WorldWideScience

Sample records for multi-step density forecasts

  1. Multi-step wind speed forecasting based on a hybrid forecasting architecture and an improved bat algorithm

    International Nuclear Information System (INIS)

    Xiao, Liye; Qian, Feng; Shao, Wei

    2017-01-01

    Highlights: • Propose a hybrid architecture based on a modified bat algorithm for multi-step wind speed forecasting. • Improve the accuracy of multi-step wind speed forecasting. • Modify bat algorithm with CG to improve optimized performance. - Abstract: As one of the most promising sustainable energy sources, wind energy plays an important role in energy development because of its cleanliness without causing pollution. Generally, wind speed forecasting, which has an essential influence on wind power systems, is regarded as a challenging task. Analyses based on single-step wind speed forecasting have been widely used, but their results are insufficient in ensuring the reliability and controllability of wind power systems. In this paper, a new forecasting architecture based on decomposing algorithms and modified neural networks is successfully developed for multi-step wind speed forecasting. Four different hybrid models are contained in this architecture, and to further improve the forecasting performance, a modified bat algorithm (BA) with the conjugate gradient (CG) method is developed to optimize the initial weights between layers and thresholds of the hidden layer of neural networks. To investigate the forecasting abilities of the four models, the wind speed data collected from four different wind power stations in Penglai, China, were used as a case study. The numerical experiments showed that the hybrid model including the singular spectrum analysis and general regression neural network with CG-BA (SSA-CG-BA-GRNN) achieved the most accurate forecasting results in one-step to three-step wind speed forecasting.

  2. Multi-Step Time Series Forecasting with an Ensemble of Varied Length Mixture Models.

    Science.gov (United States)

    Ouyang, Yicun; Yin, Hujun

    2018-05-01

    Many real-world problems require modeling and forecasting of time series, such as weather temperature, electricity demand, stock prices and foreign exchange (FX) rates. Often, the tasks involve predicting over a long-term period, e.g. several weeks or months. Most existing time series models are inheritably for one-step prediction, that is, predicting one time point ahead. Multi-step or long-term prediction is difficult and challenging due to the lack of information and uncertainty or error accumulation. The main existing approaches, iterative and independent, either use one-step model recursively or treat the multi-step task as an independent model. They generally perform poorly in practical applications. In this paper, as an extension of the self-organizing mixture autoregressive (AR) model, the varied length mixture (VLM) models are proposed to model and forecast time series over multi-steps. The key idea is to preserve the dependencies between the time points within the prediction horizon. Training data are segmented to various lengths corresponding to various forecasting horizons, and the VLM models are trained in a self-organizing fashion on these segments to capture these dependencies in its component AR models of various predicting horizons. The VLM models form a probabilistic mixture of these varied length models. A combination of short and long VLM models and an ensemble of them are proposed to further enhance the prediction performance. The effectiveness of the proposed methods and their marked improvements over the existing methods are demonstrated through a number of experiments on synthetic data, real-world FX rates and weather temperatures.

  3. Densities of accessible final states for multi-step compound reactions

    International Nuclear Information System (INIS)

    Maoming De; Guo Hua

    1993-01-01

    The densities of accessible final states for calculations of multi-step compound reactions are derived. The Pauli exclusion principle is taken into account in the calculations. The results are compared with a previous author's results and the effect of the Pauli exclusion principle is investigated. (Author)

  4. Particle-hole state densities for statistical multi-step compound reactions

    International Nuclear Information System (INIS)

    Oblozinsky, P.

    1986-01-01

    An analytical relation is derived for the density of particle-hole bound states applying the equidistant-spacing approximation and the Darwin-Fowler statistical method. The Pauli exclusion principle as well as the finite depth of the potential well are taken into account. The set of densities needed for calculations of multi-step compound reactions is completed by deriving the densities of accessible final states for escape and damping. (orig.)

  5. Multi-step polynomial regression method to model and forecast malaria incidence.

    Directory of Open Access Journals (Sweden)

    Chandrajit Chatterjee

    Full Text Available Malaria is one of the most severe problems faced by the world even today. Understanding the causative factors such as age, sex, social factors, environmental variability etc. as well as underlying transmission dynamics of the disease is important for epidemiological research on malaria and its eradication. Thus, development of suitable modeling approach and methodology, based on the available data on the incidence of the disease and other related factors is of utmost importance. In this study, we developed a simple non-linear regression methodology in modeling and forecasting malaria incidence in Chennai city, India, and predicted future disease incidence with high confidence level. We considered three types of data to develop the regression methodology: a longer time series data of Slide Positivity Rates (SPR of malaria; a smaller time series data (deaths due to Plasmodium vivax of one year; and spatial data (zonal distribution of P. vivax deaths for the city along with the climatic factors, population and previous incidence of the disease. We performed variable selection by simple correlation study, identification of the initial relationship between variables through non-linear curve fitting and used multi-step methods for induction of variables in the non-linear regression analysis along with applied Gauss-Markov models, and ANOVA for testing the prediction, validity and constructing the confidence intervals. The results execute the applicability of our method for different types of data, the autoregressive nature of forecasting, and show high prediction power for both SPR and P. vivax deaths, where the one-lag SPR values plays an influential role and proves useful for better prediction. Different climatic factors are identified as playing crucial role on shaping the disease curve. Further, disease incidence at zonal level and the effect of causative factors on different zonal clusters indicate the pattern of malaria prevalence in the city

  6. Comparison between stochastic and machine learning methods for hydrological multi-step ahead forecasting: All forecasts are wrong!

    Science.gov (United States)

    Papacharalampous, Georgia; Tyralis, Hristos; Koutsoyiannis, Demetris

    2017-04-01

    Machine learning (ML) is considered to be a promising approach to hydrological processes forecasting. We conduct a comparison between several stochastic and ML point estimation methods by performing large-scale computational experiments based on simulations. The purpose is to provide generalized results, while the respective comparisons in the literature are usually based on case studies. The stochastic methods used include simple methods, models from the frequently used families of Autoregressive Moving Average (ARMA), Autoregressive Fractionally Integrated Moving Average (ARFIMA) and Exponential Smoothing models. The ML methods used are Random Forests (RF), Support Vector Machines (SVM) and Neural Networks (NN). The comparison refers to the multi-step ahead forecasting properties of the methods. A total of 20 methods are used, among which 9 are the ML methods. 12 simulation experiments are performed, while each of them uses 2 000 simulated time series of 310 observations. The time series are simulated using stochastic processes from the families of ARMA and ARFIMA models. Each time series is split into a fitting (first 300 observations) and a testing set (last 10 observations). The comparative assessment of the methods is based on 18 metrics, that quantify the methods' performance according to several criteria related to the accurate forecasting of the testing set, the capturing of its variation and the correlation between the testing and forecasted values. The most important outcome of this study is that there is not a uniformly better or worse method. However, there are methods that are regularly better or worse than others with respect to specific metrics. It appears that, although a general ranking of the methods is not possible, their classification based on their similar or contrasting performance in the various metrics is possible to some extent. Another important conclusion is that more sophisticated methods do not necessarily provide better forecasts

  7. Four wind speed multi-step forecasting models using extreme learning machines and signal decomposing algorithms

    International Nuclear Information System (INIS)

    Liu, Hui; Tian, Hong-qi; Li, Yan-fei

    2015-01-01

    Highlights: • A hybrid architecture is proposed for the wind speed forecasting. • Four algorithms are used for the wind speed multi-scale decomposition. • The extreme learning machines are employed for the wind speed forecasting. • All the proposed hybrid models can generate the accurate results. - Abstract: Realization of accurate wind speed forecasting is important to guarantee the safety of wind power utilization. In this paper, a new hybrid forecasting architecture is proposed to realize the wind speed accurate forecasting. In this architecture, four different hybrid models are presented by combining four signal decomposing algorithms (e.g., Wavelet Decomposition/Wavelet Packet Decomposition/Empirical Mode Decomposition/Fast Ensemble Empirical Mode Decomposition) and Extreme Learning Machines. The originality of the study is to investigate the promoted percentages of the Extreme Learning Machines by those mainstream signal decomposing algorithms in the multiple step wind speed forecasting. The results of two forecasting experiments indicate that: (1) the method of Extreme Learning Machines is suitable for the wind speed forecasting; (2) by utilizing the decomposing algorithms, all the proposed hybrid algorithms have better performance than the single Extreme Learning Machines; (3) in the comparisons of the decomposing algorithms in the proposed hybrid architecture, the Fast Ensemble Empirical Mode Decomposition has the best performance in the three-step forecasting results while the Wavelet Packet Decomposition has the best performance in the one and two step forecasting results. At the same time, the Wavelet Packet Decomposition and the Fast Ensemble Empirical Mode Decomposition are better than the Wavelet Decomposition and the Empirical Mode Decomposition in all the step predictions, respectively; and (4) the proposed algorithms are effective in the wind speed accurate predictions

  8. Stochastic rainfall-runoff forecasting: parameter estimation, multi-step prediction, and evaluation of overflow risk

    DEFF Research Database (Denmark)

    Löwe, Roland; Mikkelsen, Peter Steen; Madsen, Henrik

    2014-01-01

    Probabilistic runoff forecasts generated by stochastic greybox models can be notably useful for the improvement of the decision-making process in real-time control setups for urban drainage systems because the prediction risk relationships in these systems are often highly nonlinear. To date...... the identification of models for cases with noisy in-sewer observations. For the prediction of the overflow risk, no improvement was demonstrated through the application of stochastic forecasts instead of point predictions, although this result is thought to be caused by the notably simplified setup used...

  9. On density forecast evaluation

    NARCIS (Netherlands)

    Diks, C.

    2008-01-01

    Traditionally, probability integral transforms (PITs) have been popular means for evaluating density forecasts. For an ideal density forecast, the PITs should be uniformly distributed on the unit interval and independent. However, this is only a necessary condition, and not a sufficient one, as

  10. Multi-step ahead forecasts for electricity prices using NARX: A new approach, a critical analysis of one-step ahead forecasts

    International Nuclear Information System (INIS)

    Andalib, Arash; Atry, Farid

    2009-01-01

    The prediction of electricity prices is very important to participants of deregulated markets. Among many properties, a successful prediction tool should be able to capture long-term dependencies in market's historical data. A nonlinear autoregressive model with exogenous inputs (NARX) has proven to enjoy a superior performance to capture such dependencies than other learning machines. However, it is not examined for electricity price forecasting so far. In this paper, we have employed a NARX network for forecasting electricity prices. Our prediction model is then compared with two currently used methods, namely the multivariate adaptive regression splines (MARS) and wavelet neural network. All the models are built on the reconstructed state space of market's historical data, which either improves the results or decreases the complexity of learning algorithms. Here, we also criticize the one-step ahead forecasts for electricity price that may suffer a one-term delay and we explain why the mean square error criterion does not guarantee a functional prediction result in this case. To tackle the problem, we pursue multi-step ahead predictions. Results for the Ontario electricity market are presented

  11. Impact of multi-resolution analysis of artificial intelligence models inputs on multi-step ahead river flow forecasting

    Science.gov (United States)

    Badrzadeh, Honey; Sarukkalige, Ranjan; Jayawardena, A. W.

    2013-12-01

    Discrete wavelet transform was applied to decomposed ANN and ANFIS inputs.Novel approach of WNF with subtractive clustering applied for flow forecasting.Forecasting was performed in 1-5 step ahead, using multi-variate inputs.Forecasting accuracy of peak values and longer lead-time significantly improved.

  12. A Hybrid Multi-Step Rolling Forecasting Model Based on SSA and Simulated Annealing—Adaptive Particle Swarm Optimization for Wind Speed

    Directory of Open Access Journals (Sweden)

    Pei Du

    2016-08-01

    Full Text Available With the limitations of conventional energy becoming increasing distinct, wind energy is emerging as a promising renewable energy source that plays a critical role in the modern electric and economic fields. However, how to select optimization algorithms to forecast wind speed series and improve prediction performance is still a highly challenging problem. Traditional single algorithms are widely utilized to select and optimize parameters of neural network algorithms, but these algorithms usually ignore the significance of parameter optimization, precise searching, and the application of accurate data, which results in poor forecasting performance. With the aim of overcoming the weaknesses of individual algorithms, a novel hybrid algorithm was created, which can not only easily obtain the real and effective wind speed series by using singular spectrum analysis, but also possesses stronger adaptive search and optimization capabilities than the other algorithms: it is faster, has fewer parameters, and is less expensive. For the purpose of estimating the forecasting ability of the proposed combined model, 10-min wind speed series from three wind farms in Shandong Province, eastern China, are employed as a case study. The experimental results were considerably more accurately predicted by the presented algorithm than the comparison algorithms.

  13. Power density forecasting device for nuclear power plant

    International Nuclear Information System (INIS)

    Fukuzaki, Takaharu; Kiguchi, Takashi.

    1978-01-01

    Purpose: To attain effective reactor operation in a bwr type reactor by forecasting the power density of the reactor after adjustment and comparing the same with the present status of the reactor by the on-line calculation in a short time. Constitution: The present status for the reactor is estimated in a present status decision section based on a measurement signal from the reactor and it is stored in an operation result collection section. The reactor status after the forecasting is estimated in a forecasting section based on a setting signal from a forecasting condition setting section and it is compared with the result value from the operation results collection section. If the forecast value does not coincide with the result value in the above comparison, the setting value in the forecast condition setting section is changed in the control section. The above procedures are repeated so as to minimize the difference between the forecast value and the result value to thereby exactly forecast the reactor status and operate the reactor effectively. (Moriyama, K.)

  14. Price Density Forecasts in the U.S. Hog Market: Composite Procedures

    NARCIS (Netherlands)

    Trujillo Barrera, A.A.; Garcia, P.; Mallory, M.

    2013-01-01

    Abstract We develop and evaluate quarterly out-of-sample individual and composite density forecasts for U.S. hog prices using data from 1975.I to 2010.IV. Individual forecasts are generated from time series models and the implied distribution of USDA outlook forecasts. Composite density forecasts

  15. Randomness in multi-step direct reactions

    International Nuclear Information System (INIS)

    Koning, A.J.; Akkermans, J.M.

    1991-01-01

    The authors propose a quantum-statistical framework that provides an integrated perspective on the differences and similarities between the many current models for multi-step direct reactions in the continuum. It is argued that to obtain a statistical theory two physically different approaches are conceivable to postulate randomness, respectively called leading-particle statistics and residual-system statistics. They present a new leading-particle statistics theory for multi-step direct reactions. It is shown that the model of Feshbach et al. can be derived as a simplification of this theory and thus can be founded solely upon leading-particle statistics. The models developed by Tamura et al. and Nishioka et al. are based upon residual-system statistics and hence fall into a physically different class of multi-step direct theories, although the resulting cross-section formulae for the important first step are shown to be the same. The widely used semi-classical models such as the generalized exciton model can be interpreted as further phenomenological simplification of the leading-particle statistics theory

  16. Angular momentum in multi-step photoionization

    International Nuclear Information System (INIS)

    Yoshida, Tadashi; Adachi, Hajime; Kuwako, Akira; Nittoh, Koichi; Araki, Yoshio; Watanabe, Takashi; Yoguchi, Itaru.

    1995-01-01

    The effect of the angular momenta on the multi-step laser-ionization efficiency was investigated numerically for cases with and without the hyperfine interactions. For either cases the ionization efficiency proved to depend appreciably on the values of J in the excitation ladder. In this respect, we elaborated a simple and efficient method of determining J, which was based on the laser polarization dependence of the excitation rate. Application of this method to a couple of real excitation ladders proved its usefulness and reliability. (author)

  17. Statistical theory of multi-step compound and direct reactions

    International Nuclear Information System (INIS)

    Feshbach, H.; Kerman, A.; Koonin, S.

    1980-01-01

    The theory of nuclear reactions is extended so as to include a statistical treatment of multi-step processes. Two types are distinguished, the multi-step compound and the multi-step direct. The wave functions for the system are grouped according to their complexity. The multi-step direct process involves explicitly those states which are open, while the multi-step compound involves those which are bound. In addition to the random phase assumption which is applied differently to the multi-step direct and to the multi-step compound cross-sections, it is assumed that the residual interaction will have non-vanishing matrix elements between states whose complexities differ by at most one unit. This is referred to as the chaining hypothesis. Explicit expressions for the double differential cross-section giving the angular distribution and energy spectrum are obtained for both reaction types. The statistical multi-step compound cross-sections are symmetric about 90 0 . The classical statistical theory of nuclear reactions is a special limiting case. The cross-section for the statistical multi-step direct reaction consists of a set of convolutions of single-step direct cross-sections. For the many step case it is possible to derive a diffusion equation in momentum space. Application is made to the reaction 181 Ta(p,n) 181 W using the statistical multi-step compound formalism

  18. Forecasting Exchange Rate Density Using Parametric Models: the Case of Brazil

    Directory of Open Access Journals (Sweden)

    Benjamin Miranda Tabak

    2007-06-01

    Full Text Available This paper employs a recently developed parametric technique to obtain density forecasts for the Brazilian exchange rate, using the exchange rate options market. Empirical results suggest that the option market contains useful information about future exchange rate density. These results suggests that density forecasts using options markets may add value for portfolio and risk management, and may be useful for financial regulators to assess financial stability.

  19. Density Forecasts of Crude-Oil Prices Using Option-Implied and ARCH-Type Models

    DEFF Research Database (Denmark)

    Tsiaras, Leonidas; Høg, Esben

      The predictive accuracy of competing crude-oil price forecast densities is investigated for the 1994-2006 period. Moving beyond standard ARCH models that rely exclusively on past returns, we examine the benefits of utilizing the forward-looking information that is embedded in the prices...... as for regions and intervals that are of special interest for the economic agent. We find that non-parametric adjustments of risk-neutral density forecasts perform significantly better than their parametric counterparts. Goodness-of-fit tests and out-of-sample likelihood comparisons favor forecast densities...

  20. Multi-step prediction for influenza outbreak by an adjusted long short-term memory.

    Science.gov (United States)

    Zhang, J; Nawata, K

    2018-05-01

    Influenza results in approximately 3-5 million annual cases of severe illness and 250 000-500 000 deaths. We urgently need an accurate multi-step-ahead time-series forecasting model to help hospitals to perform dynamical assignments of beds to influenza patients for the annually varied influenza season, and aid pharmaceutical companies to formulate a flexible plan of manufacturing vaccine for the yearly different influenza vaccine. In this study, we utilised four different multi-step prediction algorithms in the long short-term memory (LSTM). The result showed that implementing multiple single-output prediction in a six-layer LSTM structure achieved the best accuracy. The mean absolute percentage errors from two- to 13-step-ahead prediction for the US influenza-like illness rates were all LSTM has been applied and refined to perform multi-step-ahead prediction for influenza outbreaks. Hopefully, this modelling methodology can be applied in other countries and therefore help prevent and control influenza worldwide.

  1. AN EVALUATION OF POINT AND DENSITY FORECASTS FOR SELECTED EU FARM GATE MILK PRICES

    Directory of Open Access Journals (Sweden)

    Dennis Bergmann

    2018-01-01

    Full Text Available Fundamental changes to the common agricultural policy (CAP have led to greater market orientation which in turn has resulted in sharply increased variability of EU farm gate milk prices and thus farmers’ income. In this market environment reliable forecasts of farm gate milk prices are extremely important as farmers can make improved decisions with regards to cash flow management and budget preparation. In addition these forecasts may be used in setting fixed priced contracts between dairy farmers and processors thus providing certainty and reducing risk. In this study both point and density forecasts from various time series models for farm gate milk prices in Germany, Ireland and for an average EU price series are evaluated using a rolling window framework. Additionally forecasts of the individual models are combined using different combination schemes. The results of the out of sample evaluation show that ARIMA type models perform well on short forecast horizons (1 to 3 month while the structural time series approach performs well on longer forecast horizons (12 month. Finally combining individual forecasts of different models significantly improves the forecast performance for all forecast horizons.

  2. 48 CFR 15.202 - Advisory multi-step process.

    Science.gov (United States)

    2010-10-01

    ... CONTRACTING METHODS AND CONTRACT TYPES CONTRACTING BY NEGOTIATION Solicitation and Receipt of Proposals and Information 15.202 Advisory multi-step process. (a) The agency may publish a presolicitation notice (see 5.204) that provides a general description of the scope or purpose of the acquisition and invites potential...

  3. DEFORMATION DEPENDENT TUL MULTI-STEP DIRECT MODEL

    International Nuclear Information System (INIS)

    WIENKE, H.; CAPOTE, R.; HERMAN, M.; SIN, M.

    2007-01-01

    The Multi-Step Direct (MSD) module TRISTAN in the nuclear reaction code EMPIRE has been extended in order to account for nuclear deformation. The new formalism was tested in calculations of neutron emission spectra emitted from the 232 Th(n,xn) reaction. These calculations include vibration-rotational Coupled Channels (CC) for the inelastic scattering to low-lying collective levels, ''deformed'' MSD with quadrupole deformation for inelastic scattering to the continuum, Multi-Step Compound (MSC) and Hauser-Feshbach with advanced treatment of the fission channel. Prompt fission neutrons were also calculated. The comparison with experimental data shows clear improvement over the ''spherical'' MSD calculations and JEFF-3.1 and JENDL-3.3 evaluations

  4. Deformation dependent TUL multi-step direct model

    International Nuclear Information System (INIS)

    Wienke, H.; Capote, R.; Herman, M.; Sin, M.

    2008-01-01

    The Multi-Step Direct (MSD) module TRISTAN in the nuclear reaction code EMPIRE has been extended to account for nuclear deformation. The new formalism was tested in calculations of neutron emission spectra emitted from the 232 Th(n,xn) reaction. These calculations include vibration-rotational Coupled Channels (CC) for the inelastic scattering to low-lying collective levels, 'deformed' MSD with quadrupole deformation for inelastic scattering to the continuum, Multi-Step Compound (MSC) and Hauser-Feshbach with advanced treatment of the fission channel. Prompt fission neutrons were also calculated. The comparison with experimental data shows clear improvement over the 'spherical' MSD calculations and JEFF-3.1 and JENDL-3.3 evaluations. (authors)

  5. Bayesian emulation for optimization in multi-step portfolio decisions

    OpenAIRE

    Irie, Kaoru; West, Mike

    2016-01-01

    We discuss the Bayesian emulation approach to computational solution of multi-step portfolio studies in financial time series. "Bayesian emulation for decisions" involves mapping the technical structure of a decision analysis problem to that of Bayesian inference in a purely synthetic "emulating" statistical model. This provides access to standard posterior analytic, simulation and optimization methods that yield indirect solutions of the decision problem. We develop this in time series portf...

  6. Improved perovskite phototransistor prepared using multi-step annealing method

    Science.gov (United States)

    Cao, Mingxuan; Zhang, Yating; Yu, Yu; Yao, Jianquan

    2018-02-01

    Organic-inorganic hybrid perovskites with good intrinsic physical properties have received substantial interest for solar cell and optoelectronic applications. However, perovskite film always suffers from a low carrier mobility due to its structural imperfection including sharp grain boundaries and pinholes, restricting their device performance and application potential. Here we demonstrate a straightforward strategy based on multi-step annealing process to improve the performance of perovskite photodetector. Annealing temperature and duration greatly affects the surface morphology and optoelectrical properties of perovskites which determines the device property of phototransistor. The perovskite films treated with multi-step annealing method tend to form highly uniform, well-crystallized and high surface coverage perovskite film, which exhibit stronger ultraviolet-visible absorption and photoluminescence spectrum compare to the perovskites prepared by conventional one-step annealing process. The field-effect mobilities of perovskite photodetector treated by one-step direct annealing method shows mobility as 0.121 (0.062) cm2V-1s-1 for holes (electrons), which increases to 1.01 (0.54) cm2V-1s-1 for that treated with muti-step slow annealing method. Moreover, the perovskite phototransistors exhibit a fast photoresponse speed of 78 μs. In general, this work focuses on the influence of annealing methods on perovskite phototransistor, instead of obtains best parameters of it. These findings prove that Multi-step annealing methods is feasible to prepared high performance based photodetector.

  7. The statistics of multi-step direct reactions

    International Nuclear Information System (INIS)

    Koning, A.J.; Akkermans, J.M.

    1991-01-01

    We propose a quantum-statistical framework that provides an integrated perspective on the differences and similarities between the many current models for multi-step direct reactions in the continuum. It is argued that to obtain a statistical theory two physically different approaches are conceivable to postulate randomness, respectively called leading-particle statistics and residual-system statistics. We present a new leading-particle statistics theory for multi-step direct reactions. It is shown that the model of Feshbach et al. can be derived as a simplification of this theory and thus can be founded solely upon leading-particle statistics. The models developed by Tamura et al. and Nishioka et al. are based upon residual-system statistics and hence fall into a physically different class of multi-step direct theories, although the resulting cross-section formulae for the important first step are shown to be the same. The widely used semi-classical models such as the generalized exciton model can be interpreted as further phenomenological simplifications of the leading-particle statistics theory. A more comprehensive exposition will appear before long. (author). 32 refs, 4 figs

  8. Comparing the Accuracy of Copula-Based Multivariate Density Forecasts in Selected Regions of Support

    NARCIS (Netherlands)

    C.G.H. Diks (Cees); V. Panchenko (Valentyn); O. Sokolinskiy (Oleg); D.J.C. van Dijk (Dick)

    2013-01-01

    textabstractThis paper develops a testing framework for comparing the predictive accuracy of copula-based multivariate density forecasts, focusing on a specific part of the joint distribution. The test is framed in the context of the Kullback-Leibler Information Criterion, but using (out-of-sample)

  9. Comparing the accuracy of copula-based multivariate density forecasts in selected regions of support

    NARCIS (Netherlands)

    Diks, C.; Panchenko, V.; Sokolinskiy, O.; van Dijk, D.

    2013-01-01

    This paper develops a testing framework for comparing the predictive accuracy of copula-based multivariate density forecasts, focusing on a specific part of the joint distribution. The test is framed in the context of the Kullback-Leibler Information Criterion, but using (out-of-sample) conditional

  10. The multi-step prompt particle emission from fission fragments

    International Nuclear Information System (INIS)

    Zhivopistsev, A.; Oprea, C.; Oprea, I.

    2003-01-01

    The purpose of this work is the study of non-equilibrium high-energy gamma emission from 252 Cf. In the framework of the formalism of statistical multi-step compound processes in nuclear reactions. A relation was found between the shape of the high-energy part of the gamma spectrum and different mechanisms of excitation of the fission fragments. Agreement with experimental data for different groups of fission fragments was obtained. The analysis of the experimental high-energy part of gamma spectra yields information about the mechanism of excitation of fission fragments. The influence of dissipation of the deformation excess on intrinsic excitation of fission fragments was studied. (authors)

  11. Multivariate statistical analysis of a multi-step industrial processes

    DEFF Research Database (Denmark)

    Reinikainen, S.P.; Høskuldsson, Agnar

    2007-01-01

    Monitoring and quality control of industrial processes often produce information on how the data have been obtained. In batch processes, for instance, the process is carried out in stages; some process or control parameters are set at each stage. However, the obtained data might not be utilized...... efficiently, even if this information may reveal significant knowledge about process dynamics or ongoing phenomena. When studying the process data, it may be important to analyse the data in the light of the physical or time-wise development of each process step. In this paper, a unified approach to analyse...... multivariate multi-step processes, where results from each step are used to evaluate future results, is presented. The methods presented are based on Priority PLS Regression. The basic idea is to compute the weights in the regression analysis for given steps, but adjust all data by the resulting score vectors...

  12. In core monitor having multi-step seals

    International Nuclear Information System (INIS)

    Kasai, Makoto; Ono, Susumu.

    1976-01-01

    Purpose: To completely prevent a sensor gas sealed in a pipe from leaking in an in-core neutron detector for use with a bwr type reactor. Constitution: In an in core monitor fabricated by disposing inner and outer electrodes in a housing, forming a layer of neutron conversion material on the outer electrode, filling an ionizing gas within the space between the layer and the inner electrode and, thereafter, attaching an insulation cable and an exhaust pipe respectively by way of insulators to both ends of the housing, the exhaust pipe is sealed in two-steps through pressure bonding using a multi-stepped pincher tool having two pressure bonding bits of a step shape and the outer sealing portion is further welded. The sensor gas sealed in the pipe can thus be prevented from leaking upon pressure bonding and welding. (Horiuchi, T.)

  13. Quantummechanical multi-step direct models for nuclear data applications

    International Nuclear Information System (INIS)

    Koning, A.J.

    1992-10-01

    Various multi-step direct models have been derived and compared on a theoretical level. Subsequently, these models have been implemented in the computer code system KAPSIES, enabling a consistent comparison on the basis of the same set of nuclear parameters and same set of numerical techniques. Continuum cross sections in the energy region between 10 and several hundreds of MeV have successfully been analysed. Both angular distributions and energy spectra can be predicted in an essentially parameter-free manner. It is demonstrated that the quantum-mechanical MSD models (in particular the FKK model) give an improved prediction of pre-equilibrium angular distributions as compared to the experiment-based systematics of Kalbach. This makes KAPSIES a reliable tool for nuclear data applications in the afore-mentioned energy region. (author). 10 refs., 2 figs

  14. In core monitor having multi-step seals

    Energy Technology Data Exchange (ETDEWEB)

    Kasai, M; Ono, S

    1976-12-09

    A method to completely prevent a sensor gas sealed in a pipe from leaking in an in-core neutron detector for use with a BWR type reactor is described. In an in core monitor fabricated by disposing inner and outer electrodes in a housing, forming a layer of neutron conversion material on the outer electrode, filling an ionizing gas within the space between the layer and the inner electrode and, thereafter, attaching an insulation cable and an exhaust pipe respectively by way of insulators to both ends of the housing, the exhaust pipe is sealed in two-steps through pressure bonding using a multi-stepped pincher tool having two pressure bonding bits of a step shape and the outer sealing portion is further welded. The sensor gas sealed in the pipe can thus be prevented from leaking upon pressure bonding and welding.

  15. Comparing Multi-Step IMAC and Multi-Step TiO2 Methods for Phosphopeptide Enrichment

    Science.gov (United States)

    Yue, Xiaoshan; Schunter, Alissa; Hummon, Amanda B.

    2016-01-01

    Phosphopeptide enrichment from complicated peptide mixtures is an essential step for mass spectrometry-based phosphoproteomic studies to reduce sample complexity and ionization suppression effects. Typical methods for enriching phosphopeptides include immobilized metal affinity chromatography (IMAC) or titanium dioxide (TiO2) beads, which have selective affinity and can interact with phosphopeptides. In this study, the IMAC enrichment method was compared with the TiO2 enrichment method, using a multi-step enrichment strategy from whole cell lysate, to evaluate their abilities to enrich for different types of phosphopeptides. The peptide-to-beads ratios were optimized for both IMAC and TiO2 beads. Both IMAC and TiO2 enrichments were performed for three rounds to enable the maximum extraction of phosphopeptides from the whole cell lysates. The phosphopeptides that are unique to IMAC enrichment, unique to TiO2 enrichment, and identified with both IMAC and TiO2 enrichment were analyzed for their characteristics. Both IMAC and TiO2 enriched similar amounts of phosphopeptides with comparable enrichment efficiency. However, phosphopeptides that are unique to IMAC enrichment showed a higher percentage of multi-phosphopeptides, as well as a higher percentage of longer, basic, and hydrophilic phosphopeptides. Also, the IMAC and TiO2 procedures clearly enriched phosphopeptides with different motifs. Finally, further enriching with two rounds of TiO2 from the supernatant after IMAC enrichment, or further enriching with two rounds of IMAC from the supernatant TiO2 enrichment does not fully recover the phosphopeptides that are not identified with the corresponding multi-step enrichment. PMID:26237447

  16. Impact of a high density GPS network on the operational forecast

    Directory of Open Access Journals (Sweden)

    C. Faccani

    2005-01-01

    Full Text Available Global Positioning System Zenith Total Delay (GPS ZTD can provide information about the water vapour in atmosphere. Its assimilation into the analysis used to initialize a model can then improve the weather forecast, giving the right amount of moisture and reducing the model spinup. In the last year, an high density GPS network has been created on the Basilicata region (south of Italy by the Italian Space Agency in the framework of a national project named MAGIC2. MAGIC2 is the Italian follow on of the EC project MAGIC has. Daily operational data assimilation experiments are performed since December 2003. The results show that the assimilation of GPS ZTD improves the forecast especially during the transition from winter to spring even if a no very high model resolution (9km is used.

  17. PEGASUS: a preequilibrium and multi-step evaporation code for neutron cross section calculation

    Energy Technology Data Exchange (ETDEWEB)

    Nakagawa, Tsuneo; Sugi, Teruo [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment; Iijima, Shungo; Nishigori, Takeo

    1999-06-01

    The computer code PEGASUS was developed to calculate neutron-induced reaction cross sections on the basis of the closed form exciton model preequilibrium theory and the multi-step evaporation theory. The cross sections and emitted particle spectra are calculated for the compound elastic scattering, (n,{gamma}), (n,n`), (n,p), (n,{alpha}), (n,d), (n,t), (n,{sup 3}He), (n,2n), (n,n`p), (n,n`{alpha}), (n,n`d), (n,n`t), (n,2p) and (n,3n) reactions. The double differential cross sections of emitted particles are also calculated. The calculated results are written on a magnetic disk in the ENDF format. Parameter files and/or systematics formulas are provided for level densities, mass excess, radiation widths and inverse cross sections so that the input data to the code are made minimum. (author)

  18. Controllable 3D architectures of aligned carbon nanotube arrays by multi-step processes

    Science.gov (United States)

    Huang, Shaoming

    2003-06-01

    An effective way to fabricate large area three-dimensional (3D) aligned CNTs pattern based on pyrolysis of iron(II) phthalocyanine (FePc) by two-step processes is reported. The controllable generation of different lengths and selective growth of the aligned CNT arrays on metal-patterned (e.g., Ag and Au) substrate are the bases for generating such 3D aligned CNTs architectures. By controlling experimental conditions 3D aligned CNT arrays with different lengths/densities and morphologies/structures as well as multi-layered architectures can be fabricated in large scale by multi-step pyrolysis of FePc. These 3D architectures could have interesting properties and be applied for developing novel nanotube-based devices.

  19. Forecasting the density of oil futures returns using model-free implied volatility and high-frequency data

    International Nuclear Information System (INIS)

    Ielpo, Florian; Sevi, Benoit

    2013-09-01

    Forecasting the density of returns is useful for many purposes in finance, such as risk management activities, portfolio choice or derivative security pricing. Existing methods to forecast the density of returns either use prices of the asset of interest or option prices on this same asset. The latter method needs to convert the risk-neutral estimate of the density into a physical measure, which is computationally cumbersome. In this paper, we take the view of a practitioner who observes the implied volatility under the form of an index, namely the recent OVX, to forecast the density of oil futures returns for horizons going from 1 to 60 days. Using the recent methodology in Maheu and McCurdy (2011) to compute density predictions, we compare the performance of time series models using implied volatility and either daily or intra-daily futures prices. Our results indicate that models based on implied volatility deliver significantly better density forecasts at all horizons, which is in line with numerous studies delivering the same evidence for volatility point forecast. (authors)

  20. High-Density Liquid-State Machine Circuitry for Time-Series Forecasting.

    Science.gov (United States)

    Rosselló, Josep L; Alomar, Miquel L; Morro, Antoni; Oliver, Antoni; Canals, Vincent

    2016-08-01

    Spiking neural networks (SNN) are the last neural network generation that try to mimic the real behavior of biological neurons. Although most research in this area is done through software applications, it is in hardware implementations in which the intrinsic parallelism of these computing systems are more efficiently exploited. Liquid state machines (LSM) have arisen as a strategic technique to implement recurrent designs of SNN with a simple learning methodology. In this work, we show a new low-cost methodology to implement high-density LSM by using Boolean gates. The proposed method is based on the use of probabilistic computing concepts to reduce hardware requirements, thus considerably increasing the neuron count per chip. The result is a highly functional system that is applied to high-speed time series forecasting.

  1. Imaging-pathologic correlation of multi-step hepatocarcinogenesis

    International Nuclear Information System (INIS)

    Matsui, O.

    2012-01-01

    Full text: Approximately 80% of Japanese HCC cases are derived from HCV-associated liver cirrhosis and chronic hepatitis, and the remaining less than 20% of patients are HBV positive. Because of the introduction of this surveillance system by periodic ultrasound in these high-risk patients, the size of HCCs firstly detected during 2004 to 2005 (n=16809) was less than 2cm in 35% of all cases, 2.1-5.0 cm 48%, respectively. However, various types of hepatocellular nodules such as dysplastic nodule are also detected during screening procedures. Pathologically, human HCC often develops in a multistep fashion from dysplastic nodule to classic hyper vascular HCC. Therefore, for the early diagnosis of HCC, understanding of the sequential changes of imaging findings in accordance with multi-step hepatocarcinogenseis is important. In addition, to understand the imaging features of various types of HCC is also important for the precise characterization of HCCs. (1) Classification of hepatocellular nodules during multistep hepatocarcinogenesis; According to International Consensus Group for Hepatocellular Neoplasia, these nodules are divided into large regenerative nodule, low grade dysplastic nodule (L-DN), high-grade dysplastic nodule (H-DN), and HCC. In addition, small HCC (less than 2 cm) is divided into early HCC and progressed HCC. Early HCC has a vaguely nodular appearance and is highly well differentiated. (2) Imaging of multistep hepatocarcinogenesis; We revealed that the intranodular blood supply changes in accordance with the progression of human hepatocarcinogenesis from dyspalstic nodule to overt HCC. The intranodular portal supply relative to the surrounding liver parenchyma evaluated by CT during arterial portography (CTAP) is decreased, whereas the intranodular arterial supply evaluated by CT during hepatic arteriography (CTHA) revealed is first decreased during the early stage of hepatocarcinogenesis and then increased in parallel with increasing grade of

  2. Improved Orbit Determination and Forecasts with an Assimilative Tool for Atmospheric Density and Satellite Drag Specification

    Science.gov (United States)

    Crowley, G.; Pilinski, M.; Sutton, E. K.; Codrescu, M.; Fuller-Rowell, T. J.; Matsuo, T.; Fedrizzi, M.; Solomon, S. C.; Qian, L.; Thayer, J. P.

    2016-12-01

    Much as aircraft are affected by the prevailing winds and weather conditions in which they fly, satellites are affected by the variability in density and motion of the near earth space environment. Drastic changes in the neutral density of the thermosphere, caused by geomagnetic storms or other phenomena, result in perturbations of LEO satellite motions through drag on the satellite surfaces. This can lead to difficulties in locating important satellites, temporarily losing track of satellites, and errors when predicting collisions in space. We describe ongoing work to build a comprehensive nowcast and forecast system for specifying the neutral atmospheric state related to orbital drag conditions. The system outputs include neutral density, winds, temperature, composition, and the satellite drag derived from these parameters. This modeling tool is based on several state-of-the-art coupled models of the thermosphere-ionosphere as well as several empirical models running in real-time and uses assimilative techniques to produce a thermospheric nowcast. This software will also produce 72 hour predictions of the global thermosphere-ionosphere system using the nowcast as the initial condition and using near real-time and predicted space weather data and indices as the inputs. Features of this technique include: • Satellite drag specifications with errors lower than current models • Altitude coverage up to 1000km • Background state representation using both first principles and empirical models • Assimilation of satellite drag and other datatypes • Real time capability • Ability to produce 72-hour forecasts of the atmospheric state In this paper, we will summarize the model design and assimilative architecture, and present preliminary validation results. Validation results will be presented in the context of satellite orbit errors and compared with several leading atmospheric models including the High Accuracy Satellite Drag Model, which is currently used

  3. KAPSIES: A program for the calculation of multi-step direct reaction cross sections

    International Nuclear Information System (INIS)

    Koning, A.J.; Akkermans, J.M.

    1994-09-01

    We present a program for the calculation of continuum cross sections, sepctra, angular distributions and analyzing powers according to various quantum-mechanical theories for statistical multi-step direct nuclear reactions. (orig.)

