem statement: Integrated care for mental disorders aims to encompass forms of collaboration between different health care settings for the treatment of mental disorders. To this end, it requires integration at several levels, i.e. integration of psychiatry in medicine, of the psychiatric discourse in the medical discourse; of localization of mental health care and general health care facilities; and of reimbursement systems.   Description of policy practice: Steps have been taken in the last decade to meet these requirements, enabling psychiatry to move on towards integrated treatment of mental disorder as such, by development of a collaborative care model that includes structural psychiatric consultation that was found to be applicable and effective in several Dutch health care settings. This collaborative care model is a feasible and effective model for integrated care in several health care settings. The Bio Psycho Social System has been developed as a feasible instrument for assessment in integrated care as well. Discussion: The discipline of Psychiatry has moved from anti-psychiatry in the last century, towards an emancipated medical discipline. This enabled big advances towards integrated care for mental disorder, in collaboration with other medical disciplines, in the last decade. Conclusion: Now is the time to further expand this concept of care towards other mental disorders, and towards integrated care for medical and mental co-morbidity. Integrated care for mental disorder should be readily available to the patient, according to his/her preference, taking somatic co-morbidity into account, and with a focus on rehabilitation of the patient in his or her social roles.

  11. Ten years integrated care for mental disorders in the Netherlands

    Directory of Open Access Journals (Sweden)

    Christina M van der Feltz-Cornelis

    2011-03-01

    Full Text Available Background and problem statement: Integrated care for mental disorders aims to encompass forms of collaboration between different health care settings for the treatment of mental disorders. To this end, it requires integration at several levels, i.e. integration of psychiatry in medicine, of the psychiatric discourse in the medical discourse; of localization of mental health care and general health care facilities; and of reimbursement systems.  Description of policy practice: Steps have been taken in the last decade to meet these requirements, enabling psychiatry to move on towards integrated treatment of mental disorder as such, by development of a collaborative care model that includes structural psychiatric consultation that was found to be applicable and effective in several Dutch health care settings. This collaborative care model is a feasible and effective model for integrated care in several health care settings. The Bio Psycho Social System has been developed as a feasible instrument for assessment in integrated care as well.Discussion: The discipline of Psychiatry has moved from anti-psychiatry in the last century, towards an emancipated medical discipline. This enabled big advances towards integrated care for mental disorder, in collaboration with other medical disciplines, in the last decade.Conclusion: Now is the time to further expand this concept of care towards other mental disorders, and towards integrated care for medical and mental co-morbidity. Integrated care for mental disorder should be readily available to the patient, according to his/her preference, taking somatic co-morbidity into account, and with a focus on rehabilitation of the patient in his or her social roles.

  12. Analyzing inflation in Nigeria: a fractionally integrated ARFIMA ...

    African Journals Online (AJOL)

    The study looked into the stochastic properties of CPI-inflation rate for Nigeria from 1995Q1 to 2016Q4. The study employed an autoregressive fractionally integrated moving average and a general autoregressive conditional heteroskedasticity (ARFIMA-GARCH) methodology as well as ADF/KPSS to investigate the ...

  13. Adaptive Counseling and Therapy: An Integrative, Eclectic Model.

    Science.gov (United States)

    Howard, George S.; And Others

    1986-01-01

    Presents an integrative model, Adaptive Counseling and Therapy (ACT), for selecting a progression of therapist styles as clients move through developmental stages during the course of counseling and psychotherapy. ACT is intended to be useful to practitioners in case conceptualization and in the application of effective treatment planning.…

  14. 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.

  15. Integrating climate change adaptation into Dutch local policies and the role of contextual factors.

    NARCIS (Netherlands)

    van den Berg, Maya Marieke; Coenen, Franciscus H.J.M.

    2012-01-01

    Moving towards a more sustainable adaptation process requires closer integration of policies related to the environment. An important actor in this is the local government. This paper examines to what extend adaptation is currently being integrated into Dutch local policies, and what the role is of

  16. 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....

  17. Categorical regression dose-response modeling

    Science.gov (United States)

    The goal of this training is to provide participants with training on the use of the U.S. EPA’s Categorical Regression soft¬ware (CatReg) and its application to risk assessment. Categorical regression fits mathematical models to toxicity data that have been assigned ord...

  18. 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.

  19. Multiple Regression Analysis of Unconfined Compression Strength of Mine Tailings Matrices

    Directory of Open Access Journals (Sweden)

    Mahmood Ali A.

    2017-01-01

    Full Text Available As part of a novel approach of sustainable development of mine tailings, experimental and numerical analysis is carried out on newly formulated tailings matrices. Several physical characteristic tests are carried out including the unconfined compression strength test to ascertain the integrity of these matrices when subjected to loading. The current paper attempts a multiple regression analysis of the unconfined compressive strength test results of these matrices to investigate the most pertinent factors affecting their strength. Results of this analysis showed that the suggested equation is reasonably applicable to the range of binder combinations used.

  20. 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…

  1. Comparison of Classical Linear Regression and Orthogonal Regression According to the Sum of Squares Perpendicular Distances

    OpenAIRE

    KELEŞ, Taliha; ALTUN, Murat

    2016-01-01

    Regression analysis is a statistical technique for investigating and modeling the relationship between variables. The purpose of this study was the trivial presentation of the equation for orthogonal regression (OR) and the comparison of classical linear regression (CLR) and OR techniques with respect to the sum of squared perpendicular distances. For that purpose, the analyses were shown by an example. It was found that the sum of squared perpendicular distances of OR is smaller. Thus, it wa...

  2. 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)

  3. Move to learn: Integrating spatial information from multiple viewpoints.

    Science.gov (United States)

    Holmes, Corinne A; Newcombe, Nora S; Shipley, Thomas F

    2018-05-11

    Recalling a spatial layout from multiple orientations - spatial flexibility - is challenging, even when the global configuration can be viewed from a single vantage point, but more so when it must be viewed piecemeal. In the current study, we examined whether experiencing the transition between multiple viewpoints enhances spatial memory and flexible recall for a spatial configuration viewed simultaneously (Exp. 1) and sequentially (Exp. 2), whether the type of transition matters, and whether action provides an additional advantage over passive experience. In Experiment 1, participants viewed an array of dollhouse furniture from four viewpoints, but with all furniture simultaneously visible. In Experiment 2, participants viewed the same array piecemeal, from four partitioned viewpoints that allowed for viewing only a segment at a time. The transition between viewpoints involved rotation of the array or participant movement around it. Rotation and participant movement were passively experienced or actively generated. The control condition presented the dollhouse as a series of static views. Across both experiments, participant movement significantly enhanced spatial memory relative to array rotation or static views. However, in Exp. 2, there was a further advantage for actively walking around the array compared to being passively pushed. These findings suggest that movement around a stable environment is key to spatial memory and flexible recall, with action providing an additional boost to the integration of temporally segmented spatial events. Thus, spatial memory may be more flexible than prior data indicate, when studied under more natural acquisition conditions. Copyright © 2018 Elsevier B.V. All rights reserved.

  4. Pathological assessment of liver fibrosis regression

    Directory of Open Access Journals (Sweden)

    WANG Bingqiong

    2017-03-01

    Full Text Available Hepatic fibrosis is the common pathological outcome of chronic hepatic diseases. An accurate assessment of fibrosis degree provides an important reference for a definite diagnosis of diseases, treatment decision-making, treatment outcome monitoring, and prognostic evaluation. At present, many clinical studies have proven that regression of hepatic fibrosis and early-stage liver cirrhosis can be achieved by effective treatment, and a correct evaluation of fibrosis regression has become a hot topic in clinical research. Liver biopsy has long been regarded as the gold standard for the assessment of hepatic fibrosis, and thus it plays an important role in the evaluation of fibrosis regression. This article reviews the clinical application of current pathological staging systems in the evaluation of fibrosis regression from the perspectives of semi-quantitative scoring system, quantitative approach, and qualitative approach, in order to propose a better pathological evaluation system for the assessment of fibrosis regression.

  5. Onwards and upwards: the evolution of integrated UAV solutions

    Directory of Open Access Journals (Sweden)

    Jean-Christophe Zufferey

    2017-12-01

    Tools need to be integrated, complete solutions, marking a move away from users seeing drones in isolation. Throughout 2018, this investment in end-to-end is set to address businesses’ key operational challenges, deliver a strong return-on-investment and streamline adherence to emerging regulations.

  6. 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.

  7. 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...

  8. Logistic Regression: Concept and Application

    Science.gov (United States)

    Cokluk, Omay

    2010-01-01

    The main focus of logistic regression analysis is classification of individuals in different groups. The aim of the present study is to explain basic concepts and processes of binary logistic regression analysis intended to determine the combination of independent variables which best explain the membership in certain groups called dichotomous…

  9. The influence of walkability on broader mobility for Canadian middle aged and older adults: An examination of Walk Score™ and the Mobility Over Varied Environments Scale (MOVES).

