WorldWideScience

Sample records for important input variables

  1. Statistical identification of effective input variables

    International Nuclear Information System (INIS)

    Vaurio, J.K.

    1982-09-01

    A statistical sensitivity analysis procedure has been developed for ranking the input data of large computer codes in the order of sensitivity-importance. The method is economical for large codes with many input variables, since it uses a relatively small number of computer runs. No prior judgemental elimination of input variables is needed. The sceening method is based on stagewise correlation and extensive regression analysis of output values calculated with selected input value combinations. The regression process deals with multivariate nonlinear functions, and statistical tests are also available for identifying input variables that contribute to threshold effects, i.e., discontinuities in the output variables. A computer code SCREEN has been developed for implementing the screening techniques. The efficiency has been demonstrated by several examples and applied to a fast reactor safety analysis code (Venus-II). However, the methods and the coding are general and not limited to such applications

  2. Importance analysis for models with correlated variables and its sparse grid solution

    International Nuclear Information System (INIS)

    Li, Luyi; Lu, Zhenzhou

    2013-01-01

    For structural models involving correlated input variables, a novel interpretation for variance-based importance measures is proposed based on the contribution of the correlated input variables to the variance of the model output. After the novel interpretation of the variance-based importance measures is compared with the existing ones, two solutions of the variance-based importance measures of the correlated input variables are built on the sparse grid numerical integration (SGI): double-loop nested sparse grid integration (DSGI) method and single loop sparse grid integration (SSGI) method. The DSGI method solves the importance measure by decreasing the dimensionality of the input variables procedurally, while SSGI method performs importance analysis through extending the dimensionality of the inputs. Both of them can make full use of the advantages of the SGI, and are well tailored for different situations. By analyzing the results of several numerical and engineering examples, it is found that the novel proposed interpretation about the importance measures of the correlated input variables is reasonable, and the proposed methods for solving importance measures are efficient and accurate. -- Highlights: •The contribution of correlated variables to the variance of the output is analyzed. •A novel interpretation for variance-based indices of correlated variables is proposed. •Two solutions for variance-based importance measures of correlated variables are built

  3. Statistical screening of input variables in a complex computer code

    International Nuclear Information System (INIS)

    Krieger, T.J.

    1982-01-01

    A method is presented for ''statistical screening'' of input variables in a complex computer code. The object is to determine the ''effective'' or important input variables by estimating the relative magnitudes of their associated sensitivity coefficients. This is accomplished by performing a numerical experiment consisting of a relatively small number of computer runs with the code followed by a statistical analysis of the results. A formula for estimating the sensitivity coefficients is derived. Reference is made to an earlier work in which the method was applied to a complex reactor code with good results

  4. Input-variable sensitivity assessment for sediment transport relations

    Science.gov (United States)

    Fernández, Roberto; Garcia, Marcelo H.

    2017-09-01

    A methodology to assess input-variable sensitivity for sediment transport relations is presented. The Mean Value First Order Second Moment Method (MVFOSM) is applied to two bed load transport equations showing that it may be used to rank all input variables in terms of how their specific variance affects the overall variance of the sediment transport estimation. In sites where data are scarce or nonexistent, the results obtained may be used to (i) determine what variables would have the largest impact when estimating sediment loads in the absence of field observations and (ii) design field campaigns to specifically measure those variables for which a given transport equation is most sensitive; in sites where data are readily available, the results would allow quantifying the effect that the variance associated with each input variable has on the variance of the sediment transport estimates. An application of the method to two transport relations using data from a tropical mountain river in Costa Rica is implemented to exemplify the potential of the method in places where input data are limited. Results are compared against Monte Carlo simulations to assess the reliability of the method and validate its results. For both of the sediment transport relations used in the sensitivity analysis, accurate knowledge of sediment size was found to have more impact on sediment transport predictions than precise knowledge of other input variables such as channel slope and flow discharge.

  5. Using Random Forests to Select Optimal Input Variables for Short-Term Wind Speed Forecasting Models

    Directory of Open Access Journals (Sweden)

    Hui Wang

    2017-10-01

    Full Text Available Achieving relatively high-accuracy short-term wind speed forecasting estimates is a precondition for the construction and grid-connected operation of wind power forecasting systems for wind farms. Currently, most research is focused on the structure of forecasting models and does not consider the selection of input variables, which can have significant impacts on forecasting performance. This paper presents an input variable selection method for wind speed forecasting models. The candidate input variables for various leading periods are selected and random forests (RF is employed to evaluate the importance of all variable as features. The feature subset with the best evaluation performance is selected as the optimal feature set. Then, kernel-based extreme learning machine is constructed to evaluate the performance of input variables selection based on RF. The results of the case study show that by removing the uncorrelated and redundant features, RF effectively extracts the most strongly correlated set of features from the candidate input variables. By finding the optimal feature combination to represent the original information, RF simplifies the structure of the wind speed forecasting model, shortens the training time required, and substantially improves the model’s accuracy and generalization ability, demonstrating that the input variables selected by RF are effective.

  6. A new interpretation and validation of variance based importance measures for models with correlated inputs

    Science.gov (United States)

    Hao, Wenrui; Lu, Zhenzhou; Li, Luyi

    2013-05-01

    In order to explore the contributions by correlated input variables to the variance of the output, a novel interpretation framework of importance measure indices is proposed for a model with correlated inputs, which includes the indices of the total correlated contribution and the total uncorrelated contribution. The proposed indices accurately describe the connotations of the contributions by the correlated input to the variance of output, and they can be viewed as the complement and correction of the interpretation about the contributions by the correlated inputs presented in "Estimation of global sensitivity indices for models with dependent variables, Computer Physics Communications, 183 (2012) 937-946". Both of them contain the independent contribution by an individual input. Taking the general form of quadratic polynomial as an illustration, the total correlated contribution and the independent contribution by an individual input are derived analytically, from which the components and their origins of both contributions of correlated input can be clarified without any ambiguity. In the special case that no square term is included in the quadratic polynomial model, the total correlated contribution by the input can be further decomposed into the variance contribution related to the correlation of the input with other inputs and the independent contribution by the input itself, and the total uncorrelated contribution can be further decomposed into the independent part by interaction between the input and others and the independent part by the input itself. Numerical examples are employed and their results demonstrate that the derived analytical expressions of the variance-based importance measure are correct, and the clarification of the correlated input contribution to model output by the analytical derivation is very important for expanding the theory and solutions of uncorrelated input to those of the correlated one.

  7. IMPORT COMPONENTS AND IMPORT MULTIPLIERS IN INDONESIAN ECONOMY: WORLD INPUT-OUTPUT ANALYSIS

    Directory of Open Access Journals (Sweden)

    Muchdie Muchdie

    2018-03-01

    Full Text Available This paper calculates, presents and discusses on import components and the impact of final demand change on Indonesian imports using Indonesian 36 sector input-output tables of years: 2000, 2005, 2010 and 2014 from World Input-Output Tables. The results showed that firstly, Indonesian import components of input were, on average, more than 20 percent; meaning that input that locally provided were less than 80 percent. Secondly, Indonesian import of input had increased significantly from US$ 36,011 million in 2000 to US$ 151,505 million in 2014. Thirdly, Indonesian imports have been dominated by Sector-3: Manufacture of food products, beverages and tobacco products, Sector-4: Manufacture of textiles, wearing apparel and leather products, Sector-24: Construction, Sector-25: Wholesale and retail trade and repair, and Sector-26: Transportation and post services. Fourthly, by country of origin, Indonesian imports have been dominated by Japan, Korea, the USA, Australia, and China. Imports from Australia, Japan, and the US have been decreased significantly, but import from China has steadily increased. Finally, highest sectoral import multipliers occurred if final demands change in Sector-1: Crop and animal production, forestry, fishing and aquaculture, Sector-2: Mining and quarrying, Sector-23: Water collection; sewerage; waste collection, treatment and disposal activities, and Sector-30: Real estate activities, but there was no significant difference of import multipliers for country origin of import.

  8. Stochastic weather inputs for improved urban water demand forecasting: application of nonlinear input variable selection and machine learning methods

    Science.gov (United States)

    Quilty, J.; Adamowski, J. F.

    2015-12-01

    Urban water supply systems are often stressed during seasonal outdoor water use as water demands related to the climate are variable in nature making it difficult to optimize the operation of the water supply system. Urban water demand forecasts (UWD) failing to include meteorological conditions as inputs to the forecast model may produce poor forecasts as they cannot account for the increase/decrease in demand related to meteorological conditions. Meteorological records stochastically simulated into the future can be used as inputs to data-driven UWD forecasts generally resulting in improved forecast accuracy. This study aims to produce data-driven UWD forecasts for two different Canadian water utilities (Montreal and Victoria) using machine learning methods by first selecting historical UWD and meteorological records derived from a stochastic weather generator using nonlinear input variable selection. The nonlinear input variable selection methods considered in this work are derived from the concept of conditional mutual information, a nonlinear dependency measure based on (multivariate) probability density functions and accounts for relevancy, conditional relevancy, and redundancy from a potential set of input variables. The results of our study indicate that stochastic weather inputs can improve UWD forecast accuracy for the two sites considered in this work. Nonlinear input variable selection is suggested as a means to identify which meteorological conditions should be utilized in the forecast.

  9. Input variable selection for interpolating high-resolution climate ...

    African Journals Online (AJOL)

    Although the primary input data of climate interpolations are usually meteorological data, other related (independent) variables are frequently incorporated in the interpolation process. One such variable is elevation, which is known to have a strong influence on climate. This research investigates the potential of 4 additional ...

  10. The Importance of Input and Interaction in SLA

    Institute of Scientific and Technical Information of China (English)

    党春花

    2009-01-01

    As is known to us, input and interaction play the crucial roles in second language acquisition (SLA). Different linguistic schools have different explanations to input and interaction Behaviorist theories hold a view that input is composed of stimuli and response, putting more emphasis on the importance of input, while mentalist theories find input is a necessary condition to SLA, not a sufficient condition. At present, social interaction theories, which is one type of cognitive linguistics, suggests that besides input, interaction is also essential to language acquisition. Then, this essay will discuss how input and interaction result in SLA.

  11. Speaker Input Variability Does Not Explain Why Larger Populations Have Simpler Languages.

    Science.gov (United States)

    Atkinson, Mark; Kirby, Simon; Smith, Kenny

    2015-01-01

    A learner's linguistic input is more variable if it comes from a greater number of speakers. Higher speaker input variability has been shown to facilitate the acquisition of phonemic boundaries, since data drawn from multiple speakers provides more information about the distribution of phonemes in a speech community. It has also been proposed that speaker input variability may have a systematic influence on individual-level learning of morphology, which can in turn influence the group-level characteristics of a language. Languages spoken by larger groups of people have less complex morphology than those spoken in smaller communities. While a mechanism by which the number of speakers could have such an effect is yet to be convincingly identified, differences in speaker input variability, which is thought to be larger in larger groups, may provide an explanation. By hindering the acquisition, and hence faithful cross-generational transfer, of complex morphology, higher speaker input variability may result in structural simplification. We assess this claim in two experiments which investigate the effect of such variability on language learning, considering its influence on a learner's ability to segment a continuous speech stream and acquire a morphologically complex miniature language. We ultimately find no evidence to support the proposal that speaker input variability influences language learning and so cannot support the hypothesis that it explains how population size determines the structural properties of language.

  12. Bottom-up and Top-down Input Augment the Variability of Cortical Neurons

    Science.gov (United States)

    Nassi, Jonathan J.; Kreiman, Gabriel; Born, Richard T.

    2016-01-01

    SUMMARY Neurons in the cerebral cortex respond inconsistently to a repeated sensory stimulus, yet they underlie our stable sensory experiences. Although the nature of this variability is unknown, its ubiquity has encouraged the general view that each cell produces random spike patterns that noisily represent its response rate. In contrast, here we show that reversibly inactivating distant sources of either bottom-up or top-down input to cortical visual areas in the alert primate reduces both the spike train irregularity and the trial-to-trial variability of single neurons. A simple model in which a fraction of the pre-synaptic input is silenced can reproduce this reduction in variability, provided that there exist temporal correlations primarily within, but not between, excitatory and inhibitory input pools. A large component of the variability of cortical neurons may therefore arise from synchronous input produced by signals arriving from multiple sources. PMID:27427459

  13. Input variable selection for data-driven models of Coriolis flowmeters for two-phase flow measurement

    International Nuclear Information System (INIS)

    Wang, Lijuan; Yan, Yong; Wang, Xue; Wang, Tao

    2017-01-01

    Input variable selection is an essential step in the development of data-driven models for environmental, biological and industrial applications. Through input variable selection to eliminate the irrelevant or redundant variables, a suitable subset of variables is identified as the input of a model. Meanwhile, through input variable selection the complexity of the model structure is simplified and the computational efficiency is improved. This paper describes the procedures of the input variable selection for the data-driven models for the measurement of liquid mass flowrate and gas volume fraction under two-phase flow conditions using Coriolis flowmeters. Three advanced input variable selection methods, including partial mutual information (PMI), genetic algorithm-artificial neural network (GA-ANN) and tree-based iterative input selection (IIS) are applied in this study. Typical data-driven models incorporating support vector machine (SVM) are established individually based on the input candidates resulting from the selection methods. The validity of the selection outcomes is assessed through an output performance comparison of the SVM based data-driven models and sensitivity analysis. The validation and analysis results suggest that the input variables selected from the PMI algorithm provide more effective information for the models to measure liquid mass flowrate while the IIS algorithm provides a fewer but more effective variables for the models to predict gas volume fraction. (paper)

  14. Partial Granger causality--eliminating exogenous inputs and latent variables.

    Science.gov (United States)

    Guo, Shuixia; Seth, Anil K; Kendrick, Keith M; Zhou, Cong; Feng, Jianfeng

    2008-07-15

    Attempts to identify causal interactions in multivariable biological time series (e.g., gene data, protein data, physiological data) can be undermined by the confounding influence of environmental (exogenous) inputs. Compounding this problem, we are commonly only able to record a subset of all related variables in a system. These recorded variables are likely to be influenced by unrecorded (latent) variables. To address this problem, we introduce a novel variant of a widely used statistical measure of causality--Granger causality--that is inspired by the definition of partial correlation. Our 'partial Granger causality' measure is extensively tested with toy models, both linear and nonlinear, and is applied to experimental data: in vivo multielectrode array (MEA) local field potentials (LFPs) recorded from the inferotemporal cortex of sheep. Our results demonstrate that partial Granger causality can reveal the underlying interactions among elements in a network in the presence of exogenous inputs and latent variables in many cases where the existing conditional Granger causality fails.

  15. Analysis of input variables of an artificial neural network using bivariate correlation and canonical correlation

    Energy Technology Data Exchange (ETDEWEB)

    Costa, Valter Magalhaes; Pereira, Iraci Martinez, E-mail: valter.costa@usp.b [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

    2011-07-01

    The monitoring of variables and diagnosis of sensor fault in nuclear power plants or processes industries is very important because a previous diagnosis allows the correction of the fault and, like this, to prevent the production stopped, improving operator's security and it's not provoking economics losses. The objective of this work is to build a set, using bivariate correlation and canonical correlation, which will be the set of input variables of an artificial neural network to monitor the greater number of variables. This methodology was applied to the IEA-R1 Research Reactor at IPEN. Initially, for the input set of neural network we selected the variables: nuclear power, primary circuit flow rate, control/safety rod position and difference in pressure in the core of the reactor, because almost whole of monitoring variables have relation with the variables early described or its effect can be result of the interaction of two or more. The nuclear power is related to the increasing and decreasing of temperatures as well as the amount radiation due fission of the uranium; the rods are controls of power and influence in the amount of radiation and increasing and decreasing of temperatures; the primary circuit flow rate has the function of energy transport by removing the nucleus heat. An artificial neural network was trained and the results were satisfactory since the IEA-R1 Data Acquisition System reactor monitors 64 variables and, with a set of 9 input variables resulting from the correlation analysis, it was possible to monitor 51 variables. (author)

  16. Analysis of input variables of an artificial neural network using bivariate correlation and canonical correlation

    International Nuclear Information System (INIS)

    Costa, Valter Magalhaes; Pereira, Iraci Martinez

    2011-01-01

    The monitoring of variables and diagnosis of sensor fault in nuclear power plants or processes industries is very important because a previous diagnosis allows the correction of the fault and, like this, to prevent the production stopped, improving operator's security and it's not provoking economics losses. The objective of this work is to build a set, using bivariate correlation and canonical correlation, which will be the set of input variables of an artificial neural network to monitor the greater number of variables. This methodology was applied to the IEA-R1 Research Reactor at IPEN. Initially, for the input set of neural network we selected the variables: nuclear power, primary circuit flow rate, control/safety rod position and difference in pressure in the core of the reactor, because almost whole of monitoring variables have relation with the variables early described or its effect can be result of the interaction of two or more. The nuclear power is related to the increasing and decreasing of temperatures as well as the amount radiation due fission of the uranium; the rods are controls of power and influence in the amount of radiation and increasing and decreasing of temperatures; the primary circuit flow rate has the function of energy transport by removing the nucleus heat. An artificial neural network was trained and the results were satisfactory since the IEA-R1 Data Acquisition System reactor monitors 64 variables and, with a set of 9 input variables resulting from the correlation analysis, it was possible to monitor 51 variables. (author)

  17. Input Variability Facilitates Unguided Subcategory Learning in Adults

    Science.gov (United States)

    Eidsvåg, Sunniva Sørhus; Austad, Margit; Plante, Elena; Asbjørnsen, Arve E.

    2015-01-01

    Purpose: This experiment investigated whether input variability would affect initial learning of noun gender subcategories in an unfamiliar, natural language (Russian), as it is known to assist learning of other grammatical forms. Method: Forty adults (20 men, 20 women) were familiarized with examples of masculine and feminine Russian words. Half…

  18. Attributing uncertainty in streamflow simulations due to variable inputs via the Quantile Flow Deviation metric

    Science.gov (United States)

    Shoaib, Syed Abu; Marshall, Lucy; Sharma, Ashish

    2018-06-01

    Every model to characterise a real world process is affected by uncertainty. Selecting a suitable model is a vital aspect of engineering planning and design. Observation or input errors make the prediction of modelled responses more uncertain. By way of a recently developed attribution metric, this study is aimed at developing a method for analysing variability in model inputs together with model structure variability to quantify their relative contributions in typical hydrological modelling applications. The Quantile Flow Deviation (QFD) metric is used to assess these alternate sources of uncertainty. The Australian Water Availability Project (AWAP) precipitation data for four different Australian catchments is used to analyse the impact of spatial rainfall variability on simulated streamflow variability via the QFD. The QFD metric attributes the variability in flow ensembles to uncertainty associated with the selection of a model structure and input time series. For the case study catchments, the relative contribution of input uncertainty due to rainfall is higher than that due to potential evapotranspiration, and overall input uncertainty is significant compared to model structure and parameter uncertainty. Overall, this study investigates the propagation of input uncertainty in a daily streamflow modelling scenario and demonstrates how input errors manifest across different streamflow magnitudes.

  19. Uncertainty importance measure for models with correlated normal variables

    International Nuclear Information System (INIS)

    Hao, Wenrui; Lu, Zhenzhou; Wei, Pengfei

    2013-01-01

    In order to explore the contributions by correlated input variables to the variance of the model output, the contribution decomposition of the correlated input variables based on Mara's definition is investigated in detail. By taking the quadratic polynomial output without cross term as an illustration, the solution of the contribution decomposition is derived analytically using the statistical inference theory. After the correction of the analytical solution is validated by the numerical examples, they are employed to two engineering examples to show their wide application. The derived analytical solutions can directly be used to recognize the contributions by the correlated input variables in case of the quadratic or linear polynomial output without cross term, and the analytical inference method can be extended to the case of higher order polynomial output. Additionally, the origins of the interaction contribution of the correlated inputs are analyzed, and the comparisons of the existing contribution indices are completed, on which the engineer can select the suitable indices to know the necessary information. At last, the degeneration of the correlated inputs to the uncorrelated ones and some computational issues are discussed in concept

  20. Study of input variables in group method of data handling methodology

    International Nuclear Information System (INIS)

    Pereira, Iraci Martinez; Bueno, Elaine Inacio

    2013-01-01

    The Group Method of Data Handling - GMDH is a combinatorial multi-layer algorithm in which a network of layers and nodes is generated using a number of inputs from the data stream being evaluated. The GMDH network topology has been traditionally determined using a layer by layer pruning process based on a pre-selected criterion of what constitutes the best nodes at each level. The traditional GMDH method is based on an underlying assumption that the data can be modeled by using an approximation of the Volterra Series or Kolmorgorov-Gabor polynomial. A Monitoring and Diagnosis System was developed based on GMDH and ANN methodologies, and applied to the IPEN research Reactor IEA-1. The system performs the monitoring by comparing the GMDH and ANN calculated values with measured ones. As the GMDH is a self-organizing methodology, the input variables choice is made automatically. On the other hand, the results of ANN methodology are strongly dependent on which variables are used as neural network input. (author)

  1. Development of a localized probabilistic sensitivity method to determine random variable regional importance

    International Nuclear Information System (INIS)

    Millwater, Harry; Singh, Gulshan; Cortina, Miguel

    2012-01-01

    There are many methods to identify the important variable out of a set of random variables, i.e., “inter-variable” importance; however, to date there are no comparable methods to identify the “region” of importance within a random variable, i.e., “intra-variable” importance. Knowledge of the critical region of an input random variable (tail, near-tail, and central region) can provide valuable information towards characterizing, understanding, and improving a model through additional modeling or testing. As a result, an intra-variable probabilistic sensitivity method was developed and demonstrated for independent random variables that computes the partial derivative of a probabilistic response with respect to a localized perturbation in the CDF values of each random variable. These sensitivities are then normalized in absolute value with respect to the largest sensitivity within a distribution to indicate the region of importance. The methodology is implemented using the Score Function kernel-based method such that existing samples can be used to compute sensitivities for negligible cost. Numerical examples demonstrate the accuracy of the method through comparisons with finite difference and numerical integration quadrature estimates. - Highlights: ► Probabilistic sensitivity methodology. ► Determines the “region” of importance within random variables such as left tail, near tail, center, right tail, etc. ► Uses the Score Function approach to reuse the samples, hence, negligible cost. ► No restrictions on the random variable types or limit states.

  2. Appreciate the Appreciation: Imported Inputs and Concern Over Dutch Disease

    Directory of Open Access Journals (Sweden)

    Wardah Naim

    2013-03-01

    Full Text Available If anything is to blame for a higher dollar having negative effects on the Central Canadian manufacturing sector, you are not likely to find it in any “Dutch Disease” supposedly caused by Alberta’s oil sands. Contrary to popular belief, the higher value of the Canadian dollar may even help Central Canadian manufacturers grow stronger, cut costs, and create jobs. The idea that a booming, commodity-driven dollar is hurting Canadian goods exports, afflicting the country with so-called Dutch Disease, may be popular among certain politicians, including federal Opposition leader Thomas Mulcair and former Premier of Ontario Dalton McGuinty, but is not supported by the facts. It turns out that the simple economic theory these politicians have in mind is incomplete. A more thorough, data-driven look at the nation’s manufacturing sector reveals that Canadian businesses rely very heavily on imported materials and equipment as inputs in the manufacturing process. Canadian industry overall has one of the highest import ratios for such intermediate goods in the OECD, roughly twice as high as that of the U.S., the European Union and Japan. Compared to all other sectors, manufacturers are the heaviest users of imported materials and equipment, with more than 40 per cent of their inputs coming from other countries. A higher dollar may make it more expensive for foreign buyers to purchase Canadian manufactured goods, but that effect appears to be more than offset by the savings that Canadian producers enjoy with a higher dollar that makes possible cheaper imported-inputs and lower cost of production, which have a lowering effect on prices. The net result is that Canadian manufacturers actually get more benefit from a higher dollar, and the regions that get the biggest boost from it are the Central Canadian provinces of Ontario and Quebec. Policy-makers looking to aid the Canadian economy as a whole, and the manufacturing sector in particular, should stop

  3. The importance of input interactions in the uncertainty and sensitivity analysis of nuclear fuel behavior

    Energy Technology Data Exchange (ETDEWEB)

    Ikonen, T., E-mail: timo.ikonen@vtt.fi; Tulkki, V.

    2014-08-15

    Highlights: • Uncertainty and sensitivity analysis of modeled nuclear fuel behavior is performed. • Burnup dependency of the uncertainties and sensitivities is characterized. • Input interactions significantly increase output uncertainties for irradiated fuel. • Identification of uncertainty sources is greatly improved with higher order methods. • Results stress the importance of using methods that take interactions into account. - Abstract: The propagation of uncertainties in a PWR fuel rod under steady-state irradiation is analyzed by computational means. A hypothetical steady-state scenario of the Three Mile Island 1 reactor fuel rod is modeled with the fuel performance FRAPCON, using realistic input uncertainties for the fabrication and model parameters, boundary conditions and material properties. The uncertainty and sensitivity analysis is performed by extensive Monte Carlo sampling of the inputs’ probability distribution and by applying correlation coefficient and Sobol’ variance decomposition analyses. The latter includes evaluation of the second order and total effect sensitivity indices, allowing the study of interactions between input variables. The results show that the interactions play a large role in the propagation of uncertainties, and first order methods such as the correlation coefficient analyses are in general insufficient for sensitivity analysis of the fuel rod. Significant improvement over the first order methods can be achieved by using higher order methods. The results also show that both the magnitude of the uncertainties and their propagation depends not only on the output in question, but also on burnup. The latter is due to onset of new phenomena (such as the fission gas release) and the gradual closure of the pellet-cladding gap with increasing burnup. Increasing burnup also affects the importance of input interactions. Interaction effects are typically highest in the moderate burnup (of the order of 10–40 MWd

  4. Imported Input Varieties and Product Innovation : Evidence from Five Developing Countries

    NARCIS (Netherlands)

    Bos, Marijke; Vannoorenberghe, Gonzague

    We examine how access to imported intermediate inputs affects firm-level product innovation in five developing counties. We combine trade data with survey data on innovation and develop a method to determine whether new inputs were essential for the product innovation. We find evidence that the

  5. Construction of an input sensitivity variable CAMAC module for measuring DC voltage

    International Nuclear Information System (INIS)

    Noda, Nobuaki.

    1979-03-01

    In on-line experimental data processing systems, the collection of DC voltage data is frequently required. In plasma confinement experiments, for example, the range of input voltage is very wide from over 1 kV applied to photomultiplier tubes to 10 mV full scale of the controller output for ionization vacuum gauges. A DC voltmeter CAMAC module with variable input range, convenient for plasma experiments and inexpensive, has been constructed for trial. The number of input channels is 16, and the input range is changeable in six steps from +-10 mV to +-200 V; these are all set by commands from a computer. The module is actually used for the on-line data processing system for JIPP T-2 experiment. The ideas behind its development, and the functions, features and usage of the module are described in this report. (J.P.N.)

  6. Wide Input Range Power Converters Using a Variable Turns Ratio Transformer

    DEFF Research Database (Denmark)

    Ouyang, Ziwei; Andersen, Michael A. E.

    2016-01-01

    A new integrated transformer with variable turns ratio is proposed to enable dc-dc converters operating over a wide input voltage range. The integrated transformer employs a new geometry of magnetic core with “four legs”, two primary windings with orthogonal arrangement, and “8” shape connection...... of diagonal secondary windings, in order to make the transformer turns ratio adjustable by controlling the phase between the two current excitations subjected to the two primary windings. Full-bridge boost dc-dc converter is employed with the proposed transformer to demonstrate the feasibility of the variable...

  7. Analysis of input variables of an artificial neural network using bivariate correlation and canonical correlation

    International Nuclear Information System (INIS)

    Costa, Valter Magalhaes

    2011-01-01

    The monitoring of variables and diagnosis of sensor fault in nuclear power plants or processes industries is very important because an early diagnosis allows the correction of the fault and, like this, do not cause the production interruption, improving operator's security and it's not provoking economics losses. The objective of this work is, in the whole of all variables monitor of a nuclear power plant, to build a set, not necessary minimum, which will be the set of input variables of an artificial neural network and, like way, to monitor the biggest number of variables. This methodology was applied to the IEA-R1 Research Reactor at IPEN. For this, the variables Power, Rate of flow of primary circuit, Rod of control/security and Difference in pressure in the core of the reactor ( Δ P) was grouped, because, for hypothesis, almost whole of monitoring variables have relation with the variables early described or its effect can be result of the interaction of two or more. The Power is related to the increasing and decreasing of temperatures as well as the amount radiation due fission of the uranium; the Rods are controls of power and influence in the amount of radiation and increasing and decreasing of temperatures and the Rate of flow of primary circuit has function of the transport of energy by removing of heat of the nucleus Like this, labeling B= {Power, Rate of flow of Primary Circuit, Rod of Control/Security and Δ P} was computed the correlation between B and all another variables monitoring (coefficient of multiple correlation), that is, by the computer of the multiple correlation, that is tool of Theory of Canonical Correlations, was possible to computer how much the set B can predict each variable. Due the impossibility of a satisfactory approximation by B in the prediction of some variables, it was included one or more variables that have high correlation with this variable to improve the quality of prediction. In this work an artificial neural network

  8. PCC/SRC, PCC and SRC Calculation from Multivariate Input for Sensitivity Analysis

    International Nuclear Information System (INIS)

    Iman, R.L.; Shortencarier, M.J.; Johnson, J.D.

    1995-01-01

    1 - Description of program or function: PCC/SRC is designed for use in conjunction with sensitivity analyses of complex computer models. PCC/SRC calculates the partial correlation coefficients (PCC) and the standardized regression coefficients (SRC) from the multivariate input to, and output from, a computer model. 2 - Method of solution: PCC/SRC calculates the coefficients on either the original observations or on the ranks of the original observations. These coefficients provide alternative measures of the relative contribution (importance) of each of the various input variables to the observed variations in output. Relationships between the coefficients and differences in their interpretations are identified. If the computer model output has an associated time or spatial history, PCC/SRC will generate a graph of the coefficients over time or space for each input-variable, output- variable combination of interest, indicating the importance of each input value over time or space. 3 - Restrictions on the complexity of the problem - Maxima of: 100 observations, 100 different time steps or intervals between successive dependent variable readings, 50 independent variables (model input), 20 dependent variables (model output). 10 ordered triples specifying intervals between dependent variable readings

  9. Wood phenology, not carbon input, controls the interannual variability of wood growth in a temperate oak forest.

    Science.gov (United States)

    Delpierre, Nicolas; Berveiller, Daniel; Granda, Elena; Dufrêne, Eric

    2016-04-01

    Although the analysis of flux data has increased our understanding of the interannual variability of carbon inputs into forest ecosystems, we still know little about the determinants of wood growth. Here, we aimed to identify which drivers control the interannual variability of wood growth in a mesic temperate deciduous forest. We analysed a 9-yr time series of carbon fluxes and aboveground wood growth (AWG), reconstructed at a weekly time-scale through the combination of dendrometer and wood density data. Carbon inputs and AWG anomalies appeared to be uncorrelated from the seasonal to interannual scales. More than 90% of the interannual variability of AWG was explained by a combination of the growth intensity during a first 'critical period' of the wood growing season, occurring close to the seasonal maximum, and the timing of the first summer growth halt. Both atmospheric and soil water stress exerted a strong control on the interannual variability of AWG at the study site, despite its mesic conditions, whilst not affecting carbon inputs. Carbon sink activity, not carbon inputs, determined the interannual variations in wood growth at the study site. Our results provide a functional understanding of the dependence of radial growth on precipitation observed in dendrological studies. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

  10. Graphical user interface for input output characterization of single variable and multivariable highly nonlinear systems

    Directory of Open Access Journals (Sweden)

    Shahrukh Adnan Khan M. D.

    2017-01-01

    Full Text Available This paper presents a Graphical User Interface (GUI software utility for the input/output characterization of single variable and multivariable nonlinear systems by obtaining the sinusoidal input describing function (SIDF of the plant. The software utility is developed on MATLAB R2011a environment. The developed GUI holds no restriction on the nonlinearity type, arrangement and system order; provided that output(s of the system is obtainable either though simulation or experiments. An insight to the GUI and its features are presented in this paper and example problems from both single variable and multivariable cases are demonstrated. The formulation of input/output behavior of the system is discussed and the nucleus of the MATLAB command underlying the user interface has been outlined. Some of the industries that would benefit from this software utility includes but not limited to aerospace, defense technology, robotics and automotive.

  11. Not All Children Agree: Acquisition of Agreement when the Input Is Variable

    Science.gov (United States)

    Miller, Karen

    2012-01-01

    In this paper we investigate the effect of variable input on the acquisition of grammar. More specifically, we examine the acquisition of the third person singular marker -s on the auxiliary "do" in comprehension and production in two groups of children who are exposed to similar varieties of English but that differ with respect to adult…

  12. Language input and acquisition in a Mayan village: how important is directed speech?

    Science.gov (United States)

    Shneidman, Laura A; Goldin-Meadow, Susan

    2012-09-01

    Theories of language acquisition have highlighted the importance of adult speakers as active participants in children's language learning. However, in many communities children are reported to be directly engaged by their caregivers only rarely (Lieven, 1994). This observation raises the possibility that these children learn language from observing, rather than participating in, communicative exchanges. In this paper, we quantify naturally occurring language input in one community where directed interaction with children has been reported to be rare (Yucatec Mayan). We compare this input to the input heard by children growing up in large families in the United States, and we consider how directed and overheard input relate to Mayan children's later vocabulary. In Study 1, we demonstrate that 1-year-old Mayan children do indeed hear a smaller proportion of total input in directed speech than children from the US. In Study 2, we show that for Mayan (but not US) children, there are great increases in the proportion of directed input that children receive between 13 and 35 months. In Study 3, we explore the validity of using videotaped data in a Mayan village. In Study 4, we demonstrate that word types directed to Mayan children from adults at 24 months (but not word types overheard by children or word types directed from other children) predict later vocabulary. These findings suggest that adult talk directed to children is important for early word learning, even in communities where much of children's early language input comes from overheard speech. © 2012 Blackwell Publishing Ltd.

  13. Continuous-variable quantum cloning of coherent states with phase-conjugate input modes using linear optics

    International Nuclear Information System (INIS)

    Chen, Haixia; Zhang, Jing

    2007-01-01

    We propose a scheme for continuous-variable quantum cloning of coherent states with phase-conjugate input modes using linear optics. The quantum cloning machine yields M identical optimal clones from N replicas of a coherent state and N replicas of its phase conjugate. This scheme can be straightforwardly implemented with the setups accessible at present since its optical implementation only employs simple linear optical elements and homodyne detection. Compared with the original scheme for continuous-variable quantum cloning with phase-conjugate input modes proposed by Cerf and Iblisdir [Phys. Rev. Lett. 87, 247903 (2001)], which utilized a nondegenerate optical parametric amplifier, our scheme loses the output of phase-conjugate clones and is regarded as irreversible quantum cloning

  14. Effects of input uncertainty on cross-scale crop modeling

    Science.gov (United States)

    Waha, Katharina; Huth, Neil; Carberry, Peter

    2014-05-01

    The quality of data on climate, soils and agricultural management in the tropics is in general low or data is scarce leading to uncertainty in process-based modeling of cropping systems. Process-based crop models are common tools for simulating crop yields and crop production in climate change impact studies, studies on mitigation and adaptation options or food security studies. Crop modelers are concerned about input data accuracy as this, together with an adequate representation of plant physiology processes and choice of model parameters, are the key factors for a reliable simulation. For example, assuming an error in measurements of air temperature, radiation and precipitation of ± 0.2°C, ± 2 % and ± 3 % respectively, Fodor & Kovacs (2005) estimate that this translates into an uncertainty of 5-7 % in yield and biomass simulations. In our study we seek to answer the following questions: (1) are there important uncertainties in the spatial variability of simulated crop yields on the grid-cell level displayed on maps, (2) are there important uncertainties in the temporal variability of simulated crop yields on the aggregated, national level displayed in time-series, and (3) how does the accuracy of different soil, climate and management information influence the simulated crop yields in two crop models designed for use at different spatial scales? The study will help to determine whether more detailed information improves the simulations and to advise model users on the uncertainty related to input data. We analyse the performance of the point-scale crop model APSIM (Keating et al., 2003) and the global scale crop model LPJmL (Bondeau et al., 2007) with different climate information (monthly and daily) and soil conditions (global soil map and African soil map) under different agricultural management (uniform and variable sowing dates) for the low-input maize-growing areas in Burkina Faso/West Africa. We test the models' response to different levels of input

  15. Analytic uncertainty and sensitivity analysis of models with input correlations

    Science.gov (United States)

    Zhu, Yueying; Wang, Qiuping A.; Li, Wei; Cai, Xu

    2018-03-01

    Probabilistic uncertainty analysis is a common means of evaluating mathematical models. In mathematical modeling, the uncertainty in input variables is specified through distribution laws. Its contribution to the uncertainty in model response is usually analyzed by assuming that input variables are independent of each other. However, correlated parameters are often happened in practical applications. In the present paper, an analytic method is built for the uncertainty and sensitivity analysis of models in the presence of input correlations. With the method, it is straightforward to identify the importance of the independence and correlations of input variables in determining the model response. This allows one to decide whether or not the input correlations should be considered in practice. Numerical examples suggest the effectiveness and validation of our analytic method in the analysis of general models. A practical application of the method is also proposed to the uncertainty and sensitivity analysis of a deterministic HIV model.

  16. Urban vs. Rural CLIL: An Analysis of Input-Related Variables, Motivation and Language Attainment

    Science.gov (United States)

    Alejo, Rafael; Piquer-Píriz, Ana

    2016-01-01

    The present article carries out an in-depth analysis of the differences in motivation, input-related variables and linguistic attainment of the students at two content and language integrated learning (CLIL) schools operating within the same institutional and educational context, the Spanish region of Extremadura, and differing only in terms of…

  17. 'Quantization' of stochastic variables: description and effects on the input noise sources in a BWR

    International Nuclear Information System (INIS)

    Matthey, M.

    1979-01-01

    A set of macrostochastic and discrete variables, with Markovian properties, is used to characterize the state of a BWR, whose input noise sources are of interest. The ratio between the auto-power spectral density (APSD) of the neutron noise fluctuations and the square modulus of the transfer function (SMTF) defines 'the total input noise source' (TINS), the components of which are the different noise source corresponding to the relevant variables. A white contribution to TINS arises from the birth and death processes of neutrons in the reactor and corresponds to a 'shot noise' (SN). Non-white contributions arise from fluctuations of the neutron cross-sections caused by fuel temperature and steam content variations. These terms called 'Flicker noises' (FN) are characterized by cut-off frequencies related to time constants of reactivity feedback effects. The respective magnitudes of the shot and flicker noises depend not only on the frequency, the feedback reactivity coefficients or the power of the reactor, but also on the 'quantization' of the continuous variables introduced such as fuel temperature and steam content. The effects of this last 'quantization' on the shapes of the noise sources and their sum are presented in this paper. (author)

  18. Statistical learning from nonrecurrent experience with discrete input variables and recursive-error-minimization equations

    Science.gov (United States)

    Carter, Jeffrey R.; Simon, Wayne E.

    1990-08-01

    Neural networks are trained using Recursive Error Minimization (REM) equations to perform statistical classification. Using REM equations with continuous input variables reduces the required number of training experiences by factors of one to two orders of magnitude over standard back propagation. Replacing the continuous input variables with discrete binary representations reduces the number of connections by a factor proportional to the number of variables reducing the required number of experiences by another order of magnitude. Undesirable effects of using recurrent experience to train neural networks for statistical classification problems are demonstrated and nonrecurrent experience used to avoid these undesirable effects. 1. THE 1-41 PROBLEM The statistical classification problem which we address is is that of assigning points in ddimensional space to one of two classes. The first class has a covariance matrix of I (the identity matrix) the covariance matrix of the second class is 41. For this reason the problem is known as the 1-41 problem. Both classes have equal probability of occurrence and samples from both classes may appear anywhere throughout the ddimensional space. Most samples near the origin of the coordinate system will be from the first class while most samples away from the origin will be from the second class. Since the two classes completely overlap it is impossible to have a classifier with zero error. The minimum possible error is known as the Bayes error and

  19. Flow variability and hillslope hydrology

    Energy Technology Data Exchange (ETDEWEB)

    Huff, D D; O' Neill, R V; Emanuel, W R; Elwood, J W; Newbold, J D

    1982-01-01

    Examination of spatial variability of streamflow in headwater areas can provide important insight about factors that influence hillslope hydrology. Detailed observations of variations in stream channel input, based on a tracer experiment, indicate that topography alone cannot explain flow variability. However, determination of changes in channel input on a small spatial scale can provide valuable clues to factors, such as structural geology that control subsurface flows.

  20. An input feature selection method applied to fuzzy neural networks for signal esitmation

    International Nuclear Information System (INIS)

    Na, Man Gyun; Sim, Young Rok

    2001-01-01

    It is well known that the performance of a fuzzy neural networks strongly depends on the input features selected for its training. In its applications to sensor signal estimation, there are a large number of input variables related with an output. As the number of input variables increases, the training time of fuzzy neural networks required increases exponentially. Thus, it is essential to reduce the number of inputs to a fuzzy neural networks and to select the optimum number of mutually independent inputs that are able to clearly define the input-output mapping. In this work, principal component analysis (PAC), genetic algorithms (GA) and probability theory are combined to select new important input features. A proposed feature selection method is applied to the signal estimation of the steam generator water level, the hot-leg flowrate, the pressurizer water level and the pressurizer pressure sensors in pressurized water reactors and compared with other input feature selection methods

  1. Impact of Formal Financial Market Participation on Farm Size and Expenditure on Variable Farm Inputs: The Case of Maize Farmers in Ghana

    OpenAIRE

    Awunyo-Vitor, Dadson; Al-Hassan, Ramatu M.; Sarpong, Daniel B.

    2014-01-01

    The study examined maize farmers’ participation in the formal financial market and its impact on farm size and expenditure on variable farm inputs. A multistage sampling method was used in selecting 595 maize farmers from the seven districts in Ashanti and Brong Ahafo Regions of Ghana. A structured questionnaire and interview schedule were used to elicit information from the respondents. The impact of formal financial market participation on farm size and expenditure on variable inputs was es...

  2. Physical-mathematical model for cybernetic description of the human organs with trace element concentrations as input variables

    International Nuclear Information System (INIS)

    Mihai, Maria; Popescu, I.V.

    2003-01-01

    In this paper we report a physical-mathematical model for studying the organs and humans fluids by cybernetic principle. The input variables represent the trace elements which are determined by atomic and nuclear methods of elemental analysis. We have determined the health limits between which the organs might function. (authors)

  3. The relative importance of oceanic nutrient inputs for Bass Harbor Marsh Estuary at Acadia National Park, Maine

    Science.gov (United States)

    Huntington, Thomas G.; Culbertson, Charles W.; Fuller, Christopher; Glibert, Patricia; Sturtevant, Luke

    2014-01-01

    years. Oceanic inputs of nitrate and ammonium were an important source of inorganic nitrogen to the estuary in both years. In both years, the total seasonal inputs of ammonium to the estuary in flood tides were much larger than the inputs from watershed runoff or direct precipitation. In 2011, the total seasonal input of nitrate from flood tides to the estuary was more than twice as large the inputs from watershed runoff and precipitation, but in 2012, the inputs from flood tides were only marginally larger than the inputs from watershed runoff and precipitation. Turbidity was measured intermittently in 2012, and the pattern that emerged from the measurements indicated that the estuary was a source of particulate matter to the ocean rather than the ocean being a source to the estuary. From the nutrient budgets determined for the estuary it is evident that oceanic sources of nitrate and ammonium are an important part of the supply of nutrients that are contributing to the growth of macroalgae in the estuary. The relative importance of these oceanic nutrients compared with sources within the watershed typically increases as the summer progresses and runoff decreases. It is likely that rising sea levels, estimated by the National Oceanic and Atmospheric Administration to be 11 centimeters from 1950 through 2006 in nearby Bar Harbor, have resulted in an increase in oceanic inputs (tidal volume and nutrients derived from oceanic sources).

  4. Quantifying input uncertainty in an assemble-to-order system simulation with correlated input variables of mixed types

    NARCIS (Netherlands)

    Akçay, A.E.; Biller, B.

    2014-01-01

    We consider an assemble-to-order production system where the product demands and the time since the last customer arrival are not independent. The simulation of this system requires a multivariate input model that generates random input vectors with correlated discrete and continuous components. In

  5. Harmonize input selection for sediment transport prediction

    Science.gov (United States)

    Afan, Haitham Abdulmohsin; Keshtegar, Behrooz; Mohtar, Wan Hanna Melini Wan; El-Shafie, Ahmed

    2017-09-01

    In this paper, three modeling approaches using a Neural Network (NN), Response Surface Method (RSM) and response surface method basis Global Harmony Search (GHS) are applied to predict the daily time series suspended sediment load. Generally, the input variables for forecasting the suspended sediment load are manually selected based on the maximum correlations of input variables in the modeling approaches based on NN and RSM. The RSM is improved to select the input variables by using the errors terms of training data based on the GHS, namely as response surface method and global harmony search (RSM-GHS) modeling method. The second-order polynomial function with cross terms is applied to calibrate the time series suspended sediment load with three, four and five input variables in the proposed RSM-GHS. The linear, square and cross corrections of twenty input variables of antecedent values of suspended sediment load and water discharge are investigated to achieve the best predictions of the RSM based on the GHS method. The performances of the NN, RSM and proposed RSM-GHS including both accuracy and simplicity are compared through several comparative predicted and error statistics. The results illustrated that the proposed RSM-GHS is as uncomplicated as the RSM but performed better, where fewer errors and better correlation was observed (R = 0.95, MAE = 18.09 (ton/day), RMSE = 25.16 (ton/day)) compared to the ANN (R = 0.91, MAE = 20.17 (ton/day), RMSE = 33.09 (ton/day)) and RSM (R = 0.91, MAE = 20.06 (ton/day), RMSE = 31.92 (ton/day)) for all types of input variables.

  6. Input-output tables and analyses 2000. Imports, employment and environment

    International Nuclear Information System (INIS)

    2002-05-01

    The publication is primarily designed as a practical reference quide presenting data and in particular analytical results (impact multipliers) on the structural characteristics and developments of the Danish economy. Also readers who are not familiar with the theoretical aspects of input-output analysis may benefit from the contents. In the different chapters of the publication a comprehensive treatment of the basic data material is given together with figures primarily for the year 1998, which is the most recent year for which final national accounts and input-output tables are available. This part is followed by the multipliers, some of which have also been 'forecasted' to the year 2000. The publication presents data for each industrial sector and the household sector in Denmark. It presents data for input-output analyses, environmental accounts, production, employment, energy consumption, and emission of pollutants. (LN)

  7. Screening important inputs in models with strong interaction properties

    International Nuclear Information System (INIS)

    Saltelli, Andrea; Campolongo, Francesca; Cariboni, Jessica

    2009-01-01

    We introduce a new method for screening inputs in mathematical or computational models with large numbers of inputs. The method proposed here represents an improvement over the best available practice for this setting when dealing with models having strong interaction effects. When the sample size is sufficiently high the same design can also be used to obtain accurate quantitative estimates of the variance-based sensitivity measures: the same simulations can be used to obtain estimates of the variance-based measures according to the Sobol' and the Jansen formulas. Results demonstrate that Sobol' is more efficient for the computation of the first-order indices, while Jansen performs better for the computation of the total indices.

  8. Screening important inputs in models with strong interaction properties

    Energy Technology Data Exchange (ETDEWEB)

    Saltelli, Andrea [European Commission, Joint Research Centre, 21020 Ispra, Varese (Italy); Campolongo, Francesca [European Commission, Joint Research Centre, 21020 Ispra, Varese (Italy)], E-mail: francesca.campolongo@jrc.it; Cariboni, Jessica [European Commission, Joint Research Centre, 21020 Ispra, Varese (Italy)

    2009-07-15

    We introduce a new method for screening inputs in mathematical or computational models with large numbers of inputs. The method proposed here represents an improvement over the best available practice for this setting when dealing with models having strong interaction effects. When the sample size is sufficiently high the same design can also be used to obtain accurate quantitative estimates of the variance-based sensitivity measures: the same simulations can be used to obtain estimates of the variance-based measures according to the Sobol' and the Jansen formulas. Results demonstrate that Sobol' is more efficient for the computation of the first-order indices, while Jansen performs better for the computation of the total indices.

  9. Remote Sensing Analysis of Malawi's Agricultural Inputs Subsidy and Climate Variability Impacts on Productivity

    Science.gov (United States)

    Galford, G. L.; Fiske, G. J.; Sedano, F.; Michelson, H.

    2016-12-01

    Agriculture in sub-Saharan Africa is characterized by smallholder production and low yields ( 1 ton ha-1 year-1 since records began in 1961) for staple food crops such as maize (Zea mays). Many years of low-input farming have depleted much of the region's agricultural land of critical soil carbon and nitrogen, further reducing yield potentials. Malawi is a 98,000 km2 subtropical nation with a short rainy season from November to May, with most rainfall occurring between December and mid-April. This short growing season supports the cultivation of one primary crop, maize. In Malawi, many smallholder farmers face annual nutrient deficits as nutrients removed as grain harvest and residues are beyond replenishment levels. As a result, Malawi has had stagnant maize yields averaging 1.2 ton ha-1 year-1 for decades. After multiple years of drought and widespread hunger in the early 2000s, Malawi introduced an agricultural input support program (fertilizer and seed subsidy) in time for the 2006 harvest that was designed to restore soil nutrients, improve maize production, and decrease dependence on food aid. Malawi's subsidy program targets 50-67% of smallholder farmers who cultivate half a hectare or less, yet collectively supply 80% of the country's maize. The country has achieved significant increases in crop yields (now 2 tons/ha/year) and, as our analysis shows, benefited from a new resilience against drought. We utilized Landsat time series to determine cropland extent from 2000-present and identify areas of marginal and/or intermittent production. We found a strong latitudinal gradient of precipitation variability from north to south in CHIRPS data. We used the precipitation variability to normalize trends in a productivity proxy derived from MODIS EVI. After normalization of productivity to precipitation variability, we found significant productivity trends correlated to subsidy distribution. This work was conducted with Google's Earth Engine, a cloud-based platform

  10. How model and input uncertainty impact maize yield simulations in West Africa

    Science.gov (United States)

    Waha, Katharina; Huth, Neil; Carberry, Peter; Wang, Enli

    2015-02-01

    Crop models are common tools for simulating crop yields and crop production in studies on food security and global change. Various uncertainties however exist, not only in the model design and model parameters, but also and maybe even more important in soil, climate and management input data. We analyze the performance of the point-scale crop model APSIM and the global scale crop model LPJmL with different climate and soil conditions under different agricultural management in the low-input maize-growing areas of Burkina Faso, West Africa. We test the models’ response to different levels of input information from little to detailed information on soil, climate (1961-2000) and agricultural management and compare the models’ ability to represent the observed spatial (between locations) and temporal variability (between years) in crop yields. We found that the resolution of different soil, climate and management information influences the simulated crop yields in both models. However, the difference between models is larger than between input data and larger between simulations with different climate and management information than between simulations with different soil information. The observed spatial variability can be represented well from both models even with little information on soils and management but APSIM simulates a higher variation between single locations than LPJmL. The agreement of simulated and observed temporal variability is lower due to non-climatic factors e.g. investment in agricultural research and development between 1987 and 1991 in Burkina Faso which resulted in a doubling of maize yields. The findings of our study highlight the importance of scale and model choice and show that the most detailed input data does not necessarily improve model performance.

  11. Estimating severity of sideways fall using a generic multi linear regression model based on kinematic input variables.

    Science.gov (United States)

    van der Zijden, A M; Groen, B E; Tanck, E; Nienhuis, B; Verdonschot, N; Weerdesteyn, V

    2017-03-21

    Many research groups have studied fall impact mechanics to understand how fall severity can be reduced to prevent hip fractures. Yet, direct impact force measurements with force plates are restricted to a very limited repertoire of experimental falls. The purpose of this study was to develop a generic model for estimating hip impact forces (i.e. fall severity) in in vivo sideways falls without the use of force plates. Twelve experienced judokas performed sideways Martial Arts (MA) and Block ('natural') falls on a force plate, both with and without a mat on top. Data were analyzed to determine the hip impact force and to derive 11 selected (subject-specific and kinematic) variables. Falls from kneeling height were used to perform a stepwise regression procedure to assess the effects of these input variables and build the model. The final model includes four input variables, involving one subject-specific measure and three kinematic variables: maximum upper body deceleration, body mass, shoulder angle at the instant of 'maximum impact' and maximum hip deceleration. The results showed that estimated and measured hip impact forces were linearly related (explained variances ranging from 46 to 63%). Hip impact forces of MA falls onto the mat from a standing position (3650±916N) estimated by the final model were comparable with measured values (3698±689N), even though these data were not used for training the model. In conclusion, a generic linear regression model was developed that enables the assessment of fall severity through kinematic measures of sideways falls, without using force plates. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. Bias in random forest variable importance measures: Illustrations, sources and a solution

    Directory of Open Access Journals (Sweden)

    Hothorn Torsten

    2007-01-01

    Full Text Available Abstract Background Variable importance measures for random forests have been receiving increased attention as a means of variable selection in many classification tasks in bioinformatics and related scientific fields, for instance to select a subset of genetic markers relevant for the prediction of a certain disease. We show that random forest variable importance measures are a sensible means for variable selection in many applications, but are not reliable in situations where potential predictor variables vary in their scale of measurement or their number of categories. This is particularly important in genomics and computational biology, where predictors often include variables of different types, for example when predictors include both sequence data and continuous variables such as folding energy, or when amino acid sequence data show different numbers of categories. Results Simulation studies are presented illustrating that, when random forest variable importance measures are used with data of varying types, the results are misleading because suboptimal predictor variables may be artificially preferred in variable selection. The two mechanisms underlying this deficiency are biased variable selection in the individual classification trees used to build the random forest on one hand, and effects induced by bootstrap sampling with replacement on the other hand. Conclusion We propose to employ an alternative implementation of random forests, that provides unbiased variable selection in the individual classification trees. When this method is applied using subsampling without replacement, the resulting variable importance measures can be used reliably for variable selection even in situations where the potential predictor variables vary in their scale of measurement or their number of categories. The usage of both random forest algorithms and their variable importance measures in the R system for statistical computing is illustrated and

  13. Reducing uncertainty at minimal cost: a method to identify important input parameters and prioritize data collection

    NARCIS (Netherlands)

    Uwizeye, U.A.; Groen, E.A.; Gerber, P.J.; Schulte, Rogier P.O.; Boer, de I.J.M.

    2016-01-01

    The study aims to illustrate a method to identify important input parameters that explain most of the output variance ofenvironmental assessment models. The method is tested for the computation of life-cycle nitrogen (N) use efficiencyindicators among mixed dairy production systems in Rwanda. We

  14. Variable importance and prediction methods for longitudinal problems with missing variables.

    Directory of Open Access Journals (Sweden)

    Iván Díaz

    Full Text Available We present prediction and variable importance (VIM methods for longitudinal data sets containing continuous and binary exposures subject to missingness. We demonstrate the use of these methods for prognosis of medical outcomes of severe trauma patients, a field in which current medical practice involves rules of thumb and scoring methods that only use a few variables and ignore the dynamic and high-dimensional nature of trauma recovery. Well-principled prediction and VIM methods can provide a tool to make care decisions informed by the high-dimensional patient's physiological and clinical history. Our VIM parameters are analogous to slope coefficients in adjusted regressions, but are not dependent on a specific statistical model, nor require a certain functional form of the prediction regression to be estimated. In addition, they can be causally interpreted under causal and statistical assumptions as the expected outcome under time-specific clinical interventions, related to changes in the mean of the outcome if each individual experiences a specified change in the variable (keeping other variables in the model fixed. Better yet, the targeted MLE used is doubly robust and locally efficient. Because the proposed VIM does not constrain the prediction model fit, we use a very flexible ensemble learner (the SuperLearner, which returns a linear combination of a list of user-given algorithms. Not only is such a prediction algorithm intuitive appealing, it has theoretical justification as being asymptotically equivalent to the oracle selector. The results of the analysis show effects whose size and significance would have been not been found using a parametric approach (such as stepwise regression or LASSO. In addition, the procedure is even more compelling as the predictor on which it is based showed significant improvements in cross-validated fit, for instance area under the curve (AUC for a receiver-operator curve (ROC. Thus, given that 1 our VIM

  15. Variable importance in latent variable regression models

    NARCIS (Netherlands)

    Kvalheim, O.M.; Arneberg, R.; Bleie, O.; Rajalahti, T.; Smilde, A.K.; Westerhuis, J.A.

    2014-01-01

    The quality and practical usefulness of a regression model are a function of both interpretability and prediction performance. This work presents some new graphical tools for improved interpretation of latent variable regression models that can also assist in improved algorithms for variable

  16. Analysis of reactor capital costs and correlated sampling of economic input variables - 15342

    International Nuclear Information System (INIS)

    Ganda, F.; Kim, T.K.; Taiwo, T.A.; Wigeland, R.

    2015-01-01

    In this paper we present work aimed at enhancing the capability to perform nuclear fuel cycle cost estimates and evaluation of financial risk. Reactor capital costs are of particular relevance, since they typically comprise about 60% to 70% of the calculated Levelized Cost of Electricity at Equilibrium (LCAE). The work starts with the collection of historical construction cost and construction duration of nuclear plants in the U.S. and France, as well as forecasted costs of nuclear plants currently under construction in the U.S. This data has the primary goal of supporting the introduction of an appropriate framework, supported in this paper by two case studies with historical data, which allows the development of solid and defensible assumptions on nuclear reactor capital costs. Work is also presented on the enhancement of the capability to model interdependence of cost estimates between facilities and uncertainties. The correlated sampling capabilities in the nuclear economic code NECOST have been expanded to include partial correlations between input variables, according to a given correlation matrix. Accounting for partial correlations correctly allows a narrowing, where appropriate, of the probability density function of the difference in the LCAE between alternative, but correlated, fuel cycles. It also allows the correct calculation of the standard deviation of the LCAE of multistage systems, which appears smaller than the correct value if correlated input costs are treated as uncorrelated. (authors)

  17. Methods to quantify variable importance: implications for theanalysis of noisy ecological data

    OpenAIRE

    Murray, Kim; Conner, Mary M.

    2009-01-01

    Determining the importance of independent variables is of practical relevance to ecologists and managers concerned with allocating limited resources to the management of natural systems. Although techniques that identify explanatory variables having the largest influence on the response variable are needed to design management actions effectively, the use of various indices to evaluate variable importance is poorly understood. Using Monte Carlo simulations, we compared six different indices c...

  18. Dose uncertainties for large solar particle events: Input spectra variability and human geometry approximations

    International Nuclear Information System (INIS)

    Townsend, Lawrence W.; Zapp, E. Neal

    1999-01-01

    The true uncertainties in estimates of body organ absorbed dose and dose equivalent, from exposures of interplanetary astronauts to large solar particle events (SPEs), are essentially unknown. Variations in models used to parameterize SPE proton spectra for input into space radiation transport and shielding computer codes can result in uncertainty about the reliability of dose predictions for these events. Also, different radiation transport codes and their input databases can yield significant differences in dose predictions, even for the same input spectra. Different results may also be obtained for the same input spectra and transport codes if different spacecraft and body self-shielding distributions are assumed. Heretofore there have been no systematic investigations of the variations in dose and dose equivalent resulting from these assumptions and models. In this work we present a study of the variability in predictions of organ dose and dose equivalent arising from the use of different parameters to represent the same incident SPE proton data and from the use of equivalent sphere approximations to represent human body geometry. The study uses the BRYNTRN space radiation transport code to calculate dose and dose equivalent for the skin, ocular lens and bone marrow using the October 1989 SPE as a model event. Comparisons of organ dose and dose equivalent, obtained with a realistic human geometry model and with the oft-used equivalent sphere approximation, are also made. It is demonstrated that variations of 30-40% in organ dose and dose equivalent are obtained for slight variations in spectral fitting parameters obtained when various data points are included or excluded from the fitting procedure. It is further demonstrated that extrapolating spectra from low energy (≤30 MeV) proton fluence measurements, rather than using fluence data extending out to 100 MeV results in dose and dose equivalent predictions that are underestimated by factors as large as 2

  19. Air temperature variability in a high-elevation Himalayan catchment

    NARCIS (Netherlands)

    Heynen, Martin; Miles, Evan; Ragettli, Silvan; Buri, Pascal; Immerzeel, Walter W.; Pellicciotti, Francesca

    2016-01-01

    Air temperature is a key control of processes affecting snow and glaciers in high-elevation catchments, including melt, snowfall and sublimation. It is therefore a key input variable to models of land-surface-atmosphere interaction. Despite this importance, its spatial variability is poorly

  20. Input Selection for Return Temperature Estimation in Mixing Loops using Partial Mutual Information with Flow Variable Delay

    DEFF Research Database (Denmark)

    Overgaard, Anders; Kallesøe, Carsten Skovmose; Bendtsen, Jan Dimon

    2017-01-01

    adgang til data, er ønsker at skabe en datadreven model til kontrol. Grundet den store mængde tilgængelig data anvendes der en metode til valg af inputs kaldet "Partial Mutual Information" (PMI). Denne artikel introducerer en metode til at inkluderer flow variable forsinkelser i PMI. Data fra en...... kontorbygning i Bjerringbro anvendes til analyse. Det vises at "Mutual Information" og et "Generalized Regression Neural Network" begge forbedres ved at anvende flow variabelt forsinkelse i forhold til at anvende konstante delay....

  1. ETFOD: a point model physics code with arbitrary input

    International Nuclear Information System (INIS)

    Rothe, K.E.; Attenberger, S.E.

    1980-06-01

    ETFOD is a zero-dimensional code which solves a set of physics equations by minimization. The technique used is different than normally used, in that the input is arbitrary. The user is supplied with a set of variables from which he specifies which variables are input (unchanging). The remaining variables become the output. Presently the code is being used for ETF reactor design studies. The code was written in a manner to allow easy modificaton of equations, variables, and physics calculations. The solution technique is presented along with hints for using the code

  2. Identifying the important factors in simulation models with many factors

    NARCIS (Netherlands)

    Bettonvil, B.; Kleijnen, J.P.C.

    1994-01-01

    Simulation models may have many parameters and input variables (together called factors), while only a few factors are really important (parsimony principle). For such models this paper presents an effective and efficient screening technique to identify and estimate those important factors. The

  3. Input and language development in bilingually developing children.

    Science.gov (United States)

    Hoff, Erika; Core, Cynthia

    2013-11-01

    Language skills in young bilingual children are highly varied as a result of the variability in their language experiences, making it difficult for speech-language pathologists to differentiate language disorder from language difference in bilingual children. Understanding the sources of variability in bilingual contexts and the resulting variability in children's skills will help improve language assessment practices by speech-language pathologists. In this article, we review literature on bilingual first language development for children under 5 years of age. We describe the rate of development in single and total language growth, we describe effects of quantity of input and quality of input on growth, and we describe effects of family composition on language input and language growth in bilingual children. We provide recommendations for language assessment of young bilingual children and consider implications for optimizing children's dual language development. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

  4. Input-output interactions and optimal monetary policy

    DEFF Research Database (Denmark)

    Petrella, Ivan; Santoro, Emiliano

    2011-01-01

    This paper deals with the implications of factor demand linkages for monetary policy design in a two-sector dynamic general equilibrium model. Part of the output of each sector serves as a production input in both sectors, in accordance with a realistic input–output structure. Strategic...... complementarities induced by factor demand linkages significantly alter the transmission of shocks and amplify the loss of social welfare under optimal monetary policy, compared to what is observed in standard two-sector models. The distinction between value added and gross output that naturally arises...... in this context is of key importance to explore the welfare properties of the model economy. A flexible inflation targeting regime is close to optimal only if the central bank balances inflation and value added variability. Otherwise, targeting gross output variability entails a substantial increase in the loss...