  4. Oil prices. Brownian motion or mean reversion? A study using a one year ahead density forecast criterion

    International Nuclear Information System (INIS)

    Meade, Nigel

    2010-01-01

    For oil related investment appraisal, an accurate description of the evolving uncertainty in the oil price is essential. For example, when using real option theory to value an investment, a density function for the future price of oil is central to the option valuation. The literature on oil pricing offers two views. The arbitrage pricing theory literature for oil suggests geometric Brownian motion and mean reversion models. Empirically driven literature suggests ARMA-GARCH models. In addition to reflecting the volatility of the market, the density function of future prices should also incorporate the uncertainty due to price jumps, a common occurrence in the oil market. In this study, the accuracy of density forecasts for up to a year ahead is the major criterion for a comparison of a range of models of oil price behaviour, both those proposed in the literature and following from data analysis. The Kullbach Leibler information criterion is used to measure the accuracy of density forecasts. Using two crude oil price series, Brent and West Texas Intermediate (WTI) representing the US market, we demonstrate that accurate density forecasts are achievable for up to nearly two years ahead using a mixture of two Gaussians innovation processes with GARCH and no mean reversion. (author)

  5. Oil prices. Brownian motion or mean reversion? A study using a one year ahead density forecast criterion

    Energy Technology Data Exchange (ETDEWEB)

    Meade, Nigel [Imperial College, Business School London (United Kingdom)

    2010-11-15

    For oil related investment appraisal, an accurate description of the evolving uncertainty in the oil price is essential. For example, when using real option theory to value an investment, a density function for the future price of oil is central to the option valuation. The literature on oil pricing offers two views. The arbitrage pricing theory literature for oil suggests geometric Brownian motion and mean reversion models. Empirically driven literature suggests ARMA-GARCH models. In addition to reflecting the volatility of the market, the density function of future prices should also incorporate the uncertainty due to price jumps, a common occurrence in the oil market. In this study, the accuracy of density forecasts for up to a year ahead is the major criterion for a comparison of a range of models of oil price behaviour, both those proposed in the literature and following from data analysis. The Kullbach Leibler information criterion is used to measure the accuracy of density forecasts. Using two crude oil price series, Brent and West Texas Intermediate (WTI) representing the US market, we demonstrate that accurate density forecasts are achievable for up to nearly two years ahead using a mixture of two Gaussians innovation processes with GARCH and no mean reversion. (author)

  6. Multi step FRET among three laser dyes Pyrene, Acriflavine and Rhodamine B

    International Nuclear Information System (INIS)

    Saha, Jaba; Dey, Dibyendu; Roy, Arpan Datta; Bhattacharjee, D.; Hussain, Syed Arshad

    2016-01-01

    Fluorescence Resonance Energy Transfer (FRET) system using three dyes has been demonstrated. It has been observed that multi step energy transfer occurred from Pyrene to Rhodamine B via Acriflavine. Here Acriflavine acts as an antenna to receive energy from Pyrene and transfer the same to Rhodamine B. This multi step FRET system is advantageous compared to the conventional FRET as this can be used to study molecular level interaction beyond conventional FRET distance (1–10 nm) as well as studying multi-branched macromolecules. The introduction of clay enhances the FRET efficiencies among the dye pair, which is an advantage to make the multi step system more useful. Similar approach can be used for increasing FRET efficiencies by using other dyes. - Highlights: • Multi-step FRET occurred from Pyrene (Py) to Rhodamine B (RhB) via Acriflavine (Acf). • Acf acts as an antenna to receive energy from Py and to transfer energy to RhB. • Multi-step FRET can be used to study molecular level interaction beyond 1–10 nm. • Incorporation of nanoclay laponite enhances the energy transfer efficiency.

  7. Effect of One-Step and Multi-Steps Polishing System on Enamel Roughness

    Directory of Open Access Journals (Sweden)

    Cynthia Sumali

    2013-07-01

    Full Text Available Normal 0 false false false MicrosoftInternetExplorer4 The final procedures of orthodontic treatment are bracket debonding and cleaning the remaining adhesive. Multi-step polishing system is the most common method used. The disadvantage of that system is long working time, because of the stages that should be done. Therefore, dental material manufacturer make an improvement to the system, to reduce several stages into one stage only. This new system is known as one-step polishing system. Objective: To compare the effect of one-step and multi-step polishing system on enamel roughness after orthodontic bracket debonding. Methods: Randomized control trial was conducted included twenty-eight maxillary premolar randomized into two polishing system; one-step OptraPol (Ivoclar, Vivadent and multi-step AstroPol (Ivoclar, Vivadent. After bracket debonding, the remaining adhesive on each group was cleaned by subjective polishing system for ninety seconds using low speed handpiece. The enamel roughness was subjected to profilometer, registering two roughness parameters (Ra, Rz. Independent t-test was used to analyze the mean score of enamel roughness in each group. Results: There was no significant difference of enamel roughness between one-step and multi-step polishing system (p>0.005. Conclusion: One-step polishing system can produce a similar enamel roughness to multi-step polishing system after bracket debonding and adhesive cleaning.DOI: 10.14693/jdi.v19i3.136

  8. Incremental Learning of Medical Data for Multi-Step Patient Health Classification

    DEFF Research Database (Denmark)

    Kranen, Philipp; Müller, Emmanuel; Assent, Ira

    2010-01-01

    of textile sensors, body sensors and preprocessing techniques as well as the integration and merging of sensor data in electronic health record systems. Emergency detection on multiple levels will show the benefits of multi-step classification and further enhance the scalability of emergency detection...

  9. Multi-step rearrangement mechanism for acetyl cedrene to the hydrocarbon follower

    DEFF Research Database (Denmark)

    Paknikar, Shashikumar Keshav; Kamounah, Fadhil S.; Hansen, Poul Erik

    2017-01-01

    Conversion of acetyl cedrene (2) to its follower (3) using acetic anhydride and polyphosphoric acid involves a multi-step cationic molecular rearrangement, which is consistent with deuteriation and 1-13C labeling studies of acetyl cedrene. The key step involves cyclopropylcarbinyl cation-cyclopro...

  10. Diffusion coefficients for periodically induced multi-step persistent walks on regular lattices

    International Nuclear Information System (INIS)

    Gilbert, Thomas; Sanders, David P

    2012-01-01

    We present a generalization of our formalism for the computation of diffusion coefficients of multi-step persistent random walks on regular lattices to walks which include zero-displacement states. This situation is especially relevant to systems where tracer particles move across potential barriers as a result of the action of a periodic forcing whose period sets the timescale between transitions. (paper)

  11. Short-term wind power combined forecasting based on error forecast correction

    International Nuclear Information System (INIS)

    Liang, Zhengtang; Liang, Jun; Wang, Chengfu; Dong, Xiaoming; Miao, Xiaofeng

    2016-01-01

    Highlights: • The correlation relationships of short-term wind power forecast errors are studied. • The correlation analysis method of the multi-step forecast errors is proposed. • A strategy selecting the input variables for the error forecast models is proposed. • Several novel combined models based on error forecast correction are proposed. • The combined models have improved the short-term wind power forecasting accuracy. - Abstract: With the increasing contribution of wind power to electric power grids, accurate forecasting of short-term wind power has become particularly valuable for wind farm operators, utility operators and customers. The aim of this study is to investigate the interdependence structure of errors in short-term wind power forecasting that is crucial for building error forecast models with regression learning algorithms to correct predictions and improve final forecasting accuracy. In this paper, several novel short-term wind power combined forecasting models based on error forecast correction are proposed in the one-step ahead, continuous and discontinuous multi-step ahead forecasting modes. First, the correlation relationships of forecast errors of the autoregressive model, the persistence method and the support vector machine model in various forecasting modes have been investigated to determine whether the error forecast models can be established by regression learning algorithms. Second, according to the results of the correlation analysis, the range of input variables is defined and an efficient strategy for selecting the input variables for the error forecast models is proposed. Finally, several combined forecasting models are proposed, in which the error forecast models are based on support vector machine/extreme learning machine, and correct the short-term wind power forecast values. The data collected from a wind farm in Hebei Province, China, are selected as a case study to demonstrate the effectiveness of the proposed

  12. Operational specification and forecasting advances for Dst, LEO thermospheric densities, and aviation radiation dose and dose rate

    Science.gov (United States)

    Tobiska, W. Kent

    Space weather’s effects upon the near-Earth environment are due to dynamic changes in the energy transfer processes from the Sun’s photons, particles, and fields. Of the space environment domains that are affected by space weather, the magnetosphere, thermosphere, and even troposphere are key regions that are affected. Space Environment Technologies (SET) has developed and is producing innovative space weather applications. Key operational systems for providing timely information about the effects of space weather on these domains are SET’s Magnetosphere Alert and Prediction System (MAPS), LEO Alert and Prediction System (LAPS), and Automated Radiation Measurements for Aviation Safety (ARMAS) system. MAPS provides a forecast Dst index out to 6 days through the data-driven, redundant data stream Anemomilos algorithm. Anemomilos uses observational proxies for the magnitude, location, and velocity of solar ejecta events. This forecast index is used by satellite operations to characterize upcoming geomagnetic storms, for example. In addition, an ENLIL/Rice Dst prediction out to several days has also been developed and will be described. LAPS is the SET fully redundant operational system providing recent history, current epoch, and forecast solar and geomagnetic indices for use in operational versions of the JB2008 thermospheric density model. The thermospheric densities produced by that system, driven by the LAPS data, are forecast to 72-hours to provide the global mass densities for satellite operators. ARMAS is a project that has successfully demonstrated the operation of a micro dosimeter on aircraft to capture the real-time radiation environment due to Galactic Cosmic Rays and Solar Energetic Particles. The dose and dose-rates are captured on aircraft, downlinked in real-time via the Iridium satellites, processed on the ground, incorporated into the most recent NAIRAS global radiation climatology data runs, and made available to end users via the web and

  13. Roles of multi-step transfer in fusion process induced by heavy-ion reactions

    International Nuclear Information System (INIS)

    Imanishi, B.; Oertzen, W. von.

    1993-06-01

    In nucleus-nucleus collisions of the systems, 12 C+ 13 C and 13 C+ 16 O- 12 C+ 17 O, the effects of the multi-step transfers and inelastic excitations on the fusion cross sections are investigated in the framework of the coupled-reaction-channel (CRC) method. Strong CRC effects of the multi-step processes are observed. Namely, the valence neutron in 13 C or 17 O plays an important role in the enhancement of the fusion. The potential barrier is effectively lowered with the formation of the covalent molecule of the configuration, 12 C+n+ 12 C or 12 C+n+ 16 O. In the analyses of the system 12 C+ 13 C, however, it is still required to introduce core-core optical potential of lower barrier height in the state of the positive total parity. This could be due to the neck formation with the nucleons contained in two core nuclei. (author)

  14. Multi-step wrought processing of TiAl-based alloys

    International Nuclear Information System (INIS)

    Fuchs, G.E.

    1997-04-01

    Wrought processing will likely be needed for fabrication of a variety of TiAl-based alloy structural components. Laboratory and development work has usually relied on one-step forging to produce test material. Attempts to scale-up TiAl-based alloy processing has indicated that multi-step wrought processing is necessary. The purpose of this study was to examine potential multi-step processing routes, such as two-step isothermal forging and extrusion + isothermal forging. The effects of processing (I/M versus P/M), intermediate recrystallization heat treatments and processing route on the tensile and creep properties of Ti-48Al-2Nb-2Cr alloys were examined. The results of the testing were then compared to samples from the same heats of materials processed by one-step routes. Finally, by evaluating the effect of processing on microstructure and properties, optimized and potentially lower cost processing routes could be identified

  15. Multi-step-prediction of chaotic time series based on co-evolutionary recurrent neural network

    International Nuclear Information System (INIS)

    Ma Qianli; Zheng Qilun; Peng Hong; Qin Jiangwei; Zhong Tanwei

    2008-01-01

    This paper proposes a co-evolutionary recurrent neural network (CERNN) for the multi-step-prediction of chaotic time series, it estimates the proper parameters of phase space reconstruction and optimizes the structure of recurrent neural networks by co-evolutionary strategy. The searching space was separated into two subspaces and the individuals are trained in a parallel computational procedure. It can dynamically combine the embedding method with the capability of recurrent neural network to incorporate past experience due to internal recurrence. The effectiveness of CERNN is evaluated by using three benchmark chaotic time series data sets: the Lorenz series, Mackey-Glass series and real-world sun spot series. The simulation results show that CERNN improves the performances of multi-step-prediction of chaotic time series

  16. Multi-Step Deep Reactive Ion Etching Fabrication Process for Silicon-Based Terahertz Components

    Science.gov (United States)

    Jung-Kubiak, Cecile (Inventor); Reck, Theodore (Inventor); Chattopadhyay, Goutam (Inventor); Perez, Jose Vicente Siles (Inventor); Lin, Robert H. (Inventor); Mehdi, Imran (Inventor); Lee, Choonsup (Inventor); Cooper, Ken B. (Inventor); Peralta, Alejandro (Inventor)

    2016-01-01

    A multi-step silicon etching process has been developed to fabricate silicon-based terahertz (THz) waveguide components. This technique provides precise dimensional control across multiple etch depths with batch processing capabilities. Nonlinear and passive components such as mixers and multipliers waveguides, hybrids, OMTs and twists have been fabricated and integrated into a small silicon package. This fabrication technique enables a wafer-stacking architecture to provide ultra-compact multi-pixel receiver front-ends in the THz range.

  17. The average angular distribution of emitted particles in multi-step compound processes

    International Nuclear Information System (INIS)

    Bonetti, R.; Carlson, B.V.; Hussein, M.S.; Toledo, A.S. de

    1983-05-01

    A simple model for the differential cross-section that describes the angular distribution of emitted particles in heavy-ion induced multi-step compound reactions, is constructed. It is suggested that through a careful analysis of the deviations of the experimental data from the pure Hauser-Feshbach behaviour may shed light on the physical nature of the pre-compound, heavy-ion configuration. (Author) [pt

  18. Overcoming the hurdles of multi-step targeting (MST) for effective radioimmunotherapy of solid tumors

    International Nuclear Information System (INIS)

    Larson, Steven M.; Cheung, Nai-Kong

    2009-01-01

    The 4 specific aims of this project are: (1) Optimization of MST to increase tumor uptake; (2) Antigen heterogeneity; (3) Characterization and reduction of renal uptake; and (4) Validation in vivo of optimized MST targeted therapy. This proposal focussed upon optimizing multistep immune targeting strategies for the treatment of cancer. Two multi-step targeting constructs were explored during this funding period: (1) anti-Tag-72 and (2) anti-GD2.

  19. Photon Production through Multi-step Processes Important in Nuclear Fluorescence Experiments

    International Nuclear Information System (INIS)

    Hagmann, C; Pruet, J

    2006-01-01

    The authors present calculations describing the production of photons through multi-step processes occurring when a beam of gamma rays interacts with a macroscopic material. These processes involve the creation of energetic electrons through Compton scattering, photo-absorption and pair production, the subsequent scattering of these electrons, and the creation of energetic photons occurring as these electrons are slowed through Bremsstrahlung emission. Unlike single Compton collisions, during which an energetic photon that is scattered through a large angle loses most of its energy, these multi-step processes result in a sizable flux of energetic photons traveling at large angles relative to an incident photon beam. These multi-step processes are also a key background in experiments that measure nuclear resonance fluorescence by shining photons on a thin foil and observing the spectrum of back-scattered photons. Effective cross sections describing the production of backscattered photons are presented in a tabular form that allows simple estimates of backgrounds expected in a variety of experiments. Incident photons with energies between 0.5 MeV and 8 MeV are considered. These calculations of effective cross sections may be useful for those designing NRF experiments or systems that detect specific isotopes in well-shielded environments through observation of resonance fluorescence

  20. Density forecasts of crude-oil prices using option-implied and ARCH-type models

    DEFF Research Database (Denmark)

    Høg, Esben; Tsiaras, Leonicas

    2011-01-01

    of derivative contracts. Risk-neutral densities, obtained from panels of crude-oil option prices, are adjusted to reflect real-world risks using either a parametric or a non-parametric calibration approach. The relative performance of the models is evaluated for the entire support of the density, as well...... obtained by option prices and non-parametric calibration methods over those constructed using historical returns and simulated ARCH processes. © 2010 Wiley Periodicals, Inc. Jrl Fut Mark...

  1. Evaluation of accuracy in implant site preparation performed in single- or multi-step drilling procedures.

    Science.gov (United States)

    Marheineke, Nadine; Scherer, Uta; Rücker, Martin; von See, Constantin; Rahlf, Björn; Gellrich, Nils-Claudius; Stoetzer, Marcus

    2018-06-01

    Dental implant failure and insufficient osseointegration are proven results of mechanical and thermal damage during the surgery process. We herein performed a comparative study of a less invasive single-step drilling preparation protocol and a conventional multiple drilling sequence. Accuracy of drilling holes was precisely analyzed and the influence of different levels of expertise of the handlers and additional use of drill template guidance was evaluated. Six experimental groups, deployed in an osseous study model, were representing template-guided and freehanded drilling actions in a stepwise drilling procedure in comparison to a single-drill protocol. Each experimental condition was studied by the drilling actions of respectively three persons without surgical knowledge as well as three highly experienced oral surgeons. Drilling actions were performed and diameters were recorded with a precision measuring instrument. Less experienced operators were able to significantly increase the drilling accuracy using a guiding template, especially when multi-step preparations are performed. Improved accuracy without template guidance was observed when experienced operators were executing single-step versus multi-step technique. Single-step drilling protocols have shown to produce more accurate results than multi-step procedures. The outcome of any protocol can be further improved by use of guiding templates. Operator experience can be a contributing factor. Single-step preparations are less invasive and are promoting osseointegration. Even highly experienced surgeons are achieving higher levels of accuracy by combining this technique with template guidance. Hereby template guidance enables a reduction of hands-on time and side effects during surgery and lead to a more predictable clinical diameter.

  2. Optimization of a Multi-Step Procedure for Isolation of Chicken Bone Collagen

    OpenAIRE

    Cansu, ?mran; Boran, G?khan

    2015-01-01

    Chicken bone is not adequately utilized despite its high nutritional value and protein content. Although not a common raw material, chicken bone can be used in many different ways besides manufacturing of collagen products. In this study, a multi-step procedure was optimized to isolate chicken bone collagen for higher yield and quality for manufacture of collagen products. The chemical composition of chicken bone was 2.9% nitrogen corresponding to about 15.6% protein, 9.5% fat, 14.7% mineral ...

  3. Ensemble Assimilation Using Three First-Principles Thermospheric Models as a Tool for 72-hour Density and Satellite Drag Forecasts

    Science.gov (United States)

    Hunton, D.; Pilinski, M.; Crowley, G.; Azeem, I.; Fuller-Rowell, T. J.; Matsuo, T.; Fedrizzi, M.; Solomon, S. C.; Qian, L.; Thayer, J. P.; Codrescu, M.

    2014-12-01

    Much as aircraft are affected by the prevailing winds and weather conditions in which they fly, satellites are affected by variability in the density and motion of the near earth space environment. Drastic changes in the neutral density of the thermosphere, caused by geomagnetic storms or other phenomena, result in perturbations of satellite motions through drag on the satellite surfaces. This can lead to difficulties in locating important satellites, temporarily losing track of satellites, and errors when predicting collisions in space. As the population of satellites in Earth orbit grows, higher space-weather prediction accuracy is required for critical missions, such as accurate catalog maintenance, collision avoidance for manned and unmanned space flight, reentry prediction, satellite lifetime prediction, defining on-board fuel requirements, and satellite attitude dynamics. We describe ongoing work to build a comprehensive nowcast and forecast system for neutral density, winds, temperature, composition, and satellite drag. This modeling tool will be called the Atmospheric Density Assimilation Model (ADAM). It will be based on three state-of-the-art coupled models of the thermosphere-ionosphere running in real-time, using assimilative techniques to produce a thermospheric nowcast. It will also produce, in realtime, 72-hour predictions of the global thermosphere-ionosphere system using the nowcast as the initial condition. We will review the requirements for the ADAM system, the underlying full-physics models, the plethora of input options available to drive the models, a feasibility study showing the performance of first-principles models as it pertains to satellite-drag operational needs, and review challenges in designing an assimilative space-weather prediction model. The performance of the ensemble assimilative model is expected to exceed the performance of current empirical and assimilative density models.

  4. Impact of user influence on information multi-step communication in a micro-blog

    International Nuclear Information System (INIS)

    Wu Yue; Hu Yong; He Xiao-Hai; Deng Ken

    2014-01-01

    User influence is generally considered as one of the most critical factors that affect information cascading spreading. Based on this common assumption, this paper proposes a theoretical model to examine user influence on the information multi-step communication in a micro-blog. The multi-steps of information communication are divided into first-step and non-first-step, and user influence is classified into five dimensions. Actual data from the Sina micro-blog is collected to construct the model by means of an approach based on structural equations that uses the Partial Least Squares (PLS) technique. Our experimental results indicate that the dimensions of the number of fans and their authority significantly impact the information of first-step communication. Leader rank has a positive impact on both first-step and non-first-step communication. Moreover, global centrality and weight of friends are positively related to the information non-first-step communication, but authority is found to have much less relation to it

  5. A multi-step electrochemical etching process for a three-dimensional micro probe array

    International Nuclear Information System (INIS)

    Kim, Yoonji; Youn, Sechan; Cho, Young-Ho; Park, HoJoon; Chang, Byeung Gyu; Oh, Yong Soo

    2011-01-01

    We present a simple, fast, and cost-effective process for three-dimensional (3D) micro probe array fabrication using multi-step electrochemical metal foil etching. Compared to the previous electroplating (add-on) process, the present electrochemical (subtractive) process results in well-controlled material properties of the metallic microstructures. In the experimental study, we describe the single-step and multi-step electrochemical aluminum foil etching processes. In the single-step process, the depth etch rate and the bias etch rate of an aluminum foil have been measured as 1.50 ± 0.10 and 0.77 ± 0.03 µm min −1 , respectively. On the basis of the single-step process results, we have designed and performed the two-step electrochemical etching process for the 3D micro probe array fabrication. The fabricated 3D micro probe array shows the vertical and lateral fabrication errors of 15.5 ± 5.8% and 3.3 ± 0.9%, respectively, with the surface roughness of 37.4 ± 9.6 nm. The contact force and the contact resistance of the 3D micro probe array have been measured to be 24.30 ± 0.98 mN and 2.27 ± 0.11 Ω, respectively, for an overdrive of 49.12 ± 1.25 µm.

  6. Dissolvable fluidic time delays for programming multi-step assays in instrument-free paper diagnostics.

    Science.gov (United States)

    Lutz, Barry; Liang, Tinny; Fu, Elain; Ramachandran, Sujatha; Kauffman, Peter; Yager, Paul

    2013-07-21

    Lateral flow tests (LFTs) are an ingenious format for rapid and easy-to-use diagnostics, but they are fundamentally limited to assay chemistries that can be reduced to a single chemical step. In contrast, most laboratory diagnostic assays rely on multiple timed steps carried out by a human or a machine. Here, we use dissolvable sugar applied to paper to create programmable flow delays and present a paper network topology that uses these time delays to program automated multi-step fluidic protocols. Solutions of sucrose at different concentrations (10-70% of saturation) were added to paper strips and dried to create fluidic time delays spanning minutes to nearly an hour. A simple folding card format employing sugar delays was shown to automate a four-step fluidic process initiated by a single user activation step (folding the card); this device was used to perform a signal-amplified sandwich immunoassay for a diagnostic biomarker for malaria. The cards are capable of automating multi-step assay protocols normally used in laboratories, but in a rapid, low-cost, and easy-to-use format.

  7. Electron-density critical points analysis and catastrophe theory to forecast structure instability in periodic solids.

    Science.gov (United States)

    Merli, Marcello; Pavese, Alessandro

    2018-03-01

    The critical points analysis of electron density, i.e. ρ(x), from ab initio calculations is used in combination with the catastrophe theory to show a correlation between ρ(x) topology and the appearance of instability that may lead to transformations of crystal structures, as a function of pressure/temperature. In particular, this study focuses on the evolution of coalescing non-degenerate critical points, i.e. such that ∇ρ(x c ) = 0 and λ 1 , λ 2 , λ 3 ≠ 0 [λ being the eigenvalues of the Hessian of ρ(x) at x c ], towards degenerate critical points, i.e. ∇ρ(x c ) = 0 and at least one λ equal to zero. The catastrophe theory formalism provides a mathematical tool to model ρ(x) in the neighbourhood of x c and allows one to rationalize the occurrence of instability in terms of electron-density topology and Gibbs energy. The phase/state transitions that TiO 2 (rutile structure), MgO (periclase structure) and Al 2 O 3 (corundum structure) undergo because of pressure and/or temperature are here discussed. An agreement of 3-5% is observed between the theoretical model and experimental pressure/temperature of transformation.

  8. Variation of nanopore diameter along porous anodic alumina channels by multi-step anodization.

    Science.gov (United States)

    Lee, Kwang Hong; Lim, Xin Yuan; Wai, Kah Wing; Romanato, Filippo; Wong, Chee Cheong

    2011-02-01

    In order to form tapered nanocapillaries, we investigated a method to vary the nanopore diameter along the porous anodic alumina (PAA) channels using multi-step anodization. By anodizing the aluminum in either single acid (H3PO4) or multi-acid (H2SO4, oxalic acid and H3PO4) with increasing or decreasing voltage, the diameter of the nanopore along the PAA channel can be varied systematically corresponding to the applied voltages. The pore size along the channel can be enlarged or shrunken in the range of 20 nm to 200 nm. Structural engineering of the template along the film growth direction can be achieved by deliberately designing a suitable voltage and electrolyte together with anodization time.

  9. Cross-cultural adaptation of instruments assessing breastfeeding determinants: a multi-step approach

    Science.gov (United States)

    2014-01-01

    Background Cross-cultural adaptation is a necessary process to effectively use existing instruments in other cultural and language settings. The process of cross-culturally adapting, including translation, of existing instruments is considered a critical set to establishing a meaningful instrument for use in another setting. Using a multi-step approach is considered best practice in achieving cultural and semantic equivalence of the adapted version. We aimed to ensure the content validity of our instruments in the cultural context of KwaZulu-Natal, South Africa. Methods The Iowa Infant Feeding Attitudes Scale, Breastfeeding Self-Efficacy Scale-Short Form and additional items comprise our consolidated instrument, which was cross-culturally adapted utilizing a multi-step approach during August 2012. Cross-cultural adaptation was achieved through steps to maintain content validity and attain semantic equivalence in the target version. Specifically, Lynn’s recommendation to apply an item-level content validity index score was followed. The revised instrument was translated and back-translated. To ensure semantic equivalence, Brislin’s back-translation approach was utilized followed by the committee review to address any discrepancies that emerged from translation. Results Our consolidated instrument was adapted to be culturally relevant and translated to yield more reliable and valid results for use in our larger research study to measure infant feeding determinants effectively in our target cultural context. Conclusions Undertaking rigorous steps to effectively ensure cross-cultural adaptation increases our confidence that the conclusions we make based on our self-report instrument(s) will be stronger. In this way, our aim to achieve strong cross-cultural adaptation of our consolidated instruments was achieved while also providing a clear framework for other researchers choosing to utilize existing instruments for work in other cultural, geographic and population

  10. A Dimensionality Reduction-Based Multi-Step Clustering Method for Robust Vessel Trajectory Analysis

    Directory of Open Access Journals (Sweden)

    Huanhuan Li

    2017-08-01

    Full Text Available The Shipboard Automatic Identification System (AIS is crucial for navigation safety and maritime surveillance, data mining and pattern analysis of AIS information have attracted considerable attention in terms of both basic research and practical applications. Clustering of spatio-temporal AIS trajectories can be used to identify abnormal patterns and mine customary route data for transportation safety. Thus, the capacities of navigation safety and maritime traffic monitoring could be enhanced correspondingly. However, trajectory clustering is often sensitive to undesirable outliers and is essentially more complex compared with traditional point clustering. To overcome this limitation, a multi-step trajectory clustering method is proposed in this paper for robust AIS trajectory clustering. In particular, the Dynamic Time Warping (DTW, a similarity measurement method, is introduced in the first step to measure the distances between different trajectories. The calculated distances, inversely proportional to the similarities, constitute a distance matrix in the second step. Furthermore, as a widely-used dimensional reduction method, Principal Component Analysis (PCA is exploited to decompose the obtained distance matrix. In particular, the top k principal components with above 95% accumulative contribution rate are extracted by PCA, and the number of the centers k is chosen. The k centers are found by the improved center automatically selection algorithm. In the last step, the improved center clustering algorithm with k clusters is implemented on the distance matrix to achieve the final AIS trajectory clustering results. In order to improve the accuracy of the proposed multi-step clustering algorithm, an automatic algorithm for choosing the k clusters is developed according to the similarity distance. Numerous experiments on realistic AIS trajectory datasets in the bridge area waterway and Mississippi River have been implemented to compare our

  11. A Dimensionality Reduction-Based Multi-Step Clustering Method for Robust Vessel Trajectory Analysis.

    Science.gov (United States)

    Li, Huanhuan; Liu, Jingxian; Liu, Ryan Wen; Xiong, Naixue; Wu, Kefeng; Kim, Tai-Hoon

    2017-08-04

    The Shipboard Automatic Identification System (AIS) is crucial for navigation safety and maritime surveillance, data mining and pattern analysis of AIS information have attracted considerable attention in terms of both basic research and practical applications. Clustering of spatio-temporal AIS trajectories can be used to identify abnormal patterns and mine customary route data for transportation safety. Thus, the capacities of navigation safety and maritime traffic monitoring could be enhanced correspondingly. However, trajectory clustering is often sensitive to undesirable outliers and is essentially more complex compared with traditional point clustering. To overcome this limitation, a multi-step trajectory clustering method is proposed in this paper for robust AIS trajectory clustering. In particular, the Dynamic Time Warping (DTW), a similarity measurement method, is introduced in the first step to measure the distances between different trajectories. The calculated distances, inversely proportional to the similarities, constitute a distance matrix in the second step. Furthermore, as a widely-used dimensional reduction method, Principal Component Analysis (PCA) is exploited to decompose the obtained distance matrix. In particular, the top k principal components with above 95% accumulative contribution rate are extracted by PCA, and the number of the centers k is chosen. The k centers are found by the improved center automatically selection algorithm. In the last step, the improved center clustering algorithm with k clusters is implemented on the distance matrix to achieve the final AIS trajectory clustering results. In order to improve the accuracy of the proposed multi-step clustering algorithm, an automatic algorithm for choosing the k clusters is developed according to the similarity distance. Numerous experiments on realistic AIS trajectory datasets in the bridge area waterway and Mississippi River have been implemented to compare our proposed method with

  12. Evaluation and optimisation of phenomenological multi-step soot model for spray combustion under diesel engine-like operating conditions

    Science.gov (United States)

    Pang, Kar Mun; Jangi, Mehdi; Bai, Xue-Song; Schramm, Jesper

    2015-05-01

    In this work, a two-dimensional computational fluid dynamics study is reported of an n-heptane combustion event and the associated soot formation process in a constant volume combustion chamber. The key interest here is to evaluate the sensitivity of the chemical kinetics and submodels of a semi-empirical soot model in predicting the associated events. Numerical computation is performed using an open-source code and a chemistry coordinate mapping approach is used to expedite the calculation. A library consisting of various phenomenological multi-step soot models is constructed and integrated with the spray combustion solver. Prior to the soot modelling, combustion simulations are carried out. Numerical results show that the ignition delay times and lift-off lengths exhibit good agreement with the experimental measurements across a wide range of operating conditions, apart from those in the cases with ambient temperature lower than 850 K. The variation of the soot precursor production with respect to the change of ambient oxygen levels qualitatively agrees with that of the conceptual models when the skeletal n-heptane mechanism is integrated with a reduced pyrene chemistry. Subsequently, a comprehensive sensitivity analysis is carried out to appraise the existing soot formation and oxidation submodels. It is revealed that the soot formation is captured when the surface growth rate is calculated using a square root function of the soot specific surface area and when a pressure-dependent model constant is considered. An optimised soot model is then proposed based on the knowledge gained through this exercise. With the implementation of optimised model, the simulated soot onset and transport phenomena before reaching quasi-steady state agree reasonably well with the experimental observation. Also, variation of spatial soot distribution and soot mass produced at oxygen molar fractions ranging from 10.0 to 21.0% for both low and high density conditions are reproduced.

  13. Baking Powder Actuated Centrifugo-Pneumatic Valving for Automation of Multi-Step Bioassays

    Directory of Open Access Journals (Sweden)

    David J. Kinahan

    2016-10-01

    Full Text Available We report a new flow control method for centrifugal microfluidic systems; CO2 is released from on-board stored baking powder upon contact with an ancillary liquid. The elevated pressure generated drives the sample into a dead-end pneumatic chamber sealed by a dissolvable film (DF. This liquid incursion wets and dissolves the DF, thus opening the valve. The activation pressure of the DF valve can be tuned by the geometry of the channel upstream of the DF membrane. Through pneumatic coupling with properly dimensioned disc architecture, we established serial cascading of valves, even at a constant spin rate. Similarly, we demonstrate sequential actuation of valves by dividing the disc into a number of distinct pneumatic chambers (separated by DF membranes. Opening these DFs, typically through arrival of a liquid to that location on a disc, permits pressurization of these chambers. This barrier-based scheme provides robust and strictly ordered valve actuation, which is demonstrated by the automation of a multi-step/multi-reagent DNA-based hybridization assay.

  14. Active Mycobacterium Infection Due to Intramuscular BCG Administration Following Multi-Steps Medication Errors

    Directory of Open Access Journals (Sweden)

    MohammadReza Rafati

    2015-10-01

    Full Text Available Bacillus Calmette-Guérin (BCG is indicated for treatment of primary or relapsing flat urothelial cell carcinoma in situ (CIS of the urinary bladder. Disseminated infectious complications occasionally occur due to BCG as a vaccine and intravesical therapy.  Intramuscular (IM or Intravenous (IV administrations of BCG are rare medication errors which are more probable to produce systemic infections. This report presents 13 years old case that several steps medication errors occurred consequently from physician handwriting, pharmacy dispensing, nursing administration and patient family. The physician wrote βHCG instead of HCG in the prescription. βHCG was read as BCG by the pharmacy staff and 6 vials of intravesical BCG were administered IM twice a week for 3 consecutive weeks. The patient experienced fever and chills after each injection, but he was admitted 2 months after first IM administration of BCG with fever and pancytopenia. Unfortunately four month after using drug, during second admission duo to cellulitis at the sites of BCG injection the physicians diagnosed the medication error. Using handwritten prescription and inappropriate abbreviations, spending inadequate time for taking a brief medical history in pharmacy, lack of verifying name, dose and wrote before medication administration and lack of considering medication error as an important differential diagnosis had roles to occur this multi-steps medication error.

  15. Shutdown Dose Rate Analysis Using the Multi-Step CADIS Method

    International Nuclear Information System (INIS)

    Ibrahim, Ahmad M.; Peplow, Douglas E.; Peterson, Joshua L.; Grove, Robert E.

    2015-01-01

    The Multi-Step Consistent Adjoint Driven Importance Sampling (MS-CADIS) hybrid Monte Carlo (MC)/deterministic radiation transport method was proposed to speed up the shutdown dose rate (SDDR) neutron MC calculation using an importance function that represents the neutron importance to the final SDDR. This work applied the MS-CADIS method to the ITER SDDR benchmark problem. The MS-CADIS method was also used to calculate the SDDR uncertainty resulting from uncertainties in the MC neutron calculation and to determine the degree of undersampling in SDDR calculations because of the limited ability of the MC method to tally detailed spatial and energy distributions. The analysis that used the ITER benchmark problem compared the efficiency of the MS-CADIS method to the traditional approach of using global MC variance reduction techniques for speeding up SDDR neutron MC calculation. Compared to the standard Forward-Weighted-CADIS (FW-CADIS) method, the MS-CADIS method increased the efficiency of the SDDR neutron MC calculation by 69%. The MS-CADIS method also increased the fraction of nonzero scoring mesh tally elements in the space-energy regions of high importance to the final SDDR

  16. Exact free vibration of multi-step Timoshenko beam system with several attachments

    Science.gov (United States)

    Farghaly, S. H.; El-Sayed, T. A.

    2016-05-01

    This paper deals with the analysis of the natural frequencies, mode shapes of an axially loaded multi-step Timoshenko beam combined system carrying several attachments. The influence of system design and the proposed sub-system non-dimensional parameters on the combined system characteristics are the major part of this investigation. The effect of material properties, rotary inertia and shear deformation of the beam system for each span are included. The end masses are elastically supported against rotation and translation at an offset point from the point of attachment. A sub-system having two degrees of freedom is located at the beam ends and at any of the intermediate stations and acts as a support and/or a suspension. The boundary conditions of the ordinary differential equation governing the lateral deflections and slope due to bending of the beam system including the shear force term, due to the sub-system, have been formulated. Exact global coefficient matrices for the combined modal frequencies, the modal shape and for the discrete sub-system have been derived. Based on these formulae, detailed parametric studies of the combined system are carried out. The applied mathematical model is valid for wide range of applications especially in mechanical, naval and structural engineering fields.

  17. Data-based control of a multi-step forming process

    Science.gov (United States)

    Schulte, R.; Frey, P.; Hildenbrand, P.; Vogel, M.; Betz, C.; Lechner, M.; Merklein, M.

    2017-09-01

    The fourth industrial revolution represents a new stage in the organization and management of the entire value chain. However, concerning the field of forming technology, the fourth industrial revolution has only arrived gradually until now. In order to make a valuable contribution to the digital factory the controlling of a multistage forming process was investigated. Within the framework of the investigation, an abstracted and transferable model is used to outline which data have to be collected, how an interface between the different forming machines can be designed tangible and which control tasks must be fulfilled. The goal of this investigation was to control the subsequent process step based on the data recorded in the first step. The investigated process chain links various metal forming processes, which are typical elements of a multi-step forming process. Data recorded in the first step of the process chain is analyzed and processed for an improved process control of the subsequent process. On the basis of the gained scientific knowledge, it is possible to make forming operations more robust and at the same time more flexible, and thus create the fundament for linking various production processes in an efficient way.

  18. Comparison of microbial community shifts in two parallel multi-step drinking water treatment processes.

    Science.gov (United States)

    Xu, Jiajiong; Tang, Wei; Ma, Jun; Wang, Hong

    2017-07-01

    Drinking water treatment processes remove undesirable chemicals and microorganisms from source water, which is vital to public health protection. The purpose of this study was to investigate the effects of treatment processes and configuration on the microbiome by comparing microbial community shifts in two series of different treatment processes operated in parallel within a full-scale drinking water treatment plant (DWTP) in Southeast China. Illumina sequencing of 16S rRNA genes of water samples demonstrated little effect of coagulation/sedimentation and pre-oxidation steps on bacterial communities, in contrast to dramatic and concurrent microbial community shifts during ozonation, granular activated carbon treatment, sand filtration, and disinfection for both series. A large number of unique operational taxonomic units (OTUs) at these four treatment steps further illustrated their strong shaping power towards the drinking water microbial communities. Interestingly, multidimensional scaling analysis revealed tight clustering of biofilm samples collected from different treatment steps, with Nitrospira, the nitrite-oxidizing bacteria, noted at higher relative abundances in biofilm compared to water samples. Overall, this study provides a snapshot of step-to-step microbial evolvement in multi-step drinking water treatment systems, and the results provide insight to control and manipulation of the drinking water microbiome via optimization of DWTP design and operation.

  19. Multi-step process for concentrating magnetic particles in waste sludges

    Science.gov (United States)

    Watson, John L.

    1990-01-01

    This invention involves a multi-step, multi-force process for dewatering sludges which have high concentrations of magnetic particles, such as waste sludges generated during steelmaking. This series of processing steps involves (1) mixing a chemical flocculating agent with the sludge; (2) allowing the particles to aggregate under non-turbulent conditions; (3) subjecting the mixture to a magnetic field which will pull the magnetic aggregates in a selected direction, causing them to form a compacted sludge; (4) preferably, decanting the clarified liquid from the compacted sludge; and (5) using filtration to convert the compacted sludge into a cake having a very high solids content. Steps 2 and 3 should be performed simultaneously. This reduces the treatment time and increases the extent of flocculation and the effectiveness of the process. As partially formed aggregates with active flocculating groups are pulled through the mixture by the magnetic field, they will contact other particles and form larger aggregates. This process can increase the solids concentration of steelmaking sludges in an efficient and economic manner, thereby accomplishing either of two goals: (a) it can convert hazardous wastes into economic resources for recycling as furnace feed material, or (b) it can dramatically reduce the volume of waste material which must be disposed.