    Science.gov (United States)

    Hirsch, Jana A; Winters, Meghan; Clarke, Philippa J; Ste-Marie, Nathalie; McKay, Heather A

    2017-02-01

    Neighborhood built environments may play an important role in shaping mobility and subsequent health outcomes. However, little work includes broader mobility considerations such as cognitive ability to be mobile, social connections with community, or transportation choices. We used a population-based sample of Canadian middle aged and older adults (aged 45 and older) from the Canadian Community Health Survey-Healthy Aging (CCHS-HA, 2008-2009) to create a holistic mobility measure: Mobility over Varied Environments Scale (MOVES). Data from CCHS-HA respondents from British Columbia with MOVES were linked with Street Smart Walk Score™ data by postal code (n=2046). Mean MOVES was estimated across sociodemographic and health characteristics. Linear regression, adjusted for relevant covariates, was used to estimate the association between Street Smart Walk Score™ and the MOVES. The mean MOVES was 30.67 (95% confidence interval (CI) 30.36, 30.99), 5th percentile 23.27 (CI 22.16, 24.38) and 95th percentile was 36.93 (CI 35.98, 37.87). MOVES was higher for those who were younger, married, higher socioeconomic status, and had better health. In unadjusted models, for every 10 point increase in Street Smart Walk Score™, MOVES increased 4.84 points (CI 4.52, 5.15). However, results attenuated after adjustment for sociodemographic covariates: each 10 point increase in Street Smart Walk Score™ was associated with a 0.10 (CI 0.00, 0.20) point increase in MOVES. The modest but important link we observed between walkability and mobility highlights the implication of neighborhood design on the health of middle aged and older adults. Copyright © 2016 Elsevier Inc. All rights reserved.

  10. Predictors of course in obsessive-compulsive disorder: logistic regression versus Cox regression for recurrent events.

    Science.gov (United States)

    Kempe, P T; van Oppen, P; de Haan, E; Twisk, J W R; Sluis, A; Smit, J H; van Dyck, R; van Balkom, A J L M

    2007-09-01

    Two methods for predicting remissions in obsessive-compulsive disorder (OCD) treatment are evaluated. Y-BOCS measurements of 88 patients with a primary OCD (DSM-III-R) diagnosis were performed over a 16-week treatment period, and during three follow-ups. Remission at any measurement was defined as a Y-BOCS score lower than thirteen combined with a reduction of seven points when compared with baseline. Logistic regression models were compared with a Cox regression for recurrent events model. Logistic regression yielded different models at different evaluation times. The recurrent events model remained stable when fewer measurements were used. Higher baseline levels of neuroticism and more severe OCD symptoms were associated with a lower chance of remission, early age of onset and more depressive symptoms with a higher chance. Choice of outcome time affects logistic regression prediction models. Recurrent events analysis uses all information on remissions and relapses. Short- and long-term predictors for OCD remission show overlap.

  11. CPICOR{trademark}: Clean power from integrated coal-ore reduction

    Energy Technology Data Exchange (ETDEWEB)

    Wintrell, R.; Miller, R.N.; Harbison, E.J.; LeFevre, M.O.; England, K.S.

    1997-12-31

    The US steel industry, in order to maintain its basic iron production, is thus moving to lower coke requirements and to the cokeless or direct production of iron. The US Department of Energy (DOE), in its Clean Coal Technology programs, has encouraged the move to new coal-based technology. The steel industry, in its search for alternative direct iron processes, has been limited to a single process, COREX{reg_sign}. The COREX{reg_sign} process, though offering commercial and environmental acceptance, produces a copious volume of offgas which must be effectively utilized to ensure an economical process. This volume, which normally exceeds the internal needs of a single steel company, offers a highly acceptable fuel for power generation. The utility companies seeking to offset future natural gas cost increases are interested in this clean fuel. The COREX{reg_sign} smelting process, when integrated with a combined cycle power generation facility (CCPG) and a cryogenic air separation unit (ASU), is an outstanding example of a new generation of environmentally compatible and highly energy efficient Clean Coal Technologies. This combination of highly integrated electric power and hot metal coproduction, has been designated CPICOR{trademark}, Clean Power from Integrated Coal/Ore Reduction.

  12. Sparse reduced-rank regression with covariance estimation

    KAUST Repository

    Chen, Lisha

    2014-12-08

    Improving the predicting performance of the multiple response regression compared with separate linear regressions is a challenging question. On the one hand, it is desirable to seek model parsimony when facing a large number of parameters. On the other hand, for certain applications it is necessary to take into account the general covariance structure for the errors of the regression model. We assume a reduced-rank regression model and work with the likelihood function with general error covariance to achieve both objectives. In addition we propose to select relevant variables for reduced-rank regression by using a sparsity-inducing penalty, and to estimate the error covariance matrix simultaneously by using a similar penalty on the precision matrix. We develop a numerical algorithm to solve the penalized regression problem. In a simulation study and real data analysis, the new method is compared with two recent methods for multivariate regression and exhibits competitive performance in prediction and variable selection.

  13. Sparse reduced-rank regression with covariance estimation

    KAUST Repository

    Chen, Lisha; Huang, Jianhua Z.

    2014-01-01

    Improving the predicting performance of the multiple response regression compared with separate linear regressions is a challenging question. On the one hand, it is desirable to seek model parsimony when facing a large number of parameters. On the other hand, for certain applications it is necessary to take into account the general covariance structure for the errors of the regression model. We assume a reduced-rank regression model and work with the likelihood function with general error covariance to achieve both objectives. In addition we propose to select relevant variables for reduced-rank regression by using a sparsity-inducing penalty, and to estimate the error covariance matrix simultaneously by using a similar penalty on the precision matrix. We develop a numerical algorithm to solve the penalized regression problem. In a simulation study and real data analysis, the new method is compared with two recent methods for multivariate regression and exhibits competitive performance in prediction and variable selection.

  14. 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…

  15. 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...

  16. 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…

  17. Short-term solar irradiation forecasting based on Dynamic Harmonic Regression

    International Nuclear Information System (INIS)

    Trapero, Juan R.; Kourentzes, Nikolaos; Martin, A.

    2015-01-01

    Solar power generation is a crucial research area for countries that have high dependency on fossil energy sources and is gaining prominence with the current shift to renewable sources of energy. In order to integrate the electricity generated by solar energy into the grid, solar irradiation must be reasonably well forecasted, where deviations of the forecasted value from the actual measured value involve significant costs. The present paper proposes a univariate Dynamic Harmonic Regression model set up in a State Space framework for short-term (1–24 h) solar irradiation forecasting. Time series hourly aggregated as the Global Horizontal Irradiation and the Direct Normal Irradiation will be used to illustrate the proposed approach. This method provides a fast automatic identification and estimation procedure based on the frequency domain. Furthermore, the recursive algorithms applied offer adaptive predictions. The good forecasting performance is illustrated with solar irradiance measurements collected from ground-based weather stations located in Spain. The results show that the Dynamic Harmonic Regression achieves the lowest relative Root Mean Squared Error; about 30% and 47% for the Global and Direct irradiation components, respectively, for a forecast horizon of 24 h ahead. - Highlights: • Solar irradiation forecasts at short-term are required to operate solar power plants. • This paper assesses the Dynamic Harmonic Regression to forecast solar irradiation. • Models are evaluated using hourly GHI and DNI data collected in Spain. • The results show that forecasting accuracy is improved by using the model proposed

  18. 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.

  19. 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.

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

    Science.gov (United States)

    Braden, Jeffery P.; And Others

    1990-01-01

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

  1. Regression models of reactor diagnostic signals

    International Nuclear Information System (INIS)

    Vavrin, J.

    1989-01-01

    The application is described of an autoregression model as the simplest regression model of diagnostic signals in experimental analysis of diagnostic systems, in in-service monitoring of normal and anomalous conditions and their diagnostics. The method of diagnostics is described using a regression type diagnostic data base and regression spectral diagnostics. The diagnostics is described of neutron noise signals from anomalous modes in the experimental fuel assembly of a reactor. (author)

  2. 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?

  3. 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.

  4. Humane Letters: Notes on the Concept of Integrity and the Meanings of Humanism

    Science.gov (United States)

    Higgins, Chris

    2009-01-01

    In this article, the author calls for an analysis of integrity and contends that attempting to describe wholeness precisely and incisively is not necessarily a contradiction in terms. The author makes some distinctions about integrity using two moves, one inspired by Plato, and one by Aristotle. The author uses the phrase "humane letters" to name…

  5. 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...