  5. Sensitivity analysis of complex models: Coping with dynamic and static inputs

    International Nuclear Information System (INIS)

    Anstett-Collin, F.; Goffart, J.; Mara, T.; Denis-Vidal, L.

    2015-01-01

    In this paper, we address the issue of conducting a sensitivity analysis of complex models with both static and dynamic uncertain inputs. While several approaches have been proposed to compute the sensitivity indices of the static inputs (i.e. parameters), the one of the dynamic inputs (i.e. stochastic fields) have been rarely addressed. For this purpose, we first treat each dynamic as a Gaussian process. Then, the truncated Karhunen–Loève expansion of each dynamic input is performed. Such an expansion allows to generate independent Gaussian processes from a finite number of independent random variables. Given that a dynamic input is represented by a finite number of random variables, its variance-based sensitivity index is defined by the sensitivity index of this group of variables. Besides, an efficient sampling-based strategy is described to estimate the first-order indices of all the input factors by only using two input samples. The approach is applied to a building energy model, in order to assess the impact of the uncertainties of the material properties (static inputs) and the weather data (dynamic inputs) on the energy performance of a real low energy consumption house. - Highlights: • Sensitivity analysis of models with uncertain static and dynamic inputs is performed. • Karhunen–Loève (KL) decomposition of the spatio/temporal inputs is performed. • The influence of the dynamic inputs is studied through the modes of the KL expansion. • The proposed approach is applied to a building energy model. • Impact of weather data and material properties on performance of real house is given

  6. The Mixed Effects of Phonetic Input Variability on Relative Ease of L2 Learning: Evidence from English Learners’ Production of French and Spanish Stop-Rhotic Clusters

    Directory of Open Access Journals (Sweden)

    Laura Colantoni

    2018-04-01

    Full Text Available We examined the consequences of within-category phonetic variability in the input on non-native learners’ production accuracy. Following previous empirical research on the L2 acquisition of phonetics and the lexicon, we tested the hypothesis that phonetic variability facilitates learning by analyzing English-speaking learners’ production of French and Spanish word-medial stop-rhotic clusters, which differ from their English counterparts in terms of stop and rhotic voicing and manner. Crucially, for both the stops and rhotics, there are differences in within-language variability. Twenty native speakers per language and 39 L1 English-learners of French (N = 20 and Spanish (N = 19 of intermediate and advanced proficiency performed a carrier-sentence reading task. A given parameter was deemed to have been acquired when the learners’ production fell within the range of attested native speaker values. An acoustic analysis of the data partially supports the facilitative effect of phonetic variability. To account for the unsupported hypotheses, we discuss a number of issues, including the difficulty of measuring variability, the need to determine the extent to which learners’ perception shapes intake, and the challenge of teasing apart the effects of input variability from those of transferred L1 articulatory patterns.

  7. Integrate-and-fire vs Poisson models of LGN input to V1 cortex: noisier inputs reduce orientation selectivity.

    Science.gov (United States)

    Lin, I-Chun; Xing, Dajun; Shapley, Robert

    2012-12-01

    One of the reasons the visual cortex has attracted the interest of computational neuroscience is that it has well-defined inputs. The lateral geniculate nucleus (LGN) of the thalamus is the source of visual signals to the primary visual cortex (V1). Most large-scale cortical network models approximate the spike trains of LGN neurons as simple Poisson point processes. However, many studies have shown that neurons in the early visual pathway are capable of spiking with high temporal precision and their discharges are not Poisson-like. To gain an understanding of how response variability in the LGN influences the behavior of V1, we study response properties of model V1 neurons that receive purely feedforward inputs from LGN cells modeled either as noisy leaky integrate-and-fire (NLIF) neurons or as inhomogeneous Poisson processes. We first demonstrate that the NLIF model is capable of reproducing many experimentally observed statistical properties of LGN neurons. Then we show that a V1 model in which the LGN input to a V1 neuron is modeled as a group of NLIF neurons produces higher orientation selectivity than the one with Poisson LGN input. The second result implies that statistical characteristics of LGN spike trains are important for V1's function. We conclude that physiologically motivated models of V1 need to include more realistic LGN spike trains that are less noisy than inhomogeneous Poisson processes.

  8. Interpreting Multiple Linear Regression: A Guidebook of Variable Importance

    Science.gov (United States)

    Nathans, Laura L.; Oswald, Frederick L.; Nimon, Kim

    2012-01-01

    Multiple regression (MR) analyses are commonly employed in social science fields. It is also common for interpretation of results to typically reflect overreliance on beta weights, often resulting in very limited interpretations of variable importance. It appears that few researchers employ other methods to obtain a fuller understanding of what…

  9. Input saturation in nonlinear multivariable processes resolved by nonlinear decoupling

    Directory of Open Access Journals (Sweden)

    Jens G. Balchen

    1995-04-01

    Full Text Available A new method is presented for the resolution of the problem of input saturation in nonlinear multivariable process control by means of elementary nonlinear decoupling (END. Input saturation can have serious consequences particularly in multivariable control because it may lead to very undesirable system behaviour and quite often system instability. Many authors have searched for systematic techniques for designing multivariable control systems in which saturation may occur in any of the control variables (inputs, manipulated variables. No generally accepted method seems to have been presented so far which gives a solution in closed form. The method of elementary nonlinear decoupling (END can be applied directly to the case of saturation control variables by deriving as many control strategies as there are combinations of saturating control variables. The method is demonstrated by the multivariable control of a simulated Fluidized Catalytic Cracker (FCC with very convincing results.

  10. Does linguistic input play the same role in language learning for children with and without early brain injury?

    Science.gov (United States)

    Rowe, Meredith L; Levine, Susan C; Fisher, Joan A; Goldin-Meadow, Susan

    2009-01-01

    Children with unilateral pre- or perinatal brain injury (BI) show remarkable plasticity for language learning. Previous work highlights the important role that lesion characteristics play in explaining individual variation in plasticity in the language development of children with BI. The current study examines whether the linguistic input that children with BI receive from their caregivers also contributes to this early plasticity, and whether linguistic input plays a similar role in children with BI as it does in typically developing (TD) children. Growth in vocabulary and syntactic production is modeled for 80 children (53 TD, 27 BI) between 14 and 46 months. Findings indicate that caregiver input is an equally potent predictor of vocabulary growth in children with BI and in TD children. In contrast, input is a more potent predictor of syntactic growth for children with BI than for TD children. Controlling for input, lesion characteristics (lesion size, type, seizure history) also affect the language trajectories of children with BI. Thus, findings illustrate how both variability in the environment (linguistic input) and variability in the organism (lesion characteristics) work together to contribute to plasticity in language learning.

  11. READDATA: a FORTRAN 77 codeword input package

    International Nuclear Information System (INIS)

    Lander, P.A.

    1983-07-01

    A new codeword input package has been produced as a result of the incompatibility between different dialects of FORTRAN, especially when character variables are passed as parameters. This report is for those who wish to use a codeword input package with FORTRAN 77. The package, called ''Readdata'', attempts to combine the best features of its predecessors such as BINPUT and pseudo-BINPUT. (author)

  12. Variable importance analysis based on rank aggregation with applications in metabolomics for biomarker discovery.

    Science.gov (United States)

    Yun, Yong-Huan; Deng, Bai-Chuan; Cao, Dong-Sheng; Wang, Wei-Ting; Liang, Yi-Zeng

    2016-03-10

    Biomarker discovery is one important goal in metabolomics, which is typically modeled as selecting the most discriminating metabolites for classification and often referred to as variable importance analysis or variable selection. Until now, a number of variable importance analysis methods to discover biomarkers in the metabolomics studies have been proposed. However, different methods are mostly likely to generate different variable ranking results due to their different principles. Each method generates a variable ranking list just as an expert presents an opinion. The problem of inconsistency between different variable ranking methods is often ignored. To address this problem, a simple and ideal solution is that every ranking should be taken into account. In this study, a strategy, called rank aggregation, was employed. It is an indispensable tool for merging individual ranking lists into a single "super"-list reflective of the overall preference or importance within the population. This "super"-list is regarded as the final ranking for biomarker discovery. Finally, it was used for biomarkers discovery and selecting the best variable subset with the highest predictive classification accuracy. Nine methods were used, including three univariate filtering and six multivariate methods. When applied to two metabolic datasets (Childhood overweight dataset and Tubulointerstitial lesions dataset), the results show that the performance of rank aggregation has improved greatly with higher prediction accuracy compared with using all variables. Moreover, it is also better than penalized method, least absolute shrinkage and selectionator operator (LASSO), with higher prediction accuracy or less number of selected variables which are more interpretable. Copyright © 2016 Elsevier B.V. All rights reserved.

  13. PLEXOS Input Data Generator

    Energy Technology Data Exchange (ETDEWEB)

    2017-02-01

    The PLEXOS Input Data Generator (PIDG) is a tool that enables PLEXOS users to better version their data, automate data processing, collaborate in developing inputs, and transfer data between different production cost modeling and other power systems analysis software. PIDG can process data that is in a generalized format from multiple input sources, including CSV files, PostgreSQL databases, and PSS/E .raw files and write it to an Excel file that can be imported into PLEXOS with only limited manual intervention.

  14. Categorical Inputs, Sensitivity Analysis, Optimization and Importance Tempering with tgp Version 2, an R Package for Treed Gaussian Process Models

    Directory of Open Access Journals (Sweden)

    Robert B. Gramacy

    2010-02-01

    Full Text Available This document describes the new features in version 2.x of the tgp package for R, implementing treed Gaussian process (GP models. The topics covered include methods for dealing with categorical inputs and excluding inputs from the tree or GP part of the model; fully Bayesian sensitivity analysis for inputs/covariates; sequential optimization of black-box functions; and a new Monte Carlo method for inference in multi-modal posterior distributions that combines simulated tempering and importance sampling. These additions extend the functionality of tgp across all models in the hierarchy: from Bayesian linear models, to classification and regression trees (CART, to treed Gaussian processes with jumps to the limiting linear model. It is assumed that the reader is familiar with the baseline functionality of the package, outlined in the first vignette (Gramacy 2007.

  15. Spectral Data Captures Important Variability Between and Among Species and Functional Types

    Science.gov (United States)

    Townsend, P. A.; Serbin, S. P.; Kingdon, C.; Singh, A.; Couture, J. J.; Gamon, J. A.

    2013-12-01

    Narrowband spectral data in the visible, near and shortwave infrared (400-2500 nm) are being used increasingly in plant ecology to characterize the biochemical, physiological and water status of vegetation, as well as community composition. In particular, spectroscopic data have recently received considerable attention for their capacity to discriminate plants according to functional properties or 'optical types.' Such measurements can be acquired from airborne/satellite remote sensing imagery or field spectrometers and are commonly used to directly estimate or infer properties important to photosynthesis, carbon and water fluxes, nutrient dynamics, phenology, and disturbance. Spectral data therefore represent proxies for measurements that are otherwise time consuming or expensive to make, and - more importantly - provide the opportunity to characterize the spatial and temporal variability of taxonomic or functional groups. We have found that spectral variation within species and functional types can in fact exceed the variation between types. As such, we recommend that the traditional quantification of characteristics defining species and/or functional types must be modified to include the range of variability in those properties. We provide four examples of the importance of spectral data for describing within-species/functional type variation. First, within temperate forests, the spectral properties of foliage vary considerably with canopy position. This variability is strongly related to differences in specific leaf area between shade- and sun-lit leaves, and the resulting differences among leaves in strategies for light harvesting, photosynthesis, and leaf longevity. These results point to the need to better characterize leaf optical properties throughout a canopy, rather than basing the characterization of ecosystem functioning on only the sunlit portion of the canopy crown. Second, we show considerable differences in optical properties of foliage from

  16. Soil organic carbon dynamics jointly controlled by climate, carbon inputs, soil properties and soil carbon fractions.

    Science.gov (United States)

    Luo, Zhongkui; Feng, Wenting; Luo, Yiqi; Baldock, Jeff; Wang, Enli

    2017-10-01

    Soil organic carbon (SOC) dynamics are regulated by the complex interplay of climatic, edaphic and biotic conditions. However, the interrelation of SOC and these drivers and their potential connection networks are rarely assessed quantitatively. Using observations of SOC dynamics with detailed soil properties from 90 field trials at 28 sites under different agroecosystems across the Australian cropping regions, we investigated the direct and indirect effects of climate, soil properties, carbon (C) inputs and soil C pools (a total of 17 variables) on SOC change rate (r C , Mg C ha -1  yr -1 ). Among these variables, we found that the most influential variables on r C were the average C input amount and annual precipitation, and the total SOC stock at the beginning of the trials. Overall, C inputs (including C input amount and pasture frequency in the crop rotation system) accounted for 27% of the relative influence on r C , followed by climate 25% (including precipitation and temperature), soil C pools 24% (including pool size and composition) and soil properties (such as cation exchange capacity, clay content, bulk density) 24%. Path analysis identified a network of intercorrelations of climate, soil properties, C inputs and soil C pools in determining r C . The direct correlation of r C with climate was significantly weakened if removing the effects of soil properties and C pools, and vice versa. These results reveal the relative importance of climate, soil properties, C inputs and C pools and their complex interconnections in regulating SOC dynamics. Ignorance of the impact of changes in soil properties, C pool composition and C input (quantity and quality) on SOC dynamics is likely one of the main sources of uncertainty in SOC predictions from the process-based SOC models. © 2017 John Wiley & Sons Ltd.

  17. Sequential designs for sensitivity analysis of functional inputs in computer experiments

    International Nuclear Information System (INIS)

    Fruth, J.; Roustant, O.; Kuhnt, S.

    2015-01-01

    Computer experiments are nowadays commonly used to analyze industrial processes aiming at achieving a wanted outcome. Sensitivity analysis plays an important role in exploring the actual impact of adjustable parameters on the response variable. In this work we focus on sensitivity analysis of a scalar-valued output of a time-consuming computer code depending on scalar and functional input parameters. We investigate a sequential methodology, based on piecewise constant functions and sequential bifurcation, which is both economical and fully interpretable. The new approach is applied to a sheet metal forming problem in three sequential steps, resulting in new insights into the behavior of the forming process over time. - Highlights: • Sensitivity analysis method for functional and scalar inputs is presented. • We focus on the discovery of most influential parts of the functional domain. • We investigate economical sequential methodology based on piecewise constant functions. • Normalized sensitivity indices are introduced and investigated theoretically. • Successful application to sheet metal forming on two functional inputs

  18. Important variables in explaining real-time peak price in the independent power market of Ontario

    International Nuclear Information System (INIS)

    Rueda, I.E.A.; Marathe, A.

    2005-01-01

    This paper uses support vector machines (SVM) based learning algorithm to select important variables that help explain the real-time peak electricity price in the Ontario market. The Ontario market was opened to competition only in May 2002. Due to the limited number of observations available, finding a set of variables that can explain the independent power market of Ontario (IMO) real-time peak price is a significant challenge for the traders and analysts. The kernel regressions of the explanatory variables on the IMO real-time average peak price show that non-linear dependencies exist between the explanatory variables and the IMO price. This non-linear relationship combined with the low variable-observation ratio rule out conventional statistical analysis. Hence, we use an alternative machine learning technique to find the important explanatory variables for the IMO real-time average peak price. SVM sensitivity analysis based results find that the IMO's predispatch average peak price, the actual import peak volume, the peak load of the Ontario market and the net available supply after accounting for load (energy excess) are some of the most important variables in explaining the real-time average peak price in the Ontario electricity market. (author)

  19. Lithium inputs to subduction zones

    NARCIS (Netherlands)

    Bouman, C.; Elliott, T.R.; Vroon, P.Z.

    2004-01-01

    We have studied the sedimentary and basaltic inputs of lithium to subduction zones. Various sediments from DSDP and ODP drill cores in front of the Mariana, South Sandwich, Banda, East Sunda and Lesser Antilles island arcs have been analysed and show highly variable Li contents and δ

  20. Handwriting generates variable visual input to facilitate symbol learning

    Science.gov (United States)

    Li, Julia X.; James, Karin H.

    2015-01-01

    Recent research has demonstrated that handwriting practice facilitates letter categorization in young children. The present experiments investigated why handwriting practice facilitates visual categorization by comparing two hypotheses: That handwriting exerts its facilitative effect because of the visual-motor production of forms, resulting in a direct link between motor and perceptual systems, or because handwriting produces variable visual instances of a named category in the environment that then changes neural systems. We addressed these issues by measuring performance of 5 year-old children on a categorization task involving novel, Greek symbols across 6 different types of learning conditions: three involving visual-motor practice (copying typed symbols independently, tracing typed symbols, tracing handwritten symbols) and three involving visual-auditory practice (seeing and saying typed symbols of a single typed font, of variable typed fonts, and of handwritten examples). We could therefore compare visual-motor production with visual perception both of variable and similar forms. Comparisons across the six conditions (N=72) demonstrated that all conditions that involved studying highly variable instances of a symbol facilitated symbol categorization relative to conditions where similar instances of a symbol were learned, regardless of visual-motor production. Therefore, learning perceptually variable instances of a category enhanced performance, suggesting that handwriting facilitates symbol understanding by virtue of its environmental output: supporting the notion of developmental change though brain-body-environment interactions. PMID:26726913

  1. A probabilistic graphical model based stochastic input model construction

    International Nuclear Information System (INIS)

    Wan, Jiang; Zabaras, Nicholas

    2014-01-01

    Model reduction techniques have been widely used in modeling of high-dimensional stochastic input in uncertainty quantification tasks. However, the probabilistic modeling of random variables projected into reduced-order spaces presents a number of computational challenges. Due to the curse of dimensionality, the underlying dependence relationships between these random variables are difficult to capture. In this work, a probabilistic graphical model based approach is employed to learn the dependence by running a number of conditional independence tests using observation data. Thus a probabilistic model of the joint PDF is obtained and the PDF is factorized into a set of conditional distributions based on the dependence structure of the variables. The estimation of the joint PDF from data is then transformed to estimating conditional distributions under reduced dimensions. To improve the computational efficiency, a polynomial chaos expansion is further applied to represent the random field in terms of a set of standard random variables. This technique is combined with both linear and nonlinear model reduction methods. Numerical examples are presented to demonstrate the accuracy and efficiency of the probabilistic graphical model based stochastic input models. - Highlights: • Data-driven stochastic input models without the assumption of independence of the reduced random variables. • The problem is transformed to a Bayesian network structure learning problem. • Examples are given in flows in random media

  2. The effect of long-term changes in plant inputs on soil carbon stocks

    Science.gov (United States)

    Georgiou, K.; Li, Z.; Torn, M. S.

    2017-12-01

    Soil organic carbon (SOC) is the largest actively-cycling terrestrial reservoir of C and an integral component of thriving natural and managed ecosystems. C input interventions (e.g., litter removal or organic amendments) are common in managed landscapes and present an important decision for maintaining healthy soils in sustainable agriculture and forestry. Furthermore, climate and land-cover change can also affect the amount of plant C inputs that enter the soil through changes in plant productivity, allocation, and rooting depth. Yet, the processes that dictate the response of SOC to such changes in C inputs are poorly understood and inadequately represented in predictive models. Long-term litter manipulations are an invaluable resource for exploring key controls of SOC storage and validating model representations. Here we explore the response of SOC to long-term changes in plant C inputs across a range of biomes and soil types. We synthesize and analyze data from long-term litter manipulation field experiments, and focus our meta-analysis on changes to total SOC stocks, microbial biomass carbon, and mineral-associated (`protected') carbon pools and explore the relative contribution of above- versus below-ground C inputs. Our cross-site data comparison reveals that divergent SOC responses are observed between forest sites, particularly for treatments that increase C inputs to the soil. We explore trends among key variables (e.g., microbial biomass to SOC ratios) that inform soil C model representations. The assembled dataset is an important benchmark for evaluating process-based hypotheses and validating divergent model formulations.

  3. Simulation model structure numerically robust to changes in magnitude and combination of input and output variables

    DEFF Research Database (Denmark)

    Rasmussen, Bjarne D.; Jakobsen, Arne

    1999-01-01

    Mathematical models of refrigeration systems are often based on a coupling of component models forming a “closed loop” type of system model. In these models the coupling structure of the component models represents the actual flow path of refrigerant in the system. Very often numerical...... instabilities prevent the practical use of such a system model for more than one input/output combination and for other magnitudes of refrigerating capacities.A higher numerical robustness of system models can be achieved by making a model for the refrigeration cycle the core of the system model and by using...... variables with narrow definition intervals for the exchange of information between the cycle model and the component models.The advantages of the cycle-oriented method are illustrated by an example showing the refrigeration cycle similarities between two very different refrigeration systems....

  4. Impact of the Sugar Import Reduction on Iran Economic Value Added (Input- Output Approach

    Directory of Open Access Journals (Sweden)

    Fateme Hayatgheibi

    2014-06-01

    Full Text Available The present study aimed at understanding interactions and linkages between the sugar sector with other economic sectors, and the influence of sugar import reduction on the economic value added. To achieve the purpose, the Input-Output table of Iran for the year 2006, Leontief inverse matrix and hypothetical extraction method were used. Based on the results, sugar industry has the most forward linkages with “Manufacture of food products and beverages,…”, “husbandry, aviculture,…”, “cultivation, horticulture”, “bakery products” and “restaurants”. This sector has also strong backward linkages with “cultivation, horticulture”, “chemicals and chemical products”, “other services”, “transport and telecommunication” and “financial services, insurance and bank”. Furthermore, either one unit increase in the final demand of sugar or one unit decrease in the sugar import increases the output of whole economic, agricultural and fishing, industry and mining, and services sectors by 2.3060, 0.6019, 1.4331, and 0.2710 unit, respectively. The increasing coefficients of the value added for the above sectors are 0.4308, 0.3700, and 0.1992 unit, respectively.

  5. What makes boards effective? An examination of the relationships between board inputs, structures, processes and effectiveness in non-profit organizations

    OpenAIRE

    Cornforth, Chris

    2001-01-01

    Based on a survey of charity boards in England and Wales this paper examines what influence board inputs, structures and processes have on board effectiveness. The findings provide mixed support for the normative literature on board effectiveness. Using stepwise logistic regression the research suggests that board inputs and three process variables are important in explaining board effectiveness, namely: board members have the time, skills and experience to do the job; clear board roles and r...

  6. Leaders’ receptivity to subordinates’ creative input: the role of achievement goals and composition of creative input

    NARCIS (Netherlands)

    Sijbom, R.B.L.; Janssen, O.; van Yperen, N.W.

    2015-01-01

    We identified leaders’ achievement goals and composition of creative input as important factors that can clarify when and why leaders are receptive to, and supportive of, subordinates’ creative input. As hypothesized, in two experimental studies, we found that relative to mastery goal leaders,

  7. Relative Importance of Political Instability and Economic Variables on Perceived Country Creditworthiness

    OpenAIRE

    Suk Hun Lee

    1993-01-01

    This paper examines the relative importance of political instability and economic variables on perceived country creditworthiness. Our results indicate that both political instability and economic variables are taken into account in evaluating country creditworthiness; however, it appears that bankers assign larger weight to economic performances, which we except of reflect longer term political stability. In addition, the frequency of changes in the regime and armed conflict, both proxying f...

  8. Unitary input DEA model to identify beef cattle production systems typologies

    Directory of Open Access Journals (Sweden)

    Eliane Gonçalves Gomes

    2012-08-01

    Full Text Available The cow-calf beef production sector in Brazil has a wide variety of operating systems. This suggests the identification and the characterization of homogeneous regions of production, with consequent implementation of actions to achieve its sustainability. In this paper we attempted to measure the performance of 21 livestock modal production systems, in their cow-calf phase. We measured the performance of these systems, considering husbandry and production variables. The proposed approach is based on data envelopment analysis (DEA. We used unitary input DEA model, with apparent input orientation, together with the efficiency measurements generated by the inverted DEA frontier. We identified five modal production systems typologies, using the isoefficiency layers approach. The results showed that the knowledge and the processes management are the most important factors for improving the efficiency of beef cattle production systems.

  9. Optimal Input Design for Aircraft Parameter Estimation using Dynamic Programming Principles

    Science.gov (United States)

    Morelli, Eugene A.; Klein, Vladislav

    1990-01-01

    A new technique was developed for designing optimal flight test inputs for aircraft parameter estimation experiments. The principles of dynamic programming were used for the design in the time domain. This approach made it possible to include realistic practical constraints on the input and output variables. A description of the new approach is presented, followed by an example for a multiple input linear model describing the lateral dynamics of a fighter aircraft. The optimal input designs produced by the new technique demonstrated improved quality and expanded capability relative to the conventional multiple input design method.

  10. Variability of consumer impacts from energy efficiency standards

    Energy Technology Data Exchange (ETDEWEB)

    McMahon, James E.; Liu, Xiaomin

    2000-06-15

    A typical prospective analysis of the expected impact of energy efficiency standards on consumers is based on average economic conditions (e.g., energy price) and operating characteristics. In fact, different consumers face different economic conditions and exhibit different behaviors when using an appliance. A method has been developed to characterize the variability among individual households and to calculate the life-cycle cost of appliances taking into account those differences. Using survey data, this method is applied to a distribution of consumers representing the U.S. Examples of clothes washer standards are shown for which 70-90% of the population benefit, compared to 10-30% who are expected to bear increased costs due to new standards. In some cases, sufficient data exist to distinguish among demographic subgroups (for example, low income or elderly households) who are impacted differently from the general population. Rank order correlations between the sampled input distributions and the sampled output distributions are calculated to determine which variability inputs are main factors. This ''importance analysis'' identifies the key drivers contributing to the range of results. Conversely, the importance analysis identifies variables that, while uncertain, make so little difference as to be irrelevant in deciding a particular policy. Examples will be given from analysis of water heaters to illustrate the dominance of the policy implications by a few key variables.

  11. Clinical Trials With Large Numbers of Variables: Important Advantages of Canonical Analysis.

    Science.gov (United States)

    Cleophas, Ton J

    2016-01-01

    Canonical analysis assesses the combined effects of a set of predictor variables on a set of outcome variables, but it is little used in clinical trials despite the omnipresence of multiple variables. The aim of this study was to assess the performance of canonical analysis as compared with traditional multivariate methods using multivariate analysis of covariance (MANCOVA). As an example, a simulated data file with 12 gene expression levels and 4 drug efficacy scores was used. The correlation coefficient between the 12 predictor and 4 outcome variables was 0.87 (P = 0.0001) meaning that 76% of the variability in the outcome variables was explained by the 12 covariates. Repeated testing after the removal of 5 unimportant predictor and 1 outcome variable produced virtually the same overall result. The MANCOVA identified identical unimportant variables, but it was unable to provide overall statistics. (1) Canonical analysis is remarkable, because it can handle many more variables than traditional multivariate methods such as MANCOVA can. (2) At the same time, it accounts for the relative importance of the separate variables, their interactions and differences in units. (3) Canonical analysis provides overall statistics of the effects of sets of variables, whereas traditional multivariate methods only provide the statistics of the separate variables. (4) Unlike other methods for combining the effects of multiple variables such as factor analysis/partial least squares, canonical analysis is scientifically entirely rigorous. (5) Limitations include that it is less flexible than factor analysis/partial least squares, because only 2 sets of variables are used and because multiple solutions instead of one is offered. We do hope that this article will stimulate clinical investigators to start using this remarkable method.

  12. A Framework for Categorizing Important Project Variables

    Science.gov (United States)

    Parsons, Vickie S.

    2003-01-01

    While substantial research has led to theories concerning the variables that affect project success, no universal set of such variables has been acknowledged as the standard. The identification of a specific set of controllable variables is needed to minimize project failure. Much has been hypothesized about the need to match project controls and management processes to individual projects in order to increase the chance for success. However, an accepted taxonomy for facilitating this matching process does not exist. This paper surveyed existing literature on classification of project variables. After an analysis of those proposals, a simplified categorization is offered to encourage further research.

  13. Enhanced Input in LCTL Pedagogy

    Directory of Open Access Journals (Sweden)

    Marilyn S. Manley

    2009-08-01

    Full Text Available Language materials for the more-commonly-taught languages (MCTLs often include visual input enhancement (Sharwood Smith 1991, 1993 which makes use of typographical cues like bolding and underlining to enhance the saliency of targeted forms. For a variety of reasons, this paper argues that the use of enhanced input, both visual and oral, is especially important as a tool for the lesscommonly-taught languages (LCTLs. As there continues to be a scarcity of teaching resources for the LCTLs, individual teachers must take it upon themselves to incorporate enhanced input into their own self-made materials. Specific examples of how to incorporate both visual and oral enhanced input into language teaching are drawn from the author’s own experiences teaching Cuzco Quechua. Additionally, survey results are presented from the author’s Fall 2010 semester Cuzco Quechua language students, supporting the use of both visual and oral enhanced input.

  14. Enhanced Input in LCTL Pedagogy

    Directory of Open Access Journals (Sweden)

    Marilyn S. Manley

    2010-08-01

    Full Text Available Language materials for the more-commonly-taught languages (MCTLs often include visual input enhancement (Sharwood Smith 1991, 1993 which makes use of typographical cues like bolding and underlining to enhance the saliency of targeted forms. For a variety of reasons, this paper argues that the use of enhanced input, both visual and oral, is especially important as a tool for the lesscommonly-taught languages (LCTLs. As there continues to be a scarcity of teaching resources for the LCTLs, individual teachers must take it upon themselves to incorporate enhanced input into their own self-made materials. Specific examples of how to incorporate both visual and oral enhanced input into language teaching are drawn from the author’s own experiences teaching Cuzco Quechua. Additionally, survey results are presented from the author’s Fall 2010 semester Cuzco Quechua language students, supporting the use of both visual and oral enhanced input.

  15. Liver kinetics of glucose analogs measured in pigs by PET: importance of dual-input blood sampling

    DEFF Research Database (Denmark)

    Munk, O L; Bass, L; Roelsgaard, K

    2001-01-01

    -input functions were very similar. CONCLUSION: Compartmental analysis of MG and FDG kinetics using dynamic PET data requires measurements of dual-input activity concentrations. Using the dual-input function, physiologically reasonable parameter estimates of K1, k2, and Vp were obtained, whereas the use......Metabolic processes studied by PET are quantified traditionally using compartmental models, which relate the time course of the tracer concentration in tissue to that in arterial blood. For liver studies, the use of arterial input may, however, cause systematic errors to the estimated kinetic...... parameters, because of ignorance of the dual blood supply from the hepatic artery and the portal vein to the liver. METHODS: Six pigs underwent PET after [15O]carbon monoxide inhalation, 3-O-[11C]methylglucose (MG) injection, and [18F]FDG injection. For the glucose scans, PET data were acquired for 90 min...

  16. Isotope correlation techniques for verifying input accountability measurements at a reprocessing plant

    International Nuclear Information System (INIS)

    Umezawa, H.; Nakahara, Y.

    1983-01-01

    Isotope correlation techniques were studied to verify input accountability measurements at a reprocessing plant. On the basis of a historical data bank, correlation between plutonium-to-uranium ratio and isotopic variables was derived as a function of burnup. The burnup was determined from the isotopic ratios of uranium and plutonium, too. Data treatment was therefore made in an iterative manner. The isotopic variables were defined to cover a wide spectrum of isotopes of uranium and plutonium. The isotope correlation techniques evaluated important parameters such as the fuel burnup, the most probable ratio of plutonium to uranium, and the amounts of uranium and plutonium in reprocessing batches in connection with fresh fuel fabrication data. In addition, the most probable values of isotope abundance of plutonium and uranium could be estimated from the plutonium-to-uranium ratio determined, being compared with the reported data for verification. A pocket-computer-based system was developed to enable inspectors to collect and evaluate data in a timely fashion at the input accountability measurement point by the isotope correlation techniques. The device is supported by battery power and completely independent of the operator's system. The software of the system was written in BASIC. The data input can be stored in a cassette tape and transferred into a higher level computer. The correlations used for the analysis were given as a form of analytical function. Coefficients for the function were provided relevant to the type of reactor and the initial enrichment of fuel. (author)

  17. Variability Properties of Four Million Sources in the TESS Input Catalog Observed with the Kilodegree Extremely Little Telescope Survey

    Science.gov (United States)

    Oelkers, Ryan J.; Rodriguez, Joseph E.; Stassun, Keivan G.; Pepper, Joshua; Somers, Garrett; Kafka, Stella; Stevens, Daniel J.; Beatty, Thomas G.; Siverd, Robert J.; Lund, Michael B.; Kuhn, Rudolf B.; James, David; Gaudi, B. Scott

    2018-01-01

    The Kilodegree Extremely Little Telescope (KELT) has been surveying more than 70% of the celestial sphere for nearly a decade. While the primary science goal of the survey is the discovery of transiting, large-radii planets around bright host stars, the survey has collected more than 106 images, with a typical cadence between 10–30 minutes, for more than four million sources with apparent visual magnitudes in the approximate range 7TESS Input catalog and the AAVSO Variable Star Index to precipitate the follow-up and classification of each source. The catalog is maintained as a living database on the Filtergraph visualization portal at the URL https://filtergraph.com/kelt_vars.

  18. Amplification factor variable amplifier

    NARCIS (Netherlands)

    Akitsugu, Oshita; Nauta, Bram

    2007-01-01

    PROBLEM TO BE SOLVED: To provide an amplification factor variable amplifier capable of achieving temperature compensation of an amplification factor over a wide variable amplification factor range. ; SOLUTION: A Gilbert type amplification factor variable amplifier 11 amplifies an input signal and

  19. Screening of variable importance for optimizing electrodialytic remediation of heavy metals from polluted harbour sediments

    DEFF Research Database (Denmark)

    Pedersen, Kristine B.; Lejon, Tore; Ottosen, Lisbeth M.

    2015-01-01

    Using multivariate design and modelling, the optimal conditions for electrodialytic remediation (EDR) of heavy metals were determined for polluted harbour sediments from Hammerfest harbour located in the geographic Arctic region of Norway. The comparative importance of the variables, current......) was computed and variable importance in the projection was used to assess the influence of the experimental variables. Current density and remediation time proved to have the highest influence on the remediation of the heavy metals Cr, Cu, Ni, Pb and Zn in the studied experimental domain. In addition......, it was shown that excluding the acidification time improved the PLS model, indicating the importance of applying a limited experimental domain that covers the removal phases of each heavy metal in the specific sediment. Based on PLS modelling, the optimal conditions for remediating the Hammerfest sediment were...

  20. Identification of input variables for feature based artificial neural networks-saccade detection in EOG recordings.

    Science.gov (United States)

    Tigges, P; Kathmann, N; Engel, R R

    1997-07-01

    Though artificial neural networks (ANN) are excellent tools for pattern recognition problems when signal to noise ratio is low, the identification of decision relevant features for ANN input data is still a crucial issue. The experience of the ANN designer and the existing knowledge and understanding of the problem seem to be the only links for a specific construction. In the present study a backpropagation ANN based on modified raw data inputs showed encouraging results. Investigating the specific influences of prototypical input patterns on a specially designed ANN led to a new sparse and efficient input data presentation. This data coding obtained by a semiautomatic procedure combining existing expert knowledge and the internal representation structures of the raw data based ANN yielded a list of feature vectors, each representing the relevant information for saccade identification. The feature based ANN produced a reduction of the error rate of nearly 40% compared with the raw data ANN. An overall correct classification of 92% of so far unknown data was realized. The proposed method of extracting internal ANN knowledge for the production of a better input data representation is not restricted to EOG recordings, and could be used in various fields of signal analysis.

  1. Repositioning Recitation Input in College English Teaching

    Science.gov (United States)

    Xu, Qing

    2009-01-01

    This paper tries to discuss how recitation input helps overcome the negative influences on the basis of second language acquisition theory and confirms the important role that recitation input plays in improving college students' oral and written English.

  2. Knowledge Protection and Input Complexity Arising from Open Innovation

    DEFF Research Database (Denmark)

    Peeters, Thijs; Sofka, Wolfgang

    Controlling unique knowledge is of increasing importance to firms. Therefore, firms use knowledge protection mechanisms to prevent competitors from imitating their knowledge. We study the effects of the complexity of knowledge inputs that arises from open innovation on the importance of two widely...... used protection mechanisms: patents and trademarks. We argue that this complexity makes the threat of imitation less predictable, and thus makes knowledge protection more important. By analyzing survey data of 938 German firms, we find that patents are more important for firms in industries with higher...... knowledge input complexity. Furthermore, we show that the dynamics and not the level of knowledge input complexity positively affect the importance of trademarks....

  3. Amplification factor variable amplifier

    NARCIS (Netherlands)

    Akitsugu, Oshita; Nauta, Bram

    2010-01-01

    PROBLEM TO BE SOLVED: To provide an amplification factor variable amplifier capable of achieving temperature compensation of an amplification factor over a wide variable amplification factor range. ;SOLUTION: A Gilbert type amplification factor variable amplifier 11 amplifies an input signal and can

  4. Tritium Records to Trace Stratospheric Moisture Inputs in Antarctica

    Science.gov (United States)

    Fourré, E.; Landais, A.; Cauquoin, A.; Jean-Baptiste, P.; Lipenkov, V.; Petit, J.-R.

    2018-03-01

    Better assessing the dynamic of stratosphere-troposphere exchange is a key point to improve our understanding of the climate dynamic in the East Antarctica Plateau, a region where stratospheric inputs are expected to be important. Although tritium (3H or T), a nuclide naturally produced mainly in the stratosphere and rapidly entering the water cycle as HTO, seems a first-rate tracer to study these processes, tritium data are very sparse in this region. We present the first high-resolution measurements of tritium concentration over the last 50 years in three snow pits drilled at the Vostok station. Natural variability of the tritium records reveals two prominent frequencies, one at about 10 years (to be related to the solar Schwabe cycles) and the other one at a shorter periodicity: despite dating uncertainty at this short scale, a good correlation is observed between 3H and Na+ and an anticorrelation between 3H and δ18O measured on an individual pit. The outputs from the LMDZ Atmospheric General Circulation Model including stable water isotopes and tritium show the same 3H-δ18O anticorrelation and allow further investigation on the associated mechanism. At the interannual scale, the modeled 3H variability matches well with the Southern Annular Mode index. At the seasonal scale, we show that modeled stratospheric tritium inputs in the troposphere are favored in winter cold and dry conditions.

  5. In-process tool rotational speed variation with constant heat input in friction stir welding of AZ31 sheets with variable thickness

    Science.gov (United States)

    Buffa, Gianluca; Campanella, Davide; Forcellese, Archimede; Fratini, Livan; Simoncini, Michela

    2017-10-01

    In the present work, friction stir welding experiments on AZ31 magnesium alloy sheets, characterized by a variable thickness along the welding line, were carried out. The approach adapted during welding consisted in maintaining constant the heat input to the joint. To this purpose, the rotational speed of the pin tool was increased with decreasing thickness and decreased with increasing thickness in order to obtain the same temperatures during welding. The amount by which the rotational speed was changed as a function of the sheet thickness was defined on the basis of the results given by FEM simulations of the FSW process. Finally, the effect of the in-process variation of the tool rotational speed on the mechanical and microstructural properties of FSWed joints was analysed by comparing both the nominal stress vs. nominal strain curves and microstructure of FSWed joints obtained in different process conditions. It was observed that FSW performed by keeping constant the heat input to the joint leads to almost coincident results both in terms of the curve shape, ultimate tensile strength and ultimate elongation values, and microstructure.

  6. A new chance-constrained DEA model with birandom input and output data

    OpenAIRE

    Tavana, M.; Shiraz, R. K.; Hatami-Marbini, A.

    2013-01-01

    The purpose of conventional Data Envelopment Analysis (DEA) is to evaluate the performance of a set of firms or Decision-Making Units using deterministic input and output data. However, the input and output data in the real-life performance evaluation problems are often stochastic. The stochastic input and output data in DEA can be represented with random variables. Several methods have been proposed to deal with the random input and output data in DEA. In this paper, we propose a new chance-...

  7. The Economic Impact of Tourism. An Input-Output Analysis

    OpenAIRE

    Camelia SURUGIU

    2009-01-01

    The paper presents an Input-Output Analysis for Romania, an important source of information for the investigation of the inter-relations existing among different industries. The Input-Output Analysis is used to determine the role and importance of different economic value added, incomes and employment and it analyses the existing connection in an economy. This paper is focused on tourism and the input-output analysis is finished for the Hotels and Restaurants Sector.

  8. The importance of immune gene variability (MHC in evolutionary ecology and conservation

    Directory of Open Access Journals (Sweden)

    Sommer Simone

    2005-10-01

    Full Text Available Abstract Genetic studies have typically inferred the effects of human impact by documenting patterns of genetic differentiation and levels of genetic diversity among potentially isolated populations using selective neutral markers such as mitochondrial control region sequences, microsatellites or single nucleotide polymorphism (SNPs. However, evolutionary relevant and adaptive processes within and between populations can only be reflected by coding genes. In vertebrates, growing evidence suggests that genetic diversity is particularly important at the level of the major histocompatibility complex (MHC. MHC variants influence many important biological traits, including immune recognition, susceptibility to infectious and autoimmune diseases, individual odours, mating preferences, kin recognition, cooperation and pregnancy outcome. These diverse functions and characteristics place genes of the MHC among the best candidates for studies of mechanisms and significance of molecular adaptation in vertebrates. MHC variability is believed to be maintained by pathogen-driven selection, mediated either through heterozygote advantage or frequency-dependent selection. Up to now, most of our knowledge has derived from studies in humans or from model organisms under experimental, laboratory conditions. Empirical support for selective mechanisms in free-ranging animal populations in their natural environment is rare. In this review, I first introduce general information about the structure and function of MHC genes, as well as current hypotheses and concepts concerning the role of selection in the maintenance of MHC polymorphism. The evolutionary forces acting on the genetic diversity in coding and non-coding markers are compared. Then, I summarise empirical support for the functional importance of MHC variability in parasite resistance with emphasis on the evidence derived from free-ranging animal populations investigated in their natural habitat. Finally, I

  9. R Package multiPIM: A Causal Inference Approach to Variable Importance Analysis

    Directory of Open Access Journals (Sweden)

    Stephan J Ritter

    2014-04-01

    Full Text Available We describe the R package multiPIM, including statistical background, functionality and user options. The package is for variable importance analysis, and is meant primarily for analyzing data from exploratory epidemiological studies, though it could certainly be applied in other areas as well. The approach taken to variable importance comes from the causal inference field, and is different from approaches taken in other R packages. By default, multiPIM uses a double robust targeted maximum likelihood estimator (TMLE of a parameter akin to the attributable risk. Several regression methods/machine learning algorithms are available for estimating the nuisance parameters of the models, including super learner, a meta-learner which combines several different algorithms into one. We describe a simulation in which the double robust TMLE is compared to the graphical computation estimator. We also provide example analyses using two data sets which are included with the package.

  10. Latitudinal and seasonal variability of the micrometeor input function: A study using model predictions and observations from Arecibo and PFISR

    Science.gov (United States)

    Fentzke, J. T.; Janches, D.; Sparks, J. J.

    2009-05-01

    In this work, we use a semi-empirical model of the micrometeor input function (MIF) together with meteor head-echo observations obtained with two high power and large aperture (HPLA) radars, the 430 MHz Arecibo Observatory (AO) radar in Puerto Rico (18°N, 67°W) and the 450 MHz Poker flat incoherent scatter radar (PFISR) in Alaska (65°N, 147°W), to study the seasonal and geographical dependence of the meteoric flux in the upper atmosphere. The model, recently developed by Janches et al. [2006a. Modeling the global micrometeor input function in the upper atmosphere observed by high power and large aperture radars. Journal of Geophysical Research 111] and Fentzke and Janches [2008. A semi-empirical model of the contribution from sporadic meteoroid sources on the meteor input function observed at arecibo. Journal of Geophysical Research (Space Physics) 113 (A03304)], includes an initial mass flux that is provided by the six known meteor sources (i.e. orbital families of dust) as well as detailed modeling of meteoroid atmospheric entry and ablation physics. In addition, we use a simple ionization model to treat radar sensitivity issues by defining minimum electron volume density production thresholds required in the meteor head-echo plasma for detection. This simplified approach works well because we use observations from two radars with similar frequencies, but different sensitivities and locations. This methodology allows us to explore the initial input of particles and how it manifests in different parts of the MLT as observed by these instruments without the need to invoke more sophisticated plasma models, which are under current development. The comparisons between model predictions and radar observations show excellent agreement between diurnal, seasonal, and latitudinal variability of the detected meteor rate and radial velocity distributions, allowing us to understand how individual meteoroid populations contribute to the overall flux at a particular

  11. Role of updraft velocity in temporal variability of global cloud hydrometeor number

    Science.gov (United States)

    Sullivan, Sylvia C.; Lee, Dongmin; Oreopoulos, Lazaros; Nenes, Athanasios

    2016-05-01

    Understanding how dynamical and aerosol inputs affect the temporal variability of hydrometeor formation in climate models will help to explain sources of model diversity in cloud forcing, to provide robust comparisons with data, and, ultimately, to reduce the uncertainty in estimates of the aerosol indirect effect. This variability attribution can be done at various spatial and temporal resolutions with metrics derived from online adjoint sensitivities of droplet and crystal number to relevant inputs. Such metrics are defined and calculated from simulations using the NASA Goddard Earth Observing System Model, Version 5 (GEOS-5) and the National Center for Atmospheric Research Community Atmosphere Model Version 5.1 (CAM5.1). Input updraft velocity fluctuations can explain as much as 48% of temporal variability in output ice crystal number and 61% in droplet number in GEOS-5 and up to 89% of temporal variability in output ice crystal number in CAM5.1. In both models, this vertical velocity attribution depends strongly on altitude. Despite its importance for hydrometeor formation, simulated vertical velocity distributions are rarely evaluated against observations due to the sparsity of relevant data. Coordinated effort by the atmospheric community to develop more consistent, observationally based updraft treatments will help to close this knowledge gap.

  12. Numeric Input Relations for Relational Learning with Applications to Community Structure Analysis

    DEFF Research Database (Denmark)

    Jiang, Jiuchuan; Jaeger, Manfred

    2015-01-01

    distribution is defined by the model from numerical input variables that are only used for conditioning the distribution of discrete response variables. We show how numerical input relations can very easily be used in the Relational Bayesian Network framework, and that existing inference and learning methods......Most work in the area of statistical relational learning (SRL) is focussed on discrete data, even though a few approaches for hybrid SRL models have been proposed that combine numerical and discrete variables. In this paper we distinguish numerical random variables for which a probability...... use the augmented RBN framework to define probabilistic models for multi-relational (social) networks in which the probability of a link between two nodes depends on numeric latent feature vectors associated with the nodes. A generic learning procedure can be used to obtain a maximum-likelihood fit...

  13. Increasing importance of precipitation variability on global livestock grazing lands

    Science.gov (United States)

    Sloat, Lindsey L.; Gerber, James S.; Samberg, Leah H.; Smith, William K.; Herrero, Mario; Ferreira, Laerte G.; Godde, Cécile M.; West, Paul C.

    2018-03-01

    Pastures and rangelands underpin global meat and milk production and are a critical resource for millions of people dependent on livestock for food security1,2. Forage growth, which is highly climate dependent3,4, is potentially vulnerable to climate change, although precisely where and to what extent remains relatively unexplored. In this study, we assess climate-based threats to global pastures, with a specific focus on changes in within- and between-year precipitation variability (precipitation concentration index (PCI) and coefficient of variation of precipitation (CVP), respectively). Relating global satellite measures of vegetation greenness (such as the Normalized Difference Vegetation Index; NDVI) to key climatic factors reveals that CVP is a significant, yet often overlooked, constraint on vegetation productivity across global pastures. Using independent stocking data, we found that areas with high CVP support lower livestock densities than less-variable regions. Globally, pastures experience about a 25% greater year-to-year precipitation variation (CVP = 0.27) than the average global land surface area (0.21). Over the past century, CVP has generally increased across pasture areas, although both positive (49% of pasture area) and negative (31% of pasture area) trends exist. We identify regions in which livestock grazing is important for local food access and economies, and discuss the potential for pasture intensification in the context of long-term regional trends in precipitation variability.

  14. Egocentric and allocentric alignment tasks are affected by otolith input.

    Science.gov (United States)

    Tarnutzer, Alexander A; Bockisch, Christopher J; Olasagasti, Itsaso; Straumann, Dominik

    2012-06-01

    Gravicentric visual alignments become less precise when the head is roll-tilted relative to gravity, which is most likely due to decreasing otolith sensitivity. To align a luminous line with the perceived gravity vector (gravicentric task) or the perceived body-longitudinal axis (egocentric task), the roll orientation of the line on the retina and the torsional position of the eyes relative to the head must be integrated to obtain the line orientation relative to the head. Whether otolith input contributes to egocentric tasks and whether the modulation of variability is restricted to vision-dependent paradigms is unknown. In nine subjects we compared precision and accuracy of gravicentric and egocentric alignments in various roll positions (upright, 45°, and 75° right-ear down) using a luminous line (visual paradigm) in darkness. Trial-to-trial variability doubled for both egocentric and gravicentric alignments when roll-tilted. Two mechanisms might explain the roll-angle-dependent modulation in egocentric tasks: 1) Modulating variability in estimated ocular torsion, which reflects the roll-dependent precision of otolith signals, affects the precision of estimating the line orientation relative to the head; this hypothesis predicts that variability modulation is restricted to vision-dependent alignments. 2) Estimated body-longitudinal reflects the roll-dependent variability of perceived earth-vertical. Gravicentric cues are thereby integrated regardless of the task's reference frame. To test the two hypotheses the visual paradigm was repeated using a rod instead (haptic paradigm). As with the visual paradigm, precision significantly decreased with increasing head roll for both tasks. These findings propose that the CNS integrates input coded in a gravicentric frame to solve egocentric tasks. In analogy to gravicentric tasks, where trial-to-trial variability is mainly influenced by the properties of the otolith afferents, egocentric tasks may also integrate

  15. A Simple K-Map Based Variable Selection Scheme in the Direct ...

    African Journals Online (AJOL)

    A multiplexer with (n-l) data select inputs can realise directly a function of n variables. In this paper, a simple k-map based variable selection scheme is proposed such that an n variable logic function can be synthesised using a multiplexer with (n-q) data input variables and q data select variables. The procedure is based on ...

  16. A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data

    KAUST Repository

    Babuška, Ivo; Nobile, Fabio; Tempone, Raul

    2010-01-01

    This work proposes and analyzes a stochastic collocation method for solving elliptic partial differential equations with random coefficients and forcing terms. These input data are assumed to depend on a finite number of random variables. The method consists of a Galerkin approximation in space and a collocation in the zeros of suitable tensor product orthogonal polynomials (Gauss points) in the probability space, and naturally leads to the solution of uncoupled deterministic problems as in the Monte Carlo approach. It treats easily a wide range of situations, such as input data that depend nonlinearly on the random variables, diffusivity coefficients with unbounded second moments, and random variables that are correlated or even unbounded. We provide a rigorous convergence analysis and demonstrate exponential convergence of the “probability error” with respect to the number of Gauss points in each direction of the probability space, under some regularity assumptions on the random input data. Numerical examples show the effectiveness of the method. Finally, we include a section with developments posterior to the original publication of this work. There we review sparse grid stochastic collocation methods, which are effective collocation strategies for problems that depend on a moderately large number of random variables.

  17. Plasticity of the cis-regulatory input function of a gene.

    Directory of Open Access Journals (Sweden)

    Avraham E Mayo

    2006-04-01

    Full Text Available The transcription rate of a gene is often controlled by several regulators that bind specific sites in the gene's cis-regulatory region. The combined effect of these regulators is described by a cis-regulatory input function. What determines the form of an input function, and how variable is it with respect to mutations? To address this, we employ the well-characterized lac operon of Escherichia coli, which has an elaborate input function, intermediate between Boolean AND-gate and OR-gate logic. We mapped in detail the input function of 12 variants of the lac promoter, each with different point mutations in the regulator binding sites, by means of accurate expression measurements from living cells. We find that even a few mutations can significantly change the input function, resulting in functions that resemble Pure AND gates, OR gates, or single-input switches. Other types of gates were not found. The variant input functions can be described in a unified manner by a mathematical model. The model also lets us predict which functions cannot be reached by point mutations. The input function that we studied thus appears to be plastic, in the sense that many of the mutations do not ruin the regulation completely but rather result in new ways to integrate the inputs.

  18. Chaos Synchronization Based on Unknown Input Proportional Multiple-Integral Fuzzy Observer

    Directory of Open Access Journals (Sweden)

    T. Youssef

    2013-01-01

    Full Text Available This paper presents an unknown input Proportional Multiple-Integral Observer (PIO for synchronization of chaotic systems based on Takagi-Sugeno (TS fuzzy chaotic models subject to unmeasurable decision variables and unknown input. In a secure communication configuration, this unknown input is regarded as a message encoded in the chaotic system and recovered by the proposed PIO. Both states and outputs of the fuzzy chaotic models are subject to polynomial unknown input with kth derivative zero. Using Lyapunov stability theory, sufficient design conditions for synchronization are proposed. The PIO gains matrices are obtained by resolving linear matrix inequalities (LMIs constraints. Simulation results show through two TS fuzzy chaotic models the validity of the proposed method.

  19. Input/Output linearizing control of a nuclear reactor

    International Nuclear Information System (INIS)

    Perez C, V.

    1994-01-01

    The feedback linearization technique is an approach to nonlinear control design. The basic idea is to transform, by means of algebraic methods, the dynamics of a nonlinear control system into a full or partial linear system. As a result of this linearization process, the well known basic linear control techniques can be used to obtain some desired dynamic characteristics. When full linearization is achieved, the method is referred to as input-state linearization, whereas when partial linearization is achieved, the method is referred to as input-output linearization. We will deal with the latter. By means of input-output linearization, the dynamics of a nonlinear system can be decomposed into an external part (input-output), and an internal part (unobservable). Since the external part consists of a linear relationship among the output of the plant and the auxiliary control input mentioned above, it is easy to design such an auxiliary control input so that we get the output to behave in a predetermined way. Since the internal dynamics of the system is known, we can check its dynamics behavior on order of to ensure that the internal states are bounded. The linearization method described here can be applied to systems with one-input/one-output, as well as to systems with multiple-inputs/multiple-outputs. Typical control problems such as stabilization and reference path tracking can be solved using this technique. In this work, the input/output linearization theory is presented, as well as the problem of getting the output variable to track some desired trayectories. Further, the design of an input/output control system applied to the nonlinear model of a research nuclear reactor is included, along with the results obtained by computer simulation. (Author)

  20. Role of environmental variables on radon concentration in soil

    International Nuclear Information System (INIS)

    Climent, H.; Bakalowicz, M.; Monnin, M.

    1998-01-01

    In the frame of an European project, radon concentrations in soil and measurements of environmental variables such as the nature of the soil or climatic variables were monitored. The data have been analysed by time-series analysis methods, i.e. Correlation and Spectrum Analysis, to point out relations between radon concentrations and some environmental variables. This approach is a compromise between direct observation and modelling. The observation of the rough time series is unable to point out the relation between radon concentrations and an environmental variable because of the overlapping of the influences of several variables, and the time delay induced by the medium. The Cross Spectrum function between the time series of radon and of an environmental variable describes the nature of the relation and gives the response time in the case of a cause to effect relation. It requires the only hypothesis that the environmental variable is the input function and radon concentration the output function. This analysis is an important preliminary study for modelling. By that way the importance of soil nature has been pointed out. The internal variables of the medium (permeability, porosity) appear to restrain the influence of the environmental variables such as humidity, temperature or atmospheric pressure. (author)

  1. Sequential estimation of intrinsic activity and synaptic input in single neurons by particle filtering with optimal importance density

    Science.gov (United States)

    Closas, Pau; Guillamon, Antoni

    2017-12-01

    This paper deals with the problem of inferring the signals and parameters that cause neural activity to occur. The ultimate challenge being to unveil brain's connectivity, here we focus on a microscopic vision of the problem, where single neurons (potentially connected to a network of peers) are at the core of our study. The sole observation available are noisy, sampled voltage traces obtained from intracellular recordings. We design algorithms and inference methods using the tools provided by stochastic filtering that allow a probabilistic interpretation and treatment of the problem. Using particle filtering, we are able to reconstruct traces of voltages and estimate the time course of auxiliary variables. By extending the algorithm, through PMCMC methodology, we are able to estimate hidden physiological parameters as well, like intrinsic conductances or reversal potentials. Last, but not least, the method is applied to estimate synaptic conductances arriving at a target cell, thus reconstructing the synaptic excitatory/inhibitory input traces. Notably, the performance of these estimations achieve the theoretical lower bounds even in spiking regimes.

  2. Value of Construction Company and its Dependence on Significant Variables

    Science.gov (United States)

    Vítková, E.; Hromádka, V.; Ondrušková, E.

    2017-10-01

    The paper deals with the value of the construction company assessment respecting usable approaches and determinable variables. The reasons of the value of the construction company assessment are different, but the most important reasons are the sale or the purchase of the company, the liquidation of the company, the fusion of the company with another subject or the others. According the reason of the value assessment it is possible to determine theoretically different approaches for valuation, mainly it concerns about the yield method of valuation and the proprietary method of valuation. Both approaches are dependant of detailed input variables, which quality will influence the final assessment of the company´s value. The main objective of the paper is to suggest, according to the analysis, possible ways of input variables, mainly in the form of expected cash-flows or the profit, determination. The paper is focused mainly on methods of time series analysis, regression analysis and mathematical simulation utilization. As the output, the results of the analysis on the case study will be demonstrated.

  3. Variable screening and ranking using sampling-based sensitivity measures

    International Nuclear Information System (INIS)

    Wu, Y-T.; Mohanty, Sitakanta

    2006-01-01

    This paper presents a methodology for screening insignificant random variables and ranking significant important random variables using sensitivity measures including two cumulative distribution function (CDF)-based and two mean-response based measures. The methodology features (1) using random samples to compute sensitivities and (2) using acceptance limits, derived from the test-of-hypothesis, to classify significant and insignificant random variables. Because no approximation is needed in either the form of the performance functions or the type of continuous distribution functions representing input variables, the sampling-based approach can handle highly nonlinear functions with non-normal variables. The main characteristics and effectiveness of the sampling-based sensitivity measures are investigated using both simple and complex examples. Because the number of samples needed does not depend on the number of variables, the methodology appears to be particularly suitable for problems with large, complex models that have large numbers of random variables but relatively few numbers of significant random variables

  4. Response sensitivity of barrel neuron subpopulations to simulated thalamic input.

    Science.gov (United States)

    Pesavento, Michael J; Rittenhouse, Cynthia D; Pinto, David J

    2010-06-01

    Our goal is to examine the relationship between neuron- and network-level processing in the context of a well-studied cortical function, the processing of thalamic input by whisker-barrel circuits in rodent neocortex. Here we focus on neuron-level processing and investigate the responses of excitatory and inhibitory barrel neurons to simulated thalamic inputs applied using the dynamic clamp method in brain slices. Simulated inputs are modeled after real thalamic inputs recorded in vivo in response to brief whisker deflections. Our results suggest that inhibitory neurons require more input to reach firing threshold, but then fire earlier, with less variability, and respond to a broader range of inputs than do excitatory neurons. Differences in the responses of barrel neuron subtypes depend on their intrinsic membrane properties. Neurons with a low input resistance require more input to reach threshold but then fire earlier than neurons with a higher input resistance, regardless of the neuron's classification. Our results also suggest that the response properties of excitatory versus inhibitory barrel neurons are consistent with the response sensitivities of the ensemble barrel network. The short response latency of inhibitory neurons may serve to suppress ensemble barrel responses to asynchronous thalamic input. Correspondingly, whereas neurons acting as part of the barrel circuit in vivo are highly selective for temporally correlated thalamic input, excitatory barrel neurons acting alone in vitro are less so. These data suggest that network-level processing of thalamic input in barrel cortex depends on neuron-level processing of the same input by excitatory and inhibitory barrel neurons.

  5. Does Input Quality Drive Measured Differences in Firm Productivity?

    DEFF Research Database (Denmark)

    Fox, Jeremy T.; Smeets, Valerie Anne Rolande

    is roughly of the same order of magnitude as some competitive effects found in the literature, but input quality measures do not explain most productivity dispersion, despite economically large production function coefficients. We find that the wage bill explains as much dispersion as human capital measures.......Firms in the same industry can differ in measured productivity by multiples of 3. Griliches (1957) suggests one explanation: the quality of inputs differs across firms. We add labor market history variables such as experience and firm and industry tenure, as well as general human capital measures...

  6. Complex analyses of inverted repeats in mitochondrial genomes revealed their importance and variability.

    Science.gov (United States)

    Cechová, Jana; Lýsek, Jirí; Bartas, Martin; Brázda, Václav

    2018-04-01

    The NCBI database contains mitochondrial DNA (mtDNA) genomes from numerous species. We investigated the presence and locations of inverted repeat sequences (IRs) in these mtDNA sequences, which are known to be important for regulating nuclear genomes. IRs were identified in mtDNA in all species. IR lengths and frequencies correlate with evolutionary age and the greatest variability was detected in subgroups of plants and fungi and the lowest variability in mammals. IR presence is non-random and evolutionary favoured. The frequency of IRs generally decreased with IR length, but not for IRs 24 or 30 bp long, which are 1.5 times more abundant. IRs are enriched in sequences from the replication origin, followed by D-loop, stem-loop and miscellaneous sequences, pointing to the importance of IRs in regulatory regions of mitochondrial DNA. Data were produced using Palindrome analyser, freely available on the web at http://bioinformatics.ibp.cz. vaclav@ibp.cz. Supplementary data are available at Bioinformatics online.

  7. THE RELATIVE IMPORTANCE OF FINANCIAL RATIOS AND NONFINANCIAL VARIABLES IN PREDICTING OF INSOLVENCY

    Directory of Open Access Journals (Sweden)

    Ivica Pervan

    2013-02-01

    Full Text Available One of the most important decisions in every bank is approving loans to firms, which is based on evaluated credit risk and collateral. Namely, it is necessary to evaluate the risk that client will be unable to repay the obligations according to the contract. After Beaver's (1967 and Altman's (1968 seminal papers many authors extended the initial research by changing the methodology, samples, countries, etc. But majority of business failure papers as predictors use financial ratios, while in the real life banks combine financial and nonfinancial variables. In order to test predictive power of nonfinancial variables authors in the paper compare two insolvency prediction models. The first model that used financial rations resulted with classification accuracy of 82.8%, while the combined model with financial and nonfinancial variables resulted with classification accuracy of 88.1%.

  8. Ensemble standar deviation of wind speed and direction of the FDDA input to WRF

    Data.gov (United States)

    U.S. Environmental Protection Agency — NetCDF file of the SREF standard deviation of wind speed and direction that was used to inject variability in the FDDA input. variable U_NDG_OLD contains standard...

  9. A Method to Select Software Test Cases in Consideration of Past Input Sequence

    International Nuclear Information System (INIS)

    Kim, Hee Eun; Kim, Bo Gyung; Kang, Hyun Gook

    2015-01-01

    In the Korea Nuclear I and C Systems (KNICS) project, the software for the fully-digitalized reactor protection system (RPS) was developed under a strict procedure. Even though the behavior of the software is deterministic, the randomness of input sequence produces probabilistic behavior of software. A software failure occurs when some inputs to the software occur and interact with the internal state of the digital system to trigger a fault that was introduced into the software during the software lifecycle. In this paper, the method to select test set for software failure probability estimation is suggested. This test set reflects past input sequence of software, which covers all possible cases. In this study, the method to select test cases for software failure probability quantification was suggested. To obtain profile of paired state variables, relationships of the variables need to be considered. The effect of input from human operator also have to be considered. As an example, test set of PZR-PR-Lo-Trip logic was examined. This method provides framework for selecting test cases of safety-critical software

  10. A robust hybrid model integrating enhanced inputs based extreme learning machine with PLSR (PLSR-EIELM) and its application to intelligent measurement.