  20. Self-Regulated Strategy Development Instruction for Teaching Multi-Step Equations to Middle School Students Struggling in Math

    Science.gov (United States)

    Cuenca-Carlino, Yojanna; Freeman-Green, Shaqwana; Stephenson, Grant W.; Hauth, Clara

    2016-01-01

    Six middle school students identified as having a specific learning disability or at risk for mathematical difficulties were taught how to solve multi-step equations by using the self-regulated strategy development (SRSD) model of instruction. A multiple-probe-across-pairs design was used to evaluate instructional effects. Instruction was provided…

  1. Application of multi-step direct reaction theory to 14 MeV neutron reaction, 3 (n,. cap alpha. )

    Energy Technology Data Exchange (ETDEWEB)

    Kumabe, I.; Matoba, M.; Fukuda, K. [Kyushu Univ., Fukuoka (Japan). Faculty of Engineering; Ikegami, H.; Muraoka, M [eds.

    1980-01-01

    Multi-step direct-reaction theory proposed by Tamura et al. has been applied to continuous spectra of the 14 MeV (n, ..cap alpha..) reaction with some modifications. Calculated results reproduce well the experimental energy and angular distributions of the 14 MeV (n, ..cap alpha..) reactions.

  2. Metaphase II oocytes from human unilaminar follicles grown in a multi-step culture system.

    Science.gov (United States)

    McLaughlin, M; Albertini, D F; Wallace, W H B; Anderson, R A; Telfer, E E

    2018-03-01

    Can complete oocyte development be achieved from human ovarian tissue containing primordial/unilaminar follicles and grown in vitro in a multi-step culture to meiotic maturation demonstrated by the formation of polar bodies and a Metaphase II spindle? Development of human oocytes from primordial/unilaminar stages to resumption of meiosis (Metaphase II) and emission of a polar body was achieved within a serum free multi-step culture system. Complete development of oocytes in vitro has been achieved in mouse, where in vitro grown (IVG) oocytes from primordial follicles have resulted in the production of live offspring. Human oocytes have been grown in vitro from the secondary/multi-laminar stage to obtain fully grown oocytes capable of meiotic maturation. However, there are no reports of a culture system supporting complete growth from the earliest stages of human follicle development through to Metaphase II. Ovarian cortical biopsies were obtained with informed consent from women undergoing elective caesarean section (mean age: 30.7 ± 1.7; range: 25-39 years, n = 10). Laboratory setting. Ovarian biopsies were dissected into thin strips, and after removal of growing follicles were cultured in serum free medium for 8 days (Step 1). At the end of this period secondary/multi-laminar follicles were dissected from the strips and intact follicles 100-150 μm in diameter were selected for further culture. Isolated follicles were cultured individually in serum free medium in the presence of 100 ng/ml of human recombinant Activin A (Step 2). Individual follicles were monitored and after 8 days, cumulus oocyte complexes (COCs) were retrieved by gentle pressure on the cultured follicles. Complexes with complete cumulus and adherent mural granulosa cells were selected and cultured in the presence of Activin A and FSH on membranes for a further 4 days (Step 3). At the end of Step 3, complexes containing oocytes >100 μm diameter were selected for IVM in SAGE medium (Step 4) then

  3. Multi-step intramolecular excitation energy transfer in dendritic pyrene-phosphorus(V)porphyrin heptads

    International Nuclear Information System (INIS)

    Hirakawa, Kazutaka; Segawa, Hiroshi

    2016-01-01

    Dendritic heptad molecules in which four pyrenyl groups are connected at the central phosphorus atom of the edge-porphyrins of the center-to-edge type porphyrin trimers were synthesized to investigate a multi-step excitation energy transfer. As the central energy acceptor, two types porphyrins which one was phosphorus(V)tetraphenylporphyrin (H2) and another was its derivative substituted by butoxy groups at four para-position of meso-phenyl groups (H1) were used. In the photoexcited state of the pyrene units, the excitation energy transfer to the central-porphyrin unit was observed in toluene. The excitation energy transfer is considered to be through two pathways; one is a stepwise pathway through the edge-porphyrin unit and another is a direct excitation energy transfer to the central porphyrin. The direct excitation energy transfer from pyrenes to the edge-porphyrin and central-porphyrin were observed in the case for H1. From the excited state of the edge-porphyrins, the excitation energy transfer to the central-porphyrin occurs in the H1 case. In the H2 case, the excitation energy of central-porphyrin is higher than that of H1, and the electron transfer from edge-porphyrin to the central-porphyrin become predominant process. - Highlights: • Dendritic pyrene-porphyrin heptads were synthesized. • Excitation energy transfer occurs from the pyrenyl moiety to the phosphorus(V)porphyrin. • The stepwise and direct energy transfer pathways were observed. • The quantum yields of these energy transfer pathways could be determined.

  4. Comparability of river quality assessment using macrophytes: a multi-step procedure to overcome biogeographical differences.

    Science.gov (United States)

    Aguiar, F C; Segurado, P; Urbanič, G; Cambra, J; Chauvin, C; Ciadamidaro, S; Dörflinger, G; Ferreira, J; Germ, M; Manolaki, P; Minciardi, M R; Munné, A; Papastergiadou, E; Ferreira, M T

    2014-04-01

    This paper exposes a new methodological approach to solve the problem of intercalibrating river quality national methods when a common metric is lacking and most of the countries share the same Water Framework Directive (WFD) assessment method. We provide recommendations for similar works in future concerning the assessment of ecological accuracy and highlight the importance of a good common ground to make feasible the scientific work beyond the intercalibration. The approach herein presented was applied to highly seasonal rivers of the Mediterranean Geographical Intercalibration Group for the Biological Quality Element Macrophytes. The Mediterranean Group of river macrophytes involved seven countries and two assessment methods with similar acquisition data and assessment concept: the Macrophyte Biological Index for Rivers (IBMR) for Cyprus, France, Greece, Italy, Portugal and Spain, and the River Macrophyte Index (RMI) for Slovenia. Database included 318 sites of which 78 were considered as benchmarks. The boundary harmonization was performed for common WFD-assessment methods (all countries except Slovenia) using the median of the Good/Moderate and High/Good boundaries of all countries. Then, whenever possible, the Slovenian method, RMI was computed for the entire database. The IBMR was also computed for the Slovenian sites and was regressed against RMI in order to check the relatedness of methods (R(2)=0.45; p<0.00001) and to convert RMI boundaries into the IBMR scale. The boundary bias of RMI was computed using direct comparison of classification and the median boundary values following boundary harmonization. The average absolute class differences after harmonization is 26% and the percentage of classifications differing by half of a quality class is also small (16.4%). This multi-step approach to the intercalibration was endorsed by the WFD Regulatory Committee. © 2013 Elsevier B.V. All rights reserved.

  5. Multi-step intramolecular excitation energy transfer in dendritic pyrene-phosphorus(V)porphyrin heptads

    Energy Technology Data Exchange (ETDEWEB)

    Hirakawa, Kazutaka, E-mail: hirakawa.kazutaka@shizuoka.ac.jp [Applied Chemistry and Biochemical Engineering Course, Department of Engineering, Graduate School of Integrated Science and Technology, Shizuoka University, Johoku 3-5-1, Naka-ku, Hamamatsu, Shizuoka 432-8561 (Japan); Department of Optoelectronics and Nanostructure Science, Graduate School of Science and Technology, Shizuoka University, Johoku 3-5-1, Naka-ku, Hamamatsu, Shizuoka 432-8561 (Japan); Segawa, Hiroshi [Department of Multi-Disciplinary Science - General Systems Studies, Graduate School of Arts and Sciences, The University of Tokyo, Komaba 3-8-1, Meguro-ku, Tokyo 153-8904 (Japan); Research Center for Advanced Science and Technology, The University of Tokyo, Komaba 4-6-1, Meguro-ku, Tokyo 153-8904 (Japan)

    2016-11-15

    Dendritic heptad molecules in which four pyrenyl groups are connected at the central phosphorus atom of the edge-porphyrins of the center-to-edge type porphyrin trimers were synthesized to investigate a multi-step excitation energy transfer. As the central energy acceptor, two types porphyrins which one was phosphorus(V)tetraphenylporphyrin (H2) and another was its derivative substituted by butoxy groups at four para-position of meso-phenyl groups (H1) were used. In the photoexcited state of the pyrene units, the excitation energy transfer to the central-porphyrin unit was observed in toluene. The excitation energy transfer is considered to be through two pathways; one is a stepwise pathway through the edge-porphyrin unit and another is a direct excitation energy transfer to the central porphyrin. The direct excitation energy transfer from pyrenes to the edge-porphyrin and central-porphyrin were observed in the case for H1. From the excited state of the edge-porphyrins, the excitation energy transfer to the central-porphyrin occurs in the H1 case. In the H2 case, the excitation energy of central-porphyrin is higher than that of H1, and the electron transfer from edge-porphyrin to the central-porphyrin become predominant process. - Highlights: • Dendritic pyrene-porphyrin heptads were synthesized. • Excitation energy transfer occurs from the pyrenyl moiety to the phosphorus(V)porphyrin. • The stepwise and direct energy transfer pathways were observed. • The quantum yields of these energy transfer pathways could be determined.

  6. Detection of Heterogeneous Small Inclusions by a Multi-Step MUSIC Method

    Science.gov (United States)

    Solimene, Raffaele; Dell'Aversano, Angela; Leone, Giovanni

    2014-05-01

    In this contribution the problem of detecting and localizing scatterers with small (in terms of wavelength) cross sections by collecting their scattered field is addressed. The problem is dealt with for a two-dimensional and scalar configuration where the background is given as a two-layered cylindrical medium. More in detail, while scattered field data are taken in the outermost layer, inclusions are embedded within the inner layer. Moreover, the case of heterogeneous inclusions (i.e., having different scattering coefficients) is addressed. As a pertinent applicative context we identify the problem of diagnose concrete pillars in order to detect and locate rebars, ducts and other small in-homogeneities that can populate the interior of the pillar. The nature of inclusions influences the scattering coefficients. For example, the field scattered by rebars is stronger than the one due to ducts. Accordingly, it is expected that the more weakly scattering inclusions can be difficult to be detected as their scattered fields tend to be overwhelmed by those of strong scatterers. In order to circumvent this problem, in this contribution a multi-step MUltiple SIgnal Classification (MUSIC) detection algorithm is adopted [1]. In particular, the first stage aims at detecting rebars. Once rebars have been detected, their positions are exploited to update the Green's function and to subtract the scattered field due to their presence. The procedure is repeated until all the inclusions are detected. The analysis is conducted by numerical experiments for a multi-view/multi-static single-frequency configuration and the synthetic data are generated by a FDTD forward solver. Acknowledgement This work benefited from networking activities carried out within the EU funded COST Action TU1208 "Civil Engineering Applications of Ground Penetrating Radar." [1] R. Solimene, A. Dell'Aversano and G. Leone, "MUSIC algorithms for rebar detection," J. of Geophysics and Engineering, vol. 10, pp. 1

  7. Reducing workpieces to their base geometry for multi-step incremental forming using manifold harmonics

    Science.gov (United States)

    Carette, Yannick; Vanhove, Hans; Duflou, Joost

    2018-05-01

    Single Point Incremental Forming is a flexible process that is well-suited for small batch production and rapid prototyping of complex sheet metal parts. The distributed nature of the deformation process and the unsupported sheet imply that controlling the final accuracy of the workpiece is challenging. To improve the process limits and the accuracy of SPIF, the use of multiple forming passes has been proposed and discussed by a number of authors. Most methods use multiple intermediate models, where the previous one is strictly smaller than the next one, while gradually increasing the workpieces' wall angles. Another method that can be used is the manufacture of a smoothed-out "base geometry" in the first pass, after which more detailed features can be added in subsequent passes. In both methods, the selection of these intermediate shapes is freely decided by the user. However, their practical implementation in the production of complex freeform parts is not straightforward. The original CAD model can be manually adjusted or completely new CAD models can be created. This paper discusses an automatic method that is able to extract the base geometry from a full STL-based CAD model in an analytical way. Harmonic decomposition is used to express the final geometry as the sum of individual surface harmonics. It is then possible to filter these harmonic contributions to obtain a new CAD model with a desired level of geometric detail. This paper explains the technique and its implementation, as well as its use in the automatic generation of multi-step geometries.

  8. Multi-step ahead nonlinear identification of Lorenz's chaotic system using radial basis neural network with learning by clustering and particle swarm optimization

    International Nuclear Information System (INIS)

    Guerra, Fabio A.; Coelho, Leandro dos S.

    2008-01-01

    An important problem in engineering is the identification of nonlinear systems, among them radial basis function neural networks (RBF-NN) using Gaussian activation functions models, which have received particular attention due to their potential to approximate nonlinear behavior. Several design methods have been proposed for choosing the centers and spread of Gaussian functions and training the RBF-NN. The selection of RBF-NN parameters such as centers, spreads, and weights can be understood as a system identification problem. This paper presents a hybrid training approach based on clustering methods (k-means and c-means) to tune the centers of Gaussian functions used in the hidden layer of RBF-NNs. This design also uses particle swarm optimization (PSO) for centers (local clustering search method) and spread tuning, and the Penrose-Moore pseudoinverse for the adjustment of RBF-NN weight outputs. Simulations involving this RBF-NN design to identify Lorenz's chaotic system indicate that the performance of the proposed method is superior to that of the conventional RBF-NN trained for k-means and the Penrose-Moore pseudoinverse for multi-step ahead forecasting

  9. Effects of Stroke on Ipsilesional End-Effector Kinematics in a Multi-Step Activity of Daily Living

    OpenAIRE

    Gulde, Philipp; Hughes, Charmayne Mary Lee; Hermsdörfer, Joachim

    2017-01-01

    Background: Stroke frequently impairs activities of daily living (ADL) and deteriorates the function of the contra- as well as the ipsilesional limbs. In order to analyze alterations of higher motor control unaffected by paresis or sensory loss, the kinematics of ipsilesional upper limb movements in patients with stroke has previously been analyzed during prehensile movements and simple tool use actions. By contrast, motion recording of multi-step ADL is rare and patient-control comparisons f...

  10. High speed quantitative digital beta autoradiography using a multi-step avalanche detector and an Apple-II microcomputer

    International Nuclear Information System (INIS)

    Bateman, J.E.; Connolly, J.F.; Stephenson, R.

    1985-04-01

    The development of an electronic, digital beta autoradiography system is described. Using a Multi-Step Avalanche/Multi-Wire Proportional Counter (MSA/MWPC) detector system fitted with delay line readout, high speed digital imaging is demonstrated with sub-millimeter spatial resolution. Good proportionality of observed counting rate relative to the known tritium activity is demonstrated. The application of the system to autoradiography in immunoelectrophoresis, histopathology and DNA sequencing is described. (author)

  11. Predicting respiratory motion signals for image-guided radiotherapy using multi-step linear methods (MULIN)

    International Nuclear Information System (INIS)

    Ernst, Floris; Schweikard, Achim

    2008-01-01

    Forecasting of respiration motion in image-guided radiotherapy requires algorithms that can accurately and efficiently predict target location. Improved methods for respiratory motion forecasting were developed and tested. MULIN, a new family of prediction algorithms based on linear expansions of the prediction error, was developed and tested. Computer-generated data with a prediction horizon of 150 ms was used for testing in simulation experiments. MULIN was compared to Least Mean Squares-based predictors (LMS; normalized LMS, nLMS; wavelet-based multiscale autoregression, wLMS) and a multi-frequency Extended Kalman Filter (EKF) approach. The in vivo performance of the algorithms was tested on data sets of patients who underwent radiotherapy. The new MULIN methods are highly competitive, outperforming the LMS and the EKF prediction algorithms in real-world settings and performing similarly to optimized nLMS and wLMS prediction algorithms. On simulated, periodic data the MULIN algorithms are outperformed only by the EKF approach due to its inherent advantage in predicting periodic signals. In the presence of noise, the MULIN methods significantly outperform all other algorithms. The MULIN family of algorithms is a feasible tool for the prediction of respiratory motion, performing as well as or better than conventional algorithms while requiring significantly lower computational complexity. The MULIN algorithms are of special importance wherever high-speed prediction is required. (orig.)

  12. Predicting respiratory motion signals for image-guided radiotherapy using multi-step linear methods (MULIN)

    Energy Technology Data Exchange (ETDEWEB)

    Ernst, Floris; Schweikard, Achim [University of Luebeck, Institute for Robotics and Cognitive Systems, Luebeck (Germany)

    2008-06-15

    Forecasting of respiration motion in image-guided radiotherapy requires algorithms that can accurately and efficiently predict target location. Improved methods for respiratory motion forecasting were developed and tested. MULIN, a new family of prediction algorithms based on linear expansions of the prediction error, was developed and tested. Computer-generated data with a prediction horizon of 150 ms was used for testing in simulation experiments. MULIN was compared to Least Mean Squares-based predictors (LMS; normalized LMS, nLMS; wavelet-based multiscale autoregression, wLMS) and a multi-frequency Extended Kalman Filter (EKF) approach. The in vivo performance of the algorithms was tested on data sets of patients who underwent radiotherapy. The new MULIN methods are highly competitive, outperforming the LMS and the EKF prediction algorithms in real-world settings and performing similarly to optimized nLMS and wLMS prediction algorithms. On simulated, periodic data the MULIN algorithms are outperformed only by the EKF approach due to its inherent advantage in predicting periodic signals. In the presence of noise, the MULIN methods significantly outperform all other algorithms. The MULIN family of algorithms is a feasible tool for the prediction of respiratory motion, performing as well as or better than conventional algorithms while requiring significantly lower computational complexity. The MULIN algorithms are of special importance wherever high-speed prediction is required. (orig.)

  13. Effects of Cu and Ag additions on age-hardening behavior during multi-step aging in Al--Mg--Si alloys

    International Nuclear Information System (INIS)

    Kim, JaeHwang; Daniel Marioara, Calin; Holmestad, Randi; Kobayashi, Equo; Sato, Tatsuo

    2013-01-01

    Low Cu and Ag additions (≤0.10 at%) were found to strongly affect the age-hardening behavior in Al--Mg--Si alloys with Mg+Si>1.5 at%. The hardness increased during aging at 170 °C and the formation of β ″ precipitates was kinetically accelerated. The activation energy of the formation of the β ″ phase was calculated to 127, 105, 108 and 99 KJmol −1 in the base, Cu-added, Ag-added and Cu--Ag-added alloys, respectively using the Kissinger method. The negative effect of two-step aging caused by the formation of Cluster (1) during natural aging was not overcome by the addition of microalloying elements. However, it was suppressed by the formation of Cluster (2) through a pre-aging at 100 °C. Quantitative analysis of the precipitate microstructure was performed using a transmission electron microscope equipped with a parallel electron energy loss spectrometer for the determination of specimen thickness. The formation of Cluster (2) was found to increase the number density of β ″ precipitates, whereas the formation of Cluster (1) decreased the number density and increased the needle length. The effects of low Cu and Ag additions in combination with multi-step aging are discussed based on microstructure observations and hardness and resistivity measurements.

  14. Multi-Step Ka/Ka Dichroic Plate with Rounded Corners for NASA's 34m Beam Waveguide Antenna

    Science.gov (United States)

    Veruttipong, Watt; Khayatian, Behrouz; Hoppe, Daniel; Long, Ezra

    2013-01-01

    A multi-step Ka/Ka dichroic plate Frequency Selective Surface (FSS structure) is designed, manufactured and tested for use in NASA's Deep Space Network (DSN) 34m Beam Waveguide (BWG) antennas. The proposed design allows ease of manufacturing and ability to handle the increased transmit power (reflected off the FSS) of the DSN BWG antennas from 20kW to 100 kW. The dichroic is designed using HFSS and results agree well with measured data considering the manufacturing tolerances that could be achieved on the dichroic.

  15. Improving the performance of the MWPC X-ray imaging detector by means of the Multi-Step Avalanche technique

    International Nuclear Information System (INIS)

    Bateman, J.E.; Connolly, J.F.; Stephenson, R.

    1984-01-01

    X-ray imaging systems based on conventional MWPC technology and artificial delay line readout techniques have been developed at RAL for several applications over a period of some eight years. It is perceived that very limited scope exists for the further improvement of the imaging capability of the standard MWPC design. Attention has therefore been turned to the possibility of exploiting the Multi-Step Avalanche (MSA) system of electron multiplication in this context. Results from a prototype system are presented which show spatial resolution better than that achieved in the MWPC systems. The facility for controlling the effective depth of the detector electronically is also demonstrated. (author)

  16. Simulation study of multi-step model algorithmic control of the nuclear reactor thermal power tracking system

    International Nuclear Information System (INIS)

    Shi Xiaoping; Xu Tianshu

    2001-01-01

    The classical control method is usually hard to ensure the thermal power tracking accuracy, because the nuclear reactor system is a complex nonlinear system with uncertain parameters and disturbances. A sort of non-parameter model is constructed with the open-loop impulse response of the system. Furthermore, a sort of thermal power tracking digital control law is presented using the multi-step model algorithmic control principle. The control method presented had good tracking performance and robustness. It can work despite the existence of unmeasurable disturbances. The simulation experiment testifies the correctness and effectiveness of the method. The high accuracy matching between the thermal power and the referenced load is achieved

  17. Multi-step magnetization of the Ising model on a Shastry-Sutherland lattice: a Monte Carlo simulation

    International Nuclear Information System (INIS)

    Huang, W C; Huo, L; Tian, G; Qian, H R; Gao, X S; Qin, M H; Liu, J-M

    2012-01-01

    The magnetization behaviors and spin configurations of the classical Ising model on a Shastry-Sutherland lattice are investigated using Monte Carlo simulations, in order to understand the fascinating magnetization plateaus observed in TmB 4 and other rare-earth tetraborides. The simulations reproduce the 1/2 magnetization plateau by taking into account the dipole-dipole interaction. In addition, a narrow 2/3 magnetization step at low temperature is predicted in our simulation. The multi-step magnetization can be understood as the consequence of the competitions among the spin-exchange interaction, the dipole-dipole interaction, and the static magnetic energy.

  18. Forecasting Long Memory Series Subject to Structural Change

    DEFF Research Database (Denmark)

    Dias, Gustavo Fruet; Papailias, Fotis

    A two-stage forecasting approach for long memory time series is introduced. In the first step we estimate the fractional exponent and, applying the fractional differencing operator, we obtain the underlying weakly dependent series. In the second step, we perform the multi-step ahead forecasts...... for the weakly dependent series and obtain their long memory counterparts by applying the fractional cumulation operator. The methodology applies to stationary and nonstationary cases. Simulations and an application to seven time series provide evidence that the new methodology is more robust to structural...... change and yields good forecasting results....

  19. Numerical simulation of machining distortions on a forged aerospace component following a one and a multi-step approaches

    Science.gov (United States)

    Prete, Antonio Del; Franchi, Rodolfo; Antermite, Fabrizio; Donatiello, Iolanda

    2018-05-01

    Residual stresses appear in a component as a consequence of thermo-mechanical processes (e.g. ring rolling process) casting and heat treatments. When machining these kinds of components, distortions arise due to the redistribution of residual stresses due to the foregoing process history inside the material. If distortions are excessive, they can lead to a large number of scrap parts. Since dimensional accuracy can affect directly the engines efficiency, the dimensional control for aerospace components is a non-trivial issue. In this paper, the problem related to the distortions of large thin walled aeroengines components in nickel superalloys has been addressed. In order to estimate distortions on inner diameters after internal turning operations, a 3D Finite Element Method (FEM) analysis has been developed on a real industrial test case. All the process history, has been taken into account by developing FEM models of ring rolling process and heat treatments. Three different strategies of ring rolling process have been studied and the combination of related parameters which allows to obtain the best dimensional accuracy has been found. Furthermore, grain size evolution and recrystallization phenomena during manufacturing process has been numerically investigated using a semi empirical Johnson-Mehl-Avrami-Kohnogorov (JMAK) model. The volume subtractions have been simulated by boolean trimming: a one step and a multi step analysis have been performed. The multi-step procedure has allowed to choose the best material removal sequence in order to reduce machining distortions.

  20. Effects of the multi-step activation process on the carrier concentration of p-type GaN

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jae-Kwan [Department of Materials Science and Metallurgical Engineering, Sunchon National University, Sunchon, Chonnam 540-742 (Korea, Republic of); Jeon, Seong-Ran [LED Research and Business Division, Korea Photonics Technology Institute, Gwanju 500-779 (Korea, Republic of); Lee, Ji-Myon, E-mail: jimlee@sunchon.ac.kr [Department of Printed Electronics Engineering, Sunchon National University, Sunchon, Chonnam 540-742 (Korea, Republic of)

    2014-06-25

    Highlights: • Hole concentration of p-GaN was enhanced by multi-step activation process. • The O{sub 2} plasma treatment is attributed to the enhanced hole concentration of p-GaN. • PL peak intensity was also enhanced by MS activation process. - Abstract: A multi-step activation method, which include an oxygen plasma treatment, chemical treatment, and post annealing in N{sub 2} was proposed to enhance the hole concentration of a p-type GaN epitaxial layer. This process was found to effectively activate p-GaN by increasing the hole concentration compared to that of the conventionally annealed sample. After the optimal oxygen plasma treatment (10 min at a source and table power of 500 W and 100 W, respectively), followed by a HCl and buffered oxide etchant treatment, and then by a post-RTA process in a N{sub 2} environment, the hole concentration was increased from 4.0 × 10{sup 17} to 2.0 × 10{sup 18} cm{sup −3}. The oxygen plasma was found to effectively remove the remaining H atoms and subsequent wet treatment can effectively remove the GaO{sub x} that had formed during O plasma treatment, resulting in the higher intensity of photoluminescence.

  1. Abundance and composition of indigenous bacterial communities in a multi-step biofiltration-based drinking water treatment plant.

    Science.gov (United States)

    Lautenschlager, Karin; Hwang, Chiachi; Ling, Fangqiong; Liu, Wen-Tso; Boon, Nico; Köster, Oliver; Egli, Thomas; Hammes, Frederik

    2014-10-01

    Indigenous bacterial communities are essential for biofiltration processes in drinking water treatment systems. In this study, we examined the microbial community composition and abundance of three different biofilter types (rapid sand, granular activated carbon, and slow sand filters) and their respective effluents in a full-scale, multi-step treatment plant (Zürich, CH). Detailed analysis of organic carbon degradation underpinned biodegradation as the primary function of the biofilter biomass. The biomass was present in concentrations ranging between 2-5 × 10(15) cells/m(3) in all filters but was phylogenetically, enzymatically and metabolically diverse. Based on 16S rRNA gene-based 454 pyrosequencing analysis for microbial community composition, similar microbial taxa (predominantly Proteobacteria, Planctomycetes, Acidobacteria, Bacteriodetes, Nitrospira and Chloroflexi) were present in all biofilters and in their respective effluents, but the ratio of microbial taxa was different in each filter type. This change was also reflected in the cluster analysis, which revealed a change of 50-60% in microbial community composition between the different filter types. This study documents the direct influence of the filter biomass on the microbial community composition of the final drinking water, particularly when the water is distributed without post-disinfection. The results provide new insights on the complexity of indigenous bacteria colonizing drinking water systems, especially in different biofilters of a multi-step treatment plant. Copyright © 2014 Elsevier Ltd. All rights reserved.

  2. Fabrication of different pore shapes by multi-step etching technique in ion-irradiated PET membranes

    Science.gov (United States)

    Mo, D.; Liu, J. D.; Duan, J. L.; Yao, H. J.; Latif, H.; Cao, D. L.; Chen, Y. H.; Zhang, S. X.; Zhai, P. F.; Liu, J.

    2014-08-01

    A method for the fabrication of different pore shapes in polyethylene terephthalate (PET)-based track etched membranes (TEMs) is reported. A multi-step etching technique involving etchant variation and track annealing was applied to fabricate different pore shapes in PET membranes. PET foils of 12-μm thickness were irradiated with Bi ions (kinetic energy 9.5 MeV/u, fluence 106 ions/cm2) at the Heavy Ion Research Facility (HIRFL, Lanzhou). The cross-sections of fundamental pore shapes (cylinder, cone, and double cone) were analyzed. Funnel-shaped and pencil-shaped pores were obtained using a two-step etching process. Track annealing was carried out in air at 180 °C for 120 min. After track annealing, the selectivity of the etching process decreased, which resulted in isotropic etching in subsequent etching steps. Rounded cylinder and rounded cone shapes were obtained by introducing a track-annealing step in the etching process. Cup and spherical funnel-shaped pores were fabricated using a three- and four-step etching process, respectively. The described multi-step etching technique provides a controllable method to fabricate new pore shapes in TEMs. Introduction of a variety of pore shapes may improve the separation properties of TEMs and enrich the series of TEM products.

  3. State updating of a distributed hydrological model with Ensemble Kalman Filtering: Effects of updating frequency and observation network density on forecast accuracy

    Science.gov (United States)

    Rakovec, O.; Weerts, A.; Hazenberg, P.; Torfs, P.; Uijlenhoet, R.

    2012-12-01

    This paper presents a study on the optimal setup for discharge assimilation within a spatially distributed hydrological model (Rakovec et al., 2012a). The Ensemble Kalman filter (EnKF) is employed to update the grid-based distributed states of such an hourly spatially distributed version of the HBV-96 model. By using a physically based model for the routing, the time delay and attenuation are modelled more realistically. The discharge and states at a given time step are assumed to be dependent on the previous time step only (Markov property). Synthetic and real world experiments are carried out for the Upper Ourthe (1600 km2), a relatively quickly responding catchment in the Belgian Ardennes. The uncertain precipitation model forcings were obtained using a time-dependent multivariate spatial conditional simulation method (Rakovec et al., 2012b), which is further made conditional on preceding simulations. We assess the impact on the forecasted discharge of (1) various sets of the spatially distributed discharge gauges and (2) the filtering frequency. The results show that the hydrological forecast at the catchment outlet is improved by assimilating interior gauges. This augmentation of the observation vector improves the forecast more than increasing the updating frequency. In terms of the model states, the EnKF procedure is found to mainly change the pdfs of the two routing model storages, even when the uncertainty in the discharge simulations is smaller than the defined observation uncertainty. Rakovec, O., Weerts, A. H., Hazenberg, P., Torfs, P. J. J. F., and Uijlenhoet, R.: State updating of a distributed hydrological model with Ensemble Kalman Filtering: effects of updating frequency and observation network density on forecast accuracy, Hydrol. Earth Syst. Sci. Discuss., 9, 3961-3999, doi:10.5194/hessd-9-3961-2012, 2012a. Rakovec, O., Hazenberg, P., Torfs, P. J. J. F., Weerts, A. H., and Uijlenhoet, R.: Generating spatial precipitation ensembles: impact of

  4. Forecasting electricity market pricing using artificial neural networks

    International Nuclear Information System (INIS)

    Pao, Hsiao-Tien

    2007-01-01

    Electricity price forecasting is extremely important for all market players, in particular for generating companies: in the short term, they must set up bids for the spot market; in the medium term, they have to define contract policies; and in the long term, they must define their expansion plans. For forecasting long-term electricity market pricing, in order to avoid excessive round-off and prediction errors, this paper proposes a new artificial neural network (ANN) with single output node structure by using direct forecasting approach. The potentials of ANNs are investigated by employing a rolling cross validation scheme. Out of sample performance evaluated with three criteria across five forecasting horizons shows that the proposed ANNs are a more robust multi-step ahead forecasting method than autoregressive error models. Moreover, ANN predictions are quite accurate even when the length of the forecast horizon is relatively short or long

  5. Enhancing multi-step quantum state tomography by PhaseLift

    Science.gov (United States)

    Lu, Yiping; Zhao, Qing

    2017-09-01

    Multi-photon system has been studied by many groups, however the biggest challenge faced is the number of copies of an unknown state are limited and far from detecting quantum entanglement. The difficulty to prepare copies of the state is even more serious for the quantum state tomography. One possible way to solve this problem is to use adaptive quantum state tomography, which means to get a preliminary density matrix in the first step and revise it in the second step. In order to improve the performance of adaptive quantum state tomography, we develop a new distribution scheme of samples and extend it to three steps, that is to correct it once again based on the density matrix obtained in the traditional adaptive quantum state tomography. Our numerical results show that the mean square error of the reconstructed density matrix by our new method is improved to the level from 10-4 to 10-9 for several tested states. In addition, PhaseLift is also applied to reduce the required storage space of measurement operator.

  6. A systematic multi-step screening of numerous salt hydrates for low temperature thermochemical energy storage

    International Nuclear Information System (INIS)

    N’Tsoukpoe, Kokouvi Edem; Schmidt, Thomas; Rammelberg, Holger Urs; Watts, Beatriz Amanda; Ruck, Wolfgang K.L.

    2014-01-01

    Highlights: • We report an evaluation of the potential of salt hydrates for thermochemical storage. • Both theoretical calculations and experimental measurements using TGA/DSC are used. • Salt hydrates offer very low potential for thermochemical heat storage. • The efficiency of classical processes using salt hydrates is very low: typically 25%. • New processes are needed for the use of salt hydrates in thermochemical heat storage. - Abstract: In this paper, the potential energy storage density and the storage efficiency of salt hydrates as thermochemical storage materials for the storage of heat generated by a micro-combined heat and power (micro-CHP) have been assessed. Because salt hydrates used in various thermochemical heat storage processes fail to meet the expectations, a systematic evaluation of the suitability of 125 salt hydrates has been performed in a three-step approach. In the first step general issues such as toxicity and risk of explosion have been considered. In the second and third steps, the authors implement a combined approach consisting of theoretical calculations and experimental measurements using Thermogravimetric Analysis (TGA). Thus, application-oriented comparison criteria, among which the net energy storage density of the material and the thermal efficiency, have been used to evaluate the potential of 45 preselected salt hydrates for a low temperature thermochemical heat storage application. For an application that requires a discharging temperature above 60 °C, SrBr 2 ·6H 2 O and LaCl 3 ·7H 2 O appear to be the most promising, only from thermodynamic point of view. However, the maximum net energy storage density including the water in the water storage tank that they offer (respectively 133 kW h m −3 and 89 kW h m −3 ) for a classical thermochemical heat storage process are not attractive for the intended application. Furthermore, the thermal efficiency that would result from the storage process based on salt hydrates

  7. A data acquisition system for measuring ionization cross section in laser multi-step resonant ionization experiment

    International Nuclear Information System (INIS)

    Qian Dongbin; Guo Yuhui; Zhang Dacheng; Chinese Academy of Sciences, Beijing; Ma Xinwen; Zhao Zhizheng; Wang Yanyu; Zu Kailing

    2006-01-01

    A CAMAC data acquisition system for measuring ionization cross section in laser multi-step resonant ionization experiment is described. The number of scalers in the front-end CAMAC can be adjusted by changing the data read-out table files. Both continuous and manual acquisition models are available, and there is a wide adjustable range from 1 ms to 800 s with the acquisition time unit. The long-term stability, Δt/t, for the data acquisition system with an acquisition time unit of 100 s was measured to be better than ±0.01%, thus validating its reliability in long-term online experimental data acquisition. The time response curves for three electrothermal power-meters were also measured by this DAQ system. (authors)

  8. Rapid determination and chemical change tracking of benzoyl peroxide in wheat flour by multi-step IR macro-fingerprinting

    Science.gov (United States)

    Guo, Xiao-Xi; Hu, Wei; Liu, Yuan; Sun, Su-Qin; Gu, Dong-Chen; He, Helen; Xu, Chang-Hua; Wang, Xi-Chang

    2016-02-01

    BPO is often added to wheat flour as flour improver, but its excessive use and edibility are receiving increasing concern. A multi-step IR macro-fingerprinting was employed to identify BPO in wheat flour and unveil its changes during storage. BPO contained in wheat flour (treatment of BPO in wheat flour based on 2DCOS-IR and spectral subtraction analysis, it was found that BPO in wheat flour not only decomposed into benzoic acid and benzoate, but also produced other deleterious substances, e.g., benzene. This study offers a promising method with minimum pretreatment and time-saving to identify BPO in wheat flour and its chemical products during storage in a holistic manner.

  9. Grade Distribution Modeling within the Bauxite Seams of the Wachangping Mine, China, Using a Multi-Step Interpolation Algorithm

    Directory of Open Access Journals (Sweden)

    Shaofeng Wang

    2017-05-01

    Full Text Available Mineral reserve estimation and mining design depend on a precise modeling of the mineralized deposit. A multi-step interpolation algorithm, including 1D biharmonic spline estimator for interpolating floor altitudes, 2D nearest neighbor, linear, natural neighbor, cubic, biharmonic spline, inverse distance weighted, simple kriging, and ordinary kriging interpolations for grade distribution on the two vertical sections at roadways, and 3D linear interpolation for grade distribution between sections, was proposed to build a 3D grade distribution model of the mineralized seam in a longwall mining panel with a U-shaped layout having two roadways at both sides. Compared to field data from exploratory boreholes, this multi-step interpolation using a natural neighbor method shows an optimal stability and a minimal difference between interpolation and field data. Using this method, the 97,576 m3 of bauxite, in which the mass fraction of Al2O3 (Wa and the mass ratio of Al2O3 to SiO2 (Wa/s are 61.68% and 27.72, respectively, was delimited from the 189,260 m3 mineralized deposit in the 1102 longwall mining panel in the Wachangping mine, Southwest China. The mean absolute errors, the root mean squared errors and the relative standard deviations of errors between interpolated data and exploratory grade data at six boreholes are 2.544, 2.674, and 32.37% of Wa; and 1.761, 1.974, and 67.37% of Wa/s, respectively. The proposed method can be used for characterizing the grade distribution in a mineralized seam between two roadways at both sides of a longwall mining panel.

  10. Forecast Combinations

    OpenAIRE

    Timmermann, Allan G

    2005-01-01

    Forecast combinations have frequently been found in empirical studies to produce better forecasts on average than methods based on the ex-ante best individual forecasting model. Moreover, simple combinations that ignore correlations between forecast errors often dominate more refined combination schemes aimed at estimating the theoretically optimal combination weights. In this paper we analyse theoretically the factors that determine the advantages from combining forecasts (for example, the d...

  11. Forecast combinations

    OpenAIRE

    Aiolfi, Marco; Capistrán, Carlos; Timmermann, Allan

    2010-01-01

    We consider combinations of subjective survey forecasts and model-based forecasts from linear and non-linear univariate specifications as well as multivariate factor-augmented models. Empirical results suggest that a simple equal-weighted average of survey forecasts outperform the best model-based forecasts for a majority of macroeconomic variables and forecast horizons. Additional improvements can in some cases be gained by using a simple equal-weighted average of survey and model-based fore...

  12. Forecasting Skill

    Science.gov (United States)

    1981-01-01

    for the third and fourth day precipitation forecasts. A marked improvement was shown for the consensus 24 hour precipitation forecast, and small... Zuckerberg (1980) found a small long term skill increase in forecasts of heavy snow events for nine eastern cities. Other National Weather Service...and maximum temperature) are each awarded marks 2, 1, or 0 according to whether the forecast is correct, 8 - *- -**■*- ———"—- - -■ t0m 1 MM—IB I

  13. Purification of melt-spun metallurgical grade silicon micro-flakes through a multi-step segregation procedure

    Science.gov (United States)

    Martinsen, F. A.; Nordstrand, E. F.; Gibson, U. J.

    2013-01-01

    Melt-spun metallurgical grade (MG) micron dimension silicon flakes have been purified into near solar grade (SG) quality through a multi-step melting and re-solidification procedure. A wet oxidation-applied thermal oxide maintained the sample morphology during annealing while the interiors were melted and re-solidified. The small thickness of the flakes allowed for near elimination of in-plane grain boundaries, with segregation enhanced accumulation of impurities at the object surface and in the few remaining grain boundaries. A subsequent etch in 48% hydrofluoric acid (HF) removed the impure oxide layer, and part of the contamination at the oxide-silicon interface, as shown by electron dispersive spectroscopy (EDS) and backscattered electron imaging (BEI). The sample grains were investigated by electron back-scattered diffraction (EBSD) after varying numbers of oxidation-annealing-etch cycles, and were observed to grow from ˜5 μm to ˜200 μm. The concentration of iron, titanium, copper and aluminium were shown by secondary ion mass spectroscopy (SIMS) and inductively coupled plasma mass spectroscopy (ICPMS) to drop between five and six orders of magnitude. The concentration of boron was observed to drop approximately one order of magnitude. A good correlation was observed between impurity removal rates and segregation models, indicating that the purification effect is mainly caused by segregation. Deviations from these models could be explained by the formation of oxides and hydroxides later removed through etching.