  6. Regression and Sparse Regression Methods for Viscosity Estimation of Acid Milk From it’s Sls Features

    DEFF Research Database (Denmark)

    Sharifzadeh, Sara; Skytte, Jacob Lercke; Nielsen, Otto Højager Attermann

    2012-01-01

    Statistical solutions find wide spread use in food and medicine quality control. We investigate the effect of different regression and sparse regression methods for a viscosity estimation problem using the spectro-temporal features from new Sub-Surface Laser Scattering (SLS) vision system. From...... with sparse LAR, lasso and Elastic Net (EN) sparse regression methods. Due to the inconsistent measurement condition, Locally Weighted Scatter plot Smoothing (Loess) has been employed to alleviate the undesired variation in the estimated viscosity. The experimental results of applying different methods show...

  7. Testing discontinuities in nonparametric regression

    KAUST Repository

    Dai, Wenlin

    2017-01-19

    In nonparametric regression, it is often needed to detect whether there are jump discontinuities in the mean function. In this paper, we revisit the difference-based method in [13 H.-G. Müller and U. Stadtmüller, Discontinuous versus smooth regression, Ann. Stat. 27 (1999), pp. 299–337. doi: 10.1214/aos/1018031100

  8. Testing discontinuities in nonparametric regression

    KAUST Repository

    Dai, Wenlin; Zhou, Yuejin; Tong, Tiejun

    2017-01-01

    In nonparametric regression, it is often needed to detect whether there are jump discontinuities in the mean function. In this paper, we revisit the difference-based method in [13 H.-G. Müller and U. Stadtmüller, Discontinuous versus smooth regression, Ann. Stat. 27 (1999), pp. 299–337. doi: 10.1214/aos/1018031100

  9. On pure spinor formalism for quantum superstring and spinor moving frame

    International Nuclear Information System (INIS)

    Bandos, Igor A

    2013-01-01

    The D = 10 pure spinor constraint can be solved in terms of spinor moving frame variables v -α q and eight-component complex null vector Λ + q , Λ + q Λ + q =0, which can be related to the κ-symmetry ghost. Using this and similar solutions for the conjugate pure spinor and other elements of the non-minimal pure spinor formalism, we present a (hopefully useful) reformulation of the measure of the pure spinor path integral for superstring in terms of products of Cartan forms corresponding to the coset of 10D Lorentz group and to the coset of complex orthogonal group SO(8, C). Our study suggests a possible complete reformulation of the pure spinor superstring in terms of new irreducible set of variable. (paper)

  10. 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

  11. On Solving Lq-Penalized Regressions

    Directory of Open Access Journals (Sweden)

    Tracy Zhou Wu

    2007-01-01

    Full Text Available Lq-penalized regression arises in multidimensional statistical modelling where all or part of the regression coefficients are penalized to achieve both accuracy and parsimony of statistical models. There is often substantial computational difficulty except for the quadratic penalty case. The difficulty is partly due to the nonsmoothness of the objective function inherited from the use of the absolute value. We propose a new solution method for the general Lq-penalized regression problem based on space transformation and thus efficient optimization algorithms. The new method has immediate applications in statistics, notably in penalized spline smoothing problems. In particular, the LASSO problem is shown to be polynomial time solvable. Numerical studies show promise of our approach.

  12. 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.

  13. Integrating Planning, Assessment, and Improvement in Higher Education

    Science.gov (United States)

    Sherlock, Barbara J.

    2009-01-01

    Based on Penn State's popular "Innovation Insights" series, this book brings together in one handy reference nearly a decade of tried and true insights into continuous quality improvements in higher education. Their five-step model for integrating planning, assessment, and improvement moves plans off the shelf and into the weekly and daily…

  14. Integrated engineering increases flexibility

    International Nuclear Information System (INIS)

    Smith, Ray

    1991-01-01

    Integrated Engineering (IE) can be used to describe the best use of increasingly rare good engineering talent in an increasingly competive world. A number of organisations are now moving towards IE without any general agreement on a precise definition. The engineering division of British Nuclear Fuels (BNFL) is one such organisation. This feature covers the reasoning behind the decision, and our experience to date. BNFL engineering division is responsible primarily for the provision of major facilities on BNFL operational sites. This provision includes feasibility, front end and detailed design, procurement, installation and commissioning. Task force working has been used for some of the large projects. But the future workload is expected to comprise many more smaller projects. At the same time, equipment is becoming more complex and the need for mutual understanding and appreciation between disciplines is increasing. To meet this increasing need for flexibility, BNFL has decided to move to the matrix structure of project management and functional departments described in the article. (Author)

  15. ATLAS Solenoid Integration

    CERN Multimedia

    Ruber, R

    Last month the central solenoid was installed in the barrel cryostat, which it shares with the liquid argon calorimeter. Some two years ago the central solenoid arrived at CERN after being manufactured and tested in Japan. It was kept in storage until last October when it was finally moved to the barrel cryostat integration area. Here a position survey of the solenoid (with respect to the cryostat's inner warm vessel) was performed. At the start of the New Year the solenoid was moved to the cryostat insertion stand. After a test insertion on 6th February and a few weeks of preparation work it was finally inserted on 27th February. A couple of hectic 24-hours/7-day weeks followed in order to connect all services in the cryostat bulkhead. But last Monday, 15th March, both warm flanges of the cryostat could be closed. In another week's time we expect to finish the connection of the cryogenic cooling lines and the superconducting bus lines with the external services. Then the cool-down and test will commence... ...

  16. Boosted regression trees, multivariate adaptive regression splines and their two-step combinations with multiple linear regression or partial least squares to predict blood-brain barrier passage: a case study.

    Science.gov (United States)

    Deconinck, E; Zhang, M H; Petitet, F; Dubus, E; Ijjaali, I; Coomans, D; Vander Heyden, Y

    2008-02-18

    The use of some unconventional non-linear modeling techniques, i.e. classification and regression trees and multivariate adaptive regression splines-based methods, was explored to model the blood-brain barrier (BBB) passage of drugs and drug-like molecules. The data set contains BBB passage values for 299 structural and pharmacological diverse drugs, originating from a structured knowledge-based database. Models were built using boosted regression trees (BRT) and multivariate adaptive regression splines (MARS), as well as their respective combinations with stepwise multiple linear regression (MLR) and partial least squares (PLS) regression in two-step approaches. The best models were obtained using combinations of MARS with either stepwise MLR or PLS. It could be concluded that the use of combinations of a linear with a non-linear modeling technique results in some improved properties compared to the individual linear and non-linear models and that, when the use of such a combination is appropriate, combinations using MARS as non-linear technique should be preferred over those with BRT, due to some serious drawbacks of the BRT approaches.

  17. Testing Heteroscedasticity in Robust Regression

    Czech Academy of Sciences Publication Activity Database

    Kalina, Jan

    2011-01-01

    Roč. 1, č. 4 (2011), s. 25-28 ISSN 2045-3345 Grant - others:GA ČR(CZ) GA402/09/0557 Institutional research plan: CEZ:AV0Z10300504 Keywords : robust regression * heteroscedasticity * regression quantiles * diagnostics Subject RIV: BB - Applied Statistics , Operational Research http://www.researchjournals.co.uk/documents/Vol4/06%20Kalina.pdf

  18. Iterative integral parameter identification of a respiratory mechanics model

    Directory of Open Access Journals (Sweden)

    Schranz Christoph

    2012-07-01

    Full Text Available Abstract Background Patient-specific respiratory mechanics models can support the evaluation of optimal lung protective ventilator settings during ventilation therapy. Clinical application requires that the individual’s model parameter values must be identified with information available at the bedside. Multiple linear regression or gradient-based parameter identification methods are highly sensitive to noise and initial parameter estimates. Thus, they are difficult to apply at the bedside to support therapeutic decisions. Methods An iterative integral parameter identification method is applied to a second order respiratory mechanics model. The method is compared to the commonly used regression methods and error-mapping approaches using simulated and clinical data. The clinical potential of the method was evaluated on data from 13 Acute Respiratory Distress Syndrome (ARDS patients. Results The iterative integral method converged to error minima 350 times faster than the Simplex Search Method using simulation data sets and 50 times faster using clinical data sets. Established regression methods reported erroneous results due to sensitivity to noise. In contrast, the iterative integral method was effective independent of initial parameter estimations, and converged successfully in each case tested. Conclusion These investigations reveal that the iterative integral method is beneficial with respect to computing time, operator independence and robustness, and thus applicable at the bedside for this clinical application.