    Science.gov (United States)

    He, Yan-Lin; Geng, Zhi-Qiang; Xu, Yuan; Zhu, Qun-Xiong

    2015-09-01

    In this paper, a robust hybrid model integrating an enhanced inputs based extreme learning machine with the partial least square regression (PLSR-EIELM) was proposed. The proposed PLSR-EIELM model can overcome two main flaws in the extreme learning machine (ELM), i.e. the intractable problem in determining the optimal number of the hidden layer neurons and the over-fitting phenomenon. First, a traditional extreme learning machine (ELM) is selected. Second, a method of randomly assigning is applied to the weights between the input layer and the hidden layer, and then the nonlinear transformation for independent variables can be obtained from the output of the hidden layer neurons. Especially, the original input variables are regarded as enhanced inputs; then the enhanced inputs and the nonlinear transformed variables are tied together as the whole independent variables. In this way, the PLSR can be carried out to identify the PLS components not only from the nonlinear transformed variables but also from the original input variables, which can remove the correlation among the whole independent variables and the expected outputs. Finally, the optimal relationship model of the whole independent variables with the expected outputs can be achieved by using PLSR. Thus, the PLSR-EIELM model is developed. Then the PLSR-EIELM model served as an intelligent measurement tool for the key variables of the Purified Terephthalic Acid (PTA) process and the High Density Polyethylene (HDPE) process. The experimental results show that the predictive accuracy of PLSR-EIELM is stable, which indicate that PLSR-EIELM has good robust character. Moreover, compared with ELM, PLSR, hierarchical ELM (HELM), and PLSR-ELM, PLSR-EIELM can achieve much smaller predicted relative errors in these two applications. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  11. Global sensitivity analysis of computer models with functional inputs

    International Nuclear Information System (INIS)

    Iooss, Bertrand; Ribatet, Mathieu

    2009-01-01

    Global sensitivity analysis is used to quantify the influence of uncertain model inputs on the response variability of a numerical model. The common quantitative methods are appropriate with computer codes having scalar model inputs. This paper aims at illustrating different variance-based sensitivity analysis techniques, based on the so-called Sobol's indices, when some model inputs are functional, such as stochastic processes or random spatial fields. In this work, we focus on large cpu time computer codes which need a preliminary metamodeling step before performing the sensitivity analysis. We propose the use of the joint modeling approach, i.e., modeling simultaneously the mean and the dispersion of the code outputs using two interlinked generalized linear models (GLMs) or generalized additive models (GAMs). The 'mean model' allows to estimate the sensitivity indices of each scalar model inputs, while the 'dispersion model' allows to derive the total sensitivity index of the functional model inputs. The proposed approach is compared to some classical sensitivity analysis methodologies on an analytical function. Lastly, the new methodology is applied to an industrial computer code that simulates the nuclear fuel irradiation.

  12. Effect of variable heat input on the heat transfer characteristics in an Organic Rankine Cycle system

    Directory of Open Access Journals (Sweden)

    Aboaltabooq Mahdi Hatf Kadhum

    2016-01-01

    Full Text Available This paper analyzes the heat transfer characteristics of an ORC evaporator applied on a diesel engine using measured data from experimental work such as flue gas mass flow rate and flue gas temperature. A mathematical model was developed with regard to the preheater, boiler and the superheater zones of a counter flow evaporator. Each of these zones has been subdivided into a number of cells. The hot source of the ORC cycle was modeled. The study involves the variable heat input's dependence on the ORC system's heat transfer characteristics, with especial emphasis on the evaporator. The results show that the refrigerant's heat transfer coefficient has a higher value for a 100% load from the diesel engine, and decreases with the load decrease. Also, on the exhaust gas side, the heat transfer coefficient decreases with the decrease of the load. The refrigerant's heat transfer coefficient increased normally with the evaporator's tube length in the preheater zone, and then increases rapidly in the boiler zone, followed by a decrease in the superheater zone. The exhaust gases’ heat transfer coefficient increased with the evaporator’ tube length in all zones. The results were compared with result by other authors and were found to be in agreement.

  13. Energy assessment of nitrogen variable rate fertilization on wheat; Analise energetica da aplicacao de nitrogenio em taxa variavel em trigo

    Energy Technology Data Exchange (ETDEWEB)

    Colaco, A.F.; Karam, E.H.; Romanelli, T.L.; Molin, J.P. [Escola Superior de Agricultura Luiz Queiroz (ESALQ/USP), Piracicaba, SP (Brazil). Dept. de Engenharia de Biossistemas], Email: andrecolaco@usp.br; Povh, F.P. [Fundacao ABC Pesquisa e Desenvolvimento Agropecuario, Castro, PR (Brazil)

    2011-07-01

    Precision Agriculture (PA) is a technique that can reduce the inputs utilization in agriculture production, including the nitrogen fertilizer consume. Great importance is given to this fertilizer, due to its contribution on energy input in agriculture. Methodologies based on the calculation of energy flow of agriculture systems are capable to identify management practices that use energy more efficiently. So, this study's objective is to evaluate the variable-rate nitrogen fertilization on wheat, using energy assessment. This study was carried on in two wheat fields, in which the fertilization was done adopting strips alternated by conventional method (single nitrogen dose) and by nitrogen variable-rate technology. Thus, the input and output energy in the system, energy balance, energy return on investment (EROI) and incorporated energy were determined for each geo-referenced point within the fields. Results showed that less energy was demanded when using variable-rate technology, due to the nitrogen saving, providing greater energy balance, EROI and lower incorporated energy on the areas managed using PA. The energy assessment showed to be an important tool to evaluate systems that use PA, because it is capable of monitoring crops energy potential. (author)

  14. Heat input control in coke ovens battery using artificial intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, R.; Kannan, C.; Sistla, S.; Kumar, D. [Tata Steel, Jamshedpur (India)

    2005-07-01

    Controlled heating is very essential for producing coke with certain desired properties. Controlled heating involves controlling the heat input into the battery dynamically depending on the various process parameters like current battery temperature, the set point of battery temperature, moisture in coal, ambient temperature, coal fineness, cake breakage etc. An artificial intelligence (AI) based heat input control has been developed in which currently some of the above mentioned process parameters are considered and used for calculating the pause time which is applied between reversal during the heating process. The AI based model currently considers 3 input variables, temperature deviation history, current deviation of the battery temperature from the target temperature and the actual heat input into the battery. Work is in progress to control the standard deviation of coke end temperature using this model. The new system which has been developed in-house has replaced Hoogovens supplied model. 7 figs.

  15. FLUTAN input specifications

    International Nuclear Information System (INIS)

    Borgwaldt, H.; Baumann, W.; Willerding, G.

    1991-05-01

    FLUTAN is a highly vectorized computer code for 3-D fluiddynamic and thermal-hydraulic analyses in cartesian and cylinder coordinates. It is related to the family of COMMIX codes originally developed at Argonne National Laboratory, USA. To a large extent, FLUTAN relies on basic concepts and structures imported from COMMIX-1B and COMMIX-2 which were made available to KfK in the frame of cooperation contracts in the fast reactor safety field. While on the one hand not all features of the original COMMIX versions have been implemented in FLUTAN, the code on the other hand includes some essential innovative options like CRESOR solution algorithm, general 3-dimensional rebalacing scheme for solving the pressure equation, and LECUSSO-QUICK-FRAM techniques suitable for reducing 'numerical diffusion' in both the enthalphy and momentum equations. This report provides users with detailed input instructions, presents formulations of the various model options, and explains by means of comprehensive sample input, how to use the code. (orig.) [de

  16. Studies and research concerning BNFP. Identification and simplified modeling of economically important radwaste variables

    International Nuclear Information System (INIS)

    Ebel, P.E.; Godfrey, W.L.; Henry, J.L.; Postles, R.L.

    1983-09-01

    An extensive computer model describing the mass balance and economic characteristics of radioactive waste disposal systems was exercised in a series of runs designed using linear statistical methods. The most economically important variables were identified, their behavior characterized, and a simplified computer model prepared which runs on desk-top minicomputers. This simplified model allows the investigation of the effects of the seven most significant variables in each of four waste areas: Liquid Waste Storage, Liquid Waste Solidification, General Process Trash Handling, and Hulls Handling. 8 references, 1 figure, 12 tables

  17. Variance-based sensitivity indices for stochastic models with correlated inputs

    Energy Technology Data Exchange (ETDEWEB)

    Kala, Zdeněk [Brno University of Technology, Faculty of Civil Engineering, Department of Structural Mechanics Veveří St. 95, ZIP 602 00, Brno (Czech Republic)

    2015-03-10

    The goal of this article is the formulation of the principles of one of the possible strategies in implementing correlation between input random variables so as to be usable for algorithm development and the evaluation of Sobol’s sensitivity analysis. With regard to the types of stochastic computational models, which are commonly found in structural mechanics, an algorithm was designed for effective use in conjunction with Monte Carlo methods. Sensitivity indices are evaluated for all possible permutations of the decorrelation procedures for input parameters. The evaluation of Sobol’s sensitivity coefficients is illustrated on an example in which a computational model was used for the analysis of the resistance of a steel bar in tension with statistically dependent input geometric characteristics.

  18. Variance-based sensitivity indices for stochastic models with correlated inputs

    International Nuclear Information System (INIS)

    Kala, Zdeněk

    2015-01-01

    The goal of this article is the formulation of the principles of one of the possible strategies in implementing correlation between input random variables so as to be usable for algorithm development and the evaluation of Sobol’s sensitivity analysis. With regard to the types of stochastic computational models, which are commonly found in structural mechanics, an algorithm was designed for effective use in conjunction with Monte Carlo methods. Sensitivity indices are evaluated for all possible permutations of the decorrelation procedures for input parameters. The evaluation of Sobol’s sensitivity coefficients is illustrated on an example in which a computational model was used for the analysis of the resistance of a steel bar in tension with statistically dependent input geometric characteristics

  19. Managing N Inputs and the Effect on N Losses Following Excretion in Open-Dirt Feedlots in Nebraska

    Directory of Open Access Journals (Sweden)

    Galen E. Erickson

    2001-01-01

    Full Text Available Nutrition will play an important role in meeting the environmental challenges of beef cattle feedlots. Nutritionists are continually refining protein requirements, and have recently adopted a new metabolizable protein (MP system to more efficiently use nitrogen (N and allow more accurate diet formulation. Protein requirements vary by animal age and weight during the finishing period. Our hypothesis was that formulating diets with the MP system would decrease N inputs and lead to decreased excretion and losses. Comparing industry average diets (13.5% crude protein to phase-fed diets formulated to not exceed MP requirements decreased N inputs by 10 to 20% for calves and yearlings without affecting average daily gain. Decreasing inputs led to a concomitant decrease in N excretion (12 to 21% and losses (15 to 33% in open-dirt feedlot pens. N losses are variable with time of year, with averages of 60 to 70% of excreted N lost during the summer months and 40% lost during the November to May feeding periods. Protein requirements are being refined continually as more research data are collected. However, formulation to meet protein requirements, but not exceed them, is an important nutritional management option for feedlots to become sustainable.

  20. A Brief Talk on Cultural Input in English Teaching

    Institute of Scientific and Technical Information of China (English)

    王敏

    2007-01-01

    Different countries have different languages and cultures. My paper starts from the differentiation between western culture and Chinese culture to point out the importance and necessity of cultural input in English teaching and puts forward some approaches to enforce the cultural input in language teaching.

  1. Framework for Modelling Multiple Input Complex Aggregations for Interactive Installations

    DEFF Research Database (Denmark)

    Padfield, Nicolas; Andreasen, Troels

    2012-01-01

    on fuzzy logic and provides a method for variably balancing interaction and user input with the intention of the artist or director. An experimental design is presented, demonstrating an intuitive interface for parametric modelling of a complex aggregation function. The aggregation function unifies...

  2. Variabilidade espacial de atributos químicos de um argissolo para aplicação de insumos à taxa variável em diferentes formas de relevo Spatial variability of chemical attributes in an alfisol for variable rates of inputs in different forms of relief

    Directory of Open Access Journals (Sweden)

    Diogo M. Barbieri

    2008-12-01

    Full Text Available A agricultura de precisão implica análise da variabilidade espacial de fatores de produção e a aplicação de insumos de forma localizada. Várias são as causas que condicionam a variabilidade espacial dos solos, sendo o relevo um dos fatores mais importantes. O presente estudo teve por objetivo analisar a variabilidade espacial dos atributos químicos do solo e a elaboração de mapas de necessidade de aplicação de insumos de forma localizada, em áreas com diferentes formas de relevo. Duas parcelas de 1 ha cada foram delimitadas em áreas com topografia côncava e convexa. Foram retiradas, em cada área, 242 amostras de solos em 121 pontos, nas profundidades de solo de 0,00-0,20 m e 0,20-0,40 m. Os resultados de análise química foram submetidos às análises da estatística descritiva, geoestatística e interpolação por krigagem. A área convexa apresentou maior variabilidade espacial do solo em relação a área côncava. A adoção da agricultura de precisão possibilitou economia de aproximadamente 25 kg ha-1 de P2O5 na área côncava.The precision agriculture implies an analysis of spatial variability of production factors and the inputs application of located form. There are several factors that cause spatial variability in soils; relief is one of the most important ones. The objective of this study was to analyze the spatial variability, the chemical attributes of the soil and the elaboration of maps necessity for input application of located form, in areas with different relief forms. Two parcels of one hectare each were delimited in areas with concave and convex shaped topography. A set of 242 samples were collected from each area at 121 points in depths of 0.00-0.20 m and 0.20-0.40 m. The data were submitted to the descriptive statistical analyses, geostatistics and interpolation for kriging. The convex area presented more spatial variability of the soil in relation the concave area. The adoption of precision agriculture

  3. Learning a Novel Pattern through Balanced and Skewed Input

    Science.gov (United States)

    McDonough, Kim; Trofimovich, Pavel

    2013-01-01

    This study compared the effectiveness of balanced and skewed input at facilitating the acquisition of the transitive construction in Esperanto, characterized by the accusative suffix "-n" and variable word order (SVO, OVS). Thai university students (N = 98) listened to 24 sentences under skewed (one noun with high token frequency) or…

  4. ProMC: Input-output data format for HEP applications using varint encoding

    Science.gov (United States)

    Chekanov, S. V.; May, E.; Strand, K.; Van Gemmeren, P.

    2014-10-01

    A new data format for Monte Carlo (MC) events, or any structural data, including experimental data, is discussed. The format is designed to store data in a compact binary form using variable-size integer encoding as implemented in the Google's Protocol Buffers package. This approach is implemented in the PROMC library which produces smaller file sizes for MC records compared to the existing input-output libraries used in high-energy physics (HEP). Other important features of the proposed format are a separation of abstract data layouts from concrete programming implementations, self-description and random access. Data stored in PROMC files can be written, read and manipulated in a number of programming languages, such C++, JAVA, FORTRAN and PYTHON.

  5. Does Input Quality Drive Measured Differences in Firm Productivity?

    DEFF Research Database (Denmark)

    Fox, Jeremy T.; Smeets, Valerie Anne Rolande

    2011-01-01

    One explanation for productivity dispersion is that the quality of inputs differs across firms. We add labor market history variables such as experience and firm and industry tenure, as well as general human capital measures such as schooling and sex. Adding these variables decreases the ratio...... of the 90th to 10th productivity quantiles from 3.27 to 2.68 across eight Danish manufacturing and service industries. We also use the wage bill and worker fixed effects. We find that the wage bill explains as much dispersion as human capital measures....

  6. Linking annual N2O emission in organic soils to mineral nitrogen input as estimated by heterotrophic respiration and soil C/N ratio.

    Science.gov (United States)

    Mu, Zhijian; Huang, Aiying; Ni, Jiupai; Xie, Deti

    2014-01-01

    Organic soils are an important source of N2O, but global estimates of these fluxes remain uncertain because measurements are sparse. We tested the hypothesis that N2O fluxes can be predicted from estimates of mineral nitrogen input, calculated from readily-available measurements of CO2 flux and soil C/N ratio. From studies of organic soils throughout the world, we compiled a data set of annual CO2 and N2O fluxes which were measured concurrently. The input of soil mineral nitrogen in these studies was estimated from applied fertilizer nitrogen and organic nitrogen mineralization. The latter was calculated by dividing the rate of soil heterotrophic respiration by soil C/N ratio. This index of mineral nitrogen input explained up to 69% of the overall variability of N2O fluxes, whereas CO2 flux or soil C/N ratio alone explained only 49% and 36% of the variability, respectively. Including water table level in the model, along with mineral nitrogen input, further improved the model with the explanatory proportion of variability in N2O flux increasing to 75%. Unlike grassland or cropland soils, forest soils were evidently nitrogen-limited, so water table level had no significant effect on N2O flux. Our proposed approach, which uses the product of soil-derived CO2 flux and the inverse of soil C/N ratio as a proxy for nitrogen mineralization, shows promise for estimating regional or global N2O fluxes from organic soils, although some further enhancements may be warranted.

  7. Predicting local dengue transmission in Guangzhou, China, through the influence of imported cases, mosquito density and climate variability.

    Directory of Open Access Journals (Sweden)

    Shaowei Sang

    Full Text Available Each year there are approximately 390 million dengue infections worldwide. Weather variables have a significant impact on the transmission of Dengue Fever (DF, a mosquito borne viral disease. DF in mainland China is characterized as an imported disease. Hence it is necessary to explore the roles of imported cases, mosquito density and climate variability in dengue transmission in China. The study was to identify the relationship between dengue occurrence and possible risk factors and to develop a predicting model for dengue's control and prevention purpose.Three traditional suburbs and one district with an international airport in Guangzhou city were selected as the study areas. Autocorrelation and cross-correlation analysis were used to perform univariate analysis to identify possible risk factors, with relevant lagged effects, associated with local dengue cases. Principal component analysis (PCA was applied to extract principal components and PCA score was used to represent the original variables to reduce multi-collinearity. Combining the univariate analysis and prior knowledge, time-series Poisson regression analysis was conducted to quantify the relationship between weather variables, Breteau Index, imported DF cases and the local dengue transmission in Guangzhou, China. The goodness-of-fit of the constructed model was determined by pseudo-R2, Akaike information criterion (AIC and residual test. There were a total of 707 notified local DF cases from March 2006 to December 2012, with a seasonal distribution from August to November. There were a total of 65 notified imported DF cases from 20 countries, with forty-six cases (70.8% imported from Southeast Asia. The model showed that local DF cases were positively associated with mosquito density, imported cases, temperature, precipitation, vapour pressure and minimum relative humidity, whilst being negatively associated with air pressure, with different time lags.Imported DF cases and mosquito

  8. SOERP, Statistics and 2. Order Error Propagation for Function of Random Variables

    International Nuclear Information System (INIS)

    Cox, N. D.; Miller, C. F.

    1985-01-01

    1 - Description of problem or function: SOERP computes second-order error propagation equations for the first four moments of a function of independently distributed random variables. SOERP was written for a rigorous second-order error propagation of any function which may be expanded in a multivariable Taylor series, the input variables being independently distributed. The required input consists of numbers directly related to the partial derivatives of the function, evaluated at the nominal values of the input variables and the central moments of the input variables from the second through the eighth. 2 - Method of solution: The development of equations for computing the propagation of errors begins by expressing the function of random variables in a multivariable Taylor series expansion. The Taylor series expansion is then truncated, and statistical operations are applied to the series in order to obtain equations for the moments (about the origin) of the distribution of the computed value. If the Taylor series is truncated after powers of two, the procedure produces second-order error propagation equations. 3 - Restrictions on the complexity of the problem: The maximum number of component variables allowed is 30. The IBM version will only process one set of input data per run

  9. Unraveling the photovoltaic technology learning curve by incorporation of input price changes and scale effects

    International Nuclear Information System (INIS)

    Yu, C.F.; van Sark, W.G.J.H.M.; Alsema, E.A.

    2011-01-01

    In a large number of energy models, the use of learning curves for estimating technological improvements has become popular. This is based on the assumption that technological development can be monitored by following cost development as a function of market size. However, recent data show that in some stages of photovoltaic technology (PV) production, the market price of PV modules stabilizes even though the cumulative capacity increases. This implies that no technological improvement takes place in these periods: the cost predicted by the learning curve in the PV study is lower than the market one. We propose that this bias results from ignoring the effects of input prices and scale effects, and that incorporating the input prices and scale effects into the learning curve theory is an important issue in making cost predictions more reliable. In this paper, a methodology is described to incorporate the scale and input-prices effect as the additional variables into the one factor learning curve, which leads to the definition of the multi-factor learning curve. This multi-factor learning curve is not only derived from economic theories, but also supported by an empirical study. The results clearly show that input prices and scale effects are to be included, and that, although market prices are stabilizing, learning is still taking place. (author)

  10. New hybrid multivariate analysis approach to optimize multiple response surfaces considering correlations in both inputs and outputs

    OpenAIRE

    Hejazi, Taha Hossein; Amirkabir University of Technology - Iran; Seyyed-Esfahani, Mirmehdi; Amirkabir University of Technology - Iran; Ramezani, Majid; Amirkabir University of Technology - Iran

    2014-01-01

    Quality control in industrial and service systems requires the correct setting of input factors by which the outputs result at minimum cost with desirable characteristics. There are often more than one input and output in such systems. Response surface methodology in its multiple variable forms is one of the most applied methods to estimate and improve the quality characteristics of products with respect to control factors. When there is some degree of correlation among the variables, the exi...

  11. Modeling inputs to computer models used in risk assessment

    International Nuclear Information System (INIS)

    Iman, R.L.

    1987-01-01

    Computer models for various risk assessment applications are closely scrutinized both from the standpoint of questioning the correctness of the underlying mathematical model with respect to the process it is attempting to model and from the standpoint of verifying that the computer model correctly implements the underlying mathematical model. A process that receives less scrutiny, but is nonetheless of equal importance, concerns the individual and joint modeling of the inputs. This modeling effort clearly has a great impact on the credibility of results. Model characteristics are reviewed in this paper that have a direct bearing on the model input process and reasons are given for using probabilities-based modeling with the inputs. The authors also present ways to model distributions for individual inputs and multivariate input structures when dependence and other constraints may be present

  12. El análisis input-output

    Directory of Open Access Journals (Sweden)

    de Parada, Javier

    1964-07-01

    Full Text Available Economic development has been the permanent aim of the economic policy of every country. This requires a detailed knowledge of the relationships between the various economic activities, so that available resources can be applied to those activities that will lead to the greatest increase in the total national production, and also to the largest increment in labour vacancies, and exports. This optimum exploitation of available economic resources has been attempted width the introduction of the so called economic development plans. An important instrument in economic planning is the input output analysis. This article gives the basic hypotheses and the theoretical fundamentals underlying this type of analysis. From the latest input output table of Spanish economic activity, a secondary table has been prepared covering the aspects that affect construction most closely, so that the construction industry can also be subjected to this type of analysis. The predetermined variables have been taken to be the state provisions for future subsidies to the housing and road construction industries.Cuando en 1758 el Dr. F. Quesnay, médico de Luis XV, formula su famoso «Tableau Economique», las ideas sobre la interdependencia general de los sectores económicos calaron profundamente en el espíritu de los economistas de la época. La escuela fisiócrata, entonces en boga, consideraba el «dejar obrar» a las leyes naturales como la mejor forma de gobierno. Quesnay intuyó el movimiento natural circulatorio de los bienes económicos, y como fruto de sus investigaciones surgió el celebérrimo «Tableau Economique», que fue aclamado por sus contemporáneos como uno de los más grandes descubrimientos de la Historia.

  13. Least-squares adjustment of a 'known' neutron spectrum: The importance of the covariance matrix of the input spectrum

    International Nuclear Information System (INIS)

    Mannhart, W.

    1986-01-01

    Based on the responses of 25 different neutron activation detectors, the neutron spectrum of Cf-252 hs been adjusted with least-squares methods. For a fixed input neutron spectrum, the covariance matrix of this spectrum has been systematically varied to investigate the influence of this matrix on the final result. The investigation showed that the adjusted neutron spectrum is rather sensitive to the structure of the covariance matrix for the input spectrum. (author)

  14. A Novel Coupled State/Input/Parameter Identification Method for Linear Structural Systems

    Directory of Open Access Journals (Sweden)

    Zhimin Wan

    2018-01-01

    Full Text Available In many engineering applications, unknown states, inputs, and parameters exist in the structures. However, most methods require one or two of these variables to be known in order to identify the other(s. Recently, the authors have proposed a method called EGDF for coupled state/input/parameter identification for nonlinear system in state space. However, the EGDF method based solely on acceleration measurements is found to be unstable, which can cause the drift of the identified inputs and displacements. Although some regularization methods can be adopted for solving the problem, they are not suitable for joint input-state identification in real time. In this paper, a strategy of data fusion of displacement and acceleration measurements is used to avoid the low-frequency drift in the identified inputs and structural displacements for linear structural systems. Two numerical examples about a plane truss and a single-stage isolation system are conducted to verify the effectiveness of the proposed modified EGDF algorithm.

  15. Inverse Tasks In The Tsunami Problem: Nonlinear Regression With Inaccurate Input Data

    Science.gov (United States)

    Lavrentiev, M.; Shchemel, A.; Simonov, K.

    A variant of modified training functional that allows considering inaccurate input data is suggested. A limiting case when a part of input data is completely undefined, and, therefore, a problem of reconstruction of hidden parameters should be solved, is also considered. Some numerical experiments are presented. It is assumed that a dependence of known output variables on known input ones should be found is the classic problem definition, which is widely used in the majority of neural nets algorithms. The quality of approximation is evaluated as a performance function. Often the error of the task is evaluated as squared distance between known input data and predicted data multiplied by weighed coefficients. These coefficients may be named "precision coefficients". When inputs are not known exactly, natural generalization of performance function is adding member that responsible for distance between known inputs and shifted inputs, which lessen model's error. It is desirable that the set of variable parameters is compact for training to be con- verging. In the above problem it is possible to choose variants of demands of a priori compactness, which allow meaningful interpretation in the smoothness of the model dependence. Two kinds of regularization was used, first limited squares of coefficients responsible for nonlinearity and second limited multiplication of the above coeffi- cients and linear coefficients. Asymptotic universality of neural net ability to approxi- mate various smooth functions with any accuracy by increase of the number of tunable parameters is often the base for selecting a type of neural net approximation. It is pos- sible to show that used neural net will approach to Fourier integral transform, which approximate abilities are known, with increasing of the number of tunable parameters. In the limiting case, when input data is set with zero precision, the problem of recon- struction of hidden parameters with observed output data appears. The

  16. Sensitivity Analysis of Input Parameters for a Dynamic Food Chain Model DYNACON

    International Nuclear Information System (INIS)

    Hwang, Won Tae; Lee, Geun Chang; Han, Moon Hee; Cho, Gyu Seong

    2000-01-01

    The sensitivity analysis of input parameters for a dynamic food chain model DYNACON was conducted as a function of deposition data for the long-lived radionuclides ( 137 Cs, 90 Sr). Also, the influence of input parameters for the short and long-terms contamination of selected foodstuffs (cereals, leafy vegetables, milk) was investigated. The input parameters were sampled using the LHS technique, and their sensitivity indices represented as PRCC. The sensitivity index was strongly dependent on contamination period as well as deposition data. In case of deposition during the growing stages of plants, the input parameters associated with contamination by foliar absorption were relatively important in long-term contamination as well as short-term contamination. They were also important in short-term contamination in case of deposition during the non-growing stages. In long-term contamination, the influence of input parameters associated with foliar absorption decreased, while the influence of input parameters associated with root uptake increased. These phenomena were more remarkable in case of the deposition of non-growing stages than growing stages, and in case of 90 Sr deposition than 137 Cs deposition. In case of deposition during growing stages of pasture, the input parameters associated with the characteristics of cattle such as feed-milk transfer factor and daily intake rate of cattle were relatively important in contamination of milk

  17. Experimental demonstration of continuous variable cloning with phase-conjugate inputs

    DEFF Research Database (Denmark)

    Sabuncu, Metin; Andersen, Ulrik Lund; Leuchs, G.

    2007-01-01

    We report the first experimental demonstration of continuous variable cloning of phase-conjugate coherent states as proposed by Cerf and Iblisdir [Phys. Rev. Lett. 87, 247903 (2001)]. In contrast to this proposal, the cloning transformation is accomplished using only linear optical components......, homodyne detection, and feedforward. As a result of combining phase conjugation with a joint measurement strategy, superior cloning is demonstrated with cloning fidelities reaching 89%....

  18. Learner Variables Important for Success in L2 Listening Comprehension in French Immersion Classrooms

    Science.gov (United States)

    Vandergrift, Larry; Baker, Susan C.

    2018-01-01

    Listening comprehension, which is relatively straightforward for native language (L1) speakers, is often frustrating for second language (L2) learners. Listening comprehension is important to L2 acquisition, but little is known about the variables that influence the development of L2 listening skills. The goal of this study was to determine which…

  19. Whole-Brain Monosynaptic Afferent Inputs to Basal Forebrain Cholinergic System

    Directory of Open Access Journals (Sweden)

    Rongfeng Hu

    2016-10-01

    Full Text Available The basal forebrain cholinergic system (BFCS robustly modulates many important behaviors, such as arousal, attention, learning and memory, through heavy projections to cortex and hippocampus. However, the presynaptic partners governing BFCS activity still remain poorly understood. Here, we utilized a recently developed rabies virus-based cell-type-specific retrograde tracing system to map the whole-brain afferent inputs of the BFCS. We found that the BFCS receives inputs from multiple cortical areas, such as orbital frontal cortex, motor cortex, and insular cortex, and that the BFCS also receives dense inputs from several subcortical nuclei related to motivation and stress, including lateral septum (LS, central amygdala (CeA, paraventricular nucleus of hypothalamus (PVH, dorsal raphe (DRN and parabrachial nucleus (PBN. Interestingly, we found that the BFCS receives inputs from the olfactory areas and the entorhinal-hippocampal system. These results greatly expand our knowledge about the connectivity of the mouse BFCS and provided important preliminary indications for future exploration of circuit function.

  20. Analysis and Improvement of Control Algorithm for Operation Mode Transition due to Input Channel Trouble in Control Systems

    International Nuclear Information System (INIS)

    Ahn, Myunghoon; Kim, Woogoon; Yim, Hyeongsoon

    2016-01-01

    The PI (Proportional plus Integral) controller, which is the essential functional block in control systems, can automatically perform the stable control of an important plant process while reducing the steady state error and improving the transient response. However, if the received input PV (Process Variable) is not normal due to input channel trouble, it will be difficult to control the system automatically. For this reason, many control systems are implemented to change the operation mode from automatic to manual mode in the PI controller when the failed input PV is detected. If the PI controller is in automatic mode for all the time, the control signal varies as the change of the input PV is continuously reflected in the control algorithm. In the other cases, since the controller changes into the manual mode at t=0, the control signal is fixed at the last PI controller output and thus the feedback control is not performed anymore until the operator takes an action such as the operation mode change. As a result of analysis and simulations for the controller’s operation modes in all the cases of input channel trouble, we discovered that it is more appropriate to maintain the automatic mode despite the bad quality in the PV. Therefore, we improved the control system algorithm reflecting the analysis results for the operator’s convenience and the stability of a control system

  1. Analysis and Improvement of Control Algorithm for Operation Mode Transition due to Input Channel Trouble in Control Systems

    Energy Technology Data Exchange (ETDEWEB)

    Ahn, Myunghoon; Kim, Woogoon; Yim, Hyeongsoon [KEPCO Engineering and Construction Co., Deajeon (Korea, Republic of)

    2016-10-15

    The PI (Proportional plus Integral) controller, which is the essential functional block in control systems, can automatically perform the stable control of an important plant process while reducing the steady state error and improving the transient response. However, if the received input PV (Process Variable) is not normal due to input channel trouble, it will be difficult to control the system automatically. For this reason, many control systems are implemented to change the operation mode from automatic to manual mode in the PI controller when the failed input PV is detected. If the PI controller is in automatic mode for all the time, the control signal varies as the change of the input PV is continuously reflected in the control algorithm. In the other cases, since the controller changes into the manual mode at t=0, the control signal is fixed at the last PI controller output and thus the feedback control is not performed anymore until the operator takes an action such as the operation mode change. As a result of analysis and simulations for the controller’s operation modes in all the cases of input channel trouble, we discovered that it is more appropriate to maintain the automatic mode despite the bad quality in the PV. Therefore, we improved the control system algorithm reflecting the analysis results for the operator’s convenience and the stability of a control system.

  2. [Prosody, speech input and language acquisition].

    Science.gov (United States)

    Jungheim, M; Miller, S; Kühn, D; Ptok, M

    2014-04-01

    In order to acquire language, children require speech input. The prosody of the speech input plays an important role. In most cultures adults modify their code when communicating with children. Compared to normal speech this code differs especially with regard to prosody. For this review a selective literature search in PubMed and Scopus was performed. Prosodic characteristics are a key feature of spoken language. By analysing prosodic features, children gain knowledge about underlying grammatical structures. Child-directed speech (CDS) is modified in a way that meaningful sequences are highlighted acoustically so that important information can be extracted from the continuous speech flow more easily. CDS is said to enhance the representation of linguistic signs. Taking into consideration what has previously been described in the literature regarding the perception of suprasegmentals, CDS seems to be able to support language acquisition due to the correspondence of prosodic and syntactic units. However, no findings have been reported, stating that the linguistically reduced CDS could hinder first language acquisition.

  3. What variables are important in predicting bovine viral diarrhea virus? A random forest approach.

    Science.gov (United States)

    Machado, Gustavo; Mendoza, Mariana Recamonde; Corbellini, Luis Gustavo

    2015-07-24

    Bovine viral diarrhea virus (BVDV) causes one of the most economically important diseases in cattle, and the virus is found worldwide. A better understanding of the disease associated factors is a crucial step towards the definition of strategies for control and eradication. In this study we trained a random forest (RF) prediction model and performed variable importance analysis to identify factors associated with BVDV occurrence. In addition, we assessed the influence of features selection on RF performance and evaluated its predictive power relative to other popular classifiers and to logistic regression. We found that RF classification model resulted in an average error rate of 32.03% for the negative class (negative for BVDV) and 36.78% for the positive class (positive for BVDV).The RF model presented area under the ROC curve equal to 0.702. Variable importance analysis revealed that important predictors of BVDV occurrence were: a) who inseminates the animals, b) number of neighboring farms that have cattle and c) rectal palpation performed routinely. Our results suggest that the use of machine learning algorithms, especially RF, is a promising methodology for the analysis of cross-sectional studies, presenting a satisfactory predictive power and the ability to identify predictors that represent potential risk factors for BVDV investigation. We examined classical predictors and found some new and hard to control practices that may lead to the spread of this disease within and among farms, mainly regarding poor or neglected reproduction management, which should be considered for disease control and eradication.

  4. Computational Techniques for Model Predictive Control of Large-Scale Systems with Continuous-Valued and Discrete-Valued Inputs

    Directory of Open Access Journals (Sweden)

    Koichi Kobayashi

    2013-01-01

    Full Text Available We propose computational techniques for model predictive control of large-scale systems with both continuous-valued control inputs and discrete-valued control inputs, which are a class of hybrid systems. In the proposed method, we introduce the notion of virtual control inputs, which are obtained by relaxing discrete-valued control inputs to continuous variables. In online computation, first, we find continuous-valued control inputs and virtual control inputs minimizing a cost function. Next, using the obtained virtual control inputs, only discrete-valued control inputs at the current time are computed in each subsystem. In addition, we also discuss the effect of quantization errors. Finally, the effectiveness of the proposed method is shown by a numerical example. The proposed method enables us to reduce and decentralize the computation load.

  5. Characteristic length scale of input data in distributed models: implications for modeling grid size

    Science.gov (United States)

    Artan, G. A.; Neale, C. M. U.; Tarboton, D. G.

    2000-01-01

    The appropriate spatial scale for a distributed energy balance model was investigated by: (a) determining the scale of variability associated with the remotely sensed and GIS-generated model input data; and (b) examining the effects of input data spatial aggregation on model response. The semi-variogram and the characteristic length calculated from the spatial autocorrelation were used to determine the scale of variability of the remotely sensed and GIS-generated model input data. The data were collected from two hillsides at Upper Sheep Creek, a sub-basin of the Reynolds Creek Experimental Watershed, in southwest Idaho. The data were analyzed in terms of the semivariance and the integral of the autocorrelation. The minimum characteristic length associated with the variability of the data used in the analysis was 15 m. Simulated and observed radiometric surface temperature fields at different spatial resolutions were compared. The correlation between agreement simulated and observed fields sharply declined after a 10×10 m2 modeling grid size. A modeling grid size of about 10×10 m2 was deemed to be the best compromise to achieve: (a) reduction of computation time and the size of the support data; and (b) a reproduction of the observed radiometric surface temperature.

  6. Characteristic length scale of input data in distributed models: implications for modeling grain size

    Science.gov (United States)

    Artan, Guleid A.; Neale, C. M. U.; Tarboton, D. G.

    2000-01-01

    The appropriate spatial scale for a distributed energy balance model was investigated by: (a) determining the scale of variability associated with the remotely sensed and GIS-generated model input data; and (b) examining the effects of input data spatial aggregation on model response. The semi-variogram and the characteristic length calculated from the spatial autocorrelation were used to determine the scale of variability of the remotely sensed and GIS-generated model input data. The data were collected from two hillsides at Upper Sheep Creek, a sub-basin of the Reynolds Creek Experimental Watershed, in southwest Idaho. The data were analyzed in terms of the semivariance and the integral of the autocorrelation. The minimum characteristic length associated with the variability of the data used in the analysis was 15 m. Simulated and observed radiometric surface temperature fields at different spatial resolutions were compared. The correlation between agreement simulated and observed fields sharply declined after a 10×10 m2 modeling grid size. A modeling grid size of about 10×10 m2 was deemed to be the best compromise to achieve: (a) reduction of computation time and the size of the support data; and (b) a reproduction of the observed radiometric surface temperature.

  7. Measures of uncertainty, importance and sensitivity of the SEDA code

    International Nuclear Information System (INIS)

    Baron, J.; Caruso, A.; Vinate, H.

    1996-01-01

    The purpose of this work is the estimation of the uncertainty on the results of the SEDA code (Sistema de Evaluacion de Dosis en Accidentes) in accordance with the input data and its parameters. The SEDA code has been developed by the Comision Nacional de Energia Atomica for the estimation of doses during emergencies in the vicinity of Atucha and Embalse, nuclear power plants. The user should feed the code with meteorological data, source terms and accident data (timing involved, release height, thermal content of the release, etc.) It is designed to be used during the emergency, and to bring fast results that enable to make decisions. The uncertainty in the results of the SEDA code is quantified in the present paper. This uncertainty is associated both with the data the user inputs to the code, and with the uncertain parameters of the code own models. The used method consisted in the statistical characterization of the parameters and variables, assigning them adequate probability distributions. These distributions have been sampled with the Latin Hypercube Sampling method, which is a stratified multi-variable Monte-Carlo technique. The code has been performed for each of the samples and finally, a result sample has been obtained. These results have been characterized from the statistical point of view (obtaining their mean, most probable value, distribution shape, etc.) for several distances from the source. Finally, the Partial Correlation Coefficients and Standard Regression Coefficients techniques have been used to obtain the relative importance of each input variable, and the Sensitivity of the code to its variations. The measures of Importance and Sensitivity have been obtained for several distances from the source and various cases of atmospheric stability, making comparisons possible. This paper allowed to confide in the results of the code, and the association of their uncertainty to them, as a way to know the limits in which the results can vary in a real

  8. Learning from input and memory evolution: points of vulnerability on a pathway to mastery in word learning.

    Science.gov (United States)

    Storkel, Holly L

    2015-02-01

    Word learning consists of at least two neurocognitive processes: learning from input during training and memory evolution during gaps between training sessions. Fine-grained analysis of word learning by normal adults provides evidence that learning from input is swift and stable, whereas memory evolution is a point of potential vulnerability on the pathway to mastery. Moreover, success during learning from input is linked to positive outcomes from memory evolution. These two neurocognitive processes can be overlaid on to components of clinical treatment with within-session variables (i.e. dose form and dose) potentially linked to learning from input and between-session variables (i.e. dose frequency) linked to memory evolution. Collecting data at the beginning and end of a treatment session can be used to identify the point of vulnerability in word learning for a given client and the appropriate treatment component can then be adjusted to improve the client's word learning. Two clinical cases are provided to illustrate this approach.

  9. Quality of early parent input predicts child vocabulary 3 years later.

    Science.gov (United States)

    Cartmill, Erica A; Armstrong, Benjamin F; Gleitman, Lila R; Goldin-Meadow, Susan; Medina, Tamara N; Trueswell, John C

    2013-07-09

    Children vary greatly in the number of words they know when they enter school, a major factor influencing subsequent school and workplace success. This variability is partially explained by the differential quantity of parental speech to preschoolers. However, the contexts in which young learners hear new words are also likely to vary in referential transparency; that is, in how clearly word meaning can be inferred from the immediate extralinguistic context, an aspect of input quality. To examine this aspect, we asked 218 adult participants to guess 50 parents' words from (muted) videos of their interactions with their 14- to 18-mo-old children. We found systematic differences in how easily individual parents' words could be identified purely from this socio-visual context. Differences in this kind of input quality correlated with the size of the children's vocabulary 3 y later, even after controlling for differences in input quantity. Although input quantity differed as a function of socioeconomic status, input quality (as here measured) did not, suggesting that the quality of nonverbal cues to word meaning that parents offer to their children is an individual matter, widely distributed across the population of parents.

  10. TART input manual

    International Nuclear Information System (INIS)

    Kimlinger, J.R.; Plechaty, E.F.

    1982-01-01

    The TART code is a Monte Carlo neutron/photon transport code that is only on the CRAY computer. All the input cards for the TART code are listed, and definitions for all input parameters are given. The execution and limitations of the code are described, and input for two sample problems are given

  11. Variable input parameter influence on river corridor prediction

    NARCIS (Netherlands)

    Zerfu, T.; Beevers, L.; Crosato, A.; Wright, N.

    2015-01-01

    This paper considers the erodible river corridor, which is the area in which the main river channel is free to migrate over a period of time. Due to growing anthropogenic pressure, predicting the corridor width has become increasingly important for the planning of development along rivers. Several

  12. Permutation importance: a corrected feature importance measure.

    Science.gov (United States)

    Altmann, André; Toloşi, Laura; Sander, Oliver; Lengauer, Thomas

    2010-05-15

    In life sciences, interpretability of machine learning models is as important as their prediction accuracy. Linear models are probably the most frequently used methods for assessing feature relevance, despite their relative inflexibility. However, in the past years effective estimators of feature relevance have been derived for highly complex or non-parametric models such as support vector machines and RandomForest (RF) models. Recently, it has been observed that RF models are biased in such a way that categorical variables with a large number of categories are preferred. In this work, we introduce a heuristic for normalizing feature importance measures that can correct the feature importance bias. The method is based on repeated permutations of the outcome vector for estimating the distribution of measured importance for each variable in a non-informative setting. The P-value of the observed importance provides a corrected measure of feature importance. We apply our method to simulated data and demonstrate that (i) non-informative predictors do not receive significant P-values, (ii) informative variables can successfully be recovered among non-informative variables and (iii) P-values computed with permutation importance (PIMP) are very helpful for deciding the significance of variables, and therefore improve model interpretability. Furthermore, PIMP was used to correct RF-based importance measures for two real-world case studies. We propose an improved RF model that uses the significant variables with respect to the PIMP measure and show that its prediction accuracy is superior to that of other existing models. R code for the method presented in this article is available at http://www.mpi-inf.mpg.de/ approximately altmann/download/PIMP.R CONTACT: altmann@mpi-inf.mpg.de, laura.tolosi@mpi-inf.mpg.de Supplementary data are available at Bioinformatics online.

  13. Quantitative assessment of drivers of recent climate variability

    DEFF Research Database (Denmark)

    Bhaskar, Ankush; Ramesh, Durbha Sai; Vichare, Geeta

    2016-01-01

    Identification and quantification of possible drivers of recent climate variability remain a challenging task. This important issue is addressed adopting a non-parametric information theory technique, the Transfer Entropy and its normalized variant. It distinctly quantifies actual information...... exchanged along with the directional flow of information between any two variables with no bearing on their common history or inputs, unlike correlation, mutual information etc. Measurements of greenhouse gases, CO2, CH4, and N2O; volcanic aerosols; solar activity: UV radiation, total solar irradiance (TSI...... ) and cosmic ray flux (CR); El Nino Southern Oscillation (ENSO) and Global Mean Temperature Anomaly (GMTA) made during 1984-2005 are utilized to distinguish driving and responding climate signals. Estimates of their relative contributions reveal that CO 2 (~24%), CH 4 (~19%) and volcanic aerosols (~23...

  14. Automation of RELAP5 input calibration and code validation using genetic algorithm

    International Nuclear Information System (INIS)

    Phung, Viet-Anh; Kööp, Kaspar; Grishchenko, Dmitry; Vorobyev, Yury; Kudinov, Pavel

    2016-01-01

    Highlights: • Automated input calibration and code validation using genetic algorithm is presented. • Predictions generally overlap experiments for individual system response quantities (SRQs). • It was not possible to predict simultaneously experimental maximum flow rate and oscillation period. • Simultaneous consideration of multiple SRQs is important for code validation. - Abstract: Validation of system thermal-hydraulic codes is an important step in application of the codes to reactor safety analysis. The goal of the validation process is to determine how well a code can represent physical reality. This is achieved by comparing predicted and experimental system response quantities (SRQs) taking into account experimental and modelling uncertainties. Parameters which are required for the code input but not measured directly in the experiment can become an important source of uncertainty in the code validation process. Quantification of such parameters is often called input calibration. Calibration and uncertainty quantification may become challenging tasks when the number of calibrated input parameters and SRQs is large and dependencies between them are complex. If only engineering judgment is employed in the process, the outcome can be prone to so called “user effects”. The goal of this work is to develop an automated approach to input calibration and RELAP5 code validation against data on two-phase natural circulation flow instability. Multiple SRQs are used in both calibration and validation. In the input calibration, we used genetic algorithm (GA), a heuristic global optimization method, in order to minimize the discrepancy between experimental and simulation data by identifying optimal combinations of uncertain input parameters in the calibration process. We demonstrate the importance of the proper selection of SRQs and respective normalization and weighting factors in the fitness function. In the code validation, we used maximum flow rate as the

  15. Automation of RELAP5 input calibration and code validation using genetic algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Phung, Viet-Anh, E-mail: vaphung@kth.se [Division of Nuclear Power Safety, Royal Institute of Technology, Roslagstullsbacken 21, 10691 Stockholm (Sweden); Kööp, Kaspar, E-mail: kaspar@safety.sci.kth.se [Division of Nuclear Power Safety, Royal Institute of Technology, Roslagstullsbacken 21, 10691 Stockholm (Sweden); Grishchenko, Dmitry, E-mail: dmitry@safety.sci.kth.se [Division of Nuclear Power Safety, Royal Institute of Technology, Roslagstullsbacken 21, 10691 Stockholm (Sweden); Vorobyev, Yury, E-mail: yura3510@gmail.com [National Research Center “Kurchatov Institute”, Kurchatov square 1, Moscow 123182 (Russian Federation); Kudinov, Pavel, E-mail: pavel@safety.sci.kth.se [Division of Nuclear Power Safety, Royal Institute of Technology, Roslagstullsbacken 21, 10691 Stockholm (Sweden)

    2016-04-15

    Highlights: • Automated input calibration and code validation using genetic algorithm is presented. • Predictions generally overlap experiments for individual system response quantities (SRQs). • It was not possible to predict simultaneously experimental maximum flow rate and oscillation period. • Simultaneous consideration of multiple SRQs is important for code validation. - Abstract: Validation of system thermal-hydraulic codes is an important step in application of the codes to reactor safety analysis. The goal of the validation process is to determine how well a code can represent physical reality. This is achieved by comparing predicted and experimental system response quantities (SRQs) taking into account experimental and modelling uncertainties. Parameters which are required for the code input but not measured directly in the experiment can become an important source of uncertainty in the code validation process. Quantification of such parameters is often called input calibration. Calibration and uncertainty quantification may become challenging tasks when the number of calibrated input parameters and SRQs is large and dependencies between them are complex. If only engineering judgment is employed in the process, the outcome can be prone to so called “user effects”. The goal of this work is to develop an automated approach to input calibration and RELAP5 code validation against data on two-phase natural circulation flow instability. Multiple SRQs are used in both calibration and validation. In the input calibration, we used genetic algorithm (GA), a heuristic global optimization method, in order to minimize the discrepancy between experimental and simulation data by identifying optimal combinations of uncertain input parameters in the calibration process. We demonstrate the importance of the proper selection of SRQs and respective normalization and weighting factors in the fitness function. In the code validation, we used maximum flow rate as the

  16. A Practical pedestrian approach to parsimonious regression with inaccurate inputs

    Directory of Open Access Journals (Sweden)

    Seppo Karrila

    2014-04-01

    Full Text Available A measurement result often dictates an interval containing the correct value. Interval data is also created by roundoff, truncation, and binning. We focus on such common interval uncertainty in data. Inaccuracy in model inputs is typically ignored on model fitting. We provide a practical approach for regression with inaccurate data: the mathematics is easy, and the linear programming formulations simple to use even in a spreadsheet. This self-contained elementary presentation introduces interval linear systems and requires only basic knowledge of algebra. Feature selection is automatic; but can be controlled to find only a few most relevant inputs; and joint feature selection is enabled for multiple modeled outputs. With more features than cases, a novel connection to compressed sensing emerges: robustness against interval errors-in-variables implies model parsimony, and the input inaccuracies determine the regularization term. A small numerical example highlights counterintuitive results and a dramatic difference to total least squares.

  17. Integration of auditory and tactile inputs in musical meter perception.

    Science.gov (United States)

    Huang, Juan; Gamble, Darik; Sarnlertsophon, Kristine; Wang, Xiaoqin; Hsiao, Steven

    2013-01-01

    Musicians often say that they not only hear but also "feel" music. To explore the contribution of tactile information to "feeling" music, we investigated the degree that auditory and tactile inputs are integrated in humans performing a musical meter-recognition task. Subjects discriminated between two types of sequences, "duple" (march-like rhythms) and "triple" (waltz-like rhythms), presented in three conditions: (1) unimodal inputs (auditory or tactile alone); (2) various combinations of bimodal inputs, where sequences were distributed between the auditory and tactile channels such that a single channel did not produce coherent meter percepts; and (3) bimodal inputs where the two channels contained congruent or incongruent meter cues. We first show that meter is perceived similarly well (70-85 %) when tactile or auditory cues are presented alone. We next show in the bimodal experiments that auditory and tactile cues are integrated to produce coherent meter percepts. Performance is high (70-90 %) when all of the metrically important notes are assigned to one channel and is reduced to 60 % when half of these notes are assigned to one channel. When the important notes are presented simultaneously to both channels, congruent cues enhance meter recognition (90 %). Performance dropped dramatically when subjects were presented with incongruent auditory cues (10 %), as opposed to incongruent tactile cues (60 %), demonstrating that auditory input dominates meter perception. These observations support the notion that meter perception is a cross-modal percept with tactile inputs underlying the perception of "feeling" music.

  18. Variable identification in group method of data handling methodology

    Energy Technology Data Exchange (ETDEWEB)

    Pereira, Iraci Martinez, E-mail: martinez@ipen.b [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil); Bueno, Elaine Inacio [Instituto Federal de Educacao, Ciencia e Tecnologia, Guarulhos, SP (Brazil)

    2011-07-01

    The Group Method of Data Handling - GMDH is a combinatorial multi-layer algorithm in which a network of layers and nodes is generated using a number of inputs from the data stream being evaluated. The GMDH network topology has been traditionally determined using a layer by layer pruning process based on a preselected criterion of what constitutes the best nodes at each level. The traditional GMDH method is based on an underlying assumption that the data can be modeled by using an approximation of the Volterra Series or Kolmorgorov-Gabor polynomial. A Monitoring and Diagnosis System was developed based on GMDH and Artificial Neural Network - ANN methodologies, and applied to the IPEN research Reactor IEA-R1. The GMDH was used to study the best set of variables to be used to train an ANN, resulting in a best monitoring variable estimative. The system performs the monitoring by comparing these estimative calculated values with measured ones. The IPEN Reactor Data Acquisition System is composed of 58 variables (process and nuclear variables). As the GMDH is a self-organizing methodology, the input variables choice is made automatically, and the real input variables used in the Monitoring and Diagnosis System were not showed in the final result. This work presents a study of variable identification of GMDH methodology by means of an algorithm that works in parallel with the GMDH algorithm and traces the initial variables paths, resulting in an identification of the variables that composes the best Monitoring and Diagnosis Model. (author)

  19. Variable identification in group method of data handling methodology

    International Nuclear Information System (INIS)

    Pereira, Iraci Martinez; Bueno, Elaine Inacio

    2011-01-01

    The Group Method of Data Handling - GMDH is a combinatorial multi-layer algorithm in which a network of layers and nodes is generated using a number of inputs from the data stream being evaluated. The GMDH network topology has been traditionally determined using a layer by layer pruning process based on a preselected criterion of what constitutes the best nodes at each level. The traditional GMDH method is based on an underlying assumption that the data can be modeled by using an approximation of the Volterra Series or Kolmorgorov-Gabor polynomial. A Monitoring and Diagnosis System was developed based on GMDH and Artificial Neural Network - ANN methodologies, and applied to the IPEN research Reactor IEA-R1. The GMDH was used to study the best set of variables to be used to train an ANN, resulting in a best monitoring variable estimative. The system performs the monitoring by comparing these estimative calculated values with measured ones. The IPEN Reactor Data Acquisition System is composed of 58 variables (process and nuclear variables). As the GMDH is a self-organizing methodology, the input variables choice is made automatically, and the real input variables used in the Monitoring and Diagnosis System were not showed in the final result. This work presents a study of variable identification of GMDH methodology by means of an algorithm that works in parallel with the GMDH algorithm and traces the initial variables paths, resulting in an identification of the variables that composes the best Monitoring and Diagnosis Model. (author)

  20. Observing Two Important Teaching Variables.

    Science.gov (United States)

    Gustafson, John A.

    1986-01-01

    Two behaviors essential to good teaching, teacher expectation and teacher flexibility, have been incorporated into the observation system used in the student teacher program at the University of New Mexico. The importance of these behaviors in teaching and in evaluating student teachers is discussed. (MT)

  1. Input-output supervisor

    International Nuclear Information System (INIS)

    Dupuy, R.

    1970-01-01

    The input-output supervisor is the program which monitors the flow of informations between core storage and peripheral equipments of a computer. This work is composed of three parts: 1 - Study of a generalized input-output supervisor. With sample modifications it looks like most of input-output supervisors which are running now on computers. 2 - Application of this theory on a magnetic drum. 3 - Hardware requirement for time-sharing. (author) [fr

  2. Partitioning the impacts of spatial and climatological rainfall variability in urban drainage modeling

    Science.gov (United States)

    Peleg, Nadav; Blumensaat, Frank; Molnar, Peter; Fatichi, Simone; Burlando, Paolo

    2017-03-01

    The performance of urban drainage systems is typically examined using hydrological and hydrodynamic models where rainfall input is uniformly distributed, i.e., derived from a single or very few rain gauges. When models are fed with a single uniformly distributed rainfall realization, the response of the urban drainage system to the rainfall variability remains unexplored. The goal of this study was to understand how climate variability and spatial rainfall variability, jointly or individually considered, affect the response of a calibrated hydrodynamic urban drainage model. A stochastic spatially distributed rainfall generator (STREAP - Space-Time Realizations of Areal Precipitation) was used to simulate many realizations of rainfall for a 30-year period, accounting for both climate variability and spatial rainfall variability. The generated rainfall ensemble was used as input into a calibrated hydrodynamic model (EPA SWMM - the US EPA's Storm Water Management Model) to simulate surface runoff and channel flow in a small urban catchment in the city of Lucerne, Switzerland. The variability of peak flows in response to rainfall of different return periods was evaluated at three different locations in the urban drainage network and partitioned among its sources. The main contribution to the total flow variability was found to originate from the natural climate variability (on average over 74 %). In addition, the relative contribution of the spatial rainfall variability to the total flow variability was found to increase with longer return periods. This suggests that while the use of spatially distributed rainfall data can supply valuable information for sewer network design (typically based on rainfall with return periods from 5 to 15 years), there is a more pronounced relevance when conducting flood risk assessments for larger return periods. The results show the importance of using multiple distributed rainfall realizations in urban hydrology studies to capture the

  3. Effect of input data variability on estimations of the equivalent constant temperature time for microbial inactivation by HTST and retort thermal processing.

    Science.gov (United States)

    Salgado, Diana; Torres, J Antonio; Welti-Chanes, Jorge; Velazquez, Gonzalo

    2011-08-01

    Consumer demand for food safety and quality improvements, combined with new regulations, requires determining the processor's confidence level that processes lowering safety risks while retaining quality will meet consumer expectations and regulatory requirements. Monte Carlo calculation procedures incorporate input data variability to obtain the statistical distribution of the output of prediction models. This advantage was used to analyze the survival risk of Mycobacterium avium subspecies paratuberculosis (M. paratuberculosis) and Clostridium botulinum spores in high-temperature short-time (HTST) milk and canned mushrooms, respectively. The results showed an estimated 68.4% probability that the 15 sec HTST process would not achieve at least 5 decimal reductions in M. paratuberculosis counts. Although estimates of the raw milk load of this pathogen are not available to estimate the probability of finding it in pasteurized milk, the wide range of the estimated decimal reductions, reflecting the variability of the experimental data available, should be a concern to dairy processors. Knowledge of the C. botulinum initial load and decimal thermal time variability was used to estimate an 8.5 min thermal process time at 110 °C for canned mushrooms reducing the risk to 10⁻⁹ spores/container with a 95% confidence. This value was substantially higher than the one estimated using average values (6.0 min) with an unacceptable 68.6% probability of missing the desired processing objective. Finally, the benefit of reducing the variability in initial load and decimal thermal time was confirmed, achieving a 26.3% reduction in processing time when standard deviation values were lowered by 90%. In spite of novel technologies, commercialized or under development, thermal processing continues to be the most reliable and cost-effective alternative to deliver safe foods. However, the severity of the process should be assessed to avoid under- and over

  4. Gain tuning and fidelity in continuous-variable quantum teleportation

    International Nuclear Information System (INIS)

    Ide, Toshiki; Hofmann, Holger F.; Furusawa, Akira; Kobayashi, Takayoshi

    2002-01-01

    The fidelity of continuous-variable teleportation can be optimized by changing the gain in the modulation of the output field. We discuss the gain dependence of fidelity for coherent, vacuum, and one-photon inputs and propose optimal gain tuning strategies for corresponding input selections

  5. Automatic creation of LabVIEW network shared variables

    International Nuclear Information System (INIS)

    Kluge, T.; Schroeder, H.

    2012-01-01

    We are in the process of preparing the LabVIEW controlled system components of our Solid State Direct Drive experiments for the integration into a Supervisory Control And Data Acquisition (SCADA) or distributed control system. The predetermined route to this is the generation of LabVIEW network shared variables that can easily be exported by LabVIEW to the SCADA system using OLE for Process Control (OPC) or other means. Many repetitive tasks are associated with the creation of the shared variables and the required code. We are introducing an efficient and inexpensive procedure that automatically creates shared variable libraries and sets default values for the shared variables. Furthermore, LabVIEW controls are created that are used for managing the connection to the shared variable inside the LabVIEW code operating on the shared variables. The procedure takes as input an XML spread-sheet defining the required input. The procedure utilizes XSLT and LabVIEW scripting. In a later state of the project the code generation can be expanded to also create code and configuration files that will become necessary in order to access the shared variables from the SCADA system of choice. (authors)

  6. Temporal variability in the importance of hydrologic, biotic, and climatic descriptors of dissolved oxygen dynamics in a shallow tidal-marsh creek

    Science.gov (United States)

    Nelson, N.; Munoz-Carpena, R.; Neale, P.; Tzortziou, M.; Megonigal, P.

    2017-12-01

    Due to strong abiotic forcing, dissolved oxygen (DO) in shallow tidal creeks often disobeys the conventional explanation of general aquatic DO cycling as biologically-regulated. In the present work, we seek to quantify the relative importance of abiotic (hydrologic and climatic), and biotic (primary productivity as represented by chlorophyll-a) descriptors of tidal creek DO. By fitting multiple linear regression models of DO to hourly chlorophyll-a, water quality, hydrology, and weather data collected in a tidal creek of a Chesapeake Bay marsh (Maryland, USA), temporal shifts (summer - early winter) in the relative importance of tidal creek DO descriptors were uncovered. Moreover, this analysis identified an alternative approach to evaluating tidal stage as a driver of DO by dividing stage into two DO-relevant variables: stage above and below bankfull depth. Within the hydrologic variable class, stage below bankfull depth dominated as an important descriptor, thus highlighting the role of pore water drainage and mixing as influential processes forcing tidal creek DO. Study findings suggest that tidal creek DO dynamics are explained by a balance of hydrologic, climatic, and biotic descriptors during warmer seasons due to many of these variables (i.e., chlorophyll-a, water temperature) acting as tracers of estuarine-marsh water mixing; conversely, in early winter months when estuarine and marsh waters differ less distinctly, hydrologic variables increase in relative importance as descriptors of tidal creek DO. These findings underline important distinctions in the underlying mechanisms dictating DO variability in shallow tidal marsh-creek environments relative to open water estuarine systems.

  7. Behavioral and electrophysiological evidence for early and automatic detection of phonological equivalence in variable speech inputs.

    Science.gov (United States)

    Kharlamov, Viktor; Campbell, Kenneth; Kazanina, Nina

    2011-11-01

    Speech sounds are not always perceived in accordance with their acoustic-phonetic content. For example, an early and automatic process of perceptual repair, which ensures conformity of speech inputs to the listener's native language phonology, applies to individual input segments that do not exist in the native inventory or to sound sequences that are illicit according to the native phonotactic restrictions on sound co-occurrences. The present study with Russian and Canadian English speakers shows that listeners may perceive phonetically distinct and licit sound sequences as equivalent when the native language system provides robust evidence for mapping multiple phonetic forms onto a single phonological representation. In Russian, due to an optional but productive t-deletion process that affects /stn/ clusters, the surface forms [sn] and [stn] may be phonologically equivalent and map to a single phonological form /stn/. In contrast, [sn] and [stn] clusters are usually phonologically distinct in (Canadian) English. Behavioral data from identification and discrimination tasks indicated that [sn] and [stn] clusters were more confusable for Russian than for English speakers. The EEG experiment employed an oddball paradigm with nonwords [asna] and [astna] used as the standard and deviant stimuli. A reliable mismatch negativity response was elicited approximately 100 msec postchange in the English group but not in the Russian group. These findings point to a perceptual repair mechanism that is engaged automatically at a prelexical level to ensure immediate encoding of speech inputs in phonological terms, which in turn enables efficient access to the meaning of a spoken utterance.

  8. A numeric comparison of variable selection algorithms for supervised learning

    International Nuclear Information System (INIS)

    Palombo, G.; Narsky, I.

    2009-01-01

    Datasets in modern High Energy Physics (HEP) experiments are often described by dozens or even hundreds of input variables. Reducing a full variable set to a subset that most completely represents information about data is therefore an important task in analysis of HEP data. We compare various variable selection algorithms for supervised learning using several datasets such as, for instance, imaging gamma-ray Cherenkov telescope (MAGIC) data found at the UCI repository. We use classifiers and variable selection methods implemented in the statistical package StatPatternRecognition (SPR), a free open-source C++ package developed in the HEP community ( (http://sourceforge.net/projects/statpatrec/)). For each dataset, we select a powerful classifier and estimate its learning accuracy on variable subsets obtained by various selection algorithms. When possible, we also estimate the CPU time needed for the variable subset selection. The results of this analysis are compared with those published previously for these datasets using other statistical packages such as R and Weka. We show that the most accurate, yet slowest, method is a wrapper algorithm known as generalized sequential forward selection ('Add N Remove R') implemented in SPR.