  14. Mechanical properties of molybdenum-titanium alloys micro-structurally controlled by multi-step internal nitriding

    International Nuclear Information System (INIS)

    Nagae, M.; Yoshio, T.; Takemoto, Y.; Takada, J.; Hiraoka, Y.

    2001-01-01

    Internally nitrided dilute Mo-Ti alloys having a heavily deformed microstructure near the specimen surface were prepared by a novel two-step nitriding process at 1173 to 1773 K in N 2 gas. For the nitrided specimens three-point bend tests were performed at temperatures from 77 to 298 K in order to investigate the effect of microstructure control by internal nitriding on the ductile-to-brittle transition temperature (DBTT) of the alloy Yield strength obtained at 243 K of the specimen maintaining the deformed microstructure by the two-step nitriding was about 1.7 times as much as recrystallized specimen. The specimen subjected to the two-step nitriding was bent more than 90 degree at 243 K, whereas recrystallized specimen was fractured after showing a slight ductility at 243 K. DBTT of the specimen subjected to the two-step nitriding and recrystallized specimen was about 153 K and 203 K, respectively. These results indicate that multi-step internal nitriding is very effective to the improvement in the embrittlement by the recrystallization of molybdenum alloys. (author)

  15. Municipal solid waste incineration plant: A multi-step approach to the evaluation of an energy-recovery configuration.

    Science.gov (United States)

    Panepinto, D; Zanetti, M C

    2018-03-01

    This study proposes a multi-step approach to evaluating the environmental and economic aspects of a thermal treatment plant with an energy-recovery configuration. In order to validate the proposed approach, the Turin incineration plant was analyzed, and the potential of the incinerator and several different possible connections to the district heating network were then considered. Both local and global environmental balances were defined. The global-scale results provided information on carbon dioxide emissions, while the local-scale results were used as reference values for the implementation of a Gaussian model that could evaluate the actual concentrations of pollutants released into the atmosphere. The economic aspects were then analyzed, and a correspondence between the environmental and economic advantages defined. The results showed a high energy efficiency for the combined production of heat and electricity, and the opportunity to minimize environmental impacts by including cogeneration in a district heating scheme. This scheme showed an environmental advantage, whereas the electricity-only configuration showed an economic advantage. A change in the thermal energy price (specifically, to 40 €/MWh), however, would make it possible to obtain both environmental and economic advantages. Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. Automatic Generation of Wide Dynamic Range Image without Pseudo-Edge Using Integration of Multi-Steps Exposure Images

    Science.gov (United States)

    Migiyama, Go; Sugimura, Atsuhiko; Osa, Atsushi; Miike, Hidetoshi

    Recently, digital cameras are offering technical advantages rapidly. However, the shot image is different from the sight image generated when that scenery is seen with the naked eye. There are blown-out highlights and crushed blacks in the image that photographed the scenery of wide dynamic range. The problems are hardly generated in the sight image. These are contributory cause of difference between the shot image and the sight image. Blown-out highlights and crushed blacks are caused by the difference of dynamic range between the image sensor installed in a digital camera such as CCD and CMOS and the human visual system. Dynamic range of the shot image is narrower than dynamic range of the sight image. In order to solve the problem, we propose an automatic method to decide an effective exposure range in superposition of edges. We integrate multi-step exposure images using the method. In addition, we try to erase pseudo-edges using the process to blend exposure values. Afterwards, we get a pseudo wide dynamic range image automatically.

  17. Characterization of olive oil volatiles by multi-step direct thermal desorption-comprehensive gas chromatography-time-of-flight mass spectrometry using a programmed temperature vaporizing injector

    NARCIS (Netherlands)

    de Koning, S.; Kaal, E.; Janssen, H.-G.; van Platerink, C.; Brinkman, U.A.Th.

    2008-01-01

    The feasibility of a versatile system for multi-step direct thermal desorption (DTD) coupled to comprehensive gas chromatography (GC × GC) with time-of-flight mass spectrometric (TOF-MS) detection is studied. As an application the system is used for the characterization of fresh versus aged olive

  18. Continuous Video Modeling to Assist with Completion of Multi-Step Home Living Tasks by Young Adults with Moderate Intellectual Disability

    Science.gov (United States)

    Mechling, Linda C.; Ayres, Kevin M.; Bryant, Kathryn J.; Foster, Ashley L.

    2014-01-01

    The current study evaluated a relatively new video-based procedure, continuous video modeling (CVM), to teach multi-step cleaning tasks to high school students with moderate intellectual disability. CVM in contrast to video modeling and video prompting allows repetition of the video model (looping) as many times as needed while the user completes…

  19. Performance assessment of laboratory and field-scale multi-step passive treatment of iron-rich acid mine drainage for design improvement.

    Science.gov (United States)

    Rakotonimaro, Tsiverihasina V; Neculita, Carmen Mihaela; Bussière, Bruno; Genty, Thomas; Zagury, Gérald J

    2018-04-17

    Multi-step passive systems for the treatment of iron-rich acid mine drainage (Fe-rich AMD) perform satisfactorily at the laboratory scale. However, their field-scale application has revealed dissimilarities in performance, particularly with respect to hydraulic parameters. In this study, the assessment of factors potentially responsible for the variations in performance of laboratory and field-scale multi-step systems was undertaken. Three laboratory multi-step treatment scenarios, involving a combination of dispersed alkaline substrate (DAS) units, anoxic dolomitic drains, and passive biochemical reactors (PBRs), were set up in 10.7-L columns. The field-scale treatment consisted of two PBRs separated by a wood ash (WA) reactor. The parameters identified as possibly influencing the performances of the laboratory and field-scale experiments were the following: AMD chemistry (electrical conductivity and Fe and SO 4 2- concentrations), flow rate (Q), and saturated hydraulic conductivity (k sat ). Based on these findings, the design of an efficient passive multi-step treatment system is suggested to consider the following: (1) Fe pretreatment, using materials with high k sat and low HRT. If a PBR is to be used, the Fe load should be PBR/DAS filled with a mixture with at least 20% of neutralizing agent; (3) include Q and k sat (> 10 -3  cm/s) in the long-term prediction. Finally, mesocosm testing is strongly recommended prior to construction of full-scale systems for the treatment of Fe-rich AMD.

  20. A transition from using multi-step procedures to a fully integrated system for performing extracorporeal photopheresis: A comparison of costs and efficiencies.

    Science.gov (United States)

    Azar, Nabih; Leblond, Veronique; Ouzegdouh, Maya; Button, Paul

    2017-12-01

    The Pitié Salpêtrière Hospital Hemobiotherapy Department, Paris, France, has been providing extracorporeal photopheresis (ECP) since November 2011, and started using the Therakos ® CELLEX ® fully integrated system in 2012. This report summarizes our single-center experience of transitioning from the use of multi-step ECP procedures to the fully integrated ECP system, considering the capacity and cost implications. The total number of ECP procedures performed 2011-2015 was derived from department records. The time taken to complete a single ECP treatment using a multi-step technique and the fully integrated system at our department was assessed. Resource costs (2014€) were obtained for materials and calculated for personnel time required. Time-driven activity-based costing methods were applied to provide a cost comparison. The number of ECP treatments per year increased from 225 (2012) to 727 (2015). The single multi-step procedure took 270 min compared to 120 min for the fully integrated system. The total calculated per-session cost of performing ECP using the multi-step procedure was greater than with the CELLEX ® system (€1,429.37 and €1,264.70 per treatment, respectively). For hospitals considering a transition from multi-step procedures to fully integrated methods for ECP where cost may be a barrier, time-driven activity-based costing should be utilized to gain a more comprehensive understanding the full benefit that such a transition offers. The example from our department confirmed that there were not just cost and time savings, but that the time efficiencies gained with CELLEX ® allow for more patient treatments per year. © 2017 The Authors Journal of Clinical Apheresis Published by Wiley Periodicals, Inc.

  1. A Novel Molten Salt Reactor Concept to Implement the Multi-Step Time-Scheduled Transmutation Strategy

    International Nuclear Information System (INIS)

    Csom, Gyula; Feher, Sandor; Szieberthj, Mate

    2002-01-01

    Nowadays the molten salt reactor (MSR) concept seems to revive as one of the most promising systems for the realization of transmutation. In the molten salt reactors and subcritical systems the fuel and material to be transmuted circulate dissolved in some molten salt. The main advantage of this reactor type is the possibility of the continuous feed and reprocessing of the fuel. In the present paper a novel molten salt reactor concept is introduced and its transmutation capabilities are studied. The goal is the development of a transmutation technique along with a device implementing it, which yield higher transmutation efficiencies than that of the known procedures and thus results in radioactive waste whose load on the environment is reduced both in magnitude and time length. The procedure is the multi-step time-scheduled transmutation, in which transformation is done in several consecutive steps of different neutron flux and spectrum. In the new MSR concept, named 'multi-region' MSR (MRMSR), the primary circuit is made up of a few separate loops, in which salt-fuel mixtures of different compositions are circulated. The loop sections constituting the core region are only neutronically and thermally coupled. This new concept makes possible the utilization of the spatial dependence of spectrum as well as the advantageous features of liquid fuel such as the possibility of continuous chemical processing etc. In order to compare a 'conventional' MSR and a proposed MRMSR in terms of efficiency, preliminary calculational results are shown. Further calculations in order to find the optimal implementation of this new concept and to emphasize its other advantageous features are going on. (authors)

  2. The Effect of Multi-step Oral-revision Processes on Iranian EFL Learners’ Argumentative Writing Achievement

    Directory of Open Access Journals (Sweden)

    Farrokhlagha Heidari

    2010-05-01

    Full Text Available The purpose of this study was to explore the role of two multi-step oral-revision processes as feedback providing tools on Iranian EFL learners’ argumentative writing achievement. The participants taking part in this study were 45 Iranian EFL students who were randomly assigned into three groups. The participants of the groups were given three argumentative writing assignments, each assignment demanding three separate drafts. In the control group, the participants revised their essays in response to teacher's written feedback, while the participants of the two experimental groups experienced oral-revision talks with their teacher or a peer. Two sets of quantitative and qualitative data were collected: Argumentative essays written at the beginning and the end of the semester and interviews. The results of the quantitative aspect of the study revealed the significant outperformance of the two experimental groups. Moreover, the data provided through interviews revealed some differences in terms of the effectiveness of feedback between the two experimental groups. The participants of the peer-led group reported more awareness of the rhetorical structures and an ability to revise surface errors. While, the teacher-led group reported more global writing concerns like content, organization of ideas,   and discourse. The obtained results point out that the mutual co-construction of participation roles and certain combinations of negotiation and scaffolding let the teacher provide a supportive conversational environment and assistance in accordance with the proficiency of learners of the teacher-led group to promote greater learner participation.

  3. Load forecasting

    International Nuclear Information System (INIS)

    Mak, H.

    1995-01-01

    Slides used in a presentation at The Power of Change Conference in Vancouver, BC in April 1995 about the changing needs for load forecasting were presented. Technological innovations and population increase were said to be the prime driving forces behind the changing needs in load forecasting. Structural changes, market place changes, electricity supply planning changes, and changes in planning objectives were other factors discussed. It was concluded that load forecasting was a form of information gathering, that provided important market intelligence

  4. Multi-step Monte Carlo calculations applied to nuclear reactor instrumentation - source definition and renormalization to physical values

    Energy Technology Data Exchange (ETDEWEB)

    Radulovic, Vladimir; Barbot, Loic; Fourmentel, Damien; Villard, Jean-Francois [CEA, DEN, DER, Instrumentation Sensors and Dosimetry Laboratory, Cadarache, F-13108 St Paul-Lez-Durance, (France); Snoj, Luka; Zerovnik, Gasper [Jozef Stefan Institute, Reactor Physics Department, Jamova cesta 39, SI-1000 Ljubljana, (Slovenia); Trkov, Andrej [IAEA, Vienna International Centre, PO Box 100, A-1400 Vienna, (Austria)

    2015-07-01

    Significant efforts have been made over the last few years in the French Alternative Energies and Atomic Energy Commission (CEA) to adopt multi-step Monte Carlo calculation schemes in the investigation and interpretation of the response of nuclear reactor instrumentation detectors (e.g. miniature ionization chambers - MICs and self-powered neutron or gamma detectors - SPNDs and SPGDs). The first step consists of the calculation of the primary data, i.e. evaluation of the neutron and gamma flux levels and spectra in the environment where the detector is located, using a computational model of the complete nuclear reactor core and its surroundings. These data are subsequently used to define sources for the following calculation steps, in which only a model of the detector under investigation is used. This approach enables calculations with satisfactory statistical uncertainties (of the order of a few %) within regions which are very small in size (the typical volume of which is of the order of 1 mm{sup 3}). The main drawback of a calculation scheme as described above is that perturbation effects on the radiation conditions caused by the detectors themselves are not taken into account. Depending on the detector, the nuclear reactor and the irradiation position, the perturbation in the neutron flux as primary data may reach 10 to 20%. A further issue is whether the model used in the second step calculations yields physically representative results. This is generally not the case, as significant deviations may arise, depending on the source definition. In particular, as presented in the paper, the injudicious use of special options aimed at increasing the computation efficiency (e.g. reflective boundary conditions) may introduce unphysical bias in the calculated flux levels and distortions in the spectral shapes. This paper presents examples of the issues described above related to a case study on the interpretation of the signal from different types of SPNDs, which

  5. MSBIS: A Multi-Step Biomedical Informatics Screening Approach for Identifying Medications that Mitigate the Risks of Metoclopramide-Induced Tardive Dyskinesia

    OpenAIRE

    Dong Xu; Alexandrea G. Ham; Rickey D. Tivis; Matthew L. Caylor; Aoxiang Tao; Steve T. Flynn; Peter J. Economen; Hung K. Dang; Royal W. Johnson; Vaughn L. Culbertson

    2017-01-01

    In 2009 the U.S. Food and Drug Administration (FDA) placed a black box warning on metoclopramide (MCP) due to the increased risks and prevalence of tardive dyskinesia (TD). In this study, we developed a multi-step biomedical informatics screening (MSBIS) approach leveraging publicly available bioactivity and drug safety data to identify concomitant drugs that mitigate the risks of MCP-induced TD. MSBIS includes (1) TargetSearch (http://dxulab.org/software) bioinformatics scoring for drug anti...

  6. Influence of multi-step heat treatments in creep age forming of 7075 aluminum alloy: Optimization for springback, strength and exfoliation corrosion

    Energy Technology Data Exchange (ETDEWEB)

    Arabi Jeshvaghani, R.; Zohdi, H. [Department of Materials Engineering, Tarbiat Modares University, P.O. Box 14115-143, Tehran (Iran, Islamic Republic of); Shahverdi, H.R., E-mail: shahverdi@modares.ac.ir [Department of Materials Engineering, Tarbiat Modares University, P.O. Box 14115-143, Tehran (Iran, Islamic Republic of); Bozorg, M. [Department of Materials Engineering, Tarbiat Modares University, P.O. Box 14115-143, Tehran (Iran, Islamic Republic of); Hadavi, S.M.M. [School of Materials Science and Engineering, MA University of Technology, P.O. Box 16765-3197, Tehran (Iran, Islamic Republic of)

    2012-11-15

    Multi-step heat treatments comprise of high temperature forming (150 Degree-Sign C/24 h plus 190 Degree-Sign C for several minutes) and subsequent low temperature forming (120 Degree-Sign C for 24 h) is developed in creep age forming of 7075 aluminum alloy to decrease springback and exfoliation corrosion susceptibility without reduction in tensile properties. The results show that the multi-step heat treatment gives the low springback and the best combination of exfoliation corrosion resistance and tensile strength. The lower springback is attributed to the dislocation recovery and more stress relaxation at higher temperature. Transmission electron microscopy observations show that corrosion resistance is improved due to the enlargement in the size and the inter-particle distance of the grain boundaries precipitates. Furthermore, the achievement of the high strength is related to the uniform distribution of ultrafine {eta} Prime precipitates within grains. - Highlights: Black-Right-Pointing-Pointer Creep age forming developed for manufacturing of aircraft wing panels by aluminum alloy. Black-Right-Pointing-Pointer A good combination of properties with minimal springback is required in this component. Black-Right-Pointing-Pointer This requirement can be improved through the appropriate heat treatments. Black-Right-Pointing-Pointer Multi-step cycles developed in creep age forming of AA7075 for improving of springback and properties. Black-Right-Pointing-Pointer Results indicate simultaneous enhancing the properties and shape accuracy (lower springback).

  7. Multi-step processes in the (d, t) and (d, 3He) reactions on 116Sn and 208Pb targets at Ed = 200 MeV

    International Nuclear Information System (INIS)

    Langevin-Joliot, H.; Van de Wiele, J.; Guillot, J.; Koning, A.J.

    2000-01-01

    The role of multi-step processes in the reactions 116 Sn(d,t), 208 Pb(d,t) and 116 Sn(d, 3 He), previously studied at E d = 200 MeV at forward angles and for relatively low energy transfers, has been investigated. We have performed for the first time multi-step calculations taking into account systematically collective excitations in the second and higher order step inelastic transitions. A calculation code based on the Feshbach, Kerman and Koonin model has been modified to handle explicitly these collective excitations, most important in the forward angle domain. One step double differential pick-up cross sections were built from finite range distorted wave results spread in energy using known or estimated hole state characteristics. It is shown that two-step cross sections calculated using the above method compare rather well with those deduced via coupled channel calculations for the same collective excitations. The multi-step calculations performed up to 6 steps reproduce reasonably well the 115 Sn, 207 Pb and 115 In experimental spectra measured up to E x ∼- 40 MeV and 15 deg. The relative contributions of steps of increasing order to pick-up cross sections at E d = 200 MeV and 150 MeV are discussed. (authors)

  8. Probabilistic Wind Power Forecasting with Hybrid Artificial Neural Networks

    DEFF Research Database (Denmark)

    Wan, Can; Song, Yonghua; Xu, Zhao

    2016-01-01

    probabilities of prediction errors provide an alternative yet effective solution. This article proposes a hybrid artificial neural network approach to generate prediction intervals of wind power. An extreme learning machine is applied to conduct point prediction of wind power and estimate model uncertainties...... via a bootstrap technique. Subsequently, the maximum likelihood estimation method is employed to construct a distinct neural network to estimate the noise variance of forecasting results. The proposed approach has been tested on multi-step forecasting of high-resolution (10-min) wind power using...... actual wind power data from Denmark. The numerical results demonstrate that the proposed hybrid artificial neural network approach is effective and efficient for probabilistic forecasting of wind power and has high potential in practical applications....

  9. Exposure Forecaster

    Data.gov (United States)

    U.S. Environmental Protection Agency — The Exposure Forecaster Database (ExpoCastDB) is EPA's database for aggregating chemical exposure information and can be used to help with chemical exposure...

  10. Strategic Forecasting

    DEFF Research Database (Denmark)

    Duus, Henrik Johannsen

    2016-01-01

    Purpose: The purpose of this article is to present an overview of the area of strategic forecasting and its research directions and to put forward some ideas for improving management decisions. Design/methodology/approach: This article is conceptual but also informed by the author’s long contact...... and collaboration with various business firms. It starts by presenting an overview of the area and argues that the area is as much a way of thinking as a toolbox of theories and methodologies. It then spells out a number of research directions and ideas for management. Findings: Strategic forecasting is seen...... as a rebirth of long range planning, albeit with new methods and theories. Firms should make the building of strategic forecasting capability a priority. Research limitations/implications: The article subdivides strategic forecasting into three research avenues and suggests avenues for further research efforts...

  11. State updating of a distributed hydrological model with Ensemble Kalman Filtering: effects of updating frequency and observation network density on forecast accuracy

    Directory of Open Access Journals (Sweden)

    O. Rakovec

    2012-09-01

    Full Text Available This paper presents a study on the optimal setup for discharge assimilation within a spatially distributed hydrological model. The Ensemble Kalman filter (EnKF is employed to update the grid-based distributed states of such an hourly spatially distributed version of the HBV-96 model. By using a physically based model for the routing, the time delay and attenuation are modelled more realistically. The discharge and states at a given time step are assumed to be dependent on the previous time step only (Markov property.

    Synthetic and real world experiments are carried out for the Upper Ourthe (1600 km2, a relatively quickly responding catchment in the Belgian Ardennes. We assess the impact on the forecasted discharge of (1 various sets of the spatially distributed discharge gauges and (2 the filtering frequency. The results show that the hydrological forecast at the catchment outlet is improved by assimilating interior gauges. This augmentation of the observation vector improves the forecast more than increasing the updating frequency. In terms of the model states, the EnKF procedure is found to mainly change the pdfs of the two routing model storages, even when the uncertainty in the discharge simulations is smaller than the defined observation uncertainty.

  12. Uncertainties in Forecasting Streamflow using Entropy Theory

    Science.gov (United States)

    Cui, H.; Singh, V. P.

    2017-12-01

    Streamflow forecasting is essential in river restoration, reservoir operation, power generation, irrigation, navigation, and water management. However, there is always uncertainties accompanied in forecast, which may affect the forecasting results and lead to large variations. Therefore, uncertainties must be considered and be assessed properly when forecasting streamflow for water management. The aim of our work is to quantify the uncertainties involved in forecasting streamflow and provide reliable streamflow forecast. Despite that streamflow time series are stochastic, they exhibit seasonal and periodic patterns. Therefore, streamflow forecasting entails modeling seasonality, periodicity, and its correlation structure, and assessing uncertainties. This study applies entropy theory to forecast streamflow and measure uncertainties during the forecasting process. To apply entropy theory for streamflow forecasting, spectral analysis is combined to time series analysis, as spectral analysis can be employed to characterize patterns of streamflow variation and identify the periodicity of streamflow. That is, it permits to extract significant information for understanding the streamflow process and prediction thereof. Application of entropy theory for streamflow forecasting involves determination of spectral density, determination of parameters, and extension of autocorrelation function. The uncertainties brought by precipitation input, forecasting model and forecasted results are measured separately using entropy. With information theory, how these uncertainties transported and aggregated during these processes will be described.

  13. Forecasting metal prices: Do forecasters herd?

    DEFF Research Database (Denmark)

    Pierdzioch, C.; Rulke, J. C.; Stadtmann, G.

    2013-01-01

    We analyze more than 20,000 forecasts of nine metal prices at four different forecast horizons. We document that forecasts are heterogeneous and report that anti-herding appears to be a source of this heterogeneity. Forecaster anti-herding reflects strategic interactions among forecasters...

  14. A New Multi-Step Iterative Algorithm for Approximating Common Fixed Points of a Finite Family of Multi-Valued Bregman Relatively Nonexpansive Mappings

    Directory of Open Access Journals (Sweden)

    Wiyada Kumam

    2016-05-01

    Full Text Available In this article, we introduce a new multi-step iteration for approximating a common fixed point of a finite class of multi-valued Bregman relatively nonexpansive mappings in the setting of reflexive Banach spaces. We prove a strong convergence theorem for the proposed iterative algorithm under certain hypotheses. Additionally, we also use our results for the solution of variational inequality problems and to find the zero points of maximal monotone operators. The theorems furnished in this work are new and well-established and generalize many well-known recent research works in this field.

  15. A Software Module for High-Accuracy Calibration of Rings and Cylinders on CMM using Multi-Orientation Techniques (Multi-Step and Reversal methods)

    DEFF Research Database (Denmark)

    Tosello, Guido; De Chiffre, Leonardo

    . The Centre for Geometrical Metrology (CGM) at the Technical University of Denmark takes care of free form measurements, in collaboration with DIMEG, University of Padova, Italy. The present report describes a software module, ROUNDCAL, to be used for high-accuracy calibration of rings and cylinders....... The purpose of the software is to calculate the form error and the least square circle of rings and cylinders by mean of average of pontwise measuring results becoming from so-called multi-orientation techniques (both reversal and multi-step methods) in order to eliminate systematic errors of CMM ....

  16. Performance Optimization of a Solar-Driven Multi-Step Irreversible Brayton Cycle Based on a Multi-Objective Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Ahmadi Mohammad Hosein

    2016-01-01

    Full Text Available An applicable approach for a multi-step regenerative irreversible Brayton cycle on the basis of thermodynamics and optimization of thermal efficiency and normalized output power is presented in this work. In the present study, thermodynamic analysis and a NSGA II algorithm are coupled to determine the optimum values of thermal efficiency and normalized power output for a Brayton cycle system. Moreover, three well-known decision-making methods are employed to indicate definite answers from the outputs gained from the aforementioned approach. Finally, with the aim of error analysis, the values of the average and maximum error of the results are also calculated.

  17. Forecasting long memory series subject to structural change: A two-stage approach

    DEFF Research Database (Denmark)

    Papailias, Fotis; Dias, Gustavo Fruet

    2015-01-01

    A two-stage forecasting approach for long memory time series is introduced. In the first step, we estimate the fractional exponent and, by applying the fractional differencing operator, obtain the underlying weakly dependent series. In the second step, we produce multi-step-ahead forecasts...... for the weakly dependent series and obtain their long memory counterparts by applying the fractional cumulation operator. The methodology applies to both stationary and nonstationary cases. Simulations and an application to seven time series provide evidence that the new methodology is more robust to structural...

  18. Rapid discrimination of sea buckthorn berries from different H. rhamnoides subspecies by multi-step IR spectroscopy coupled with multivariate data analysis

    Science.gov (United States)

    Liu, Yue; Zhang, Ying; Zhang, Jing; Fan, Gang; Tu, Ya; Sun, Suqin; Shen, Xudong; Li, Qingzhu; Zhang, Yi

    2018-03-01

    As an important ethnic medicine, sea buckthorn was widely used to prevent and treat various diseases due to its nutritional and medicinal properties. According to the Chinese Pharmacopoeia, sea buckthorn was originated from H. rhamnoides, which includes five subspecies distributed in China. Confusion and misidentification usually occurred due to their similar morphology, especially in dried and powdered forms. Additionally, these five subspecies have vital differences in quality and physiological efficacy. This paper focused on the quick classification and identification method of sea buckthorn berry powders from five H. rhamnoides subspecies using multi-step IR spectroscopy coupled with multivariate data analysis. The holistic chemical compositions revealed by the FT-IR spectra demonstrated that flavonoids, fatty acids and sugars were the main chemical components. Further, the differences in FT-IR spectra regarding their peaks, positions and intensities were used to identify H. rhamnoides subspecies samples. The discrimination was achieved using principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA). The results showed that the combination of multi-step IR spectroscopy and chemometric analysis offered a simple, fast and reliable method for the classification and identification of the sea buckthorn berry powders from different H. rhamnoides subspecies.

  19. Influence of multi-step washing using Na2EDTA, oxalic acid and phosphoric acid on metal fractionation and spectroscopy characteristics from contaminated soil.

    Science.gov (United States)

    Wei, Meng; Chen, Jiajun

    2016-11-01

    A multi-step soil washing test using a typical chelating agent (Na 2 EDTA), organic acid (oxalic acid), and inorganic weak acid (phosphoric acid) was conducted to remediate soil contaminated with heavy metals near an arsenic mining area. The aim of the test was to improve the heavy metal removal efficiency and investigate its influence on metal fractionation and the spectroscopy characteristics of contaminated soil. The results indicated that the orders of the multi-step washing were critical for the removal efficiencies of the metal fractions, bioavailability, and potential mobility due to the different dissolution levels of mineral fractions and the inter-transformation of metal fractions by XRD and FT-IR spectral analyses. The optimal soil washing options were identified as the Na 2 EDTA-phosphoric-oxalic acid (EPO) and phosphoric-oxalic acid-Na 2 EDTA (POE) sequences because of their high removal efficiencies (approximately 45 % for arsenic and 88 % for cadmium) and the minimal harmful effects that were determined by the mobility and bioavailability of the remaining heavy metals based on the metal stability (I R ) and modified redistribution index ([Formula: see text]).

  20. Microarc oxidation coating covered Ti implants with micro-scale gouges formed by a multi-step treatment for improving osseointegration.

    Science.gov (United States)

    Bai, Yixin; Zhou, Rui; Cao, Jianyun; Wei, Daqing; Du, Qing; Li, Baoqiang; Wang, Yaming; Jia, Dechang; Zhou, Yu

    2017-07-01

    The sub-microporous microarc oxidation (MAO) coating covered Ti implant with micro-scale gouges has been fabricated via a multi-step MAO process to overcome the compromised bone-implant integration. The as-prepared implant has been further mediated by post-heat treatment to compare the effects of -OH functional group and the nano-scale orange peel-like morphology on osseointegration. The bone regeneration, bone-implant contact interface, and biomechanical push-out force of the modified Ti implant have been discussed thoroughly in this work. The greatly improved push-out force for the MAO coated Ti implants with micro-scale gouges could be attributed to the excellent mechanical interlocking effect between implants and biologically meshed bone tissues. Attributed to the -OH functional group which promotes synostosis between the biologically meshed bone and the gouge surface of implant, the multi-step MAO process could be an effective strategy to improve the osseointegration of Ti implant. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. Evaluation and optimisation of phenomenological multi-step soot model for spray combustion under diesel engine-like operating conditions

    DEFF Research Database (Denmark)

    Pang, Kar Mun; Jangi, Mehdi; Bai, Xue-Song

    2015-01-01

    with the spray combustion solver. Prior to the soot modelling, combustion simulations are carried out. Numerical results show that the ignition delay times and lift-off lengths exhibit good agreement with the experimental measurements across a wide range of operating conditions, apart from those in the cases......, variation of spatial soot distribution and soot mass produced at oxygen molar fractions ranging from 10.0 to 21.0% for both low and high density conditions are reproduced....

  2. Simulation of self-focusing of laser beam through medium with multi-step photo-ionization

    International Nuclear Information System (INIS)

    Akaoka, Katsuaki; Wakaida, Ikuo; Arisawa, Takashi

    1995-01-01

    We built a computation code for the coupled nonlinear Maxwell-Density Matrix equations of multi-level atomic systems including transverse and time-dependent variations. Numerical solutions for two-level atomic systems shown as a function of laser detuning in Na and U are in good agreement with the experimental result. Applying this code to the laser beam propagation through medium with two-step photo-ionization, it is concluded that the group velocity in the spatial edge of a laser pulse is slower than that in the center, and the self-focusing and the temporal reshaping of the laser pulse used for the first-excitation are more distinguished than that used for ionization. (author)

  3. Multi-step resistive switching behavior of Li-doped ZnO resistance random access memory device controlled by compliance current

    Energy Technology Data Exchange (ETDEWEB)

    Lin, Chun-Cheng [Department of Electrical Engineering, National Cheng Kung University, Tainan 701, Taiwan (China); Department of Mathematic and Physical Sciences, R.O.C. Air Force Academy, Kaohsiung 820, Taiwan (China); Tang, Jian-Fu; Su, Hsiu-Hsien [Department of Electrical Engineering, National Cheng Kung University, Tainan 701, Taiwan (China); Hong, Cheng-Shong; Huang, Chih-Yu [Department of Electronic Engineering, National Kaohsiung Normal University, Kaohsiung 802, Taiwan (China); Chu, Sheng-Yuan, E-mail: chusy@mail.ncku.edu.tw [Department of Electrical Engineering, National Cheng Kung University, Tainan 701, Taiwan (China); Center for Micro/Nano Science and Technology, National Cheng Kung University, Tainan 701, Taiwan (China)

    2016-06-28

    The multi-step resistive switching (RS) behavior of a unipolar Pt/Li{sub 0.06}Zn{sub 0.94}O/Pt resistive random access memory (RRAM) device is investigated. It is found that the RRAM device exhibits normal, 2-, 3-, and 4-step RESET behaviors under different compliance currents. The transport mechanism within the device is investigated by means of current-voltage curves, in-situ transmission electron microscopy, and electrochemical impedance spectroscopy. It is shown that the ion transport mechanism is dominated by Ohmic behavior under low electric fields and the Poole-Frenkel emission effect (normal RS behavior) or Li{sup +} ion diffusion (2-, 3-, and 4-step RESET behaviors) under high electric fields.

  4. Multi-step resistive switching behavior of Li-doped ZnO resistance random access memory device controlled by compliance current

    International Nuclear Information System (INIS)

    Lin, Chun-Cheng; Tang, Jian-Fu; Su, Hsiu-Hsien; Hong, Cheng-Shong; Huang, Chih-Yu; Chu, Sheng-Yuan

    2016-01-01

    The multi-step resistive switching (RS) behavior of a unipolar Pt/Li 0.06 Zn 0.94 O/Pt resistive random access memory (RRAM) device is investigated. It is found that the RRAM device exhibits normal, 2-, 3-, and 4-step RESET behaviors under different compliance currents. The transport mechanism within the device is investigated by means of current-voltage curves, in-situ transmission electron microscopy, and electrochemical impedance spectroscopy. It is shown that the ion transport mechanism is dominated by Ohmic behavior under low electric fields and the Poole-Frenkel emission effect (normal RS behavior) or Li + ion diffusion (2-, 3-, and 4-step RESET behaviors) under high electric fields.

  5. Contributions of dopamine-related genes and environmental factors to highly sensitive personality: a multi-step neuronal system-level approach.

    Directory of Open Access Journals (Sweden)

    Chunhui Chen

    Full Text Available Traditional behavioral genetic studies (e.g., twin, adoption studies have shown that human personality has moderate to high heritability, but recent molecular behavioral genetic studies have failed to identify quantitative trait loci (QTL with consistent effects. The current study adopted a multi-step approach (ANOVA followed by multiple regression and permutation to assess the cumulative effects of multiple QTLs. Using a system-level (dopamine system genetic approach, we investigated a personality trait deeply rooted in the nervous system (the Highly Sensitive Personality, HSP. 480 healthy Chinese college students were given the HSP scale and genotyped for 98 representative polymorphisms in all major dopamine neurotransmitter genes. In addition, two environment factors (stressful life events and parental warmth that have been implicated for their contributions to personality development were included to investigate their relative contributions as compared to genetic factors. In Step 1, using ANOVA, we identified 10 polymorphisms that made statistically significant contributions to HSP. In Step 2, these polymorphism's main effects and interactions were assessed using multiple regression. This model accounted for 15% of the variance of HSP (p<0.001. Recent stressful life events accounted for an additional 2% of the variance. Finally, permutation analyses ascertained the probability of obtaining these findings by chance to be very low, p ranging from 0.001 to 0.006. Dividing these loci by the subsystems of dopamine synthesis, degradation/transport, receptor and modulation, we found that the modulation and receptor subsystems made the most significant contribution to HSP. The results of this study demonstrate the utility of a multi-step neuronal system-level approach in assessing genetic contributions to individual differences in human behavior. It can potentially bridge the gap between the high heritability estimates based on traditional

  6. Extent and Area of Swidden in Montane Mainland Southeast Asia: Estimation by Multi-Step Thresholds with Landsat-8 OLI Data

    Directory of Open Access Journals (Sweden)

    Peng Li

    2016-01-01

    Full Text Available Information on the distribution, area and extent of swidden agriculture landscape is necessary for implementing the program of Reducing Emissions from Deforestation and Forest Degradation (REDD, biodiversity conservation and local livelihood improvement. To our knowledge, explicit spatial maps and accurate area data on swidden agriculture remain surprisingly lacking. However, this traditional farming practice has been transforming into other profit-driven land use, like tree plantations and permanent cash agriculture. Swidden agriculture is characterized by a rotational and dynamic nature of agroforestry, with land cover changing from natural forests, newly-cleared swiddens to different-aged fallows. The Operational Land Imager (OLI onboard the Landsat-8 satellite has visible, near-infrared and shortwave infrared bands, which are sensitive to the changes in vegetation cover, land surface moisture content and soil exposure, and therefore, four vegetation indices (VIs were calculated, including the Normalized Difference Vegetation Index (NDVI, the Normalized Difference Moisture Index (NDMI, the Normalized Burn Ratio (NBR and the Soil Adjusted Vegetation Index (SAVI. In this study, we developed a multi-step threshold approach that uses a combination of thresholds of four VIs and local elevation range (LER and applied it to detect and map newly-opened swiddens and different-aged fallows using OLI imagery acquired between 2013 and 2015. The resultant Landsat-derived swidden agriculture maps have high accuracy with an overall accuracy of 86.9% and a Kappa coefficient of 0.864. The results of this study indicated that the Landsat-based multi-step threshold algorithms could potentially be applied to monitor the long-term change pattern of swidden agriculture in montane mainland Southeast Asia since the late 1980s and also in other tropical regions, like insular Southeast Asia, South Asia, Latin America and Central Africa, where swidden agriculture is

  7. Evaluating the spatio-temporal performance of sky imager based solar irradiance analysis and forecasts

    Science.gov (United States)

    Schmidt, T.; Kalisch, J.; Lorenz, E.; Heinemann, D.

    2015-10-01

    Clouds are the dominant source of variability in surface solar radiation and uncertainty in its prediction. However, the increasing share of solar energy in the world-wide electric power supply increases the need for accurate solar radiation forecasts. In this work, we present results of a shortest-term global horizontal irradiance (GHI) forecast experiment based on hemispheric sky images. A two month dataset with images from one sky imager and high resolutive GHI measurements from 99 pyranometers distributed over 10 km by 12 km is used for validation. We developed a multi-step model and processed GHI forecasts up to 25 min with an update interval of 15 s. A cloud type classification is used to separate the time series in different cloud scenarios. Overall, the sky imager based forecasts do not outperform the reference persistence forecasts. Nevertheless, we find that analysis and forecast performance depend strongly on the predominant cloud conditions. Especially convective type clouds lead to high temporal and spatial GHI variability. For cumulus cloud conditions, the analysis error is found to be lower than that introduced by a single pyranometer if it is used representatively for the whole area in distances from the camera larger than 1-2 km. Moreover, forecast skill is much higher for these conditions compared to overcast or clear sky situations causing low GHI variability which is easier to predict by persistence. In order to generalize the cloud-induced forecast error, we identify a variability threshold indicating conditions with positive forecast skill.

  8. Forecasting Cryptocurrencies Financial Time Series

    DEFF Research Database (Denmark)

    Catania, Leopoldo; Grassi, Stefano; Ravazzolo, Francesco

    2018-01-01

    This paper studies the predictability of cryptocurrencies time series. We compare several alternative univariate and multivariate models in point and density forecasting of four of the most capitalized series: Bitcoin, Litecoin, Ripple and Ethereum. We apply a set of crypto–predictors and rely...

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  20. kama Terminal Aerodrome Forecast

    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  19. kcre Terminal Aerodrome Forecast

    Data.gov (United States)

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  1. kotm Terminal Aerodrome Forecast

    Data.gov (United States)

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    Data.gov (United States)

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  3. kabr Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  5. kelp Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  7. khbg Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  8. kpbf Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  9. konp Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  10. pkwa Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  11. ktvf Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  12. paga Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  15. kpsm Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

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    Data.gov (United States)

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  18. papg Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  20. pamc Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  1. klrd Terminal Aerodrome Forecast

    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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  5. kjac Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  6. kphx Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  7. Forecasting with Option-Implied Information

    DEFF Research Database (Denmark)

    Christoffersen, Peter; Jacobs, Kris; Chang, Bo Young

    2013-01-01

    This chapter surveys the methods available for extracting information from option prices that can be used in forecasting. We consider option-implied volatilities, skewness, kurtosis, and densities. More generally, we discuss how any forecasting object that is a twice differentiable function...... of the future realization of the underlying risky asset price can utilize option-implied information in a well-defined manner. Going beyond the univariate option-implied density, we also consider results on option-implied covariance, correlation and beta forecasting, as well as the use of option......-implied information in cross-sectional forecasting of equity returns. We discuss how option-implied information can be adjusted for risk premia to remove biases in forecasting regressions....

  8. Robust forecast comparison

    OpenAIRE

    Jin, Sainan; Corradi, Valentina; Swanson, Norman

    2015-01-01

    Forecast accuracy is typically measured in terms of a given loss function. However, as a consequence of the use of misspecified models in multiple model comparisons, relative forecast rankings are loss function dependent. This paper addresses this issue by using a novel criterion for forecast evaluation which is based on the entire distribution of forecast errors. We introduce the concepts of general-loss (GL) forecast superiority and convex-loss (CL) forecast superiority, and we establish a ...