  19. Spontaneous regression of a congenital melanocytic nevus

    Directory of Open Access Journals (Sweden)

    Amiya Kumar Nath

    2011-01-01

    Full Text Available Congenital melanocytic nevus (CMN may rarely regress which may also be associated with a halo or vitiligo. We describe a 10-year-old girl who presented with CMN on the left leg since birth, which recently started to regress spontaneously with associated depigmentation in the lesion and at a distant site. Dermoscopy performed at different sites of the regressing lesion demonstrated loss of epidermal pigments first followed by loss of dermal pigments. Histopathology and Masson-Fontana stain demonstrated lymphocytic infiltration and loss of pigment production in the regressing area. Immunohistochemistry staining (S100 and HMB-45, however, showed that nevus cells were present in the regressing areas.

  20. Wind Power Ramp Events Prediction with Hybrid Machine Learning Regression Techniques and Reanalysis Data

    Directory of Open Access Journals (Sweden)

    Laura Cornejo-Bueno

    2017-11-01

    Full Text Available Wind Power Ramp Events (WPREs are large fluctuations of wind power in a short time interval, which lead to strong, undesirable variations in the electric power produced by a wind farm. Its accurate prediction is important in the effort of efficiently integrating wind energy in the electric system, without affecting considerably its stability, robustness and resilience. In this paper, we tackle the problem of predicting WPREs by applying Machine Learning (ML regression techniques. Our approach consists of using variables from atmospheric reanalysis data as predictive inputs for the learning machine, which opens the possibility of hybridizing numerical-physical weather models with ML techniques for WPREs prediction in real systems. Specifically, we have explored the feasibility of a number of state-of-the-art ML regression techniques, such as support vector regression, artificial neural networks (multi-layer perceptrons and extreme learning machines and Gaussian processes to solve the problem. Furthermore, the ERA-Interim reanalysis from the European Center for Medium-Range Weather Forecasts is the one used in this paper because of its accuracy and high resolution (in both spatial and temporal domains. Aiming at validating the feasibility of our predicting approach, we have carried out an extensive experimental work using real data from three wind farms in Spain, discussing the performance of the different ML regression tested in this wind power ramp event prediction problem.

  1. 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.

  2. Let’s move our health! The experience of 40 physical activity motivational workshops

    Science.gov (United States)

    Bouté, Catherine; Cailliez, Elisabeth; D Hour, Alain; Goxe, Didier; Gusto, Gaëlle; Copin, Nane; Lantieri, Olivier

    2016-10-19

    Aims: To set up physical activity promotion workshops in health centres to help people with a sedentary lifestyle achieve an adequate level of physical activity. Methods: This health programme, called ‘Bougeons Notre Santé’ (Let’s move our health) has been implemented since 2006 by four health centres in the Pays de la Loire region, in France. This article describes implementation of the programme, its feasibility, how it can be integrated into a global preventive approach and its outcomes on promoting more physical activity. The “Let’s move our health!” programme comprises four group meetings with participants over a period of several months. At these meetings, participants discuss, exchange and monitor their qualitative and quantitative level of physical activity. Realistic and achievable goals are set in consultation with each participant in relation to their personal circumstances and are monitored with a pedometer and a follow-up diary. Support on healthy eating is also provided. This programme is an opportunity to promote health and refer participants to existing local resources. Results: Forty groups, comprising a total of 275 people, have participated in the programme since 2006. After the four meetings, participants had increased their physical activity level by an average of 723 steps per day and 85% reported that they had changed their eating habits. Conclusion: This health promotion programme is feasible and effective: an increase in the physical activity of participants was observed, together with a favourable impact on perceived health, well-being and social links. These workshops are integrated into a network of associations and institutional partners and could be implemented by similar social or health organisations.

  3. 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.

  4. 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.

  5. 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.

  6. Estimation of Fine Particulate Matter in Taipei Using Landuse Regression and Bayesian Maximum Entropy Methods

    Directory of Open Access Journals (Sweden)

    Yi-Ming Kuo

    2011-06-01

    Full Text Available Fine airborne particulate matter (PM2.5 has adverse effects on human health. Assessing the long-term effects of PM2.5 exposure on human health and ecology is often limited by a lack of reliable PM2.5 measurements. In Taipei, PM2.5 levels were not systematically measured until August, 2005. Due to the popularity of geographic information systems (GIS, the landuse regression method has been widely used in the spatial estimation of PM concentrations. This method accounts for the potential contributing factors of the local environment, such as traffic volume. Geostatistical methods, on other hand, account for the spatiotemporal dependence among the observations of ambient pollutants. This study assesses the performance of the landuse regression model for the spatiotemporal estimation of PM2.5 in the Taipei area. Specifically, this study integrates the landuse regression model with the geostatistical approach within the framework of the Bayesian maximum entropy (BME method. The resulting epistemic framework can assimilate knowledge bases including: (a empirical-based spatial trends of PM concentration based on landuse regression, (b the spatio-temporal dependence among PM observation information, and (c site-specific PM observations. The proposed approach performs the spatiotemporal estimation of PM2.5 levels in the Taipei area (Taiwan from 2005–2007.

  7. Estimation of fine particulate matter in Taipei using landuse regression and bayesian maximum entropy methods.

    Science.gov (United States)

    Yu, Hwa-Lung; Wang, Chih-Hsih; Liu, Ming-Che; Kuo, Yi-Ming

    2011-06-01

    Fine airborne particulate matter (PM2.5) has adverse effects on human health. Assessing the long-term effects of PM2.5 exposure on human health and ecology is often limited by a lack of reliable PM2.5 measurements. In Taipei, PM2.5 levels were not systematically measured until August, 2005. Due to the popularity of geographic information systems (GIS), the landuse regression method has been widely used in the spatial estimation of PM concentrations. This method accounts for the potential contributing factors of the local environment, such as traffic volume. Geostatistical methods, on other hand, account for the spatiotemporal dependence among the observations of ambient pollutants. This study assesses the performance of the landuse regression model for the spatiotemporal estimation of PM2.5 in the Taipei area. Specifically, this study integrates the landuse regression model with the geostatistical approach within the framework of the Bayesian maximum entropy (BME) method. The resulting epistemic framework can assimilate knowledge bases including: (a) empirical-based spatial trends of PM concentration based on landuse regression, (b) the spatio-temporal dependence among PM observation information, and (c) site-specific PM observations. The proposed approach performs the spatiotemporal estimation of PM2.5 levels in the Taipei area (Taiwan) from 2005-2007.

  8. 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…

  9. 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…

  10. 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

  11. Regression Analysis by Example. 5th Edition

    Science.gov (United States)

    Chatterjee, Samprit; Hadi, Ali S.

    2012-01-01

    Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. "Regression Analysis by Example, Fifth Edition" has been expanded and thoroughly…

  12. Gaussian process regression analysis for functional data

    CERN Document Server

    Shi, Jian Qing

    2011-01-01

    Gaussian Process Regression Analysis for Functional Data presents nonparametric statistical methods for functional regression analysis, specifically the methods based on a Gaussian process prior in a functional space. The authors focus on problems involving functional response variables and mixed covariates of functional and scalar variables.Covering the basics of Gaussian process regression, the first several chapters discuss functional data analysis, theoretical aspects based on the asymptotic properties of Gaussian process regression models, and new methodological developments for high dime

  13. Is past life regression therapy ethical?

    Science.gov (United States)

    Andrade, Gabriel

    2017-01-01

    Past life regression therapy is used by some physicians in cases with some mental diseases. Anxiety disorders, mood disorders, and gender dysphoria have all been treated using life regression therapy by some doctors on the assumption that they reflect problems in past lives. Although it is not supported by psychiatric associations, few medical associations have actually condemned it as unethical. In this article, I argue that past life regression therapy is unethical for two basic reasons. First, it is not evidence-based. Past life regression is based on the reincarnation hypothesis, but this hypothesis is not supported by evidence, and in fact, it faces some insurmountable conceptual problems. If patients are not fully informed about these problems, they cannot provide an informed consent, and hence, the principle of autonomy is violated. Second, past life regression therapy has the great risk of implanting false memories in patients, and thus, causing significant harm. This is a violation of the principle of non-malfeasance, which is surely the most important principle in medical ethics.

  14. 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...

  15. Regression Models for Market-Shares

    DEFF Research Database (Denmark)

    Birch, Kristina; Olsen, Jørgen Kai; Tjur, Tue

    2005-01-01

    On the background of a data set of weekly sales and prices for three brands of coffee, this paper discusses various regression models and their relation to the multiplicative competitive-interaction model (the MCI model, see Cooper 1988, 1993) for market-shares. Emphasis is put on the interpretat......On the background of a data set of weekly sales and prices for three brands of coffee, this paper discusses various regression models and their relation to the multiplicative competitive-interaction model (the MCI model, see Cooper 1988, 1993) for market-shares. Emphasis is put...... on the interpretation of the parameters in relation to models for the total sales based on discrete choice models.Key words and phrases. MCI model, discrete choice model, market-shares, price elasitcity, regression model....