  9. Review of input stages used in front end electronics for particle detectors

    CERN Document Server

    Kaplon, J

    2015-01-01

    In this paper we present noise analysis of the input stages most commonly used in front end electronics for particle detectors. Analysis shows the calculation of the input referenced noise related to the active devices. It identifies the type, parallel or series, of the equivalent noise sources related to the input transistors, which is the important input for the further choice of the signal processing method. Moreover we calculate the input impedance of amplifiers employed in applications where the particle detector is connected to readout electronics by means of transmission line. We present schematics, small signal models,a complete set of equations, and results of the major steps of calculations for all discussed circuits.

  10. Machine learning for toxicity characterization of organic chemical emissions using USEtox database: Learning the structure of the input space.

    Science.gov (United States)

    Marvuglia, Antonino; Kanevski, Mikhail; Benetto, Enrico

    2015-10-01

    Toxicity characterization of chemical emissions in Life Cycle Assessment (LCA) is a complex task which usually proceeds via multimedia (fate, exposure and effect) models attached to models of dose-response relationships to assess the effects on target. Different models and approaches do exist, but all require a vast amount of data on the properties of the chemical compounds being assessed, which are hard to collect or hardly publicly available (especially for thousands of less common or newly developed chemicals), therefore hampering in practice the assessment in LCA. An example is USEtox, a consensual model for the characterization of human toxicity and freshwater ecotoxicity. This paper places itself in a line of research aiming at providing a methodology to reduce the number of input parameters necessary to run multimedia fate models, focusing in particular to the application of the USEtox toxicity model. By focusing on USEtox, in this paper two main goals are pursued: 1) performing an extensive exploratory analysis (using dimensionality reduction techniques) of the input space constituted by the substance-specific properties at the aim of detecting particular patterns in the data manifold and estimating the dimension of the subspace in which the data manifold actually lies; and 2) exploring the application of a set of linear models, based on partial least squares (PLS) regression, as well as a nonlinear model (general regression neural network--GRNN) in the seek for an automatic selection strategy of the most informative variables according to the modelled output (USEtox factor). After extensive analysis, the intrinsic dimension of the input manifold has been identified between three and four. The variables selected as most informative may vary according to the output modelled and the model used, but for the toxicity factors modelled in this paper the input variables selected as most informative are coherent with prior expectations based on scientific knowledge

  11. Tracing anthropogenic inputs to production in the Seto Inland Sea, Japan - A stable isotope approach

    International Nuclear Information System (INIS)

    Miller, Todd W.; Omori, Koji; Hamaoka, Hideki; Shibata, Jun-ya; Hidejiro, Onishi

    2010-01-01

    The Seto Inland Sea (SIS) receives waste runoff from ∼24% of Japan's total population, yet it is also important in regional fisheries, recreation and commerce. During August 2006 we measured carbon and nitrogen stable isotopes of particulate organic matter (POM) and zooplankton across urban population gradients of the SIS. Results showed a consistent trend of increasing δ 15 N in POM and zooplankton from the western to eastern subsystems of the SIS, corresponding to increasing population load. Principal components analysis of environmental variables indicated high positive loadings of δ 15 N and δ 13 C with high chlorophyll-a and surface water temperatures, and negative loadings of low salinities related to inputs from large rivers and high urban development in the eastern SIS. Anthropogenic nitrogen was therefore readily integrated into the SIS food web from primary production to copepods, which are a critical food source for many commercially important fishes.

  12. Analysis of event tree with imprecise inputs by fuzzy set theory

    International Nuclear Information System (INIS)

    Ahn, Kwang Il; Chun, Moon Hyun

    1990-01-01

    Fuzzy set theory approach is proposed as a method to analyze event trees with imprecise or linguistic input variables such as 'likely' or 'improbable' instead of the numerical probability. In this paper, it is shown how the fuzzy set theory can be applied to the event tree analysis. The result of this study shows that the fuzzy set theory approach can be applied as an acceptable and effective tool for analysis of the event tree with fuzzy type of inputs. Comparisons of the fuzzy theory approach with the probabilistic approach of computing probabilities of final states of the event tree through subjective weighting factors and LHS technique show that the two approaches have common factors and give reasonable results

  13. ColloInputGenerator

    DEFF Research Database (Denmark)

    2013-01-01

    This is a very simple program to help you put together input files for use in Gries' (2007) R-based collostruction analysis program. It basically puts together a text file with a frequency list of lexemes in the construction and inserts a column where you can add the corpus frequencies. It requires...... it as input for basic collexeme collostructional analysis (Stefanowitsch & Gries 2003) in Gries' (2007) program. ColloInputGenerator is, in its current state, based on programming commands introduced in Gries (2009). Projected updates: Generation of complete work-ready frequency lists....

  14. Limitations of the usual blood-pressure hypothesis and importance of variability, instability, and episodic hypertension.

    Science.gov (United States)

    Rothwell, Peter M

    2010-03-13

    Although hypertension is the most prevalent treatable vascular risk factor, how it causes end-organ damage and vascular events is poorly understood. Yet, a widespread belief exists that underlying usual blood pressure can alone account for all blood-pressure-related risk of vascular events and for the benefits of antihypertensive drugs, and this notion has come to underpin all major clinical guidelines on diagnosis and treatment of hypertension. Other potentially informative measures, such as variability in clinic blood pressure or maximum blood pressure reached, have been neglected, and effects of antihypertensive drugs on such measures are largely unknown. Clinical guidelines recommend that episodic hypertension is not treated, and the potential risks of residual variability in blood pressure in treated hypertensive patients have been ignored. This Review discusses shortcomings of the usual blood-pressure hypothesis, provides background to accompanying reports on the importance of blood-pressure variability in prediction of risk of vascular events and in accounting for benefits of antihypertensive drugs, and draws attention to clinical implications and directions for future research. Copyright 2010 Elsevier Ltd. All rights reserved.

  15. Input or intimacy

    Directory of Open Access Journals (Sweden)

    Judit Navracsics

    2014-01-01

    Full Text Available According to the critical period hypothesis, the earlier the acquisition of a second language starts, the better. Owing to the plasticity of the brain, up until a certain age a second language can be acquired successfully according to this view. Early second language learners are commonly said to have an advantage over later ones especially in phonetic/phonological acquisition. Native-like pronunciation is said to be most likely to be achieved by young learners. However, there is evidence of accentfree speech in second languages learnt after puberty as well. Occasionally, on the other hand, a nonnative accent may appear even in early second (or third language acquisition. Cross-linguistic influences are natural in multilingual development, and we would expect the dominant language to have an impact on the weaker one(s. The dominant language is usually the one that provides the largest amount of input for the child. But is it always the amount that counts? Perhaps sometimes other factors, such as emotions, ome into play? In this paper, data obtained from an EnglishPersian-Hungarian trilingual pair of siblings (under age 4 and 3 respectively is analyzed, with a special focus on cross-linguistic influences at the phonetic/phonological levels. It will be shown that beyond the amount of input there are more important factors that trigger interference in multilingual development.

  16. Estimating net present value variability for deterministic models

    NARCIS (Netherlands)

    van Groenendaal, W.J.H.

    1995-01-01

    For decision makers the variability in the net present value (NPV) of an investment project is an indication of the project's risk. So-called risk analysis is one way to estimate this variability. However, risk analysis requires knowledge about the stochastic character of the inputs. For large,

  17. Input frequency and lexical variability in phonological development: a survival analysis of word-initial cluster production.

    Science.gov (United States)

    Ota, Mitsuhiko; Green, Sam J

    2013-06-01

    Although it has been often hypothesized that children learn to produce new sound patterns first in frequently heard words, the available evidence in support of this claim is inconclusive. To re-examine this question, we conducted a survival analysis of word-initial consonant clusters produced by three children in the Providence Corpus (0 ; 11-4 ; 0). The analysis took account of several lexical factors in addition to lexical input frequency, including the age of first production, production frequency, neighborhood density and number of phonemes. The results showed that lexical input frequency was a significant predictor of the age at which the accuracy level of cluster production in each word first reached 80%. The magnitude of the frequency effect differed across cluster types. Our findings indicate that some of the between-word variance found in the development of sound production can indeed be attributed to the frequency of words in the child's ambient language.

  18. Muscle synergies in neuroscience and robotics: from input-space to task-space perspectives

    Directory of Open Access Journals (Sweden)

    Cristiano eAlessandro

    2013-04-01

    Full Text Available In this paper we review the works related to muscle synergies that have been carried-out in neuroscience and control engineering. In particular, we refer to the hypothesis that the central nervous system (CNS generates desired muscle contractions by combining a small number of predefined modules, called muscle synergies. We provide an overview of the methods that have been employed to test the validity of this scheme, and we show how the concept of muscle synergy has been generalized for the control of artificial agents. The comparison between these two lines of research, in particular their different goals and approaches, is instrumental to explain the computational implications of the hypothesized modular organization. Moreover, it clarifies the importance of assessing the functional role of muscle synergies: although these basic modules are defined at the level of muscle activations (input-space, they should result in the effective accomplishment of the desired task. This requirement is not always explicitly considered in experimental neuroscience, as muscle synergies are often estimated solely by analyzing recorded muscle activities. We suggest that synergy extraction methods should explicitly take into account task execution variables, thus moving from a perspective purely based on input-space to one grounded on task-space as well.

  19. Input-output linearizing tracking control of induction machine with the included magnetic saturation

    DEFF Research Database (Denmark)

    Dolinar, Drago; Ljusev, Petar; Stumberger, Gorazd

    2003-01-01

    The tracking control design of an induction motor, based on input-output linearisation with magnetic saturation included is addressed. The magnetic saturation is represented by a nonlinear magnetising curve for the iron core and is used in the control, the observer of the state variables......, and in the load torque estimator. An input-output linearising control is used to achieve better tracking performances. It is based on the mixed 'stator current - rotor flux linkage' induction motor model with magnetic saturation considered in the stationary reference frame. Experimental results show...... that the proposed input-output linearising tracking control with saturation included behaves considerably better than the one without saturation, and that it introduces smaller position and speed errors, and better motor stiffness on account of the increased computational complexity....

  20. Variability in the Second Language Acquisition of Verb Morphology ...

    African Journals Online (AJOL)

    This article seeks to make a developmental study of variability in the acquisition of verb morphology by second language (L2) pupils who learn at an English input impoverished school where variability in learner language is often presumed to be quite extensive. By studying variability in such settings, it is hoped that we can ...

  1. The Effect of Visual Variability on the Learning of Academic Concepts.

    Science.gov (United States)

    Bourgoyne, Ashley; Alt, Mary

    2017-06-10

    The purpose of this study was to identify effects of variability of visual input on development of conceptual representations of academic concepts for college-age students with normal language (NL) and those with language-learning disabilities (LLD). Students with NL (n = 11) and LLD (n = 11) participated in a computer-based training for introductory biology course concepts. Participants were trained on half the concepts under a low-variability condition and half under a high-variability condition. Participants completed a posttest in which they were asked to identify and rate the accuracy of novel and trained visual representations of the concepts. We performed separate repeated measures analyses of variance to examine the accuracy of identification and ratings. Participants were equally accurate on trained and novel items in the high-variability condition, but were less accurate on novel items only in the low-variability condition. The LLD group showed the same pattern as the NL group; they were just less accurate. Results indicated that high-variability visual input may facilitate the acquisition of academic concepts in college students with NL and LLD. High-variability visual input may be especially beneficial for generalization to novel representations of concepts. Implicit learning methods may be harnessed by college courses to provide students with basic conceptual knowledge when they are entering courses or beginning new units.

  2. Prognostic importance of glycaemic variability on hospital mortality in patients hospitalised in Internal Medicine Departments.

    Science.gov (United States)

    Sáenz-Abad, D; Gimeno-Orna, J A; Pérez-Calvo, J I

    2015-12-01

    The objective was to assess the prognostic importance of various glycaemic control measures on hospital mortality. Retrospective, analytical cohort study that included patients hospitalised in internal medicine departments with a diagnosis related to diabetes mellitus (DM), excluding acute decompensations. The clinical endpoint was hospital mortality. We recorded clinical, analytical and glycaemic control-related variables (scheduled insulin administration, plasma glycaemia at admission, HbA1c, mean glycaemia (MG) and in-hospital glycaemic variability and hypoglycaemia). The measurement of hospital mortality predictors was performed using univariate and multivariate logistic regression. A total of 384 patients (50.3% men) were included. The mean age was 78.5 (SD, 10.3) years. The DM-related diagnoses were type 2 diabetes (83.6%) and stress hyperglycaemia (6.8%). Thirty-one (8.1%) patients died while in hospital. In the multivariate analysis, the best model for predicting mortality (R(2)=0.326; P<.0001) consisted, in order of importance, of age (χ(2)=8.19; OR=1.094; 95% CI 1.020-1.174; P=.004), Charlson index (χ(2)=7.28; OR=1.48; 95% CI 1.11-1.99; P=.007), initial glycaemia (χ(2)=6.05; OR=1.007; 95% CI 1.001-1.014; P=.014), HbA1c (χ(2)=5.76; OR=0.59; 95% CI 0.33-1; P=.016), glycaemic variability (χ(2)=4.41; OR=1.031; 95% CI 1-1.062; P=.036), need for corticosteroid treatment (χ(2)=4.03; OR=3.1; 95% CI 1-9.64; P=.045), administration of scheduled insulin (χ(2)=3.98; OR=0.26; 95% CI 0.066-1; P=.046) and systolic blood pressure (χ(2)=2.92; OR=0.985; 95% CI 0.97-1.003; P=.088). An increase in initial glycaemia and in-hospital glycaemic variability predict the risk of mortality for hospitalised patients with DM. Copyright © 2015 Elsevier España, S.L.U. y Sociedad Española de Medicina Interna (SEMI). All rights reserved.

  3. Concepts in production ecology for analysis and quantification of agricultural input-output combinations.

    NARCIS (Netherlands)

    Ittersum, van M.K.; Rabbinge, R.

    1997-01-01

    Definitions and concepts of production ecology are presented as a basis for development of alternative production technologies characterized by their input-output combinations. With these concepts the relative importance of several growth factors and inputs is investigated to explain actual yield

  4. A new importance measure for sensitivity analysis

    International Nuclear Information System (INIS)

    Liu, Qiao; Homma, Toshimitsu

    2010-01-01

    Uncertainty is an integral part of risk assessment of complex engineering systems, such as nuclear power plants and space crafts. The aim of sensitivity analysis is to identify the contribution of the uncertainty in model inputs to the uncertainty in the model output. In this study, a new importance measure that characterizes the influence of the entire input distribution on the entire output distribution was proposed. It represents the expected deviation of the cumulative distribution function (CDF) of the model output that would be obtained when one input parameter of interest were known. The applicability of this importance measure was tested with two models, a nonlinear nonmonotonic mathematical model and a risk model. In addition, a comparison of this new importance measure with several other importance measures was carried out and the differences between these measures were explained. (author)

  5. The impact of 14nm photomask variability and uncertainty on computational lithography solutions

    Science.gov (United States)

    Sturtevant, John; Tejnil, Edita; Buck, Peter D.; Schulze, Steffen; Kalk, Franklin; Nakagawa, Kent; Ning, Guoxiang; Ackmann, Paul; Gans, Fritz; Buergel, Christian

    2013-09-01

    Computational lithography solutions rely upon accurate process models to faithfully represent the imaging system output for a defined set of process and design inputs. These models rely upon the accurate representation of multiple parameters associated with the scanner and the photomask. Many input variables for simulation are based upon designed or recipe-requested values or independent measurements. It is known, however, that certain measurement methodologies, while precise, can have significant inaccuracies. Additionally, there are known errors associated with the representation of certain system parameters. With shrinking total CD control budgets, appropriate accounting for all sources of error becomes more important, and the cumulative consequence of input errors to the computational lithography model can become significant. In this work, we examine via simulation, the impact of errors in the representation of photomask properties including CD bias, corner rounding, refractive index, thickness, and sidewall angle. The factors that are most critical to be accurately represented in the model are cataloged. CD bias values are based on state of the art mask manufacturing data and other variables changes are speculated, highlighting the need for improved metrology and communication between mask and OPC model experts. The simulations are done by ignoring the wafer photoresist model, and show the sensitivity of predictions to various model inputs associated with the mask. It is shown that the wafer simulations are very dependent upon the 1D/2D representation of the mask and for 3D, that the mask sidewall angle is a very sensitive factor influencing simulated wafer CD results.

  6. The input and output management of solid waste using DEA models: A case study at Jengka, Pahang

    Science.gov (United States)

    Mohamed, Siti Rosiah; Ghazali, Nur Fadzrina Mohd; Mohd, Ainun Hafizah

    2017-08-01

    Data Envelopment Analysis (DEA) as a tool for obtaining performance indices has been used extensively in several of organizations sector. The ways to improve the efficiency of Decision Making Units (DMUs) is impractical because some of inputs and outputs are uncontrollable and in certain situation its produce weak efficiency which often reflect the impact for operating environment. Based on the data from Alam Flora Sdn. Bhd Jengka, the researcher wants to determine the efficiency of solid waste management (SWM) in town Jengka Pahang using CCRI and CCRO model of DEA and duality formulation with vector average input and output. Three input variables (length collection in meter, frequency time per week in hour and number of garbage truck) and 2 outputs variables (frequency collection and the total solid waste collection in kilogram) are analyzed. As a conclusion, it shows only three roads from 23 roads are efficient that achieve efficiency score 1. Meanwhile, 20 other roads are in an inefficient management.

  7. Effect of input variability on the quality of laser shock processing

    Energy Technology Data Exchange (ETDEWEB)

    Arif, Abul Fazal M. [King Fahd University of Petroleum and Minerals, Dhahran (Saudi Arabia)

    2009-10-15

    Laser shock processing (LSP) involves high-energy laser radiation combined with suitable overlays to generate highpressure pulses on the surface of the metal. The stress wave generated due to high pressure pulses propagates into the material causing the surface layer to yield and plastically deform, and thereby, develop a significant residual compressive stress in the surface region of the substrate material. The developed compressive stress field is beneficial to improve surface properties such as fatigue, wear, and corrosion. To improve the understanding of the shock hardening process, investigation into the physical processes involved is necessary. In the first part of this paper, the temporal variation in the pressure intensity and spot size is calculated by using a two-dimensional recoil pressure prediction model. Using an explicit non-linear FEA code, ANSYS LS-DYNA, the deformation behavior and residual stresses in the substrate material are predicted. In the second part, a probabilistic approach to the modeling and analysis of LSP is presented in this paper. Various factors that affect the probabilistic performance of the LSP are grouped into categories and a select number of factors known to be significant, for which the variability could be assessed, are modeled as random variables (such as recoil pressure, laser beam spot size, substrate material properties and others). The potential of the probabilistic approach in predicting the structural integrity of the laser-shocked components is addressed

  8. Effect of input variability on the quality of laser shock processing

    International Nuclear Information System (INIS)

    Arif, Abul Fazal M.

    2009-01-01

    Laser shock processing (LSP) involves high-energy laser radiation combined with suitable overlays to generate highpressure pulses on the surface of the metal. The stress wave generated due to high pressure pulses propagates into the material causing the surface layer to yield and plastically deform, and thereby, develop a significant residual compressive stress in the surface region of the substrate material. The developed compressive stress field is beneficial to improve surface properties such as fatigue, wear, and corrosion. To improve the understanding of the shock hardening process, investigation into the physical processes involved is necessary. In the first part of this paper, the temporal variation in the pressure intensity and spot size is calculated by using a two-dimensional recoil pressure prediction model. Using an explicit non-linear FEA code, ANSYS LS-DYNA, the deformation behavior and residual stresses in the substrate material are predicted. In the second part, a probabilistic approach to the modeling and analysis of LSP is presented in this paper. Various factors that affect the probabilistic performance of the LSP are grouped into categories and a select number of factors known to be significant, for which the variability could be assessed, are modeled as random variables (such as recoil pressure, laser beam spot size, substrate material properties and others). The potential of the probabilistic approach in predicting the structural integrity of the laser-shocked components is addressed

  9. Modeling Short-Range Soil Variability and its Potential Use in Variable-Rate Treatment of Experimental Plots

    Directory of Open Access Journals (Sweden)

    A Moameni

    2011-02-01

    Full Text Available Abstract In Iran, the experimental plots under fertilizer trials are managed in such a way that the whole plot area uniformly receives agricultural inputs. This could lead to biased research results and hence to suppressing of the efforts made by the researchers. This research was conducted in a selected site belonging to the Gonbad Agricultural Research Station, located in the semiarid region, northeastern Iran. The aim was to characterize the short-range spatial variability of the inherent and management-depended soil properties and to determine if this variation is large and can be managed at practical scales. The soils were sampled using a grid 55 m apart. In total, 100 composite soil samples were collected from topsoil (0-30 cm and were analyzed for calcium carbonate equivalent, organic carbon, clay, available phosphorus, available potassium, iron, copper, zinc and manganese. Descriptive statistics were applied to check data trends. Geostatistical analysis was applied to variography, model fitting and contour mapping. Sampling at 55 m made it possible to split the area of the selected experimental plot into relatively uniform areas that allow application of agricultural inputs with variable rates. Keywords: Short-range soil variability, Within-field soil variability, Interpolation, Precision agriculture, Geostatistics

  10. Input-profile-based software failure probability quantification for safety signal generation systems

    International Nuclear Information System (INIS)

    Kang, Hyun Gook; Lim, Ho Gon; Lee, Ho Jung; Kim, Man Cheol; Jang, Seung Cheol

    2009-01-01

    The approaches for software failure probability estimation are mainly based on the results of testing. Test cases represent the inputs, which are encountered in an actual use. The test inputs for the safety-critical application such as a reactor protection system (RPS) of a nuclear power plant are the inputs which cause the activation of protective action such as a reactor trip. A digital system treats inputs from instrumentation sensors as discrete digital values by using an analog-to-digital converter. Input profile must be determined in consideration of these characteristics for effective software failure probability quantification. Another important characteristic of software testing is that we do not have to repeat the test for the same input value since the software response is deterministic for each specific digital input. With these considerations, we propose an effective software testing method for quantifying the failure probability. As an example application, the input profile of the digital RPS is developed based on the typical plant data. The proposed method in this study is expected to provide a simple but realistic mean to quantify the software failure probability based on input profile and system dynamics.

  11. Simplex-based optimization of numerical and categorical inputs in early bioprocess development: Case studies in HT chromatography.

    Science.gov (United States)

    Konstantinidis, Spyridon; Titchener-Hooker, Nigel; Velayudhan, Ajoy

    2017-08-01

    Bioprocess development studies often involve the investigation of numerical and categorical inputs via the adoption of Design of Experiments (DoE) techniques. An attractive alternative is the deployment of a grid compatible Simplex variant which has been shown to yield optima rapidly and consistently. In this work, the method is combined with dummy variables and it is deployed in three case studies wherein spaces are comprised of both categorical and numerical inputs, a situation intractable by traditional Simplex methods. The first study employs in silico data and lays out the dummy variable methodology. The latter two employ experimental data from chromatography based studies performed with the filter-plate and miniature column High Throughput (HT) techniques. The solute of interest in the former case study was a monoclonal antibody whereas the latter dealt with the separation of a binary system of model proteins. The implemented approach prevented the stranding of the Simplex method at local optima, due to the arbitrary handling of the categorical inputs, and allowed for the concurrent optimization of numerical and categorical, multilevel and/or dichotomous, inputs. The deployment of the Simplex method, combined with dummy variables, was therefore entirely successful in identifying and characterizing global optima in all three case studies. The Simplex-based method was further shown to be of equivalent efficiency to a DoE-based approach, represented here by D-Optimal designs. Such an approach failed, however, to both capture trends and identify optima, and led to poor operating conditions. It is suggested that the Simplex-variant is suited to development activities involving numerical and categorical inputs in early bioprocess development. © 2017 The Authors. Biotechnology Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  12. Hypothesis: Low frequency heart rate variability (LF-HRV) is an input for undisclosed yet biological adaptive control, governing the cardiovascular regulations to assure optimal functioning.

    Science.gov (United States)

    Gabbay, Uri; Bobrovsky, Ben Zion

    2012-02-01

    Cardiovascular regulation is considered today as having three levels: autoregulations, neural regulations and hormonal regulations. We hypothesize that the cardiovascular regulation has an additional (fourth) control level which is outer, hierarchical (adaptive) loop where LF-HRV amplitude serves as a reference input which the neural cardiovascular center detects and responses in order to maintain LF-HRV around some prescribed level. Supporting evidences: LF-HRV absence during artificial cardiac pacing may be associated with "pacemaker syndrome" which had not been sufficiently understood regardless of apparently unimpaired cardiovascular performance. The hypothesis may provide an essential basis for understanding several cardiovascular morbidities and insight toward diagnostic measures and treatments (including but not limited to adding variability to the pulse generator of artificial pacemakers to eliminate "pace maker syndrome"). Copyright © 2011 Elsevier Ltd. All rights reserved.

  13. Total dose induced increase in input offset voltage in JFET input operational amplifiers

    International Nuclear Information System (INIS)

    Pease, R.L.; Krieg, J.; Gehlhausen, M.; Black, J.

    1999-01-01

    Four different types of commercial JFET input operational amplifiers were irradiated with ionizing radiation under a variety of test conditions. All experienced significant increases in input offset voltage (Vos). Microprobe measurement of the electrical characteristics of the de-coupled input JFETs demonstrates that the increase in Vos is a result of the mismatch of the degraded JFETs. (authors)

  14. Litter input controls on soil carbon in a temperate deciduous forest

    DEFF Research Database (Denmark)

    Bowden, Richard D.; Deem, Lauren; Plante, Alain F.

    2014-01-01

    Above- and belowground litter inputs in a temperate deciduous forest were altered for 20 yr to determine the importance of leaves and roots on soil C and soil organic matter (SOM) quantity and quality. Carbon and SOM quantity and quality were measured in the O horizon and mineral soil to 50 cm...... soil C, but decreases in litter inputs resulted in rapid soil C declines. Root litter may ultimately provide more stable sources of soil C. Management activities or environmental alterations that decrease litter inputs in mature forests can lower soil C content; however, increases in forest...

  15. Statistical Dependence of Pipe Breaks on Explanatory Variables

    Directory of Open Access Journals (Sweden)

    Patricia Gómez-Martínez

    2017-02-01

    Full Text Available Aging infrastructure is the main challenge currently faced by water suppliers. Estimation of assets lifetime requires reliable criteria to plan assets repair and renewal strategies. To do so, pipe break prediction is one of the most important inputs. This paper analyzes the statistical dependence of pipe breaks on explanatory variables, determining their optimal combination and quantifying their influence on failure prediction accuracy. A large set of registered data from Madrid water supply network, managed by Canal de Isabel II, has been filtered, classified and studied. Several statistical Bayesian models have been built and validated from the available information with a technique that combines reference periods of time as well as geographical location. Statistical models of increasing complexity are built from zero up to five explanatory variables following two approaches: a set of independent variables or a combination of two joint variables plus an additional number of independent variables. With the aim of finding the variable combination that provides the most accurate prediction, models are compared following an objective validation procedure based on the model skill to predict the number of pipe breaks in a large set of geographical locations. As expected, model performance improves as the number of explanatory variables increases. However, the rate of improvement is not constant. Performance metrics improve significantly up to three variables, but the tendency is softened for higher order models, especially in trunk mains where performance is reduced. Slight differences are found between trunk mains and distribution lines when selecting the most influent variables and models.

  16. Modelling Implicit Communication in Multi-Agent Systems with Hybrid Input/Output Automata

    Directory of Open Access Journals (Sweden)

    Marta Capiluppi

    2012-10-01

    Full Text Available We propose an extension of Hybrid I/O Automata (HIOAs to model agent systems and their implicit communication through perturbation of the environment, like localization of objects or radio signals diffusion and detection. To this end we decided to specialize some variables of the HIOAs whose values are functions both of time and space. We call them world variables. Basically they are treated similarly to the other variables of HIOAs, but they have the function of representing the interaction of each automaton with the surrounding environment, hence they can be output, input or internal variables. Since these special variables have the role of simulating implicit communication, their dynamics are specified both in time and space, because they model the perturbations induced by the agent to the environment, and the perturbations of the environment as perceived by the agent. Parallel composition of world variables is slightly different from parallel composition of the other variables, since their signals are summed. The theory is illustrated through a simple example of agents systems.

  17. Importance of Non-invasive Right and Left Ventricular Variables on Exercise Capacity in Patients with Tetralogy of Fallot Hemodynamics.

    Science.gov (United States)

    Meierhofer, Christian; Tavakkoli, Timon; Kühn, Andreas; Ulm, Kurt; Hager, Alfred; Müller, Jan; Martinoff, Stefan; Ewert, Peter; Stern, Heiko

    2017-12-01

    Good quality of life correlates with a good exercise capacity in daily life in patients with tetralogy of Fallot (ToF). Patients after correction of ToF usually develop residual defects such as pulmonary regurgitation or stenosis of variable severity. However, the importance of different hemodynamic parameters and their impact on exercise capacity is unclear. We investigated several hemodynamic parameters measured by cardiovascular magnetic resonance (CMR) and echocardiography and evaluated which parameter has the most pronounced effect on maximal exercise capacity determined by cardiopulmonary exercise testing (CPET). 132 patients with ToF-like hemodynamics were tested during routine follow-up with CMR, echocardiography and CPET. Right and left ventricular volume data, ventricular ejection fraction and pulmonary regurgitation were evaluated by CMR. Echocardiographic pressure gradients in the right ventricular outflow tract and through the tricuspid valve were measured. All data were classified and correlated with the results of CPET evaluations of these patients. The analysis was performed using the Random Forest model. In this way, we calculated the importance of the different hemodynamic variables related to the maximal oxygen uptake in CPET (VO 2 %predicted). Right ventricular pressure showed the most important influence on maximal oxygen uptake, whereas pulmonary regurgitation and right ventricular enddiastolic volume were not important hemodynamic variables to predict maximal oxygen uptake in CPET. Maximal exercise capacity was only very weakly influenced by right ventricular enddiastolic volume and not at all by pulmonary regurgitation in patients with ToF. The variable with the most pronounced influence was the right ventricular pressure.

  18. Tracing anthropogenic inputs to production in the Seto Inland Sea, Japan--a stable isotope approach.

    Science.gov (United States)

    Miller, Todd W; Omori, Koji; Hamaoka, Hideki; Shibata, Jun-ya; Hidejiro, Onishi

    2010-10-01

    The Seto Inland Sea (SIS) receives waste runoff from ∼24% of Japan's total population, yet it is also important in regional fisheries, recreation and commerce. During August 2006 we measured carbon and nitrogen stable isotopes of particulate organic matter (POM) and zooplankton across urban population gradients of the SIS. Results showed a consistent trend of increasing δ(15)N in POM and zooplankton from the western to eastern subsystems of the SIS, corresponding to increasing population load. Principal components analysis of environmental variables indicated high positive loadings of δ(15)N and δ(13)C with high chlorophyll-a and surface water temperatures, and negative loadings of low salinities related to inputs from large rivers and high urban development in the eastern SIS. Anthropogenic nitrogen was therefore readily integrated into the SIS food web from primary production to copepods, which are a critical food source for many commercially important fishes. Copyright © 2010 Elsevier Ltd. All rights reserved.

  19. Metacognitive Instruction: Global and Local Shifts in Considering Listening Input

    Directory of Open Access Journals (Sweden)

    Hossein Bozorgian

    2013-01-01

    Full Text Available A key shift of thinking for effective learning and teaching of listening input has been seen and organized in education locally and globally. This study has probed whether metacognitive instruction through a pedagogical cycle shifts high-intermediate students' English language learning and English as a second language (ESL teacher's teaching focus on listening input. Twenty male Iranian students with an age range of 18 to 24 received a guided methodology including metacognitive strategies (planning, monitoring, and evaluation for a period of three months. This study has used the strategies and probed the importance of metacognitive instruction through interviewing both the teacher and the students. The results have shown that metacognitive instruction helped both the ESL teacher's and the students' shift of thinking about teaching and learning listening input. This key shift of thinking has implications globally and locally for classroom practices of listening input.

  20. Fault diagnosis of an intelligent hydraulic pump based on a nonlinear unknown input observer

    Directory of Open Access Journals (Sweden)

    Zhonghai MA

    2018-02-01

    Full Text Available Hydraulic piston pumps are commonly used in aircraft. In order to improve the viability of aircraft and energy efficiency, intelligent variable pressure pump systems have been used in aircraft hydraulic systems more and more widely. Efficient fault diagnosis plays an important role in improving the reliability and performance of hydraulic systems. In this paper, a fault diagnosis method of an intelligent hydraulic pump system (IHPS based on a nonlinear unknown input observer (NUIO is proposed. Different from factors of a full-order Luenberger-type unknown input observer, nonlinear factors of the IHPS are considered in the NUIO. Firstly, a new type of intelligent pump is presented, the mathematical model of which is established to describe the IHPS. Taking into account the real-time requirements of the IHPS and the special structure of the pump, the mechanism of the intelligent pump and failure modes are analyzed and two typical failure modes are obtained. Furthermore, a NUIO of the IHPS is performed based on the output pressure and swashplate angle signals. With the residual error signals produced by the NUIO, online intelligent pump failure occurring in real-time can be detected. Lastly, through analysis and simulation, it is confirmed that this diagnostic method could accurately diagnose and isolate those typical failure modes of the nonlinear IHPS. The method proposed in this paper is of great significance in improving the reliability of the IHPS. Keywords: Fault diagnosis, Hydraulic piston pump, Model-based, Nonlinear unknown input observer (NUIO, Residual error

  1. Multimedia Environmental Pollutant Assessment System (MEPAS) application guidance. Guidelines for evaluating MEPAS input parameters for Version 3.1

    International Nuclear Information System (INIS)

    Buck, J.W.; Whelan, G.; Droppo, J.G. Jr.; Strenge, D.L.; Castleton, K.J.; McDonald, J.P.; Sato, C.; Streile, G.P.

    1995-02-01

    The Multimedia Environmental Pollutant Assessment System (MEPAS) was developed by Pacific Northwest Laboratory (PNL) for the U.S. Department of Energy (DOE) Office of Environment, Safety and Health and Office of Environmental Management and Environmental Restoration. MEPAS is a set of computer codes developed to provide decision makers with risk information integrated for hazardous, radioactive, and mixed-waste sites based on their potential hazard to public health. It is applicable to a wide range of environmental management and regulatory conditions, including inactive sites covered under the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) and active air and water releases covered under the Clean Air Act, the Clean Water Act, and the Resource Conservation and Recovery Act. MEPAS integrates contaminant release, transport, and exposure models into a single system. An interactive user interface assists the investigator in defining problems, assembling data and entering input, and developing reports. PNL has compiled two documents that explain the methodology behind the MEPAS model and instruct the user in how to input, retrieve, and evaluate data. This report contains detailed guidelines for defining the input data required to conduct an analysis with MEPAS. Entries for each variable have a short definition, units, and text explaining what a variable is and how it can be quantified. As appropriate, ranges and typical values are given. This report also contains listings of the input screens (worksheets) that are used in the MEPAS user interface for these variables

  2. Statistical Analysis of Input Parameters Impact on the Modelling of Underground Structures

    Directory of Open Access Journals (Sweden)

    M. Hilar

    2008-01-01

    Full Text Available The behaviour of a geomechanical model and its final results are strongly affected by the input parameters. As the inherent variability of rock mass is difficult to model, engineers are frequently forced to face the question “Which input values should be used for analyses?” The correct answer to such a question requires a probabilistic approach, considering the uncertainty of site investigations and variation in the ground. This paper describes the statistical analysis of input parameters for FEM calculations of traffic tunnels in the city of Prague. At the beginning of the paper, the inaccuracy in the geotechnical modelling is discussed. In the following part the Fuzzy techniques are summarized, including information about an application of the Fuzzy arithmetic on the shotcrete parameters. The next part of the paper is focused on the stochastic simulation – Monte Carlo Simulation is briefly described, Latin Hypercubes method is described more in details. At the end several practical examples are described: statistical analysis of the input parameters on the numerical modelling of the completed Mrázovka tunnel (profile West Tunnel Tube km 5.160 and modelling of the constructed tunnel Špejchar – Pelc Tyrolka. 

  3. Interleaved Boost-Half-Bridge Dual–Input DC-DC Converter with a PWM plus Phase-Shift Control for Fuel Cell Applications

    DEFF Research Database (Denmark)

    Zhang, Zhe; Andersen, Michael A. E.

    2013-01-01

    This paper presents an isolated dual-input DC-DC converter with a PWM plus phase-shift control for fuel cell hybrid energy systems. The power switches are controlled by phase shifted PWM signals with a variable duty cycle, and thus the two input voltages as well as the output voltage can...

  4. Two-Stage Variable Sample-Rate Conversion System

    Science.gov (United States)

    Tkacenko, Andre

    2009-01-01

    A two-stage variable sample-rate conversion (SRC) system has been pro posed as part of a digital signal-processing system in a digital com munication radio receiver that utilizes a variety of data rates. The proposed system would be used as an interface between (1) an analog- todigital converter used in the front end of the receiver to sample an intermediatefrequency signal at a fixed input rate and (2) digita lly implemented tracking loops in subsequent stages that operate at v arious sample rates that are generally lower than the input sample r ate. This Two-Stage System would be capable of converting from an input sample rate to a desired lower output sample rate that could be var iable and not necessarily a rational fraction of the input rate.

  5. How input fluctuations reshape the dynamics of a biological switching system

    Science.gov (United States)

    Hu, Bo; Kessler, David A.; Rappel, Wouter-Jan; Levine, Herbert

    2012-12-01

    An important task in quantitative biology is to understand the role of stochasticity in biochemical regulation. Here, as an extension of our recent work [Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.107.148101 107, 148101 (2011)], we study how input fluctuations affect the stochastic dynamics of a simple biological switch. In our model, the on transition rate of the switch is directly regulated by a noisy input signal, which is described as a non-negative mean-reverting diffusion process. This continuous process can be a good approximation of the discrete birth-death process and is much more analytically tractable. Within this setup, we apply the Feynman-Kac theorem to investigate the statistical features of the output switching dynamics. Consistent with our previous findings, the input noise is found to effectively suppress the input-dependent transitions. We show analytically that this effect becomes significant when the input signal fluctuates greatly in amplitude and reverts slowly to its mean.

  6. A latent low-dimensional common input drives a pool of motor neurons: a probabilistic latent state-space model.

    Science.gov (United States)

    Feeney, Daniel F; Meyer, François G; Noone, Nicholas; Enoka, Roger M

    2017-10-01

    Motor neurons appear to be activated with a common input signal that modulates the discharge activity of all neurons in the motor nucleus. It has proven difficult for neurophysiologists to quantify the variability in a common input signal, but characterization of such a signal may improve our understanding of how the activation signal varies across motor tasks. Contemporary methods of quantifying the common input to motor neurons rely on compiling discrete action potentials into continuous time series, assuming the motor pool acts as a linear filter, and requiring signals to be of sufficient duration for frequency analysis. We introduce a space-state model in which the discharge activity of motor neurons is modeled as inhomogeneous Poisson processes and propose a method to quantify an abstract latent trajectory that represents the common input received by motor neurons. The approach also approximates the variation in synaptic noise in the common input signal. The model is validated with four data sets: a simulation of 120 motor units, a pair of integrate-and-fire neurons with a Renshaw cell providing inhibitory feedback, the discharge activity of 10 integrate-and-fire neurons, and the discharge times of concurrently active motor units during an isometric voluntary contraction. The simulations revealed that a latent state-space model is able to quantify the trajectory and variability of the common input signal across all four conditions. When compared with the cumulative spike train method of characterizing common input, the state-space approach was more sensitive to the details of the common input current and was less influenced by the duration of the signal. The state-space approach appears to be capable of detecting rather modest changes in common input signals across conditions. NEW & NOTEWORTHY We propose a state-space model that explicitly delineates a common input signal sent to motor neurons and the physiological noise inherent in synaptic signal

  7. Quantified carbon input for maintaining existing soil organic carbon stocks in global wheat systems

    Science.gov (United States)

    Wang, G.

    2017-12-01

    Soil organic carbon (SOC) dynamics in croplands is a crucial component of global carbon (C) cycle. Depending on local environmental conditions and management practices, typical C input is generally required to reduce or reverse C loss in agricultural soils. No studies have quantified the critical C input for maintaining SOC at global scale with high resolution. Such information will provide a baseline map for assessing soil C dynamics under potential changes in management practices and climate, and thus enable development of management strategies to reduce C footprint from farm to regional scales. We used the soil C model RothC to simulate the critical C input rates needed to maintain existing soil C level at 0.1°× 0.1° resolution in global wheat systems. On average, the critical C input was estimated to be 2.0 Mg C ha-1 yr-1, with large spatial variability depending on local soil and climatic conditions. Higher C inputs are required in wheat system of central United States and western Europe, mainly due to the higher current soil C stocks present in these regions. The critical C input could be effectively estimated using a summary model driven by current SOC level, mean annual temperature, precipitation, and soil clay content.

  8. Critical carbon input to maintain current soil organic carbon stocks in global wheat systems.

    Science.gov (United States)

    Wang, Guocheng; Luo, Zhongkui; Han, Pengfei; Chen, Huansheng; Xu, Jingjing

    2016-01-13

    Soil organic carbon (SOC) dynamics in croplands is a crucial component of global carbon (C) cycle. Depending on local environmental conditions and management practices, typical C input is generally required to reduce or reverse C loss in agricultural soils. No studies have quantified the critical C input for maintaining SOC at global scale with high resolution. Such information will provide a baseline map for assessing soil C dynamics under potential changes in management practices and climate, and thus enable development of management strategies to reduce C footprint from farm to regional scales. We used the soil C model RothC to simulate the critical C input rates needed to maintain existing soil C level at 0.1° × 0.1° resolution in global wheat systems. On average, the critical C input was estimated to be 2.0 Mg C ha(-1) yr(-1), with large spatial variability depending on local soil and climatic conditions. Higher C inputs are required in wheat system of central United States and western Europe, mainly due to the higher current soil C stocks present in these regions. The critical C input could be effectively estimated using a summary model driven by current SOC level, mean annual temperature, precipitation, and soil clay content.

  9. Sensory Synergy as Environmental Input Integration

    Directory of Open Access Journals (Sweden)

    Fady eAlnajjar

    2015-01-01

    Full Text Available The development of a method to feed proper environmental inputs back to the central nervous system (CNS remains one of the challenges in achieving natural movement when part of the body is replaced with an artificial device. Muscle synergies are widely accepted as a biologically plausible interpretation of the neural dynamics between the CNS and the muscular system. Yet the sensorineural dynamics of environmental feedback to the CNS has not been investigated in detail. In this study, we address this issue by exploring the concept of sensory synergy. In contrast to muscle synergy, we hypothesize that sensory synergy plays an essential role in integrating the overall environmental inputs to provide low-dimensional information to the CNS. We assume that sensor synergy and muscle synergy communicate using these low-dimensional signals. To examine our hypothesis, we conducted posture control experiments involving lateral disturbance with 9 healthy participants. Proprioceptive information represented by the changes on muscle lengths were estimated by using the musculoskeletal model analysis software SIMM. Changes on muscles lengths were then used to compute sensory synergies. The experimental results indicate that the environmental inputs were translated into the two dimensional signals and used to move the upper limb to the desired position immediately after the lateral disturbance. Participants who showed high skill in posture control were found to be likely to have a strong correlation between sensory and muscle signaling as well as high coordination between the utilized sensory synergies. These results suggest the importance of integrating environmental inputs into suitable low-dimensional signals before providing them to the CNS. This mechanism should be essential when designing the prosthesis’ sensory system to make the controller simpler

  10. Sensory synergy as environmental input integration.

    Science.gov (United States)

    Alnajjar, Fady; Itkonen, Matti; Berenz, Vincent; Tournier, Maxime; Nagai, Chikara; Shimoda, Shingo

    2014-01-01

    The development of a method to feed proper environmental inputs back to the central nervous system (CNS) remains one of the challenges in achieving natural movement when part of the body is replaced with an artificial device. Muscle synergies are widely accepted as a biologically plausible interpretation of the neural dynamics between the CNS and the muscular system. Yet the sensorineural dynamics of environmental feedback to the CNS has not been investigated in detail. In this study, we address this issue by exploring the concept of sensory synergy. In contrast to muscle synergy, we hypothesize that sensory synergy plays an essential role in integrating the overall environmental inputs to provide low-dimensional information to the CNS. We assume that sensor synergy and muscle synergy communicate using these low-dimensional signals. To examine our hypothesis, we conducted posture control experiments involving lateral disturbance with nine healthy participants. Proprioceptive information represented by the changes on muscle lengths were estimated by using the musculoskeletal model analysis software SIMM. Changes on muscles lengths were then used to compute sensory synergies. The experimental results indicate that the environmental inputs were translated into the two dimensional signals and used to move the upper limb to the desired position immediately after the lateral disturbance. Participants who showed high skill in posture control were found to be likely to have a strong correlation between sensory and muscle signaling as well as high coordination between the utilized sensory synergies. These results suggest the importance of integrating environmental inputs into suitable low-dimensional signals before providing them to the CNS. This mechanism should be essential when designing the prosthesis' sensory system to make the controller simpler.

  11. The behaviour of random forest permutation-based variable importance measures under predictor correlation.

    Science.gov (United States)

    Nicodemus, Kristin K; Malley, James D; Strobl, Carolin; Ziegler, Andreas

    2010-02-27

    Random forests (RF) have been increasingly used in applications such as genome-wide association and microarray studies where predictor correlation is frequently observed. Recent works on permutation-based variable importance measures (VIMs) used in RF have come to apparently contradictory conclusions. We present an extended simulation study to synthesize results. In the case when both predictor correlation was present and predictors were associated with the outcome (HA), the unconditional RF VIM attributed a higher share of importance to correlated predictors, while under the null hypothesis that no predictors are associated with the outcome (H0) the unconditional RF VIM was unbiased. Conditional VIMs showed a decrease in VIM values for correlated predictors versus the unconditional VIMs under HA and was unbiased under H0. Scaled VIMs were clearly biased under HA and H0. Unconditional unscaled VIMs are a computationally tractable choice for large datasets and are unbiased under the null hypothesis. Whether the observed increased VIMs for correlated predictors may be considered a "bias" - because they do not directly reflect the coefficients in the generating model - or if it is a beneficial attribute of these VIMs is dependent on the application. For example, in genetic association studies, where correlation between markers may help to localize the functionally relevant variant, the increased importance of correlated predictors may be an advantage. On the other hand, we show examples where this increased importance may result in spurious signals.

  12. Development of NUPREP PC Version and Input Structures for NUCIRC Single Channel Analyses

    International Nuclear Information System (INIS)

    Yoon, Churl; Jun, Ji Su; Park, Joo Hwan

    2007-12-01

    The input file for a steady-state thermal-hydraulic code NUCIRC consists of common channel input data and specific channel input data in a case of single channel analysis. Even when all the data is ready for the 380 channels' single channel analyses, it takes long time and requires enormous effort to compose an input file by hand-editing. The automatic pre-processor for this tedious job is a NUPREP code. In this study, a NUPREP PC version has been developed from the source list in the program manual of NUCIRC-MOD2.000 that is imported in a form of an execution file. In this procedure, some errors found in PC executions and lost statements are fixed accordingly. It is confirmed that the developed NUPREP code produces input file correctly for the CANDU-6 single channel analysis. Additionally, the NUCIRC input structure and data format are summarized for a single channel analysis and the input CARDs required for the creep information of aged channels are listed

  13. Input and execution

    International Nuclear Information System (INIS)

    Carr, S.; Lane, G.; Rowling, G.

    1986-11-01

    This document describes the input procedures, input data files and operating instructions for the SYVAC A/C 1.03 computer program. SYVAC A/C 1.03 simulates the groundwater mediated movement of radionuclides from underground facilities for the disposal of low and intermediate level wastes to the accessible environment, and provides an estimate of the subsequent radiological risk to man. (author)

  14. Comparison of climate envelope models developed using expert-selected variables versus statistical selection

    Science.gov (United States)

    Brandt, Laura A.; Benscoter, Allison; Harvey, Rebecca G.; Speroterra, Carolina; Bucklin, David N.; Romañach, Stephanie; Watling, James I.; Mazzotti, Frank J.

    2017-01-01

    Climate envelope models are widely used to describe potential future distribution of species under different climate change scenarios. It is broadly recognized that there are both strengths and limitations to using climate envelope models and that outcomes are sensitive to initial assumptions, inputs, and modeling methods Selection of predictor variables, a central step in modeling, is one of the areas where different techniques can yield varying results. Selection of climate variables to use as predictors is often done using statistical approaches that develop correlations between occurrences and climate data. These approaches have received criticism in that they rely on the statistical properties of the data rather than directly incorporating biological information about species responses to temperature and precipitation. We evaluated and compared models and prediction maps for 15 threatened or endangered species in Florida based on two variable selection techniques: expert opinion and a statistical method. We compared model performance between these two approaches for contemporary predictions, and the spatial correlation, spatial overlap and area predicted for contemporary and future climate predictions. In general, experts identified more variables as being important than the statistical method and there was low overlap in the variable sets (0.9 for area under the curve (AUC) and >0.7 for true skill statistic (TSS). Spatial overlap, which compares the spatial configuration between maps constructed using the different variable selection techniques, was only moderate overall (about 60%), with a great deal of variability across species. Difference in spatial overlap was even greater under future climate projections, indicating additional divergence of model outputs from different variable selection techniques. Our work is in agreement with other studies which have found that for broad-scale species distribution modeling, using statistical methods of variable

  15. Experimental investigation of a low-temperature organic Rankine cycle (ORC) engine under variable heat input operating at both subcritical and supercritical conditions

    International Nuclear Information System (INIS)

    Kosmadakis, George; Manolakos, Dimitris; Papadakis, George

    2016-01-01

    Highlights: • Small-scale ORC engine with converted scroll expander is installed at laboratory. • Design suitable for supercritical operation. • ORC engine tested at temperature equal to 95 °C. • Focus is given on expansion and thermal efficiency. • Supercritical operation showed some promising performance. - Abstract: The detailed experimental investigation of an organic Rankine cycle (ORC) is presented, which is designed to operate at supercritical conditions. The net capacity of this engine is almost 3 kW and the laboratory testing of the engine includes the variation of the heat input and of the hot water temperature. The maximum heat input is 48 kW_t_h, while the hot water temperature ranges from 65 up to 100°C. The tests are conducted at the laboratory and the heat source is a controllable electric heater, which can keep the hot water temperature constant, by switching on/off its electrical resistances. The expansion machine is a modified scroll compressor with major conversions, in order to be able to operate with safety at high pressure (or even supercritical at some conditions). The ORC engine is equipped with a dedicated heat exchanger of helical coil design, suitable for such applications. The speeds of the expander and ORC pump are regulated with frequency inverters, in order to control the cycle top pressure and heat input. The performance of all components is evaluated, while special attention is given on the supercritical heat exchanger and the scroll expander. The performance tests examined here concern the variation of the heat input, while the hot water temperature is equal to 95 °C. The aim is to examine the engine performance at the design conditions, as well as at off-design ones. Especially the latter ones are very important, since this engine will be coupled with solar collectors at the final configuration, where the available heat is varied to a great extent. The engine has been measured at the laboratory, where a thermal

  16. Importance of the macroeconomic variables for variance prediction: A GARCH-MIDAS approach

    DEFF Research Database (Denmark)

    Asgharian, Hossein; Hou, Ai Jun; Javed, Farrukh

    2013-01-01

    This paper aims to examine the role of macroeconomic variables in forecasting the return volatility of the US stock market. We apply the GARCH-MIDAS (Mixed Data Sampling) model to examine whether information contained in macroeconomic variables can help to predict short-term and long-term compone......This paper aims to examine the role of macroeconomic variables in forecasting the return volatility of the US stock market. We apply the GARCH-MIDAS (Mixed Data Sampling) model to examine whether information contained in macroeconomic variables can help to predict short-term and long...

  17. On Babies and Bathwater: Input in Foreign Language Learning.

    Science.gov (United States)

    VanPatten, Bill

    1987-01-01

    A discussion of Krashen's monitor theory and its applications to foreign language teaching includes consideration of the very important role input plays in language development and examination of the relationship between the development of grammatical competence and traditional instruction in grammar. (CB)

  18. Serial Holter ST-segment monitoring after first acute myocardial infarction. Prevalence, variability, and long-term prognostic importance of transient myocardial ischemia

    DEFF Research Database (Denmark)

    Mickley, H; Nielsen, J R; Berning, J

    1998-01-01

    Based on serial Holter monitoring performed 7 times within 3 years after a first acute myocardial infarction, we assessed the prevalence, variability and long-term clinical importance of transient myocardial ischemia (TMI) defined as episodes of ambulatory ST-segment depression. In all, 121...... consecutive male patients variability was found within and between patients...

  19. Isolating Graphical Failure-Inducing Input for Privacy Protection in Error Reporting Systems

    Directory of Open Access Journals (Sweden)

    Matos João

    2016-04-01

    Full Text Available This work proposes a new privacy-enhancing system that minimizes the disclosure of information in error reports. Error reporting mechanisms are of the utmost importance to correct software bugs but, unfortunately, the transmission of an error report may reveal users’ private information. Some privacy-enhancing systems for error reporting have been presented in the past years, yet they rely on path condition analysis, which we show in this paper to be ineffective when it comes to graphical-based input. Knowing that numerous applications have graphical user interfaces (GUI, it is very important to overcome such limitation. This work describes a new privacy-enhancing error reporting system, based on a new input minimization algorithm called GUIᴍɪɴ that is geared towards GUI, to remove input that is unnecessary to reproduce the observed failure. Before deciding whether to submit the error report, the user is provided with a step-by-step graphical replay of the minimized input, to evaluate whether it still yields sensitive information. We also provide an open source implementation of the proposed system and evaluate it with well-known applications.

  20. Ground motion input in seismic evaluation studies

    International Nuclear Information System (INIS)

    Sewell, R.T.; Wu, S.C.

    1996-07-01

    This report documents research pertaining to conservatism and variability in seismic risk estimates. Specifically, it examines whether or not artificial motions produce unrealistic evaluation demands, i.e., demands significantly inconsistent with those expected from real earthquake motions. To study these issues, two types of artificial motions are considered: (a) motions with smooth response spectra, and (b) motions with realistic variations in spectral amplitude across vibration frequency. For both types of artificial motion, time histories are generated to match target spectral shapes. For comparison, empirical motions representative of those that might result from strong earthquakes in the Eastern U.S. are also considered. The study findings suggest that artificial motions resulting from typical simulation approaches (aimed at matching a given target spectrum) are generally adequate and appropriate in representing the peak-response demands that may be induced in linear structures and equipment responding to real earthquake motions. Also, given similar input Fourier energies at high-frequencies, levels of input Fourier energy at low frequencies observed for artificial motions are substantially similar to those levels noted in real earthquake motions. In addition, the study reveals specific problems resulting from the application of Western U.S. type motions for seismic evaluation of Eastern U.S. nuclear power plants

  1. Biological 2-Input Decoder Circuit in Human Cells

    Science.gov (United States)

    2015-01-01

    Decoders are combinational circuits that convert information from n inputs to a maximum of 2n outputs. This operation is of major importance in computing systems yet it is vastly underexplored in synthetic biology. Here, we present a synthetic gene network architecture that operates as a biological decoder in human cells, converting 2 inputs to 4 outputs. As a proof-of-principle, we use small molecules to emulate the two inputs and fluorescent reporters as the corresponding four outputs. The experiments are performed using transient transfections in human kidney embryonic cells and the characterization by fluorescence microscopy and flow cytometry. We show a clear separation between the ON and OFF mean fluorescent intensity states. Additionally, we adopt the integrated mean fluorescence intensity for the characterization of the circuit and show that this metric is more robust to transfection conditions when compared to the mean fluorescent intensity. To conclude, we present the first implementation of a genetic decoder. This combinational system can be valuable toward engineering higher-order circuits as well as accommodate a multiplexed interface with endogenous cellular functions. PMID:24694115

  2. Biological 2-input decoder circuit in human cells.

    Science.gov (United States)

    Guinn, Michael; Bleris, Leonidas

    2014-08-15

    Decoders are combinational circuits that convert information from n inputs to a maximum of 2(n) outputs. This operation is of major importance in computing systems yet it is vastly underexplored in synthetic biology. Here, we present a synthetic gene network architecture that operates as a biological decoder in human cells, converting 2 inputs to 4 outputs. As a proof-of-principle, we use small molecules to emulate the two inputs and fluorescent reporters as the corresponding four outputs. The experiments are performed using transient transfections in human kidney embryonic cells and the characterization by fluorescence microscopy and flow cytometry. We show a clear separation between the ON and OFF mean fluorescent intensity states. Additionally, we adopt the integrated mean fluorescence intensity for the characterization of the circuit and show that this metric is more robust to transfection conditions when compared to the mean fluorescent intensity. To conclude, we present the first implementation of a genetic decoder. This combinational system can be valuable toward engineering higher-order circuits as well as accommodate a multiplexed interface with endogenous cellular functions.

  3. Impacts and managerial implications for sewer systems due to recent changes to inputs in domestic wastewater - A review.

    Science.gov (United States)

    Mattsson, Jonathan; Hedström, Annelie; Ashley, Richard M; Viklander, Maria

    2015-09-15

    Ever since the advent of major sewer construction in the 1850s, the issue of increased solids deposition in sewers due to changes in domestic wastewater inputs has been frequently debated. Three recent changes considered here are the introduction of kitchen sink food waste disposers (FWDs); rising levels of inputs of fat, oil and grease (FOG); and the installation of low-flush toilets (LFTs). In this review these changes have been examined with regard to potential solids depositional impacts on sewer systems and the managerial implications. The review indicates that each of the changes has the potential to cause an increase in solids deposition in sewers and this is likely to be more pronounced for the upstream reaches of networks that serve fewer households than the downstream parts and for specific sewer features such as sags. The review has highlighted the importance of educational campaigns directed to the public to mitigate deposition as many of the observed problems have been linked to domestic behaviour in regard to FOGs, FWDs and toilet flushing. A standardized monitoring procedure of repeat sewer blockage locations can also be a means to identify depositional hot-spots. Interactions between the various changes in inputs in the studies reviewed here indicated an increased potential for blockage formation, but this would need to be further substantiated. As the precise nature of these changes in inputs have been found to be variable, depending on lifestyles and type of installation, the additional problems that may arise pose particular challenges to sewer operators and managers because of the difficulty in generalizing the nature of the changes, particularly where retrofitting projects in households are being considered. The three types of changes to inputs reviewed here highlight the need to consider whether or not more or less solid waste from households should be diverted into sewers. Copyright © 2015 Elsevier Ltd. All rights reserved.

  4. Sensitivity Analysis of Input Parameters for the Dose Assessment from Gaseous Effluents due to the Normal Operation of Jordan Research and Training Reactor

    International Nuclear Information System (INIS)

    Kim, Sukhoon; Lee, Seunghee; Kim, Juyoul; Kim, Juyub; Han, Moonhee

    2015-01-01

    In this study, therefore, the sensitivity analysis of input variables for the dose assessment was performed for reviewing the effect of each parameter on the result after determining the type and range of parameters that could affect the exposure dose of the public. (Since JRTR will be operated by the concept of 'no liquid discharge,' the input parameters used for calculation of dose due to liquid effluents are not considered in the sensitivity analysis.) In this paper, the sensitivity analysis of input parameters for the dose assessment in the vicinity of the site boundary due to gaseous effluents was performed for a total of thirty-five (35) cases. And, detailed results for the input variables that have an significant effect are shown in Figures 1 through 7, respectively. For preparing a R-ER for the operating license of the JRTR, these results will be updated by the additional information and could be applied to predicting the variation trend of the exposure dose in the process of updating the input parameters for the dose assessment reflecting the characteristics of the JRTR site

  5. Verification of models for ballistic movement time and endpoint variability.

    Science.gov (United States)

    Lin, Ray F; Drury, Colin G

    2013-01-01

    A hand control movement is composed of several ballistic movements. The time required in performing a ballistic movement and its endpoint variability are two important properties in developing movement models. The purpose of this study was to test potential models for predicting these two properties. Twelve participants conducted ballistic movements of specific amplitudes using a drawing tablet. The measured data of movement time and endpoint variability were then used to verify the models. This study was successful with Hoffmann and Gan's movement time model (Hoffmann, 1981; Gan and Hoffmann 1988) predicting more than 90.7% data variance for 84 individual measurements. A new theoretically developed ballistic movement variability model, proved to be better than Howarth, Beggs, and Bowden's (1971) model, predicting on average 84.8% of stopping-variable error and 88.3% of aiming-variable errors. These two validated models will help build solid theoretical movement models and evaluate input devices. This article provides better models for predicting end accuracy and movement time of ballistic movements that are desirable in rapid aiming tasks, such as keying in numbers on a smart phone. The models allow better design of aiming tasks, for example button sizes on mobile phones for different user populations.

  6. The variability of the potential radiation exposure to man arising from radionuclides released to the ground water

    International Nuclear Information System (INIS)

    Proehl, G.; Mueller, H.

    1994-12-01

    The variability of the potential radiation exposure of the population is estimated if radionuclides (Np-237, Tc-99, I-129, Cs-135, Ra-226, U-238) are released to the ground water which is used by man as drinking water for humans and animals, for irrigation of food and feed crops, and for the production of fish in freshwater bodies. Annual effective dose equivalents are calculated assuming a normalized activity concentration in the water of 1 Bq/l for each radionuclide considered. An important aim is the estimation of the uncertainty of the exposure due to the uncertainty and the variability of the input parameters. The estimated frequency distributions of the input parameters were used as a model input and processed with Latin Hypercube Sampling and a Monte-Carlo technique. This estimation is based on an exposure scenario which reflects the present conditions. The critical group for the exposure due to the use of contaminated ground water are for most radionuclides the children of 1 year, although the activity intake of children is much lower than for adults. However the ingestion dose factors for infants are higher; in many cases the differences are higher than a factor of 5. (orig./HP)

  7. International Trade in Intermediate Inputs: The Case of the Automobile Industry

    OpenAIRE

    Markus Diehl

    2001-01-01

    International trade statistics and input-output tables are analyzed in order to test the hypothesis that international production networks have become more relevant. The share of imported inputs in the gross output value of the motor vehicle industry has grown significantly during the last two decades. Moreover, some low-income countries have become strong exporters of automobile parts, but this trade is mainly regional rather than global. Detailed results are presented in case studies on fou...

  8. Estimation of functional failure probability of passive systems based on adaptive importance sampling method

    International Nuclear Information System (INIS)

    Wang Baosheng; Wang Dongqing; Zhang Jianmin; Jiang Jing

    2012-01-01

    In order to estimate the functional failure probability of passive systems, an innovative adaptive importance sampling methodology is presented. In the proposed methodology, information of variables is extracted with some pre-sampling of points in the failure region. An important sampling density is then constructed from the sample distribution in the failure region. Taking the AP1000 passive residual heat removal system as an example, the uncertainties related to the model of a passive system and the numerical values of its input parameters are considered in this paper. And then the probability of functional failure is estimated with the combination of the response surface method and adaptive importance sampling method. The numerical results demonstrate the high computed efficiency and excellent computed accuracy of the methodology compared with traditional probability analysis methods. (authors)

  9. SSYST-3. Input description

    International Nuclear Information System (INIS)

    Meyder, R.