  9. On probabilistic forecasting of wind power time-series

    DEFF Research Database (Denmark)

    Pinson, Pierre

    power dynamics. In both cases, the model parameters are adaptively and recursively estimated, time-adaptativity being the result of exponential forgetting of past observations. The probabilistic forecasting methodology is applied at the Horns Rev wind farm in Denmark, for 10-minute ahead probabilistic...... forecasting of wind power generation. Probabilistic forecasts generated from the proposed methodology clearly have higher skill than those obtained from a classical Gaussian assumption about wind power predictive densities. Corresponding point forecasts also exhibit significantly lower error criteria....

  10. Forecaster Behaviour and Bias in Macroeconomic Forecasts

    OpenAIRE

    Roy Batchelor

    2007-01-01

    This paper documents the presence of systematic bias in the real GDP and inflation forecasts of private sector forecasters in the G7 economies in the years 1990–2005. The data come from the monthly Consensus Economics forecasting service, and bias is measured and tested for significance using parametric fixed effect panel regressions and nonparametric tests on accuracy ranks. We examine patterns across countries and forecasters to establish whether the bias reflects the inefficient use of i...

  11. PredPPCrys: accurate prediction of sequence cloning, protein production, purification and crystallization propensity from protein sequences using multi-step heterogeneous feature fusion and selection.

    Directory of Open Access Journals (Sweden)

    Huilin Wang

    Full Text Available X-ray crystallography is the primary approach to solve the three-dimensional structure of a protein. However, a major bottleneck of this method is the failure of multi-step experimental procedures to yield diffraction-quality crystals, including sequence cloning, protein material production, purification, crystallization and ultimately, structural determination. Accordingly, prediction of the propensity of a protein to successfully undergo these experimental procedures based on the protein sequence may help narrow down laborious experimental efforts and facilitate target selection. A number of bioinformatics methods based on protein sequence information have been developed for this purpose. However, our knowledge on the important determinants of propensity for a protein sequence to produce high diffraction-quality crystals remains largely incomplete. In practice, most of the existing methods display poorer performance when evaluated on larger and updated datasets. To address this problem, we constructed an up-to-date dataset as the benchmark, and subsequently developed a new approach termed 'PredPPCrys' using the support vector machine (SVM. Using a comprehensive set of multifaceted sequence-derived features in combination with a novel multi-step feature selection strategy, we identified and characterized the relative importance and contribution of each feature type to the prediction performance of five individual experimental steps required for successful crystallization. The resulting optimal candidate features were used as inputs to build the first-level SVM predictor (PredPPCrys I. Next, prediction outputs of PredPPCrys I were used as the input to build second-level SVM classifiers (PredPPCrys II, which led to significantly enhanced prediction performance. Benchmarking experiments indicated that our PredPPCrys method outperforms most existing procedures on both up-to-date and previous datasets. In addition, the predicted crystallization

  12. Weather forecast

    CERN Document Server

    Courtier, P

    1994-02-07

    Weather prediction is performed using the numerical model of the atmosphere evolution.The evolution equations are derived from the Navier Stokes equation for the adiabatic part but the are very much complicated by the change of phase of water, the radiation porocess and the boundary layer.The technique used operationally is described. Weather prediction is an initial value problem and accurate initial conditions need to be specified. Due to the small number of observations available (105 ) as compared to the dimension of the model state variable (107),the problem is largely underdetermined. Techniques of optimal control and inverse problems are used and have been adapted to the large dimension of our problem. our problem.The at mosphere is a chaotic system; the implication for weather prediction is discussed. Ensemble prediction is used operationally and the technique for generating initial conditions which lead to a numerical divergence of the subsequent forecasts is described.

  13. Multi-step direct reactions

    International Nuclear Information System (INIS)

    Koning, A.J.

    1992-07-01

    In recent years a variety of statistical theories has been developed concerning multistep direct (MSD) nuclear reactions. In addition, dominant in applications is a whole class of semiclassical models that may be subsumed under the heading of 'generalized exciton models'; these are basically MSD-type extensions on top of compound-like concepts. In this report the relation between their underlying statistical MSD-postulates are highlighted. A command framework is sketched that enables to generate the various MSD theories through assigning statistical properties to different parts of the nuclear Hamiltonian. Then it is shown that distinct forms of nuclear randomness are embodied in the mentioned theories. All these theories appear to be very similar at a qualitative level. In order to explain the high energy-tails and forward-peaked angular distribution typical for particles emitted in MSD reactions, it is imagined that the incident continuum particle stepwise looses its energy and direction in a sequence of collisions, thereby creating new particle-hole pairs in the target system. At each step emission may take place. The statistical aspect comes in because many continuum states are involved in the process. These are supposed to display chaotic behavior, the associated randomness assumption giving rise to important simplifications in the expression for MSD emission cross sections. This picture suggests that mentioned MSD models can be interpreted as a variant of essentially one and the same theory. 113 refs.; 25 figs.; 9 tabs

  14. Development of a new Xe-133 single dose multi-step method (SDMM) for muscle blood flow measurement using gamma camera

    International Nuclear Information System (INIS)

    Bunko, Hisashi; Seto, Mikito; Taki, Junichi

    1985-01-01

    In order to measure the muscle blood flow (MBF) during exercise (Ex), a new Xe-133 single dose multi-step method (SDMM) for leg MBF measurement before, during and after Ex using gamma camera was developped. Theoretically, if the activity of Xe-133 in the muscle immediately before and after Ex are known, then the mean MBF during Ex can be calculated. In SDMM, these activities are corrected through correction formula using time delays between end of data aquisition (DA) at rest (R1) and begining of the Ex (TAB), and between end of Ex and begining of the DA after Ex (R2) (TDA). Validity of the SDMM and MBF response on mild and heavy Ex were evaluated in 11 normal volunteers. Ex MBF calculated from 5 and 2.5 min DA (5 sec/frame) both at R1 and R2 were highly correlated (r=.996). Ex MBF by SDMM and direct(measurement by fixed leg exercise were also highly correlated (r=.999). Reproducibility of the R1 and Ex MBF were excellent (r=.999). The highest MBF was seen in GCM on miled walking Ex and in VLM on heavy squatting Ex. After miled Ex, MBF rapidly returned to normal. After heavy Ex, MBF remaind high in VLM In conclusion, SDMM is simple and accurate method for evaluation of dynamic MBF response according to exercise. SDMM is also applicable to the field of sports medicine. (author)

  15. Batch and multi-step fed-batch enzymatic saccharification of Formiline-pretreated sugarcane bagasse at high solid loadings for high sugar and ethanol titers.

    Science.gov (United States)

    Zhao, Xuebing; Dong, Lei; Chen, Liang; Liu, Dehua

    2013-05-01

    Formiline pretreatment pertains to a biomass fractionation process. In the present work, Formiline-pretreated sugarcane bagasse was hydrolyzed with cellulases by batch and multi-step fed-batch processes at 20% solid loading. For wet pulp, after 144 h incubation with cellulase loading of 10 FPU/g dry solid, fed-batch process obtained ~150 g/L glucose and ~80% glucan conversion, while batch process obtained ~130 g/L glucose with corresponding ~70% glucan conversion. Solid loading could be further increased to 30% for the acetone-dried pulp. By fed-batch hydrolysis of the dried pulp in pH 4.8 buffer solution, glucose concentration could be 247.3±1.6 g/L with corresponding 86.1±0.6% glucan conversion. The enzymatic hydrolyzates could be well converted to ethanol by a subsequent fermentation using Saccharomices cerevisiae with ethanol titer of 60-70 g/L. Batch and fed-batch SSF indicated that Formiline-pretreated substrate showed excellent fermentability. The final ethanol concentration was 80 g/L with corresponding 82.7% of theoretical yield. Copyright © 2012 Elsevier Ltd. All rights reserved.

  16. Analyzing powers and interference between one- and multi-step processes in (polarized p, t) reactions on medium-mass vibrational nuclei

    International Nuclear Information System (INIS)

    Yagi, K.; Kunori, S.; Aoki, Y.; Nagano, K.; Tagishi, Y.

    1978-01-01

    A neutron-number (N) dependence of analyzing powers A (theta) has been observed for the first time in (polarized p, t) reactions leading to the quadrupole vibrational states (2 1 + ) in 98 Ru, sup(102,108)Pd, 114 Cd, 116 Sn, and sup(120,126)Te. Although analyzing powers for the ground-state transitions A(theta,0 sub(g)sup(+)) are very similar to each other, those for the 2 1 + transitions A(theta,2 1 + ) for the nuclei belonging to the beginning of the N = 50 - 82 shell are markedly different, having almost opposite signs, from A(theta,2 1 + ) for nuclei belonging to the latter half of the major shell. The difference is explained as a result of a sign change of the interference between one- and inelastic multi-step processes in two-neutron pickup reactions. Nuclear structure effects on such an interference are discussed on the basis of the microscopic description of collective quadrupole oscillation of nuclei. (author)

  17. A multi-step approach for testing non-toxic amphiphilic antifouling coatings against marine microfouling at different levels of biological complexity.

    Science.gov (United States)

    Zecher, Karsten; Aitha, Vishwa Prasad; Heuer, Kirsten; Ahlers, Herbert; Roland, Katrin; Fiedel, Michael; Philipp, Bodo

    2018-03-01

    Marine biofouling on artificial surfaces such as ship hulls or fish farming nets causes enormous economic damage. The time for the developmental process of antifouling coatings can be shortened by reliable laboratory assays. For designing such test systems, it is important that toxic effects can be excluded, that multiple parameters can be addressed simultaneously and that mechanistic aspects can be included. In this study, a multi-step approach for testing antifouling coatings was established employing photoautotrophic biofilm formation of marine microorganisms in micro- and mesoscoms. Degree and pattern of biofilm formation was determined by quantification of chlorophyll fluorescence. For the microcosms, co-cultures of diatoms and a heterotrophic bacterium were exposed to fouling-release coatings. For the mesocosms, a novel device was developed that permits parallel quantification of a multitude of coatings under defined conditions with varying degrees of shear stress. Additionally, the antifouling coatings were tested for leaching of potential compounds and finally tested in sea trials. This multistep-approach revealed that the individual steps led to consistent results regarding antifouling activity of the coatings. Furthermore, the novel mesocosm system can be employed for advanced antifouling analysis including metagenomic approaches for determination of microbial diversity attaching to different coatings under changing shear forces. Copyright © 2018 Elsevier B.V. All rights reserved.

  18. A multi-step pathway connecting short sleep duration to daytime somnolence, reduced attention, and poor academic performance: an exploratory cross-sectional study in teenagers.

    Science.gov (United States)

    Perez-Lloret, Santiago; Videla, Alejandro J; Richaudeau, Alba; Vigo, Daniel; Rossi, Malco; Cardinali, Daniel P; Perez-Chada, Daniel

    2013-05-15

    A multi-step causality pathway connecting short sleep duration to daytime somnolence and sleepiness leading to reduced attention and poor academic performance as the final result can be envisaged. However this hypothesis has never been explored. To explore consecutive correlations between sleep duration, daytime somnolence, attention levels, and academic performance in a sample of school-aged teenagers. We carried out a survey assessing sleep duration and daytime somnolence using the Pediatric Daytime Sleepiness Scale (PDSS). Sleep duration variables included week-days' total sleep time, usual bedtimes, and absolute weekday to-weekend sleep time difference. Attention was assessed by d2 test and by the coding subtest from the WISC-IV scale. Academic performance was obtained from literature and math grades. Structural equation modeling was used to assess the independent relationships between these variables, while controlling for confounding effects of other variables, in one single model. Standardized regression weights (SWR) for relationships between these variables are reported. Study sample included 1,194 teenagers (mean age: 15 years; range: 13-17 y). Sleep duration was inversely associated with daytime somnolence (SWR = -0.36, p academic results (SWR = 0.18, p academic achievements (SWR = -0.16, p sleep duration influenced attention through daytime somnolence (p academic achievements through reduced attention (p academic achievements correlated with reduced attention, which in turn was related to daytime somnolence. Somnolence correlated with short sleep duration.

  19. Grain refinement in a AlZnMgCuTi alloy by intensive melt shearing: A multi-step nucleation mechanism

    Science.gov (United States)

    Li, H. T.; Xia, M.; Jarry, Ph.; Scamans, G. M.; Fan, Z.

    2011-01-01

    Direct chill (DC) cast ingots of wrought Al alloys conventionally require the deliberate addition of a grain refiner to provide a uniform as-cast microstructure for the optimisation of both mechanical properties and processability. Grain refiner additions have been in widespread industrial use for more than half a century. Intensive melt shearing can provide grain refinement without the need for a specific grain refiner addition for both magnesium and aluminium based alloys. In this paper we present experimental evidence of the grain refinement in an experimental wrought aluminium alloy achieved by intensive melt shearing in the liquid state prior to solidification. The mechanisms for high shear induced grain refinement are correlated with the evolution of oxides in alloys. The oxides present in liquid aluminium alloys, normally as oxide films and clusters, can be effectively dispersed by intensive shearing and then provide effective sites for the heterogeneous nucleation of Al 3Ti phase. As a result, Al 3Ti particles with a narrower size distribution and hence improved efficiency as active nucleation sites of α-aluminium grains are responsible for the achieved significant grain refinement. This is termed a multi-step nucleation mechanism.

  20. MSBIS: A Multi-Step Biomedical Informatics Screening Approach for Identifying Medications that Mitigate the Risks of Metoclopramide-Induced Tardive Dyskinesia.

    Science.gov (United States)

    Xu, Dong; Ham, Alexandrea G; Tivis, Rickey D; Caylor, Matthew L; Tao, Aoxiang; Flynn, Steve T; Economen, Peter J; Dang, Hung K; Johnson, Royal W; Culbertson, Vaughn L

    2017-12-01

    In 2009 the U.S. Food and Drug Administration (FDA) placed a black box warning on metoclopramide (MCP) due to the increased risks and prevalence of tardive dyskinesia (TD). In this study, we developed a multi-step biomedical informatics screening (MSBIS) approach leveraging publicly available bioactivity and drug safety data to identify concomitant drugs that mitigate the risks of MCP-induced TD. MSBIS includes (1) TargetSearch (http://dxulab.org/software) bioinformatics scoring for drug anticholinergic activity using CHEMBL bioactivity data; (2) unadjusted odds ratio (UOR) scoring for indications of TD-mitigating effects using the FDA Adverse Event Reporting System (FAERS); (3) adjusted odds ratio (AOR) re-scoring by removing the effect of cofounding factors (age, gender, reporting year); (4) logistic regression (LR) coefficient scoring for confirming the best TD-mitigating drug candidates. Drugs with increasing TD protective potential and statistical significance were obtained at each screening step. Fentanyl is identified as the most promising drug against MCP-induced TD (coefficient: -2.68; p-valueTD after fentanyl-induced general anesthesia. Loperamide is identified as a potent mitigating drug against a broader range of drug-induced movement disorders through pharmacokinetic modifications. Using drug-induced TD as an example, we demonstrated that MSBIS is an efficient in silico tool for unknown drug-drug interaction detection, drug repurposing, and combination therapy design. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  1. National Forecast Charts

    Science.gov (United States)

    code. Press enter or select the go button to submit request Local forecast by "City, St" or Prediction Center on Twitter NCEP Quarterly Newsletter WPC Home Analyses and Forecasts National Forecast to all federal, state, and local government web resources and services. National Forecast Charts

  2. Are Forecast Updates Progressive?

    NARCIS (Netherlands)

    C-L. Chang (Chia-Lin); Ph.H.B.F. Franses (Philip Hans); M.J. McAleer (Michael)

    2010-01-01

    textabstractMacro-economic forecasts typically involve both a model component, which is replicable, as well as intuition, which is non-replicable. Intuition is expert knowledge possessed by a forecaster. If forecast updates are progressive, forecast updates should become more accurate, on average,

  3. Forecasting freight flows

    DEFF Research Database (Denmark)

    Lyk-Jensen, Stéphanie

    2011-01-01

    Trade patterns and transport markets are changing as a result of the growth and globalization of international trade, and forecasting future freight flow has to rely on trade forecasts. Forecasting freight flows is critical for matching infrastructure supply to demand and for assessing investment...... constitute a valuable input to freight models for forecasting future capacity problems.......Trade patterns and transport markets are changing as a result of the growth and globalization of international trade, and forecasting future freight flow has to rely on trade forecasts. Forecasting freight flows is critical for matching infrastructure supply to demand and for assessing investment...

  4. The Effects of Vent Location, Event Scale, and Time Forecasts on Pyroclastic Density Current Hazard Maps at Campi Flegrei Caldera (Italy

    Directory of Open Access Journals (Sweden)

    Andrea Bevilacqua

    2017-09-01

    Full Text Available This study presents a new method for producing long-term hazard maps for pyroclastic density currents (PDC originating at Campi Flegrei caldera. Such method is based on a doubly stochastic approach and is able to combine the uncertainty assessments on the spatial location of the volcanic vent, the size of the flow and the expected time of such an event. The results are obtained by using a Monte Carlo approach and adopting a simplified invasion model based on the box model integral approximation. Temporal assessments are modeled through a Cox-type process including self-excitement effects, based on the eruptive record of the last 15 kyr. Mean and percentile maps of PDC invasion probability are produced, exploring their sensitivity to some sources of uncertainty and to the effects of the dependence between PDC scales and the caldera sector where they originated. Conditional maps representative of PDC originating inside limited zones of the caldera, or of PDC with a limited range of scales are also produced. Finally, the effect of assuming different time windows for the hazard estimates is explored, also including the potential occurrence of a sequence of multiple events. Assuming that the last eruption of Monte Nuovo (A.D. 1538 marked the beginning of a new epoch of activity similar to the previous ones, results of the statistical analysis indicate a mean probability of PDC invasion above 5% in the next 50 years on almost the entire caldera (with a probability peak of ~25% in the central part of the caldera. In contrast, probability values reduce by a factor of about 3 if the entire eruptive record is considered over the last 15 kyr, i.e., including both eruptive epochs and quiescent periods.

  5. Effect of caries-affected dentin on one-step universal and multi-step etch-and-rinse adhesives’ bond strength

    Directory of Open Access Journals (Sweden)

    Clecila MÜLLER

    2017-10-01

    Full Text Available Abstract Objective To evaluate the influence of caries-affected dentin on bond strength of a universal one-step and a multi-step etch-and-rinse adhesive system. Material and method Enamel of 60 third human molars with and without caries was removed to expose dentin. The teeth were randomly assigned to six groups: Single Bond Universal (3M ESPE, St. Paul, MN, USA in etch-and-rinse and in self-etch mode and Prime & Bond NT (Dentsply Co, Konstanz, Germany, all on sound and caries-affected dentin. Smear layer of the 30 sound dentin specimens was standardized by polishing with 600-grit SiC paper under water cooling. Residual infected dentin of the 30 caries-affected specimens was removed with a number 4 CA carbide bur until no caries smooth tissue was detectable by tactile-visual inspection. Cylinders of a light cured composite resin (Filtek Z350 XT, 3M ESPE were built up using starch tubes and microshear test was performed until failure. The data was analyzed by one-way ANOVA and Tukey’s post hoc test. Result Significant differences in microshear bond strength (μSBS were observed for the caries-affected groups, but not for sound dentin. The μSBS of Single Bond Universal were not influenced by the application protocol on sound dentin, however they were lower in the caries-affected group with both application protocols. The μSBS for Prime & Bond NT was not influenced by the dentin conditions. Conclusion Caries-affected dentin decrease in bond strength of Single Bond Universal in comparison to sound dentin. The bond strength of Prime & Bond NT was not altered by substrate conditions.

  6. Treatment for the recoil effects of the multi-step heavy-ion nucleon transfers with the orthogonalized coupled-reaction-channel theory

    International Nuclear Information System (INIS)

    Misono, S.; Imanishi, B.

    1997-02-01

    We have investigated recoil effects in heavy-ion reactions for the nucleon transfers, and the validity of the spatially local approximation for the non-local transfer interaction defined by the orthogonalized coupled-reaction-channel (OCRC) theory. This approximation makes it easier to treat multi-step transfer processes with the coupled channel method and makes it possible to define the nucleon molecular orbitals with the inclusion of the recoil effects. The transfer interaction is expanded in a power series of the momentum operator, and is approximated by the first order term, i.e., the spatially local term. The numerical calculation for the core-symmetric systems 12 C+ 13 C and 16 O+ 17 O with this approximation shows that the recoil effects are well included in the results at energies lower than a few MeV/nucleon. Furthermore, the OCRC formalism allows us even to employ the complete no-recoil approximation for the calculation of cross sections, even though it is not adequate to use this approximation in the distorted wave Born approximation (DWBA) method. As to polarization, however, the no-recoil approximation is not good even in the OCRC formalism. We discuss the recoil effects on nucleon molecular-orbital states. It is shown that states of the covalent molecular orbitals of the valence (transferred) nucleon are little affected by the recoil effects, as already suggested by Korotky et al. in the full finite-range DWBA analysis of the transfer reaction, 13 C( 13 C, 12 C) 14 C. (author). 59 refs

  7. MSBIS: A Multi-Step Biomedical Informatics Screening Approach for Identifying Medications that Mitigate the Risks of Metoclopramide-Induced Tardive Dyskinesia

    Directory of Open Access Journals (Sweden)

    Dong Xu

    2017-12-01

    Full Text Available In 2009 the U.S. Food and Drug Administration (FDA placed a black box warning on metoclopramide (MCP due to the increased risks and prevalence of tardive dyskinesia (TD. In this study, we developed a multi-step biomedical informatics screening (MSBIS approach leveraging publicly available bioactivity and drug safety data to identify concomitant drugs that mitigate the risks of MCP-induced TD. MSBIS includes (1 TargetSearch (http://dxulab.org/software bioinformatics scoring for drug anticholinergic activity using CHEMBL bioactivity data; (2 unadjusted odds ratio (UOR scoring for indications of TD-mitigating effects using the FDA Adverse Event Reporting System (FAERS; (3 adjusted odds ratio (AOR re-scoring by removing the effect of cofounding factors (age, gender, reporting year; (4 logistic regression (LR coefficient scoring for confirming the best TD-mitigating drug candidates. Drugs with increasing TD protective potential and statistical significance were obtained at each screening step. Fentanyl is identified as the most promising drug against MCP-induced TD (coefficient: −2.68; p-value < 0.01. The discovery is supported by clinical reports that patients fully recovered from MCP-induced TD after fentanyl-induced general anesthesia. Loperamide is identified as a potent mitigating drug against a broader range of drug-induced movement disorders through pharmacokinetic modifications. Using drug-induced TD as an example, we demonstrated that MSBIS is an efficient in silico tool for unknown drug-drug interaction detection, drug repurposing, and combination therapy design.

  8. Flood forecasting and uncertainty of precipitation forecasts

    International Nuclear Information System (INIS)

    Kobold, Mira; Suselj, Kay

    2004-01-01

    The timely and accurate flood forecasting is essential for the reliable flood warning. The effectiveness of flood warning is dependent on the forecast accuracy of certain physical parameters, such as the peak magnitude of the flood, its timing, location and duration. The conceptual rainfall - runoff models enable the estimation of these parameters and lead to useful operational forecasts. The accurate rainfall is the most important input into hydrological models. The input for the rainfall can be real time rain-gauges data, or weather radar data, or meteorological forecasted precipitation. The torrential nature of streams and fast runoff are characteristic for the most of the Slovenian rivers. Extensive damage is caused almost every year- by rainstorms affecting different regions of Slovenia' The lag time between rainfall and runoff is very short for Slovenian territory and on-line data are used only for now casting. Forecasted precipitations are necessary for hydrological forecast for some days ahead. ECMWF (European Centre for Medium-Range Weather Forecasts) gives general forecast for several days ahead while more detailed precipitation data with limited area ALADIN/Sl model are available for two days ahead. There is a certain degree of uncertainty using such precipitation forecasts based on meteorological models. The variability of precipitation is very high in Slovenia and the uncertainty of ECMWF predicted precipitation is very large for Slovenian territory. ECMWF model can predict precipitation events correctly, but underestimates amount of precipitation in general The average underestimation is about 60% for Slovenian region. The predictions of limited area ALADIN/Si model up to; 48 hours ahead show greater applicability in hydrological forecasting. The hydrological models are sensitive to precipitation input. The deviation of runoff is much bigger than the rainfall deviation. Runoff to rainfall error fraction is about 1.6. If spatial and time distribution

  9. Forecasting Cryptocurrencies Financial Time Series

    OpenAIRE

    Catania, Leopoldo; Grassi, Stefano; Ravazzolo, Francesco

    2018-01-01

    This paper studies the predictability of cryptocurrencies time series. We compare several alternative univariate and multivariate models in point and density forecasting of four of the most capitalized series: Bitcoin, Litecoin, Ripple and Ethereum. We apply a set of crypto–predictors and rely on Dynamic Model Averaging to combine a large set of univariate Dynamic Linear Models and several multivariate Vector Autoregressive models with different forms of time variation. We find statistical si...

  10. Efficient Resources Provisioning Based on Load Forecasting in Cloud

    Directory of Open Access Journals (Sweden)

    Rongdong Hu

    2014-01-01

    Full Text Available Cloud providers should ensure QoS while maximizing resources utilization. One optimal strategy is to timely allocate resources in a fine-grained mode according to application’s actual resources demand. The necessary precondition of this strategy is obtaining future load information in advance. We propose a multi-step-ahead load forecasting method, KSwSVR, based on statistical learning theory which is suitable for the complex and dynamic characteristics of the cloud computing environment. It integrates an improved support vector regression algorithm and Kalman smoother. Public trace data taken from multitypes of resources were used to verify its prediction accuracy, stability, and adaptability, comparing with AR, BPNN, and standard SVR. Subsequently, based on the predicted results, a simple and efficient strategy is proposed for resource provisioning. CPU allocation experiment indicated it can effectively reduce resources consumption while meeting service level agreements requirements.

  11. Fuel cycle forecasting - there are forecasts and there are forecasts

    Energy Technology Data Exchange (ETDEWEB)

    Puechl, K H

    1975-12-01

    The FORECAST-NUCLEAR computer program described recognizes that forecasts are made to answer a variety of questions and, therefore, that no single forecast is universally appropriate. Also, it recognizes that no two individuals will completely agree as to the input data that are appropriate for obtaining an answer to even a single simple question. Accordingly, the program was written from a utilitarian standpoint: it allows working with multiple projections; data inputting is simple to allow game-playing; computation time is short to minimize the cost of 'what if' assessements; and detail is internally carried to allow meaningful analysis.

  12. Fuel cycle forecasting - there are forecasts and there are forecasts

    International Nuclear Information System (INIS)

    Puechl, K.H.

    1975-01-01

    The FORECAST-NUCLEAR computer program described recognizes that forecasts are made to answer a variety of questions and, therefore, that no single forecast is universally appropriate. Also, it recognizes that no two individuals will completely agree as to the input data that are appropriate for obtaining an answer to even a single simple question. Accordingly, the program was written from a utilitarian standpoint: it allows working with multiple projections; data inputting is simple to allow game-playing; computation time is short to minimize the cost of 'what if' assessements; and detail is internally carried to allow meaningful analysis. (author)

  13. Prevalence of fibromyalgia in France: a multi-step study research combining national screening and clinical confirmation: The DEFI study (Determination of Epidemiology of FIbromyalgia

    Directory of Open Access Journals (Sweden)

    Ravaud Philippe

    2011-10-01

    Full Text Available Abstract Background Fibromyalgia is a common disease, but little is known on its real prevalence in France. This epidemiological study aimed to assess fibromyalgia (FM prevalence in the French metropolitan population, based on a multi-step sampling analysis, combining national screening and clinical confirmation by trained specialists. Methods a sampling method on the entire national territory was used: patients over 18 years of age accepting to take part in the study were contacted by telephone using the LFES Questionnaire, a screening test for FM. The, for patients detected by the LFESQ, a visit with a FM-trained rheumatologist was proposed to confirm FM, based on 1990 ACR criteria. Each detected patient completed the following self-questionnaires: SF36, HADS, stress VAS, Co-morbidities and Regional pain score. Results 3081 patients were contacted in 5 representative French regions, of which 232 patients were screened for FM. A fibromyalgia diagnosis was then confirmed by rheumatologist in 20 cases (17 female and 3 male, 56.9 ± 13.2 years. The final estimated FM prevalence was 1.6 (CI95: 1.2%; 2.0%. No significant difference was detected between the patients accepting (CS+ and refusing (CS- rheumatologist visit for the SF36 score, regional pain score, stress VAS scale and co-morbidities. In patients detected for FM by the LFESQ, we found a statistically significant decrease in quality of life and a statistically significant increase in stress level in patients with a confirmed diagnosis (FM+ (6.3 ± 1.9 compared to patients with an invalidated diagnosis (FM- (4.4 ± 2.8; p = 0.007. The study also demonstrated a significant association, independently of ACR criteria, between the diagnosis of FM and several factors such as regional pain score > 10, elevated stress level, low SF36 scale score and presence of gastro-intestinal disorder co-morbidities. Conclusion Fibromyalgia is a common condition; the 1.6% prevalence calculated in the French

  14. A multi-step method with signal quality assessment and fine-tuning procedure to locate maternal and fetal QRS complexes from abdominal ECG recordings

    International Nuclear Information System (INIS)

    Liu, Chengyu; Li, Peng; Zhao, Lina; Di Maria, Costanzo; Zhang, Henggui; Chen, Zhiqing

    2014-01-01

    Non-invasive monitoring of fetal electrocardiogram (fECG) plays an important role in detecting and diagnosing fetal diseases. This study aimed to develop a multi-step method for locating both maternal and fetal QRS complexes from abdominal ECG (aECG) recordings. The proposed method included four major steps: abdominal ECG pre-processing, maternal QRS complex locating, maternal ECG cancellation and fetal QRS complex locating. Signal quality assessment (SQA) and fine-tuning for maternal ECG (FTM) were implemented in the first and third steps, respectively. The method was then evaluated using 75 non-invasive 4-channel aECG recordings provided by the PhysioNet/Computing in Cardiology Challenge 2013. The F 1 measure, which is a new index introduced by Behar et al (2013 Proc. Comput. Cardiol. 40 297–300), was used to assess the locating accuracy. The other two indices, mean squared error of heart rate (MSE H R) between the fetal HR signals estimated from the reference and our method (MSE H R in bpm 2 ) and root mean squared difference between the corresponding fetal RR intervals (MSE R R in ms) were also used to assess the locating accuracy. Overall, for the maternal QRS complex, the F 1 measure was 98.4% from the method without the implementation of SQA, and it was improved to 99.8% with SQA. For the fetal QRS complex, the F 1 measure, MSE H R and MSE R R were 84.9%, 185.6 bpm 2 and 19.4 ms for the method without both SQA and FTM procedures. They were improved to 93.9%, 47.5 bpm 2 and 7.6 ms with both SQA and FTM procedures. These improvements were observed from each individual subject. It can be concluded that implementing both SQA and FTM procedures could achieve better performance for locating both maternal and fetal QRS complexes. (paper)

  15. In vitro response of human osteoblasts to multi-step sol–gel derived bioactive glass nanoparticles for bone tissue engineering

    International Nuclear Information System (INIS)

    Fan, Jian Ping; Kalia, Priya; Di Silvio, Lucy; Huang, Jie

    2014-01-01

    A multi-step sol–gel process was employed to synthesize bioactive glass (BG) nanoparticles. Transmission electron microscopy (TEM) revealed that the BG nanoparticles were spherical and ranged from 30 to 60 nm in diameter. In vitro reactivity of the BG nanoparticles was tested in phosphate buffer saline (PBS), Tris-buffer (TRIS), simulated body fluid (SBF), and Dulbecco's modified Eagle's medium (DMEM), in comparison with similar sized hydroxyapatite (HA) and silicon substituted HA (SiHA) nanoparticles. Bioactivity of the BG nanoparticles was confirmed through Fourier transform infrared spectroscopy (FTIR) analysis. It was found that bone-like apatite was formed after immersion in SBF at 7 days. Solutions containing BG nanoparticles were slightly more alkaline than HA and SiHA, suggesting that a more rapid apatite formation on BG was related to solution-mediated dissolution. Primary human osteoblast (HOB) cell model was used to evaluate biological responses to BG nanoparticles. Lactate dehydrogenase (LDH) cytotoxicity assay showed that HOB cells were not adversely affected by the BG nanoparticles throughout the 7 day test period. Interestingly, MTS assay results showed an enhancement in cell proliferation in the presence of BG when compared to HA and SiHA nanoparticles. Particularly, statistically significant (p < 0.05) alkaline phosphatase (ALP) activity of HOB cells was found on the culture containing BG nanoparticles, suggesting that the cell differentiation might be promoted by BG. Real-time quantitative PCR analysis (qPCR) further confirmed this finding, as a significantly higher level of RUNX2 gene expression was recorded on the cells cultured in the presence of BG nanoparticles when compared to those with HA and SiHA. - Highlights: • Spherical bioactive glass nanoparticles (BG) under 60 nm were synthesized. • An alkali morphological catalyst was used in the synthesis. • Cytotoxicity assays demonstrated that BG was not cytotoxic towards HOB

  16. Evaluation of glycodendron and synthetically-modified dextran clearing agents for multi-step targeting of radioisotopes for molecular imaging and radioimmunotherapy

    Science.gov (United States)

    Cheal, Sarah M.; Yoo, Barney; Boughdad, Sarah; Punzalan, Blesida; Yang, Guangbin; Dilhas, Anna; Torchon, Geralda; Pu, Jun; Axworthy, Don B.; Zanzonico, Pat; Ouerfelli, Ouathek; Larson, Steven M.

    2014-01-01

    A series of N-acetylgalactosamine-dendrons (NAG-dendrons) and dextrans bearing biotin moieties were compared for their ability to complex with and sequester circulating bispecific anti-tumor antibody (scFv4) streptavidin (SA) fusion protein (scFv4-SA) in vivo, to improve tumor to normal tissue concentration ratios for targeted radioimmunotherapy and diagnosis. Specifically, a total of five NAG-dendrons employing a common synthetic scaffold structure containing 4, 8, 16, or 32 carbohydrate residues and a single biotin moiety were prepared (NAGB), and for comparative purposes, a biotinylated-dextran with average molecular weight (MW) of 500 kD was synthesized from amino-dextran (DEXB). One of the NAGB compounds, CA16, has been investigated in humans; our aim was to determine if other NAGB analogs (e.g. CA8 or CA4) were bioequivalent to CA16 and/or better suited as MST reagents. In vivo studies included dynamic positron-emission tomography (PET) imaging of 124I-labelled-scFv4-SA clearance and dual-label biodistribution studies following multi-step targeting (MST) directed at subcutaneous (s.c.) human colon adenocarcinoma xenografts in mice. The MST protocol consists of three injections: first, a bispecific antibody specific for an anti-tumor associated glycoprotein (TAG-72) single chain genetically-fused with SA (scFv4-SA); second, CA16 or other clearing agent; and third, radiolabeled biotin. We observed using PET imaging of 124I-labelled-scFv4-SA clearance that the spatial arrangement of ligands conjugated to NAG (i.e. biotin) can impact the binding to antibody in circulation and subsequent liver uptake of the NAG-antibody complex. Also, NAGB CA32-LC or CA16-LC can be utilized during MST to achieve comparable tumor- to-blood ratios and absolute tumor uptake seen previously with CA16. Finally, DEXB was equally effective as NAGB CA32-LC at lowering scFv4-SA in circulation, but at the expense of reducing absolute tumor uptake of radiolabeled biotin. PMID:24219178

  17. Robust Approaches to Forecasting

    OpenAIRE

    Jennifer Castle; David Hendry; Michael P. Clements

    2014-01-01

    We investigate alternative robust approaches to forecasting, using a new class of robust devices, contrasted with equilibrium correction models. Their forecasting properties are derived facing a range of likely empirical problems at the forecast origin, including measurement errors, implulses, omitted variables, unanticipated location shifts and incorrectly included variables that experience a shift. We derive the resulting forecast biases and error variances, and indicate when the methods ar...

  18. Inflation Forecast Contracts

    OpenAIRE

    Gersbach, Hans; Hahn, Volker

    2012-01-01

    We introduce a new type of incentive contract for central bankers: inflation forecast contracts, which make central bankers’ remunerations contingent on the precision of their inflation forecasts. We show that such contracts enable central bankers to influence inflation expectations more effectively, thus facilitating more successful stabilization of current inflation. Inflation forecast contracts improve the accuracy of inflation forecasts, but have adverse consequences for output. On balanc...

  19. How uncertain are day-ahead wind forecasts?

    Energy Technology Data Exchange (ETDEWEB)

    Grimit, E. [3TIER Environmental Forecast Group, Seattle, WA (United States)

    2006-07-01

    Recent advances in the combination of weather forecast ensembles with Bayesian statistical techniques have helped to address uncertainties in wind forecasting. Weather forecast ensembles are a collection of numerical weather predictions. The combination of several equally-skilled forecasts typically results in a consensus forecast with greater accuracy. The distribution of forecasts also provides an estimate of forecast inaccuracy. However, weather forecast ensembles tend to be under-dispersive, and not all forecast uncertainties can be taken into account. In order to address these issues, a multi-variate linear regression approach was used to correct the forecast bias for each ensemble member separately. Bayesian model averaging was used to provide a predictive probability density function to allow for multi-modal probability distributions. A test location in eastern Canada was used to demonstrate the approach. Results of the test showed that the method improved wind forecasts and generated reliable prediction intervals. Prediction intervals were much shorter than comparable intervals based on a single forecast or on historical observations alone. It was concluded that the approach will provide economic benefits to both wind energy developers and investors. refs., tabs., figs.

  20. Multi-step processes in the (d, t) and (d, {sup 3}He) reactions on {sup 116}Sn and {sup 208}Pb targets at E{sub d} = 200 MeV

    Energy Technology Data Exchange (ETDEWEB)

    Langevin-Joliot, H.; Van de Wiele, J.; Guillot, J. [Institut de Physique Nucleaire, IN2P3/CNRS, 91 - Orsay (France); Koning, A.J. [Nuclear Research and Consultancy Group NRG, NL (Netherlands)

    2000-07-01

    The role of multi-step processes in the reactions {sup 116}Sn(d,t), {sup 208}Pb(d,t) and {sup 116}Sn(d,{sup 3}He), previously studied at E{sub d} = 200 MeV at forward angles and for relatively low energy transfers, has been investigated. We have performed for the first time multi-step calculations taking into account systematically collective excitations in the second and higher order step inelastic transitions. A calculation code based on the Feshbach, Kerman and Koonin model has been modified to handle explicitly these collective excitations, most important in the forward angle domain. One step double differential pick-up cross sections were built from finite range distorted wave results spread in energy using known or estimated hole state characteristics. It is shown that two-step cross sections calculated using the above method compare rather well with those deduced via coupled channel calculations for the same collective excitations. The multi-step calculations performed up to 6 steps reproduce reasonably well the {sup 115}Sn, {sup 207}Pb and {sup 115}In experimental spectra measured up to E{sub x}{approx}- 40 MeV and 15 deg. The relative contributions of steps of increasing order to pick-up cross sections at E{sub d} = 200 MeV and 150 MeV are discussed. (authors)

  1. Electricity demand forecasting techniques

    International Nuclear Information System (INIS)

    Gnanalingam, K.

    1994-01-01

    Electricity demand forecasting plays an important role in power generation. The two areas of data that have to be forecasted in a power system are peak demand which determines the capacity (MW) of the plant required and annual energy demand (GWH). Methods used in electricity demand forecasting include time trend analysis and econometric methods. In forecasting, identification of manpower demand, identification of key planning factors, decision on planning horizon, differentiation between prediction and projection (i.e. development of different scenarios) and choosing from different forecasting techniques are important

  2. Spatial electric load forecasting

    CERN Document Server

    Willis, H Lee

    2002-01-01

    Containing 12 new chapters, this second edition contains offers increased-coverage of weather correction and normalization of forecasts, anticipation of redevelopment, determining the validity of announced developments, and minimizing risk from over- or under-planning. It provides specific examples and detailed explanations of key points to consider for both standard and unusual utility forecasting situations, information on new algorithms and concepts in forecasting, a review of forecasting pitfalls and mistakes, case studies depicting challenging forecast environments, and load models illustrating various types of demand.