  16. Monthly reservoir inflow forecasting using a new hybrid SARIMA ...

    Indian Academy of Sciences (India)

    Seasonal autoregressive integrated moving average (SARIMA) models have been frequently ... studied the perfor- mance of stochastic models against ANN models in ..... the model parameters and Se is the standard error. 2.1.3 Nonlinear term ...... ison of regression, ARIMA and ANN models for reservoir inflow forecasting ...

  17. Numerical analysis for the stick-slip vibration of a transversely moving beam in contact with a frictional wall

    Science.gov (United States)

    Won, Hong-In; Chung, Jintai

    2018-04-01

    This paper presents a numerical analysis for the stick-slip vibration of a transversely moving beam, considering both stick-slip transition and friction force discontinuity. The dynamic state of the beam was separated into the stick state and the slip state, and boundary conditions were defined for both. By applying the finite element method, two matrix-vector equations were derived: one for stick state and the other for slip state. However, the equations have different degrees of freedom depending on whether the end of a beam sticks or slips, so we encountered difficulties in time integration. To overcome the difficulties, we proposed a new numerical technique to alternatively use the matrix-vector equations with different matrix sizes. In addition, to eliminate spurious high-frequency responses, we applied the generalized-α time integration method with appropriate value of high-frequency numerical dissipation. Finally, the dynamic responses of stick-slip vibration were analyzed in time and frequency domains: the dynamic behavior of the beam was explained to facilitate understanding of the stick-slip motion, and frequency characteristics of the stick-slip vibration were investigated in relation to the natural frequencies of the beam. The effects of the axial load and the moving speed upon the dynamic response were also examined.

  18. Final Report for Bio-Inspired Approaches to Moving-Target Defense Strategies

    Energy Technology Data Exchange (ETDEWEB)

    Fink, Glenn A.; Oehmen, Christopher S.

    2012-09-01

    This report records the work and contributions of the NITRD-funded Bio-Inspired Approaches to Moving-Target Defense Strategies project performed by Pacific Northwest National Laboratory under the technical guidance of the National Security Agency’s R6 division. The project has incorporated a number of bio-inspired cyber defensive technologies within an elastic framework provided by the Digital Ants. This project has created the first scalable, real-world prototype of the Digital Ants Framework (DAF)[11] and integrated five technologies into this flexible, decentralized framework: (1) Ant-Based Cyber Defense (ABCD), (2) Behavioral Indicators, (3) Bioinformatic Clas- sification, (4) Moving-Target Reconfiguration, and (5) Ambient Collaboration. The DAF can be used operationally to decentralize many such data intensive applications that normally rely on collection of large amounts of data in a central repository. In this work, we have shown how these component applications may be decentralized and may perform analysis at the edge. Operationally, this will enable analytics to scale far beyond current limitations while not suffering from the bandwidth or computational limitations of centralized analysis. This effort has advanced the R6 Cyber Security research program to secure digital infrastructures by developing a dynamic means to adaptively defend complex cyber systems. We hope that this work will benefit both our client’s efforts in system behavior modeling and cyber security to the overall benefit of the nation.

  19. Prediction of Tourist Arrivals to the Island of Bali with Holt Method of Winter and Seasonal Autoregressive Integrated Moving Average (SARIMA

    Directory of Open Access Journals (Sweden)

    Agus Supriatna

    2017-11-01

    Full Text Available The tourism sector is one of the contributors of foreign exchange is quite influential in improving the economy of Indonesia. The development of this sector will have a positive impact, including employment opportunities and opportunities for entrepreneurship in various industries such as adventure tourism, craft or hospitality. The beauty and natural resources owned by Indonesia become a tourist attraction for domestic and foreign tourists. One of the many tourist destination is the island of Bali. The island of Bali is not only famous for its natural, cultural diversity and arts but there are also add the value of tourism. In 2015 the increase in the number of tourist arrivals amounted to 6.24% from the previous year. In improving the quality of services, facing a surge of visitors, or prepare a strategy in attracting tourists need a prediction of arrival so that planning can be more efficient and effective. This research used  Holt Winter's method and Seasonal Autoregressive Integrated Moving Average (SARIMA method  to predict tourist arrivals. Based on data of foreign tourist arrivals who visited the Bali island in January 2007 until June 2016, the result of Holt Winter's method with parameter values α=0.1 ,β=0.1 ,γ=0.3 has an error MAPE is 6,171873. While the result of SARIMA method with (0,1,1〖(1,0,0〗12 model has an error MAPE is 5,788615 and it can be concluded that SARIMA method is better. Keywords: Foreign Tourist, Prediction, Bali Island, Holt-Winter’s, SARIMA.

  20. 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)

  1. 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.

  2. 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.

  3. New integrable PDEs of boomeronic type

    International Nuclear Information System (INIS)

    Calogero, F; Degasperis, A

    2006-01-01

    Novel integrable systems of coupled first-order autonomous PDEs in 1 + 1 dimensions (space x and time t) are presented. Integrable covariant 2-vector and 3-vector PDEs, as well as higher-order integrable PDEs for a single, or a couple, of scalar-dependent variables (including an extension of the sine-Gordon equation and a remarkably neat, highly nonlinear third-order PDE), are also obtained by appropriate reductions of the basic matrix equations. The Lax pairs that characterize the integrable character of the basic matrix PDEs are also exhibited, as well as their single-soliton solutions. These solitons generally exhibit the boomeronic (and, less generically, the trapponic) phenomenology, namely they do not move uniformly, but rather (in an appropriate reference system) come in from one end in the remote past and boomerang back to that same end in the remote future (boomerons), or are trapped to oscillate around a value fixed by the initial data (trappons)

  4. Detection of epistatic effects with logic regression and a classical linear regression model.

    Science.gov (United States)

    Malina, Magdalena; Ickstadt, Katja; Schwender, Holger; Posch, Martin; Bogdan, Małgorzata

    2014-02-01

    To locate multiple interacting quantitative trait loci (QTL) influencing a trait of interest within experimental populations, usually methods as the Cockerham's model are applied. Within this framework, interactions are understood as the part of the joined effect of several genes which cannot be explained as the sum of their additive effects. However, if a change in the phenotype (as disease) is caused by Boolean combinations of genotypes of several QTLs, this Cockerham's approach is often not capable to identify them properly. To detect such interactions more efficiently, we propose a logic regression framework. Even though with the logic regression approach a larger number of models has to be considered (requiring more stringent multiple testing correction) the efficient representation of higher order logic interactions in logic regression models leads to a significant increase of power to detect such interactions as compared to a Cockerham's approach. The increase in power is demonstrated analytically for a simple two-way interaction model and illustrated in more complex settings with simulation study and real data analysis.

  5. Wind Turbine Gearbox Condition Monitoring with AAKR and Moving Window Statistic Methods

    Directory of Open Access Journals (Sweden)

    Peng Guo

    2011-11-01

    Full Text Available Condition Monitoring (CM of wind turbines can greatly reduce the maintenance costs for wind farms, especially for offshore wind farms. A new condition monitoring method for a wind turbine gearbox using temperature trend analysis is proposed. Autoassociative Kernel Regression (AAKR is used to construct the normal behavior model of the gearbox temperature. With a proper construction of the memory matrix, the AAKR model can cover the normal working space for the gearbox. When the gearbox has an incipient failure, the residuals between AAKR model estimates and the measurement temperature will become significant. A moving window statistical method is used to detect the changes of the residual mean value and standard deviation in a timely manner. When one of these parameters exceeds predefined thresholds, an incipient failure is flagged. In order to simulate the gearbox fault, manual temperature drift is added to the initial Supervisory Control and Data Acquisitions (SCADA data. Analysis of simulated gearbox failures shows that the new condition monitoring method is effective.

  6. Youth Migration in Indonesia: Decision to Move and Choice of Destination Areas

    Directory of Open Access Journals (Sweden)

    Meirina Ayumi Malamassam

    2016-08-01

    Full Text Available Using intercensal population survey data, this paper examines migration behavior of youth in Indonesia aged 15 to 24 years old. Logistic regressions are employed to understand factors influencing youth’s decision to migrate as well as their choice of destination areas. The study findings suggest that migration preferences are determined by both the individual characteristics as well as the development level in both areas of origin and destination. It is also shown that education plays an important role in youth migration in Indonesia, not only in improving individual’s capacity to migrate, but also in prompting migration to big cities. In addition, youth migrants tend to move to areas with similar characteristics or similar cultural background to their areas of origin. For most of young people, migration is considered as an attempt for gaining upward social mobility, thus the prevalence of youth migration to less developed areas is low.