    1983-12-01

    The code system SSYST-3 is designed to analyse the thermal and mechanical behaviour of a fuel rod during a LOCA. The report contains a complete input-list for all modules and several tested inputs for a LOCA analysis. (orig.)

  10. Importance of Statistical Evidence in Estimating Valid DEA Scores.

    Science.gov (United States)

    Barnum, Darold T; Johnson, Matthew; Gleason, John M

    2016-03-01

    Data Envelopment Analysis (DEA) allows healthcare scholars to measure productivity in a holistic manner. It combines a production unit's multiple outputs and multiple inputs into a single measure of its overall performance relative to other units in the sample being analyzed. It accomplishes this task by aggregating a unit's weighted outputs and dividing the output sum by the unit's aggregated weighted inputs, choosing output and input weights that maximize its output/input ratio when the same weights are applied to other units in the sample. Conventional DEA assumes that inputs and outputs are used in different proportions by the units in the sample. So, for the sample as a whole, inputs have been substituted for each other and outputs have been transformed into each other. Variables are assigned different weights based on their marginal rates of substitution and marginal rates of transformation. If in truth inputs have not been substituted nor outputs transformed, then there will be no marginal rates and therefore no valid basis for differential weights. This paper explains how to statistically test for the presence of substitutions among inputs and transformations among outputs. Then, it applies these tests to the input and output data from three healthcare DEA articles, in order to identify the effects on DEA scores when input substitutions and output transformations are absent in the sample data. It finds that DEA scores are badly biased when substitution and transformation are absent and conventional DEA models are used.

  11. Common Input to Motor Units of Intrinsic and Extrinsic Hand Muscles During Two-Digit Object Hold

    OpenAIRE

    Winges, Sara A.; Kornatz, Kurt W.; Santello, Marco

    2008-01-01

    Anatomical and physiological evidence suggests that common input to motor neurons of hand muscles is an important neural mechanism for hand control. To gain insight into the synaptic input underlying the coordination of hand muscles, significant effort has been devoted to describing the distribution of common input across motor units of extrinsic muscles. Much less is known, however, about the distribution of common input to motor units belonging to different intrinsic muscles and to intrinsi...

  12. Impact of magnetic saturation on the input-output linearising tracking control of an induction motor

    DEFF Research Database (Denmark)

    Dolinar, Drago; Ljusev, Petar; Stumberger, Gorazd

    2004-01-01

    This paper deals with the tracking control design of an induction motor, based on input-output linearization with magnetic saturation included. Magnetic saturation is represented by the nonlinear magnetizing curve of the iron core and is used in the control design, the observer of state variables......, and in the load torque estimator. An input-output linearising control is used to achieve better tracking performances of the drive. It is based on the mixed ”stator current - rotor flux linkage” induction motor model with magnetic saturation considered in the stationary reference frame. Experimental results show...... that the proposed input-output linearising tracking control with the included saturation behaves considerably better than the one without saturation, and that it introduces smaller position and speed errors, and better motor stiffness on account of the increased computational complexity....

  13. Material input of nuclear fuel

    International Nuclear Information System (INIS)

    Rissanen, S.; Tarjanne, R.

    2001-01-01

    The Material Input (MI) of nuclear fuel, expressed in terms of the total amount of natural material needed for manufacturing a product, is examined. The suitability of the MI method for assessing the environmental impacts of fuels is also discussed. Material input is expressed as a Material Input Coefficient (MIC), equalling to the total mass of natural material divided by the mass of the completed product. The material input coefficient is, however, only an intermediate result, which should not be used as such for the comparison of different fuels, because the energy contents of nuclear fuel is about 100 000-fold compared to the energy contents of fossil fuels. As a final result, the material input is expressed in proportion to the amount of generated electricity, which is called MIPS (Material Input Per Service unit). Material input is a simplified and commensurable indicator for the use of natural material, but because it does not take into account the harmfulness of materials or the way how the residual material is processed, it does not alone express the amount of environmental impacts. The examination of the mere amount does not differentiate between for example coal, natural gas or waste rock containing usually just sand. Natural gas is, however, substantially more harmful for the ecosystem than sand. Therefore, other methods should also be used to consider the environmental load of a product. The material input coefficient of nuclear fuel is calculated using data from different types of mines. The calculations are made among other things by using the data of an open pit mine (Key Lake, Canada), an underground mine (McArthur River, Canada) and a by-product mine (Olympic Dam, Australia). Furthermore, the coefficient is calculated for nuclear fuel corresponding to the nuclear fuel supply of Teollisuuden Voima (TVO) company in 2001. Because there is some uncertainty in the initial data, the inaccuracy of the final results can be even 20-50 per cent. The value

  14. Nitrogen input inventory in the Nooksack-Abbotsford-Sumas ...

    Science.gov (United States)

    Nitrogen (N) is an essential biological element, so optimizing N use for food production while minimizing the release of N and co-pollutants to the environment is an important challenge. The Nooksack-Abbotsford-Sumas Transboundary (NAS) Region, spanning a portion of the western interface of British Columbia, Washington state, and the Lummi Nation and the Nooksack Tribe, supports agriculture, fisheries, diverse wildlife, and vibrant urban areas. Groundwater nitrate contamination affects thousands of households in this region. Fisheries and air quality are also affected including periodic closures of shellfish harvest. To reduce the release of N to the environment, successful approaches are needed that partner all stakeholders with appropriate institutions to integrate science, outreach and management efforts. Our goal is to determine the distribution and quantities of N inventories of the watershed. This work synthesizes publicly available data on N sources including deposition, sewage and septic inputs, fertilizer and manure applications, marine-derived N from salmon, and more. The information on cross-boundary N inputs to the landscape will be coupled with stream monitoring data and existing knowledge about N inputs and exports from the watershed to estimate the N residual and inform N management in the search for the environmentally and economically viable and effective solutions. We will estimate the N inputs into the NAS region and transfers within

  15. Development of NUPREP PC Version and Input Structures for NUCIRC Single Channel Analyses

    Energy Technology Data Exchange (ETDEWEB)

    Yoon, Churl; Jun, Ji Su; Park, Joo Hwan

    2007-12-15

    The input file for a steady-state thermal-hydraulic code NUCIRC consists of common channel input data and specific channel input data in a case of single channel analysis. Even when all the data is ready for the 380 channels' single channel analyses, it takes long time and requires enormous effort to compose an input file by hand-editing. The automatic pre-processor for this tedious job is a NUPREP code. In this study, a NUPREP PC version has been developed from the source list in the program manual of NUCIRC-MOD2.000 that is imported in a form of an execution file. In this procedure, some errors found in PC executions and lost statements are fixed accordingly. It is confirmed that the developed NUPREP code produces input file correctly for the CANDU-6 single channel analysis. Additionally, the NUCIRC input structure and data format are summarized for a single channel analysis and the input CARDs required for the creep information of aged channels are listed.

  16. Unequal Input Voltages Distribution Between the Serial Connected Halfbridges

    Directory of Open Access Journals (Sweden)

    Radovan Ovcarcik

    2006-01-01

    Full Text Available This paper describes a topology of DC-DC converter consisting in two serial connected half-bridges. Secondary circuit is realized like a conventional full-wave rectifier. The main advantage of this topology is the possibility of dividing the input voltage between the half-bridges. The converter is controlled using the phase-shift modulation, which allows a ZVSoperation mode. The voltage unbalance between the inputs causes an important problem of the presented topology. It is necessary to avoid it by the control algorithm, which is described in the text. The practical results show a zero voltage switching technique and the limits of the chosen topology and of the control.

  17. The importance of accurate meteorological input fields and accurate planetary boundary layer parameterizations, tested against ETEX-1

    International Nuclear Information System (INIS)

    Brandt, J.; Ebel, A.; Elbern, H.; Jakobs, H.; Memmesheimer, M.; Mikkelsen, T.; Thykier-Nielsen, S.; Zlatev, Z.

    1997-01-01

    Atmospheric transport of air pollutants is, in principle, a well understood process. If information about the state of the atmosphere is given in all details (infinitely accurate information about wind speed, etc.) and infinitely fast computers are available then the advection equation could in principle be solved exactly. This is, however, not the case: discretization of the equations and input data introduces some uncertainties and errors in the results. Therefore many different issues have to be carefully studied in order to diminish these uncertainties and to develop an accurate transport model. Some of these are e.g. the numerical treatment of the transport equation, accuracy of the mean meteorological input fields and parameterizations of sub-grid scale phenomena (as e.g. parameterizations of the 2 nd and higher order turbulence terms in order to reach closure in the perturbation equation). A tracer model for studying transport and dispersion of air pollution caused by a single but strong source is under development. The model simulations from the first ETEX release illustrate the differences caused by using various analyzed fields directly in the tracer model or using a meteorological driver. Also different parameterizations of the mixing height and the vertical exchange are compared. (author)

  18. The importance of histopathological and clinical variables in predicting the evolution of colon cancer.

    Science.gov (United States)

    Diculescu, Mircea; Iacob, Răzvan; Iacob, Speranţa; Croitoru, Adina; Becheanu, Gabriel; Popeneciu, Valentin

    2002-09-01

    It has been a consensus that prognostic factors should always be taken into account before planning treatment in colorectal cancer. A 5 year prospective study was conducted, in order to assess the importance of several histopathological and clinical prognostic variables in the prediction of evolution in colon cancer. Some of the factors included in the analysis are still subject to dispute by different authors. 46 of 53 screened patients qualified to enter the study and underwent a potentially curative resection of the tumor, followed, when necessary, by adjuvant chemotherapy. Univariate and multivariate analyses were carried out in order to identify independent prognostic indicators. The endpoint of the study was considered the recurrence of the tumor or the detection of metastases. 65.2% of the patients had a good evolution during the follow up period. Multivariate survival analysis performed by Cox proportional hazard model identified 3 independent prognostic factors: Dukes stage (p = 0.00002), the grade of differentiation (p = 0.0009) and the weight loss index, representing the weight loss of the patient divided by the number of months when it was actually lost (p = 0.02). Age under 40 years, sex, microscopic aspect of the tumor, tumor location, anemia degree were not identified by our analysis as having prognostic importance. Histopathological factors continue to be the most valuable source of information regarding the possible evolution of patients with colorectal cancer. Individual clinical symptoms or biological parameters such as erytrocyte sedimentation rate or hemoglobin level are of little or no prognostic value. More research is required relating to the impact of a performance status index (which could include also weight loss index) as another reliable prognostic variable.

  19. Understanding virtual water flows: A multiregion input-output case study of Victoria

    Science.gov (United States)

    Lenzen, Manfred

    2009-09-01

    This article explains and interprets virtual water flows from the well-established perspective of input-output analysis. Using a case study of the Australian state of Victoria, it demonstrates that input-output analysis can enumerate virtual water flows without systematic and unknown truncation errors, an issue which has been largely absent from the virtual water literature. Whereas a simplified flow analysis from a producer perspective would portray Victoria as a net virtual water importer, enumerating the water embodiments across the full supply chain using input-output analysis shows Victoria as a significant net virtual water exporter. This study has succeeded in informing government policy in Australia, which is an encouraging sign that input-output analysis will be able to contribute much value to other national and international applications.

  20. Analysis on electronic control unit of continuously variable transmission

    Science.gov (United States)

    Cao, Shuanggui

    Continuously variable transmission system can ensure that the engine work along the line of best fuel economy, improve fuel economy, save fuel and reduce harmful gas emissions. At the same time, continuously variable transmission allows the vehicle speed is more smooth and improves the ride comfort. Although the CVT technology has made great development, but there are many shortcomings in the CVT. The CVT system of ordinary vehicles now is still low efficiency, poor starting performance, low transmission power, and is not ideal controlling, high cost and other issues. Therefore, many scholars began to study some new type of continuously variable transmission. The transmission system with electronic systems control can achieve automatic control of power transmission, give full play to the characteristics of the engine to achieve optimal control of powertrain, so the vehicle is always traveling around the best condition. Electronic control unit is composed of the core processor, input and output circuit module and other auxiliary circuit module. Input module collects and process many signals sent by sensor and , such as throttle angle, brake signals, engine speed signal, speed signal of input and output shaft of transmission, manual shift signals, mode selection signals, gear position signal and the speed ratio signal, so as to provide its corresponding processing for the controller core.

  1. Chemical sensors are hybrid-input memristors

    Science.gov (United States)

    Sysoev, V. I.; Arkhipov, V. E.; Okotrub, A. V.; Pershin, Y. V.

    2018-04-01

    Memristors are two-terminal electronic devices whose resistance depends on the history of input signal (voltage or current). Here we demonstrate that the chemical gas sensors can be considered as memristors with a generalized (hybrid) input, namely, with the input consisting of the voltage, analyte concentrations and applied temperature. The concept of hybrid-input memristors is demonstrated experimentally using a single-walled carbon nanotubes chemical sensor. It is shown that with respect to the hybrid input, the sensor exhibits some features common with memristors such as the hysteretic input-output characteristics. This different perspective on chemical gas sensors may open new possibilities for smart sensor applications.

  2. Why is variability important for performance assessment and what are its consequences for site characterisation and repository design?

    International Nuclear Information System (INIS)

    Dverstorp, B.; Smith, P.A.; Zuidema, P.

    1998-01-01

    The importance of spatial variability is discussed in terms of its consequences for site characterisation and for repository design and safety. Variability is described in terms of various scales of discrete structural features and a pragmatic classification is proposed according to whether the features are: feasibility-determining (i.e. features within which repository construction and operation is not practical and which preclude long-term safety); layout-determining (i.e. features which, if avoided, would enhance long-term safety); safety-determining features (i.e. features which cannot be shown to be avoidable and which strongly influence the calculated long-term safety of the repository system). The significance with respect to the geosphere-transport barrier of small-scale pore structure within the various classes of feature is also discussed. The practical problems of characterising variability and modelling its effects on radionuclide transport are described. Key factors affecting groundwater flow and radionuclide transport are identified, models that incorporate spatial variability are described and the estimation of appropriate parameters for these models is discussed. (author)

  3. Limiting labor input is an overall prerequisite for sustainability

    DEFF Research Database (Denmark)

    Nørgaard, Jørgen

    2006-01-01

    The purpose of the paper is to show by a simple, aggregate, descriptive model, how the importance of labor input to the production sector has to be revised in a future aiming at sustainable development. Despite substantial technological potentials for more eco-efficient utilization of nature...

  4. Hourly air pollution concentrations and their important predictors over Houston, Texas using deep neural networks: case study of DISCOVER-AQ time period

    Science.gov (United States)

    Eslami, E.; Choi, Y.; Roy, A.

    2017-12-01

    Air quality forecasting carried out by chemical transport models often show significant error. This study uses a deep-learning approach over the Houston-Galveston-Brazoria (HGB) area to overcome this forecasting challenge, for the DISCOVER-AQ period (September 2013). Two approaches, deep neural network (DNN) using a Multi-Layer Perceptron (MLP) and Restricted Boltzmann Machine (RBM) were utilized. The proposed approaches analyzed input data by identifying features abstracted from its previous layer using a stepwise method. The approaches predicted hourly ozone and PM in September 2013 using several predictors of prior three days, including wind fields, temperature, relative humidity, cloud fraction, precipitation along with PM, ozone, and NOx concentrations. Model-measurement comparisons for available monitoring sites reported Indexes of Agreement (IOA) of around 0.95 for both DNN and RBM. A standard artificial neural network (ANN) (IOA=0.90) with similar architecture showed poorer performance than the deep networks, clearly demonstrating the superiority of the deep approaches. Additionally, each network (both deep and standard) performed significantly better than a previous CMAQ study, which showed an IOA of less than 0.80. The most influential input variables were identified using their associated weights, which represented the sensitivity of ozone to input parameters. The results indicate deep learning approaches can achieve more accurate ozone forecasting and identify the important input variables for ozone predictions in metropolitan areas.

  5. A fast integrated discriminator with continuously variable width

    International Nuclear Information System (INIS)

    Borghesi, A.; Goggi, G.; Nardo, R.

    1976-01-01

    A simple dc-coupled discriminator with fast switching characteristics has been realized. Both input threshold and output width are continuously variable; the ECL design allows high speed and high density with ample fanout. (Auth.)

  6. Feeling music: integration of auditory and tactile inputs in musical meter perception.

    Science.gov (United States)

    Huang, Juan; Gamble, Darik; Sarnlertsophon, Kristine; Wang, Xiaoqin; Hsiao, Steven

    2012-01-01

    Musicians often say that they not only hear, but also "feel" music. To explore the contribution of tactile information in "feeling" musical rhythm, we investigated the degree that auditory and tactile inputs are integrated in humans performing a musical meter recognition task. Subjects discriminated between two types of sequences, 'duple' (march-like rhythms) and 'triple' (waltz-like rhythms) presented in three conditions: 1) Unimodal inputs (auditory or tactile alone), 2) Various combinations of bimodal inputs, where sequences were distributed between the auditory and tactile channels such that a single channel did not produce coherent meter percepts, and 3) Simultaneously presented bimodal inputs where the two channels contained congruent or incongruent meter cues. We first show that meter is perceived similarly well (70%-85%) when tactile or auditory cues are presented alone. We next show in the bimodal experiments that auditory and tactile cues are integrated to produce coherent meter percepts. Performance is high (70%-90%) when all of the metrically important notes are assigned to one channel and is reduced to 60% when half of these notes are assigned to one channel. When the important notes are presented simultaneously to both channels, congruent cues enhance meter recognition (90%). Performance drops dramatically when subjects were presented with incongruent auditory cues (10%), as opposed to incongruent tactile cues (60%), demonstrating that auditory input dominates meter perception. We believe that these results are the first demonstration of cross-modal sensory grouping between any two senses.

  7. Culture Input in Foreign Language Teaching

    Institute of Scientific and Technical Information of China (English)

    胡晶

    2009-01-01

    Language and culture are highly interrelated, that is to say, language is not only the carrier of culture but it is also restricted by culture. Therefore, foreign language teaching aiming at cultivate students' intercultural communication should take culture differences into consideration. In this paper, the relationship between language and culture will be discussed. Then I will illustrate the importance of intercultural communication. Finally, according to the present situation of foreign language teaching in China, several strategies for cultural input in and out of class will be suggested.

  8. Parametric Study on Important Variables of Aircraft Impact to Prestressed Concrete Containment Vessels

    Energy Technology Data Exchange (ETDEWEB)

    Shin, Sangshup; Hahm, Daegi; Choi, Inkil [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2013-05-15

    In this paper, to find the damage parameter, it is necessary to use many analysis cases and the time reduction. Thus, this paper uses a revised version of Riera's method. Using this method, the response has been found a Prestressed Concrete Containments Vessels (PCCVs) subject to impact loading, and the results of the velocity and mass of the important parameters have been analyzed. To find the response of the PCCVs subjected to aircraft impact load, it is made that a variable forcing functions depending on the velocity and fuel in the paper. The velocity variation affects more than fuel percentage, and we expect that the severe damage of the PCCVs with the same material properties is subject to aircraft impact load (more than 200m/s and 70%)

  9. Prediction-Based Control for Nonlinear Systems with Input Delay

    Directory of Open Access Journals (Sweden)

    I. Estrada-Sánchez

    2017-01-01

    Full Text Available This work has two primary objectives. First, it presents a state prediction strategy for a class of nonlinear Lipschitz systems subject to constant time delay in the input signal. As a result of a suitable change of variable, the state predictor asymptotically provides the value of the state τ units of time ahead. Second, it proposes a solution to the stabilization and trajectory tracking problems for the considered class of systems using predicted states. The predictor-controller convergence is proved by considering a complete Lyapunov functional. The proposed predictor-based controller strategy is evaluated using numerical simulations.

  10. Nitrogen input from residential lawn care practices in suburban watersheds in Baltimore county, MD

    Science.gov (United States)

    Neely L. Law; Lawrence E. Band; J. Morgan. Grove

    2004-01-01

    A residential lawn care survey was conducted as part of the Baltimore Ecosystem Study, a Long-term Ecological Research project funded by the National Science Foundation and collaborating agencies, to estimate the nitrogen input to urban watersheds from lawn care practices. The variability in the fertilizer N application rates and the factors affecting the application...

  11. Crossover Can Be Constructive When Computing Unique Input Output Sequences

    DEFF Research Database (Denmark)

    Lehre, Per Kristian; Yao, Xin

    2010-01-01

    Unique input output (UIO) sequences have important applications in conformance testing of finite state machines (FSMs). Previous experimental and theoretical research has shown that evolutionary algorithms (EAs) can compute UIOs efficiently on many FSM instance classes, but fail on others. However...

  12. Monitoring of airborne biological particles in outdoor atmosphere. Part 1: Importance, variability and ratios.

    Science.gov (United States)

    Núñez, Andrés; Amo de Paz, Guillermo; Rastrojo, Alberto; García, Ana M; Alcamí, Antonio; Gutiérrez-Bustillo, A Montserrat; Moreno, Diego A

    2016-03-01

    The first part of this review ("Monitoring of airborne biological particles in outdoor atmosphere. Part 1: Importance, variability and ratios") describes the current knowledge on the major biological particles present in the air regarding their global distribution, concentrations, ratios and influence of meteorological factors in an attempt to provide a framework for monitoring their biodiversity and variability in such a singular environment as the atmosphere. Viruses, bacteria, fungi, pollen and fragments thereof are the most abundant microscopic biological particles in the air outdoors. Some of them can cause allergy and severe diseases in humans, other animals and plants, with the subsequent economic impact. Despite the harsh conditions, they can be found from land and sea surfaces to beyond the troposphere and have been proposed to play a role also in weather conditions and climate change by acting as nucleation particles and inducing water vapour condensation. In regards to their global distribution, marine environments act mostly as a source for bacteria while continents additionally provide fungal and pollen elements. Within terrestrial environments, their abundances and diversity seem to be influenced by the land-use type (rural, urban, coastal) and their particularities. Temporal variability has been observed for all these organisms, mostly triggered by global changes in temperature, relative humidity, et cetera. Local fluctuations in meteorological factors may also result in pronounced changes in the airbiota. Although biological particles can be transported several hundreds of meters from the original source, and even intercontinentally, the time and final distance travelled are strongly influenced by factors such as wind speed and direction. [Int Microbiol 2016; 19(1):1-1 3]. Copyright© by the Spanish Society for Microbiology and Institute for Catalan Studies.

  13. Has central sensitization become independent of nociceptive input in chronic pancreatitis patients who fail thoracoscopic splanchnicectomy?

    NARCIS (Netherlands)

    Bouwense, S.A.W.; Buscher, H.C.J.L.; Goor, H. van; Wilder-Smith, O.H.G.

    2011-01-01

    BACKGROUND AND OBJECTIVES: : Central sensitization due to visceral pancreatic nociceptive input may be important in chronic pancreatitis pain. We investigated whether bilateral thoracoscopic splanchnicectomy (BTS) to reduce nociceptive input in chronic pancreatitis patients (CPP) with poor pain

  14. Stabilization of Networked Control Systems with Variable Delays and Saturating Inputs

    Directory of Open Access Journals (Sweden)

    M. Mahmodi Kaleybar

    2014-06-01

    Full Text Available In this paper, improved conditions for the synthesis of static state-feedback controller are derived to stabilize networked control systems (NCSs subject to actuator saturation. Both of the data packet latency and dropout which deteriorate the performance of the closed-loop system are considered in the NCS model via variable delays. Two different techniques are employed to incorporate actuator saturation in the system description. Utilizing Lyapunov-Krasovskii Theorem, delay-dependent conditions are obtained in terms of linear matrix inequalities (LMIs to determine the static feedback gain. Moreover, an optimization problem is formulated in order to find the less conservative estimate for the region of attraction corresponding to different maximum allowable delays. Numerical examples are introduced to demonstrate the effectiveness and advantages of the proposed schemes.

  15. MDS MIC Catalog Inputs

    Science.gov (United States)

    Johnson-Throop, Kathy A.; Vowell, C. W.; Smith, Byron; Darcy, Jeannette

    2006-01-01

    This viewgraph presentation reviews the inputs to the MDS Medical Information Communique (MIC) catalog. The purpose of the group is to provide input for updating the MDS MIC Catalog and to request that MMOP assign Action Item to other working groups and FSs to support the MITWG Process for developing MIC-DDs.

  16. Variability in Measured Space Temperatures in 60 Homes

    Energy Technology Data Exchange (ETDEWEB)

    Roberts, D.; Lay, K.

    2013-03-01

    This report discusses the observed variability in indoor space temperature in a set of 60 homes located in Florida, New York, Oregon, and Washington. Temperature data were collected at 15-minute intervals for an entire year, including living room, master bedroom, and outdoor air temperature (Arena, et. al). The data were examined to establish the average living room temperature for the set of homes for the heating and cooling seasons, the variability of living room temperature depending on climate, and the variability of indoor space temperature within the homes. The accuracy of software-based energy analysis depends on the accuracy of input values. Thermostat set point is one of the most influential inputs for building energy simulation. Several industry standards exist that recommend differing default thermostat settings for heating and cooling seasons. These standards were compared to the values calculated for this analysis. The data examined for this report show that there is a definite difference between the climates and that the data do not agree well with any particular standard.

  17. Simplified quantitative treatment of uncertainty and interindividual variability in health risk assessment

    International Nuclear Information System (INIS)

    Bogen, K.T.

    1993-01-01

    A distinction between uncertainty (or the extent of lack of knowledge) and interindividual variability (or the extent of person-to-person heterogeneity) regarding the values of input variates must be maintained if a quantitative characterization of uncertainty in population risk or in individual risk is sought. Here, some practical methods are presented that should facilitate implementation of the analytic framework for uncertainty and variability proposed by Bogen and Spear. (1,2) Two types of methodology are discussed: one that facilitates the distinction between uncertainty and variability per se, and another that may be used to simplify quantitative analysis of distributed inputs representing either uncertainty or variability. A simple and a complex form for modeled increased risk are presented and then used to illustrate methods facilitating the distinction between uncertainty and variability in reference to characterization of both population and individual risk. Finally, a simple form of discrete probability calculus is proposed as an easily implemented, practical altemative to Monte-Carlo based procedures to quantitative integration of uncertainty and variability in risk assessment

  18. Evolution of dispersal in spatially and temporally variable environments: The importance of life cycles.

    Science.gov (United States)

    Massol, François; Débarre, Florence

    2015-07-01

    Spatiotemporal variability of the environment is bound to affect the evolution of dispersal, and yet model predictions strongly differ on this particular effect. Recent studies on the evolution of local adaptation have shown that the life cycle chosen to model the selective effects of spatiotemporal variability of the environment is a critical factor determining evolutionary outcomes. Here, we investigate the effect of the order of events in the life cycle on the evolution of unconditional dispersal in a spatially heterogeneous, temporally varying landscape. Our results show that the occurrence of intermediate singular strategies and disruptive selection are conditioned by the temporal autocorrelation of the environment and by the life cycle. Life cycles with dispersal of adults versus dispersal of juveniles, local versus global density regulation, give radically different evolutionary outcomes that include selection for total philopatry, evolutionary bistability, selection for intermediate stable states, and evolutionary branching points. Our results highlight the importance of accounting for life-cycle specifics when predicting the effects of the environment on evolutionarily selected trait values, such as dispersal, as well as the need to check the robustness of model conclusions against modifications of the life cycle. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

  19. Uncertainty importance analysis using parametric moment ratio functions.

    Science.gov (United States)

    Wei, Pengfei; Lu, Zhenzhou; Song, Jingwen

    2014-02-01

    This article presents a new importance analysis framework, called parametric moment ratio function, for measuring the reduction of model output uncertainty when the distribution parameters of inputs are changed, and the emphasis is put on the mean and variance ratio functions with respect to the variances of model inputs. The proposed concepts efficiently guide the analyst to achieve a targeted reduction on the model output mean and variance by operating on the variances of model inputs. The unbiased and progressive unbiased Monte Carlo estimators are also derived for the parametric mean and variance ratio functions, respectively. Only a set of samples is needed for implementing the proposed importance analysis by the proposed estimators, thus the computational cost is free of input dimensionality. An analytical test example with highly nonlinear behavior is introduced for illustrating the engineering significance of the proposed importance analysis technique and verifying the efficiency and convergence of the derived Monte Carlo estimators. Finally, the moment ratio function is applied to a planar 10-bar structure for achieving a targeted 50% reduction of the model output variance. © 2013 Society for Risk Analysis.

  20. The role of updraft velocity in temporal variability of cloud hydrometeor number

    Science.gov (United States)

    Sullivan, Sylvia; Nenes, Athanasios; Lee, Dong Min; Oreopoulos, Lazaros

    2016-04-01

    Significant effort has been dedicated to incorporating direct aerosol-cloud links, through parameterization of liquid droplet activation and ice crystal nucleation, within climate models. This significant accomplishment has generated the need for understanding which parameters affecting hydrometer formation drives its variability in coupled climate simulations, as it provides the basis for optimal parameter estimation as well as robust comparison with data, and other models. Sensitivity analysis alone does not address this issue, given that the importance of each parameter for hydrometer formation depends on its variance and sensitivity. To address the above issue, we develop and use a series of attribution metrics defined with adjoint sensitivities to attribute the temporal variability in droplet and crystal number to important aerosol and dynamical parameters. This attribution analysis is done both for the NASA Global Modeling and Assimilation Office Goddard Earth Observing System Model, Version 5 and the National Center for Atmospheric Research Community Atmosphere Model Version 5.1. Within the GEOS simulation, up to 48% of temporal variability in output ice crystal number and 61% in droplet number can be attributed to input updraft velocity fluctuations, while for the CAM simulation, they explain as much as 89% of the ice crystal number variability. This above results suggest that vertical velocity in both model frameworks is seen to be a very important (or dominant) driver of hydrometer variability. Yet, observations of vertical velocity are seldomly available (or used) to evaluate the vertical velocities in simulations; this strikingly contrasts the amount and quality of data available for aerosol-related parameters. Consequentially, there is a strong need for retrievals or measurements of vertical velocity for addressing this important knowledge gap that requires a significant investment and effort by the atmospheric community. The attribution metrics as a

  1. Climate variables explain neutral and adaptive variation within salmonid metapopulations: The importance of replication in landscape genetics

    Science.gov (United States)

    Hand, Brian K.; Muhlfeld, Clint C.; Wade, Alisa A.; Kovach, Ryan; Whited, Diane C.; Narum, Shawn R.; Matala, Andrew P.; Ackerman, Michael W.; Garner, B. A.; Kimball, John S; Stanford, Jack A.; Luikart, Gordon

    2016-01-01

    Understanding how environmental variation influences population genetic structure is important for conservation management because it can reveal how human stressors influence population connectivity, genetic diversity and persistence. We used riverscape genetics modelling to assess whether climatic and habitat variables were related to neutral and adaptive patterns of genetic differentiation (population-specific and pairwise FST) within five metapopulations (79 populations, 4583 individuals) of steelhead trout (Oncorhynchus mykiss) in the Columbia River Basin, USA. Using 151 putatively neutral and 29 candidate adaptive SNP loci, we found that climate-related variables (winter precipitation, summer maximum temperature, winter highest 5% flow events and summer mean flow) best explained neutral and adaptive patterns of genetic differentiation within metapopulations, suggesting that climatic variation likely influences both demography (neutral variation) and local adaptation (adaptive variation). However, we did not observe consistent relationships between climate variables and FST across all metapopulations, underscoring the need for replication when extrapolating results from one scale to another (e.g. basin-wide to the metapopulation scale). Sensitivity analysis (leave-one-population-out) revealed consistent relationships between climate variables and FST within three metapopulations; however, these patterns were not consistent in two metapopulations likely due to small sample sizes (N = 10). These results provide correlative evidence that climatic variation has shaped the genetic structure of steelhead populations and highlight the need for replication and sensitivity analyses in land and riverscape genetics.

  2. Noise and crosstalk in two quorum-sensing inputs of Vibrio fischeri

    Directory of Open Access Journals (Sweden)

    Weiss Joel T

    2011-09-01

    Full Text Available Abstract Background One of the puzzles in bacterial quorum sensing is understanding how an organism integrates the information gained from multiple input signals. The marine bacterium Vibrio fischeri regulates its bioluminescence through a quorum sensing mechanism that receives input from three pheromone signals, including two acyl homoserine lactone (HSL signals. While the role of the 3-oxo-C6 homoserine lactone (3OC6HSL signal in activating the lux genes has been extensively studied and modeled, the role of the C8 homoserine lactone (C8HSL is less obvious, as it can either activate luminescence or block its activation. It remains unclear how crosstalk between C8HSL and 3OC6HSL affects the information that the bacterium obtains through quorum sensing. Results We have used microfluidic methods to measure the response of individual V.fischeri cells to combinations of C8HSL and 3OC6HSL. By measuring the fluorescence of individual V.fischeri cells containing a chromosomal gfp-reporter for the lux genes, we study how combinations of exogenous HSLs affect both the population average and the cell-to-cell variability of lux activation levels. At the level of a population average, the crosstalk between the C8HSL and 3OC6HSL inputs is well-described by a competitive inhibition model. At the level of individual cells, the heterogeneity in the lux response depends only on the average degree of activation, so that the noise in the output is not reduced by the presence of the second HSL signal. Overall we find that the mutual information between the signal inputs and the lux output is less than one bit. A nonlinear correlation between fluorescence and bioluminescence outputs from lux leads to different noise properties for these reporters. Conclusions The lux genes in V.fischeri do not appear to distinguish between the two HSL inputs, and even with two signal inputs the regulation of lux is extremely noisy. Hence the role of crosstalk from the C8HSL input

  3. Rose bush leaf and internode expansion dynamics: analysis and development of a model capturing interplant variability

    Directory of Open Access Journals (Sweden)

    Sabine eDemotes-Mainard

    2013-10-01

    Full Text Available Bush rose architecture, among other factors, such as plant health, determines plant visual quality. The commercial product is the individual plant and interplant variability may be high within a crop. Thus, both mean plant architecture and interplant variability should be studied. Expansion is an important feature of architecture, but it has been little studied at the level of individual organs in bush roses. We investigated the expansion kinetics of primary shoot organs, to develop a model reproducing the organ expansion of real crops from non destructive input variables. We took interplant variability in expansion kinetics and the model’s ability to simulate this variability into account. Changes in leaflet and internode dimensions over thermal time were recorded for primary shoot expansion, on 83 plants from three crops grown in different climatic conditions and densities. An empirical model was developed, to reproduce organ expansion kinetics for individual plants of a real crop of bush rose primary shoots. Leaflet or internode length was simulated as a logistic function of thermal time. The model was evaluated by cross-validation. We found that differences in leaflet or internode expansion kinetics between phytomer positions and between plants at a given phytomer position were due mostly to large differences in time of organ expansion and expansion rate, rather than differences in expansion duration. Thus, in the model, the parameters linked to expansion duration were predicted by values common to all plants, whereas variability in final size and organ expansion time was captured by input data. The model accurately simulated leaflet and internode expansion for individual plants (RMSEP = 7.3% and 10.2% of final length, respectively. Thus, this study defines the measurements required to simulate expansion and provides the first model simulating organ expansion in rosebush to capture interplant variability.

  4. State, Parameter, and Unknown Input Estimation Problems in Active Automotive Safety Applications

    Science.gov (United States)

    Phanomchoeng, Gridsada

    A variety of driver assistance systems such as traction control, electronic stability control (ESC), rollover prevention and lane departure avoidance systems are being developed by automotive manufacturers to reduce driver burden, partially automate normal driving operations, and reduce accidents. The effectiveness of these driver assistance systems can be significant enhanced if the real-time values of several vehicle parameters and state variables, namely tire-road friction coefficient, slip angle, roll angle, and rollover index, can be known. Since there are no inexpensive sensors available to measure these variables, it is necessary to estimate them. However, due to the significant nonlinear dynamics in a vehicle, due to unknown and changing plant parameters, and due to the presence of unknown input disturbances, the design of estimation algorithms for this application is challenging. This dissertation develops a new approach to observer design for nonlinear systems in which the nonlinearity has a globally (or locally) bounded Jacobian. The developed approach utilizes a modified version of the mean value theorem to express the nonlinearity in the estimation error dynamics as a convex combination of known matrices with time varying coefficients. The observer gains are then obtained by solving linear matrix inequalities (LMIs). A number of illustrative examples are presented to show that the developed approach is less conservative and more useful than the standard Lipschitz assumption based nonlinear observer. The developed nonlinear observer is utilized for estimation of slip angle, longitudinal vehicle velocity, and vehicle roll angle. In order to predict and prevent vehicle rollovers in tripped situations, it is necessary to estimate the vertical tire forces in the presence of unknown road disturbance inputs. An approach to estimate unknown disturbance inputs in nonlinear systems using dynamic model inversion and a modified version of the mean value theorem is

  5. Input filter compensation for switching regulators

    Science.gov (United States)

    Lee, F. C.; Kelkar, S. S.

    1982-01-01

    The problems caused by the interaction between the input filter, output filter, and the control loop are discussed. The input filter design is made more complicated because of the need to avoid performance degradation and also stay within the weight and loss limitations. Conventional input filter design techniques are then dicussed. The concept of pole zero cancellation is reviewed; this concept is the basis for an approach to control the peaking of the output impedance of the input filter and thus mitigate some of the problems caused by the input filter. The proposed approach for control of the peaking of the output impedance of the input filter is to use a feedforward loop working in conjunction with feedback loops, thus forming a total state control scheme. The design of the feedforward loop for a buck regulator is described. A possible implementation of the feedforward loop design is suggested.

  6. ASSIST - a package of Fortran routines for handling input under specified syntax rules and for management of data structures

    International Nuclear Information System (INIS)

    Sinclair, J.E.

    1991-02-01

    The ASSIST package (A Structured Storage and Input Syntax Tool) provides for Fortran programs a means for handling data structures more general than those provided by the Fortran language, and for obtaining input to the program from a file or terminal according to specified syntax rules. The syntax-controlled input can be interactive, with automatic generation of prompts, and dialogue to correct any input errors. The range of syntax rules possible is sufficient to handle lists of numbers and character strings, keywords, commands with optional clauses, and many kinds of variable-format constructions, such as algebraic expressions. ASSIST was developed for use in two large programs for the analysis of safety of radioactive waste disposal facilities, but it should prove useful for a wide variety of applications. (author)

  7. Soil properties and not inputs control carbon, nitrogen, phosphorus ratios in cropped soils in the long-term

    Science.gov (United States)

    Frossard, E.; Buchmann, N.; Bünemann, E. K.; Kiba, D. I.; Lompo, F.; Oberson, A.; Tamburini, F.; Traoré, O. Y. A.

    2015-09-01

    Stoichiometric approaches have been applied to understand the relationship between soil organic matter dynamics and biological nutrient transformations. However, very few studies explicitly considered the effects of agricultural management practices on soil C : N : P ratio. The aim of this study was to assess how different input types and rates would affect the C : N : P molar ratios of bulk soil, organic matter and microbial biomass in cropped soils in the long-term. Thus, we analysed the C, N and P inputs and budgets as well as soil properties in three long-term experiments established on different soil types: the Saria soil fertility trial (Burkina Faso), the Wagga Wagga rotation/stubble management/soil preparation trial (Australia), and the DOK cropping system trial (Switzerland). In each of these trials, there was a large range of C, N and P inputs which had a strong impact on element concentrations in soils. However, although C : N : P ratios of the inputs were highly variable, they had only weak effects on soil C : N : P ratios. At Saria, a positive correlation was found between the N : P ratio of inputs and microbial biomass, while no relation was observed between the nutrient ratios of inputs and soil organic matter. At Wagga Wagga, the C : P ratio of inputs was significantly correlated to total soil C : P, N : P and C : N ratios, but had no impact on the elemental composition of microbial biomass. In the DOK trial, a positive correlation was found between the C budget and the C to organic P ratio in soils, while the nutrient ratios of inputs were not related to those in the microbial biomass. We argue that these responses are due to differences in soil properties among sites. At Saria, the soil is dominated by quartz and some kaolinite, has a coarse texture, a fragile structure and a low nutrient content. Thus, microorganisms feed on inputs (plant residues, manure). In contrast, the soil at Wagga Wagga contains illite and haematite, is richer in clay and

  8. Soil properties and not inputs control carbon : nitrogen : phosphorus ratios in cropped soils in the long term

    Science.gov (United States)

    Frossard, Emmanuel; Buchmann, Nina; Bünemann, Else K.; Kiba, Delwende I.; Lompo, François; Oberson, Astrid; Tamburini, Federica; Traoré, Ouakoltio Y. A.

    2016-02-01

    Stoichiometric approaches have been applied to understand the relationship between soil organic matter dynamics and biological nutrient transformations. However, very few studies have explicitly considered the effects of agricultural management practices on the soil C : N : P ratio. The aim of this study was to assess how different input types and rates would affect the C : N : P molar ratios of bulk soil, organic matter and microbial biomass in cropped soils in the long term. Thus, we analysed the C, N, and P inputs and budgets as well as soil properties in three long-term experiments established on different soil types: the Saria soil fertility trial (Burkina Faso), the Wagga Wagga rotation/stubble management/soil preparation trial (Australia), and the DOK (bio-Dynamic, bio-Organic, and "Konventionell") cropping system trial (Switzerland). In each of these trials, there was a large range of C, N, and P inputs which had a strong impact on element concentrations in soils. However, although C : N : P ratios of the inputs were highly variable, they had only weak effects on soil C : N : P ratios. At Saria, a positive correlation was found between the N : P ratio of inputs and microbial biomass, while no relation was observed between the nutrient ratios of inputs and soil organic matter. At Wagga Wagga, the C : P ratio of inputs was significantly correlated to total soil C : P, N : P, and C : N ratios, but had no impact on the elemental composition of microbial biomass. In the DOK trial, a positive correlation was found between the C budget and the C to organic P ratio in soils, while the nutrient ratios of inputs were not related to those in the microbial biomass. We argue that these responses are due to differences in soil properties among sites. At Saria, the soil is dominated by quartz and some kaolinite, has a coarse texture, a fragile structure, and a low nutrient content. Thus, microorganisms feed on inputs (plant residues, manure). In contrast, the soil at

  9. 7 CFR 3430.607 - Stakeholder input.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 15 2010-01-01 2010-01-01 false Stakeholder input. 3430.607 Section 3430.607 Agriculture Regulations of the Department of Agriculture (Continued) COOPERATIVE STATE RESEARCH, EDUCATION... § 3430.607 Stakeholder input. CSREES shall seek and obtain stakeholder input through a variety of forums...

  10. Input Uncertainty and its Implications on Parameter Assessment in Hydrologic and Hydroclimatic Modelling Studies

    Science.gov (United States)

    Chowdhury, S.; Sharma, A.

    2005-12-01

    Hydrological model inputs are often derived from measurements at point locations taken at discrete time steps. The nature of uncertainty associated with such inputs is thus a function of the quality and number of measurements available in time. A change in these characteristics (such as a change in the number of rain-gauge inputs used to derive spatially averaged rainfall) results in inhomogeneity in the associated distributional profile. Ignoring such uncertainty can lead to models that aim to simulate based on the observed input variable instead of the true measurement, resulting in a biased representation of the underlying system dynamics as well as an increase in both bias and the predictive uncertainty in simulations. This is especially true of cases where the nature of uncertainty likely in the future is significantly different to that in the past. Possible examples include situations where the accuracy of the catchment averaged rainfall has increased substantially due to an increase in the rain-gauge density, or accuracy of climatic observations (such as sea surface temperatures) increased due to the use of more accurate remote sensing technologies. We introduce here a method to ascertain the true value of parameters in the presence of additive uncertainty in model inputs. This method, known as SIMulation EXtrapolation (SIMEX, [Cook, 1994]) operates on the basis of an empirical relationship between parameters and the level of additive input noise (or uncertainty). The method starts with generating a series of alternate realisations of model inputs by artificially adding white noise in increasing multiples of the known error variance. The alternate realisations lead to alternate sets of parameters that are increasingly biased with respect to the truth due to the increased variability in the inputs. Once several such realisations have been drawn, one is able to formulate an empirical relationship between the parameter values and the level of additive noise

  11. Input to the PRAST computer code used in the SRS probabilistic risk assessment

    International Nuclear Information System (INIS)

    Kearnaghan, D.P.

    1992-01-01

    The PRAST (Production Reactor Algorithm for Source Terms) computer code was developed by Westinghouse Savannah River Company and Science Application International Corporation for the quantification of source terms for the SRS Savannah River Site (SRS) Reactor Probabilistic Risk Assessment. PRAST requires as input a set of release fractions, decontamination factors, transfer fractions and source term characteristics that accurately reflect the conditions that are evaluated by PRAST. This document links the analyses which form the basis for the PRAST input parameters. In addition, it gives the distribution of the input parameters that are uncertain and considered to be important to the evaluation of the source terms to the environment

  12. On the Influence of Input Data Quality to Flood Damage Estimation: The Performance of the INSYDE Model

    Directory of Open Access Journals (Sweden)

    Daniela Molinari

    2017-09-01

    Full Text Available IN-depth SYnthetic Model for Flood Damage Estimation (INSYDE is a model for the estimation of flood damage to residential buildings at the micro-scale. This study investigates the sensitivity of INSYDE to the accuracy of input data. Starting from the knowledge of input parameters at the scale of individual buildings for a case study, the level of detail of input data is progressively downgraded until the condition in which a representative value is defined for all inputs at the census block scale. The analysis reveals that two conditions are required to limit the errors in damage estimation: the representativeness of representatives values with respect to micro-scale values and the local knowledge of the footprint area of the buildings, being the latter the main extensive variable adopted by INSYDE. Such a result allows for extending the usability of the model at the meso-scale, also in different countries, depending on the availability of aggregated building data.

  13. World Input-Output Network.

    Directory of Open Access Journals (Sweden)

    Federica Cerina

    Full Text Available Production systems, traditionally analyzed as almost independent national systems, are increasingly connected on a global scale. Only recently becoming available, the World Input-Output Database (WIOD is one of the first efforts to construct the global multi-regional input-output (GMRIO tables. By viewing the world input-output system as an interdependent network where the nodes are the individual industries in different economies and the edges are the monetary goods flows between industries, we analyze respectively the global, regional, and local network properties of the so-called world input-output network (WION and document its evolution over time. At global level, we find that the industries are highly but asymmetrically connected, which implies that micro shocks can lead to macro fluctuations. At regional level, we find that the world production is still operated nationally or at most regionally as the communities detected are either individual economies or geographically well defined regions. Finally, at local level, for each industry we compare the network-based measures with the traditional methods of backward linkages. We find that the network-based measures such as PageRank centrality and community coreness measure can give valuable insights into identifying the key industries.

  14. Bounding the conservatism in flaw-related variables for pressure vessel integrity analyses

    International Nuclear Information System (INIS)

    Foulds, J.R.; Kennedy, E.L.

    1993-01-01

    The fracture mechanics-based integrity analysis of a pressure vessel, whether performed deterministically or probabilistically, requires use of one or more flaw-related input variables, such as flaw size, number of flaws, flaw location, and flaw type. The specific values of these variables are generally selected with the intent to ensure conservative predictions of vessel integrity. These selected values, however, are largely independent of vessel-specific inspection results, or are, at best, deduced by ''conservative'' interpretation of vessel-specific inspection results without adequate consideration of the pertinent inspection system performance (reliability). In either case, the conservatism associated with the flaw-related variables chosen for analysis remains examination (NDE) technology and the recently formulated ASME Code procedures for qualifying NDE system capability and performance (as applied to selected nuclear power plant components) now provides a systematic means of bounding the conservatism in flaw-related input variables for pressure vessel integrity analyses. This is essentially achieved by establishing probabilistic (risk)-based limits on the assigned variable values, dependent upon the vessel inspection results and on the inspection system unreliability. Described herein is this probabilistic method and its potential application to: (i) defining a vessel-specific ''reference'' flaw for calculating pressure-temperature limit curves in the deterministic evaluation of pressurized water reactor (PWR) reactor vessels, and (ii) limiting the flaw distribution input to a PWR reactor vessel-specific, probabilistic integrity analysis for pressurized thermal shock loads

  15. Inhibitory Gating of Basolateral Amygdala Inputs to the Prefrontal Cortex.

    Science.gov (United States)

    McGarry, Laura M; Carter, Adam G

    2016-09-07

    Interactions between the prefrontal cortex (PFC) and basolateral amygdala (BLA) regulate emotional behaviors. However, a circuit-level understanding of functional connections between these brain regions remains incomplete. The BLA sends prominent glutamatergic projections to the PFC, but the overall influence of these inputs is predominantly inhibitory. Here we combine targeted recordings and optogenetics to examine the synaptic underpinnings of this inhibition in the mouse infralimbic PFC. We find that BLA inputs preferentially target layer 2 corticoamygdala over neighboring corticostriatal neurons. However, these inputs make even stronger connections onto neighboring parvalbumin and somatostatin expressing interneurons. Inhibitory connections from these two populations of interneurons are also much stronger onto corticoamygdala neurons. Consequently, BLA inputs are able to drive robust feedforward inhibition via two parallel interneuron pathways. Moreover, the contributions of these interneurons shift during repetitive activity, due to differences in short-term synaptic dynamics. Thus, parvalbumin interneurons are activated at the start of stimulus trains, whereas somatostatin interneuron activation builds during these trains. Together, these results reveal how the BLA impacts the PFC through a complex interplay of direct excitation and feedforward inhibition. They also highlight the roles of targeted connections onto multiple projection neurons and interneurons in this cortical circuit. Our findings provide a mechanistic understanding for how the BLA can influence the PFC circuit, with important implications for how this circuit participates in the regulation of emotion. The prefrontal cortex (PFC) and basolateral amygdala (BLA) interact to control emotional behaviors. Here we show that BLA inputs elicit direct excitation and feedforward inhibition of layer 2 projection neurons in infralimbic PFC. BLA inputs are much stronger at corticoamygdala neurons compared

  16. 7 CFR 3430.15 - Stakeholder input.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 15 2010-01-01 2010-01-01 false Stakeholder input. 3430.15 Section 3430.15... Stakeholder input. Section 103(c)(2) of the Agricultural Research, Extension, and Education Reform Act of 1998... RFAs for competitive programs. CSREES will provide instructions for submission of stakeholder input in...

  17. Metabolic Syndrome and Importance of Associated Variables in Children and Adolescents in Guabiruba - SC, Brazil

    Directory of Open Access Journals (Sweden)

    Nilton Rosini

    2015-07-01

    Full Text Available Background:The risk factors that characterize metabolic syndrome (MetS may be present in childhood and adolescence, increasing the risk of cardiovascular disease in adulthood.Objective:Evaluate the prevalence of MetS and the importance of its associated variables, including insulin resistance (IR, in children and adolescents in the city of Guabiruba-SC, Brazil.Methods:Cross-sectional study with 1011 students (6–14 years, 52.4% girls, 58.5% children. Blood samples were collected for measurement of biochemical parameters by routine laboratory methods. IR was estimated by the HOMA-IR index, and weight, height, waist circumference and blood pressure were determined. Multivariate logistic regression models were used to examine the associations between risk variables and MetS.Results:The prevalence of MetS, IR, overweight and obesity in the cohort were 14%, 8.5%, 21% and 13%, respectively. Among students with MetS, 27% had IR, 33% were overweight, 45.5% were obese and 22% were eutrophic. IR was more common in overweight (48% and obese (41% students when compared with eutrophic individuals (11%; p = 0.034. The variables with greatest influence on the development of MetS were obesity (OR = 32.7, overweight (OR = 6.1, IR (OR = 4.4; p ≤ 0.0001 for all and age (OR = 1.15; p = 0.014.Conclusion:There was a high prevalence of MetS in children and adolescents evaluated in this study. Students who were obese, overweight or insulin resistant had higher chances of developing the syndrome.

  18. Input description for BIOPATH

    International Nuclear Information System (INIS)

    Marklund, J.E.; Bergstroem, U.; Edlund, O.

    1980-01-01

    The computer program BIOPATH describes the flow of radioactivity within a given ecosystem after a postulated release of radioactive material and the resulting dose for specified population groups. The present report accounts for the input data necessary to run BIOPATH. The report also contains descriptions of possible control cards and an input example as well as a short summary of the basic theory.(author)

  19. Spatial and temporal variability in seasonal snow density

    KAUST Repository

    Bormann, Kathryn J.

    2013-03-01

    Snow density is a fundamental physical property of snowpacks used in many aspects of snow research. As an integral component in the remote sensing of snow water equivalent and parameterisation of snow models, snow density may be used to describe many important features of snowpack behaviour. The present study draws on a significant dataset of snow density and climate observations from the United States, Australia and the former Soviet Union and uses regression-based techniques to identify the dominant climatological drivers for snow densification rates, characterise densification rate variability and estimate spring snow densities from more readily available climate data. Total winter precipitation was shown to be the most prominent driver of snow densification rates, with mean air temperature and melt-refreeze events also found to be locally significant. Densification rate variance is very high at Australian sites, very low throughout the former Soviet Union and between these extremes throughout much of the US. Spring snow densities were estimated using a statistical model with climate variable inputs and best results were achieved when snow types were treated differently. Given the importance of snow density information in many snow-related research disciplines, this work has implications for current methods of converting snow depths to snow water equivalent, the representation of snow dynamics in snow models and remote sensing applications globally. © 2013 Elsevier B.V.

  20. Spatial and temporal variability in seasonal snow density

    KAUST Repository

    Bormann, Kathryn J.; Westra, Seth; Evans, Jason P.; McCabe, Matthew

    2013-01-01

    Snow density is a fundamental physical property of snowpacks used in many aspects of snow research. As an integral component in the remote sensing of snow water equivalent and parameterisation of snow models, snow density may be used to describe many important features of snowpack behaviour. The present study draws on a significant dataset of snow density and climate observations from the United States, Australia and the former Soviet Union and uses regression-based techniques to identify the dominant climatological drivers for snow densification rates, characterise densification rate variability and estimate spring snow densities from more readily available climate data. Total winter precipitation was shown to be the most prominent driver of snow densification rates, with mean air temperature and melt-refreeze events also found to be locally significant. Densification rate variance is very high at Australian sites, very low throughout the former Soviet Union and between these extremes throughout much of the US. Spring snow densities were estimated using a statistical model with climate variable inputs and best results were achieved when snow types were treated differently. Given the importance of snow density information in many snow-related research disciplines, this work has implications for current methods of converting snow depths to snow water equivalent, the representation of snow dynamics in snow models and remote sensing applications globally. © 2013 Elsevier B.V.

  1. A liquid lens switching-based motionless variable fiber-optic delay line

    Science.gov (United States)

    Khwaja, Tariq Shamim; Reza, Syed Azer; Sheikh, Mumtaz

    2018-05-01

    We present a Variable Fiber-Optic Delay Line (VFODL) module capable of imparting long variable delays by switching an input optical/RF signal between Single Mode Fiber (SMF) patch cords of different lengths through a pair of Electronically Controlled Tunable Lenses (ECTLs) resulting in a polarization-independent operation. Depending on intended application, the lengths of the SMFs can be chosen accordingly to achieve the desired VFODL operation dynamic range. If so desired, the state of the input signal polarization can be preserved with the use of commercially available polarization-independent ECTLs along with polarization-maintaining SMFs (PM-SMFs), resulting in an output polarization that is identical to the input. An ECTL-based design also improves power consumption and repeatability. The delay switching mechanism is electronically-controlled, involves no bulk moving parts, and can be fully-automated. The VFODL module is compact due to the use of small optical components and SMFs that can be packaged compactly.

  2. Quasi-supervised scoring of human sleep in polysomnograms using augmented input variables.

    Science.gov (United States)

    Yaghouby, Farid; Sunderam, Sridhar

    2015-04-01

    The limitations of manual sleep scoring make computerized methods highly desirable. Scoring errors can arise from human rater uncertainty or inter-rater variability. Sleep scoring algorithms either come as supervised classifiers that need scored samples of each state to be trained, or as unsupervised classifiers that use heuristics or structural clues in unscored data to define states. We propose a quasi-supervised classifier that models observations in an unsupervised manner but mimics a human rater wherever training scores are available. EEG, EMG, and EOG features were extracted in 30s epochs from human-scored polysomnograms recorded from 42 healthy human subjects (18-79 years) and archived in an anonymized, publicly accessible database. Hypnograms were modified so that: 1. Some states are scored but not others; 2. Samples of all states are scored but not for transitional epochs; and 3. Two raters with 67% agreement are simulated. A framework for quasi-supervised classification was devised in which unsupervised statistical models-specifically Gaussian mixtures and hidden Markov models--are estimated from unlabeled training data, but the training samples are augmented with variables whose values depend on available scores. Classifiers were fitted to signal features incorporating partial scores, and used to predict scores for complete recordings. Performance was assessed using Cohen's Κ statistic. The quasi-supervised classifier performed significantly better than an unsupervised model and sometimes as well as a completely supervised model despite receiving only partial scores. The quasi-supervised algorithm addresses the need for classifiers that mimic scoring patterns of human raters while compensating for their limitations. Copyright © 2015 Elsevier Ltd. All rights reserved.

  3. Response of the Black Sea methane budget to massive short-term submarine inputs of methane

    DEFF Research Database (Denmark)

    Schmale, O.; Haeckel, M.; McGinnis, D. F.

    2011-01-01

    A steady state box model was developed to estimate the methane input into the Black Sea water column at various water depths. Our model results reveal a total input of methane of 4.7 Tg yr(-1). The model predicts that the input of methane is largest at water depths between 600 and 700 m (7......% of the total input), suggesting that the dissociation of methane gas hydrates at water depths equivalent to their upper stability limit may represent an important source of methane into the water column. In addition we discuss the effects of massive short-term methane inputs (e. g. through eruptions of deep......-water mud volcanoes or submarine landslides at intermediate water depths) on the water column methane distribution and the resulting methane emission to the atmosphere. Our non-steady state simulations predict that these inputs will be effectively buffered by intense microbial methane consumption...

  4. Method and system to estimate variables in an integrated gasification combined cycle (IGCC) plant

    Science.gov (United States)

    Kumar, Aditya; Shi, Ruijie; Dokucu, Mustafa

    2013-09-17

    System and method to estimate variables in an integrated gasification combined cycle (IGCC) plant are provided. The system includes a sensor suite to measure respective plant input and output variables. An extended Kalman filter (EKF) receives sensed plant input variables and includes a dynamic model to generate a plurality of plant state estimates and a covariance matrix for the state estimates. A preemptive-constraining processor is configured to preemptively constrain the state estimates and covariance matrix to be free of constraint violations. A measurement-correction processor may be configured to correct constrained state estimates and a constrained covariance matrix based on processing of sensed plant output variables. The measurement-correction processor is coupled to update the dynamic model with corrected state estimates and a corrected covariance matrix. The updated dynamic model may be configured to estimate values for at least one plant variable not originally sensed by the sensor suite.

  5. Fault tolerant control of wind turbines using unknown input observers

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Stoustrup, Jakob

    2012-01-01

    This paper presents a scheme for accommodating faults in the rotor and generator speed sensors in a wind turbine. These measured values are important both for the wind turbine controller as well as the supervisory control of the wind turbine. The scheme is based on unknown input observers, which...

  6. Frequency Preference Response to Oscillatory Inputs in Two-dimensional Neural Models: A Geometric Approach to Subthreshold Amplitude and Phase Resonance.

    Science.gov (United States)

    Rotstein, Horacio G

    2014-01-01

    We investigate the dynamic mechanisms of generation of subthreshold and phase resonance in two-dimensional linear and linearized biophysical (conductance-based) models, and we extend our analysis to account for the effect of simple, but not necessarily weak, types of nonlinearities. Subthreshold resonance refers to the ability of neurons to exhibit a peak in their voltage amplitude response to oscillatory input currents at a preferred non-zero (resonant) frequency. Phase-resonance refers to the ability of neurons to exhibit a zero-phase (or zero-phase-shift) response to oscillatory input currents at a non-zero (phase-resonant) frequency. We adapt the classical phase-plane analysis approach to account for the dynamic effects of oscillatory inputs and develop a tool, the envelope-plane diagrams, that captures the role that conductances and time scales play in amplifying the voltage response at the resonant frequency band as compared to smaller and larger frequencies. We use envelope-plane diagrams in our analysis. We explain why the resonance phenomena do not necessarily arise from the presence of imaginary eigenvalues at rest, but rather they emerge from the interplay of the intrinsic and input time scales. We further explain why an increase in the time-scale separation causes an amplification of the voltage response in addition to shifting the resonant and phase-resonant frequencies. This is of fundamental importance for neural models since neurons typically exhibit a strong separation of time scales. We extend this approach to explain the effects of nonlinearities on both resonance and phase-resonance. We demonstrate that nonlinearities in the voltage equation cause amplifications of the voltage response and shifts in the resonant and phase-resonant frequencies that are not predicted by the corresponding linearized model. The differences between the nonlinear response and the linear prediction increase with increasing levels of the time scale separation between

  7. Modeling and generating input processes

    Energy Technology Data Exchange (ETDEWEB)

    Johnson, M.E.

    1987-01-01

    This tutorial paper provides information relevant to the selection and generation of stochastic inputs to simulation studies. The primary area considered is multivariate but much of the philosophy at least is relevant to univariate inputs as well. 14 refs.

  8. Quantification of allochthonous nutrient input into freshwater bodies by herbivorous waterbirds

    NARCIS (Netherlands)

    Hahn, S.M.; Bauer, S.; Klaassen, M.R.J.

    2008-01-01

    1. Waterbirds are considered to import large quantities of nutrients to freshwater bodies but quantification of these loadings remains problematic. We developed two general models to calculate such allochthonous nutrient inputs considering food intake, foraging behaviour and digestive performance of

  9. How pattern formation in ring networks of excitatory and inhibitory spiking neurons depends on the input current regime.

    Science.gov (United States)

    Kriener, Birgit; Helias, Moritz; Rotter, Stefan; Diesmann, Markus; Einevoll, Gaute T

    2013-01-01

    Pattern formation, i.e., the generation of an inhomogeneous spatial activity distribution in a dynamical system with translation invariant structure, is a well-studied phenomenon in neuronal network dynamics, specifically in neural field models. These are population models to describe the spatio-temporal dynamics of large groups of neurons in terms of macroscopic variables such as population firing rates. Though neural field models are often deduced from and equipped with biophysically meaningful properties, a direct mapping to simulations of individual spiking neuron populations is rarely considered. Neurons have a distinct identity defined by their action on their postsynaptic targets. In its simplest form they act either excitatorily or inhibitorily. When the distribution of neuron identities is assumed to be periodic, pattern formation can be observed, given the coupling strength is supracritical, i.e., larger than a critical weight. We find that this critical weight is strongly dependent on the characteristics of the neuronal input, i.e., depends on whether neurons are mean- or fluctuation driven, and different limits in linearizing the full non-linear system apply in order to assess stability. In particular, if neurons are mean-driven, the linearization has a very simple form and becomes independent of both the fixed point firing rate and the variance of the input current, while in the very strongly fluctuation-driven regime the fixed point rate, as well as the input mean and variance are important parameters in the determination of the critical weight. We demonstrate that interestingly even in "intermediate" regimes, when the system is technically fluctuation-driven, the simple linearization neglecting the variance of the input can yield the better prediction of the critical coupling strength. We moreover analyze the effects of structural randomness by rewiring individual synapses or redistributing weights, as well as coarse-graining on the formation of

  10. Study of the diurnal time variability of δ15 N and δ13 C in domestic sewage of Piracicaba city (Sao Paulo State, Brazil)

    International Nuclear Information System (INIS)

    Evangelista, Ricardo A.O.; Bortoletto Junior, Milton J.; Mortatti, Jefferson

    2002-01-01

    Diurnal variability concentrations and δ 13 C of DOC (dissolved organic carbon), DTC (dissolved total carbon) and POC (particulate organic carbon) as well as concentrations and δ 13 N of NH 4 + and PON (particulate organic nitrogen) have been measured using a ANCA-SL mass spectrometry in three points of raw sewage inputs within Piracicaba river. The results shows an important variability in the isotopic signatures and concentrations of the nitrogen and carbon forms during the diurnal period that can be successfully used to characterize and to distinguish three types of investigated effluents. (author)

  11. Segmented correlation measurements on superconducting bandpass delta-sigma modulator with and without input tone

    International Nuclear Information System (INIS)

    Bulzacchelli, John F; Lee, Hae-Seung; Hong, Merit Y; Misewich, James A; Ketchen, Mark B

    2003-01-01

    Segmented correlation is a useful technique for testing a superconducting analogue-to-digital converter, as it allows the output spectrum to be estimated with fine frequency resolution even when data record lengths are limited by small on-chip acquisition memories. Previously, we presented segmented correlation measurements on a superconducting bandpass delta-sigma modulator sampling at 40.2 GHz under idle channel (no input) conditions. This paper compares the modulator output spectra measured by segmented correlation with and without an input tone. Important practical considerations of calculating segmented correlations are discussed in detail. Resolution enhancement by segmented correlation does reduce the spectral width of the input tone in the desired manner, but the signal power due to the input increases the variance of the spectral estimate near the input frequency, hindering accurate calculation of the in-band noise. This increased variance, which is predicted by theory, must be considered carefully in the application of segmented correlation. Methods for obtaining more accurate estimates of the quantization noise spectrum which are closer to those measured with no input are described

  12. Conceptualizing, Understanding, and Predicting Responsible Decisions and Quality Input

    Science.gov (United States)

    Wall, N.; PytlikZillig, L. M.