  3. Sirocco - Fukushima Forecast Description

    International Nuclear Information System (INIS)

    2011-01-01

    SYMPHONIE-NH is the non-hydrostatic ocean model following the Boussinesq hydrostatic SYMPHONIE-2010 model developed by the Sirocco system team (CNRS and Toulouse University). Both are using an Arakawa type finite difference method for the C grid. The R and D team generally gives priority to a physically based approach of modelling (global conservation of the mechanical energy, consistency of pressure and density, accuracy of the bottom pressure torque,...) that tends to favour low order and robust numerical schemes. Most of the physical and numerical options (Non-Hydrostatic, free surface, generalised coordinates combined to an ALE method,...) are particularly suitable for the coastal area. At the request of the International Atomic Energy Agency (IAEA, March 14, 2011), SIROCCO is delivering every day a real time 6-day forecast bulletin of the dispersion in seawater of radionuclides emitted by the Fukushima nuclear plant. The simulations are based on the S2010.18 release of the 3D SIROCCO ocean circulation model. The system is operational since March 24 and the bulletin is available on an 'open-access' basis since March 28. The model uses a stretched horizontal grid with a variable horizontal resolution: from 600 m x 600 m at the nearest grid point from Fukushima, to 5 km x 5 km offshore. The initial fields (T, S, U, V, SSH) and the lateral open boundary conditions are provided by the Mercator PSY4V1R3 system (one field per day, horizontal resolution 1/12 deg. x 1/12 deg.). At the sea surface, the ocean model is forced by the meteorological fluxes delivered every 3 hours by ECMWF.i The tidal forcing at the lateral open boundaries is provided by the T-UGO model, implemented for this purpose by the SIROCCO team on the Japanese Pacific coast. Some details are given on the methodology: Bathymetry, Initialization and large scale forcing, Tides, Atmospheric forcing, Forecast protocol, and Scenario for radioactive tracers

  4. Sirocco - Fukushima Forecast Description

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2011-04-10

    SYMPHONIE-NH is the non-hydrostatic ocean model following the Boussinesq hydrostatic SYMPHONIE-2010 model developed by the Sirocco system team (CNRS and Toulouse University). Both are using an Arakawa type finite difference method for the C grid. The R and D team generally gives priority to a physically based approach of modelling (global conservation of the mechanical energy, consistency of pressure and density, accuracy of the bottom pressure torque,...) that tends to favour low order and robust numerical schemes. Most of the physical and numerical options (Non-Hydrostatic, free surface, generalised coordinates combined to an ALE method,...) are particularly suitable for the coastal area. At the request of the International Atomic Energy Agency (IAEA, March 14, 2011), SIROCCO is delivering every day a real time 6-day forecast bulletin of the dispersion in seawater of radionuclides emitted by the Fukushima nuclear plant. The simulations are based on the S2010.18 release of the 3D SIROCCO ocean circulation model. The system is operational since March 24 and the bulletin is available on an 'open-access' basis since March 28. The model uses a stretched horizontal grid with a variable horizontal resolution: from 600 m x 600 m at the nearest grid point from Fukushima, to 5 km x 5 km offshore. The initial fields (T, S, U, V, SSH) and the lateral open boundary conditions are provided by the Mercator PSY4V1R3 system (one field per day, horizontal resolution 1/12 deg. x 1/12 deg.). At the sea surface, the ocean model is forced by the meteorological fluxes delivered every 3 hours by ECMWF.i The tidal forcing at the lateral open boundaries is provided by the T-UGO model, implemented for this purpose by the SIROCCO team on the Japanese Pacific coast. Some details are given on the methodology: Bathymetry, Initialization and large scale forcing, Tides, Atmospheric forcing, Forecast protocol, and Scenario for radioactive tracers

  5. Uncertainty Analysis of Multi-Model Flood Forecasts

    Directory of Open Access Journals (Sweden)

    Erich J. Plate

    2015-12-01

    Full Text Available This paper demonstrates, by means of a systematic uncertainty analysis, that the use of outputs from more than one model can significantly improve conditional forecasts of discharges or water stages, provided the models are structurally different. Discharge forecasts from two models and the actual forecasted discharge are assumed to form a three-dimensional joint probability density distribution (jpdf, calibrated on long time series of data. The jpdf is decomposed into conditional probability density distributions (cpdf by means of Bayes formula, as suggested and explored by Krzysztofowicz in a series of papers. In this paper his approach is simplified to optimize conditional forecasts for any set of two forecast models. Its application is demonstrated by means of models developed in a study of flood forecasting for station Stung Treng on the middle reach of the Mekong River in South-East Asia. Four different forecast models were used and pairwise combined: forecast with no model, with persistence model, with a regression model, and with a rainfall-runoff model. Working with cpdfs requires determination of dependency among variables, for which linear regressions are required, as was done by Krzysztofowicz. His Bayesian approach based on transforming observed probability distributions of discharges and forecasts into normal distributions is also explored. Results obtained with his method for normal prior and likelihood distributions are identical to results from direct multiple regressions. Furthermore, it is shown that in the present case forecast accuracy is only marginally improved, if Weibull distributed basic data were converted into normally distributed variables.

  6. Evaluating the spatio-temporal performance of sky-imager-based solar irradiance analysis and forecasts

    Science.gov (United States)

    Schmidt, Thomas; Kalisch, John; Lorenz, Elke; Heinemann, Detlev

    2016-03-01

    Clouds are the dominant source of small-scale variability in surface solar radiation and uncertainty in its prediction. However, the increasing share of solar energy in the worldwide electric power supply increases the need for accurate solar radiation forecasts. In this work, we present results of a very short term global horizontal irradiance (GHI) forecast experiment based on hemispheric sky images. A 2-month data set with images from one sky imager and high-resolution GHI measurements from 99 pyranometers distributed over 10 km by 12 km is used for validation. We developed a multi-step model and processed GHI forecasts up to 25 min with an update interval of 15 s. A cloud type classification is used to separate the time series into different cloud scenarios. Overall, the sky-imager-based forecasts do not outperform the reference persistence forecasts. Nevertheless, we find that analysis and forecast performance depends strongly on the predominant cloud conditions. Especially convective type clouds lead to high temporal and spatial GHI variability. For cumulus cloud conditions, the analysis error is found to be lower than that introduced by a single pyranometer if it is used representatively for the whole area in distances from the camera larger than 1-2 km. Moreover, forecast skill is much higher for these conditions compared to overcast or clear sky situations causing low GHI variability, which is easier to predict by persistence. In order to generalize the cloud-induced forecast error, we identify a variability threshold indicating conditions with positive forecast skill.

  7. Evaluating the spatio-temporal performance of sky-imager-based solar irradiance analysis and forecasts

    Directory of Open Access Journals (Sweden)

    T. Schmidt

    2016-03-01

    Full Text Available Clouds are the dominant source of small-scale variability in surface solar radiation and uncertainty in its prediction. However, the increasing share of solar energy in the worldwide electric power supply increases the need for accurate solar radiation forecasts. In this work, we present results of a very short term global horizontal irradiance (GHI forecast experiment based on hemispheric sky images. A 2-month data set with images from one sky imager and high-resolution GHI measurements from 99 pyranometers distributed over 10 km by 12 km is used for validation. We developed a multi-step model and processed GHI forecasts up to 25 min with an update interval of 15 s. A cloud type classification is used to separate the time series into different cloud scenarios. Overall, the sky-imager-based forecasts do not outperform the reference persistence forecasts. Nevertheless, we find that analysis and forecast performance depends strongly on the predominant cloud conditions. Especially convective type clouds lead to high temporal and spatial GHI variability. For cumulus cloud conditions, the analysis error is found to be lower than that introduced by a single pyranometer if it is used representatively for the whole area in distances from the camera larger than 1–2 km. Moreover, forecast skill is much higher for these conditions compared to overcast or clear sky situations causing low GHI variability, which is easier to predict by persistence. In order to generalize the cloud-induced forecast error, we identify a variability threshold indicating conditions with positive forecast skill.

  8. Inaccuracy in traffic forecasts

    DEFF Research Database (Denmark)

    Flyvbjerg, Bent; Holm, Mette K. Skamris; Buhl, Søren Ladegaard

    2006-01-01

    This paper presents results from the first statistically significant study of traffic forecasts in transportation infrastructure projects. The sample used is the largest of its kind, covering 210 projects in 14 nations worth US$58 billion. The study shows with very high statistical significance...... that forecasters generally do a poor job of estimating the demand for transportation infrastructure projects. The result is substantial downside financial and economic risk. Forecasts have not become more accurate over the 30-year period studied. If techniques and skills for arriving at accurate demand forecasts...... forecasting. Highly inaccurate traffic forecasts combined with large standard deviations translate into large financial and economic risks. But such risks are typically ignored or downplayed by planners and decision-makers, to the detriment of social and economic welfare. The paper presents the data...

  9. FORECASTING MODELS IN MANAGEMENT

    OpenAIRE

    Sindelar, Jiri

    2008-01-01

    This article deals with the problems of forecasting models. First part of the article is dedicated to definition of the relevant areas (vertical and horizontal pillar of definition) and then the forecasting model itself is defined; as article presents theoretical background for further primary research, this definition is crucial. Finally the position of forecasting models within the management system is identified. The paper is a part of the outputs of FEM CULS grant no. 1312/11/3121.

  10. Forecasting in Planning

    OpenAIRE

    Ike, P.; Voogd, Henk; Voogd, Henk; Linden, Gerard

    2004-01-01

    This chapter begins with a discussion of qualitative forecasting by describing a number of methods that depend on judgements made by stakeholders, experts or other interested parties to arrive at forecasts. Two qualitative approaches are illuminated, the Delphi and scenario methods respectively. Quantitative forecasting is illustrated with a brief overview of time series methods. Both qualitative and quantitative methods are illustrated by an example. The role and relative importance of forec...

  11. The strategy of professional forecasting

    DEFF Research Database (Denmark)

    Ottaviani, Marco; Sørensen, Peter Norman

    2006-01-01

    We develop and compare two theories of professional forecasters’ strategic behavior. The first theory, reputational cheap talk, posits that forecasters endeavor to convince the market that they are well informed. The market evaluates their forecasting talent on the basis of the forecasts...... and the realized state. If the market expects forecasters to report their posterior expectations honestly, then forecasts are shaded toward the prior mean. With correct market expectations, equilibrium forecasts are imprecise but not shaded. The second theory posits that forecasters compete in a forecasting...... contest with pre-specified rules. In a winner-take-all contest, equilibrium forecasts are excessively differentiated...

  12. Electricity demand and spot price forecasting using evolutionary computation combined with chaotic nonlinear dynamic model

    International Nuclear Information System (INIS)

    Unsihuay-Vila, C.; Zambroni de Souza, A.C.; Marangon-Lima, J.W.; Balestrassi, P.P.

    2010-01-01

    This paper proposes a new hybrid approach based on nonlinear chaotic dynamics and evolutionary strategy to forecast electricity loads and prices. The main idea is to develop a new training or identification stage in a nonlinear chaotic dynamic based predictor. In the training stage five optimal parameters for a chaotic based predictor are searched through an optimization model based on evolutionary strategy. The objective function of the optimization model is the mismatch minimization between the multi-step-ahead forecasting of predictor and observed data such as it is done in identification problems. The first contribution of this paper is that the proposed approach is capable of capturing the complex dynamic of demand and price time series considered resulting in a more accuracy forecasting. The second contribution is that the proposed approach run on-line manner, i.e. the optimal set of parameters and prediction is executed automatically which can be used to prediction in real-time, it is an advantage in comparison with other models, where the choice of their input parameters are carried out off-line, following qualitative/experience-based recipes. A case study of load and price forecasting is presented using data from New England, Alberta, and Spain. A comparison with other methods such as autoregressive integrated moving average (ARIMA) and artificial neural network (ANN) is shown. The results show that the proposed approach provides a more accurate and effective forecasting than ARIMA and ANN methods. (author)

  13. A novel hybrid ensemble learning paradigm for nuclear energy consumption forecasting

    International Nuclear Information System (INIS)

    Tang, Ling; Yu, Lean; Wang, Shuai; Li, Jianping; Wang, Shouyang

    2012-01-01

    Highlights: ► A hybrid ensemble learning paradigm integrating EEMD and LSSVR is proposed. ► The hybrid ensemble method is useful to predict time series with high volatility. ► The ensemble method can be used for both one-step and multi-step ahead forecasting. - Abstract: In this paper, a novel hybrid ensemble learning paradigm integrating ensemble empirical mode decomposition (EEMD) and least squares support vector regression (LSSVR) is proposed for nuclear energy consumption forecasting, based on the principle of “decomposition and ensemble”. This hybrid ensemble learning paradigm is formulated specifically to address difficulties in modeling nuclear energy consumption, which has inherently high volatility, complexity and irregularity. In the proposed hybrid ensemble learning paradigm, EEMD, as a competitive decomposition method, is first applied to decompose original data of nuclear energy consumption (i.e. a difficult task) into a number of independent intrinsic mode functions (IMFs) of original data (i.e. some relatively easy subtasks). Then LSSVR, as a powerful forecasting tool, is implemented to predict all extracted IMFs independently. Finally, these predicted IMFs are aggregated into an ensemble result as final prediction, using another LSSVR. For illustration and verification purposes, the proposed learning paradigm is used to predict nuclear energy consumption in China. Empirical results demonstrate that the novel hybrid ensemble learning paradigm can outperform some other popular forecasting models in both level prediction and directional forecasting, indicating that it is a promising tool to predict complex time series with high volatility and irregularity.

  14. Using forecast information for storm ride-through control

    DEFF Research Database (Denmark)

    Barahona Garzón, Braulio; Trombe, Pierre-Julien; Vincent, Claire Louise

    2013-01-01

    Using probabilistic forecast information in control algorithms can improve the performance of wind farms during periods of extreme winds. This work presents a wind farm supervisor control concept that uses probabilistic forecast information to ride-through a storm with softer ramps of power. Wind...... speed forecasts are generated with a statistical approach (i.e. time series models). The supervisor control is based on a set of logical rules that consider point forecasts and predictive densities to ramp-down the power of the wind farm before the storm hits. The potential of this supervisor control...

  15. House Price Forecasts, Forecaster Herding, and the Recent Crisis

    Directory of Open Access Journals (Sweden)

    Christian Pierdzioch

    2012-11-01

    Full Text Available We used the Wall Street Journal survey data for the period 2006–2012 to analyze whether forecasts of house prices and housing starts provide evidence of (anti-herding of forecasters. Forecasts are consistent with herding (anti-herding of forecasters if forecasts are biased towards (away from the consensus forecast. We found that anti-herding is prevalent among forecasters of house prices. We also report that, following the recent crisis, the prevalence of forecaster anti-herding seems to have changed over time.

  16. House Price Forecasts, Forecaster Herding, and the Recent Crisis

    DEFF Research Database (Denmark)

    Stadtmann, Georg; Pierdzioch; Ruelke

    2013-01-01

    We used the Wall Street Journal survey data for the period 2006–2012 to analyze whether forecasts of house prices and housing starts provide evidence of (anti-)herding of forecasters. Forecasts are consistent with herding (anti-herding) of forecasters if forecasts are biased towards (away from) t......) the consensus forecast. We found that anti-herding is prevalent among forecasters of house prices. We also report that, following the recent crisis, the prevalence of forecaster anti-herding seems to have changed over time....

  17. World Area Forecast System (WAFS)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The World Area Forecast System (WAFS) is a worldwide system by which world area forecast centers provide aeronautical meteorological en-route forecasts in uniform...

  18. Forecasting in Planning

    NARCIS (Netherlands)

    Ike, P.; Voogd, Henk; Voogd, Henk; Linden, Gerard

    2004-01-01

    This chapter begins with a discussion of qualitative forecasting by describing a number of methods that depend on judgements made by stakeholders, experts or other interested parties to arrive at forecasts. Two qualitative approaches are illuminated, the Delphi and scenario methods respectively.

  19. Improving Garch Volatility Forecasts

    NARCIS (Netherlands)

    Klaassen, F.J.G.M.

    1998-01-01

    Many researchers use GARCH models to generate volatility forecasts. We show, however, that such forecasts are too variable. To correct for this, we extend the GARCH model by distinguishing two regimes with different volatility levels. GARCH effects are allowed within each regime, so that our model

  20. Forecast Accuracy Uncertainty and Momentum

    OpenAIRE

    Bing Han; Dong Hong; Mitch Warachka

    2009-01-01

    We demonstrate that stock price momentum and earnings momentum can result from uncertainty surrounding the accuracy of cash flow forecasts. Our model has multiple information sources issuing cash flow forecasts for a stock. The investor combines these forecasts into an aggregate cash flow estimate that has minimal mean-squared forecast error. This aggregate estimate weights each cash flow forecast by the estimated accuracy of its issuer, which is obtained from their past forecast errors. Mome...

  1. Spatial electric load forecasting

    CERN Document Server

    Willis, H Lee

    2002-01-01

    Spatial Electric Load Forecasting Consumer Demand for Power and ReliabilityCoincidence and Load BehaviorLoad Curve and End-Use ModelingWeather and Electric LoadWeather Design Criteria and Forecast NormalizationSpatial Load Growth BehaviorSpatial Forecast Accuracy and Error MeasuresTrending MethodsSimulation Method: Basic ConceptsA Detailed Look at the Simulation MethodBasics of Computerized SimulationAnalytical Building Blocks for Spatial SimulationAdvanced Elements of Computerized SimulationHybrid Trending-Simulation MethodsAdvanced

  2. A comparison of the stochastic and machine learning approaches in hydrologic time series forecasting

    Science.gov (United States)

    Kim, T.; Joo, K.; Seo, J.; Heo, J. H.

    2016-12-01

    Hydrologic time series forecasting is an essential task in water resources management and it becomes more difficult due to the complexity of runoff process. Traditional stochastic models such as ARIMA family has been used as a standard approach in time series modeling and forecasting of hydrological variables. Due to the nonlinearity in hydrologic time series data, machine learning approaches has been studied with the advantage of discovering relevant features in a nonlinear relation among variables. This study aims to compare the predictability between the traditional stochastic model and the machine learning approach. Seasonal ARIMA model was used as the traditional time series model, and Random Forest model which consists of decision tree and ensemble method using multiple predictor approach was applied as the machine learning approach. In the application, monthly inflow data from 1986 to 2015 of Chungju dam in South Korea were used for modeling and forecasting. In order to evaluate the performances of the used models, one step ahead and multi-step ahead forecasting was applied. Root mean squared error and mean absolute error of two models were compared.

  3. Short-Term Wind Speed Forecasting Using Support Vector Regression Optimized by Cuckoo Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Jianzhou Wang

    2015-01-01

    Full Text Available This paper develops an effectively intelligent model to forecast short-term wind speed series. A hybrid forecasting technique is proposed based on recurrence plot (RP and optimized support vector regression (SVR. Wind caused by the interaction of meteorological systems makes itself extremely unsteady and difficult to forecast. To understand the wind system, the wind speed series is analyzed using RP. Then, the SVR model is employed to forecast wind speed, in which the input variables are selected by RP, and two crucial parameters, including the penalties factor and gamma of the kernel function RBF, are optimized by various optimization algorithms. Those optimized algorithms are genetic algorithm (GA, particle swarm optimization algorithm (PSO, and cuckoo optimization algorithm (COA. Finally, the optimized SVR models, including COA-SVR, PSO-SVR, and GA-SVR, are evaluated based on some criteria and a hypothesis test. The experimental results show that (1 analysis of RP reveals that wind speed has short-term predictability on a short-term time scale, (2 the performance of the COA-SVR model is superior to that of the PSO-SVR and GA-SVR methods, especially for the jumping samplings, and (3 the COA-SVR method is statistically robust in multi-step-ahead prediction and can be applied to practical wind farm applications.

  4. About the National Forecast Chart

    Science.gov (United States)

    code. Press enter or select the go button to submit request Local forecast by "City, St" or Prediction Center on Twitter NCEP Quarterly Newsletter WPC Home Analyses and Forecasts National Forecast to all federal, state, and local government web resources and services. The National Forecast Charts

  5. Device for forecasting reactor power-up routes

    International Nuclear Information System (INIS)

    Fukuzaki, Takaharu.

    1980-01-01

    Purpose: To improve the reliability and forecasting accuracy for a device forecasting the change of the state on line in BWR type reactors. Constitution: The present state in a nuclear reactor is estimated in a present state judging section based on measuring signals for thermal power, core flow rate, control rod density and the like from the nuclear reactor, and the estimated results are accumulated in an operation result collecting section. While on the other hand, a forecasting section forecasts the future state in the reactor based on the signals from the forecasting condition setting section. The actual result values from the collecting section and the forecasting results are compared to each other. If they are not equal, new setting signals are outputted from the setting section to perform the forecasting again. These procedures are repeated till the difference between the forecast results and the actual result values is minimized, by which accurate forecasting for the state of the reactor is made possible. (Furukawa, Y.)

  6. Improving operational flood forecasting through data assimilation

    Science.gov (United States)

    Rakovec, Oldrich; Weerts, Albrecht; Uijlenhoet, Remko; Hazenberg, Pieter; Torfs, Paul

    2010-05-01

    Accurate flood forecasts have been a challenging topic in hydrology for decades. Uncertainty in hydrological forecasts is due to errors in initial state (e.g. forcing errors in historical mode), errors in model structure and parameters and last but not least the errors in model forcings (weather forecasts) during the forecast mode. More accurate flood forecasts can be obtained through data assimilation by merging observations with model simulations. This enables to identify the sources of uncertainties in the flood forecasting system. Our aim is to assess the different sources of error that affect the initial state and to investigate how they propagate through hydrological models with different levels of spatial variation, starting from lumped models. The knowledge thus obtained can then be used in a data assimilation scheme to improve the flood forecasts. This study presents the first results of this framework and focuses on quantifying precipitation errors and its effect on discharge simulations within the Ourthe catchment (1600 km2), which is situated in the Belgian Ardennes and is one of the larger subbasins of the Meuse River. Inside the catchment, hourly rain gauge information from 10 different locations is available over a period of 15 years. Based on these time series, the bootstrap method has been applied to generate precipitation ensembles. These were then used to simulate the catchment's discharges at the outlet. The corresponding streamflow ensembles were further assimilated with observed river discharges to update the model states of lumped hydrological models (R-PDM, HBV) through Residual Resampling. This particle filtering technique is a sequential data assimilation method and takes no prior assumption of the probability density function for the model states, which in contrast to the Ensemble Kalman filter does not have to be Gaussian. Our further research will be aimed at quantifying and reducing the sources of uncertainty that affect the initial

  7. Marine Point Forecasts

    Science.gov (United States)

    will link to the zone forecast and then allow further zooming to the point of interest whereas on the Honolulu, HI Chicago, IL Northern Indiana, IN Lake Charles, LA New Orleans, LA Boston, MA Caribou, ME

  8. Socioeconomic Forecasting : [Technical Summary

    Science.gov (United States)

    2012-01-01

    Because the traffic forecasts produced by the Indiana : Statewide Travel Demand Model (ISTDM) are driven by : the demographic and socioeconomic inputs to the model, : particular attention must be given to obtaining the most : accurate demographic and...

  9. NYHOPS Forecast Model Results

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — 3D Marine Nowcast/Forecast System for the New York Bight NYHOPS subdomain. Currents, waves, surface meteorology, and water conditions.

  10. Inflow forecasting at BPA

    Energy Technology Data Exchange (ETDEWEB)

    McManamon, A. [Bonneville Power Administration, Portland, OR (United States)

    2007-07-01

    The Columbia River Power System operates with consideration for flood control, endangered species, navigation, irrigation, water supply, recreation, other fish and wildlife concerns and power production. The Bonneville Power Association (BPA) located in Portland, Oregon is responsible for 35-40 per cent of the power consumed within the region. This presentation discussed inflow power concerns at BPA. The presentation illustrated elevational relief of projects; annual and daily variability; the hydrologic cycle; national river service weather forecasting service (NRSWFS); components of NRSWFS; and hydrologic forecast locations. Project operations and inventory were included along with a comparison of the 71-year average unregulated flow with regulated flow at the Dalles. Consistency between short-term and long-term forecasts and long-term streamflow forecasts were also illustrated in graphical format. The presentation also discussed the issue of reducing model and parameter uncertainty; reducing initial conditions uncertainty; snow updating; and reducing meteorological uncertainty. tabs., figs.

  11. CCAA seasonal forecasting

    International Development Research Centre (IDRC) Digital Library (Canada)

    Integrating meteorological and indigenous knowledge-based seasonal climate forecasts in ..... Explanation is based on spiritual and social values. Taught by .... that provided medicine and food became the subject of strict rules and practices ...

  12. Forecast Icing Product

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Forecast Icing Product (FIP) is an automatically-generated index suitable for depicting areas of potentially hazardous airframe icing. The FIP algorithm uses...

  13. Conditional Probabilistic Population Forecasting

    OpenAIRE

    Sanderson, W.C.; Scherbov, S.; O'Neill, B.C.; Lutz, W.

    2003-01-01

    Since policy makers often prefer to think in terms of scenarios, the question has arisen as to whether it is possible to make conditional population forecasts in a probabilistic context. This paper shows that it is both possible and useful to make these forecasts. We do this with two different kinds of examples. The first is the probabilistic analog of deterministic scenario analysis. Conditional probabilistic scenario analysis is essential for policy makers it allows them to answer "what if"...

  14. Conditional probabilistic population forecasting

    OpenAIRE

    Sanderson, Warren; Scherbov, Sergei; O'Neill, Brian; Lutz, Wolfgang

    2003-01-01

    Since policy-makers often prefer to think in terms of alternative scenarios, the question has arisen as to whether it is possible to make conditional population forecasts in a probabilistic context. This paper shows that it is both possible and useful to make these forecasts. We do this with two different kinds of examples. The first is the probabilistic analog of deterministic scenario analysis. Conditional probabilistic scenario analysis is essential for policy-makers because it allows them...

  15. Conditional Probabilistic Population Forecasting

    OpenAIRE

    Sanderson, Warren C.; Scherbov, Sergei; O'Neill, Brian C.; Lutz, Wolfgang

    2004-01-01

    Since policy-makers often prefer to think in terms of alternative scenarios, the question has arisen as to whether it is possible to make conditional population forecasts in a probabilistic context. This paper shows that it is both possible and useful to make these forecasts. We do this with two different kinds of examples. The first is the probabilistic analog of deterministic scenario analysis. Conditional probabilistic scenario analysis is essential for policy-makers because...

  16. EU pharmaceutical expenditure forecast

    OpenAIRE

    Urbinati, Duccio; Rémuzat, Cécile; Kornfeld, Åsa; Vataire, Anne-Lise; Cetinsoy, Laurent; Aballéa, Samuel; Mzoughi, Olfa; Toumi, Mondher

    2014-01-01

    Background and Objectives: With constant incentives for healthcare payers to contain their pharmaceutical budgets, forecasting has become critically important. Some countries have, for instance, developed pharmaceutical horizon scanning units. The objective of this project was to build a model to assess the net effect of the entrance of new patented medicinal products versus medicinal products going off-patent, with a defined forecast horizon, on selected European Union (EU) Member States’ ph...

  17. Problems of Forecast

    OpenAIRE

    Kucharavy , Dmitry; De Guio , Roland

    2005-01-01

    International audience; The ability to foresee future technology is a key task of Innovative Design. The paper focuses on the obstacles to reliable prediction of technological evolution for the purpose of Innovative Design. First, a brief analysis of problems for existing forecasting methods is presented. The causes for the complexity of technology prediction are discussed in the context of reduction of the forecast errors. Second, using a contradiction analysis, a set of problems related to ...

  18. Radiation-induced transformation in oncogene primed C3H/10T1/2 cells; a new system for analysis of multi-step transformation in vitro

    International Nuclear Information System (INIS)

    Drozdoff, V.V.

    1988-01-01

    Several established rodent cell lines, such as C3H/10T1/2 fibroblasts, have been developed to study radiation and chemically-induced malignant transformation. Most experimental evidence has supported the idea that transformation in 10T1/2 cells involved at least two steps but that the apparent frequency of transformation depends on the density of plated cells. A new approach is presented here for studying radiation-induced transformation. An oncogene primed cell system (C3H-myc) was developed by introducing a constitutively active mouse c-myc gene into 10T1/2 cells. A primary goal was to determine if the introduction of an activated oncogene could substitute for one of the required steps in radiation-induced transformation. Results are presented that show that the expression of the exogenous myc gene significantly increased the frequency of radiation-induced transformation in these cells. Subculture experiments performed to analyze the kinetics of transformation in C3H-myc cells and reconstruction experiments allowing the effects of normal cells on radiation-induced transformants to be determined indicated that transformed cells arose very shortly after irradiation. These results support the conclusion that a radiation-induced event can complement the effect of myc in C3H-myc cells and directly result in transformation. This system thus provides an opportunity to isolate early steps in radiation-induced transformation and should facilitate the identification and analysis of these events

  19. MSSM Forecast for the LHC

    CERN Document Server

    Cabrera, Maria Eugenia; de Austri, Roberto Ruiz

    2009-01-01

    We perform a forecast of the MSSM with universal soft terms (CMSSM) for the LHC, based on an improved Bayesian analysis. We do not incorporate ad hoc measures of the fine-tuning to penalize unnatural possibilities: such penalization arises from the Bayesian analysis itself when the experimental value of $M_Z$ is considered. This allows to scan the whole parameter space, allowing arbitrarily large soft terms. Still the low-energy region is statistically favoured (even before including dark matter or g-2 constraints). Contrary to other studies, the results are almost unaffected by changing the upper limits taken for the soft terms. The results are also remarkable stable when using flat or logarithmic priors, a fact that arises from the larger statistical weight of the low-energy region in both cases. Then we incorporate all the important experimental constrains to the analysis, obtaining a map of the probability density of the MSSM parameter space, i.e. the forecast of the MSSM. Since not all the experimental i...

  20. Operational hydrological forecasting in Bavaria. Part II: Ensemble forecasting

    Science.gov (United States)

    Ehret, U.; Vogelbacher, A.; Moritz, K.; Laurent, S.; Meyer, I.; Haag, I.

    2009-04-01

    In part I of this study, the operational flood forecasting system in Bavaria and an approach to identify and quantify forecast uncertainty was introduced. The approach is split into the calculation of an empirical 'overall error' from archived forecasts and the calculation of an empirical 'model error' based on hydrometeorological forecast tests, where rainfall observations were used instead of forecasts. The 'model error' can especially in upstream catchments where forecast uncertainty is strongly dependent on the current predictability of the atrmosphere be superimposed on the spread of a hydrometeorological ensemble forecast. In Bavaria, two meteorological ensemble prediction systems are currently tested for operational use: the 16-member COSMO-LEPS forecast and a poor man's ensemble composed of DWD GME, DWD Cosmo-EU, NCEP GFS, Aladin-Austria, MeteoSwiss Cosmo-7. The determination of the overall forecast uncertainty is dependent on the catchment characteristics: 1. Upstream catchment with high influence of weather forecast a) A hydrological ensemble forecast is calculated using each of the meteorological forecast members as forcing. b) Corresponding to the characteristics of the meteorological ensemble forecast, each resulting forecast hydrograph can be regarded as equally likely. c) The 'model error' distribution, with parameters dependent on hydrological case and lead time, is added to each forecast timestep of each ensemble member d) For each forecast timestep, the overall (i.e. over all 'model error' distribution of each ensemble member) error distribution is calculated e) From this distribution, the uncertainty range on a desired level (here: the 10% and 90% percentile) is extracted and drawn as forecast envelope. f) As the mean or median of an ensemble forecast does not necessarily exhibit meteorologically sound temporal evolution, a single hydrological forecast termed 'lead forecast' is chosen and shown in addition to the uncertainty bounds. This can be

  1. Integrating a Storage Factor into R-NARX Neural Networks for Flood Forecasts

    Science.gov (United States)

    Chou, Po-Kai; Chang, Li-Chiu; Chang, Fi-John; Shih, Ban-Jwu

    2017-04-01

    Because mountainous terrains and steep landforms rapidly accelerate the speed of flood flow in Taiwan island, accurate multi-step-ahead inflow forecasts during typhoon events for providing reliable information benefiting the decision-makings of reservoir pre-storm release and flood-control operation are considered crucial and challenging. Various types of artificial neural networks (ANNs) have been successfully applied in hydrological fields. This study proposes a recurrent configuration of the nonlinear autoregressive with exogenous inputs (NARX) network, called R-NARX, with various effective inputs to forecast the inflows of the Feitsui Reservoir, a pivot reservoir for water supply to Taipei metropolitan in Taiwan, during typhoon periods. The proposed R-NARX is constructed based on the recurrent neural network (RNN), which is commonly used for modelling nonlinear dynamical systems. A large number of hourly rainfall and inflow data sets collected from 95 historical typhoon events in the last thirty years are used to train, validate and test the models. The potential input variables, including rainfall in previous time steps (one to six hours), cumulative rainfall, the storage factor and the storage function, are assessed, and various models are constructed with their reliability and accuracy being tested. We find that the previous (t-2) rainfall and cumulative rainfall are crucial inputs and the storage factor and the storage function would also improve the forecast accuracy of the models. We demonstrate that the R-NARX model not only can accurately forecast the inflows but also effectively catch the peak flow without adopting observed inflow data during the entire typhoon period. Besides, the model with the storage factor is superior to the model with the storage function, where its improvement can reach 24%. This approach can well model the rainfall-runoff process for the entire flood forecasting period without the use of observed inflow data and can provide

  2. Multi-step surface functionalization of polyimide based evanescent wave photonic biosensors and application for DNA hybridization by Mach-Zehnder interferometer

    Energy Technology Data Exchange (ETDEWEB)

    Melnik, Eva [Health and Environment Department, Nano Systems, AIT Austrian Institute of Technology GmbH, Donau-City-Strasse 1, 1220 Vienna (Austria); Department of Analytical Chemistry, University of Vienna, Waehringer Strasse 38, 1090 Vienna (Austria); Bruck, Roman [Health and Environment Department, Nano Systems, AIT Austrian Institute of Technology GmbH, Donau-City-Strasse 1, 1220 Vienna (Austria); Hainberger, Rainer, E-mail: rainer.hainberger@ait.ac.at [Health and Environment Department, Nano Systems, AIT Austrian Institute of Technology GmbH, Donau-City-Strasse 1, 1220 Vienna (Austria); Laemmerhofer, Michael, E-mail: michael.laemmerhofer@univie.ac.at [Department of Analytical Chemistry, University of Vienna, Waehringer Strasse 38, 1090 Vienna (Austria)

    2011-08-12

    Highlights: {yields} We realize a biosensing platform for polyimide evanescent photonic wave sensors. {yields} We show that the surface functionalization via silanisation and biotinylation followed by streptavidin immobilization do not destroy or damage the thin polyimide film. {yields} A highly dense streptavidin layer enables the immobilisation of biotinylated ligands such as biotinylated ssDNA for the selective measurement of DNA hybridization. - Abstract: The process of surface functionalization involving silanization, biotinylation and streptavidin bonding as platform for biospecific ligand immobilization was optimized for thin film polyimide spin-coated silicon wafers, of which the polyimide film serves as a wave guiding layer in evanescent wave photonic biosensors. This type of optical sensors make great demands on the materials involved as well as on the layer properties, such as the optical quality, the layer thickness and the surface roughness. In this work we realized the binding of a 3-mercaptopropyl trimethoxysilane on an oxygen plasma activated polyimide surface followed by subsequent derivatization of the reactive thiol groups with maleimide-PEG{sub 2}-biotin and immobilization of streptavidin. The progress of the functionalization was monitored by using different fluorescence labels for optimization of the chemical derivatization steps. Further, X-ray photoelectron spectroscopy and atomic force microscopy were utilized for the characterization of the modified surface. These established analytical methods allowed to derive information like chemical composition of the surface, surface coverage with immobilized streptavidin, as well as parameters of the surface roughness. The proposed functionalization protocol furnished a surface density of 144 fmol mm{sup -2} streptavidin with good reproducibility (13.9% RSD, n = 10) and without inflicted damage to the surface. This surface modification was applied to polyimide based Mach-Zehnder interferometer

  3. Space Weather Forecasting at IZMIRAN

    Science.gov (United States)

    Gaidash, S. P.; Belov, A. V.; Abunina, M. A.; Abunin, A. A.

    2017-12-01

    Since 1998, the Institute of Terrestrial Magnetism, Ionosphere, and Radio Wave Propagation (IZMIRAN) has had an operating heliogeophysical service—the Center for Space Weather Forecasts. This center transfers the results of basic research in solar-terrestrial physics into daily forecasting of various space weather parameters for various lead times. The forecasts are promptly available to interested consumers. This article describes the center and the main types of forecasts it provides: solar and geomagnetic activity, magnetospheric electron fluxes, and probabilities of proton increases. The challenges associated with the forecasting of effects of coronal mass ejections and coronal holes are discussed. Verification data are provided for the center's forecasts.

  4. Wind power forecasting accuracy and uncertainty in Finland

    Energy Technology Data Exchange (ETDEWEB)

    Holttinen, H.; Miettinen, J.; Sillanpaeae, S.

    2013-04-15

    forecasts for short horizons like the following hour, more advanced combining techniques than simple average, such as Kalmar filtering or recursive least squares provided better results. Two different uncertainty quantification methods, based on empirical cumulative density function and kernel densities, were analysed for 3 sites. Aggregation of wind power production will not only decrease relative prediction errors, but also decreases the variation and uncertainty of prediction errors. (orig.)

  5. Assessment of storm forecast

    DEFF Research Database (Denmark)

    Cutululis, Nicolaos Antonio; Hahmann, Andrea N.; Huus Bjerge, Martin

    When wind speed exceeds a certain value, wind turbines shut-down in order to protect their structure. This leads to sudden wind plants shut down and to new challenges concerning the secure operation of the pan-European electric system with future large scale offshore wind power. This task aims...... stopped, completely or partially, producing due to extreme wind speeds. Wind speed and power measurements from those events are presented and compared to the forecast available at Energinet.dk. The analysis looked at wind speed and wind power forecast. The main conclusion of the analysis is that the wind...... to consider it an EWP) and that the available wind speed forecasts are given as a mean wind speed over a rather large area. At wind power level, the analysis shows that prediction of accurate production levels from a wind farm experiencing EWP is rather poor. This is partially because the power curve...

  6. Financial Analysts’ Forecasts

    DEFF Research Database (Denmark)

    Stæhr, Simone

    . The primary focus is on financial analysts in the task of conducting earnings forecasts while a secondary focus is on investors’ abilities to interpret and make use of these forecasts. Simply put, financial analysts can be seen as information intermediators receiving inputs to their analyses from firm...... in the decision making and the magnitude of these constraints does sometimes vary with personal traits. Therefore, to the extent that financial analysts are subjects to behavioral biases their outputs to the investors are likely to be biased by their interpretation of information. Because investors need accuracy...... management and providing outputs to the investors. Amongst various outputs from the analysts are forecasts of earnings. According to decision theories mostly from the literature in psychology all humans are affected by cognitive constraints to some degree. These constraints may lead to unintentional biases...

  7. Wind power forecast

    Energy Technology Data Exchange (ETDEWEB)

    Pestana, Rui [Rede Electrica Nacional (REN), S.A., Lisboa (Portugal). Dept. Systems and Development System Operator; Trancoso, Ana Rosa; Delgado Domingos, Jose [Univ. Tecnica de Lisboa (Portugal). Seccao de Ambiente e Energia

    2012-07-01

    Accurate wind power forecast are needed to reduce integration costs in the electric grid caused by wind inherent variability. Currently, Portugal has a significant wind power penetration level and consequently the need to have reliable wind power forecasts at different temporal scales, including localized events such as ramps. This paper provides an overview of the methodologies used by REN to forecast wind power at national level, based on statistical and probabilistic combinations of NWP and measured data with the aim of improving accuracy of pure NWP. Results show that significant improvement can be achieved with statistical combination with persistence in the short-term and with probabilistic combination in the medium-term. NWP are also able to detect ramp events with 3 day notice to the operational planning. (orig.)