  7. Prediction of tissue-specific cis-regulatory modules using Bayesian networks and regression trees

    Directory of Open Access Journals (Sweden)

    Chen Xiaoyu

    2007-12-01

    Full Text Available Abstract Background In vertebrates, a large part of gene transcriptional regulation is operated by cis-regulatory modules. These modules are believed to be regulating much of the tissue-specificity of gene expression. Results We develop a Bayesian network approach for identifying cis-regulatory modules likely to regulate tissue-specific expression. The network integrates predicted transcription factor binding site information, transcription factor expression data, and target gene expression data. At its core is a regression tree modeling the effect of combinations of transcription factors bound to a module. A new unsupervised EM-like algorithm is developed to learn the parameters of the network, including the regression tree structure. Conclusion Our approach is shown to accurately identify known human liver and erythroid-specific modules. When applied to the prediction of tissue-specific modules in 10 different tissues, the network predicts a number of important transcription factor combinations whose concerted binding is associated to specific expression.

  8. Poisson Mixture Regression Models for Heart Disease Prediction.

    Science.gov (United States)

    Mufudza, Chipo; Erol, Hamza

    2016-01-01

    Early heart disease control can be achieved by high disease prediction and diagnosis efficiency. This paper focuses on the use of model based clustering techniques to predict and diagnose heart disease via Poisson mixture regression models. Analysis and application of Poisson mixture regression models is here addressed under two different classes: standard and concomitant variable mixture regression models. Results show that a two-component concomitant variable Poisson mixture regression model predicts heart disease better than both the standard Poisson mixture regression model and the ordinary general linear Poisson regression model due to its low Bayesian Information Criteria value. Furthermore, a Zero Inflated Poisson Mixture Regression model turned out to be the best model for heart prediction over all models as it both clusters individuals into high or low risk category and predicts rate to heart disease componentwise given clusters available. It is deduced that heart disease prediction can be effectively done by identifying the major risks componentwise using Poisson mixture regression model.

  9. Poisson Mixture Regression Models for Heart Disease Prediction

    Science.gov (United States)

    Erol, Hamza

    2016-01-01

    Early heart disease control can be achieved by high disease prediction and diagnosis efficiency. This paper focuses on the use of model based clustering techniques to predict and diagnose heart disease via Poisson mixture regression models. Analysis and application of Poisson mixture regression models is here addressed under two different classes: standard and concomitant variable mixture regression models. Results show that a two-component concomitant variable Poisson mixture regression model predicts heart disease better than both the standard Poisson mixture regression model and the ordinary general linear Poisson regression model due to its low Bayesian Information Criteria value. Furthermore, a Zero Inflated Poisson Mixture Regression model turned out to be the best model for heart prediction over all models as it both clusters individuals into high or low risk category and predicts rate to heart disease componentwise given clusters available. It is deduced that heart disease prediction can be effectively done by identifying the major risks componentwise using Poisson mixture regression model. PMID:27999611

  10. Regression analysis using dependent Polya trees.

    Science.gov (United States)

    Schörgendorfer, Angela; Branscum, Adam J

    2013-11-30

    Many commonly used models for linear regression analysis force overly simplistic shape and scale constraints on the residual structure of data. We propose a semiparametric Bayesian model for regression analysis that produces data-driven inference by using a new type of dependent Polya tree prior to model arbitrary residual distributions that are allowed to evolve across increasing levels of an ordinal covariate (e.g., time, in repeated measurement studies). By modeling residual distributions at consecutive covariate levels or time points using separate, but dependent Polya tree priors, distributional information is pooled while allowing for broad pliability to accommodate many types of changing residual distributions. We can use the proposed dependent residual structure in a wide range of regression settings, including fixed-effects and mixed-effects linear and nonlinear models for cross-sectional, prospective, and repeated measurement data. A simulation study illustrates the flexibility of our novel semiparametric regression model to accurately capture evolving residual distributions. In an application to immune development data on immunoglobulin G antibodies in children, our new model outperforms several contemporary semiparametric regression models based on a predictive model selection criterion. Copyright © 2013 John Wiley & Sons, Ltd.

  11. 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.

  12. Applied Regression Modeling A Business Approach

    CERN Document Server

    Pardoe, Iain

    2012-01-01

    An applied and concise treatment of statistical regression techniques for business students and professionals who have little or no background in calculusRegression analysis is an invaluable statistical methodology in business settings and is vital to model the relationship between a response variable and one or more predictor variables, as well as the prediction of a response value given values of the predictors. In view of the inherent uncertainty of business processes, such as the volatility of consumer spending and the presence of market uncertainty, business professionals use regression a

  13. Regression relation for pure quantum states and its implications for efficient computing.

    Science.gov (United States)

    Elsayed, Tarek A; Fine, Boris V

    2013-02-15

    We obtain a modified version of the Onsager regression relation for the expectation values of quantum-mechanical operators in pure quantum states of isolated many-body quantum systems. We use the insights gained from this relation to show that high-temperature time correlation functions in many-body quantum systems can be controllably computed without complete diagonalization of the Hamiltonians, using instead the direct integration of the Schrödinger equation for randomly sampled pure states. This method is also applicable to quantum quenches and other situations describable by time-dependent many-body Hamiltonians. The method implies exponential reduction of the computer memory requirement in comparison with the complete diagonalization. We illustrate the method by numerically computing infinite-temperature correlation functions for translationally invariant Heisenberg chains of up to 29 spins 1/2. Thereby, we also test the spin diffusion hypothesis and find it in a satisfactory agreement with the numerical results. Both the derivation of the modified regression relation and the justification of the computational method are based on the notion of quantum typicality.

  14. Development of a Watershed-Scale Long-Term Hydrologic Impact Assessment Model with the Asymptotic Curve Number Regression Equation

    Directory of Open Access Journals (Sweden)

    Jichul Ryu

    2016-04-01

    Full Text Available In this study, 52 asymptotic Curve Number (CN regression equations were developed for combinations of representative land covers and hydrologic soil groups. In addition, to overcome the limitations of the original Long-term Hydrologic Impact Assessment (L-THIA model when it is applied to larger watersheds, a watershed-scale L-THIA Asymptotic CN (ACN regression equation model (watershed-scale L-THIA ACN model was developed by integrating the asymptotic CN regressions and various modules for direct runoff/baseflow/channel routing. The watershed-scale L-THIA ACN model was applied to four watersheds in South Korea to evaluate the accuracy of its streamflow prediction. The coefficient of determination (R2 and Nash–Sutcliffe Efficiency (NSE values for observed versus simulated streamflows over intervals of eight days were greater than 0.6 for all four of the watersheds. The watershed-scale L-THIA ACN model, including the asymptotic CN regression equation method, can simulate long-term streamflow sufficiently well with the ten parameters that have been added for the characterization of streamflow.

  15. 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...

  16. Regression of environmental noise in LIGO data

    International Nuclear Information System (INIS)

    Tiwari, V; Klimenko, S; Mitselmakher, G; Necula, V; Drago, M; Prodi, G; Frolov, V; Yakushin, I; Re, V; Salemi, F; Vedovato, G

    2015-01-01

    We address the problem of noise regression in the output of gravitational-wave (GW) interferometers, using data from the physical environmental monitors (PEM). The objective of the regression analysis is to predict environmental noise in the GW channel from the PEM measurements. One of the most promising regression methods is based on the construction of Wiener–Kolmogorov (WK) filters. Using this method, the seismic noise cancellation from the LIGO GW channel has already been performed. In the presented approach the WK method has been extended, incorporating banks of Wiener filters in the time–frequency domain, multi-channel analysis and regulation schemes, which greatly enhance the versatility of the regression analysis. Also we present the first results on regression of the bi-coherent noise in the LIGO data. (paper)

  17. Bi-Hamiltonian operators, integrable flows of curves using moving frames and geometric map equations

    International Nuclear Information System (INIS)

    Anco, Stephen C

    2006-01-01

    Moving frames of various kinds are used to derive bi-Hamiltonian operators and associated hierarchies of multi-component soliton equations from group-invariant flows of non-stretching curves in constant-curvature manifolds and Lie-group manifolds. The hierarchy in the constant-curvature case consists of a vector mKdV equation coming from a parallel frame, a vector potential mKdV equation coming from a covariantly constant frame, and higher order counterparts generated by an underlying vector mKdV recursion operator. In the Lie-group case, the hierarchy comprises a group-invariant analogue of the vector NLS equation coming from a left-invariant frame, along with higher order counterparts generated by a recursion operator that is like a square root of the mKdV one. The corresponding respective curve flows are found to be given by geometric nonlinear PDEs, specifically mKdV and group-invariant analogues of Schroedinger maps. In all cases the hierarchies also contain variants of vector sine-Gordon equations arising from the kernel of the respective recursion operators. The geometric PDEs that describe the corresponding curve flows are shown to be wave maps