    2012-12-01

    In areas such as climate change, where uncertainty is high, it is arguably less difficult to tell when efforts have resulted in changes in knowledge, than when those efforts have resulted in responsible decisions. What is a responsible decision? More broadly, when it comes to citizen input, what is "high quality" input? And most importantly, how are responsible decisions and quality input enhanced? The aim of this paper is to contribute to the understanding of the different dimensions of "responsible" or "quality" public input and citizen decisions by comparing and contrasting the different predictors of those different dimensions. We first present different possibilities for defining, operationalizing and assessing responsible or high quality decisions. For example, responsible decisions or quality input might be defined as using specific content (e.g., using climate change information in decisions appropriately), as using specific processes (e.g., investing time and effort in learning about and discussing the issues prior to making decisions), or on the basis of some judgment of the decision or input itself (e.g., judgments of the rationale provided for the decisions, or number of issues considered when giving input). Second, we present results from our work engaging people with science policy topics, and the different ways that we have tried to define these two constructs. In the area of climate change specifically, we describe the development of a short survey that assesses exposure to climate information, knowledge of and attitudes toward climate change, and use of climate information in one's decisions. Specifically, the short survey was developed based on a review of common surveys of climate change related knowledge, attitudes, and behaviors, and extensive piloting and cognitive interviews. Next, we analyze more than 200 responses to that survey (data collection is currently ongoing and will be complete after the AGU deadline), and report the predictors of

  13. Investigation of RADTRAN Stop Model input parameters for truck stops

    International Nuclear Information System (INIS)

    Griego, N.R.; Smith, J.D.; Neuhauser, K.S.

    1996-01-01

    RADTRAN is a computer code for estimating the risks and consequences as transport of radioactive materials (RAM). RADTRAN was developed and is maintained by Sandia National Laboratories for the US Department of Energy (DOE). For incident-free transportation, the dose to persons exposed while the shipment is stopped is frequently a major percentage of the overall dose. This dose is referred to as Stop Dose and is calculated by the Stop Model. Because stop dose is a significant portion of the overall dose associated with RAM transport, the values used as input for the Stop Model are important. Therefore, an investigation of typical values for RADTRAN Stop Parameters for truck stops was performed. The resulting data from these investigations were analyzed to provide mean values, standard deviations, and histograms. Hence, the mean values can be used when an analyst does not have a basis for selecting other input values for the Stop Model. In addition, the histograms and their characteristics can be used to guide statistical sampling techniques to measure sensitivity of the RADTRAN calculated Stop Dose to the uncertainties in the stop model input parameters. This paper discusses the details and presents the results of the investigation of stop model input parameters at truck stops

  14. Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations

    Science.gov (United States)

    Hoffmann, Holger; Zhao, Gang; Asseng, Senthold; Bindi, Marco; Biernath, Christian; Constantin, Julie; Coucheney, Elsa; Dechow, Rene; Doro, Luca; Eckersten, Henrik; Gaiser, Thomas; Grosz, Balázs; Heinlein, Florian; Kassie, Belay T.; Kersebaum, Kurt-Christian; Klein, Christian; Kuhnert, Matthias; Lewan, Elisabet; Moriondo, Marco; Nendel, Claas; Priesack, Eckart; Raynal, Helene; Roggero, Pier P.; Rötter, Reimund P.; Siebert, Stefan; Specka, Xenia; Tao, Fulu; Teixeira, Edmar; Trombi, Giacomo; Wallach, Daniel; Weihermüller, Lutz; Yeluripati, Jagadeesh; Ewert, Frank

    2016-01-01

    We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations. PMID:27055028

  15. Development a computer codes to couple PWR-GALE output and PC-CREAM input

    Science.gov (United States)

    Kuntjoro, S.; Budi Setiawan, M.; Nursinta Adi, W.; Deswandri; Sunaryo, G. R.

    2018-02-01

    Radionuclide dispersion analysis is part of an important reactor safety analysis. From the analysis it can be obtained the amount of doses received by radiation workers and communities around nuclear reactor. The radionuclide dispersion analysis under normal operating conditions is carried out using the PC-CREAM code, and it requires input data such as source term and population distribution. Input data is derived from the output of another program that is PWR-GALE and written Population Distribution data in certain format. Compiling inputs for PC-CREAM programs manually requires high accuracy, as it involves large amounts of data in certain formats and often errors in compiling inputs manually. To minimize errors in input generation, than it is make coupling program for PWR-GALE and PC-CREAM programs and a program for writing population distribution according to the PC-CREAM input format. This work was conducted to create the coupling programming between PWR-GALE output and PC-CREAM input and programming to written population data in the required formats. Programming is done by using Python programming language which has advantages of multiplatform, object-oriented and interactive. The result of this work is software for coupling data of source term and written population distribution data. So that input to PC-CREAM program can be done easily and avoid formatting errors. Programming sourceterm coupling program PWR-GALE and PC-CREAM is completed, so that the creation of PC-CREAM inputs in souceterm and distribution data can be done easily and according to the desired format.

  16. Wave energy input into the Ekman layer

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    This paper is concerned with the wave energy input into the Ekman layer, based on 3 observational facts that surface waves could significantly affect the profile of the Ekman layer. Under the assumption of constant vertical diffusivity, the analytical form of wave energy input into the Ekman layer is derived. Analysis of the energy balance shows that the energy input to the Ekman layer through the wind stress and the interaction of the Stokes-drift with planetary vorticity can be divided into two kinds. One is the wind energy input, and the other is the wave energy input which is dependent on wind speed, wave characteristics and the wind direction relative to the wave direction. Estimates of wave energy input show that wave energy input can be up to 10% in high-latitude and high-wind speed areas and higher than 20% in the Antarctic Circumpolar Current, compared with the wind energy input into the classical Ekman layer. Results of this paper are of significance to the study of wave-induced large scale effects.

  17. Optimization modeling of U.S. renewable electricity deployment using local input variables

    Science.gov (United States)

    Bernstein, Adam

    For the past five years, state Renewable Portfolio Standard (RPS) laws have been a primary driver of renewable electricity (RE) deployments in the United States. However, four key trends currently developing: (i) lower natural gas prices, (ii) slower growth in electricity demand, (iii) challenges of system balancing intermittent RE within the U.S. transmission regions, and (iv) fewer economical sites for RE development, may limit the efficacy of RPS laws over the remainder of the current RPS statutes' lifetime. An outsized proportion of U.S. RE build occurs in a small number of favorable locations, increasing the effects of these variables on marginal RE capacity additions. A state-by-state analysis is necessary to study the U.S. electric sector and to generate technology specific generation forecasts. We used LP optimization modeling similar to the National Renewable Energy Laboratory (NREL) Renewable Energy Development System (ReEDS) to forecast RE deployment across the 8 U.S. states with the largest electricity load, and found state-level RE projections to Year 2031 significantly lower than thoseimplied in the Energy Information Administration (EIA) 2013 Annual Energy Outlook forecast. Additionally, the majority of states do not achieve their RPS targets in our forecast. Combined with the tendency of prior research and RE forecasts to focus on larger national and global scale models, we posit that further bottom-up state and local analysis is needed for more accurate policy assessment, forecasting, and ongoing revision of variables as parameter values evolve through time. Current optimization software eliminates much of the need for algorithm coding and programming, allowing for rapid model construction and updating across many customized state and local RE parameters. Further, our results can be tested against the empirical outcomes that will be observed over the coming years, and the forecast deviation from the actuals can be attributed to discrete parameter

  18. Tropical rainforests dominate multi-decadal variability of the global carbon cycle

    Science.gov (United States)

    Zhang, X.; Wang, Y. P.; Peng, S.; Rayner, P. J.; Silver, J.; Ciais, P.; Piao, S.; Zhu, Z.; Lu, X.; Zheng, X.

    2017-12-01

    Recent studies find that inter-annual variability of global atmosphere-to-land CO2 uptake (NBP) is dominated by semi-arid ecosystems. However, the NBP variations at decadal to multi-decadal timescales are still not known. By developing a basic theory for the role of net primary production (NPP) and heterotrophic respiration (Rh) on NBP and applying it to 100-year simulations of terrestrial ecosystem models forced by observational climate, we find that tropical rainforests dominate the multi-decadal variability of global NBP (48%) rather than the semi-arid lands (35%). The NBP variation at inter-annual timescales is almost 90% contributed by NPP, but across longer timescales is progressively controlled by Rh that constitutes the response from the NPP-derived soil carbon input (40%) and the response of soil carbon turnover rates to climate variability (60%). The NBP variations of tropical rainforests is modulated by the ENSO and the PDO through their significant influences on temperature and precipitation at timescales of 2.5-7 and 25-50 years, respectively. This study highlights the importance of tropical rainforests on the multi-decadal variability of global carbon cycle, suggesting that we need to carefully differentiate the effect of NBP long-term fluctuations associated with ocean-related climate modes on the long-term trend in land sink.

  19. Energy inputs and outputs in a chickpea production system in ...

    African Journals Online (AJOL)

    Chickpea (Cicer arietinum L.) is one of the most important grain legumes which traditionally cultivated in marginal areas and saline soils. In this study, chickpea production in Kurdistan, Iran and the energy equivalences of input used in production were investigated. The aims of this study were to determine the amount of ...

  20. Gestures and multimodal input

    OpenAIRE

    Keates, Simeon; Robinson, Peter

    1999-01-01

    For users with motion impairments, the standard keyboard and mouse arrangement for computer access often presents problems. Other approaches have to be adopted to overcome this. In this paper, we will describe the development of a prototype multimodal input system based on two gestural input channels. Results from extensive user trials of this system are presented. These trials showed that the physical and cognitive loads on the user can quickly become excessive and detrimental to the interac...

  1. Estimated anthropogenic nitrogen and phosphorus inputs to the land surface of the conterminous United States--1992, 1997, and 2002

    Science.gov (United States)

    Sprague, Lori A.; Gronberg, Jo Ann M.

    2013-01-01

    Anthropogenic inputs of nitrogen and phosphorus to each county in the conterminous United States and to the watersheds of 495 surface-water sites studied as part of the U.S. Geological Survey National Water-Quality Assessment Program were quantified for the years 1992, 1997, and 2002. Estimates of inputs of nitrogen and phosphorus from biological fixation by crops (for nitrogen only), human consumption, crop production for human consumption, animal production for human consumption, animal consumption, and crop production for animal consumption for each county are provided in a tabular dataset. These county-level estimates were allocated to the watersheds of the surface-water sites to estimate watershed-level inputs from the same sources; these estimates also are provided in a tabular dataset, together with calculated estimates of net import of food and net import of feed and previously published estimates of inputs from atmospheric deposition, fertilizer, and recoverable manure. The previously published inputs are provided for each watershed so that final estimates of total anthropogenic nutrient inputs could be calculated. Estimates of total anthropogenic inputs are presented together with previously published estimates of riverine loads of total nitrogen and total phosphorus for reference.

  2. Effects of allochthonous inputs in the control of infectious disease of prey

    International Nuclear Information System (INIS)

    Sahoo, Banshidhar; Poria, Swarup

    2015-01-01

    Highlights: •Infected predator–prey model with allochthonous inputs is proposed. •Stability and persistence conditions are derived. •Bifurcation is determined with respect to allochthonous inputs. •Results show that system can not be disease free without allochthonous inputs. •Hopf and its continuation bifurcation is analysed numerically. -- Abstract: Allochthonous inputs are important sources of productivity in many food webs and their influences on food chain model demand further investigations. In this paper, assuming the existence of allochthonous inputs for intermediate predator, a food chain model is formulated with disease in the prey. The stability and persistence conditions of the equilibrium points are determined. Extinction criterion for infected prey population is obtained. It is shown that suitable amount of allochthonous inputs to intermediate predator can control infectious disease of prey population, provided initial intermediate predator population is above a critical value. This critical intermediate population size increases monotonically with the increase of infection rate. It is also shown that control of infectious disease of prey is possible in some cases of seasonally varying contact rate. Dynamical behaviours of the model are investigated numerically through one and two parameter bifurcation analysis using MATCONT 2.5.1 package. The occurrence of Hopf and its continuation curves are noted with the variation of infection rate and allochthonous food availability. The continuation curves of limit point cycle and Neimark Sacker bifurcation are drawn by varying the rate of infection and allochthonous inputs. This study introduces a novel natural non-toxic method for controlling infectious disease of prey in a food chain model

  3. On the Relationship Between Input and Interaction Psycholinguistic, Cognitive, and Ecological Perspectives in SLA

    Directory of Open Access Journals (Sweden)

    Parisa Daftarifard

    2010-09-01

    Full Text Available Input is one of the most important elements in the process of second language acquisition (SLA. As Gass (1997 points out, second language learning simply cannot take place without input of some sort. Since then, specific issues have been actively debated in SLA on the nature of input and input processing, such as the amount of input that is necessary for language acquisition, various attributes of input and how they may facilitate or hinder acquisition, and instructional method that may enhance input. In this paper, four hypotheses and paradigms of input processing have been described. It is delineated that although the three paradigms of triggering, input hypothesis, and interaction hypothesis have been widely used and accepted, they lack the ability to account for the dynamic nature of language. Affordance, on the other hand, can account for such a nature of language.
    Therefore, affordance replaces fixed-eye vision by mobile-eye vision; an active learner establishes relationships with and within the environment. The learner can directly perceive and act on the ambient language without having to route everything through a pre-existing mental apparatus of schemata and representation, while this is not true in the fixed-code theory. In the fixed-eye theory of communication it is assumed that ready-made messages are coded at one end, transmitted,
    and then decoded in identical form at the other end. We need in its place a constructivist theory of message construction and interpretation.

  4. Fatigue life assessment under multiaxial variable amplitude loading

    International Nuclear Information System (INIS)

    Morilhat, P.; Kenmeugne, B.; Vidal-Salle, E.; Robert, J.L.

    1996-06-01

    A variable amplitude multiaxial fatigue life prediction method is presented in this paper. It is based on a stress as input data are the stress tensor histories which may be calculated by FEM analysis or measured directly on the structure during the service loading. The different steps of he method are first presented then its experimental validation is realized for log and finite fatigue lives through biaxial variable amplitude loading tests using cruciform steel samples. (authors). 9 refs., 7 figs

  5. Responses of tree and insect herbivores to elevated nitrogen inputs: A meta-analysis

    Science.gov (United States)

    Li, Furong; Dudley, Tom L.; Chen, Baoming; Chang, Xiaoyu; Liang, Liyin; Peng, Shaolin

    2016-11-01

    Increasing atmospheric nitrogen (N) inputs have the potential to alter terrestrial ecosystem function through impacts on plant-herbivore interactions. The goal of our study is to search for a general pattern in responses of tree characteristics important for herbivores and insect herbivorous performance to elevated N inputs. We conducted a meta-analysis based on 109 papers describing impacts of nitrogen inputs on tree characteristics and 16 papers on insect performance. The differences in plant characteristics and insect performance between broadleaves and conifers were also explored. Tree aboveground biomass, leaf biomass and leaf N concentration significantly increased under elevated N inputs. Elevated N inputs had no significantly overall effect on concentrations of phenolic compounds and lignin but adversely affected tannin, as defensive chemicals for insect herbivores. Additionally, the overall effect of insect herbivore performance (including development time, insect biomass, relative growth rate, and so on) was significantly increased by elevated N inputs. According to the inconsistent responses between broadleaves and conifers, broadleaves would be more likely to increase growth by light interception and photosynthesis rather than producing more defensive chemicals to elevated N inputs by comparison with conifers. Moreover, the overall carbohydrate concentration was significantly reduced by 13.12% in broadleaves while increased slightly in conifers. The overall tannin concentration decreased significantly by 39.21% in broadleaves but a 5.8% decrease in conifers was not significant. The results of the analysis indicated that elevated N inputs would provide more food sources and ameliorate tree palatability for insects, while the resistance of trees against their insect herbivores was weakened, especially for broadleaves. Thus, global forest insect pest problems would be aggravated by elevated N inputs. As N inputs continue to rise in the future, forest

  6. Soil-related Input Parameters for the Biosphere Model

    International Nuclear Information System (INIS)

    A. J. Smith

    2003-01-01

    This analysis is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN), a biosphere model supporting the Total System Performance Assessment (TSPA) for the geologic repository at Yucca Mountain. The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A graphical representation of the documentation hierarchy for the ERMYN biosphere model is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (BSC 2003 [163602]). It should be noted that some documents identified in Figure 1-1 may be under development at the time this report is issued and therefore not available. This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this report. This report, ''Soil Related Input Parameters for the Biosphere Model'', is one of the five analysis reports that develop input parameters for use in the ERMYN model. This report is the source documentation for the six biosphere parameters identified in Table 1-1. ''The Biosphere Model Report'' (BSC 2003 [160699]) describes in detail the conceptual model as well as the mathematical model and its input parameters. The purpose of this analysis was to develop the biosphere model parameters needed to evaluate doses from pathways associated with the accumulation and depletion of radionuclides in the soil. These parameters support the calculation of radionuclide concentrations in soil from on-going irrigation and ash

  7. Importance of fishing as a segmentation variable in the application of a social worlds model

    Science.gov (United States)

    Gigliotti, Larry M.; Chase, Loren

    2017-01-01

    Market segmentation is useful to understanding and classifying the diverse range of outdoor recreation experiences sought by different recreationists. Although many different segmentation methodologies exist, many are complex and difficult to measure accurately during in-person intercepts, such as that of creel surveys. To address that gap in the literature, we propose a single-item measure of the importance of fishing as a surrogate to often overly- or needlesslycomplex segmentation techniques. The importance of fishing item is a measure of the value anglers place on the activity or a coarse quantification of how central the activity is to the respondent’s lifestyle (scale: 0 = not important, 1 = slightly, 2 = moderately, 3 = very, and 4 = fishing is my most important recreational activity). We suggest the importance scale may be a proxy measurement for segmenting anglers using the social worlds model as a theoretical framework. Vaske (1980) suggested that commitment to recreational activities may be best understood in relation to social group participation and the social worlds model provides a rich theoretical framework for understanding social group segments. Unruh (1983) identified four types of actor involvement in social worlds: strangers, tourists, regulars, and insiders, differentiated by four characteristics (orientation, experiences, relationships, and commitment). We evaluated the importance of fishing as a segmentation variable using data collected by a mixed-mode survey of South Dakota anglers fishing in 2010. We contend that this straightforward measurement may be useful for segmenting outdoor recreation activities when more complicated segmentation schemes are not suitable. Further, this index, when coupled with the social worlds model, provides a valuable framework for understanding the segments and making management decisions.

  8. Simplifying BRDF input data for optical signature modeling

    Science.gov (United States)

    Hallberg, Tomas; Pohl, Anna; Fagerström, Jan

    2017-05-01

    Scene simulations of optical signature properties using signature codes normally requires input of various parameterized measurement data of surfaces and coatings in order to achieve realistic scene object features. Some of the most important parameters are used in the model of the Bidirectional Reflectance Distribution Function (BRDF) and are normally determined by surface reflectance and scattering measurements. Reflectance measurements of the spectral Directional Hemispherical Reflectance (DHR) at various incident angles can normally be performed in most spectroscopy labs, while measuring the BRDF is more complicated or may not be available at all in many optical labs. We will present a method in order to achieve the necessary BRDF data directly from DHR measurements for modeling software using the Sandford-Robertson BRDF model. The accuracy of the method is tested by modeling a test surface by comparing results from using estimated and measured BRDF data as input to the model. These results show that using this method gives no significant loss in modeling accuracy.

  9. Effect of heat input on dilution and heat affected zone in submerged ...

    Indian Academy of Sciences (India)

    Proper management of heat input in weld- ing is important .... total nugget area, heat transfer boundary length, and nugget parameter. 3. ... Predominant parameters that had greater influence on welding quality were identified as wire feed rate ...

  10. Patterns in the Physical, Chemical, and Biological Composition of Icelandic Lakes and the Dominant Factors Controlling Variability Across Watersheds

    Science.gov (United States)

    Greco, A.; Strock, K.; Edwards, B. R.

    2017-12-01

    Fourteen lakes were sampled in the southern and western area of Iceland in June of 2017. The southern systems, within the Eastern Volcanic Zone, have minimal soil development and active volcanoes that produce ash input to lakes. Lakes in the Western Volcanic Zone were more diverse and located in older bedrock with more extensively weathered soil. Physical variables (temperature, oxygen concentration, and water clarity), chemical variables (pH, conductivity, dissolved and total nitrogen and phosphorus concentrations, and dissolved organic carbon concentration), and biological variables (algal biomass) were compared across the lakes sampled in these geographic regions. There was a large range in lake characteristics, including five to eighteen times higher algal biomass in the southern systems that experience active ash input to lakes. The lakes located in the Eastern Volcanic Zone also had higher conductivity and lower pH, especially in systems receiving substantial geothermal input. These results were analyzed in the context of more extensive lake sampling efforts across Iceland (46 lakes) to determine defining characteristics of lakes in each region and to identify variables that drive heterogeneous patterns in physical, chemical, and biological lake features within each region. Coastal systems, characterized by high conductivity, and glacially-fed systems, characterized by high iron concentrations, were unique from lakes in all other regions. Clustering and principal component analyses revealed that lake type (plateau, valley, spring-fed, and direct-runoff) was not the primary factor explaining variability in lake chemistry outside of the coastal and glacial lake types. Instead, lakes differentiated along a gradient of iron concentration and total nitrogen concentration. The physical and chemical properties of subarctic lakes are especially susceptible to both natural and human-induced environmental impacts. However, relatively little is known about the

  11. Fertilizer consumption and energy input for 16 crops in the United States

    Science.gov (United States)

    Amenumey, Sheila E.; Capel, Paul D.

    2014-01-01

    Fertilizer use by U.S. agriculture has increased over the past few decades. The production and transportation of fertilizers (nitrogen, N; phosphorus, P; potassium, K) are energy intensive. In general, about a third of the total energy input to crop production goes to the production of fertilizers, one-third to mechanization, and one-third to other inputs including labor, transportation, pesticides, and electricity. For some crops, fertilizer is the largest proportion of total energy inputs. Energy required for the production and transportation of fertilizers, as a percentage of total energy input, was determined for 16 crops in the U.S. to be: 19–60% for seven grains, 10–41% for two oilseeds, 25% for potatoes, 12–30% for three vegetables, 2–23% for two fruits, and 3% for dry beans. The harvested-area weighted-average of the fraction of crop fertilizer energy to the total input energy was 28%. The current sources of fertilizers for U.S. agriculture are dependent on imports, availability of natural gas, or limited mineral resources. Given these dependencies plus the high energy costs for fertilizers, an integrated approach for their efficient and sustainable use is needed that will simultaneously maintain or increase crop yields and food quality while decreasing adverse impacts on the environment.

  12. Analysis on relation between safety input and accidents

    Institute of Scientific and Technical Information of China (English)

    YAO Qing-guo; ZHANG Xue-mu; LI Chun-hui

    2007-01-01

    The number of safety input directly determines the level of safety, and there exists dialectical and unified relations between safety input and accidents. Based on the field investigation and reliable data, this paper deeply studied the dialectical relationship between safety input and accidents, and acquired the conclusions. The security situation of the coal enterprises was related to the security input rate, being effected little by the security input scale, and build the relationship model between safety input and accidents on this basis, that is the accident model.

  13. Measuring Input Thresholds on an Existing Board

    Science.gov (United States)

    Kuperman, Igor; Gutrich, Daniel G.; Berkun, Andrew C.

    2011-01-01

    A critical PECL (positive emitter-coupled logic) interface to Xilinx interface needed to be changed on an existing flight board. The new Xilinx input interface used a CMOS (complementary metal-oxide semiconductor) type of input, and the driver could meet its thresholds typically, but not in worst-case, according to the data sheet. The previous interface had been based on comparison with an external reference, but the CMOS input is based on comparison with an internal divider from the power supply. A way to measure what the exact input threshold was for this device for 64 inputs on a flight board was needed. The measurement technique allowed an accurate measurement of the voltage required to switch a Xilinx input from high to low for each of the 64 lines, while only probing two of them. Directly driving an external voltage was considered too risky, and tests done on any other unit could not be used to qualify the flight board. The two lines directly probed gave an absolute voltage threshold calibration, while data collected on the remaining 62 lines without probing gave relative measurements that could be used to identify any outliers. The PECL interface was forced to a long-period square wave by driving a saturated square wave into the ADC (analog to digital converter). The active pull-down circuit was turned off, causing each line to rise rapidly and fall slowly according to the input s weak pull-down circuitry. The fall time shows up as a change in the pulse width of the signal ready by the Xilinx. This change in pulse width is a function of capacitance, pulldown current, and input threshold. Capacitance was known from the different trace lengths, plus a gate input capacitance, which is the same for all inputs. The pull-down current is the same for all inputs including the two that are probed directly. The data was combined, and the Excel solver tool was used to find input thresholds for the 62 lines. This was repeated over different supply voltages and

  14. Assessment of oil content and fatty acid composition variability in two economically important Hibiscus species.

    Science.gov (United States)

    Wang, Ming Li; Morris, Brad; Tonnis, Brandon; Davis, Jerry; Pederson, Gary A

    2012-07-04

    The Hibiscus genus encompasses more than 300 species, but kenaf (Hibiscus cannabinus L.) and roselle (Hibiscus sabdariffa L.) are the two most economically important species within the genus. Seeds from these two Hibiscus species contain a relatively high amount of oil with two unusual fatty acids: dihydrosterculic and vernolic acids. The fatty acid composition in the oil can directly affect oil quality and its utilization. However, the variability in oil content and fatty acid composition for these two species is unclear. For these two species, 329 available accessions were acquired from the USDA germplasm collection. Their oil content and fatty acid composition were determined by nuclear magnetic resonance (NMR) and gas chromatography (GC), respectively. Using NMR and GC analyses, we found that Hibiscus seeds on average contained 18% oil and seed oil was composed of six major fatty acids (each >1%) and seven minor fatty acids (each Hibiscus cannabinus seeds contained significantly higher amounts of oil (18.14%), palmitic (20.75%), oleic (28.91%), vernolic acids (VA, 4.16%), and significantly lower amounts of stearic (3.96%), linoleic (39.49%), and dihydrosterculic acids (DHSA, 1.08%) than H. sabdariffa seeds (17.35%, 18.52%, 25.16%, 3.52%, 4.31%, 44.72%, and 1.57%, respectively). For edible oils, a higher oleic/linoleic (O/L) ratio and lower level of DHSA are preferred, and for industrial oils a high level of VA is preferred. Our results indicate that seeds from H. cannabinus may be of higher quality than H. sabdariffa seeds for these reasons. Significant variability in oil content and major fatty acids was also detected within both species. The variability in oil content and fatty acid composition revealed from this study will be useful for exploring seed utilization and developing new cultivars in these Hibiscus species.

  15. Soil-Related Input Parameters for the Biosphere Model

    International Nuclear Information System (INIS)

    Smith, A. J.

    2004-01-01

    This report presents one of the analyses that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN). The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the details of the conceptual model as well as the mathematical model and the required input parameters. The biosphere model is one of a series of process models supporting the postclosure Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A schematic representation of the documentation flow for the Biosphere input to TSPA is presented in Figure 1-1. This figure shows the evolutionary relationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan for Biosphere Modeling and Expert Support'' (TWP) (BSC 2004 [DIRS 169573]). This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this report. This report, ''Soil-Related Input Parameters for the Biosphere Model'', is one of the five analysis reports that develop input parameters for use in the ERMYN model. This report is the source documentation for the six biosphere parameters identified in Table 1-1. The purpose of this analysis was to develop the biosphere model parameters associated with the accumulation and depletion of radionuclides in the soil. These parameters support the calculation of radionuclide concentrations in soil from on-going irrigation or ash deposition and, as a direct consequence, radionuclide concentration in other environmental media that are affected by radionuclide concentrations in soil. The analysis was performed in accordance with the TWP (BSC 2004 [DIRS 169573]) where the governing procedure was defined as AP-SIII.9Q, ''Scientific Analyses''. This

  16. COMPETITION AND PRICING OF ESSENTIAL INPUTS: THE CASE OF ACCESS CHARGES FOR THE USE OF THE ITALIAN RAIL INFRASTRUCTURE

    Directory of Open Access Journals (Sweden)

    Ugo Arrigo

    2013-12-01

    Full Text Available This paper explores the access charge for the use of the Italian rail infrastructure. Access problems arise when the provision of a complete service to end users requires the combination of two or more inputs, one of which is non-competitive (OECD, 2004. It is a well-known fact that excessive access charges mean higher prices for rail passengers and rail freight companies when using the infrastructure. We conclude that the structure of the access charge has changed significantly with the recent introduction of the HS/HC (high-speed and high-capacity network; specifically, the fixed component has lost importance, whilst the variable component reaches 94%. The results of this paper provide evidence of the access charge for HS/HC being above 13 €/km.

  17. A statistical survey of heat input parameters into the cusp thermosphere

    Science.gov (United States)

    Moen, J. I.; Skjaeveland, A.; Carlson, H. C.

    2017-12-01

    Based on three winters of observational data, we present those ionosphere parameters deemed most critical to realistic space weather ionosphere and thermosphere representation and prediction, in regions impacted by variability in the cusp. The CHAMP spacecraft revealed large variability in cusp thermosphere densities, measuring frequent satellite drag enhancements, up to doublings. The community recognizes a clear need for more realistic representation of plasma flows and electron densities near the cusp. Existing average-value models produce order of magnitude errors in these parameters, resulting in large under estimations of predicted drag. We fill this knowledge gap with statistics-based specification of these key parameters over their range of observed values. The EISCAT Svalbard Radar (ESR) tracks plasma flow Vi , electron density Ne, and electron, ion temperatures Te, Ti , with consecutive 2-3 minute windshield-wipe scans of 1000x500 km areas. This allows mapping the maximum Ti of a large area within or near the cusp with high temporal resolution. In magnetic field-aligned mode the radar can measure high-resolution profiles of these plasma parameters. By deriving statistics for Ne and Ti , we enable derivation of thermosphere heating deposition under background and frictional-drag-dominated magnetic reconnection conditions. We separate our Ne and Ti profiles into quiescent and enhanced states, which are not closely correlated due to the spatial structure of the reconnection foot point. Use of our data-based parameter inputs can make order of magnitude corrections to input data driving thermosphere models, enabling removal of previous two fold drag errors.

  18. Mars 2.2 code manual: input requirements

    International Nuclear Information System (INIS)

    Chung, Bub Dong; Lee, Won Jae; Jeong, Jae Jun; Lee, Young Jin; Hwang, Moon Kyu; Kim, Kyung Doo; Lee, Seung Wook; Bae, Sung Won

    2003-07-01

    Korea Advanced Energy Research Institute (KAERI) conceived and started the development of MARS code with the main objective of producing a state-of-the-art realistic thermal hydraulic systems analysis code with multi-dimensional analysis capability. MARS achieves this objective by very tightly integrating the one dimensional RELAP5/MOD3 with the multi-dimensional COBRA-TF codes. The method of integration of the two codes is based on the dynamic link library techniques, and the system pressure equation matrices of both codes are implicitly integrated and solved simultaneously. In addition, the Equation-of-State (EOS) for the light water was unified by replacing the EOS of COBRA-TF by that of the RELAP5. This input manual provides a complete list of input required to run MARS. The manual is divided largely into two parts, namely, the one-dimensional part and the multi-dimensional part. The inputs for auxiliary parts such as minor edit requests and graph formatting inputs are shared by the two parts and as such mixed input is possible. The overall structure of the input is modeled on the structure of the RELAP5 and as such the layout of the manual is very similar to that of the RELAP. This similitude to RELAP5 input is intentional as this input scheme will allow minimum modification between the inputs of RELAP5 and MARS. MARS development team would like to express its appreciation to the RELAP5 Development Team and the USNRC for making this manual possible

  19. MARS code manual volume II: input requirements

    International Nuclear Information System (INIS)

    Chung, Bub Dong; Kim, Kyung Doo; Bae, Sung Won; Jeong, Jae Jun; Lee, Seung Wook; Hwang, Moon Kyu

    2010-02-01

    Korea Advanced Energy Research Institute (KAERI) conceived and started the development of MARS code with the main objective of producing a state-of-the-art realistic thermal hydraulic systems analysis code with multi-dimensional analysis capability. MARS achieves this objective by very tightly integrating the one dimensional RELAP5/MOD3 with the multi-dimensional COBRA-TF codes. The method of integration of the two codes is based on the dynamic link library techniques, and the system pressure equation matrices of both codes are implicitly integrated and solved simultaneously. In addition, the Equation-Of-State (EOS) for the light water was unified by replacing the EOS of COBRA-TF by that of the RELAP5. This input manual provides a complete list of input required to run MARS. The manual is divided largely into two parts, namely, the one-dimensional part and the multi-dimensional part. The inputs for auxiliary parts such as minor edit requests and graph formatting inputs are shared by the two parts and as such mixed input is possible. The overall structure of the input is modeled on the structure of the RELAP5 and as such the layout of the manual is very similar to that of the RELAP. This similitude to RELAP5 input is intentional as this input scheme will allow minimum modification between the inputs of RELAP5 and MARS3.1. MARS3.1 development team would like to express its appreciation to the RELAP5 Development Team and the USNRC for making this manual possible

  20. Robust input design for nonlinear dynamic modeling of AUV.

    Science.gov (United States)

    Nouri, Nowrouz Mohammad; Valadi, Mehrdad

    2017-09-01

    Input design has a dominant role in developing the dynamic model of autonomous underwater vehicles (AUVs) through system identification. Optimal input design is the process of generating informative inputs that can be used to generate the good quality dynamic model of AUVs. In a problem with optimal input design, the desired input signal depends on the unknown system which is intended to be identified. In this paper, the input design approach which is robust to uncertainties in model parameters is used. The Bayesian robust design strategy is applied to design input signals for dynamic modeling of AUVs. The employed approach can design multiple inputs and apply constraints on an AUV system's inputs and outputs. Particle swarm optimization (PSO) is employed to solve the constraint robust optimization problem. The presented algorithm is used for designing the input signals for an AUV, and the estimate obtained by robust input design is compared with that of the optimal input design. According to the results, proposed input design can satisfy both robustness of constraints and optimality. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  1. Improved Stabilization Conditions for Nonlinear Systems with Input and State Delays via T-S Fuzzy Model

    Directory of Open Access Journals (Sweden)

    Chang Che

    2018-01-01

    Full Text Available This paper focuses on the problem of nonlinear systems with input and state delays. The considered nonlinear systems are represented by Takagi-Sugeno (T-S fuzzy model. A new state feedback control approach is introduced for T-S fuzzy systems with input delay and state delays. A new Lyapunov-Krasovskii functional is employed to derive less conservative stability conditions by incorporating a recently developed Wirtinger-based integral inequality. Based on the Lyapunov stability criterion, a series of linear matrix inequalities (LMIs are obtained by using the slack variables and integral inequality, which guarantees the asymptotic stability of the closed-loop system. Several numerical examples are given to show the advantages of the proposed results.

  2. Factors that contribute to physician variability in decisions to limit life support in the ICU: a qualitative study.

    Science.gov (United States)

    Wilson, Michael E; Rhudy, Lori M; Ballinger, Beth A; Tescher, Ann N; Pickering, Brian W; Gajic, Ognjen

    2013-06-01

    Our aim was to explore reasons for physician variability in decisions to limit life support in the intensive care unit (ICU) utilizing qualitative methodology. Single center study consisting of semi-structured interviews with experienced physicians and nurses. Seventeen intensivists from medical (n = 7), surgical (n = 5), and anesthesia (n = 5) critical care backgrounds, and ten nurses from medical (n = 5) and surgical (n = 5) ICU backgrounds were interviewed. Principles of grounded theory were used to analyze the interview transcripts. Eleven factors within four categories were identified that influenced physician variability in decisions to limit life support: (1) physician work environment-workload and competing priorities, shift changes and handoffs, and incorporation of nursing input; (2) physician experiences-of unexpected patient survival, and of limiting life support in physician's family; (3) physician attitudes-investment in a good surgical outcome, specialty perspective, values and beliefs; and (4) physician relationship with patient and family-hearing the patient's wishes firsthand, engagement in family communication, and family negotiation. We identified several factors which physicians and nurses perceived were important sources of physician variability in decisions to limit life support. Ways to raise awareness and ameliorate the potentially adverse effects of factors such as workload, competing priorities, shift changes, and handoffs should be explored. Exposing intensivists to long term patient outcomes, formalizing nursing input, providing additional training, and emphasizing firsthand knowledge of patient wishes may improve decision making.

  3. Phase-based vascular input function: Improved quantitative DCE-MRI of atherosclerotic plaques

    NARCIS (Netherlands)

    van Hoof, R. H. M.; Hermeling, E.; Truijman, M. T. B.; van Oostenbrugge, R. J.; Daemen, J. W. H.; van der Geest, R. J.; van Orshoven, N. P.; Schreuder, A. H.; Backes, W. H.; Daemen, M. J. A. P.; Wildberger, J. E.; Kooi, M. E.

    2015-01-01

    Purpose: Quantitative pharmacokinetic modeling of dynamic contrast-enhanced (DCE)-MRI can be used to assess atherosclerotic plaque microvasculature, which is an important marker of plaque vulnerability. Purpose of the present study was (1) to compare magnitude-versus phase-based vascular input

  4. Spatial variability of methane production and methanogen communities within a eutrophic reservoir: evaluating the importance of organic matter source and quantity

    Science.gov (United States)

    Freshwater reservoirs are an important source of the greenhouse gas methane (CH4) to the atmosphere, but there is a wide range of estimates of global emissions, due in part to variability of methane emissions rates within reservoirs. While morphological characteristics, including...

  5. Analysis of North Sea Offshore Wind Power Variability

    NARCIS (Netherlands)

    Buatois, A.; Gibescu, M.; Rawn, B.G.; Van der Meijden, M.A.M.M.

    2014-01-01

    This paper evaluates, for a 2030 scenario, the impact on onshore power systems in terms of the variability of the power generated by 81 GW of offshore wind farms installed in the North Sea. Meso-scale reanalysis data are used as input for computing the hourly power production for offshore wind

  6. Convergent responses of nitrogen and phosphorus resorption to nitrogen inputs in a semiarid grassland

    Science.gov (United States)

    Lü, Xiao-Tao; Reed, Sasha; Yu, Qiang; He, Nian-Peng; Wang, Zheng-Wen; Han, Xing-Guo

    2013-01-01

    Human activities have significantly altered nitrogen (N) availability in most terrestrial ecosystems, with consequences for community composition and ecosystem functioning. Although studies of how changes in N availability affect biodiversity and community composition are relatively common, much less remains known about the effects of N inputs on the coupled biogeochemical cycling of N and phosphorus (P), and still fewer data exist regarding how increased N inputs affect the internal cycling of these two elements in plants. Nutrient resorption is an important driver of plant nutrient economies and of the quality of litter plants produce. Accordingly, resorption patterns have marked ecological implications for plant population and community fitness, as well as for ecosystem nutrient cycling. In a semiarid grassland in northern China, we studied the effects of a wide range of N inputs on foliar nutrient resorption of two dominant grasses, Leymus chinensis and Stipa grandis. After 4 years of treatments, N and P availability in soil and N and P concentrations in green and senesced grass leaves increased with increasing rates of N addition. Foliar N and P resorption significantly decreased along the N addition gradient, implying a resorption-mediated, positive plant–soil feedback induced by N inputs. Furthermore, N : P resorption ratios were negatively correlated with the rates of N addition, indicating the sensitivity of plant N and P stoichiometry to N inputs. Taken together, the results demonstrate that N additions accelerate ecosystem uptake and turnover of both N and P in the temperate steppe and that N and P cycles are coupled in dynamic ways. The convergence of N and P resorption in response to N inputs emphasizes the importance of nutrient resorption as a pathway by which plants and ecosystems adjust in the face of increasing N availability.

  7. Six axis force feedback input device

    Science.gov (United States)

    Ohm, Timothy (Inventor)

    1998-01-01

    The present invention is a low friction, low inertia, six-axis force feedback input device comprising an arm with double-jointed, tendon-driven revolute joints, a decoupled tendon-driven wrist, and a base with encoders and motors. The input device functions as a master robot manipulator of a microsurgical teleoperated robot system including a slave robot manipulator coupled to an amplifier chassis, which is coupled to a control chassis, which is coupled to a workstation with a graphical user interface. The amplifier chassis is coupled to the motors of the master robot manipulator and the control chassis is coupled to the encoders of the master robot manipulator. A force feedback can be applied to the input device and can be generated from the slave robot to enable a user to operate the slave robot via the input device without physically viewing the slave robot. Also, the force feedback can be generated from the workstation to represent fictitious forces to constrain the input device's control of the slave robot to be within imaginary predetermined boundaries.

  8. College Oral English teaching from the perspective of input and output theory

    Directory of Open Access Journals (Sweden)

    Xiangxiang Yuan

    2017-11-01

    Full Text Available With the development of society and the deepening of economic globalization, the communicative competence of spoken English has become an important indicator of the talent. Therefore, how to improve college students’ oral English proficiency has become the focus of college English teaching. The phenomenon of “heavy input and light output” in college English teaching in China for a long period of time has led to the emergence of “dumb English, low efficiency”. Aiming at these problems, this paper discusses the functions of input and output and their relationship, and puts forward some views on oral English teaching.

  9. Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations.

    Science.gov (United States)

    Hoffmann, Holger; Zhao, Gang; Asseng, Senthold; Bindi, Marco; Biernath, Christian; Constantin, Julie; Coucheney, Elsa; Dechow, Rene; Doro, Luca; Eckersten, Henrik; Gaiser, Thomas; Grosz, Balázs; Heinlein, Florian; Kassie, Belay T; Kersebaum, Kurt-Christian; Klein, Christian; Kuhnert, Matthias; Lewan, Elisabet; Moriondo, Marco; Nendel, Claas; Priesack, Eckart; Raynal, Helene; Roggero, Pier P; Rötter, Reimund P; Siebert, Stefan; Specka, Xenia; Tao, Fulu; Teixeira, Edmar; Trombi, Giacomo; Wallach, Daniel; Weihermüller, Lutz; Yeluripati, Jagadeesh; Ewert, Frank

    2016-01-01

    We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations.

  10. Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations.

    Directory of Open Access Journals (Sweden)

    Holger Hoffmann

    Full Text Available We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations.

  11. An AUC-based permutation variable importance measure for random forests.

    Science.gov (United States)

    Janitza, Silke; Strobl, Carolin; Boulesteix, Anne-Laure

    2013-04-05

    The random forest (RF) method is a commonly used tool for classification with high dimensional data as well as for ranking candidate predictors based on the so-called random forest variable importance measures (VIMs). However the classification performance of RF is known to be suboptimal in case of strongly unbalanced data, i.e. data where response class sizes differ considerably. Suggestions were made to obtain better classification performance based either on sampling procedures or on cost sensitivity analyses. However to our knowledge the performance of the VIMs has not yet been examined in the case of unbalanced response classes. In this paper we explore the performance of the permutation VIM for unbalanced data settings and introduce an alternative permutation VIM based on the area under the curve (AUC) that is expected to be more robust towards class imbalance. We investigated the performance of the standard permutation VIM and of our novel AUC-based permutation VIM for different class imbalance levels using simulated data and real data. The results suggest that the new AUC-based permutation VIM outperforms the standard permutation VIM for unbalanced data settings while both permutation VIMs have equal performance for balanced data settings. The standard permutation VIM loses its ability to discriminate between associated predictors and predictors not associated with the response for increasing class imbalance. It is outperformed by our new AUC-based permutation VIM for unbalanced data settings, while the performance of both VIMs is very similar in the case of balanced classes. The new AUC-based VIM is implemented in the R package party for the unbiased RF variant based on conditional inference trees. The codes implementing our study are available from the companion website: http://www.ibe.med.uni-muenchen.de/organisation/mitarbeiter/070_drittmittel/janitza/index.html.

  12. Selection of components based on their importance

    International Nuclear Information System (INIS)

    Stvan, F.

    2004-12-01

    A proposal is presented for sorting components of the Dukovany nuclear power plant with respect to their importance. The classification scheme includes property priority, property criticality and property structure. Each area has its criteria with weight coefficients to calculate the importance of each component by the Risk Priority Number method. The aim of the process is to generate a list of components in order of operating and safety importance, which will help spend funds to ensure operation and safety in an optimal manner. This proposal is linked to a proposal for a simple database which should serve to enter information and perform assessments. The present stage focused on a safety assessment of components categorized in safety classes BT1, BT2 and BT3 pursuant to Decree No. 76. Assessment was performed based ona PSE study for Level 1. The database includes inputs for entering financial data, which are represented by a potential damage resulting from the given failure and by the loss of MWh in financial terms. In a next input, the failure incidence intensity and time of correction can be entered. Information regarding the property structure, represented by the degree of backup and reparability of the component, is the last input available

  13. Variability in Adaptive Behavior in Autism: Evidence for the Importance of Family History

    Science.gov (United States)

    Mazefsky, Carla A.; Williams, Diane L.; Minshew, Nancy J.

    2008-01-01

    Adaptive behavior in autism is highly variable and strongly related to prognosis. This study explored family history as a potential source of variability in adaptive behavior in autism. Participants included 77 individuals (mean age = 18) with average or better intellectual ability and autism. Parents completed the Family History Interview about…

  14. Influence of deleting some of the inputs and outputs on efficiency status of units in DEA

    Directory of Open Access Journals (Sweden)

    Abbas ali Noora

    2013-06-01

    Full Text Available One of the important issues in data envelopment analysis (DEA is sensitivity analysis. This study discusses about deleting some of the inputs and outputs and investigates the influence of it on efficiency status of Decision Making Units (DMUs. To this end some models are presented for recognizing this influence on efficient DMUs. Model 2 (Model 3 in section 3 investigates the influence of deleting i(th input (r(th output on an efficient DMU. Thereafter these models are improved for deleting multiple inputs and outputs. Furthermore, a model is presented for recognizing the maximum number of inputs and (or outputs from among specified inputs and outputs which can be deleted, whereas an efficient DMU preserves its efficiency. Finally, the presented models are utilized for a set of DMUs and the results are reported.

  15. Internal versus external controls on age variability: Definitions, origins and implications in a changing climate

    Science.gov (United States)

    Harman, C. J.

    2015-12-01

    The unsteadiness of stream water age is now well established, but the controls on the age dynamics, and the adequate representation and prediction of those dynamics, are not. A basic distinction can be made between internal variability that arises from changes in the proportions of flow moving through the diverse flow pathways of a hydrologic system, and external variability that arises from the stochasticity of inputs and outputs (such as precipitation and streamflow). In this talk I will show how these two types of age variability can be formally defined and distinguished within the framework of rank StorAge Selection (rSAS) functions. Internal variability implies variations in time in the rSAS function, while external variability does not. This leads naturally to the definition of several modes of internal variability, reflecting generic ways that system flowpaths may be rearranged. This rearrangement may be induced by fluctuations in the system state (such as catchment wetness), or by longer-term changes in catchment structure (such as land use change). One type of change, the 'inverse storage effect' is characterized by an increase in the release of young water from the system in response to an increase in overall system storage. This effect can be seen in many hydrologic settings, and has important implications for the effect of altered hydroclimatic conditions on solute transport through a landscape. External variability, such as increased precipitation, can induce a decrease in mean transit time (and vice versa), but this effect is greatly enhanced if accompanied by an internal shift in flow pathways that increases the relative importance of younger water. These effects will be illustrated using data from field and experimental studies.

  16. High-frequency matrix converter with square wave input

    Science.gov (United States)

    Carr, Joseph Alexander; Balda, Juan Carlos

    2015-03-31

    A device for producing an alternating current output voltage from a high-frequency, square-wave input voltage comprising, high-frequency, square-wave input a matrix converter and a control system. The matrix converter comprises a plurality of electrical switches. The high-frequency input and the matrix converter are electrically connected to each other. The control system is connected to each switch of the matrix converter. The control system is electrically connected to the input of the matrix converter. The control system is configured to operate each electrical switch of the matrix converter converting a high-frequency, square-wave input voltage across the first input port of the matrix converter and the second input port of the matrix converter to an alternating current output voltage at the output of the matrix converter.

  17. Conceptual study of calibration software for large scale input accountancy tank

    International Nuclear Information System (INIS)

    Uchikoshi, Seiji; Yasu, Kan-ichi; Watanabe, Yuichi; Matsuda, Yuji; Kawai, Akio; Tamura, Toshiyuki; Shimizu, Hidehiko.

    1996-01-01

    Demonstration experiments for large scale input accountancy tank are going to be under way by Nuclear Material Control Center. Development of calibration software for accountancy system with dip-tube manometer is an important task in the experiments. A conceptual study of the software has been carried out to construct high precision accountancy system. And, the study was based on ANSI N15.19-1989. Items of the study are overall configuration, correction method for influence of bubble formation, function model of calibration, and fitting method for calibration curve. Following remarks are the results of this study. 1) Overall configuration of the software was constructed. 2) It was shown by numerical solution, that the influence of bubble formation can be corrected using period of pressure wave. 3) Two function models of calibration for well capacity and for inner structure volume were prepared from tank design, and good fitness of the model for net capacity (balance of both models) was confirmed by fitting to designed shape of the tank. 4) The necessity of further consideration about both-variables-in-error-model and cumulative-error-model was recognized. We are going to develop a practical software on the basis of the results, and to verify it by the demonstration experiments. (author)

  18. Sensitivity of a complex urban air quality model to input data

    International Nuclear Information System (INIS)

    Seigneur, C.; Tesche, T.W.; Roth, P.M.; Reid, L.E.

    1981-01-01

    In recent years, urban-scale photochemical simulation models have been developed that are of practical value for predicting air quality and analyzing the impacts of alternative emission control strategies. Although the performance of some urban-scale models appears to be acceptable, the demanding data requirements of such models have prompted concern about the costs of data acquistion, which might be high enough to preclude use of photochemical models for many urban areas. To explore this issue, sensitivity studies with the Systems Applications, Inc. (SAI) Airshed Model, a grid-based time-dependent photochemical dispersion model, have been carried out for the Los Angeles basin. Reductions in the amount and quality of meteorological, air quality and emission data, as well as modifications of the model gridded structure, have been analyzed. This paper presents and interprets the results of 22 sensitivity studies. A sensitivity-uncertainty index is defined to rank input data needs for an urban photochemical model. The index takes into account the sensitivity of model predictions to the amount of input data, the costs of data acquistion, and the uncertainties in the air quality model input variables. The results of these sensitivity studies are considered in light of the limitations of specific attributes of the Los Angeles basin and of the modeling conditions (e.g., choice of wind model, length of simulation time). The extent to which the results may be applied to other urban areas also is discussed

  19. High-T /SUB c/ Superconducting integrated circuit: a dc SQUID with input coil

    International Nuclear Information System (INIS)

    Di Iorio, M.S.; Beasley, M.R.

    1985-01-01

    We have fabricated a high transition temperature superconducting integrated circuit consisting of a dc SQUID and an input coupling coil. The purpose is to ascertain the generic problems associated with constructing a high-T /SUB c/ circuit as well as to fabricate a high performance dc SQUID. The superconductor used for both the SQUID and the input coil is Nb 3 Sn which must be deposited at 800 0 C. Importantly, the insulator separating SQUID and input coil maintains its integrity at this elevated temperature. A hole in the insulator permits contact to the innermost winding of the coil. This contact has been achieved without significant degradation of the superconductivity. Consequently, the device operates over a wide temperature range, from below 4.2 K to near T /SUB c/

  20. Optimizing microwave photodetection: input-output theory

    Science.gov (United States)

    Schöndorf, M.; Govia, L. C. G.; Vavilov, M. G.; McDermott, R.; Wilhelm, F. K.

    2018-04-01

    High fidelity microwave photon counting is an important tool for various areas from background radiation analysis in astronomy to the implementation of circuit quantum electrodynamic architectures for the realization of a scalable quantum information processor. In this work we describe a microwave photon counter coupled to a semi-infinite transmission line. We employ input-output theory to examine a continuously driven transmission line as well as traveling photon wave packets. Using analytic and numerical methods, we calculate the conditions on the system parameters necessary to optimize measurement and achieve high detection efficiency. With this we can derive a general matching condition depending on the different system rates, under which the measurement process is optimal.

  1. Flexible input, dazzling output with IBM i

    CERN Document Server

    Victória-Pereira, Rafael

    2014-01-01

    Link your IBM i system to the modern business server world! This book presents easier and more flexible ways to get data into your IBM i system, along with rather surprising methods to export and present the vital business data it contains. You'll learn how to automate file transfers, seamlessly connect PC applications with your RPG programs, and much more. Input operations will become more flexible and user-proof, with self-correcting import processes and direct file transfers that require a minimum of user intervention. Also learn novel ways to present information: your DB2 data will look gr

  2. A non-linear dimension reduction methodology for generating data-driven stochastic input models

    Science.gov (United States)

    Ganapathysubramanian, Baskar; Zabaras, Nicholas

    2008-06-01

    Stochastic analysis of random heterogeneous media (polycrystalline materials, porous media, functionally graded materials) provides information of significance only if realistic input models of the topology and property variations are used. This paper proposes a framework to construct such input stochastic models for the topology and thermal diffusivity variations in heterogeneous media using a data-driven strategy. Given a set of microstructure realizations (input samples) generated from given statistical information about the medium topology, the framework constructs a reduced-order stochastic representation of the thermal diffusivity. This problem of constructing a low-dimensional stochastic representation of property variations is analogous to the problem of manifold learning and parametric fitting of hyper-surfaces encountered in image processing and psychology. Denote by M the set of microstructures that satisfy the given experimental statistics. A non-linear dimension reduction strategy is utilized to map M to a low-dimensional region, A. We first show that M is a compact manifold embedded in a high-dimensional input space Rn. An isometric mapping F from M to a low-dimensional, compact, connected set A⊂Rd(d≪n) is constructed. Given only a finite set of samples of the data, the methodology uses arguments from graph theory and differential geometry to construct the isometric transformation F:M→A. Asymptotic convergence of the representation of M by A is shown. This mapping F serves as an accurate, low-dimensional, data-driven representation of the property variations. The reduced-order model of the material topology and thermal diffusivity variations is subsequently used as an input in the solution of stochastic partial differential equations that describe the evolution of dependant variables. A sparse grid collocation strategy (Smolyak algorithm) is utilized to solve these stochastic equations efficiently. We showcase the methodology by constructing low

  3. A non-linear dimension reduction methodology for generating data-driven stochastic input models

    International Nuclear Information System (INIS)

    Ganapathysubramanian, Baskar; Zabaras, Nicholas

    2008-01-01

    Stochastic analysis of random heterogeneous media (polycrystalline materials, porous media, functionally graded materials) provides information of significance only if realistic input models of the topology and property variations are used. This paper proposes a framework to construct such input stochastic models for the topology and thermal diffusivity variations in heterogeneous media using a data-driven strategy. Given a set of microstructure realizations (input samples) generated from given statistical information about the medium topology, the framework constructs a reduced-order stochastic representation of the thermal diffusivity. This problem of constructing a low-dimensional stochastic representation of property variations is analogous to the problem of manifold learning and parametric fitting of hyper-surfaces encountered in image processing and psychology. Denote by M the set of microstructures that satisfy the given experimental statistics. A non-linear dimension reduction strategy is utilized to map M to a low-dimensional region, A. We first show that M is a compact manifold embedded in a high-dimensional input space R n . An isometric mapping F from M to a low-dimensional, compact, connected set A is contained in R d (d<< n) is constructed. Given only a finite set of samples of the data, the methodology uses arguments from graph theory and differential geometry to construct the isometric transformation F:M→A. Asymptotic convergence of the representation of M by A is shown. This mapping F serves as an accurate, low-dimensional, data-driven representation of the property variations. The reduced-order model of the material topology and thermal diffusivity variations is subsequently used as an input in the solution of stochastic partial differential equations that describe the evolution of dependant variables. A sparse grid collocation strategy (Smolyak algorithm) is utilized to solve these stochastic equations efficiently. We showcase the methodology

  4. Contextuality in canonical systems of random variables

    Science.gov (United States)

    Dzhafarov, Ehtibar N.; Cervantes, Víctor H.; Kujala, Janne V.

    2017-10-01

    Random variables representing measurements, broadly understood to include any responses to any inputs, form a system in which each of them is uniquely identified by its content (that which it measures) and its context (the conditions under which it is recorded). Two random variables are jointly distributed if and only if they share a context. In a canonical representation of a system, all random variables are binary, and every content-sharing pair of random variables has a unique maximal coupling (the joint distribution imposed on them so that they coincide with maximal possible probability). The system is contextual if these maximal couplings are incompatible with the joint distributions of the context-sharing random variables. We propose to represent any system of measurements in a canonical form and to consider the system contextual if and only if its canonical representation is contextual. As an illustration, we establish a criterion for contextuality of the canonical system consisting of all dichotomizations of a single pair of content-sharing categorical random variables. This article is part of the themed issue `Second quantum revolution: foundational questions'.

  5. Textual Enhancement of Input: Issues and Possibilities

    Science.gov (United States)

    Han, ZhaoHong; Park, Eun Sung; Combs, Charles

    2008-01-01

    The input enhancement hypothesis proposed by Sharwood Smith (1991, 1993) has stimulated considerable research over the last 15 years. This article reviews the research on textual enhancement of input (TE), an area where the majority of input enhancement studies have aggregated. Methodological idiosyncrasies are the norm of this body of research.…

  6. Impact of operational factors on fossil energy inputs in motor-manual tree felling and processing: results of two case studies

    Directory of Open Access Journals (Sweden)

    Gheorghe Ignea

    2017-07-01

    Full Text Available In many cases tree felling and processing operations are carried out motor-manually and knowledge about fossil fuel consumption and direct energy inputs when using such equipment is required for different purposes starting with operational costing and ending with environmental assessment of forest operations. In this study, fuel mixture, chain oil and direct fossil energy inputs were evaluated for two chainsaws which were used to fell and process trees in two silvicultural systems. The results of this study suggest that there is a strong dependence relation between selected tree size variables such as the diameter at breast height and tree volume on one hand and the fuel mixture, chain oil and direct fossil energy inputs when felling and processing broadleaved hardwood and resinous softwood trees on the other hand. For the broadleaved trees (mean tree volume of 1.50 m3 × tree-1, DBH of 45.5 cm and tree height of 21.84 m the mean direct fossil energy input was of 3.86 MJ m-3 while for resinous trees (mean tree volume of 1.77 m3 tree-1, DBH of 39.28 cm and tree height of 32.49 m it was of 3.93 MJ m-3. Other variables, including but not limited to the technology used, work experience and procedural pattern, may influence the mentioned figures and extensive studies are required to clarify their effects.

  7. Data input guide for SWIFT II. The Sandia waste-isolation flow and transport model for fractured media, Release 4.84

    International Nuclear Information System (INIS)

    Reeves, M.; Ward, D.S.; Johns, N.D.; Cranwell, R.M.

    1986-04-01

    This report is one of three which describes the SWIFT II computer code. The code simulates flow and transport processes in geologic media which may be fractured. SWIFT II was developed for use in the analysis of deep geologic facilities for nuclear-waste disposal. This user's manual should permit the analyst to use the code effectively by facilitating the preparation of input data. A second companion document discusses the theory and implementation of the models employed by the SWIFT II code. A third document provides illustrative problems for instructional purposes. This report contains detailed descriptions of the input data along with an appendix of the input diagnostics. The use of auxiliary files, unit conversions, and program variable descriptors also are included in this document

  8. Residents' numeric inputting error in computerized physician order entry prescription.

    Science.gov (United States)

    Wu, Xue; Wu, Changxu; Zhang, Kan; Wei, Dong

    2016-04-01

    Computerized physician order entry (CPOE) system with embedded clinical decision support (CDS) can significantly reduce certain types of prescription error. However, prescription errors still occur. Various factors such as the numeric inputting methods in human computer interaction (HCI) produce different error rates and types, but has received relatively little attention. This study aimed to examine the effects of numeric inputting methods and urgency levels on numeric inputting errors of prescription, as well as categorize the types of errors. Thirty residents participated in four prescribing tasks in which two factors were manipulated: numeric inputting methods (numeric row in the main keyboard vs. numeric keypad) and urgency levels (urgent situation vs. non-urgent situation). Multiple aspects of participants' prescribing behavior were measured in sober prescribing situations. The results revealed that in urgent situations, participants were prone to make mistakes when using the numeric row in the main keyboard. With control of performance in the sober prescribing situation, the effects of the input methods disappeared, and urgency was found to play a significant role in the generalized linear model. Most errors were either omission or substitution types, but the proportion of transposition and intrusion error types were significantly higher than that of the previous research. Among numbers 3, 8, and 9, which were the less common digits used in prescription, the error rate was higher, which was a great risk to patient safety. Urgency played a more important role in CPOE numeric typing error-making than typing skills and typing habits. It was recommended that inputting with the numeric keypad had lower error rates in urgent situation. An alternative design could consider increasing the sensitivity of the keys with lower frequency of occurrence and decimals. To improve the usability of CPOE, numeric keyboard design and error detection could benefit from spatial

  9. Fast metabolite identification with Input Output Kernel Regression

    Science.gov (United States)

    Brouard, Céline; Shen, Huibin; Dührkop, Kai; d'Alché-Buc, Florence; Böcker, Sebastian; Rousu, Juho

    2016-01-01

    Motivation: An important problematic of metabolomics is to identify metabolites using tandem mass spectrometry data. Machine learning methods have been proposed recently to solve this problem by predicting molecular fingerprint vectors and matching these fingerprints against existing molecular structure databases. In this work we propose to address the metabolite identification problem using a structured output prediction approach. This type of approach is not limited to vector output space and can handle structured output space such as the molecule space. Results: We use the Input Output Kernel Regression method to learn the mapping between tandem mass spectra and molecular structures. The principle of this method is to encode the similarities in the input (spectra) space and the similarities in the output (molecule) space using two kernel functions. This method approximates the spectra-molecule mapping in two phases. The first phase corresponds to a regression problem from the input space to the feature space associated to the output kernel. The second phase is a preimage problem, consisting in mapping back the predicted output feature vectors to the molecule space. We show that our approach achieves state-of-the-art accuracy in metabolite identification. Moreover, our method has the advantage of decreasing the running times for the training step and the test step by several orders of magnitude over the preceding methods. Availability and implementation: Contact: celine.brouard@aalto.fi Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307628

  10. Effect of plasma arc welding variables on fusion zone grain size and hardness of AISI 321 austenitic stainless steel

    Science.gov (United States)

    Kondapalli, S. P.