  8. Adaptively smoothed seismicity earthquake forecasts for Italy

    Directory of Open Access Journals (Sweden)

    Yan Y. Kagan

    2010-11-01

    Full Text Available We present a model for estimation of the probabilities of future earthquakes of magnitudes m ≥ 4.95 in Italy. This model is a modified version of that proposed for California, USA, by Helmstetter et al. [2007] and Werner et al. [2010a], and it approximates seismicity using a spatially heterogeneous, temporally homogeneous Poisson point process. The temporal, spatial and magnitude dimensions are entirely decoupled. Magnitudes are independently and identically distributed according to a tapered Gutenberg-Richter magnitude distribution. We have estimated the spatial distribution of future seismicity by smoothing the locations of past earthquakes listed in two Italian catalogs: a short instrumental catalog, and a longer instrumental and historic catalog. The bandwidth of the adaptive spatial kernel is estimated by optimizing the predictive power of the kernel estimate of the spatial earthquake density in retrospective forecasts. When available and reliable, we used small earthquakes of m ≥ 2.95 to reveal active fault structures and 29 probable future epicenters. By calibrating the model with these two catalogs of different durations to create two forecasts, we intend to quantify the loss (or gain of predictability incurred when only a short, but recent, data record is available. Both forecasts were scaled to five and ten years, and have been submitted to the Italian prospective forecasting experiment of the global Collaboratory for the Study of Earthquake Predictability (CSEP. An earlier forecast from the model was submitted by Helmstetter et al. [2007] to the Regional Earthquake Likelihood Model (RELM experiment in California, and with more than half of the five-year experimental period over, the forecast has performed better than the others.

  9. Forecast of auroral activity

    International Nuclear Information System (INIS)

    Lui, A.T.Y.

    2004-01-01

    A new technique is developed to predict auroral activity based on a sample of over 9000 auroral sites identified in global auroral images obtained by an ultraviolet imager on the NASA Polar satellite during a 6-month period. Four attributes of auroral activity sites are utilized in forecasting, namely, the area, the power, and the rates of change in area and power. This new technique is quite accurate, as indicated by the high true skill scores for forecasting three different levels of auroral dissipation during the activity lifetime. The corresponding advanced warning time ranges from 22 to 79 min from low to high dissipation levels

  10. Forecasting Turbine Icing Events

    DEFF Research Database (Denmark)

    Davis, Neil; Hahmann, Andrea N.; Clausen, Niels-Erik

    2012-01-01

    In this study, we present a method for forecasting icing events. The method is validated at two European wind farms in with known icing events. The icing model used was developed using current ice accretion methods, and newly developed ablation algorithms. The model is driven by inputs from the WRF...... mesoscale model, allowing for both climatological estimates of icing and short term icing forecasts. The current model was able to detect periods of icing reasonably well at the warmer site. However at the cold climate site, the model was not able to remove ice quickly enough leading to large ice...

  11. Spatial load forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Willis, H.L.; Engel, M.V.; Buri, M.J.

    1995-04-01

    The reliability, efficiency, and economy of a power delivery system depend mainly on how well its substations, transmission lines, and distribution feeders are located within the utility service area, and how well their capacities match power needs in their respective localities. Often, utility planners are forced to commit to sites, rights of way, and equipment capacities year in advance. A necessary element of effective expansion planning is a forecast of where and how much demand must be served by the future T and D system. This article reports that a three-stage method forecasts with accuracy and detail, allowing meaningful determination of sties and sizes for future substation, transmission, and distribution facilities.

  12. Forecasting Housing Approvals in Australia: Do Forecasters Herd?

    DEFF Research Database (Denmark)

    Stadtmann, Georg; Pierdzioch; Rülke

    2012-01-01

    Price trends in housing markets may reflect herding of market participants. A natural question is whether such herding, to the extent that it occurred, reflects herding in forecasts of professional forecasters. Using more than 6,000 forecasts of housing approvals for Australia, we did not find...

  13. CDM Convective Forecast Planning guidance

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The CDM Convective Forecast Planning (CCFP) guidance product provides a foreast of en-route aviation convective hazards. The forecasts are updated every 2 hours and...

  14. Are demand forecasting techniques applicable to libraries?

    OpenAIRE

    Sridhar, M. S.

    1984-01-01

    Examines the nature and limitations of demand forecasting, discuses plausible methods of forecasting demand for information, suggests some useful hints for demand forecasting and concludes by emphasizing unified approach to demand forecasting.

  15. Forecasting of superconducting compounds

    International Nuclear Information System (INIS)

    Savitskii, E.M.; Gribulya, V.G.; Kiseleva, N.N.

    1981-01-01

    In forecasting new superconducting intermetallic compounds of the A15 and Mo 3 Se types most promising from the viewpoint of high critical temperature Tsub(c), high critical magnetic fields Hsub(c), and high critical currents and in estimating their transition temperature it is proposed to apply cybernetic methods of computer learning

  16. Forecast of nuclear energetics

    Energy Technology Data Exchange (ETDEWEB)

    Sikora, W

    1976-01-01

    The forecast concerning the development of nuclear energetics is presented. Some information on economics of nuclear power plants is given. The nuclear fuel reserves are estimated on the background of power resources of the world. The safety and environment protection problems are mentioned.

  17. Climate Forecast System

    Science.gov (United States)

    Weather Service NWS logo - Click to go to the NWS home page Climate Forecast System Home News Organization Web portal to all Federal, state and local government Web resources and services. The NCEP Climate when using the CFS Reanalysis (CFSR) data. Saha, Suranjana, and Coauthors, 2010: The NCEP Climate

  18. Foresight and Forecasts

    DEFF Research Database (Denmark)

    Kilbourn, Kyle; Bay, Marie Brøndum

    In predicting areas of growth, public innovation projects may rely on optimistic visions of technology still in development as a way of ensuring novelty for funding. This paper explores what happens when forecasts of robotic technology meets the practice of sterile supply in a preliminary stage...

  19. Hydrology and flow forecasting

    NARCIS (Netherlands)

    Vrijling, J.K.; Kwadijk, J.; Van Duivendijk, J.; Van Gelder, P.; Pang, H.; Rao, S.Q.; Wang, G.Q.; Huang, X.Q.

    2002-01-01

    We have studied and applied the statistic model (i.e. MMC) and hydrological models to Upper Yellow River. This report introduces the results and some conclusions from the model. The three models, MMC, MWBM and NAM, have be applied in the research area. The forecasted discharge by the three models

  20. NWS Marine Forecast Areas

    Science.gov (United States)

    of Commerce Ocean Prediction Center National Oceanic and Atmospheric Administration Analysis & Unified Surface Analysis Ocean Ocean Products Ice & Icebergs NIC Ice Products NAIS Iceberg Analysis Social Media Facebook Twitter YouTube Search Search For Go NWS All NOAA NWS Marine Forecast Areas

  1. The Latest Forecast.

    Science.gov (United States)

    Laurence, David

    2002-01-01

    Discusses the "latest forecast" for the future of English departments. Addresses departmental and institutional staffing practices, employment opportunities for PhDs, the acceleration of change in the institution, and the general state of the study and teaching of English. (RS)

  2. Ecological forecasts: An emerging imperative

    Science.gov (United States)

    James S. Clark; Steven R. Carpenter; Mary Barber; Scott Collins; Andy Dobson; Jonathan A. Foley; David M. Lodge; Mercedes Pascual; Roger Pielke; William Pizer; Cathy Pringle; Walter V. Reid; Kenneth A. Rose; Osvaldo Sala; William H. Schlesinger; Diana H. Wall; David Wear

    2001-01-01

    Planning and decision-making can be improved by access to reliable forecasts of ecosystem state, ecosystem services, and natural capital. Availability of new data sets, together with progress in computation and statistics, will increase our ability to forecast ecosystem change. An agenda that would lead toward a capacity to produce, evaluate, and communicate forecasts...

  3. Air Pollution Forecasts: An Overview

    Science.gov (United States)

    Bai, Lu; Wang, Jianzhou; Lu, Haiyan

    2018-01-01

    Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies. PMID:29673227

  4. Air Pollution Forecasts: An Overview.

    Science.gov (United States)

    Bai, Lu; Wang, Jianzhou; Ma, Xuejiao; Lu, Haiyan

    2018-04-17

    Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies.

  5. Air Pollution Forecasts: An Overview

    Directory of Open Access Journals (Sweden)

    Lu Bai

    2018-04-01

    Full Text Available Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies.

  6. Storm Prediction Center Forecast Products

    Science.gov (United States)

    select the go button to submit request Local forecast by "City, St" or "ZIP" City, St Archive NOAA Weather Radio Research Non-op. Products Forecast Tools Svr. Tstm. Events SPC Publications SPC services. Forecast Products Current Weather Watches This is the current graphic showing any severe

  7. Aggregated wind power generation probabilistic forecasting based on particle filter

    International Nuclear Information System (INIS)

    Li, Pai; Guan, Xiaohong; Wu, Jiang

    2015-01-01

    Highlights: • A new method for probabilistic forecasting of aggregated wind power generation. • A dynamic system is established based on a numerical weather prediction model. • The new method handles the non-Gaussian and time-varying wind power uncertainties. • Particle filter is applied to forecast predictive densities of wind generation. - Abstract: Probability distribution of aggregated wind power generation in a region is one of important issues for power system daily operation. This paper presents a novel method to forecast the predictive densities of the aggregated wind power generation from several geographically distributed wind farms, considering the non-Gaussian and non-stationary characteristics in wind power uncertainties. Based on a mesoscale numerical weather prediction model, a dynamic system is established to formulate the relationship between the atmospheric and near-surface wind fields of geographically distributed wind farms. A recursively backtracking framework based on the particle filter is applied to estimate the atmospheric state with the near-surface wind power generation measurements, and to forecast the possible samples of the aggregated wind power generation. The predictive densities of the aggregated wind power generation are then estimated based on these predicted samples by a kernel density estimator. In case studies, the new method presented is tested on a 9 wind farms system in Midwestern United States. The testing results that the new method can provide competitive interval forecasts for the aggregated wind power generation with conventional statistical based models, which validates the effectiveness of the new method

  8. Propagation of Uncertainty in Bayesian Kernel Models - Application to Multiple-Step Ahead Forecasting

    DEFF Research Database (Denmark)

    Quinonero, Joaquin; Girard, Agathe; Larsen, Jan

    2003-01-01

    The object of Bayesian modelling is predictive distribution, which, in a forecasting scenario, enables evaluation of forecasted values and their uncertainties. We focus on reliably estimating the predictive mean and variance of forecasted values using Bayesian kernel based models such as the Gaus......The object of Bayesian modelling is predictive distribution, which, in a forecasting scenario, enables evaluation of forecasted values and their uncertainties. We focus on reliably estimating the predictive mean and variance of forecasted values using Bayesian kernel based models...... such as the Gaussian process and the relevance vector machine. We derive novel analytic expressions for the predictive mean and variance for Gaussian kernel shapes under the assumption of a Gaussian input distribution in the static case, and of a recursive Gaussian predictive density in iterative forecasting...

  9. Predictability of monthly temperature and precipitation using automatic time series forecasting methods

    Science.gov (United States)

    Papacharalampous, Georgia; Tyralis, Hristos; Koutsoyiannis, Demetris

    2018-02-01

    We investigate the predictability of monthly temperature and precipitation by applying automatic univariate time series forecasting methods to a sample of 985 40-year-long monthly temperature and 1552 40-year-long monthly precipitation time series. The methods include a naïve one based on the monthly values of the last year, as well as the random walk (with drift), AutoRegressive Fractionally Integrated Moving Average (ARFIMA), exponential smoothing state-space model with Box-Cox transformation, ARMA errors, Trend and Seasonal components (BATS), simple exponential smoothing, Theta and Prophet methods. Prophet is a recently introduced model inspired by the nature of time series forecasted at Facebook and has not been applied to hydrometeorological time series before, while the use of random walk, BATS, simple exponential smoothing and Theta is rare in hydrology. The methods are tested in performing multi-step ahead forecasts for the last 48 months of the data. We further investigate how different choices of handling the seasonality and non-normality affect the performance of the models. The results indicate that: (a) all the examined methods apart from the naïve and random walk ones are accurate enough to be used in long-term applications; (b) monthly temperature and precipitation can be forecasted to a level of accuracy which can barely be improved using other methods; (c) the externally applied classical seasonal decomposition results mostly in better forecasts compared to the automatic seasonal decomposition used by the BATS and Prophet methods; and (d) Prophet is competitive, especially when it is combined with externally applied classical seasonal decomposition.

  10. Load forecasting for supermarket refrigeration

    DEFF Research Database (Denmark)

    Bacher, Peder; Madsen, Henrik; Aalborg Nielsen, Henrik

    This report presents a study of models for forecasting the load for supermarket refrigeration. The data used for building the forecasting models consists of load measurements, local climate measurements and weather forecasts. The load measurements are from a supermarket located in a village...... in Denmark. The load for refrigeration is the sum of all cabinets in the supermarket, both low and medium temperature cabinets, and spans a period of one year. As input to the forecasting models the ambient temperature observed near the supermarket together with weather forecasts are used. Every hour...

  11. Multi-step contrast sensitivity gauge

    Science.gov (United States)

    Quintana, Enrico C; Thompson, Kyle R; Moore, David G; Heister, Jack D; Poland, Richard W; Ellegood, John P; Hodges, George K; Prindville, James E

    2014-10-14

    An X-ray contrast sensitivity gauge is described herein. The contrast sensitivity gauge comprises a plurality of steps of varying thicknesses. Each step in the gauge includes a plurality of recesses of differing depths, wherein the depths are a function of the thickness of their respective step. An X-ray image of the gauge is analyzed to determine a contrast-to-noise ratio of a detector employed to generate the image.

  12. Multi-step cure kinetic model of ultra-thin glass fiber epoxy prepreg exhibiting both autocatalytic and diffusion-controlled regimes under isothermal and dynamic-heating conditions

    Science.gov (United States)

    Kim, Ye Chan; Min, Hyunsung; Hong, Sungyong; Wang, Mei; Sun, Hanna; Park, In-Kyung; Choi, Hyouk Ryeol; Koo, Ja Choon; Moon, Hyungpil; Kim, Kwang J.; Suhr, Jonghwan; Nam, Jae-Do

    2017-08-01

    As packaging technologies are demanded that reduce the assembly area of substrate, thin composite laminate substrates require the utmost high performance in such material properties as the coefficient of thermal expansion (CTE), and stiffness. Accordingly, thermosetting resin systems, which consist of multiple fillers, monomers and/or catalysts in thermoset-based glass fiber prepregs, are extremely complicated and closely associated with rheological properties, which depend on the temperature cycles for cure. For the process control of these complex systems, it is usually required to obtain a reliable kinetic model that could be used for the complex thermal cycles, which usually includes both the isothermal and dynamic-heating segments. In this study, an ultra-thin prepreg with highly loaded silica beads and glass fibers in the epoxy/amine resin system was investigated as a model system by isothermal/dynamic heating experiments. The maximum degree of cure was obtained as a function of temperature. The curing kinetics of the model prepreg system exhibited a multi-step reaction and a limited conversion as a function of isothermal curing temperatures, which are often observed in epoxy cure system because of the rate-determining diffusion of polymer chain growth. The modified kinetic equation accurately described the isothermal behavior and the beginning of the dynamic-heating behavior by integrating the obtained maximum degree of cure into the kinetic model development.

  13. Intranodular signal intensity analysis of hypovascular high-risk borderline lesions of HCC that illustrate multi-step hepatocarcinogenesis within the nodule on Gd–EOB–DTPA-enhanced MRI

    International Nuclear Information System (INIS)

    Kobayashi, Satoshi; Matsui, Osamu; Gabata, Toshifumi; Koda, Wataru; Minami, Tetsuya; Ryu, Yasuji; Kozaka, Kazuto; Kitao, Azusa

    2012-01-01

    Objectives: To analyze intranodular signal intensity pattern of hypovascular high-risk borderline lesions of HCC that illustrate multi-step hepatocarcinogenesis within the nodule on Gd–EOB–DTPA-enhanced MRI. Methods: A total of 73 nodules showing hypervascular foci in hypovascular high-risk borderline lesions identified by angiography-assisted CT were included in this study. The intranodular signal intensities of both the hypervascular foci and the hypovascular high-risk borderline lesions were evaluated on hepatobiliary-phase EOB-enhanced MRI obtained 20 min after intravenous injection of contrast media. Results: Among 59 hypervascular foci within hypointense hypovascular high-risk borderline lesions, 6 showed more hypointensity, 32 isointensity, and 21 hyperintensity compared to the surrounding hypointense, hypovascular portion of the nodules. Among 14 hypervascular foci within isointense hypovascular high-risk borderline lesions, 5 showed isointensity, and 9 hypointensity compared to the surrounding isointense hypovascular high-risk borderline lesions. No hypervascular foci showed hyperintensity compared to the surrounding isointense hypovascular high-risk borderline lesions. Conclusions: In most of the hypovascular high-risk borderline lesions containing hypervascular foci within the nodule, the signal intensity was decreased in hypervascular foci as compared with hypovascular high-risk borderline lesions and the surrounding background liver parenchyma. This supports the concept of signal intensity decrease during the dedifferentiation process in multistep hepatocarcinogenesis. However, around 30% of the nodules did not follow this rule, and hypervascular foci showed hyperintensity relative to the hypovascular high-risk borderline lesions.

  14. Forecasting military expenditure

    Directory of Open Access Journals (Sweden)

    Tobias Böhmelt

    2014-05-01

    Full Text Available To what extent do frequently cited determinants of military spending allow us to predict and forecast future levels of expenditure? The authors draw on the data and specifications of a recent model on military expenditure and assess the predictive power of its variables using in-sample predictions, out-of-sample forecasts and Bayesian model averaging. To this end, this paper provides guidelines for prediction exercises in general using these three techniques. More substantially, however, the findings emphasize that previous levels of military spending as well as a country’s institutional and economic characteristics particularly improve our ability to predict future levels of investment in the military. Variables pertaining to the international security environment also matter, but seem less important. In addition, the results highlight that the updated model, which drops weak predictors, is not only more parsimonious, but also slightly more accurate than the original specification.

  15. The forecaster's added value

    Science.gov (United States)

    Turco, M.; Milelli, M.

    2009-09-01

    To the authors' knowledge there are relatively few studies that try to answer this topic: "Are humans able to add value to computer-generated forecasts and warnings ?". Moreover, the answers are not always positive. In particular some postprocessing method is competitive or superior to human forecast (see for instance Baars et al., 2005, Charba et al., 2002, Doswell C., 2003, Roebber et al., 1996, Sanders F., 1986). Within the alert system of ARPA Piemonte it is possible to study in an objective manner if the human forecaster is able to add value with respect to computer-generated forecasts. Every day the meteorology group of the Centro Funzionale of Regione Piemonte produces the HQPF (Human QPF) in terms of an areal average for each of the 13 regional warning areas, which have been created according to meteo-hydrological criteria. This allows the decision makers to produce an evaluation of the expected effects by comparing these HQPFs with predefined rainfall thresholds. Another important ingredient in this study is the very dense non-GTS network of rain gauges available that makes possible a high resolution verification. In this context the most useful verification approach is the measure of the QPF and HQPF skills by first converting precipitation expressed as continuous amounts into ‘‘exceedance'' categories (yes-no statements indicating whether precipitation equals or exceeds selected thresholds) and then computing the performances for each threshold. In particular in this work we compare the performances of the latest three years of QPF derived from two meteorological models COSMO-I7 (the Italian version of the COSMO Model, a mesoscale model developed in the framework of the COSMO Consortium) and IFS (the ECMWF global model) with the HQPF. In this analysis it is possible to introduce the hypothesis test developed by Hamill (1999), in which a confidence interval is calculated with the bootstrap method in order to establish the real difference between the

  16. Forecasting carbon dioxide emissions.

    Science.gov (United States)

    Zhao, Xiaobing; Du, Ding

    2015-09-01

    This study extends the literature on forecasting carbon dioxide (CO2) emissions by applying the reduced-form econometrics approach of Schmalensee et al. (1998) to a more recent sample period, the post-1997 period. Using the post-1997 period is motivated by the observation that the strengthening pace of global climate policy may have been accelerated since 1997. Based on our parameter estimates, we project 25% reduction in CO2 emissions by 2050 according to an economic and population growth scenario that is more consistent with recent global trends. Our forecasts are conservative due to that we do not have sufficient data to fully take into account recent developments in the global economy. Copyright © 2015 Elsevier Ltd. All rights reserved.

  17. Forecasting potential crises

    International Nuclear Information System (INIS)

    Neufeld, W.P.

    1984-01-01

    Recently, the Trend Analysis Program (TAP) of the American Council of Life Insurance commissioned the Futures Group of Glastonbury, Connecticut, to examine the potential for large-scale catastrophic events in the near future. TAP was specifically concerned with five potential crises: the warming of the earth's atmosphere, the water shortage, the collapse of the physical infrastructure, the global financial crisis, and the threat of nuclear war. We are often unprepared to take action; in these cases, we lose an advantage we might have otherwise had. This is the whole idea behind forecasting: to foresee possibilities and to project how we can respond. If we are able to create forecasts against which we can test policy options and choices, we may have the luxury of adopting policies ahead of events. Rather than simply fighting fires, we have the option of creating a future more to our choosing. Short descriptions of these five potential crises and, in some cases, possible solutions are presented

  18. Forecasting oilfield economic performance

    International Nuclear Information System (INIS)

    Bradley, M.E.; Wood, A.R.O.

    1994-01-01

    This paper presents a general method for forecasting oilfield economic performance that integrates cost data with operational, reservoir, and financial information. Practices are developed for determining economic limits for an oil field and its components. The economic limits of marginal wells and the role of underground competition receive special attention. Also examined is the influence of oil prices on operating costs. Examples illustrate application of these concepts. Categorization of costs for historical tracking and projections is recommended

  19. Frost Forecasting for Fruitgrowers

    Science.gov (United States)

    Martsolf, J. D.; Chen, E.

    1983-01-01

    Progress in forecasting from satellite data reviewed. University study found data from satellites displayed in color and used to predict frost are valuable aid to agriculture. Study evaluated scheme to use Earth-temperature data from Geostationary Operational Environmental Satellite in computer model that determines when and where freezing temperatures endanger developing fruit crops, such as apples, peaches and cherries in spring and citrus crops in winter.

  20. Uranium price forecasting methods

    International Nuclear Information System (INIS)

    Fuller, D.M.

    1994-01-01

    This article reviews a number of forecasting methods that have been applied to uranium prices and compares their relative strengths and weaknesses. The methods reviewed are: (1) judgemental methods, (2) technical analysis, (3) time-series methods, (4) fundamental analysis, and (5) econometric methods. Historically, none of these methods has performed very well, but a well-thought-out model is still useful as a basis from which to adjust to new circumstances and try again

  1. PyForecastTools

    Energy Technology Data Exchange (ETDEWEB)

    2017-09-22

    The PyForecastTools package provides Python routines for calculating metrics for model validation, forecast verification and model comparison. For continuous predictands the package provides functions for calculating bias (mean error, mean percentage error, median log accuracy, symmetric signed bias), and for calculating accuracy (mean squared error, mean absolute error, mean absolute scaled error, normalized RMSE, median symmetric accuracy). Convenience routines to calculate the component parts (e.g. forecast error, scaled error) of each metric are also provided. To compare models the package provides: generic skill score; percent better. Robust measures of scale including median absolute deviation, robust standard deviation, robust coefficient of variation and the Sn estimator are all provided by the package. Finally, the package implements Python classes for NxN contingency tables. In the case of a multi-class prediction, accuracy and skill metrics such as proportion correct and the Heidke and Peirce skill scores are provided as object methods. The special case of a 2x2 contingency table inherits from the NxN class and provides many additional metrics for binary classification: probability of detection, probability of false detection, false alarm ration, threat score, equitable threat score, bias. Confidence intervals for many of these quantities can be calculated using either the Wald method or Agresti-Coull intervals.

  2. Seismic forecast using geostatistics

    International Nuclear Information System (INIS)

    Grecu, Valeriu; Mateiciuc, Doru

    2007-01-01

    The main idea of this research direction consists in the special way of constructing a new type of mathematical function as being a correlation between a computed statistical quantity and another physical quantity. This type of function called 'position function' was taken over by the authors of this study in the field of seismology with the hope of solving - at least partially - the difficult problem of seismic forecast. The geostatistic method of analysis focuses on the process of energy accumulation in a given seismic area, completing this analysis by a so-called loading function. This function - in fact a temporal function - describes the process of energy accumulation during a seismic cycle from a given seismic area. It was possible to discover a law of evolution of the seismic cycles that was materialized in a so-called characteristic function. This special function will help us to forecast the magnitude and the occurrence moment of the largest earthquake in the analysed area. Since 2000, the authors have been evolving to a new stage of testing: real - time analysis, in order to verify the quality of the method. There were five large earthquakes forecasts. (authors)

  3. Statistical methods for forecasting

    CERN Document Server

    Abraham, Bovas

    2009-01-01

    The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists."This book, it must be said, lives up to the words on its advertising cover: ''Bridging the gap between introductory, descriptive approaches and highly advanced theoretical treatises, it provides a practical, intermediate level discussion of a variety of forecasting tools, and explains how they relate to one another, both in theory and practice.'' It does just that!"-Journal of the Royal Statistical Society"A well-written work that deals with statistical methods and models that can be used to produce short-term forecasts, this book has wide-ranging applications. It could be used in the context of a study of regression, forecasting, and time series ...

  4. Development and testing of improved statistical wind power forecasting methods.

    Energy Technology Data Exchange (ETDEWEB)

    Mendes, J.; Bessa, R.J.; Keko, H.; Sumaili, J.; Miranda, V.; Ferreira, C.; Gama, J.; Botterud, A.; Zhou, Z.; Wang, J. (Decision and Information Sciences); (INESC Porto)

    2011-12-06

    Wind power forecasting (WPF) provides important inputs to power system operators and electricity market participants. It is therefore not surprising that WPF has attracted increasing interest within the electric power industry. In this report, we document our research on improving statistical WPF algorithms for point, uncertainty, and ramp forecasting. Below, we provide a brief introduction to the research presented in the following chapters. For a detailed overview of the state-of-the-art in wind power forecasting, we refer to [1]. Our related work on the application of WPF in operational decisions is documented in [2]. Point forecasts of wind power are highly dependent on the training criteria used in the statistical algorithms that are used to convert weather forecasts and observational data to a power forecast. In Chapter 2, we explore the application of information theoretic learning (ITL) as opposed to the classical minimum square error (MSE) criterion for point forecasting. In contrast to the MSE criterion, ITL criteria do not assume a Gaussian distribution of the forecasting errors. We investigate to what extent ITL criteria yield better results. In addition, we analyze time-adaptive training algorithms and how they enable WPF algorithms to cope with non-stationary data and, thus, to adapt to new situations without requiring additional offline training of the model. We test the new point forecasting algorithms on two wind farms located in the U.S. Midwest. Although there have been advancements in deterministic WPF, a single-valued forecast cannot provide information on the dispersion of observations around the predicted value. We argue that it is essential to generate, together with (or as an alternative to) point forecasts, a representation of the wind power uncertainty. Wind power uncertainty representation can take the form of probabilistic forecasts (e.g., probability density function, quantiles), risk indices (e.g., prediction risk index) or scenarios

  5. Analysing UK real estate market forecast disagreement

    OpenAIRE

    McAllister, Patrick; Newell, G.; Matysiak, George

    2005-01-01

    Given the significance of forecasting in real estate investment decisions, this paper investigates forecast uncertainty and disagreement in real estate market forecasts. Using the Investment Property Forum (IPF) quarterly survey amongst UK independent real estate forecasters, these real estate forecasts are compared with actual real estate performance to assess a number of real estate forecasting issues in the UK over 1999-2004, including real estate forecast error, bias and consensus. The re...

  6. Effective Feature Preprocessing for Time Series Forecasting

    DEFF Research Database (Denmark)

    Zhao, Junhua; Dong, Zhaoyang; Xu, Zhao

    2006-01-01

    Time series forecasting is an important area in data mining research. Feature preprocessing techniques have significant influence on forecasting accuracy, therefore are essential in a forecasting model. Although several feature preprocessing techniques have been applied in time series forecasting...... performance in time series forecasting. It is demonstrated in our experiment that, effective feature preprocessing can significantly enhance forecasting accuracy. This research can be a useful guidance for researchers on effectively selecting feature preprocessing techniques and integrating them with time...... series forecasting models....

  7. EU pharmaceutical expenditure forecast.

    Science.gov (United States)

    Urbinati, Duccio; Rémuzat, Cécile; Kornfeld, Åsa; Vataire, Anne-Lise; Cetinsoy, Laurent; Aballéa, Samuel; Mzoughi, Olfa; Toumi, Mondher

    2014-01-01

    With constant incentives for healthcare payers to contain their pharmaceutical budgets, forecasting has become critically important. Some countries have, for instance, developed pharmaceutical horizon scanning units. The objective of this project was to build a model to assess the net effect of the entrance of new patented medicinal products versus medicinal products going off-patent, with a defined forecast horizon, on selected European Union (EU) Member States' pharmaceutical budgets. This model took into account population ageing, as well as current and future country-specific pricing, reimbursement, and market access policies (the project was performed for the European Commission; see http://ec.europa.eu/health/healthcare/key_documents/index_en.htm). In order to have a representative heterogeneity of EU Member States, the following countries were selected for the analysis: France, Germany, Greece, Hungary, Poland, Portugal, and the United Kingdom. A forecasting period of 5 years (2012-2016) was chosen to assess the net pharmaceutical budget impact. A model for generics and biosimilars was developed for each country. The model estimated a separate and combined effect of the direct and indirect impacts of the patent cliff. A second model, estimating the sales development and the risk of development failure, was developed for new drugs. New drugs were reviewed individually to assess their clinical potential and translate it into commercial potential. The forecast was carried out according to three perspectives (healthcare public payer, society, and manufacturer), and several types of distribution chains (retail, hospital, and combined retail and hospital). Probabilistic and deterministic sensitivity analyses were carried out. According to the model, all countries experienced drug budget reductions except Poland (+€41 million). Savings were expected to be the highest in the United Kingdom (-€9,367 million), France (-€5,589 million), and, far behind them

  8. Do we need demographic data to forecast plant population dynamics?

    Science.gov (United States)

    Tredennick, Andrew T.; Hooten, Mevin B.; Adler, Peter B.

    2017-01-01

    Rapid environmental change has generated growing interest in forecasts of future population trajectories. Traditional population models built with detailed demographic observations from one study site can address the impacts of environmental change at particular locations, but are difficult to scale up to the landscape and regional scales relevant to management decisions. An alternative is to build models using population-level data that are much easier to collect over broad spatial scales than individual-level data. However, it is unknown whether models built using population-level data adequately capture the effects of density-dependence and environmental forcing that are necessary to generate skillful forecasts.Here, we test the consequences of aggregating individual responses when forecasting the population states (percent cover) and trajectories of four perennial grass species in a semi-arid grassland in Montana, USA. We parameterized two population models for each species, one based on individual-level data (survival, growth and recruitment) and one on population-level data (percent cover), and compared their forecasting accuracy and forecast horizons with and without the inclusion of climate covariates. For both models, we used Bayesian ridge regression to weight the influence of climate covariates for optimal prediction.In the absence of climate effects, we found no significant difference between the forecast accuracy of models based on individual-level data and models based on population-level data. Climate effects were weak, but increased forecast accuracy for two species. Increases in accuracy with climate covariates were similar between model types.In our case study, percent cover models generated forecasts as accurate as those from a demographic model. For the goal of forecasting, models based on aggregated individual-level data may offer a practical alternative to data-intensive demographic models. Long time series of percent cover data already exist

  9. Forecasting Volatility of USD/MUR Exchange Rate using a GARCH ...

    African Journals Online (AJOL)

    that both distributions may forecast quite well with a slight advantage to the. GARCH(1 ... Financial time series tend to exhibit certain characteristic features such as volatility ... Heteroscedasticity-adjusted MAE to evaluate the forecasts. Chuanga et .... the Student's-t distribution or the GED with the following probability density.

  10. Evaluation of Probabilistic Disease Forecasts.

    Science.gov (United States)

    Hughes, Gareth; Burnett, Fiona J

    2017-10-01

    The statistical evaluation of probabilistic disease forecasts often involves calculation of metrics defined conditionally on disease status, such as sensitivity and specificity. However, for the purpose of disease management decision making, metrics defined conditionally on the result of the forecast-predictive values-are also important, although less frequently reported. In this context, the application of scoring rules in the evaluation of probabilistic disease forecasts is discussed. An index of separation with application in the evaluation of probabilistic disease forecasts, described in the clinical literature, is also considered and its relation to scoring rules illustrated. Scoring rules provide a principled basis for the evaluation of probabilistic forecasts used in plant disease management. In particular, the decomposition of scoring rules into interpretable components is an advantageous feature of their application in the evaluation of disease forecasts.

  11. Operational hydrological forecasting in Bavaria. Part I: Forecast uncertainty

    Science.gov (United States)

    Ehret, U.; Vogelbacher, A.; Moritz, K.; Laurent, S.; Meyer, I.; Haag, I.

    2009-04-01

    In Bavaria, operational flood forecasting has been established since the disastrous flood of 1999. Nowadays, forecasts based on rainfall information from about 700 raingauges and 600 rivergauges are calculated and issued for nearly 100 rivergauges. With the added experience of the 2002 and 2005 floods, awareness grew that the standard deterministic forecast, neglecting the uncertainty associated with each forecast is misleading, creating a false feeling of unambiguousness. As a consequence, a system to identify, quantify and communicate the sources and magnitude of forecast uncertainty has been developed, which will be presented in part I of this study. In this system, the use of ensemble meteorological forecasts plays a key role which will be presented in part II. Developing the system, several constraints stemming from the range of hydrological regimes and operational requirements had to be met: Firstly, operational time constraints obviate the variation of all components of the modeling chain as would be done in a full Monte Carlo simulation. Therefore, an approach was chosen where only the most relevant sources of uncertainty were dynamically considered while the others were jointly accounted for by static error distributions from offline analysis. Secondly, the dominant sources of uncertainty vary over the wide range of forecasted catchments: In alpine headwater catchments, typically of a few hundred square kilometers in size, rainfall forecast uncertainty is the key factor for forecast uncertainty, with a magnitude dynamically changing with the prevailing predictability of the atmosphere. In lowland catchments encompassing several thousands of square kilometers, forecast uncertainty in the desired range (usually up to two days) is mainly dependent on upstream gauge observation quality, routing and unpredictable human impact such as reservoir operation. The determination of forecast uncertainty comprised the following steps: a) From comparison of gauge

  12. Using Analog Ensemble to generate spatially downscaled probabilistic wind power forecasts

    Science.gov (United States)

    Delle Monache, L.; Shahriari, M.; Cervone, G.

    2017-12-01

    We use the Analog Ensemble (AnEn) method to generate probabilistic 80-m wind power forecasts. We use data from the NCEP GFS ( 28 km resolution) and NCEP NAM (12 km resolution). We use forecasts data from NAM and GFS, and analysis data from NAM which enables us to: 1) use a lower-resolution model to create higher-resolution forecasts, and 2) use a higher-resolution model to create higher-resolution forecasts. The former essentially increases computing speed and the latter increases forecast accuracy. An aggregated model of the former can be compared against the latter to measure the accuracy of the AnEn spatial downscaling. The AnEn works by taking a deterministic future forecast and comparing it with past forecasts. The model searches for the best matching estimates within the past forecasts and selects the predictand value corresponding to these past forecasts as the ensemble prediction for the future forecast. Our study is based on predicting wind speed and air density at more than 13,000 grid points in the continental US. We run the AnEn model twice: 1) estimating 80-m wind speed by using predictor variables such as temperature, pressure, geopotential height, U-component and V-component of wind, 2) estimating air density by using predictors such as temperature, pressure, and relative humidity. We use the air density values to correct the standard wind power curves for different values of air density. The standard deviation of the ensemble members (i.e. ensemble spread) will be used as the degree of difficulty to predict wind power at different locations. The value of the correlation coefficient between the ensemble spread and the forecast error determines the appropriateness of this measure. This measure is prominent for wind farm developers as building wind farms in regions with higher predictability will reduce the real-time risks of operating in the electricity markets.

  13. Global Energy Forecasting Competition 2012

    DEFF Research Database (Denmark)

    Hong, Tao; Pinson, Pierre; Fan, Shu

    2014-01-01

    The Global Energy Forecasting Competition (GEFCom2012) attracted hundreds of participants worldwide, who contributed many novel ideas to the energy forecasting field. This paper introduces both tracks of GEFCom2012, hierarchical load forecasting and wind power forecasting, with details...... on the aspects of the problem, the data, and a summary of the methods used by selected top entries. We also discuss the lessons learned from this competition from the organizers’ perspective. The complete data set, including the solution data, is published along with this paper, in an effort to establish...

  14. Forecasting Lightning Threat Using WRF Proxy Fields

    Science.gov (United States)

    McCaul, E. W., Jr.

    2010-01-01

    Objectives: Given that high-resolution WRF forecasts can capture the character of convective outbreaks, we seek to: 1. Create WRF forecasts of LTG threat (1-24 h), based on 2 proxy fields from explicitly simulated convection: - graupel flux near -15 C (captures LTG time variability) - vertically integrated ice (captures LTG threat area). 2. Calibrate each threat to yield accurate quantitative peak flash rate densities. 3. Also evaluate threats for areal coverage, time variability. 4. Blend threats to optimize results. 5. Examine sensitivity to model mesh, microphysics. Methods: 1. Use high-resolution 2-km WRF simulations to prognose convection for a diverse series of selected case studies. 2. Evaluate graupel fluxes; vertically integrated ice (VII). 3. Calibrate WRF LTG proxies using peak total LTG flash rate densities from NALMA; relationships look linear, with regression line passing through origin. 4. Truncate low threat values to make threat areal coverage match NALMA flash extent density obs. 5. Blend proxies to achieve optimal performance 6. Study CAPS 4-km ensembles to evaluate sensitivities.

  15. Forecasting in Complex Systems

    Science.gov (United States)

    Rundle, J. B.; Holliday, J. R.; Graves, W. R.; Turcotte, D. L.; Donnellan, A.

    2014-12-01

    Complex nonlinear systems are typically characterized by many degrees of freedom, as well as interactions between the elements. Interesting examples can be found in the areas of earthquakes and finance. In these two systems, fat tails play an important role in the statistical dynamics. For earthquake systems, the Gutenberg-Richter magnitude-frequency is applicable, whereas for daily returns for the securities in the financial markets are known to be characterized by leptokurtotic statistics in which the tails are power law. Very large fluctuations are present in both systems. In earthquake systems, one has the example of great earthquakes such as the M9.1, March 11, 2011 Tohoku event. In financial systems, one has the example of the market crash of October 19, 1987. Both were largely unexpected events that severely impacted the earth and financial systems systemically. Other examples include the M9.3 Andaman earthquake of December 26, 2004, and the Great Recession which began with the fall of Lehman Brothers investment bank on September 12, 2013. Forecasting the occurrence of these damaging events has great societal importance. In recent years, national funding agencies in a variety of countries have emphasized the importance of societal relevance in research, and in particular, the goal of improved forecasting technology. Previous work has shown that both earthquakes and financial crashes can be described by a common Landau-Ginzburg-type free energy model. These metastable systems are characterized by fat tail statistics near the classical spinodal. Correlations in these systems can grow and recede, but do not imply causation, a common source of misunderstanding. In both systems, a common set of techniques can be used to compute the probabilities of future earthquakes or crashes. In this talk, we describe the basic phenomenology of these systems and emphasize their similarities and differences. We also consider the problem of forecast validation and verification

  16. In-season retail sales forecasting using survival models

    African Journals Online (AJOL)

    Retail sales forecasting, survival analysis, time series analysis, Holt's smoothing .... where fx(t) is the probability density function of the future lifetime, Tx, of a .... Adjustments were made to the shape of the smoothed mortality rates in light of new.