  18. Bi-Hamiltonian operators, integrable flows of curves using moving frames and geometric map equations

    Energy Technology Data Exchange (ETDEWEB)

    Anco, Stephen C [Department of Mathematics, Brock University, St Catharines, ON (Canada)

    2006-03-03

    Moving frames of various kinds are used to derive bi-Hamiltonian operators and associated hierarchies of multi-component soliton equations from group-invariant flows of non-stretching curves in constant-curvature manifolds and Lie-group manifolds. The hierarchy in the constant-curvature case consists of a vector mKdV equation coming from a parallel frame, a vector potential mKdV equation coming from a covariantly constant frame, and higher order counterparts generated by an underlying vector mKdV recursion operator. In the Lie-group case, the hierarchy comprises a group-invariant analogue of the vector NLS equation coming from a left-invariant frame, along with higher order counterparts generated by a recursion operator that is like a square root of the mKdV one. The corresponding respective curve flows are found to be given by geometric nonlinear PDEs, specifically mKdV and group-invariant analogues of Schroedinger maps. In all cases the hierarchies also contain variants of vector sine-Gordon equations arising from the kernel of the respective recursion operators. The geometric PDEs that describe the corresponding curve flows are shown to be wave maps.

  19. Open architecture design and approach for the Integrated Sensor Architecture (ISA)

    Science.gov (United States)

    Moulton, Christine L.; Krzywicki, Alan T.; Hepp, Jared J.; Harrell, John; Kogut, Michael

    2015-05-01

    Integrated Sensor Architecture (ISA) is designed in response to stovepiped integration approaches. The design, based on the principles of Service Oriented Architectures (SOA) and Open Architectures, addresses the problem of integration, and is not designed for specific sensors or systems. The use of SOA and Open Architecture approaches has led to a flexible, extensible architecture. Using these approaches, and supported with common data formats, open protocol specifications, and Department of Defense Architecture Framework (DoDAF) system architecture documents, an integration-focused architecture has been developed. ISA can help move the Department of Defense (DoD) from costly stovepipe solutions to a more cost-effective plug-and-play design to support interoperability.

  20. Development of an Agent-Based Model (ABM) to Simulate the Immune System and Integration of a Regression Method to Estimate the Key ABM Parameters by Fitting the Experimental Data

    Science.gov (United States)

    Tong, Xuming; Chen, Jinghang; Miao, Hongyu; Li, Tingting; Zhang, Le

    2015-01-01

    Agent-based models (ABM) and differential equations (DE) are two commonly used methods for immune system simulation. However, it is difficult for ABM to estimate key parameters of the model by incorporating experimental data, whereas the differential equation model is incapable of describing the complicated immune system in detail. To overcome these problems, we developed an integrated ABM regression model (IABMR). It can combine the advantages of ABM and DE by employing ABM to mimic the multi-scale immune system with various phenotypes and types of cells as well as using the input and output of ABM to build up the Loess regression for key parameter estimation. Next, we employed the greedy algorithm to estimate the key parameters of the ABM with respect to the same experimental data set and used ABM to describe a 3D immune system similar to previous studies that employed the DE model. These results indicate that IABMR not only has the potential to simulate the immune system at various scales, phenotypes and cell types, but can also accurately infer the key parameters like DE model. Therefore, this study innovatively developed a complex system development mechanism that could simulate the complicated immune system in detail like ABM and validate the reliability and efficiency of model like DE by fitting the experimental data. PMID:26535589

  1. Pilots' Attention Distributions Between Chasing a Moving Target and a Stationary Target.

    Science.gov (United States)

    Li, Wen-Chin; Yu, Chung-San; Braithwaite, Graham; Greaves, Matthew

    2016-12-01

    Attention plays a central role in cognitive processing; ineffective attention may induce accidents in flight operations. The objective of the current research was to examine military pilots' attention distributions between chasing a moving target and a stationary target. In the current research, 37 mission-ready F-16 pilots participated. Subjects' eye movements were collected by a portable head-mounted eye-tracker during tactical training in a flight simulator. The scenarios of chasing a moving target (air-to-air) and a stationary target (air-to-surface) consist of three operational phases: searching, aiming, and lock-on to the targets. The findings demonstrated significant differences in pilots' percentage of fixation during the searching phase between air-to-air (M = 37.57, SD = 5.72) and air-to-surface (M = 33.54, SD = 4.68). Fixation duration can indicate pilots' sustained attention to the trajectory of a dynamic target during air combat maneuvers. Aiming at the stationary target resulted in larger pupil size (M = 27,105, SD = 6565), reflecting higher cognitive loading than aiming at the dynamic target (M = 23,864, SD = 8762). Pilots' visual behavior is not only closely related to attention distribution, but also significantly associated with task characteristics. Military pilots demonstrated various visual scan patterns for searching and aiming at different types of targets based on the research settings of a flight simulator. The findings will facilitate system designers' understanding of military pilots' cognitive processes during tactical operations. They will assist human-centered interface design to improve pilots' situational awareness. The application of an eye-tracking device integrated with a flight simulator is a feasible and cost-effective intervention to improve the efficiency and safety of tactical training.Li W-C, Yu C-S, Braithwaite G, Greaves M. Pilots' attention distributions between chasing a moving target and a stationary target. Aerosp Med

  2. Air ambulance services--integrated emergency care.

    Science.gov (United States)

    Ferdinand, M

    1994-10-01

    In the name of cost-conscious care, air ambulance program directors and service contractors are seeing the dawn of integrated networks as a boon to their business. As integrated networks form, facilities will become increasingly specialized in the types of services they provide. Patients will need to be moved around the system, resulting in more frequent patient transport and more points of transfer. Many programs are considering aircraft replacement and additions, rather than leasing. Financial benefits could come on depreciation and the high resale value of aircraft. Unless reimbursement levels increase, more program mergers and affiliations may take place to spread and reduce cost. Air ambulance services will increasingly become part of a facility's strategic plan.

  3. Integrated coherent matter wave circuits

    International Nuclear Information System (INIS)

    Ryu, C.; Boshier, M. G.

    2015-01-01

    An integrated coherent matter wave circuit is a single device, analogous to an integrated optical circuit, in which coherent de Broglie waves are created and then launched into waveguides where they can be switched, divided, recombined, and detected as they propagate. Applications of such circuits include guided atom interferometers, atomtronic circuits, and precisely controlled delivery of atoms. We report experiments demonstrating integrated circuits for guided coherent matter waves. The circuit elements are created with the painted potential technique, a form of time-averaged optical dipole potential in which a rapidly moving, tightly focused laser beam exerts forces on atoms through their electric polarizability. Moreover, the source of coherent matter waves is a Bose-Einstein condensate (BEC). Finally, we launch BECs into painted waveguides that guide them around bends and form switches, phase coherent beamsplitters, and closed circuits. These are the basic elements that are needed to engineer arbitrarily complex matter wave circuitry

  4. 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...

  5. 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.

  6. Forecasting with Dynamic Regression Models

    CERN Document Server

    Pankratz, Alan

    2012-01-01

    One of the most widely used tools in statistical forecasting, single equation regression models is examined here. A companion to the author's earlier work, Forecasting with Univariate Box-Jenkins Models: Concepts and Cases, the present text pulls together recent time series ideas and gives special attention to possible intertemporal patterns, distributed lag responses of output to input series and the auto correlation patterns of regression disturbance. It also includes six case studies.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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.

  9. Automation of Flight Software Regression Testing

    Science.gov (United States)

    Tashakkor, Scott B.

    2016-01-01

    NASA is developing the Space Launch System (SLS) to be a heavy lift launch vehicle supporting human and scientific exploration beyond earth orbit. SLS will have a common core stage, an upper stage, and different permutations of boosters and fairings to perform various crewed or cargo missions. Marshall Space Flight Center (MSFC) is writing the Flight Software (FSW) that will operate the SLS launch vehicle. The FSW is developed in an incremental manner based on "Agile" software techniques. As the FSW is incrementally developed, testing the functionality of the code needs to be performed continually to ensure that the integrity of the software is maintained. Manually testing the functionality on an ever-growing set of requirements and features is not an efficient solution and therefore needs to be done automatically to ensure testing is comprehensive. To support test automation, a framework for a regression test harness has been developed and used on SLS FSW. The test harness provides a modular design approach that can compile or read in the required information specified by the developer of the test. The modularity provides independence between groups of tests and the ability to add and remove tests without disturbing others. This provides the SLS FSW team a time saving feature that is essential to meeting SLS Program technical and programmatic requirements. During development of SLS FSW, this technique has proved to be a useful tool to ensure all requirements have been tested, and that desired functionality is maintained, as changes occur. It also provides a mechanism for developers to check functionality of the code that they have developed. With this system, automation of regression testing is accomplished through a scheduling tool and/or commit hooks. Key advantages of this test harness capability includes execution support for multiple independent test cases, the ability for developers to specify precisely what they are testing and how, the ability to add

  10. Simultaneous Force Regression and Movement Classification of Fingers via Surface EMG within a Unified Bayesian Framework.