    2017-12-01

    In the present work, pulsed current microplasma arc welding is carried out on AISI 321 austenitic stainless steel of 0.3 mm thickness. Peak current, Base current, Pulse rate and Pulse width are chosen as the input variables, whereas grain size and hardness are considered as output responses. Response surface method is adopted by using Box-Behnken Design, and in total 27 experiments are performed. Empirical relation between input and output response is developed using statistical software and analysis of variance (ANOVA) at 95% confidence level to check the adequacy. The main effect and interaction effect of input variables on output response are also studied.

  11. Posterior Inferotemporal Cortex Cells Use Multiple Input Pathways for Shape Encoding.

    Science.gov (United States)

    Ponce, Carlos R; Lomber, Stephen G; Livingstone, Margaret S

    2017-05-10

    In the macaque monkey brain, posterior inferior temporal (PIT) cortex cells contribute to visual object recognition. They receive concurrent inputs from visual areas V4, V3, and V2. We asked how these different anatomical pathways shape PIT response properties by deactivating them while monitoring PIT activity in two male macaques. We found that cooling of V4 or V2|3 did not lead to consistent changes in population excitatory drive; however, population pattern analyses showed that V4-based pathways were more important than V2|3-based pathways. We did not find any image features that predicted decoding accuracy differences between both interventions. Using the HMAX hierarchical model of visual recognition, we found that different groups of simulated "PIT" units with different input histories (lacking "V2|3" or "V4" input) allowed for comparable levels of object-decoding performance and that removing a large fraction of "PIT" activity resulted in similar drops in performance as in the cooling experiments. We conclude that distinct input pathways to PIT relay similar types of shape information, with V1-dependent V4 cells providing more quantitatively useful information for overall encoding than cells in V2 projecting directly to PIT. SIGNIFICANCE STATEMENT Convolutional neural networks are the best models of the visual system, but most emphasize input transformations across a serial hierarchy akin to the primary "ventral stream" (V1 → V2 → V4 → IT). However, the ventral stream also comprises parallel "bypass" pathways: V1 also connects to V4, and V2 to IT. To explore the advantages of mixing long and short pathways in the macaque brain, we used cortical cooling to silence inputs to posterior IT and compared the findings with an HMAX model with parallel pathways. Copyright © 2017 the authors 0270-6474/17/375019-16$15.00/0.

  12. HOW NORMAL IS VARIABLE, OR HOW VARIABLE IS NORMAL

    NARCIS (Netherlands)

    TOUWEN, BCL

    Variability is an important property of the central nervous system, and it shows characteristic changes during infancy and childhood. The large amount of variations in the performance of sensomotor functions in infancy is called indiscriminate or primary variability. During toddling age the child

  13. GESAMP Working Group 38, The Atmospheric Input of Chemicals to the Ocean

    Science.gov (United States)

    Duce, Robert; Liss, Peter

    2014-05-01

    There is growing recognition of the impact of the atmospheric input of both natural and anthropogenic substances on ocean chemistry, biology, and biogeochemistry as well as climate. These inputs are closely related to a number of important global change issues. For example, the increasing input of anthropogenic nitrogen species from the atmosphere to much of the ocean may cause a low level fertilization that could result in an increase in marine 'new' productivity of up to ~3% and thus impact carbon drawdown from the atmosphere. Similarly, much of the oceanic iron, which is a limiting nutrient in significant areas of the ocean, originates from the atmospheric input of minerals as a result of the long-range transport of mineral dust from continental regions. The increased supply of soluble phosphorus from atmospheric anthropogenic sources (through large-scale use of fertilizers) may also have a significant impact on surface-ocean biogeochemistry, but estimates of any effects are highly uncertain. There have been few assessments of the atmospheric inputs of sulfur and nitrogen oxides to the ocean and their impact on the rates of ocean acidification. These inputs may be particularly critical in heavily trafficked shipping lanes and in ocean regions proximate to highly industrialized land areas. Other atmospheric substances may also have an impact on the ocean, in particular lead, cadmium, and POPs. To address these and related issues the United Nations Group of Experts on the Scientific Aspects of Marine Environmental Protection (GESAMP) initiated Working Group 38, The Atmospheric Input of Chemicals to the Ocean, in 2008. This Working Group has had four meetings. To date four peer reviewed papers have been produced from this effort, with a least eight others in the process of being written or published. This paper will discuss some of the results of the Working Group's deliberations and its plans for possible future work.

  14. Variable Delay Element For Jitter Control In High Speed Data Links

    Science.gov (United States)

    Livolsi, Robert R.

    2002-06-11

    A circuit and method for decreasing the amount of jitter present at the receiver input of high speed data links which uses a driver circuit for input from a high speed data link which comprises a logic circuit having a first section (1) which provides data latches, a second section (2) which provides a circuit generates a pre-destorted output and for compensating for level dependent jitter having an OR function element and a NOR function element each of which is coupled to two inputs and to a variable delay element as an input which provides a bi-modal delay for pulse width pre-distortion, a third section (3) which provides a muxing circuit, and a forth section (4) for clock distribution in the driver circuit. A fifth section is used for logic testing the driver circuit.

  15. Effect of input compression and input frequency response on music perception in cochlear implant users.

    Science.gov (United States)

    Halliwell, Emily R; Jones, Linor L; Fraser, Matthew; Lockley, Morag; Hill-Feltham, Penelope; McKay, Colette M

    2015-06-01

    A study was conducted to determine whether modifications to input compression and input frequency response characteristics can improve music-listening satisfaction in cochlear implant users. Experiment 1 compared three pre-processed versions of music and speech stimuli in a laboratory setting: original, compressed, and flattened frequency response. Music excerpts comprised three music genres (classical, country, and jazz), and a running speech excerpt was compared. Experiment 2 implemented a flattened input frequency response in the speech processor program. In a take-home trial, participants compared unaltered and flattened frequency responses. Ten and twelve adult Nucleus Freedom cochlear implant users participated in Experiments 1 and 2, respectively. Experiment 1 revealed a significant preference for music stimuli with a flattened frequency response compared to both original and compressed stimuli, whereas there was a significant preference for the original (rising) frequency response for speech stimuli. Experiment 2 revealed no significant mean preference for the flattened frequency response, with 9 of 11 subjects preferring the rising frequency response. Input compression did not alter music enjoyment. Comparison of the two experiments indicated that individual frequency response preferences may depend on the genre or familiarity, and particularly whether the music contained lyrics.

  16. Ecological niche models reveal the importance of climate variability for the biogeography of protosteloid amoebae.

    Science.gov (United States)

    Aguilar, María; Lado, Carlos

    2012-08-01

    Habitat availability and environmental preferences of species are among the most important factors in determining the success of dispersal processes and therefore in shaping the distribution of protists. We explored the differences in fundamental niches and potential distributions of an ecological guild of slime moulds-protosteloid amoebae-in the Iberian Peninsula. A large set of samples collected in a north-east to south-west transect of approximately 1000 km along the peninsula was used to test the hypothesis that, together with the existence of suitable microhabitats, climate conditions may determine the probability of survival of species. Although protosteloid amoebae share similar morphologies and life history strategies, canonical correspondence analyses showed that they have varied ecological optima, and that climate conditions have an important effect in niche differentiation. Maxent environmental niche models provided consistent predictions of the probability of presence of the species based on climate data, and they were used to generate maps of potential distribution in an 'everything is everywhere' scenario. The most important climatic factors were, in both analyses, variables that measure changes in conditions throughout the year, confirming that the alternation of fruiting bodies, cysts and amoeboid stages in the life cycles of protosteloid amoebae constitutes an advantage for surviving in a changing environment. Microhabitat affinity seems to be influenced by climatic conditions, which suggests that the micro-environment may vary at a local scale and change together with the external climate at a larger scale.

  17. The Relative Importance of Spatial and Local Environmental Factors in Determining Beetle Assemblages in the Inner Mongolia Grassland.

    Directory of Open Access Journals (Sweden)

    Xiao-Dong Yu

    Full Text Available The aim of this paper is to increase understanding of the relative importance of the input of geographic and local environmental factors on richness and composition of epigaeic steppe beetles (Coleoptera: Carabidae and Tenebrionidae along a geographic (longitudinal/precipitation gradient in the Inner Mongolia grassland. Specifically, we evaluate the associations of environmental variables representing climate and environmental heterogeneity with beetle assemblages. Beetles were sampled using pitfall traps at 25 sites scattered across the full geographic extent of the study biome in 2011-2012. We used variance partitioning techniques and multi-model selection based on the Akaike information criterion to assess the relative importance of the spatial and environmental variables on beetle assemblages. Species richness and abundance showed unimodal patterns along the geographic gradient. Together with space, climate variables associated with precipitation, water-energy balance and harshness of climate had strong explanatory power in richness pattern. Abundance pattern showed strongest association with variation in temperature and environmental heterogeneity. Climatic factors associated with temperature and precipitation variables and the interaction between climate with space were able to explain a substantial amount of variation in community structure. In addition, the turnover of species increased significantly as geographic distances increased. We confirmed that spatial and local environmental factors worked together to shape epigaeic beetle communities along the geographic gradient in the Inner Mongolia grassland. Moreover, the climate features, especially precipitation, water-energy balance and temperature, and the interaction between climate with space and environmental heterogeneity appeared to play important roles on controlling richness and abundance, and species compositions of epigaeic beetles.

  18. A Study of the Relative Importance of Communication and Economic Variables in Diffusion: Dwarf Wheats on Unirrigated Small Holdings in Pakistan.

    Science.gov (United States)

    Rochin, Refugio I.

    The purpose of this paper is twofold: (1) it presents some empirical findings of the relative importance of both "economic" and "communication" variables in the diffusion of an innovation (dwarf wheats) in an unirrigated region of Pakistan which is densely populated by smallholders. The sample of farmers reported are…

  19. Dust – A geology-orientated attempt to reappraise the natural components, amounts, inputs to sediment, and importance for correlation purposes

    Czech Academy of Sciences Publication Activity Database

    Hladil, Jindřich; Čejchan, Petr; Bábek, O.; Koptíková, Leona; Navrátil, Tomáš; Kubínová, Petra

    2010-01-01

    Roč. 13, č. 4 (2010), s. 367-384 ISSN 1374-8505 R&D Projects: GA AV ČR IAAX00130702 Institutional research plan: CEZ:AV0Z30130516 Keywords : natural dust * particulare matter * aerosol * sedimentary background * sedimentary inputs * dust teleconnection * limestones * iron contents * Holocene Subject RIV: DB - Geology ; Mineralogy Impact factor: 0.645, year: 2010 http://popups.ulg.ac.be/Geol/docannexe.php?id=3104

  20. Global sensitivity analysis for fuzzy inputs based on the decomposition of fuzzy output entropy

    Science.gov (United States)

    Shi, Yan; Lu, Zhenzhou; Zhou, Yicheng

    2018-06-01

    To analyse the component of fuzzy output entropy, a decomposition method of fuzzy output entropy is first presented. After the decomposition of fuzzy output entropy, the total fuzzy output entropy can be expressed as the sum of the component fuzzy entropy contributed by fuzzy inputs. Based on the decomposition of fuzzy output entropy, a new global sensitivity analysis model is established for measuring the effects of uncertainties of fuzzy inputs on the output. The global sensitivity analysis model can not only tell the importance of fuzzy inputs but also simultaneously reflect the structural composition of the response function to a certain degree. Several examples illustrate the validity of the proposed global sensitivity analysis, which is a significant reference in engineering design and optimization of structural systems.

  1. Multi input single output model predictive control of non-linear bio-polymerization process

    Energy Technology Data Exchange (ETDEWEB)

    Arumugasamy, Senthil Kumar; Ahmad, Z. [School of Chemical Engineering, Univerisiti Sains Malaysia, Engineering Campus, Seri Ampangan,14300 Nibong Tebal, Seberang Perai Selatan, Pulau Pinang (Malaysia)

    2015-05-15

    This paper focuses on Multi Input Single Output (MISO) Model Predictive Control of bio-polymerization process in which mechanistic model is developed and linked with the feedforward neural network model to obtain a hybrid model (Mechanistic-FANN) of lipase-catalyzed ring-opening polymerization of ε-caprolactone (ε-CL) for Poly (ε-caprolactone) production. In this research, state space model was used, in which the input to the model were the reactor temperatures and reactor impeller speeds and the output were the molecular weight of polymer (M{sub n}) and polymer polydispersity index. State space model for MISO created using System identification tool box of Matlab™. This state space model is used in MISO MPC. Model predictive control (MPC) has been applied to predict the molecular weight of the biopolymer and consequently control the molecular weight of biopolymer. The result shows that MPC is able to track reference trajectory and give optimum movement of manipulated variable.

  2. Variability and uncertainty in Swedish exposure factors for use in quantitative exposure assessments.

    Science.gov (United States)

    Filipsson, Monika; Öberg, Tomas; Bergbäck, Bo

    2011-01-01

    Information of exposure factors used in quantitative risk assessments has previously been compiled and reported for U.S. and European populations. However, due to the advancement of science and knowledge, these reports are in continuous need of updating with new data. Equally important is the change over time of many exposure factors related to both physiological characteristics and human behavior. Body weight, skin surface, time use, and dietary habits are some of the most obvious examples covered here. A wealth of data is available from literature not primarily gathered for the purpose of risk assessment. Here we review a number of key exposure factors and compare these factors between northern Europe--here represented by Sweden--and the United States. Many previous compilations of exposure factor data focus on interindividual variability and variability between sexes and age groups, while uncertainty is mainly dealt with in a qualitative way. In this article variability is assessed along with uncertainty. As estimates of central tendency and interindividual variability, mean, standard deviation, skewness, kurtosis, and multiple percentiles were calculated, while uncertainty was characterized using 95% confidence intervals for these parameters. The presented statistics are appropriate for use in deterministic analyses using point estimates for each input parameter as well as in probabilistic assessments. © 2010 Society for Risk Analysis.

  3. Quantitative assessment of drivers of recent global temperature variability: an information theoretic approach

    Science.gov (United States)

    Bhaskar, Ankush; Ramesh, Durbha Sai; Vichare, Geeta; Koganti, Triven; Gurubaran, S.

    2017-12-01

    Identification and quantification of possible drivers of recent global temperature variability remains a challenging task. This important issue is addressed adopting a non-parametric information theory technique, the Transfer Entropy and its normalized variant. It distinctly quantifies actual information exchanged along with the directional flow of information between any two variables with no bearing on their common history or inputs, unlike correlation, mutual information etc. Measurements of greenhouse gases: CO2, CH4 and N2O; volcanic aerosols; solar activity: UV radiation, total solar irradiance ( TSI) and cosmic ray flux ( CR); El Niño Southern Oscillation ( ENSO) and Global Mean Temperature Anomaly ( GMTA) made during 1984-2005 are utilized to distinguish driving and responding signals of global temperature variability. Estimates of their relative contributions reveal that CO2 ({˜ } 24 %), CH4 ({˜ } 19 %) and volcanic aerosols ({˜ }23 %) are the primary contributors to the observed variations in GMTA. While, UV ({˜ } 9 %) and ENSO ({˜ } 12 %) act as secondary drivers of variations in the GMTA, the remaining play a marginal role in the observed recent global temperature variability. Interestingly, ENSO and GMTA mutually drive each other at varied time lags. This study assists future modelling efforts in climate science.

  4. Influence of Road Excitation and Steering Wheel Input on Vehicle System Dynamic Responses

    Directory of Open Access Journals (Sweden)

    Zhen-Feng Wang

    2017-06-01

    Full Text Available Considering the importance of increasing driving safety, the study of safety is a popular and critical topic of research in the vehicle industry. Vehicle roll behavior with sudden steering input is a main source of untripped rollover. However, previous research has seldom considered road excitation and its coupled effect on vehicle lateral response when focusing on lateral and vertical dynamics. To address this issue, a novel method was used to evaluate effects of varying road level and steering wheel input on vehicle roll behavior. Then, a 9 degree of freedom (9-DOF full-car roll nonlinear model including vertical and lateral dynamics was developed to study vehicle roll dynamics with or without of road excitation. Based on a 6-DOF half-car roll model and 9-DOF full-car nonlinear model, relationship between three-dimensional (3-D road excitation and various steering wheel inputs on vehicle roll performance was studied. Finally, an E-Class (SUV level car model in CARSIM® was used, as a benchmark, with and without road input conditions. Both half-car and full-car models were analyzed under steering wheel inputs of 5°, 10° and 15°. Simulation results showed that the half-car model considering road input was found to have a maximum accuracy of 65%. Whereas, the full-car model had a minimum accuracy of 85%, which was significantly higher compared to the half-car model under the same scenario.

  5. Evaluating the Sensitivity of Agricultural Model Performance to Different Climate Inputs: Supplemental Material

    Science.gov (United States)

    Glotter, Michael J.; Ruane, Alex C.; Moyer, Elisabeth J.; Elliott, Joshua W.

    2015-01-01

    Projections of future food production necessarily rely on models, which must themselves be validated through historical assessments comparing modeled and observed yields. Reliable historical validation requires both accurate agricultural models and accurate climate inputs. Problems with either may compromise the validation exercise. Previous studies have compared the effects of different climate inputs on agricultural projections but either incompletely or without a ground truth of observed yields that would allow distinguishing errors due to climate inputs from those intrinsic to the crop model. This study is a systematic evaluation of the reliability of a widely used crop model for simulating U.S. maize yields when driven by multiple observational data products. The parallelized Decision Support System for Agrotechnology Transfer (pDSSAT) is driven with climate inputs from multiple sources reanalysis, reanalysis that is bias corrected with observed climate, and a control dataset and compared with observed historical yields. The simulations show that model output is more accurate when driven by any observation-based precipitation product than when driven by non-bias-corrected reanalysis. The simulations also suggest, in contrast to previous studies, that biased precipitation distribution is significant for yields only in arid regions. Some issues persist for all choices of climate inputs: crop yields appear to be oversensitive to precipitation fluctuations but under sensitive to floods and heat waves. These results suggest that the most important issue for agricultural projections may be not climate inputs but structural limitations in the crop models themselves.

  6. Use of Sobol's quasirandom sequence generator for integration of modified uncertainty importance measure

    International Nuclear Information System (INIS)

    Homma, Toshimitsu; Saltelli, A.

    1995-01-01

    Sensitivity analysis of model output is relevant to a number of practices, including verification of models and computer code quality assurance. It deals with the identification of influential model parameters, especially in complex models implemented in computer programs with many uncertain input variables. In a recent article a new method for sensitivity analysis, named HIM * based on a rank transformation of the uncertainty importance measure suggested by Hora and Iman was proved very powerful for performing automated sensitivity analysis of model output, even in presence of model non-monotonicity. The same was not true of other widely used non-parametric techniques such as standardized rank regression coefficients. A drawback of the HIM * method was the large dimension of the stochastic sample needed for its estimation, which made HIM * impracticable for systems with large number of uncertain parameters. In the present note a more effective sampling algorithm, based on Sobol's quasirandom generator is coupled with HIM * , thereby greatly reducing the sample size needed for an effective identification of influential variables. The performances of the new technique are investigated for two different benchmarks. (author)

  7. Important variables for parents' postnatal sense of security: evaluating a new Swedish instrument (the PPSS instrument).

    Science.gov (United States)

    Persson, Eva K; Dykes, Anna-Karin

    2009-08-01

    to evaluate dimensions of both parents' postnatal sense of security the first week after childbirth, and to determine associations between the PPSS instrument and different sociodemographic and situational background variables. evaluative, cross-sectional design. 113 mothers and 99 fathers with children live born at term, from five hospitals in southern Sweden. mothers and fathers had similar feelings concerning postnatal sense of security. Of the dimensions in the PPSS instrument, a sense of midwives'/nurses' empowering behaviour, a sense of one's own general well-being and a sense of the mother's well-being as experienced by the father were the most important dimensions for parents' experienced security. A sense of affinity within the family (for both parents) and a sense of manageable breast feeding (for mothers) were not significantly associated with their experienced security. A sense of participation during pregnancy and general anxiety were significantly associated background variables for postnatal sense of security for both parents. For the mothers, parity and a sense that the father was participating during pregnancy were also significantly associated. more focus on parents' participation during pregnancy as well as midwives'/nurses' empowering behaviour during the postnatal period will be beneficial for both parents' postnatal sense of security.

  8. Soil-Related Input Parameters for the Biosphere Model

    Energy Technology Data Exchange (ETDEWEB)

    A. J. Smith

    2004-09-09

    This report presents one of the analyses that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN). The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the details of the conceptual model as well as the mathematical model and the required input parameters. The biosphere model is one of a series of process models supporting the postclosure Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A schematic representation of the documentation flow for the Biosphere input to TSPA is presented in Figure 1-1. This figure shows the evolutionary relationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan for Biosphere Modeling and Expert Support'' (TWP) (BSC 2004 [DIRS 169573]). This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this report. This report, ''Soil-Related Input Parameters for the Biosphere Model'', is one of the five analysis reports that develop input parameters for use in the ERMYN model. This report is the source documentation for the six biosphere parameters identified in Table 1-1. The purpose of this analysis was to develop the biosphere model parameters associated with the accumulation and depletion of radionuclides in the soil. These parameters support the calculation of radionuclide concentrations in soil from on-going irrigation or ash deposition and, as a direct consequence, radionuclide concentration in other environmental media that are affected by radionuclide concentrations in soil. The analysis was performed in accordance with the TWP (BSC 2004 [DIRS 169573]) where the governing procedure

  9. Importance of fruit variability in the assessment of apple quality by sensory evaluation

    DEFF Research Database (Denmark)

    Bavay, Cécile; Symoneaux, Ronan; Maître, Isabelle

    2013-01-01

    cultivars, apples were sorted into homogenous acoustic firmness categories within each cultivar. The discrimination ability of the trained panel was observed not only between cultivars but also within each cultivar for crunchiness, firmness, juiciness and acidity. Following these results, a mixed......The assessment of produce quality is a major aspect of applied postharvest biology. Horticultural researchers working on organoleptic quality of fruit need objective methods for the evaluation of sensory properties. The development of sensory methodologies specifically for apples highlighted...... the problem of handling variation due to fruit variability and assessor differences. The aim of this study was to investigate the weight of within-batch variability in sensory evaluation of apples and to propose a methodology that accounts for this variability. Prior to sensory analysis, for three apple...

  10. Multiregional input-output model for the evaluation of Spanish water flows.

    Science.gov (United States)

    Cazcarro, Ignacio; Duarte, Rosa; Sánchez Chóliz, Julio

    2013-01-01

    We construct a multiregional input-output model for Spain, in order to evaluate the pressures on the water resources, virtual water flows, and water footprints of the regions, and the water impact of trade relationships within Spain and abroad. The study is framed with those interregional input-output models constructed to study water flows and impacts of regions in China, Australia, Mexico, or the UK. To build our database, we reconcile regional IO tables, national and regional accountancy of Spain, trade and water data. Results show an important imbalance between origin of water resources and final destination, with significant water pressures in the South, Mediterranean, and some central regions. The most populated and dynamic regions of Madrid and Barcelona are important drivers of water consumption in Spain. Main virtual water exporters are the South and Central agrarian regions: Andalusia, Castile-La Mancha, Castile-Leon, Aragon, and Extremadura, while the main virtual water importers are the industrialized regions of Madrid, Basque country, and the Mediterranean coast. The paper shows the different location of direct and indirect consumers of water in Spain and how the economic trade and consumption pattern of certain areas has significant impacts on the availability of water resources in other different and often drier regions.

  11. Development and operation of K-URT data input system

    International Nuclear Information System (INIS)

    Kim, Yun Jae; Myoung, Noh Hoon; Kim, Jong Hyun; Han, Jae Jun

    2010-05-01

    Activities for TSPA(Total System Performance Assessment) on the permanent disposal of high level radioactive waste includes production of input data, safety assessment using input data, license procedure and others. These activities are performed in 5 steps as follows; (1) Adequate planning, (2) Controlled execution, (3) Complete documentation, (4) Thorough review, (5) Independent oversight. For the confidence building, it is very important to record and manage the materials obtained from research works in transparency. For the documentation of disposal research work from planning stage to data management stage, KAERI developed CYPRUS named CYBER R and D Platform for Radwaste Disposal in Underground System with a QA(Quality Assurance) System. In CYPRUS, QA system makes effects on other functions such as data management, project management and others. This report analyzes the structure of CYPRUS and proposes to accumulate qualified data, to provide a convenient application and to promote access and use of CYPRUS for a future-oriented system

  12. Comfort constraints. Input for simulation of residents' behavior; Comforthinder. Input bij simulatie van bewonersgedrag

    Energy Technology Data Exchange (ETDEWEB)

    Phaff, H. [TNO Bouw en Ondergrond, Delft (Netherlands)

    2010-04-15

    Buildings in reality, use more energy than predicted. Among many causes, occupant behaviour plays an important role. Better simulation of occupant behaviour, with respect to thermal comfort and energy use of buildings, opens the possibility to design better, comfortable buildings that have lower energy consumption in reality. Thermal discomfort, a dynamical version of Fanger's PPD, is proposed to be used as input to simulate occupant behaviour via a 'flexible task list' and two Markov processes. [Dutch] Simulatie van bewonersgedrag m.b.t. energiegebruik in gebouwen biedt de mogelijkheid om gebouwen en bijbehorende energie installaties zo te ontwerpen dat ze prettiger zijn om in te wonen en te werken. Thermisch discomfort, een dynamische versie van PPD (percentage of dissatisfied persons) wordt hier voorgesteld om via een Markov-proces en een takenlijst bewonersgedrag mee te simuleren.

  13. Push-Pull and Feedback Mechanisms Can Align Signaling System Outputs with Inputs.

    Science.gov (United States)

    Andrews, Steven S; Peria, William J; Yu, Richard C; Colman-Lerner, Alejandro; Brent, Roger

    2016-11-23

    Many cell signaling systems, including the yeast pheromone response system, exhibit "dose-response alignment" (DoRA), in which output of one or more downstream steps closely matches the fraction of occupied receptors. DoRA can improve the fidelity of transmitted dose information. Here, we searched systematically for biochemical network topologies that produced DoRA. Most networks, including many containing feedback and feedforward loops, could not produce DoRA. However, networks including "push-pull" mechanisms, in which the active form of a signaling species stimulates downstream activity and the nominally inactive form reduces downstream activity, enabled perfect DoRA. Networks containing feedbacks enabled DoRA, but only if they also compared feedback to input and adjusted output to match. Our results establish push-pull as a non-feedback mechanism to align output with variable input and maximize information transfer in signaling systems. They also suggest genetic approaches to determine whether particular signaling systems use feedback or push-pull control. Copyright © 2016 Elsevier Inc. All rights reserved.

  14. Experimental characterization of variable output refractive beamshapers using freeform elements

    Science.gov (United States)

    Shultz, Jason A.; Smilie, Paul J.; Dutterer, Brian S.; Davies, Matthew A.; Suleski, Thomas J.

    2014-09-01

    We present experimental results from variable output refractive beam shapers based on freeform optical surfaces. Two freeform elements in close proximity comprise a beam shaper that maps a circular Gaussian input to a circular `flat-top' output. Different lateral relative shifts between the elements result in a varying output diameter while maintaining the uniform irradiance distribution. We fabricated the beam shaping elements in PMMA using multi-axis milling on a Moore Nanotech 350FG diamond machining center and tested with a 632.8 nm Gaussian input. Initial optical testing confirmed both the predicted beam shaping and variable functionality, but with poor output uniformity. The effects of surface finish on optical performance were investigated using LightTrans VirtualLabTM to perform physical optics simulations of the milled freeform surfaces. These simulations provided an optimization path for determining machining parameters to improve the output uniformity of the beam shaping elements. A second variable beam shaper based on a super-Gaussian output was designed and fabricated using the newly determined machining parameters. Experimental test results from the second beam shaper showed outputs with significantly higher quality, but also suggest additional areas of study for further improvements in uniformity.

  15. Robust Machine Learning Variable Importance Analyses of Medical Conditions for Health Care Spending.

    Science.gov (United States)

    Rose, Sherri

    2018-03-11

    To propose nonparametric double robust machine learning in variable importance analyses of medical conditions for health spending. 2011-2012 Truven MarketScan database. I evaluate how much more, on average, commercially insured enrollees with each of 26 of the most prevalent medical conditions cost per year after controlling for demographics and other medical conditions. This is accomplished within the nonparametric targeted learning framework, which incorporates ensemble machine learning. Previous literature studying the impact of medical conditions on health care spending has almost exclusively focused on parametric risk adjustment; thus, I compare my approach to parametric regression. My results demonstrate that multiple sclerosis, congestive heart failure, severe cancers, major depression and bipolar disorders, and chronic hepatitis are the most costly medical conditions on average per individual. These findings differed from those obtained using parametric regression. The literature may be underestimating the spending contributions of several medical conditions, which is a potentially critical oversight. If current methods are not capturing the true incremental effect of medical conditions, undesirable incentives related to care may remain. Further work is needed to directly study these issues in the context of federal formulas. © Health Research and Educational Trust.

  16. From water use to water scarcity footprinting in environmentally extended input-output analysis.

    Science.gov (United States)

    Ridoutt, Bradley George; Hadjikakou, Michalis; Nolan, Martin; Bryan, Brett A

    2018-05-18

    Environmentally extended input-output analysis (EEIOA) supports environmental policy by quantifying how demand for goods and services leads to resource use and emissions across the economy. However, some types of resource use and emissions require spatially-explicit impact assessment for meaningful interpretation, which is not possible in conventional EEIOA. For example, water use in locations of scarcity and abundance is not environmentally equivalent. Opportunities for spatially-explicit impact assessment in conventional EEIOA are limited because official input-output tables tend to be produced at the scale of political units which are not usually well aligned with environmentally relevant spatial units. In this study, spatially-explicit water scarcity factors and a spatially disaggregated Australian water use account were used to develop water scarcity extensions that were coupled with a multi-regional input-output model (MRIO). The results link demand for agricultural commodities to the problem of water scarcity in Australia and globally. Important differences were observed between the water use and water scarcity footprint results, as well as the relative importance of direct and indirect water use, with significant implications for sustainable production and consumption-related policies. The approach presented here is suggested as a feasible general approach for incorporating spatially-explicit impact assessment in EEIOA.

  17. Norway spruce fine root dynamics and carbon input into soil in relation to environmental factors

    OpenAIRE

    Leppälammi-Kujansuu, Jaana

    2014-01-01

    Knowledge of the quantity of belowground litter carbon (C) input is scarce but highly valued in C budget calculations. Specifically, the turnover rate of fine roots is considered to be one of the most important parameters in the estimation of changes in soil C stock. In this thesis Norway spruce (Picea abies L. (Karst.)) fine root lifespan and litter production and their responses to nutrient availability and temperature were examined. Aboveground foliage and understory litter C inputs were a...

  18. On the Nature of the Input in Optimality Theory

    DEFF Research Database (Denmark)

    Heck, Fabian; Müller, Gereon; Vogel, Ralf

    2002-01-01

    The input has two main functions in optimality theory (Prince and Smolensky 1993). First, the input defines the candidate set, in other words it determines which output candidates compete for optimality, and which do not. Second, the input is referred to by faithfulness constraints that prohibit...... output candidates from deviating from specifications in the input. Whereas there is general agreement concerning the relevance of the input in phonology, the nature of the input in syntax is notoriously unclear. In this article, we show that the input should not be taken to define syntactic candidate...... and syntax is due to a basic, irreducible difference between these two components of grammar: Syntax is an information preserving system, phonology is not....

  19. Residential-commercial energy input estimation based on genetic algorithm (GA) approaches: an application of Turkey

    International Nuclear Information System (INIS)

    Ozturk, H.K.; Canyurt, O.E.; Hepbasli, A.; Utlu, Z.

    2004-01-01

    The main objective of the present study is to develop the energy input estimation equations for the residential-commercial sector (RCS) in order to estimate the future projections based on genetic algorithm (GA) notion and to examine the effect of the design parameters on the energy input of the sector. For this purpose, the Turkish RCS is given as an example. The GA Energy Input Estimation Model (GAEIEM) is used to estimate Turkey's future residential-commercial energy input demand based on gross domestic product (GDP), population, import, export, house production, cement production and basic house appliances consumption figures. It may be concluded that the three various forms of models proposed here can be used as an alternative solution and estimation techniques to available estimation techniques. It is also expected that this study will be helpful in developing highly applicable and productive planning for energy policies. (author)

  20. How the type of input function affects the dynamic response of conducting polymer actuators

    Science.gov (United States)

    Xiang, Xingcan; Alici, Gursel; Mutlu, Rahim; Li, Weihua

    2014-10-01

    There has been a growing interest in smart actuators typified by conducting polymer actuators, especially in their (i) fabrication, modeling and control with minimum external data and (ii) applications in bio-inspired devices, robotics and mechatronics. Their control is a challenging research problem due to the complex and nonlinear properties of these actuators, which cannot be predicted accurately. Based on an input-shaping technique, we propose a new method to improve the conducting polymer actuators’ command-following ability, while minimizing their electric power consumption. We applied four input functions with smooth characteristics to a trilayer conducting polymer actuator to experimentally evaluate its command-following ability under an open-loop control strategy and a simulated feedback control strategy, and, more importantly, to quantify how the type of input function affects the dynamic response of this class of actuators. We have found that the four smooth inputs consume less electrical power than sharp inputs such as a step input with discontinuous higher-order derivatives. We also obtained an improved transient response performance from the smooth inputs, especially under the simulated feedback control strategy, which we have proposed previously [X Xiang, R Mutlu, G Alici, and W Li, 2014 “Control of conducting polymer actuators without physical feedback: simulated feedback control approach with particle swarm optimization’, Journal of Smart Materials and Structure, 23]. The idea of using a smooth input command, which results in lower power consumption and better control performance, can be extended to other smart actuators. Consuming less electrical energy or power will have a direct effect on enhancing the operational life of these actuators.

  1. How the type of input function affects the dynamic response of conducting polymer actuators

    International Nuclear Information System (INIS)

    Xiang, Xingcan; Alici, Gursel; Mutlu, Rahim; Li, Weihua

    2014-01-01

    There has been a growing interest in smart actuators typified by conducting polymer actuators, especially in their (i) fabrication, modeling and control with minimum external data and (ii) applications in bio-inspired devices, robotics and mechatronics. Their control is a challenging research problem due to the complex and nonlinear properties of these actuators, which cannot be predicted accurately. Based on an input-shaping technique, we propose a new method to improve the conducting polymer actuators’ command-following ability, while minimizing their electric power consumption. We applied four input functions with smooth characteristics to a trilayer conducting polymer actuator to experimentally evaluate its command-following ability under an open-loop control strategy and a simulated feedback control strategy, and, more importantly, to quantify how the type of input function affects the dynamic response of this class of actuators. We have found that the four smooth inputs consume less electrical power than sharp inputs such as a step input with discontinuous higher-order derivatives. We also obtained an improved transient response performance from the smooth inputs, especially under the simulated feedback control strategy, which we have proposed previously [X Xiang, R Mutlu, G Alici, and W Li, 2014 “Control of conducting polymer actuators without physical feedback: simulated feedback control approach with particle swarm optimization’, Journal of Smart Materials and Structure, 23]. The idea of using a smooth input command, which results in lower power consumption and better control performance, can be extended to other smart actuators. Consuming less electrical energy or power will have a direct effect on enhancing the operational life of these actuators. (paper)

  2. Cross-Regional Assessment Of Coupling And Variability In Precipitation-Runoff Relationships

    Science.gov (United States)

    Carey, S. K.; Tetzlaff, D.; Soulsby, C.; Buttle, J. M.; Laudon, H.; McDonnell, J. J.; McGuire, K. J.; Seibert, J.; Shanley, J. B.

    2011-12-01

    The higher mid-latitudes of the northern hemisphere are particularly sensitive to change due to the important role the zero-degree isotherm plays in the phase of precipitation and intermediate storage as snow. An international inter-catchment comparison program North-Watch seeks to improve our understanding of the sensitivity of northern catchments to change by examining their hydrological and biogeochemical variability and response. The catchments are located in Sweden (Krycklan), Scotland (Mharcaidh, Girnock and Strontian), the United States (Sleepers River, Hubbard Brook and HJ Andrews) and Canada (Catamaran, Dorset and Wolf Creek). For this study, 8 catchments with 10 continuous years of daily precipitation and runoff data were selected to assess the seasonal coupling of rainfall and runoff and the memory effect of runoff events on the hydrograph at different time scales. To assess the coupling and synchroneity of precipitation, continuous wavelet transforms and wavelet coherence were used. Wavelet spectra identified the relative importance of both annual versus seasonal flows while wavelet coherence was applied to identify over different time scales along the 10-year window how well precipitation and runoff were coupled. For example, while on a given day, precipitation may be closely coupled to runoff, a wet year may not necessarily be a high runoff year in catchments with large storage. Assessing different averaging periods in the variation of daily flows highlights the importance of seasonality in runoff response and the relative influence of rain versus snowmelt on flow magnitude and variability. Wet catchments with limited seasonal precipitation variability (Strontian, Girnock) have precipitation signals more closely coupled with runoff, whereas dryer catchments dominated by snow (Wolf Creek, Krycklan) have strongly coupling only during freshet. Most catchments with highly seasonal precipitation show strong intermittent coupling during their wet season. At

  3. Phasing Out a Polluting Input

    OpenAIRE

    Eriksson, Clas

    2015-01-01

    This paper explores economic policies related to the potential conflict between economic growth and the environment. It applies a model with directed technological change and focuses on the case with low elasticity of substitution between clean and dirty inputs in production. New technology is substituted for the polluting input, which results in a gradual decline in pollution along the optimal long-run growth path. In contrast to some recent work, the era of pollution and environmental polic...

  4. Thermoelectric power generator for variable thermal power source

    Science.gov (United States)

    Bell, Lon E; Crane, Douglas Todd

    2015-04-14

    Traditional power generation systems using thermoelectric power generators are designed to operate most efficiently for a single operating condition. The present invention provides a power generation system in which the characteristics of the thermoelectrics, the flow of the thermal power, and the operational characteristics of the power generator are monitored and controlled such that higher operation efficiencies and/or higher output powers can be maintained with variably thermal power input. Such a system is particularly beneficial in variable thermal power source systems, such as recovering power from the waste heat generated in the exhaust of combustion engines.

  5. Energy sensitivity and variability analysis of Populus hybrid short-rotation plantations in northeastern United States. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Bowersox, T.W.; Blankenhorn, P.R.

    1979-10-24

    Production of biomass by corn-like plantations has been demonstrated by a number of researchers. These forest analogs of agronomic cropping systems have the potential to yield substantially more biomass per unit area than traditional forests. Care is needed in choosing the appropriate sites, species, spacing, and harvesting strategies. Opportunities for increased yields have been suggested for fertilization and irrigation. Utilization of the biomass from these dense plantations for energy was the focus of this study. Although the amount of energy potential of the biomass is important, the energy output must be greater than the energy input for biomass to have a positive benefit to society. Further, in order to completely evaluate the net energy of the system it is necessary to examine the energy out-to-in ratios on the basis of usable energy (for example, usable heat, process steam and electricity), as well as all of the energies expended in producing, harvesting, transporting and processing the biomass. The objective of this study is to establish and analyze the energy inputs for selected management strategies in order to evaluate the sensitivity and variability of the energy inputs in the net energy analysis, and based on the net energy analysis to recommend a management strategy that minimizes energy inputs while maximizing biomass yield for short-rotation systems of Populus spp. in the northeastern United States.

  6. Runtime analysis of the (1+1) EA on computing unique input output sequences

    DEFF Research Database (Denmark)

    Lehre, Per Kristian; Yao, Xin

    2010-01-01

    Computing unique input output (UIO) sequences is a fundamental and hard problem in conformance testing of finite state machines (FSM). Previous experimental research has shown that evolutionary algorithms (EAs) can be applied successfully to find UIOs for some FSMs. However, before EAs can...... in the theoretical analysis, and the variability of the runtime. The numerical results fit well with the theoretical results, even for small problem instance sizes. Together, these results provide a first theoretical characterisation of the potential and limitations of the (1 + 1) EA on the problem of computing UIOs....

  7. Using traditional methods and indigenous technologies for coping with climate variability

    NARCIS (Netherlands)

    Stigter, C.J.; Zheng Dawei,; Onyewotu, L.O.Z.; Mei Xurong,

    2005-01-01

    In agrometeorology and management of meteorology related natural resources, many traditional methods and indigenous technologies are still in use or being revived for managing low external inputs sustainable agriculture (LEISA) under conditions of climate variability. This paper starts with the

  8. FIRE: an SPSS program for variable selection in multiple linear regression analysis via the relative importance of predictors.

    Science.gov (United States)

    Lorenzo-Seva, Urbano; Ferrando, Pere J

    2011-03-01

    We provide an SPSS program that implements currently recommended techniques and recent developments for selecting variables in multiple linear regression analysis via the relative importance of predictors. The approach consists of: (1) optimally splitting the data for cross-validation, (2) selecting the final set of predictors to be retained in the equation regression, and (3) assessing the behavior of the chosen model using standard indices and procedures. The SPSS syntax, a short manual, and data files related to this article are available as supplemental materials from brm.psychonomic-journals.org/content/supplemental.

  9. The economic impact of multifunctional agriculture in Dutch regions: An input-output model

    NARCIS (Netherlands)

    Heringa, P.W.; Heide, van der C.M.; Heijman, W.J.M.

    2013-01-01

    Multifunctional agriculture is a broad concept lacking a precise definition. Moreover, little is known about the societal importance of multifunctional agriculture. This paper is an empirical attempt to fill this gap. To this end, an input-output model was constructed for multifunctional agriculture

  10. The Effects of Type and Quantity of Input on Iranian EFL Learners’ Oral Language Proficiency

    Directory of Open Access Journals (Sweden)

    Zahra Hassanzadeh

    2014-05-01

    Full Text Available In the written texts on foreign language learning, a group of studies has stressed the function of learning context and learning chances for learners’ language input. The present thesis had two main goals: on the one hand, different types of input to which Iranian grade four high school EFL learners’ are exposed were looked at; on the other hand, the possible relationship between types and quantity of input and Iranian EFL learners’ oral proficiency was investigated. It was supposed that EFL learners who have access to more input will show better oral proficiency than those who do not have. Instruments used in the present study for the purpose of data collation included  PET test, researcher- made questionnaire, oral language proficiency test and face- to -face interview. Data were gathered from 50 Iranian female grade four high school foreign language learners who were selected from among 120 students whose score on PET test were +1SD from the mean score. The results of the Spearman rank –order correlation test for the types of input and oral language proficiency scores, showed that the participants’ oral proficiency score significantly correlated with the intended four sources of input including spoken (rho= 0.416, sig=0.003, written (rho= 0.364, sig=0.009, aural (rho= 0.343, sig=0.015 and visual or audio-visual types of input (rho= 0.47, sig=0.00. The findings of Spearman rank –order correlation test for the quantity of input and oral language proficiency scores also showed a significant relationship between quantity of input and oral language proficiency (rho= 0.543, sig= 0.00. The findings showed that EFL learners’ oral proficiency is significantly correlated with efficient and effective input. The findings may also suggest  answers to the question why most Iranian English learners fail to speak English fluently, which might be due to  lack of effective input. This may emphasize the importance of the types and quantity of

  11. WORM: A general-purpose input deck specification language

    International Nuclear Information System (INIS)

    Jones, T.

    1999-01-01

    Using computer codes to perform criticality safety calculations has become common practice in the industry. The vast majority of these codes use simple text-based input decks to represent the geometry, materials, and other parameters that describe the problem. However, the data specified in input files are usually processed results themselves. For example, input decks tend to require the geometry specification in linear dimensions and materials in atom or weight fractions, while the parameter of interest might be mass or concentration. The calculations needed to convert from the item of interest to the required parameter in the input deck are usually performed separately and then incorporated into the input deck. This process of calculating, editing, and renaming files to perform a simple parameter study is tedious at best. In addition, most computer codes require dimensions to be specified in centimeters, while drawings or other materials used to create the input decks might be in other units. This also requires additional calculation or conversion prior to composition of the input deck. These additional calculations, while extremely simple, introduce a source for error in both the calculations and transcriptions. To overcome these difficulties, WORM (Write One, Run Many) was created. It is an easy-to-use programming language to describe input decks and can be used with any computer code that uses standard text files for input. WORM is available, via the Internet, at worm.lanl.gov. A user's guide, tutorials, example models, and other WORM-related materials are also available at this Web site. Questions regarding WORM should be directed to wormatlanl.gov

  12. Technological change in energy systems. Learning curves, logistic curves and input-output coefficients

    International Nuclear Information System (INIS)

    Pan, Haoran; Koehler, Jonathan

    2007-01-01

    Learning curves have recently been widely adopted in climate-economy models to incorporate endogenous change of energy technologies, replacing the conventional assumption of an autonomous energy efficiency improvement. However, there has been little consideration of the credibility of the learning curve. The current trend that many important energy and climate change policy analyses rely on the learning curve means that it is of great importance to critically examine the basis for learning curves. Here, we analyse the use of learning curves in energy technology, usually implemented as a simple power function. We find that the learning curve cannot separate the effects of price and technological change, cannot reflect continuous and qualitative change of both conventional and emerging energy technologies, cannot help to determine the time paths of technological investment, and misses the central role of R and D activity in driving technological change. We argue that a logistic curve of improving performance modified to include R and D activity as a driving variable can better describe the cost reductions in energy technologies. Furthermore, we demonstrate that the top-down Leontief technology can incorporate the bottom-up technologies that improve along either the learning curve or the logistic curve, through changing input-output coefficients. An application to UK wind power illustrates that the logistic curve fits the observed data better and implies greater potential for cost reduction than the learning curve does. (author)

  13. Microbial Communities Are Well Adapted to Disturbances in Energy Input.

    Science.gov (United States)

    Fernandez-Gonzalez, Nuria; Huber, Julie A; Vallino, Joseph J

    2016-01-01

    Although microbial systems are well suited for studying concepts in ecological theory, little is known about how microbial communities respond to long-term periodic perturbations beyond diel oscillations. Taking advantage of an ongoing microcosm experiment, we studied how methanotrophic microbial communities adapted to disturbances in energy input over a 20-day cycle period. Sequencing of bacterial 16S rRNA genes together with quantification of microbial abundance and ecosystem function were used to explore the long-term dynamics (510 days) of methanotrophic communities under continuous versus cyclic chemical energy supply. We observed that microbial communities appeared inherently well adapted to disturbances in energy input and that changes in community structure in both treatments were more dependent on internal dynamics than on external forcing. The results also showed that the rare biosphere was critical to seeding the internal community dynamics, perhaps due to cross-feeding or other strategies. We conclude that in our experimental system, internal feedbacks were more important than external drivers in shaping the community dynamics over time, suggesting that ecosystems can maintain their function despite inherently unstable community dynamics. IMPORTANCE Within the broader ecological context, biological communities are often viewed as stable and as only experiencing succession or replacement when subject to external perturbations, such as changes in food availability or the introduction of exotic species. Our findings indicate that microbial communities can exhibit strong internal dynamics that may be more important in shaping community succession than external drivers. Dynamic "unstable" communities may be important for ecosystem functional stability, with rare organisms playing an important role in community restructuring. Understanding the mechanisms responsible for internal community dynamics will certainly be required for understanding and manipulating

  14. Generation of correlated finite alphabet waveforms using gaussian random variables

    KAUST Repository

    Ahmed, Sajid

    2016-01-13

    Various examples of methods and systems are provided for generation of correlated finite alphabet waveforms using Gaussian random variables in, e.g., radar and communication applications. In one example, a method includes mapping an input signal comprising Gaussian random variables (RVs) onto finite-alphabet non-constant-envelope (FANCE) symbols using a predetermined mapping function, and transmitting FANCE waveforms through a uniform linear array of antenna elements to obtain a corresponding beampattern. The FANCE waveforms can be based upon the mapping of the Gaussian RVs onto the FANCE symbols. In another example, a system includes a memory unit that can store a plurality of digital bit streams corresponding to FANCE symbols and a front end unit that can transmit FANCE waveforms through a uniform linear array of antenna elements to obtain a corresponding beampattern. The system can include a processing unit that can encode the input signal and/or determine the mapping function.

  15. Generation of correlated finite alphabet waveforms using gaussian random variables

    KAUST Repository

    Ahmed, Sajid; Alouini, Mohamed-Slim; Jardak, Seifallah

    2016-01-01

    Various examples of methods and systems are provided for generation of correlated finite alphabet waveforms using Gaussian random variables in, e.g., radar and communication applications. In one example, a method includes mapping an input signal comprising Gaussian random variables (RVs) onto finite-alphabet non-constant-envelope (FANCE) symbols using a predetermined mapping function, and transmitting FANCE waveforms through a uniform linear array of antenna elements to obtain a corresponding beampattern. The FANCE waveforms can be based upon the mapping of the Gaussian RVs onto the FANCE symbols. In another example, a system includes a memory unit that can store a plurality of digital bit streams corresponding to FANCE symbols and a front end unit that can transmit FANCE waveforms through a uniform linear array of antenna elements to obtain a corresponding beampattern. The system can include a processing unit that can encode the input signal and/or determine the mapping function.

  16. Input/output manual of light water reactor fuel analysis code FEMAXI-7 and its related codes

    Energy Technology Data Exchange (ETDEWEB)

    Suzuki, Motoe; Udagawa, Yutaka; Nagase, Fumihisa [Japan Atomic Energy Agency, Nuclear Safety Research Center, Tokai, Ibaraki (Japan); Saitou, Hiroaki [ITOCHU Techno-Solutions Corporation, Tokyo (Japan)

    2013-10-15

    A light water reactor fuel analysis code FEMAXI-7 has been developed, as an extended version from the former version FEMAXI-6, for the purpose of analyzing the fuel behavior in normal conditions and in anticipated transient conditions. Numerous functional improvements and extensions have been incorporated in FEMAXI-7, which are fully disclosed in the code model description published in the form of another JAEA-Data/Code report. The present manual, which is the very counterpart of this description document, gives detailed explanations of files and operation method of FEMAXI-7 code and its related codes, methods of input/output, sample Input/Output, methods of source code modification, subroutine structure, and internal variables in a specific manner in order to facilitate users to perform fuel analysis by FEMAXI-7. (author)

  17. Input/output manual of light water reactor fuel analysis code FEMAXI-7 and its related codes

    International Nuclear Information System (INIS)

    Suzuki, Motoe; Udagawa, Yutaka; Nagase, Fumihisa; Saitou, Hiroaki

    2013-10-01

    A light water reactor fuel analysis code FEMAXI-7 has been developed, as an extended version from the former version FEMAXI-6, for the purpose of analyzing the fuel behavior in normal conditions and in anticipated transient conditions. Numerous functional improvements and extensions have been incorporated in FEMAXI-7, which are fully disclosed in the code model description published in the form of another JAEA-Data/Code report. The present manual, which is the very counterpart of this description document, gives detailed explanations of files and operation method of FEMAXI-7 code and its related codes, methods of input/output, sample Input/Output, methods of source code modification, subroutine structure, and internal variables in a specific manner in order to facilitate users to perform fuel analysis by FEMAXI-7. (author)

  18. A new environmental Kuznets curve? Relationship between direct material input and income per capita. Evidence from industrialised countries

    Energy Technology Data Exchange (ETDEWEB)

    Canas, Angela; Ferrao, Paulo; Conceicao, Pedro [IN+-Centre for Innovation, Technology and Policy Research, IST-Instituto Superior Tecnico, Av. Rovisco Pais, 1049-001 Lisbon (Portugal)

    2003-09-01

    Many studies have focused on the quantification of the input of materials into the economy. However, the insights provided by those studies have generally been limited. This paper attempts to bring analytical value to the discussion on 'dematerialization' considering direct material input (DMI) per capita as the dependent variable in a test of the environmental Kuznets curve (EKC). The explanatory variable is, as usual, gross domestic product per capita. The quadratic and cubic versions of the EKC are tested econometrically, using panel data ranging from 1960 to 1998 for 16 industrialised countries. The results indicate a strong and robust support for both the quadratic and cubic EKC relationships between material input and income, in industrialised economies. While the statistical support to both types of evolution may seem contradictory, it suggests that as industrialised economies grow, the intensity of material consumption first increases, but eventually starts exhibiting a decreasing trend after a certain income threshold is reached. The inverted-U, or quadratic, relationship is confirmed, even though for the ranges of income considered in this study, the trend is mostly on the increasing part of the inverted-U curve. However, the statistical support to the cubic specification suggests that these results need to be regarded with caution. Overall, the statistically stronger models are the quadratic and cubic models with country random effects, and the cubic model with country and year fixed effects.

  19. Sound effects: Multimodal input helps infants find displaced objects.

    Science.gov (United States)

    Shinskey, Jeanne L

    2017-09-01

    Before 9 months, infants use sound to retrieve a stationary object hidden by darkness but not one hidden by occlusion, suggesting auditory input is more salient in the absence of visual input. This article addresses how audiovisual input affects 10-month-olds' search for displaced objects. In AB tasks, infants who previously retrieved an object at A subsequently fail to find it after it is displaced to B, especially following a delay between hiding and retrieval. Experiment 1 manipulated auditory input by keeping the hidden object audible versus silent, and visual input by presenting the delay in the light versus dark. Infants succeeded more at B with audible than silent objects and, unexpectedly, more after delays in the light than dark. Experiment 2 presented both the delay and search phases in darkness. The unexpected light-dark difference disappeared. Across experiments, the presence of auditory input helped infants find displaced objects, whereas the absence of visual input did not. Sound might help by strengthening object representation, reducing memory load, or focusing attention. This work provides new evidence on when bimodal input aids object processing, corroborates claims that audiovisual processing improves over the first year of life, and contributes to multisensory approaches to studying cognition. Statement of contribution What is already known on this subject Before 9 months, infants use sound to retrieve a stationary object hidden by darkness but not one hidden by occlusion. This suggests they find auditory input more salient in the absence of visual input in simple search tasks. After 9 months, infants' object processing appears more sensitive to multimodal (e.g., audiovisual) input. What does this study add? This study tested how audiovisual input affects 10-month-olds' search for an object displaced in an AB task. Sound helped infants find displaced objects in both the presence and absence of visual input. Object processing becomes more

  20. Uncertainty and variability in computational and mathematical models of cardiac physiology.

    Science.gov (United States)

    Mirams, Gary R; Pathmanathan, Pras; Gray, Richard A; Challenor, Peter; Clayton, Richard H

    2016-12-01

    Mathematical and computational models of cardiac physiology have been an integral component of cardiac electrophysiology since its inception, and are collectively known as the Cardiac Physiome. We identify and classify the numerous sources of variability and uncertainty in model formulation, parameters and other inputs that arise from both natural variation in experimental data and lack of knowledge. The impact of uncertainty on the outputs of Cardiac Physiome models is not well understood, and this limits their utility as clinical tools. We argue that incorporating variability and uncertainty should be a high priority for the future of the Cardiac Physiome. We suggest investigating the adoption of approaches developed in other areas of science and engineering while recognising unique challenges for the Cardiac Physiome; it is likely that novel methods will be necessary that require engagement with the mathematics and statistics community. The Cardiac Physiome effort is one of the most mature and successful applications of mathematical and computational modelling for describing and advancing the understanding of physiology. After five decades of development, physiological cardiac models are poised to realise the promise of translational research via clinical applications such as drug development and patient-specific approaches as well as ablation, cardiac resynchronisation and contractility modulation therapies. For models to be included as a vital component of the decision process in safety-critical applications, rigorous assessment of model credibility will be required. This White Paper describes one aspect of this process by identifying and classifying sources of variability and uncertainty in models as well as their implications for the application and development of cardiac models. We stress the need to understand and quantify the sources of variability and uncertainty in model inputs, and the impact of model structure and complexity and their consequences for

  1. 7 CFR 3431.4 - Solicitation of stakeholder input.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 15 2010-01-01 2010-01-01 false Solicitation of stakeholder input. 3431.4 Section... Designation of Veterinarian Shortage Situations § 3431.4 Solicitation of stakeholder input. The Secretary will solicit stakeholder input on the process and procedures used to designate veterinarian shortage situations...

  2. Determination of the arterial input function in mouse-models using clinical MRI

    International Nuclear Information System (INIS)

    Theis, D.; Fachhochschule Giessen-Friedberg; Keil, B.; Heverhagen, J.T.; Klose, K.J.; Behe, M.; Fiebich, M.

    2008-01-01

    Dynamic contrast enhanced magnetic resonance imaging is a promising method for quantitative analysis of tumor perfusion and is increasingly used in study of cancer in small animal models. In those studies the determination of the arterial input function (AIF) of the target tissue can be the first step. Series of short-axis images of the heart were acquired during administration of a bolus of Gd-DTPA using saturation-recovery gradient echo pulse sequences. The AIF was determined from the changes of the signal intensity in the left ventricle. The native T1 relaxation times and AIF were determined for 11 mice. An average value of (1.16 ± 0.09) s for the native T1 relaxation time was measured. However, the AIF showed significant inter animal variability, as previously observed by other authors. The inter-animal variability shows, that a direct measurement of the AIF is reasonable to avoid significant errors. The proposed method for determination of the AIF proved to be reliable. (orig.)

  3. ZnO crystals obtained by electrodeposition: Statistical analysis of most important process variables

    International Nuclear Information System (INIS)

    Cembrero, Jesus; Busquets-Mataix, David

    2009-01-01

    In this paper a comparative study by means of a statistical analysis of the main process variables affecting ZnO crystal electrodeposition is presented. ZnO crystals were deposited on two different substrates, silicon wafer and indium tin oxide. The control variables were substrate types, electrolyte concentration, temperature, exposition time and current density. The morphologies of the different substrates were observed using scanning electron microscopy. The percentage of substrate area covered by ZnO deposit was calculated by computational image analysis. The design of the applied experiments was based on a two-level factorial analysis involving a series of 32 experiments and an analysis of variance. Statistical results reveal that variables exerting a significant influence on the area covered by ZnO deposit are electrolyte concentration, substrate type and time of deposition, together with a combined two-factor interaction between temperature and current density. However, morphology is also influenced by surface roughness of the substrates

  4. WIMS-D use by ZfK - Data input, experience, and examples

    International Nuclear Information System (INIS)

    Wand, H.

    1983-05-01

    The report provides users of the ZfK-version (EC-1055 computer) of the cell program WIMS-D with all necessary information to compile by oneself input data sets. By means of 10 examples which comprise a large number of the practically most important program options the data compilation is explained. Some experience in using special options is given. (author)

  5. Input-Output Budget of Nitrogen and the Effect of Experimentally Changed Deposition in the Forest Ecosystems in Central Japan

    Directory of Open Access Journals (Sweden)

    Junko Shindo

    2001-01-01

    Full Text Available To evaluate the current nitrogen (N status in Japanese forests, field measurements of rainfall, throughfall, litter layer percolation, and soil solution percolation were conducted in a red pine stand (Kannondai and a deciduous stand (Yasato located in central Japan. N input via throughfall was 31 and 14 kg ha–1 year–1and output below rooting zone was 9.6 and 5.5 kg ha1 year–1 in Kannondai and in Yasato, respectively. Two thirds of input N were retained in plant-soil systems. Manipulation of N input was carried out. Ionic constituents were removed from throughfall with ion exchange resin at removal sites and ammonium nitrate containing twice the N of the throughfall was applied at N addition sites periodically. SO42– output below 20-cm soil layer changed depending on the input, while NO3– output was regulated mainly by the internal cycle and effect of manipulation was undetected. These Japanese stands were generally considered to have a larger capacity to assimilate N than NITREX sites in Europe. However, N output fluxes had large spatial variability and some sites in Kannondai showed high N leaching below rooting zone almost balanced with the input via throughfall.

  6. Uncertainty of input data for room acoustic simulations

    DEFF Research Database (Denmark)

    Jeong, Cheol-Ho; Marbjerg, Gerd; Brunskog, Jonas

    2016-01-01

    Although many room acoustic simulation models have been well established, simulation results will never be accurate with inaccurate and uncertain input data. This study addresses inappropriateness and uncertainty of input data for room acoustic simulations. Firstly, the random incidence absorption...... and scattering coefficients are insufficient when simulating highly non-diffuse rooms. More detailed information, such as the phase and angle dependence, can greatly improve the simulation results of pressure-based geometrical and wave-based models at frequencies well below the Schroeder frequency. Phase...... summarizes potential advanced absorption measurement techniques that can improve the quality of input data for room acoustic simulations. Lastly, plenty of uncertain input data are copied from unreliable sources. Software developers and users should be careful when spreading such uncertain input data. More...

  7. Enhancing the comparability of costing methods: cross-country variability in the prices of non-traded inputs to health programmes.

    Science.gov (United States)

    Johns, Benjamin; Adam, Taghreed; Evans, David B

    2006-04-24

    National and international policy makers have been increasing their focus on developing strategies to enable poor countries achieve the millennium development goals. This requires information on the costs of different types of health interventions and the resources needed to scale them up, either singly or in combinations. Cost data also guides decisions about the most appropriate mix of interventions in different settings, in view of the increasing, but still limited, resources available to improve health. Many cost and cost-effectiveness studies include only the costs incurred at the point of delivery to beneficiaries, omitting those incurred at other levels of the system such as administration, media, training and overall management. The few studies that have measured them directly suggest that they can sometimes account for a substantial proportion of total costs, so that their omission can result in biased estimates of the resources needed to run a programme or the relative cost-effectiveness of different choices. However, prices of different inputs used in the production of health interventions can vary substantially within a country. Basing cost estimates on a single price observation runs the risk that the results are based on an outlier observation rather than the typical costs of the input. We first explore the determinants of the observed variation in the prices of selected "non-traded" intermediate inputs to health programmes--printed matter and media advertising, and water and electricity--accounting for variation within and across countries. We then use the estimated relationship to impute average prices for countries where limited data are available with uncertainty intervals. Prices vary across countries with GDP per capita and a number of determinants of supply and demand. Media and printing were inelastic with respect to GDP per capita, with a positive correlation, while the utilities had a surprisingly negative relationship. All equations had

  8. Simulation Study on the Effect of Reduced Inputs of Artificial Neural Networks on the Predictive Performance of the Solar Energy System

    Directory of Open Access Journals (Sweden)

    Wahiba Yaïci

    2017-08-01

    Full Text Available In recent years, there has been a strong growth in solar power generation industries. The need for highly efficient and optimised solar thermal energy systems, stand-alone or grid connected photovoltaic systems, has substantially increased. This requires the development of efficient and reliable performance prediction capabilities of solar heat and power production over the day. This contribution investigates the effect of the number of input variables on both the accuracy and the reliability of the artificial neural network (ANN method for predicting the performance parameters of a solar energy system. This paper describes the ANN models and the optimisation process in detail for predicting performance. Comparison with experimental data from a solar energy system tested in Ottawa, Canada during two years under different weather conditions demonstrates the good prediction accuracy attainable with each of the models using reduced input variables. However, it is likely true that the degree of model accuracy would gradually decrease with reduced inputs. Overall, the results of this study demonstrate that the ANN technique is an effective approach for predicting the performance of highly non-linear energy systems. The suitability of the modelling approach using ANNs as a practical engineering tool in renewable energy system performance analysis and prediction is clearly demonstrated.

  9. Spatio-temporal variability in accretion and erosion of coastal foredunes in the Netherlands: regional climate and local topography.