  17. Flood Forecasting Based on TIGGE Precipitation Ensemble Forecast

    Directory of Open Access Journals (Sweden)

    Jinyin Ye

    2016-01-01

    Full Text Available TIGGE (THORPEX International Grand Global Ensemble was a major part of the THORPEX (Observing System Research and Predictability Experiment. It integrates ensemble precipitation products from all the major forecast centers in the world and provides systematic evaluation on the multimodel ensemble prediction system. Development of meteorologic-hydrologic coupled flood forecasting model and early warning model based on the TIGGE precipitation ensemble forecast can provide flood probability forecast, extend the lead time of the flood forecast, and gain more time for decision-makers to make the right decision. In this study, precipitation ensemble forecast products from ECMWF, NCEP, and CMA are used to drive distributed hydrologic model TOPX. We focus on Yi River catchment and aim to build a flood forecast and early warning system. The results show that the meteorologic-hydrologic coupled model can satisfactorily predict the flow-process of four flood events. The predicted occurrence time of peak discharges is close to the observations. However, the magnitude of the peak discharges is significantly different due to various performances of the ensemble prediction systems. The coupled forecasting model can accurately predict occurrence of the peak time and the corresponding risk probability of peak discharge based on the probability distribution of peak time and flood warning, which can provide users a strong theoretical foundation and valuable information as a promising new approach.

  18. Probabilistic Electricity Price Forecasting Models by Aggregation of Competitive Predictors

    Directory of Open Access Journals (Sweden)

    Claudio Monteiro

    2018-04-01

    Full Text Available This article presents original probabilistic price forecasting meta-models (PPFMCP models, by aggregation of competitive predictors, for day-ahead hourly probabilistic price forecasting. The best twenty predictors of the EEM2016 EPF competition are used to create ensembles of hourly spot price forecasts. For each hour, the parameter values of the probability density function (PDF of a Beta distribution for the output variable (hourly price can be directly obtained from the expected and variance values associated to the ensemble for such hour, using three aggregation strategies of predictor forecasts corresponding to three PPFMCP models. A Reliability Indicator (RI and a Loss function Indicator (LI are also introduced to give a measure of uncertainty of probabilistic price forecasts. The three PPFMCP models were satisfactorily applied to the real-world case study of the Iberian Electricity Market (MIBEL. Results from PPFMCP models showed that PPFMCP model 2, which uses aggregation by weight values according to daily ranks of predictors, was the best probabilistic meta-model from a point of view of mean absolute errors, as well as of RI and LI. PPFMCP model 1, which uses the averaging of predictor forecasts, was the second best meta-model. PPFMCP models allow evaluations of risk decisions based on the price to be made.

  19. FORECASTING NEW PRODUCT SALES

    Directory of Open Access Journals (Sweden)

    R. Siriram

    2012-01-01

    Full Text Available

    ENGLISH ABSTRACT: This paper tests the accuracy of using Linear regression, Logistics regression, and Bass curves in selected new product rollouts, based on sales data. The selected new products come from the electronics and electrical engineering and information and communications technology industries. The eight selected products are: electronic switchgear, electric motors, supervisory control and data acquisition systems, programmable logic controllers, cell phones, wireless modules, routers, and antennas. We compare the Linear regression, Logistics regression and Bass curves with respect to forecasting using analysis of variance. The accuracy of these three curves is studied and conclusions are drawn. We use an expert panel to compare the different curves and provide lessons for managers to improve forecasting new product sales. In addition, comparison between the two industries is drawn, and areas for further research are indicated.

    AFRIKAANSE OPSOMMING: Hierdie artikel toets die akkuraatheid van die gebruik van linêere regressie, logistiese regressie en Bass-krommes by die bekendstelling van nuwe produkte gebaseer op verkoopsdata. Die geselekteerde nuwe produkte is uit die elektriese en elektroniese asook informasietegnologie- en kommunikasie bedrywe. Linêere regressie, logistiese regressie en Bass-krommes word vergelyk ten opsigte van vooruitskatting deur variansie te ontleed. Die akkuraatheid word ontleed en gevolgtrekkings gemaak. Die doel is om vooruitskatting van nuwe produkverkope te verbeter.

  20. Issues in Forecasting CMEs

    Science.gov (United States)

    Pizzo, V. J.

    2017-12-01

    I will present my view of the current status of space weather forecasting abilities related to CMEs. This talk will address the large-scale aspects, but specifically not energetic particle phenomena. A key point is that all models, whether sophisticated numerical contraptions or quasi-empirical ones, are only as good as the data you feed them. Hence the emphasis will be on observations and analysis methods. First I will review where we stand with regard to the near-Sun quantitative data needed to drive any model, no matter how complex or simple-minded, and I will discuss technological roadblocks that suggest it may be some time before we see any meaningful improvements beyond what we have today. Then I cover issues related to characterizing CME propagation out through the corona and into interplanetary space, as well as to observational limitations in the vicinity of 1 AU. Since none of these observational constraints are likely to be resolved anytime soon, the real challenge is to make more informed use of what is available. Thus, this talk will focus on how we may identify and pursue the most profitable approaches, for both forecast and research applications. The discussion will highlight a number of promising leads, including those related to inclusion of solar backside information, joint magnetograph observations from L5 and Earth, how to use (not just run) ensembles, more rational use of HI observations, and suggestions for using cube-sats for deep space observations of CMEs and MCs.

  1. On the relation between forecast precision and trading profitability of financial analysts

    DEFF Research Database (Denmark)

    Marinelli, Carlo; Weissensteiner, Alex

    2014-01-01

    We analyze the relation between earnings forecast accuracy and the expected profitability of financial analysts. Modeling forecast errors with a multivariate normal distribution, a complete characterization of the payoff of each analyst is provided. In particular, closed-form expressions for the ......We analyze the relation between earnings forecast accuracy and the expected profitability of financial analysts. Modeling forecast errors with a multivariate normal distribution, a complete characterization of the payoff of each analyst is provided. In particular, closed-form expressions...... for the probability density function, for the expectation, and, more generally, for moments of all orders are obtained. Our analysis shows that the relationship between forecast precision and trading profitability needs not be monotonic, and that the impact of the correlation between the forecasts on the expected...

  2. Multiple-Decrement Compositional Forecasting with the Lee-Carter Model

    OpenAIRE

    Guan, Tianyu

    2014-01-01

    Changes in cause of death patterns have a great impact on health and social care costs paid by government and insurance companies. Unfortunately an overwhelming majority of methods for mortality projections is based on overall mortality with only very few studies focusing on forecasting cause-specific mortality. In this project, our aim is to forecast cause-specific death density with a coherent model. Since cause-specific death density obeys a unit sum constraint, it can be considered as com...

  3. Global Ensemble Forecast System (GEFS) [1 Deg.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Ensemble Forecast System (GEFS) is a weather forecast model made up of 21 separate forecasts, or ensemble members. The National Centers for Environmental...

  4. Guidelines for forecasting energy demand

    International Nuclear Information System (INIS)

    Sonino, T.

    1976-11-01

    Four methodologies for forecasting energy demand are reviewed here after considering the role of energy in the economy and the analysis of energy use in different economic sectors. The special case of Israel is considered throughout, and some forecasts for energy demands in the year 2000 are presented. An energy supply mix that may be considered feasible is proposed. (author)

  5. Regional-seasonal weather forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Abarbanel, H.; Foley, H.; MacDonald, G.; Rothaus, O.; Rudermann, M.; Vesecky, J.

    1980-08-01

    In the interest of allocating heating fuels optimally, the state-of-the-art for seasonal weather forecasting is reviewed. A model using an enormous data base of past weather data is contemplated to improve seasonal forecasts, but present skills do not make that practicable. 90 references. (PSB)

  6. Forecasting the future of biodiversity

    DEFF Research Database (Denmark)

    Fitzpatrick, M. C.; Sanders, Nate; Ferrier, Simon

    2011-01-01

    , but their application to forecasting climate change impacts on biodiversity has been limited. Here we compare forecasts of changes in patterns of ant biodiversity in North America derived from ensembles of single-species models to those from a multi-species modeling approach, Generalized Dissimilarity Modeling (GDM...... climate change impacts on biodiversity....

  7. Forecasts: uncertain, inaccurate and biased?

    DEFF Research Database (Denmark)

    Nicolaisen, Morten Skou; Ambrasaite, Inga; Salling, Kim Bang

    2012-01-01

    Cost Benefit Analysis (CBA) is the dominating methodology for appraisal of transport infrastructure projects across the globe. In order to adequately assess the costs and benefits of such projects two types of forecasts are crucial to the validity of the appraisal. First are the forecasts of cons....... It is recommended that more attention is given to monitoring completed projects so future forecasts can benefit from better data availability through systematic ex-post evaluations, and an example of how to utilize such data in practice is presented.......Cost Benefit Analysis (CBA) is the dominating methodology for appraisal of transport infrastructure projects across the globe. In order to adequately assess the costs and benefits of such projects two types of forecasts are crucial to the validity of the appraisal. First are the forecasts...... of construction costs, which account for the majority of total project costs. Second are the forecasts of travel time savings, which account for the majority of total project benefits. The latter of these is, inter alia, determined by forecasts of travel demand, which we shall use as a proxy for the forecasting...

  8. Ensemble hydromoeteorological forecasting in Denmark

    DEFF Research Database (Denmark)

    Lucatero Villasenor, Diana

    forecasts where a dampening of the differences of precipitation quality occurs. Seasonal meteorological forecasts are possible due to changes of large scale patterns of the ocean and land, such as el Niño, that evolve at a much slower pace than the atmosphere, which can have an impact on its evolution later...

  9. Now, Here's the Weather Forecast...

    Science.gov (United States)

    Richardson, Mathew

    2013-01-01

    The Met Office has a long history of weather forecasting, creating tailored weather forecasts for customers across the world. Based in Exeter, the Met Office is also home to the Met Office Hadley Centre, a world-leading centre for the study of climate change and its potential impacts. Climate information from the Met Office Hadley Centre is used…

  10. Method of forecasting power distribution

    International Nuclear Information System (INIS)

    Kaneto, Kunikazu.

    1981-01-01

    Purpose: To obtain forecasting results at high accuracy by reflecting the signals from neutron detectors disposed in the reactor core on the forecasting results. Method: An on-line computer transfers, to a simulator, those process data such as temperature and flow rate for coolants in each of the sections and various measuring signals such as control rod positions from the nuclear reactor. The simulator calculates the present power distribution before the control operation. The signals from the neutron detectors at each of the positions in the reactor core are estimated from the power distribution and errors are determined based on the estimated values and the measured values to determine the smooth error distribution in the axial direction. Then, input conditions at the time to be forecast are set by a data setter. The simulator calculates the forecast power distribution after the control operation based on the set conditions. The forecast power distribution is corrected using the error distribution. (Yoshino, Y.)

  11. Energy forecasts, perspectives and methods

    Energy Technology Data Exchange (ETDEWEB)

    Svensson, J E; Mogren, A

    1984-01-01

    The authors have analyzed different methods for long term energy prognoses, in particular energy consumption forecasts. Energy supply and price prognoses are also treated, but in a less detailed manner. After defining and discussing the various methods/models used in forecasts, a generalized discussion of the influence on the prognoses from the perspectives (background factors, world view, norms, ideology) of the prognosis makers is given. Some basic formal demands that should be asked from any rational forecast are formulated and discussed. The authors conclude that different forecasting methodologies are supplementing each other. There is no best method, forecasts should be accepted as views of the future from differing perspectives. The primary prognostic problem is to show the possible futures, selecting the wanted future is a question of political process.

  12. Hydrocarbon Rocket Technology Impact Forecasting

    Science.gov (United States)

    Stuber, Eric; Prasadh, Nishant; Edwards, Stephen; Mavris, Dimitri N.

    2012-01-01

    Ever since the Apollo program ended, the development of launch propulsion systems in the US has fallen drastically, with only two new booster engine developments, the SSME and the RS-68, occurring in the past few decades.1 In recent years, however, there has been an increased interest in pursuing more effective launch propulsion technologies in the U.S., exemplified by the NASA Office of the Chief Technologist s inclusion of Launch Propulsion Systems as the first technological area in the Space Technology Roadmaps2. One area of particular interest to both government agencies and commercial entities has been the development of hydrocarbon engines; NASA and the Air Force Research Lab3 have expressed interest in the use of hydrocarbon fuels for their respective SLS Booster and Reusable Booster System concepts, and two major commercially-developed launch vehicles SpaceX s Falcon 9 and Orbital Sciences Antares feature engines that use RP-1 kerosene fuel. Compared to engines powered by liquid hydrogen, hydrocarbon-fueled engines have a greater propellant density (usually resulting in a lighter overall engine), produce greater propulsive force, possess easier fuel handling and loading, and for reusable vehicle concepts can provide a shorter turnaround time between launches. These benefits suggest that a hydrocarbon-fueled launch vehicle would allow for a cheap and frequent means of access to space.1 However, the time and money required for the development of a new engine still presents a major challenge. Long and costly design, development, testing and evaluation (DDT&E) programs underscore the importance of identifying critical technologies and prioritizing investment efforts. Trade studies must be performed on engine concepts examining the affordability, operability, and reliability of each concept, and quantifying the impacts of proposed technologies. These studies can be performed through use of the Technology Impact Forecasting (TIF) method. The Technology Impact

  13. Demonstrating the value of larger ensembles in forecasting physical systems

    Directory of Open Access Journals (Sweden)

    Reason L. Machete

    2016-12-01

    Full Text Available Ensemble simulation propagates a collection of initial states forward in time in a Monte Carlo fashion. Depending on the fidelity of the model and the properties of the initial ensemble, the goal of ensemble simulation can range from merely quantifying variations in the sensitivity of the model all the way to providing actionable probability forecasts of the future. Whatever the goal is, success depends on the properties of the ensemble, and there is a longstanding discussion in meteorology as to the size of initial condition ensemble most appropriate for Numerical Weather Prediction. In terms of resource allocation: how is one to divide finite computing resources between model complexity, ensemble size, data assimilation and other components of the forecast system. One wishes to avoid undersampling information available from the model's dynamics, yet one also wishes to use the highest fidelity model available. Arguably, a higher fidelity model can better exploit a larger ensemble; nevertheless it is often suggested that a relatively small ensemble, say ~16 members, is sufficient and that larger ensembles are not an effective investment of resources. This claim is shown to be dubious when the goal is probabilistic forecasting, even in settings where the forecast model is informative but imperfect. Probability forecasts for a ‘simple’ physical system are evaluated at different lead times; ensembles of up to 256 members are considered. The pure density estimation context (where ensemble members are drawn from the same underlying distribution as the target differs from the forecasting context, where one is given a high fidelity (but imperfect model. In the forecasting context, the information provided by additional members depends also on the fidelity of the model, the ensemble formation scheme (data assimilation, the ensemble interpretation and the nature of the observational noise. The effect of increasing the ensemble size is quantified by

  14. Forecasting global atmospheric CO2

    International Nuclear Information System (INIS)

    Agusti-Panareda, A.; Massart, S.; Boussetta, S.; Balsamo, G.; Beljaars, A.; Engelen, R.; Jones, L.; Peuch, V.H.; Chevallier, F.; Ciais, P.; Paris, J.D.; Sherlock, V.

    2014-01-01

    A new global atmospheric carbon dioxide (CO 2 ) real-time forecast is now available as part of the preoperational Monitoring of Atmospheric Composition and Climate - Interim Implementation (MACC-II) service using the infrastructure of the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS). One of the strengths of the CO 2 forecasting system is that the land surface, including vegetation CO 2 fluxes, is modelled online within the IFS. Other CO 2 fluxes are prescribed from inventories and from off-line statistical and physical models. The CO 2 forecast also benefits from the transport modelling from a state-of-the-art numerical weather prediction (NWP) system initialized daily with a wealth of meteorological observations. This paper describes the capability of the forecast in modelling the variability of CO 2 on different temporal and spatial scales compared to observations. The modulation of the amplitude of the CO 2 diurnal cycle by near-surface winds and boundary layer height is generally well represented in the forecast. The CO 2 forecast also has high skill in simulating day-to-day synoptic variability. In the atmospheric boundary layer, this skill is significantly enhanced by modelling the day-to-day variability of the CO 2 fluxes from vegetation compared to using equivalent monthly mean fluxes with a diurnal cycle. However, biases in the modelled CO 2 fluxes also lead to accumulating errors in the CO 2 forecast. These biases vary with season with an underestimation of the amplitude of the seasonal cycle both for the CO 2 fluxes compared to total optimized fluxes and the atmospheric CO 2 compared to observations. The largest biases in the atmospheric CO 2 forecast are found in spring, corresponding to the onset of the growing season in the Northern Hemisphere. In the future, the forecast will be re-initialized regularly with atmospheric CO 2 analyses based on the assimilation of CO 2 products retrieved from satellite

  15. Climate Forecast System Version 2 (CFSv2) Operational Forecasts

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Climate Forecast System Version 2 (CFSv2) produced by the NOAA National Centers for Environmental Prediction (NCEP) is a fully coupled model representing the...

  16. Black Sea coastal forecasting system

    Directory of Open Access Journals (Sweden)

    A. I. Kubryakov

    2012-03-01

    Full Text Available The Black Sea coastal nowcasting and forecasting system was built within the framework of EU FP6 ECOOP (European COastalshelf sea OPerational observing and forecasting system project for five regions: the south-western basin along the coasts of Bulgaria and Turkey, the north-western shelf along the Romanian and Ukrainian coasts, coastal zone around of the Crimea peninsula, the north-eastern Russian coastal zone and the coastal zone of Georgia. The system operates in the real-time mode during the ECOOP project and afterwards. The forecasts include temperature, salinity and current velocity fields. Ecosystem model operates in the off-line mode near the Crimea coast.

  17. Magnetogram Forecast: An All-Clear Space Weather Forecasting System

    Science.gov (United States)

    Barghouty, Nasser; Falconer, David

    2015-01-01

    Solar flares and coronal mass ejections (CMEs) are the drivers of severe space weather. Forecasting the probability of their occurrence is critical in improving space weather forecasts. The National Oceanic and Atmospheric Administration (NOAA) currently uses the McIntosh active region category system, in which each active region on the disk is assigned to one of 60 categories, and uses the historical flare rates of that category to make an initial forecast that can then be adjusted by the NOAA forecaster. Flares and CMEs are caused by the sudden release of energy from the coronal magnetic field by magnetic reconnection. It is believed that the rate of flare and CME occurrence in an active region is correlated with the free energy of an active region. While the free energy cannot be measured directly with present observations, proxies of the free energy can instead be used to characterize the relative free energy of an active region. The Magnetogram Forecast (MAG4) (output is available at the Community Coordinated Modeling Center) was conceived and designed to be a databased, all-clear forecasting system to support the operational goals of NASA's Space Radiation Analysis Group. The MAG4 system automatically downloads nearreal- time line-of-sight Helioseismic and Magnetic Imager (HMI) magnetograms on the Solar Dynamics Observatory (SDO) satellite, identifies active regions on the solar disk, measures a free-energy proxy, and then applies forecasting curves to convert the free-energy proxy into predicted event rates for X-class flares, M- and X-class flares, CMEs, fast CMEs, and solar energetic particle events (SPEs). The forecast curves themselves are derived from a sample of 40,000 magnetograms from 1,300 active region samples, observed by the Solar and Heliospheric Observatory Michelson Doppler Imager. Figure 1 is an example of MAG4 visual output

  18. Earthquake number forecasts testing

    Science.gov (United States)

    Kagan, Yan Y.

    2017-10-01

    We study the distributions of earthquake numbers in two global earthquake catalogues: Global Centroid-Moment Tensor and Preliminary Determinations of Epicenters. The properties of these distributions are especially required to develop the number test for our forecasts of future seismic activity rate, tested by the Collaboratory for Study of Earthquake Predictability (CSEP). A common assumption, as used in the CSEP tests, is that the numbers are described by the Poisson distribution. It is clear, however, that the Poisson assumption for the earthquake number distribution is incorrect, especially for the catalogues with a lower magnitude threshold. In contrast to the one-parameter Poisson distribution so widely used to describe earthquake occurrences, the negative-binomial distribution (NBD) has two parameters. The second parameter can be used to characterize the clustering or overdispersion of a process. We also introduce and study a more complex three-parameter beta negative-binomial distribution. We investigate the dependence of parameters for both Poisson and NBD distributions on the catalogue magnitude threshold and on temporal subdivision of catalogue duration. First, we study whether the Poisson law can be statistically rejected for various catalogue subdivisions. We find that for most cases of interest, the Poisson distribution can be shown to be rejected statistically at a high significance level in favour of the NBD. Thereafter, we investigate whether these distributions fit the observed distributions of seismicity. For this purpose, we study upper statistical moments of earthquake numbers (skewness and kurtosis) and compare them to the theoretical values for both distributions. Empirical values for the skewness and the kurtosis increase for the smaller magnitude threshold and increase with even greater intensity for small temporal subdivision of catalogues. The Poisson distribution for large rate values approaches the Gaussian law, therefore its skewness

  19. 25 years of time series forecasting

    NARCIS (Netherlands)

    de Gooijer, J.G.; Hyndman, R.J.

    2006-01-01

    We review the past 25 years of research into time series forecasting. In this silver jubilee issue, we naturally highlight results published in journals managed by the International Institute of Forecasters (Journal of Forecasting 1982-1985 and International Journal of Forecasting 1985-2005). During

  20. Estimates of Uncertainty around the RBA's Forecasts

    OpenAIRE

    Peter Tulip; Stephanie Wallace

    2012-01-01

    We use past forecast errors to construct confidence intervals and other estimates of uncertainty around the Reserve Bank of Australia's forecasts of key macroeconomic variables. Our estimates suggest that uncertainty about forecasts is high. We find that the RBA's forecasts have substantial explanatory power for the inflation rate but not for GDP growth.

  1. Ensemble forecasting for renewable energy applications - status and current challenges for their generation and verification

    Science.gov (United States)

    Pinson, Pierre

    2016-04-01

    The operational management of renewable energy generation in power systems and electricity markets requires forecasts in various forms, e.g., deterministic or probabilistic, continuous or categorical, depending upon the decision process at hand. Besides, such forecasts may also be necessary at various spatial and temporal scales, from high temporal resolutions (in the order of minutes) and very localized for an offshore wind farm, to coarser temporal resolutions (hours) and covering a whole country for day-ahead power scheduling problems. As of today, weather predictions are a common input to forecasting methodologies for renewable energy generation. Since for most decision processes, optimal decisions can only be made if accounting for forecast uncertainties, ensemble predictions and density forecasts are increasingly seen as the product of choice. After discussing some of the basic approaches to obtaining ensemble forecasts of renewable power generation, it will be argued that space-time trajectories of renewable power production may or may not be necessitate post-processing ensemble forecasts for relevant weather variables. Example approaches and test case applications will be covered, e.g., looking at the Horns Rev offshore wind farm in Denmark, or gridded forecasts for the whole continental Europe. Eventually, we will illustrate some of the limitations of current frameworks to forecast verification, which actually make it difficult to fully assess the quality of post-processing approaches to obtain renewable energy predictions.

  2. A stochastic HMM-based forecasting model for fuzzy time series.

    Science.gov (United States)

    Li, Sheng-Tun; Cheng, Yi-Chung

    2010-10-01

    Recently, fuzzy time series have attracted more academic attention than traditional time series due to their capability of dealing with the uncertainty and vagueness inherent in the data collected. The formulation of fuzzy relations is one of the key issues affecting forecasting results. Most of the present works adopt IF-THEN rules for relationship representation, which leads to higher computational overhead and rule redundancy. Sullivan and Woodall proposed a Markov-based formulation and a forecasting model to reduce computational overhead; however, its applicability is limited to handling one-factor problems. In this paper, we propose a novel forecasting model based on the hidden Markov model by enhancing Sullivan and Woodall's work to allow handling of two-factor forecasting problems. Moreover, in order to make the nature of conjecture and randomness of forecasting more realistic, the Monte Carlo method is adopted to estimate the outcome. To test the effectiveness of the resulting stochastic model, we conduct two experiments and compare the results with those from other models. The first experiment consists of forecasting the daily average temperature and cloud density in Taipei, Taiwan, and the second experiment is based on the Taiwan Weighted Stock Index by forecasting the exchange rate of the New Taiwan dollar against the U.S. dollar. In addition to improving forecasting accuracy, the proposed model adheres to the central limit theorem, and thus, the result statistically approximates to the real mean of the target value being forecast.

  3. Towards a GME ensemble forecasting system: Ensemble initialization using the breeding technique

    Directory of Open Access Journals (Sweden)

    Jan D. Keller

    2008-12-01

    Full Text Available The quantitative forecast of precipitation requires a probabilistic background particularly with regard to forecast lead times of more than 3 days. As only ensemble simulations can provide useful information of the underlying probability density function, we built a new ensemble forecasting system (GME-EFS based on the GME model of the German Meteorological Service (DWD. For the generation of appropriate initial ensemble perturbations we chose the breeding technique developed by Toth and Kalnay (1993, 1997, which develops perturbations by estimating the regions of largest model error induced uncertainty. This method is applied and tested in the framework of quasi-operational forecasts for a three month period in 2007. The performance of the resulting ensemble forecasts are compared to the operational ensemble prediction systems ECMWF EPS and NCEP GFS by means of ensemble spread of free atmosphere parameters (geopotential and temperature and ensemble skill of precipitation forecasting. This comparison indicates that the GME ensemble forecasting system (GME-EFS provides reasonable forecasts with spread skill score comparable to that of the NCEP GFS. An analysis with the continuous ranked probability score exhibits a lack of resolution for the GME forecasts compared to the operational ensembles. However, with significant enhancements during the 3 month test period, the first results of our work with the GME-EFS indicate possibilities for further development as well as the potential for later operational usage.

  4. Fennec dust forecast intercomparison over the Sahara in June 2011

    Directory of Open Access Journals (Sweden)

    J.-P. Chaboureau

    2016-06-01

    Full Text Available In the framework of the Fennec international programme, a field campaign was conducted in June 2011 over the western Sahara. It led to the first observational data set ever obtained that documents the dynamics, thermodynamics and composition of the Saharan atmospheric boundary layer (SABL under the influence of the heat low. In support to the aircraft operation, four dust forecasts were run daily at low and high resolutions with convection-parameterizing and convection-permitting models, respectively. The unique airborne and ground-based data sets allowed the first ever intercomparison of dust forecasts over the western Sahara. At monthly scale, large aerosol optical depths (AODs were forecast over the Sahara, a feature observed by satellite retrievals but with different magnitudes. The AOD intensity was correctly predicted by the high-resolution models, while it was underestimated by the low-resolution models. This was partly because of the generation of strong near-surface wind associated with thunderstorm-related density currents that could only be reproduced by models representing convection explicitly. Such models yield emissions mainly in the afternoon that dominate the total emission over the western fringes of the Adrar des Iforas and the Aïr Mountains in the high-resolution forecasts. Over the western Sahara, where the harmattan contributes up to 80 % of dust emission, all the models were successful in forecasting the deep well-mixed SABL. Some of them, however, missed the large near-surface dust concentration generated by density currents and low-level winds. This feature, observed repeatedly by the airborne lidar, was partly forecast by one high-resolution model only.

  5. Recurrent networks for wave forecasting

    Digital Repository Service at National Institute of Oceanography (India)

    Mandal, S.; Prabaharan, N.

    , merchant vessel routing, nearshore construction, etc. more efficiently and safely. This paper presents an application of the Artificial Neural Network, namely Backpropagation Recurrent Neural Network (BRNN) with rprop update algorithm for wave forecasting...

  6. Ensemble forecasting of species distributions.

    Science.gov (United States)

    Araújo, Miguel B; New, Mark

    2007-01-01

    Concern over implications of climate change for biodiversity has led to the use of bioclimatic models to forecast the range shifts of species under future climate-change scenarios. Recent studies have demonstrated that projections by alternative models can be so variable as to compromise their usefulness for guiding policy decisions. Here, we advocate the use of multiple models within an ensemble forecasting framework and describe alternative approaches to the analysis of bioclimatic ensembles, including bounding box, consensus and probabilistic techniques. We argue that, although improved accuracy can be delivered through the traditional tasks of trying to build better models with improved data, more robust forecasts can also be achieved if ensemble forecasts are produced and analysed appropriately.

  7. Forecasting and management of technology

    National Research Council Canada - National Science Library

    Roper, A. T

    2011-01-01

    .... The scope of this edition has broadened to include management of technology content that is relevant to now to executives in organizations while updating and strengthening the technology forecasting...

  8. Forecasting Croatian inbound tourism demand

    OpenAIRE

    Tica, Josip; Kožić, Ivan

    2015-01-01

    The aim of this paper is to present a forecasting model for the overnight stays of foreign tourists in Croatia. Tourism is one of the most important parts of the Croatian economy. It is particularly important in the context of the services sector. Regular and significant surpluses and the consumption of foreign guests are an important element of budget revenues, especially VAT. The ability to forecast the development of inbound tourism demand in a timely manner is crucial for both business...

  9. Preparing for an Uncertain Forecast

    Science.gov (United States)

    Karolak, Eric

    2011-01-01

    Navigating the world of government relations and public policy can be a little like predicting the weather. One can't always be sure what's in store or how it will affect him/her down the road. But there are common patterns and a few basic steps that can help one best prepare for a change in the forecast. Though the forecast is uncertain, early…

  10. 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.

  11. Forecasting market developments

    International Nuclear Information System (INIS)

    Weller, T.

    1997-01-01

    Traditional planning in essence consists of linear extrapolation of established facts and experience. This approach was good enough until recently, when progress would be relatively foreseeable within a stable system. The situation has been changing with developments and modifications in the global economic sector proceeding at accelerated pace, so that conventional planning methods become hopelessly inadequate. The past is of low significance to emerging markets; planners today have to keep abreast with and take into account the possible and emerging influencing factors. Experience is a factor to be replaced by intelligent analysis and conclusion within the framework of system networks. Modern scenario modelling methods are based on this approach: They are able to simulate and forecast a whole range of ''possible futures'', derived from perceivable trends. The article illustrates the novel planning methodology by assessing the future of the renewable energy sources, applying a computerized planning method (vision design) which is based on intelligent comparative analysis of all relevant trends. (Orig./RHM) [de

  12. Quantile forecast discrimination ability and value

    DEFF Research Database (Denmark)

    Ben Bouallègue, Zied; Pinson, Pierre; Friederichs, Petra

    2015-01-01

    While probabilistic forecast verification for categorical forecasts is well established, some of the existing concepts and methods have not found their equivalent for the case of continuous variables. New tools dedicated to the assessment of forecast discrimination ability and forecast value are ...... is illustrated based on synthetic datasets, as well as for the case of global radiation forecasts from the high resolution ensemble COSMO-DE-EPS of the German Weather Service....

  13. Markov Chain Modelling for Short-Term NDVI Time Series Forecasting

    Directory of Open Access Journals (Sweden)

    Stepčenko Artūrs

    2016-12-01

    Full Text Available In this paper, the NDVI time series forecasting model has been developed based on the use of discrete time, continuous state Markov chain of suitable order. The normalised difference vegetation index (NDVI is an indicator that describes the amount of chlorophyll (the green mass and shows the relative density and health of vegetation; therefore, it is an important variable for vegetation forecasting. A Markov chain is a stochastic process that consists of a state space. This stochastic process undergoes transitions from one state to another in the state space with some probabilities. A Markov chain forecast model is flexible in accommodating various forecast assumptions and structures. The present paper discusses the considerations and techniques in building a Markov chain forecast model at each step. Continuous state Markov chain model is analytically described. Finally, the application of the proposed Markov chain model is illustrated with reference to a set of NDVI time series data.

  14. Evaluating long term forecasts

    Energy Technology Data Exchange (ETDEWEB)

    Lady, George M. [Department of Economics, College of Liberal Arts, Temple University, Philadelphia, PA 19122 (United States)

    2010-03-15

    The U.S. Department of Energy's Energy Information Administration (EIA), and its predecessor organizations, has published projections of U.S. energy production, consumption, distribution and prices annually for over 30 years. A natural issue to raise in evaluating the projections is an assessment of their accuracy compared to eventual outcomes. A related issue is the determination of the sources of 'error' in the projections that are due to differences between the actual versus realized values of the associated assumptions. One way to do this would be to run the computer-based model from which the projections are derived at the time the projected values are realized, using actual rather than assumed values for model assumptions; and, compare these results to the original projections. For long term forecasts, this approach would require that the model's software and hardware configuration be archived and available for many years, possibly decades, into the future. Such archival creates many practical problems; and, in general, it is not being done. This paper reports on an alternative approach for evaluating the projections. In the alternative approach, the model is run many times for cases in which important assumptions are changed individually and in combinations. A database is assembled from the solutions and a regression analysis is conducted for each important projected variable with the associated assumptions chosen as exogenous variables. When actual data are eventually available, the regression results are then used to estimate the sources of the differences in the projections of the endogenous variables compared to their eventual outcomes. The results presented here are for residential and commercial sector natural gas and electricity consumption. (author)

  15. Probabilistic wind power forecasting based on logarithmic transformation and boundary kernel

    International Nuclear Information System (INIS)

    Zhang, Yao; Wang, Jianxue; Luo, Xu

    2015-01-01

    Highlights: • Quantitative information on the uncertainty of wind power generation. • Kernel density estimator provides non-Gaussian predictive distributions. • Logarithmic transformation reduces the skewness of wind power density. • Boundary kernel method eliminates the density leakage near the boundary. - Abstracts: Probabilistic wind power forecasting not only produces the expectation of wind power output, but also gives quantitative information on the associated uncertainty, which is essential for making better decisions about power system and market operations with the increasing penetration of wind power generation. This paper presents a novel kernel density estimator for probabilistic wind power forecasting, addressing two characteristics of wind power which have adverse impacts on the forecast accuracy, namely, the heavily skewed and double-bounded nature of wind power density. Logarithmic transformation is used to reduce the skewness of wind power density, which improves the effectiveness of the kernel density estimator in a transformed scale. Transformations partially relieve the boundary effect problem of the kernel density estimator caused by the double-bounded nature of wind power density. However, the case study shows that there are still some serious problems of density leakage after the transformation. In order to solve this problem in the transformed scale, a boundary kernel method is employed to eliminate the density leak at the bounds of wind power distribution. The improvement of the proposed method over the standard kernel density estimator is demonstrated by short-term probabilistic forecasting results based on the data from an actual wind farm. Then, a detailed comparison is carried out of the proposed method and some existing probabilistic forecasting methods

  16. Probabilistic energy forecasting: Global Energy Forecasting Competition 2014 and beyond

    DEFF Research Database (Denmark)

    Hong, Tao; Pinson, Pierre; Fan, Shu

    2016-01-01

    The energy industry has been going through a significant modernization process over the last decade. Its infrastructure is being upgraded rapidly. The supply, demand and prices are becoming more volatile and less predictable than ever before. Even its business model is being challenged fundamenta......The energy industry has been going through a significant modernization process over the last decade. Its infrastructure is being upgraded rapidly. The supply, demand and prices are becoming more volatile and less predictable than ever before. Even its business model is being challenged...... fundamentally. In this competitive and dynamic environment, many decision-making processes rely on probabilistic forecasts to quantify the uncertain future. Although most of the papers in the energy forecasting literature focus on point or singlevalued forecasts, the research interest in probabilistic energy...

  17. Comparative Analysis of NOAA REFM and SNB3GEO Tools for the Forecast of the Fluxes of High-Energy Electrons at GEO

    Science.gov (United States)

    Balikhin, M. A.; Rodriguez, J. V.; Boynton, R. J.; Walker, S. N.; Aryan, Homayon; Sibeck, D. G.; Billings, S. A.

    2016-01-01

    Reliable forecasts of relativistic electrons at geostationary orbit (GEO) are important for the mitigation of their hazardous effects on spacecraft at GEO. For a number of years the Space Weather Prediction Center at NOAA has provided advanced online forecasts of the fluence of electrons with energy >2 MeV at GEO using the Relativistic Electron Forecast Model (REFM). The REFM forecasts are based on real-time solar wind speed observations at L1. The high reliability of this forecasting tool serves as a benchmark for the assessment of other forecasting tools. Since 2012 the Sheffield SNB3GEO model has been operating online, providing a 24 h ahead forecast of the same fluxes. In addition to solar wind speed, the SNB3GEO forecasts use solar wind density and interplanetary magnetic field B(sub z) observations at L1. The period of joint operation of both of these forecasts has been used to compare their accuracy. Daily averaged measurements of electron fluxes by GOES 13 have been used to estimate the prediction efficiency of both forecasting tools. To assess the reliability of both models to forecast infrequent events of very high fluxes, the Heidke skill score was employed. The results obtained indicate that SNB3GEO provides a more accurate 1 day ahead forecast when compared to REFM. It is shown that the correction methodology utilized by REFM potentially can improve the SNB3GEO forecast.

  18. Comparative analysis of NOAA REFM and SNB3GEO tools for the forecast of the fluxes of high-energy electrons at GEO

    Science.gov (United States)

    Balikhin, M. A.; Rodriguez, J. V.; Boynton, R. J.; Walker, S. N.; Aryan, H.; Sibeck, D. G.; Billings, S. A.

    2016-01-01

    Reliable forecasts of relativistic electrons at geostationary orbit (GEO) are important for the mitigation of their hazardous effects on spacecraft at GEO. For a number of years the Space Weather Prediction Center at NOAA has provided advanced online forecasts of the fluence of electrons with energy >2 MeV at GEO using the Relativistic Electron Forecast Model (REFM). The REFM forecasts are based on real-time solar wind speed observations at L1. The high reliability of this forecasting tool serves as a benchmark for the assessment of other forecasting tools. Since 2012 the Sheffield SNB3GEO model has been operating online, providing a 24 h ahead forecast of the same fluxes. In addition to solar wind speed, the SNB3GEO forecasts use solar wind density and interplanetary magnetic field Bz observations at L1.The period of joint operation of both of these forecasts has been used to compare their accuracy. Daily averaged measurements of electron fluxes by GOES 13 have been used to estimate the prediction efficiency of both forecasting tools. To assess the reliability of both models to forecast infrequent events of very high fluxes, the Heidke skill score was employed. The results obtained indicate that SNB3GEO provides a more accurate 1 day ahead forecast when compared to REFM. It is shown that the correction methodology utilized by REFM potentially can improve the SNB3GEO forecast.

  19. The new Met Office strategy for seasonal forecasts

    Science.gov (United States)

    Hewson, T. D.

    2012-04-01

    In October 2011 the Met Office began issuing a new-format UK seasonal forecast, called "The 3-month Outlook". Government interest in a UK-relevant product had been heightened by infrastructure issues arising during the severe cold of previous winters. At the same time there was evidence that the Met Office's "GLOSEA4" long range forecasting system exhibited some hindcast skill for the UK, that was comparable to its hindcast skill for the larger (and therefore less useful) 'northern Europe' region. Also, the NAO- and AO- signals prevailing in the previous two winters had been highlighted by the GLOSEA4 model well in advance. This presentation will initially give a brief overview of GLOSEA4, describing key features such as evolving sea-ice, a well-resolved stratosphere, and the perturbation strategy. Skill measures will be shown, along with forecasts for the last 3 winters. The new structure 3-month outlook will then be described and presented. Previously, our seasonal forecasts had been based on a tercile approach. The new format outlook aims to substantially improve upon this by illustrating graphically, and with text, the full range of possible outcomes, and by placing those outcomes in the context of climatology. In one key component the forecast pdfs (probability density functions) are displayed alongside climatological pdfs. To generate the forecast pdf we take the bias-corrected GLOSEA4 output (42 members), and then incorporate, via expert team, all other relevant information. Firstly model forecasts from other centres are examined. Then external 'forcing factors', such as solar, and the state of the land-ocean-ice system, are referenced, assessing how well the models represent their influence, and bringing in statistical relationships where appropriate. The expert team thereby decides upon any changes to the GLOSEA4 data, employing an interactive tool to shift, expand or contract the forecast pdfs accordingly. The full modification process will be illustrated

  20. Forecasting seeing and parameters of long-exposure images by means of ARIMA

    Science.gov (United States)

    Kornilov, Matwey V.

    2016-02-01

    Atmospheric turbulence is the one of the major limiting factors for ground-based astronomical observations. In this paper, the problem of short-term forecasting seeing is discussed. The real data that were obtained by atmospheric optical turbulence (OT) measurements above Mount Shatdzhatmaz in 2007-2013 have been analysed. Linear auto-regressive integrated moving average (ARIMA) models are used for the forecasting. A new procedure for forecasting the image characteristics of direct astronomical observations (central image intensity, full width at half maximum, radius encircling 80 % of the energy) has been proposed. Probability density functions of the forecast of these quantities are 1.5-2 times thinner than the respective unconditional probability density functions. Overall, this study found that the described technique could adequately describe temporal stochastic variations of the OT power.