    Science.gov (United States)

    Baldacchino, Tara; Jacobs, William R; Anderson, Sean R; Worden, Keith; Rowson, Jennifer

    2018-01-01

    This contribution presents a novel methodology for myolectric-based control using surface electromyographic (sEMG) signals recorded during finger movements. A multivariate Bayesian mixture of experts (MoE) model is introduced which provides a powerful method for modeling force regression at the fingertips, while also performing finger movement classification as a by-product of the modeling algorithm. Bayesian inference of the model allows uncertainties to be naturally incorporated into the model structure. This method is tested using data from the publicly released NinaPro database which consists of sEMG recordings for 6 degree-of-freedom force activations for 40 intact subjects. The results demonstrate that the MoE model achieves similar performance compared to the benchmark set by the authors of NinaPro for finger force regression. Additionally, inherent to the Bayesian framework is the inclusion of uncertainty in the model parameters, naturally providing confidence bounds on the force regression predictions. Furthermore, the integrated clustering step allows a detailed investigation into classification of the finger movements, without incurring any extra computational effort. Subsequently, a systematic approach to assessing the importance of the number of electrodes needed for accurate control is performed via sensitivity analysis techniques. A slight degradation in regression performance is observed for a reduced number of electrodes, while classification performance is unaffected.

  11. Estimating Loess Plateau Average Annual Precipitation with Multiple Linear Regression Kriging and Geographically Weighted Regression Kriging

    Directory of Open Access Journals (Sweden)

    Qiutong Jin

    2016-06-01

    Full Text Available Estimating the spatial distribution of precipitation is an important and challenging task in hydrology, climatology, ecology, and environmental science. In order to generate a highly accurate distribution map of average annual precipitation for the Loess Plateau in China, multiple linear regression Kriging (MLRK and geographically weighted regression Kriging (GWRK methods were employed using precipitation data from the period 1980–2010 from 435 meteorological stations. The predictors in regression Kriging were selected by stepwise regression analysis from many auxiliary environmental factors, such as elevation (DEM, normalized difference vegetation index (NDVI, solar radiation, slope, and aspect. All predictor distribution maps had a 500 m spatial resolution. Validation precipitation data from 130 hydrometeorological stations were used to assess the prediction accuracies of the MLRK and GWRK approaches. Results showed that both prediction maps with a 500 m spatial resolution interpolated by MLRK and GWRK had a high accuracy and captured detailed spatial distribution data; however, MLRK produced a lower prediction error and a higher variance explanation than GWRK, although the differences were small, in contrast to conclusions from similar studies.

  12. Integrative Physiology 2.0’: integration of systems biology into physiology and its application to cardiovascular homeostasis

    Science.gov (United States)

    Kuster, Diederik W D; Merkus, Daphne; van der Velden, Jolanda; Verhoeven, Adrie J M; Duncker, Dirk J

    2011-01-01

    Since the completion of the Human Genome Project and the advent of the large scaled unbiased ‘-omics’ techniques, the field of systems biology has emerged. Systems biology aims to move away from the traditional reductionist molecular approach, which focused on understanding the role of single genes or proteins, towards a more holistic approach by studying networks and interactions between individual components of networks. From a conceptual standpoint, systems biology elicits a ‘back to the future’ experience for any integrative physiologist. However, many of the new techniques and modalities employed by systems biologists yield tremendous potential for integrative physiologists to expand their tool arsenal to (quantitatively) study complex biological processes, such as cardiac remodelling and heart failure, in a truly holistic fashion. We therefore advocate that systems biology should not become/stay a separate discipline with ‘-omics’ as its playing field, but should be integrated into physiology to create ‘Integrative Physiology 2.0’. PMID:21224228

  13. 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.

  14. A flow-through cell with integrated coulometric pH actuator

    NARCIS (Netherlands)

    Bohm, S.; Olthuis, Wouter; Bergveld, Piet

    1998-01-01

    A flow-through cell with integrated coulometric actuator capable of controlling the pH of a flowing liquid is presented. The cell, consisting of a rectangular channel with a noble metal actuator electrode deposited on the bottom, enables the titration of a moving liquid without the need for pumps

  15. Assessing the impacts of droughts and heat waves at thermoelectric power plants in the United States using integrated regression, thermodynamic, and climate models

    Directory of Open Access Journals (Sweden)

    Margaret A. Cook

    2015-11-01

    Full Text Available Recent droughts and heat waves have revealed the vulnerability of some power plants to effects from higher temperature intake water for cooling. In this evaluation, we develop a methodology for predicting whether power plants are at risk of violating thermal pollution limits. We begin by developing a regression model of average monthly intake temperatures for open loop and recirculating cooling pond systems. We then integrate that information into a thermodynamic model of energy flows within each power plant to determine the change in cooling water temperature that occurs at each plant and the relationship of that water temperature to other plants in the river system. We use these models together with climate change models to estimate the monthly effluent temperature at twenty-six power plants in the Upper Mississippi River Basin and Texas between 2015 and 2035 to predict which ones are at risk of reaching thermal pollution limits. The intake model shows that two plants could face elevated intake temperatures between 2015 and 2035 compared to the 2010–2013 baseline. In general, a rise in ambient cooling water temperature of 1 °C could cause a drop in power output of 0.15%–0.5%. The energy balance shows that twelve plants might exceed state summer effluent limits.

  16. 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…

  17. Gibrat’s law and quantile regressions

    DEFF Research Database (Denmark)

    Distante, Roberta; Petrella, Ivan; Santoro, Emiliano

    2017-01-01

    The nexus between firm growth, size and age in U.S. manufacturing is examined through the lens of quantile regression models. This methodology allows us to overcome serious shortcomings entailed by linear regression models employed by much of the existing literature, unveiling a number of important...

  18. ON REGRESSION REPRESENTATIONS OF STOCHASTIC-PROCESSES

    NARCIS (Netherlands)

    RUSCHENDORF, L; DEVALK, [No Value

    We construct a.s. nonlinear regression representations of general stochastic processes (X(n))n is-an-element-of N. As a consequence we obtain in particular special regression representations of Markov chains and of certain m-dependent sequences. For m-dependent sequences we obtain a constructive

  19. Implantable fiber-optic interface for parallel multisite long-term optical dynamic brain interrogation in freely moving mice

    Science.gov (United States)

    Doronina-Amitonova, L. V.; Fedotov, I. V.; Ivashkina, O. I.; Zots, M. A.; Fedotov, A. B.; Anokhin, K. V.; Zheltikov, A. M.

    2013-01-01

    Seeing the big picture of functional responses within large neural networks in a freely functioning brain is crucial for understanding the cellular mechanisms behind the higher nervous activity, including the most complex brain functions, such as cognition and memory. As a breakthrough toward meeting this challenge, implantable fiber-optic interfaces integrating advanced optogenetic technologies and cutting-edge fiber-optic solutions have been demonstrated, enabling a long-term optogenetic manipulation of neural circuits in freely moving mice. Here, we show that a specifically designed implantable fiber-optic interface provides a powerful tool for parallel long-term optical interrogation of distinctly separate, functionally different sites in the brain of freely moving mice. This interface allows the same groups of neurons lying deeply in the brain of a freely behaving mouse to be reproducibly accessed and optically interrogated over many weeks, providing a long-term dynamic detection of genome activity in response to a broad variety of pharmacological and physiological stimuli. PMID:24253232

  20. Introduction to the use of regression models in epidemiology.

    Science.gov (United States)

    Bender, Ralf

    2009-01-01

    Regression modeling is one of the most important statistical techniques used in analytical epidemiology. By means of regression models the effect of one or several explanatory variables (e.g., exposures, subject characteristics, risk factors) on a response variable such as mortality or cancer can be investigated. From multiple regression models, adjusted effect estimates can be obtained that take the effect of potential confounders into account. Regression methods can be applied in all epidemiologic study designs so that they represent a universal tool for data analysis in epidemiology. Different kinds of regression models have been developed in dependence on the measurement scale of the response variable and the study design. The most important methods are linear regression for continuous outcomes, logistic regression for binary outcomes, Cox regression for time-to-event data, and Poisson regression for frequencies and rates. This chapter provides a nontechnical introduction to these regression models with illustrating examples from cancer research.