    Science.gov (United States)

    Keijsers, Joep G S; Poortinga, Ate; Riksen, Michel J P M; Maroulis, Jerry

    2014-01-01

    Depending on the amount of aeolian sediment input and dune erosion, dune size and morphology change over time. Since coastal foredunes play an important role in the Dutch coastal defence, it is important to have good insight in the main factors that control these changes. In this paper the temporal variations in foredune erosion and accretion were studied in relation to proxies for aeolian transport potential and storminess using yearly elevation measurements from 1965 to 2012 for six sections of the Dutch coast. Longshore differences in the relative impacts of erosion and accretion were examined in relation to local beach width. The results show that temporal variability in foredune accretion and erosion is highest in narrow beach sections. Here, dune erosion alternates with accretion, with variability displaying strong correlations with yearly values of storminess (maximum sea levels). In wider beach sections, dune erosion is less frequent, with lower temporal variability and stronger correlations with time series of transport potential. In erosion dominated years, eroded volumes decrease from narrow to wider beaches. When accretion dominates, dune-volume changes are relatively constant alongshore. Dune erosion is therefore suggested to control spatial variability in dune-volume changes. On a scale of decades, the volume of foredunes tends to increase more on wider beaches. However, where widths exceed 200 to 300 m, this trend is no longer observed.

  10. Current Practices in Defining Seismic Input for Nuclear Facilities

    International Nuclear Information System (INIS)

    2015-05-01

    information is reliable and is adequately incorporated to the analysis of the soil response. An important recommendation of this study is that a sound and widely used approach should be provided for the seismic input for design and reevaluation of the nuclear power plants. (authors)

  11. Spatially-Resolved Influence of Temperature and Salinity on Stock and Recruitment Variability of Commercially Important Fishes in the North Sea.

    Directory of Open Access Journals (Sweden)

    Anna Akimova

    Full Text Available Understanding of the processes affecting recruitment of commercially important fish species is one of the major challenges in fisheries science. Towards this aim, we investigated the relation between North Sea hydrography (temperature and salinity and fish stock variables (recruitment, spawning stock biomass and pre-recruitment survival index for 9 commercially important fishes using spatially-resolved cross-correlation analysis. We used high-resolution (0.2° × 0.2° hydrographic data fields matching the maximal temporal extent of the fish population assessments (1948-2013. Our approach allowed for the identification of regions in the North Sea where environmental variables seem to be more influential on the fish stocks, as well as the regions of a lesser or nil influence. Our results confirmed previously demonstrated negative correlations between temperature and recruitment of cod and plaice and identified regions of the strongest correlations (German Bight for plaice and north-western North Sea for cod. We also revealed a positive correlation between herring spawning stock biomass and temperature in the Orkney-Shetland area, as well as a negative correlation between sole pre-recruitment survival index and temperature in the German Bight. A strong positive correlation between sprat stock variables and salinity in the central North Sea was also found. To our knowledge the results concerning correlations between North Sea hydrography and stocks' dynamics of herring, sole and sprat are novel. The new information about spatial distribution of the correlation provides an additional help to identify mechanisms underlying these correlations. As an illustration of the utility of these results for fishery management, an example is provided that incorporates the identified environmental covariates in stock-recruitment models.

  12. The Chandra Source Catalog: Source Variability

    Science.gov (United States)

    Nowak, Michael; Rots, A. H.; McCollough, M. L.; Primini, F. A.; Glotfelty, K. J.; Bonaventura, N. R.; Chen, J. C.; Davis, J. E.; Doe, S. M.; Evans, J. D.; Evans, I.; Fabbiano, G.; Galle, E. C.; Gibbs, D. G., II; Grier, J. D.; Hain, R.; Hall, D. M.; Harbo, P. N.; He, X.; Houck, J. C.; Karovska, M.; Lauer, J.; McDowell, J. C.; Miller, J. B.; Mitschang, A. W.; Morgan, D. L.; Nichols, J. S.; Plummer, D. A.; Refsdal, B. L.; Siemiginowska, A. L.; Sundheim, B. A.; Tibbetts, M. S.; van Stone, D. W.; Winkelman, S. L.; Zografou, P.

    2009-09-01

    The Chandra Source Catalog (CSC) contains fields of view that have been studied with individual, uninterrupted observations that span integration times ranging from 1 ksec to 160 ksec, and a large number of which have received (multiple) repeat observations days to years later. The CSC thus offers an unprecedented look at the variability of the X-ray sky over a broad range of time scales, and across a wide diversity of variable X-ray sources: stars in the local galactic neighborhood, galactic and extragalactic X-ray binaries, Active Galactic Nuclei, etc. Here we describe the methods used to identify and quantify source variability within a single observation, and the methods used to assess the variability of a source when detected in multiple, individual observations. Three tests are used to detect source variability within a single observation: the Kolmogorov-Smirnov test and its variant, the Kuiper test, and a Bayesian approach originally suggested by Gregory and Loredo. The latter test not only provides an indicator of variability, but is also used to create a best estimate of the variable lightcurve shape. We assess the performance of these tests via simulation of statistically stationary, variable processes with arbitrary input power spectral densities (here we concentrate on results of red noise simulations) at variety of mean count rates and fractional root mean square variabilities relevant to CSC sources. We also assess the false positive rate via simulations of constant sources whose sole source of fluctuation is Poisson noise. We compare these simulations to an assessment of the variability found in real CSC sources, and estimate the variability sensitivities of the CSC.

  13. A guidance on MELCOR input preparation : An input deck for Ul-Chin 3 and 4 Nuclear Power Plant

    Energy Technology Data Exchange (ETDEWEB)

    Cho, Song Won

    1997-02-01

    The objective of this study is to enhance the capability of assessing the severe accident sequence analyses and the containment behavior using MELCOR computer code and to provide the guideline of its efficient use. This report shows the method of the input deck preparation as well as the assessment strategy for the MELCOR code. MELCOR code is a fully integrated, engineering-level computer code that models the progression of severe accidents in light water reactor nuclear power plants. The code is being developed at Sandia National Laboratories for the U.S. NRC as a second generation plant risk assessment tool and the successor to the source term code package. The accident sequence of the reference input deck prepared in this study for Ulchin unit 3 and 4 nuclear power plants, is the total loss of feedwater (TLOFW) without any success of safety systems, which is similar to station blackout (TLMB). It is very useful to simulate a well-known sequence through the best estimated code or experiment, because the results of the simulation before core melt can be compared with the FSAR, but no data is available after core melt. The precalculation for the TLOFW using the reference input deck is performed successfully as expected. The other sequences will be carried out with minor changes in the reference input. This input deck will be improved continually by the adding of the safety systems not included in this input deck, and also through the sensitivity and uncertainty analyses. (author). 19 refs., 10 tabs., 55 figs.

  14. A guidance on MELCOR input preparation : An input deck for Ul-Chin 3 and 4 Nuclear Power Plant

    International Nuclear Information System (INIS)

    Cho, Song Won.

    1997-02-01

    The objective of this study is to enhance the capability of assessing the severe accident sequence analyses and the containment behavior using MELCOR computer code and to provide the guideline of its efficient use. This report shows the method of the input deck preparation as well as the assessment strategy for the MELCOR code. MELCOR code is a fully integrated, engineering-level computer code that models the progression of severe accidents in light water reactor nuclear power plants. The code is being developed at Sandia National Laboratories for the U.S. NRC as a second generation plant risk assessment tool and the successor to the source term code package. The accident sequence of the reference input deck prepared in this study for Ulchin unit 3 and 4 nuclear power plants, is the total loss of feedwater (TLOFW) without any success of safety systems, which is similar to station blackout (TLMB). It is very useful to simulate a well-known sequence through the best estimated code or experiment, because the results of the simulation before core melt can be compared with the FSAR, but no data is available after core melt. The precalculation for the TLOFW using the reference input deck is performed successfully as expected. The other sequences will be carried out with minor changes in the reference input. This input deck will be improved continually by the adding of the safety systems not included in this input deck, and also through the sensitivity and uncertainty analyses. (author). 19 refs., 10 tabs., 55 figs

  15. Ultrasonic variables affecting inspection

    International Nuclear Information System (INIS)

    Lautzenheiser, C.E.; Whiting, A.R.; McElroy, J.T.

    1977-01-01

    There are many variables which affect the detection of the effects and reproducibility of results when utilizing ultrasonic techniques. The most important variable is the procedure, as this document specifies, to a great extent, the controls that are exercised over the other variables. The most important variable is personnel with regards to training, qualification, integrity, data recording, and data analysis. Although the data is very limited, these data indicate that, if the procedure is carefully controlled, reliability of defect detection and reproducibility of results are both approximately 90 percent for reliability of detection, this applies to relatively small defects as reliability increases substantially as defect size increases above the recording limit. (author)

  16. High-Voltage-Input Level Translator Using Standard CMOS

    Science.gov (United States)

    Yager, Jeremy A.; Mojarradi, Mohammad M.; Vo, Tuan A.; Blalock, Benjamin J.

    2011-01-01

    proposed integrated circuit would translate (1) a pair of input signals having a low differential potential and a possibly high common-mode potential into (2) a pair of output signals having the same low differential potential and a low common-mode potential. As used here, "low" and "high" refer to potentials that are, respectively, below or above the nominal supply potential (3.3 V) at which standard complementary metal oxide/semiconductor (CMOS) integrated circuits are designed to operate. The input common-mode potential could lie between 0 and 10 V; the output common-mode potential would be 2 V. This translation would make it possible to process the pair of signals by use of standard 3.3-V CMOS analog and/or mixed-signal (analog and digital) circuitry on the same integrated-circuit chip. A schematic of the circuit is shown in the figure. Standard 3.3-V CMOS circuitry cannot withstand input potentials greater than about 4 V. However, there are many applications that involve low-differential-potential, high-common-mode-potential input signal pairs and in which standard 3.3-V CMOS circuitry, which is relatively inexpensive, would be the most appropriate circuitry for performing other functions on the integrated-circuit chip that handles the high-potential input signals. Thus, there is a need to combine high-voltage input circuitry with standard low-voltage CMOS circuitry on the same integrated-circuit chip. The proposed circuit would satisfy this need. In the proposed circuit, the input signals would be coupled into both a level-shifting pair and a common-mode-sensing pair of CMOS transistors. The output of the level-shifting pair would be fed as input to a differential pair of transistors. The resulting differential current output would pass through six standoff transistors to be mirrored into an output branch by four heterojunction bipolar transistors. The mirrored differential current would be converted back to potential by a pair of diode-connected transistors

  17. How citizen advisory boards provide input into major waste policy decisions

    International Nuclear Information System (INIS)

    Rogers, E.; Murakami, L.; Hanson, L.

    1995-01-01

    Volunteer citizen boards, such as Site Specific Advisory Boards, can be a very important key to success for the Department of Energy's (DOE's) Waste Management program. These boards can provide informed, independent recommendations reflecting the diversity of the community and its values. A successful volunteer process requires collaboration among regulators, DOE and other Boards; knowing how and when to interface with the broader public; understanding the diversity and representational issues of a citizens group; knowing the open-quotes ins and outsclose quotes of working with volunteers; education and training and most importantly, planning. Volunteers on a citizens board were created to tackle the big picture, policy decisions. The chair of the Rocky Flats Citizens Advisory Board will describe her Board's successes, including the challenges in reaching consensus agreements, as well as the need for integration with other boards and the sites' on-going public involvement programs to provide the input the department is seeking. Finally, one of the greatest challenges for the boards is interfacing with the greater public-at-large, seeing how the CAB has overcome this challenge and integrating broader public input into its decisions

  18. How citizen advisory boards provide input into major waste policy decisions

    Energy Technology Data Exchange (ETDEWEB)

    Rogers, E.; Murakami, L.; Hanson, L. [Rocky Flats Citizen Advisory Board, Westminster, CO (United States)

    1995-12-31

    Volunteer citizen boards, such as Site Specific Advisory Boards, can be a very important key to success for the Department of Energy`s (DOE`s) Waste Management program. These boards can provide informed, independent recommendations reflecting the diversity of the community and its values. A successful volunteer process requires collaboration among regulators, DOE and other Boards; knowing how and when to interface with the broader public; understanding the diversity and representational issues of a citizens group; knowing the {open_quotes}ins and outs{close_quotes} of working with volunteers; education and training and most importantly, planning. Volunteers on a citizens board were created to tackle the big picture, policy decisions. The chair of the Rocky Flats Citizens Advisory Board will describe her Board`s successes, including the challenges in reaching consensus agreements, as well as the need for integration with other boards and the sites` on-going public involvement programs to provide the input the department is seeking. Finally, one of the greatest challenges for the boards is interfacing with the greater public-at-large, seeing how the CAB has overcome this challenge and integrating broader public input into its decisions.

  19. Physical and geochemical drivers of CDOM variability near a natural seep site in the Gulf of Mexico

    Science.gov (United States)

    Edwards, C. R.; Powers, L.; Medeiros, P. M.

    2016-02-01

    Colored dissolved organic matter (CDOM) on the continental shelf and slope can serve as a marker for fresh water influence, indicate the presence of hydrocarbons, and provide important clues about nutrient content and organic matter cycling. Autonomous underwater vehicles such as gliders allow for subsurface measurement of CDOM fluorescence for weeks to months; these time series may be especially valuable in the northern Gulf of Mexico, where CDOM inputs of both terrestrial and oil and gas sources can be significant. Data from a recent glider deployment near a natural seep site (GC600) on the continental slope over 180km from shore suggest simultaneous influence of Mississippi plume water and hydrocarbon inputs in the upper 200m, with variability in fluorescence at a range of vertical and temporal scales. We will explore patterns in spatial and temporal variability of glider-measured hydrography, dissolved oxygen, and bio-optical data (CDOM, chlorophyll-a, backscatter fluorescence), and use their combination to infer a terrigenous and/or fossil fuel source(s). Taking advantage of a combination of satellite sea surface temperature, ocean color, wind, and data from moored and mobile platforms, we will examine physical controls on transport and vertical mixing of CDOM and the potential role of nonlinear mesoscale eddies, which can trap water in their interior and may transport river- or hydrocarbon-derived CDOM over long distances. The combined data set will be used to consider and potentially constrain the effect of photodegradation and other biogeochemical causes for CDOM fluorescence variability in the upper 200m.

  20. Water resources and environmental input-output analysis and its key study issues: a review

    Science.gov (United States)

    YANG, Z.; Xu, X.

    2013-12-01

    inland water resources IOA. Recent internal study references related to environmental input-output table, pollution discharge analysis and environmental impact assessment had taken the leading position. Pollution discharge analysis mainly aiming at CO2 discharge had been regard as a new hotspot of environmental IOA. Environmental impact assessment was an important direction of inland environmental IOA in recent years. Key study issues including Domestic Technology Assumption(DTA) and Sectoral Aggregation(SA) had been mentioned remarkably. It was pointed out that multiply multi-region input-output analysis(MIOA) may be helpful to solve DTA. Because there was little study using effective analysis tools to quantify the bias of SA and the exploration of the appropriate sectoral aggregation degree was scarce, research dedicating to explore and solve these two key issues was deemed to be urgently needed. According to the study status, several points of outlook were proposed in the end.

  1. Recreation studied from above : airphoto interpretation as input into land evaluation for recreation

    NARCIS (Netherlands)

    Zee, van der D.

    1992-01-01

    Recreation and tourism are of growing importance not only in the industrialized part of the world, but also In developing countries. Remote sensing and in particular airphoto interpretation can be used in several ways as input into land evaluation for recreation and tourism. An inventory of

  2. Ecosystem responses to reduced and oxidised nitrogen inputs in European terrestrial habitats

    International Nuclear Information System (INIS)

    Stevens, Carly J.; Manning, Pete; Berg, Leon J.L. van den; Graaf, Maaike C.C. de; Wamelink, G.W. Wieger; Boxman, Andries W.; Bleeker, Albert; Vergeer, Philippine; Arroniz-Crespo, Maria; Limpens, Juul; Lamers, Leon P.M.; Bobbink, Roland; Dorland, Edu

    2011-01-01

    While it is well established that ecosystems display strong responses to elevated nitrogen deposition, the importance of the ratio between the dominant forms of deposited nitrogen (NH x and NO y ) in determining ecosystem response is poorly understood. As large changes in the ratio of oxidised and reduced nitrogen inputs are occurring, this oversight requires attention. One reason for this knowledge gap is that plants experience a different NH x :NO y ratio in soil to that seen in atmospheric deposits because atmospheric inputs are modified by soil transformations, mediated by soil pH. Consequently species of neutral and alkaline habitats are less likely to encounter high NH 4 + concentrations than species from acid soils. We suggest that the response of vascular plant species to changing ratios of NH x :NO y deposits will be driven primarily by a combination of soil pH and nitrification rates. Testing this hypothesis requires a combination of experimental and survey work in a range of systems. - Changing ratios of NH x and NO y in deposition has important consequences for ecosystem function.

  3. Accidental cloning of a single-photon qubit in two-channel continuous-variable quantum teleportation

    International Nuclear Information System (INIS)

    Ide, Toshiki; Hofmann, Holger F.

    2007-01-01

    The information encoded in the polarization of a single photon can be transferred to a remote location by two-channel continuous-variable quantum teleportation. However, the finite entanglement used in the teleportation causes random changes in photon number. If more than one photon appears in the output, the continuous-variable teleportation accidentally produces clones of the original input photon. In this paper, we derive the polarization statistics of the N-photon output components and show that they can be decomposed into an optimal cloning term and completely unpolarized noise. We find that the accidental cloning of the input photon is nearly optimal at experimentally feasible squeezing levels, indicating that the loss of polarization information is partially compensated by the availability of clones

  4. Environmental impact assessment including indirect effects--a case study using input-output analysis

    International Nuclear Information System (INIS)

    Lenzen, Manfred; Murray, Shauna A.; Korte, Britta; Dey, Christopher J.

    2003-01-01

    Environmental impact assessment (EIA) is a process covered by several international standards, dictating that as many environmental aspects as possible should be identified in a project appraisal. While the ISO 14011 standard stipulates a broad-ranging study, off-site, indirect impacts are not specifically required for an Environmental Impact Statement (EIS). The reasons for this may relate to the perceived difficulty of measuring off-site impacts, or the assumption that these are a relatively insignificant component of the total impact. In this work, we describe a method that uses input-output analysis to calculate the indirect effects of a development proposal in terms of several indicator variables. The results of our case study of a Second Sydney Airport show that the total impacts are considerably higher than the on-site impacts for the indicators land disturbance, greenhouse gas emissions, water use, emissions of NO x and SO 2 , and employment. We conclude that employing input-output analysis enhances conventional EIA, as it allows for national and international effects to be taken into account in the decision-making process

  5. Remote media vision-based computer input device

    Science.gov (United States)

    Arabnia, Hamid R.; Chen, Ching-Yi

    1991-11-01

    In this paper, we introduce a vision-based computer input device which has been built at the University of Georgia. The user of this system gives commands to the computer without touching any physical device. The system receives input through a CCD camera; it is PC- based and is built on top of the DOS operating system. The major components of the input device are: a monitor, an image capturing board, a CCD camera, and some software (developed by use). These are interfaced with a standard PC running under the DOS operating system.

  6. Serotonin gating of cortical and thalamic glutamate inputs onto principal neurons of the basolateral amygdala.

    Science.gov (United States)

    Guo, Ji-Dong; O'Flaherty, Brendan M; Rainnie, Donald G

    2017-11-01

    The basolateral amygdala (BLA) is a key site for crossmodal association of sensory stimuli and an important relay in the neural circuitry of emotion. Indeed, the BLA receives substantial glutamatergic inputs from multiple brain regions including the prefrontal cortex and thalamic nuclei. Modulation of glutamatergic transmission in the BLA regulates stress- and anxiety-related behaviors. Serotonin (5-HT) also plays an important role in regulating stress-related behavior through activation of both pre- and postsynaptic 5-HT receptors. Multiple 5-HT receptors are expressed in the BLA, where 5-HT has been reported to modulate glutamatergic transmission. However, the 5-HT receptor subtype mediating this effect is not yet clear. The aim of this study was to use patch-clamp recordings from BLA neurons in an ex vivo slice preparation to examine 1) the effect of 5-HT on extrinsic sensory inputs, and 2) to determine if any pathway specificity exists in 5-HT regulation of glutamatergic transmission. Two independent input pathways into the BLA were stimulated: the external capsule to mimic cortical input, and the internal capsule to mimic thalamic input. Bath application of 5-HT reversibly reduced the amplitude of evoked excitatory postsynaptic currents (eEPSCs) induced by stimulation of both pathways. The decrease was associated with an increase in the paired-pulse ratio and coefficient of variation of eEPSC amplitude, suggesting 5-HT acts presynaptically. Moreover, the effect of 5-HT in both pathways was mimicked by the selective 5-HT 1B receptor agonist CP93129, but not by the 5-HT 1A receptor agonist 8-OH DPAT. Similarly the effect of exogenous 5-HT was blocked by the 5-HT 1B receptor antagonist GR55562, but not affected by the 5-HT 1A receptor antagonist WAY 100635 or the 5-HT 2 receptor antagonists pirenperone and MDL 100907. Together these data suggest 5-HT gates cortical and thalamic glutamatergic inputs into the BLA by activating presynaptic 5-HT 1B receptors

  7. The SSVEP-Based BCI Text Input System Using Entropy Encoding Algorithm

    Directory of Open Access Journals (Sweden)

    Yeou-Jiunn Chen

    2015-01-01

    Full Text Available The so-called amyotrophic lateral sclerosis (ALS or motor neuron disease (MND is a neurodegenerative disease with various causes. It is characterized by muscle spasticity, rapidly progressive weakness due to muscle atrophy, and difficulty in speaking, swallowing, and breathing. The severe disabled always have a common problem that is about communication except physical malfunctions. The steady-state visually evoked potential based brain computer interfaces (BCI, which apply visual stimulus, are very suitable to play the role of communication interface for patients with neuromuscular impairments. In this study, the entropy encoding algorithm is proposed to encode the letters of multilevel selection interface for BCI text input systems. According to the appearance frequency of each letter, the entropy encoding algorithm is proposed to construct a variable-length tree for the letter arrangement of multilevel selection interface. Then, the Gaussian mixture models are applied to recognize electrical activity of the brain. According to the recognition results, the multilevel selection interface guides the subject to spell and type the words. The experimental results showed that the proposed approach outperforms the baseline system, which does not consider the appearance frequency of each letter. Hence, the proposed approach is able to ease text input interface for patients with neuromuscular impairments.

  8. Improved quality of input data for maintenance optimization using expert judgment

    International Nuclear Information System (INIS)

    Oien, Knut

    1998-01-01

    Most maintenance optimization models need an estimate of the so-called 'naked' failure rate function as input. In practice it is very difficult to estimate the 'naked' failure rate, because overhauls and other preventive maintenance actions tend to 'corrupt' the recorded lifelengths. The purpose of this paper is to stress the importance of utilizing the knowledge of maintenance engineers, i.e., expert judgment, in addition to recorded equipment lifelengths, in order to get credible input data. We have shown that without utilizing expert judgment, the estimated mean time to failure may be strongly biased, often by a factor of 2-3, depending on the life distribution that is assumed. We recommend including a simple question about the mean remaining lifelength on the work-order forms. By this approach the knowledge of maintenance engineers may be incorporated in a simple and cost-effective way

  9. Effect of variable annual precipitation and nutrient input on nitrogen and phosphorus transport from two Midwestern agricultural watersheds

    Science.gov (United States)

    Kalkhoff, Stephen J.; Hubbard, Laura E.; Tomer, Mark D.; James, D.E.

    2016-01-01

    Precipitation patterns and nutrient inputs affect transport of nitrate (NO3-N) and phosphorus (TP) from Midwest watersheds. Nutrient concentrations and yields from two subsurface-drained watersheds, the Little Cobb River (LCR) in southern Minnesota and the South Fork Iowa River (SFIR) in northern Iowa, were evaluated during 1996–2007 to document relative differences in timings and amounts of nutrients transported. Both watersheds are located in the prairie pothole region, but the SFIR exhibits a longer growing season and more livestock production. The SFIR yielded significantly more NO3-N than the LCR watershed (31.2 versus 21.3 kg NO3-N ha− 1 y− 1). The SFIR watershed also yielded more TP than the LCR watershed (1.13 versus 0.51 kg TP ha− 1 yr− 1), despite greater TP concentrations in the LCR. About 65% of NO3-N and 50% of TP loads were transported during April–June, and < 20% of the annual loads were transported later in the growing season from July–September. Monthly NO3-N and TP loads peaked in April from the LCR but peaked in June from the SFIR; this difference was attributed to greater snowmelt runoff in the LCR. The annual NO3-N yield increased with increasing annual runoff at a similar rate in both watersheds, but the LCR watershed yielded less annual NO3-N than the SFIR for a similar annual runoff. These two watersheds are within 150 km of one another and have similar dominant agricultural systems, but differences in climate and cropping inputs affected amounts and timing of nutrient transport.

  10. Ranking of input parameters importance for BWR stability based on Ringhals-1

    International Nuclear Information System (INIS)

    Gajev, Ivan; Kozlowski, Tomasz; Xu, Yunlin; Downar, Thomas

    2011-01-01

    Unstable behavior of Boiling Water Reactors (BWRs) is known to occur during operation at certain power and flow conditions. Uncertainty calculations for BWR stability, based on the Wilks' formula, have been already done for the Ringhals-1 benchmark. In this work, these calculations have been used to identify and rank the most important parameters affecting the stability of the Ringhals-1 plant. The ranking has been done in two different ways and a comparison of these two methods has been demonstrated. Results show that the methods provide different, but meaningful evaluations of the ranking. (author)

  11. Reconstruction of an input function from a dynamic PET water image using multiple tissue curves

    Science.gov (United States)

    Kudomi, Nobuyuki; Maeda, Yukito; Yamamoto, Yuka; Nishiyama, Yoshihiro

    2016-08-01

    Quantification of cerebral blood flow (CBF) is important for the understanding of normal and pathologic brain physiology. When CBF is assessed using PET with {{\\text{H}}2} 15O or C15O2, its calculation requires an arterial input function, which generally requires invasive arterial blood sampling. The aim of the present study was to develop a new technique to reconstruct an image derived input function (IDIF) from a dynamic {{\\text{H}}2} 15O PET image as a completely non-invasive approach. Our technique consisted of using a formula to express the input using tissue curve with rate constant parameter. For multiple tissue curves extracted from the dynamic image, the rate constants were estimated so as to minimize the sum of the differences of the reproduced inputs expressed by the extracted tissue curves. The estimated rates were used to express the inputs and the mean of the estimated inputs was used as an IDIF. The method was tested in human subjects (n  =  29) and was compared to the blood sampling method. Simulation studies were performed to examine the magnitude of potential biases in CBF and to optimize the number of multiple tissue curves used for the input reconstruction. In the PET study, the estimated IDIFs were well reproduced against the measured ones. The difference between the calculated CBF values obtained using the two methods was small as around  PET imaging. This suggests the possibility of using a completely non-invasive technique to assess CBF in patho-physiological studies.

  12. Inputs and spatial distribution patterns of Cr in Jiaozhou Bay

    Science.gov (United States)

    Yang, Dongfang; Miao, Zhenqing; Huang, Xinmin; Wei, Linzhen; Feng, Ming

    2018-03-01

    Cr pollution in marine bays has been one of the critical environmental issues, and understanding the input and spatial distribution patterns is essential to pollution control. In according to the source strengths of the major pollution sources, the input patterns of pollutants to marine bay include slight, moderate and heavy, and the spatial distribution are corresponding to three block models respectively. This paper analyzed input patterns and distributions of Cr in Jiaozhou Bay, eastern China based on investigation on Cr in surface waters during 1979-1983. Results showed that the input strengths of Cr in Jiaozhou Bay could be classified as moderate input and slight input, and the input strengths were 32.32-112.30 μg L-1 and 4.17-19.76 μg L-1, respectively. The input patterns of Cr included two patterns of moderate input and slight input, and the horizontal distributions could be defined by means of Block Model 2 and Block Model 3, respectively. In case of moderate input pattern via overland runoff, Cr contents were decreasing from the estuaries to the bay mouth, and the distribution pattern was parallel. In case of moderate input pattern via marine current, Cr contents were decreasing from the bay mouth to the bay, and the distribution pattern was parallel to circular. The Block Models were able to reveal the transferring process of various pollutants, and were helpful to understand the distributions of pollutants in marine bay.

  13. Modal Parameter Identification from Responses of General Unknown Random Inputs

    DEFF Research Database (Denmark)

    Ibrahim, S. R.; Asmussen, J. C.; Brincker, Rune

    1996-01-01

    Modal parameter identification from ambient responses due to a general unknown random inputs is investigated. Existing identification techniques which are based on assumptions of white noise and or stationary random inputs are utilized even though the inputs conditions are not satisfied....... This is accomplished via adding. In cascade. A force cascade conversion to the structures system under consideration. The input to the force conversion system is white noise and the output of which is the actual force(s) applied to the structure. The white noise input(s) and the structures responses are then used...

  14. Enhancing the comparability of costing methods: cross-country variability in the prices of non-traded inputs to health programmes

    Directory of Open Access Journals (Sweden)

    Evans David B

    2006-04-01

    Full Text Available Abstract Background National and international policy makers have been increasing their focus on developing strategies to enable poor countries achieve the millennium development goals. This requires information on the costs of different types of health interventions and the resources needed to scale them up, either singly or in combinations. Cost data also guides decisions about the most appropriate mix of interventions in different settings, in view of the increasing, but still limited, resources available to improve health. Many cost and cost-effectiveness studies include only the costs incurred at the point of delivery to beneficiaries, omitting those incurred at other levels of the system such as administration, media, training and overall management. The few studies that have measured them directly suggest that they can sometimes account for a substantial proportion of total costs, so that their omission can result in biased estimates of the resources needed to run a programme or the relative cost-effectiveness of different choices. However, prices of different inputs used in the production of health interventions can vary substantially within a country. Basing cost estimates on a single price observation runs the risk that the results are based on an outlier observation rather than the typical costs of the input. Methods We first explore the determinants of the observed variation in the prices of selected "non-traded" intermediate inputs to health programmes – printed matter and media advertising, and water and electricity – accounting for variation within and across countries. We then use the estimated relationship to impute average prices for countries where limited data are available with uncertainty intervals. Results Prices vary across countries with GDP per capita and a number of determinants of supply and demand. Media and printing were inelastic with respect to GDP per capita, with a positive correlation, while the utilities

  15. Off-line learning from clustered input examples

    NARCIS (Netherlands)

    Marangi, Carmela; Solla, Sara A.; Biehl, Michael; Riegler, Peter; Marinaro, Maria; Tagliaferri, Roberto

    1996-01-01

    We analyze the generalization ability of a simple perceptron acting on a structured input distribution for the simple case of two clusters of input data and a linearly separable rule. The generalization ability computed for three learning scenarios: maximal stability, Gibbs, and optimal learning, is

  16. Input reduction for long-term morphodynamic simulations

    NARCIS (Netherlands)

    Walstra, D.J.R.; Ruessink, G.; Hoekstra, R.; Tonnon, P.K.

    2013-01-01

    Input reduction is imperative to long-term (> years) morphodynamic simulations to avoid excessive computation times. Here, we discuss the input-reduction framework for wave-dominated coastal settings introduced by Walstra et al. (2013). The framework comprised 4 steps, viz. (1) the selection of the

  17. Input Enhancement and L2 Question Formation.

    Science.gov (United States)

    White, Lydia; And Others

    1991-01-01

    Investigated the extent to which form-focused instruction and corrective feedback (i.e., "input enhancement"), provided within a primarily communicative program, contribute to learners' accuracy in question formation. Study results are interpreted as evidence that input enhancement can bring about genuine changes in learners' interlanguage…

  18. Smart-Guard: Defending User Input from Malware

    DEFF Research Database (Denmark)

    Denzel, Michael; Bruni, Alessandro; Ryan, Mark

    2016-01-01

    Trusted input techniques can profoundly enhance a variety of scenarios like online banking, electronic voting, Virtual Private Networks, and even commands to a server or Industrial Control System. To protect the system from malware of the sender’s computer, input needs to be reliably authenticated...

  19. ORIGNATE: PC input processor for ORIGEN-S

    International Nuclear Information System (INIS)

    Bowman, S.M.

    1992-01-01

    ORIGNATE is a personal computer program that serves as a user- friendly interface for the ORIGEN-S isotopic generation and depletion code. It is designed to assist an ORIGEN-S user in preparing an input file for execution of light-water-reactor fuel depletion and decay cases. Output from ORIGNATE is a card-image input file that may be uploaded to a mainframe computer to execute ORIGEN-S in SCALE-4. ORIGNATE features a pulldown menu system that accesses sophisticated data entry screens. The program allows the user to quickly set up an ORIGEN-S input file and perform error checking

  20. Methods and computer codes for probabilistic sensitivity and uncertainty analysis

    International Nuclear Information System (INIS)

    Vaurio, J.K.

    1985-01-01

    This paper describes the methods and applications experience with two computer codes that are now available from the National Energy Software Center at Argonne National Laboratory. The purpose of the SCREEN code is to identify a group of most important input variables of a code that has many (tens, hundreds) input variables with uncertainties, and do this without relying on judgment or exhaustive sensitivity studies. Purpose of the PROSA-2 code is to propagate uncertainties and calculate the distributions of interesting output variable(s) of a safety analysis code using response surface techniques, based on the same runs used for screening. Several applications are discussed, but the codes are generic, not tailored to any specific safety application code. They are compatible in terms of input/output requirements but also independent of each other, e.g., PROSA-2 can be used without first using SCREEN if a set of important input variables has first been selected by other methods. Also, although SCREEN can select cases to be run (by random sampling), a user can select cases by other methods if he so prefers, and still use the rest of SCREEN for identifying important input variables

  1. Associated and Mediating Variables Related to Job Satisfaction among Professionals from Mental Health Teams.

    Science.gov (United States)

    Fleury, Marie-Josée; Grenier, Guy; Bamvita, Jean-Marie; Chiocchio, François

    2018-06-01

    Using a structural analysis, this study examines the relationship between job satisfaction among 315 mental health professionals from the province of Quebec (Canada) and a wide range of variables related to provider characteristics, team characteristics, processes, and emergent states, and organizational culture. We used the Job Satisfaction Survey to assess job satisfaction. Our conceptual framework integrated numerous independent variables adapted from the input-mediator-output-input (IMOI) model and the Integrated Team Effectiveness Model (ITEM). The structural equation model predicted 47% of the variance of job satisfaction. Job satisfaction was associated with eight variables: strong team support, participation in the decision-making process, closer collaboration, fewer conflicts among team members, modest knowledge production (team processes), firm affective commitment, multifocal identification (emergent states) and belonging to the nursing profession (provider characteristics). Team climate had an impact on six job satisfaction variables (team support, knowledge production, conflicts, affective commitment, collaboration, and multifocal identification). Results show that team processes and emergent states were mediators between job satisfaction and team climate. To increase job satisfaction among professionals, health managers need to pursue strategies that foster a positive climate within mental health teams.

  2. Declaration of input sources in scientific research: should this practice be incorporated to organizational information management?

    Directory of Open Access Journals (Sweden)

    José Osvaldo De Sordi

    Full Text Available This research studies the declaration of input sources for research in scientific communications, more specifically, whether this practice of the academy may be considered a good example to be followed by organizations. Seven hypotheses address two dimensions of input sources: origin (primary or secondary and nature (data or information. It appears that the declaration of research inputs in the academy is problematic, mostly incomplete or inaccurate. This does not reduce the importance of this practice; it simply indicates that the academy should not be considered a privileged space, with wide dominance and practice excellence. Nevertheless, the information environment of organizations can learn and benefit from the experience of the scientific academy. From the analyses of the research sample, a set of procedures has been developed, which allowed organizational analysts and researchers to elaborate a complete and accurate analysis of the input sources to be declared in organizational or scientific communication.

  3. A Model to Determinate the Influence of Probability Density Functions (PDFs of Input Quantities in Measurements

    Directory of Open Access Journals (Sweden)

    Jesús Caja

    2016-06-01

    Full Text Available A method for analysing the effect of different hypotheses about the type of the input quantities distributions of a measurement model is presented here so that the developed algorithms can be simplified. As an example, a model of indirect measurements with optical coordinate measurement machine was employed to evaluate these different hypotheses. As a result of the different experiments, the assumption that the different variables of the model can be modelled as normal distributions is proved.

  4. Comparison of different snow model formulations and their responses to input uncertainties in the Upper Indus Basin

    Science.gov (United States)

    Pritchard, David; Fowler, Hayley; Forsythe, Nathan; O'Donnell, Greg; Rutter, Nick; Bardossy, Andras

    2017-04-01

    Snow and glacier melt in the mountainous Upper Indus Basin (UIB) sustain water supplies, irrigation networks, hydropower production and ecosystems in extensive downstream lowlands. Understanding hydrological and cryospheric sensitivities to climatic variability and change in the basin is therefore critical for local, national and regional water resources management. Assessing these sensitivities using numerical modelling is challenging, due to limitations in the quality and quantity of input and evaluation data, as well as uncertainties in model structures and parameters. This study explores how these uncertainties in inputs and process parameterisations affect distributed simulations of ablation in the complex climatic setting of the UIB. The role of model forcing uncertainties is explored using combinations of local observations, remote sensing and reanalysis - including the high resolution High Asia Refined Analysis - to generate multiple realisations of spatiotemporal model input fields. Forcing a range of model structures with these input fields then provides an indication of how different ablation parameterisations respond to uncertainties and perturbations in climatic drivers. Model structures considered include simple, empirical representations of melt processes through to physically based, full energy balance models with multi-physics options for simulating snowpack evolution (including an adapted version of FSM). Analysing model input and structural uncertainties in this way provides insights for methodological choices in climate sensitivity assessments of data-sparse, high mountain catchments. Such assessments are key for supporting water resource management in these catchments, particularly given the potential complications of enhanced warming through elevation effects or, in the case of the UIB, limited understanding of how and why local climate change signals differ from broader patterns.

  5. Fresh meteoric versus recirculated saline groundwater nutrient inputs into a subtropical estuary

    International Nuclear Information System (INIS)

    Sadat-Noori, Mahmood; Santos, Isaac R.; Tait, Douglas R.; Maher, Damien T.

    2016-01-01

    The role of groundwater in transporting nutrients to coastal aquatic systems has recently received considerable attention. However, the relative importance of fresh versus saline groundwater-derived nutrient inputs to estuaries and how these groundwater pathways may alter surface water N:P ratios remains poorly constrained. We performed detailed time series measurements of nutrients in a tidal estuary (Hat Head, NSW, Australia) and used radium to quantify the contribution of fresh and saline groundwater to total surface water estuarine exports under contrasting hydrological conditions (wet and dry season). Tidally integrated nutrient fluxes showed that the estuary was a source of nutrients to the coastal waters. Dissolved inorganic nitrogen (DIN) export was 7-fold higher than the average global areal flux rate for rivers likely due to the small catchment size, surrounding wetlands and high groundwater inputs. Fresh groundwater discharge was dominant in the wet season accounting for up to 45% of total dissolved nitrogen (TDN) and 48% of total dissolved phosphorus (TDP) estuarine exports. In the dry season, fresh and saline groundwater accounted for 21 and 33% of TDN export, respectively. The combined fresh and saline groundwater fluxes of NO_3, PO_4, NH_4, DON, DOP, TDN and TDP were estimated to account for 66, 58, 55, 31, 21, 53 and 47% of surface water exports, respectively. Groundwater-derived nitrogen inputs to the estuary were responsible for a change in the surface water N:P ratio from typical N-limiting conditions to P-limiting as predicted by previous studies. This shows the importance of both fresh and saline groundwater as a source of nutrients for coastal productivity and nutrient budgets of coastal waters. - Highlights: • Groundwater TDN and TDP fluxes account for 53 and 47% of surface water exports. • The estuary DIN export was 7-fold higher than the average global areal flux. • Fresh GW nutrient input dominated the wet season and saline GW the

  6. CREATING INPUT TABLES FROM WAPDEG FOR RIP

    International Nuclear Information System (INIS)

    K.G. Mon

    1998-01-01

    The purpose of this calculation is to create tables for input into RIP ver. 5.18 (Integrated Probabilistic Simulator for Environmental Systems) from WAPDEG ver. 3.06 (Waste Package Degradation) output. This calculation details the creation of the RIP input tables for TSPA-VA REV.00

  7. Input-output analysis in fertilizers sector. A case study of Turkey

    International Nuclear Information System (INIS)

    Karkacier, O.; Guelse, H.S.; Sayili, M.; Akca, H.

    1999-01-01

    The types of structural analysis in the input-output model known are forward and backwards ties. Fertilizer sector is tied forwardly agriculture, agri-business, chemistry, petro-chemistry and glass sector. In addition, it tied backwardly mining, chemistry, petro-chemistry, electricity, gas, water and transportation. The effect of backward tie of fertilizer sector is more important than its effect of the forward ties. In this study, by means of the year of 1979, 1985 and 1990 input-output table of Turkey the own situation of fertilizer industry and the production relation with other sectors of the economy have been tired to explain with forward and backwards ties. According to the result of the research it was determined that in 1990, (u j ) input coefficient of fertilizer sector is 69 %. That is, 69 percent of the product of fertilizer sector was used as an intermediate goods by other sectors. Therefore, 31 percent of goods produced by fertilizer sector was consumed as a final good. In addition, in this year, (w i ) intermediate use coefficient of fertilizer sector is 52 %. (w i ) intermediate use coefficient of fertilizer sector decreased from 1973 to 1990, as a result of this final use coefficient (1-w i ) increased. Refs. 5 (author)

  8. PROVIDING ENGLISH LANGUAGE INPUT: DECREASING STUDENTS’ ANXIETY IN READING COMPREHENSION PERFORMANCE

    Directory of Open Access Journals (Sweden)

    Elva Yohana

    2016-11-01

    Full Text Available The primary condition for successful in second or foreign language learning is providing an adequate environment. It is as a medium of increasing the students’ language exposure in order to be able to success in acquiring second or foreign language profciency. This study was designed to propose the adequate English language input that can decrease the students’ anxiety in reading comprehension performance. Of the four skills, somehow reading can be regarded as especially important because reading is assumed to be the central means for learning new information. Some students, however, still encounter many problems in reading. It is because of their anxiety when they are reading. Providing and creating an interesting-contextual reading material and gratifed teachers can make out this problem which occurs mostly in Indonesian’s classrooms. It revealed that the younger learners of English there do not received adequate amount of the target language input in their learning of English. Hence, it suggested the adoption of extensive reading programs as the most effective means in the creation of an input-rich environment in EFL learning contexts. Besides they also give suggestion to book writers and publisher to provide myriad books that appropriate and readable for their students.

  9. The economic impact of multifunctional agriculture in The Netherlands: A regional input-output model

    NARCIS (Netherlands)

    Heringa, P.W.; Heide, van der C.M.; Heijman, W.J.M.

    2012-01-01

    Multifunctional agriculture is a broad concept lacking a precise and uniform definition. Moreover, little is known about the societal importance of multifunctional agriculture. This paper is an empirical attempt to fill this gap. To this end, an input-output model is constructed for multifunctional

  10. Adaptive Backstepping-Based Neural Tracking Control for MIMO Nonlinear Switched Systems Subject to Input Delays.

    Science.gov (United States)

    Niu, Ben; Li, Lu

    2018-06-01

    This brief proposes a new neural-network (NN)-based adaptive output tracking control scheme for a class of disturbed multiple-input multiple-output uncertain nonlinear switched systems with input delays. By combining the universal approximation ability of radial basis function NNs and adaptive backstepping recursive design with an improved multiple Lyapunov function (MLF) scheme, a novel adaptive neural output tracking controller design method is presented for the switched system. The feature of the developed design is that different coordinate transformations are adopted to overcome the conservativeness caused by adopting a common coordinate transformation for all subsystems. It is shown that all the variables of the resulting closed-loop system are semiglobally uniformly ultimately bounded under a class of switching signals in the presence of MLF and that the system output can follow the desired reference signal. To demonstrate the practicability of the obtained result, an adaptive neural output tracking controller is designed for a mass-spring-damper system.

  11. PCBs and DDE, but not PBDEs, increase with trophic level and marine input in nestling bald eagles

    International Nuclear Information System (INIS)

    Hamish Elliott, Kyle; Cesh, Lillian S.; Dooley, Jessica A.; Letcher, Robert J.; Elliott, John E.

    2009-01-01

    Concentrations of persistent contaminants often vary widely among individuals within a population. We hypothesized that such variation was caused mainly by differences in diet (biomagnification) and in coastal systems by the tendency of marine systems to act as contaminant sinks. We examined the relationship between contaminant concentrations and stable isotope ratios in nestling plasma from an apex predator with a particularly broad diet. Our study included freshwater, estuarine, inshore and pelagic breeding sites. Bald eagles (Haliaeetus leucocephalus) at the pelagic marine sites showed high trophic level and marine input, eagles at the freshwater sites showed low trophic level and marine input, and eagles at the estuarine and inshore marine sites had intermediate values. The relationship between trophic level and marine input may reflect longer food chains in pelagic compared to terrestrial ecosystems. ΣPCBs and DDE concentrations generally increased with trophic level and marine input, with the exception of the freshwater sites, while ΣPBDEs, hydroxylated-PBDEs and hydroxylated-PCBs increased with marine input, but were independent of trophic level. The relationships for ΣPCBs and DDE were often slightly stronger with marine input than trophic level, suggesting that oceanographic processes may be more important than trophic level. At freshwater locations, spatial variation may be more important than trophic level due to the heterogeneity of contaminant profiles between feeding locations (lakes, rivers, agricultural fields). Adults had similar isotopic composition to their chicks but higher contamination. Based on nests where prey composition was determined independently, isotopic enrichment values for nestling plasma were 1.6 ± 0.1 (δ 15 N) and - 0.4 ±0.2 (δ 13 C). We conclude that trophic level and marine influence are significant factors influencing PCB and DDE concentrations in eagles. However, trophic level in particular did not influence PBDEs

  12. Importance of predictor variables for models of chemical function

    Data.gov (United States)

    U.S. Environmental Protection Agency — Importance of random forest predictors for all classification models of chemical function. This dataset is associated with the following publication: Isaacs , K., M....

  13. Optimal Design of a Push-Pull-Forward Half-Bridge (PPFHB) Bidirectional DC–DC Converter With Variable Input Voltage

    DEFF Research Database (Denmark)

    Zhang, Zhe; Thomsen, Ole Cornelius; Andersen, Michael A. E.

    2012-01-01

    This paper presents a low-cost bidirectional isolated dc–dc converte, derived from dual-active-bridge converter for the power sources with variable output voltage like supercapacitors. The proposed converter consists of push-pull-forward circuit half-bridge circuit (PPFHB) and a high-frequency tr......This paper presents a low-cost bidirectional isolated dc–dc converte, derived from dual-active-bridge converter for the power sources with variable output voltage like supercapacitors. The proposed converter consists of push-pull-forward circuit half-bridge circuit (PPFHB) and a high...

  14. INPUT-OUTPUT ANALYSIS : THE NEXT 25 YEARS

    NARCIS (Netherlands)

    Dietzenbacher, Erik; Lenzen, Manfred; Los, Bart; Guan, Dabo; Lahr, Michael L.; Sancho, Ferran; Suh, Sangwon; Yang, Cuihong; Sancho, S.

    2013-01-01

    This year marks the 25th anniversary of the International Input-Output Association and the 25th volume of Economic Systems Research. To celebrate this anniversary, a group of eight experts provide their views on the future of input-output. Looking forward, they foresee progress in terms of data

  15. Variance-based sensitivity indices for models with dependent inputs

    International Nuclear Information System (INIS)

    Mara, Thierry A.; Tarantola, Stefano

    2012-01-01

    Computational models are intensively used in engineering for risk analysis or prediction of future outcomes. Uncertainty and sensitivity analyses are of great help in these purposes. Although several methods exist to perform variance-based sensitivity analysis of model output with independent inputs only a few are proposed in the literature in the case of dependent inputs. This is explained by the fact that the theoretical framework for the independent case is set and a univocal set of variance-based sensitivity indices is defined. In the present work, we propose a set of variance-based sensitivity indices to perform sensitivity analysis of models with dependent inputs. These measures allow us to distinguish between the mutual dependent contribution and the independent contribution of an input to the model response variance. Their definition relies on a specific orthogonalisation of the inputs and ANOVA-representations of the model output. In the applications, we show the interest of the new sensitivity indices for model simplification setting. - Highlights: ► Uncertainty and sensitivity analyses are of great help in engineering. ► Several methods exist to perform variance-based sensitivity analysis of model output with independent inputs. ► We define a set of variance-based sensitivity indices for models with dependent inputs. ► Inputs mutual contributions are distinguished from their independent contributions. ► Analytical and computational tests are performed and discussed.

  16. CONSTRUCTION OF A DYNAMIC INPUT-OUTPUT MODEL WITH A HUMAN CAPITAL BLOCK

    Directory of Open Access Journals (Sweden)

    Baranov A. O.

    2017-03-01

    Full Text Available The accumulation of human capital is an important factor of economic growth. It seems to be useful to include «human capital» as a factor of a macroeconomic model, as it helps to take into account the quality differentiation of the workforce. Most of the models usually distinguish labor force by the levels of education, while some of the factors remain unaccounted. Among them are health status and culture development level, which influence productivity level as well as gross product reproduction. Inclusion of the human capital block to the interindustry model can help to make it more reliable for economic development forecasting. The article presents a mathematical description of the extended dynamic input-output model (DIOM with a human capital block. The extended DIOM is based on the Input-Output Model from The KAMIN system (the System of Integrated Analyses of Interindustrial Information developed at the Institute of Economics and Industrial Engineering of the Siberian Branch of the Academy of Sciences of the Russian Federation and at the Novosibirsk State University. The extended input-output model can be used to analyze and forecast development of Russian economy.

  17. Automated input data management in manufacturing process simulation

    OpenAIRE

    Ettefaghian, Alireza

    2015-01-01

    Input Data Management (IDM) is a time consuming and costly process for Discrete Event Simulation (DES) projects. Input Data Management is considered as the basis of real-time process simulation (Bergmann, Stelzer and Strassburger, 2011). According to Bengtsson et al. (2009), data input phase constitutes on the average about 31% of the time of an entire simulation project. Moreover, the lack of interoperability between manufacturing applications and simulation software leads to a high cost to ...

  18. Radioactive inputs to the North Sea and the Channel

    International Nuclear Information System (INIS)

    1984-01-01

    The subject is covered in sections: introduction (radioactivity; radioisotopes; discharges from nuclear establishments); data sources (statutory requirements); sources of liquid radioactive waste (figure showing location of principal sources of radioactive discharges; tables listing principal discharges by activity and by nature of radioisotope); Central Electricity Generating Board nuclear power stations; research and industrial establishments; Ministy of Defence establishments; other UK inputs of radioactive waste; total inputs to the North Sea and the Channel (direct inputs; river inputs; adjacent sea areas); conclusions. (U.K.)

  19. Nonlinear Methods to Assess Changes in Heart Rate Variability in Type 2 Diabetic Patients

    Energy Technology Data Exchange (ETDEWEB)

    Bhaskar, Roy, E-mail: imbhaskarall@gmail.com [Indian Institute of Technology (India); University of Connecticut, Farmington, CT (United States); Ghatak, Sobhendu [Indian Institute of Technology (India)

    2013-10-15

    Heart rate variability (HRV) is an important indicator of autonomic modulation of cardiovascular function. Diabetes can alter cardiac autonomic modulation by damaging afferent inputs, thereby increasing the risk of cardiovascular disease. We applied nonlinear analytical methods to identify parameters associated with HRV that are indicative of changes in autonomic modulation of heart function in diabetic patients. We analyzed differences in HRV patterns between diabetic and age-matched healthy control subjects using nonlinear methods. Lagged Poincaré plot, autocorrelation, and detrended fluctuation analysis were applied to analyze HRV in electrocardiography (ECG) recordings. Lagged Poincare plot analysis revealed significant changes in some parameters, suggestive of decreased parasympathetic modulation. The detrended fluctuation exponent derived from long-term fitting was higher than the short-term one in the diabetic population, which was also consistent with decreased parasympathetic input. The autocorrelation function of the deviation of inter-beat intervals exhibited a highly correlated pattern in the diabetic group compared with the control group. The HRV pattern significantly differs between diabetic patients and healthy subjects. All three statistical methods employed in the study may prove useful to detect the onset and extent of autonomic neuropathy in diabetic patients.

  20. Nonlinear Methods to Assess Changes in Heart Rate Variability in Type 2 Diabetic Patients

    International Nuclear Information System (INIS)

    Bhaskar, Roy; Ghatak, Sobhendu

    2013-01-01

    Heart rate variability (HRV) is an important indicator of autonomic modulation of cardiovascular function. Diabetes can alter cardiac autonomic modulation by damaging afferent inputs, thereby increasing the risk of cardiovascular disease. We applied nonlinear analytical methods to identify parameters associated with HRV that are indicative of changes in autonomic modulation of heart function in diabetic patients. We analyzed differences in HRV patterns between diabetic and age-matched healthy control subjects using nonlinear methods. Lagged Poincaré plot, autocorrelation, and detrended fluctuation analysis were applied to analyze HRV in electrocardiography (ECG) recordings. Lagged Poincare plot analysis revealed significant changes in some parameters, suggestive of decreased parasympathetic modulation. The detrended fluctuation exponent derived from long-term fitting was higher than the short-term one in the diabetic population, which was also consistent with decreased parasympathetic input. The autocorrelation function of the deviation of inter-beat intervals exhibited a highly correlated pattern in the diabetic group compared with the control group. The HRV pattern significantly differs between diabetic patients and healthy subjects. All three statistical methods employed in the study may prove useful to detect the onset and extent of autonomic neuropathy in diabetic patients

  1. Strategies of Transition to Sustainable Agriculture in Iran II- Inputs Replacement and Designing Agroecosystem

    Directory of Open Access Journals (Sweden)

    Alireza Koocheki

    2018-02-01

    Full Text Available Abstract Introduction Sustainable agricultural development is an important goal in economic planning and human development worldwide. A range of processes and relationships are transformed, beginning with aspects of basic soil structure, organic matter content, and diversity and activity of soil biota. Eventually, major changes also occur in the relationships among weed, insect, and disease populations, and in the balance between beneficial and pest organisms. Ultimately, nutrient dynamics and cycling, energy use efficiency, and overall system productivity are impacted. Measuring and monitoring these changes during the conversion period helps the farmer evaluate the success of the conversion process, and provides a framework to determine the requirements for sustainability. After improving resource use efficiency, replacement of ecological inputs with chemical inputs as second step and redesign of agro-ecosystems is as final step in transition of common to sustainable agriculture. The study was investigated to evaluation of Iran’s agricultural systems status. Materials and Methods Using organic and ecological inputs than chemicals is the second step for transition to sustainable agriculture. This study was performed to assess and measure the status of inputs replacement and agro-ecosystem designing based on ecological principle in Iran. For this purpose, we used 223 studied researches on agronomical and medicinal plants. After, they analyzed based on functional and structural characteristics and then used. Considering to the importance of multi-functionality in sustainable agriculture, in this study we considered the multiple managements for inputs replacement. The using functions in the study were: improving fertility and bio-chemical characteristics of soil, ecological managements of pest and diseases, reducing the energy usage, and increasing biodiversity. Using the organic and biological inputs, remaining the plant residual on soil, using

  2. Sensitivity of traffic input parameters on rutting performance of a flexible pavement using Mechanistic Empirical Pavement Design Guide

    Directory of Open Access Journals (Sweden)

    Nur Hossain

    2016-11-01

    Full Text Available The traffic input parameters in the Mechanistic Empirical Pavement Design Guide (MEPDG are: (a general traffic inputs, (b traffic volume adjustment factors, and (c axle load spectra (ALS. Of these three traffic inputs, the traffic volume adjustment factors specifically monthly adjustment factor (MAF and the ALS are widely considered to be important and sensitive factors, which can significantly affect design of and prediction of distress in flexible pavements. Therefore, the present study was undertaken to assess the sensitivity of ALS and MAF traffic inputs on rutting distress of a flexible pavement. The traffic data of four years (from 2008 to 2012 were collected from an instrumented test section on I-35 in Oklahoma. Site specific traffic input parameters were developed. It was observed that significant differences exist between the MEPDG default and developed site-specific traffic input values. However, the differences in the yearly ALS and MAF data, developed for these four years, were not found to be as significant when compared to one another. In addition, quarterly field rut data were measured on the test section and compared with the MEPDG predicted rut values using the default and developed traffic input values for different years. It was found that significant differences exist between the measured rut and the MEPDG (AASHTOWare-ME predicted rut when default values were used. Keywords: MEPDG, Rut, Level 1 inputs, Axle load spectra, Traffic input parameters, Sensitivity

  3. Dynamic interactions between hydrogeological and exposure parameters in daily dose prediction under uncertainty and temporal variability

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, Vikas, E-mail: vikas.kumar@urv.cat [Department of Chemical Engineering, Rovira i Virgili University, Tarragona 43007 (Spain); Barros, Felipe P.J. de [Sonny Astani Department of Civil and Environmental Engineering, University of Southern California, Los Angeles 90089, CA (United States); Schuhmacher, Marta [Department of Chemical Engineering, Rovira i Virgili University, Tarragona 43007 (Spain); Fernàndez-Garcia, Daniel; Sanchez-Vila, Xavier [Hydrogeology Group, Department of Geotechnical Engineering and Geosciences, University Politècnica de Catalunya-BarcelonaTech, Barcelona 08034 (Spain)

    2013-12-15

    Highlights: • Dynamic parametric interaction in daily dose prediction under uncertainty. • Importance of temporal dynamics associated with the dose. • Different dose experienced by different population cohorts as a function of time. • Relevance of uncertainty reduction in the input parameters shows temporal dynamism. -- Abstract: We study the time dependent interaction between hydrogeological and exposure parameters in daily dose predictions due to exposure of humans to groundwater contamination. Dose predictions are treated stochastically to account for an incomplete hydrogeological and geochemical field characterization, and an incomplete knowledge of the physiological response. We used a nested Monte Carlo framework to account for uncertainty and variability arising from both hydrogeological and exposure variables. Our interest is in the temporal dynamics of the total dose and their effects on parametric uncertainty reduction. We illustrate the approach to a HCH (lindane) pollution problem at the Ebro River, Spain. The temporal distribution of lindane in the river water can have a strong impact in the evaluation of risk. The total dose displays a non-linear effect on different population cohorts, indicating the need to account for population variability. We then expand the concept of Comparative Information Yield Curves developed earlier (see de Barros et al. [29]) to evaluate parametric uncertainty reduction under temporally variable exposure dose. Results show that the importance of parametric uncertainty reduction varies according to the temporal dynamics of the lindane plume. The approach could be used for any chemical to aid decision makers to better allocate resources towards reducing uncertainty.

  4. Non-perturbative inputs for gluon distributions in the hadrons

    International Nuclear Information System (INIS)

    Ermolaev, B.I.; Troyan, S.I.

    2017-01-01

    Description of hadronic reactions at high energies is conventionally done in the framework of QCD factorization. All factorization convolutions comprise non-perturbative inputs mimicking non-perturbative contributions and perturbative evolution of those inputs. We construct inputs for the gluon-hadron scattering amplitudes in the forward kinematics and, using the optical theorem, convert them into inputs for gluon distributions in the hadrons, embracing the cases of polarized and unpolarized hadrons. In the first place, we formulate mathematical criteria which any model for the inputs should obey and then suggest a model satisfying those criteria. This model is based on a simple reasoning: after emitting an active parton off the hadron, the remaining set of spectators becomes unstable and therefore it can be described through factors of the resonance type, so we call it the resonance model. We use it to obtain non-perturbative inputs for gluon distributions in unpolarized and polarized hadrons for all available types of QCD factorization: basic, K_T-and collinear factorizations. (orig.)

  5. SO2 policy and input substitution under spatial monopoly

    International Nuclear Information System (INIS)

    Gerking, Shelby; Hamilton, Stephen F.

    2010-01-01

    Following the U.S. Clean Air Act Amendments of 1990, electric utilities dramatically increased their utilization of low-sulfur coal from the Powder River Basin (PRB). Recent studies indicate that railroads hauling PRB coal exercise a substantial degree of market power and that relative price changes in the mining and transportation sectors were contributing factors to the observed pattern of input substitution. This paper asks the related question: To what extent does more stringent SO 2 policy stimulate input substitution from high-sulfur coal to low-sulfur coal when railroads hauling low-sulfur coal exercise spatial monopoly power? The question underpins the effectiveness of incentive-based environmental policies given the essential role of market performance in input, output, and abatement markets in determining the social cost of regulation. Our analysis indicates that environmental regulation leads to negligible input substitution effects when clean and dirty inputs are highly substitutable and the clean input market is mediated by a spatial monopolist. (author)

  6. Non-perturbative inputs for gluon distributions in the hadrons

    Energy Technology Data Exchange (ETDEWEB)

    Ermolaev, B.I. [Ioffe Physico-Technical Institute, Saint Petersburg (Russian Federation); Troyan, S.I. [St. Petersburg Institute of Nuclear Physics, Gatchina (Russian Federation)

    2017-03-15

    Description of hadronic reactions at high energies is conventionally done in the framework of QCD factorization. All factorization convolutions comprise non-perturbative inputs mimicking non-perturbative contributions and perturbative evolution of those inputs. We construct inputs for the gluon-hadron scattering amplitudes in the forward kinematics and, using the optical theorem, convert them into inputs for gluon distributions in the hadrons, embracing the cases of polarized and unpolarized hadrons. In the first place, we formulate mathematical criteria which any model for the inputs should obey and then suggest a model satisfying those criteria. This model is based on a simple reasoning: after emitting an active parton off the hadron, the remaining set of spectators becomes unstable and therefore it can be described through factors of the resonance type, so we call it the resonance model. We use it to obtain non-perturbative inputs for gluon distributions in unpolarized and polarized hadrons for all available types of QCD factorization: basic, K{sub T}-and collinear factorizations. (orig.)

  7. CBM first-level event selector input interface

    Energy Technology Data Exchange (ETDEWEB)

    Hutter, Dirk [Frankfurt Institute for Advanced Studies, Goethe University, Frankfurt (Germany); Collaboration: CBM-Collaboration

    2016-07-01

    The CBM First-level Event Selector (FLES) is the central event selection system of the upcoming CBM experiment at FAIR. Designed as a high-performance computing cluster, its task is an online analysis of the physics data at a total data rate exceeding 1 TByte/s. To allow efficient event selection, the FLES performs timeslice building, which combines the data from all given input links to self-contained, overlapping processing intervals and distributes them to compute nodes. Partitioning the input data streams into specialized containers allows to perform this task very efficiently. The FLES Input Interface defines the linkage between FEE and FLES data transport framework. Utilizing a custom FPGA board, it receives data via optical links, prepares them for subsequent timeslice building, and transfers the data via DMA to the PC's memory. An accompanying HDL module implements the front-end logic interface and FLES link protocol in the front-end FPGAs. Prototypes of all Input Interface components have been implemented and integrated into the FLES framework. In contrast to earlier prototypes, which included components to work without a FPGA layer between FLES and FEE, the structure matches the foreseen final setup. This allows the implementation and evaluation of the final CBM read-out chain. An overview of the FLES Input Interface as well as studies on system integration and system start-up are presented.

  8. Pulsed flows, tributary inputs, and food web structure in a highly regulated river

    Science.gov (United States)

    Sabo, John; Caron, Melanie; Doucett, Richard R.; Dibble, Kimberly L.; Ruhi, Albert; Marks, Jane; Hungate, Bruce; Kennedy, Theodore A.

    2018-01-01

    1.Dams disrupt the river continuum, altering hydrology, biodiversity, and energy flow. Although research indicates that tributary inputs have the potential to dilute these effects, knowledge at the food web level is still scarce.2.Here we examined the riverine food web structure of the Colorado River below Glen Canyon Dam, focusing on organic matter sources, trophic diversity, and food chain length. We asked how these components respond to pulsed flows from tributaries following monsoon thunderstorms that seasonally increase streamflow in the American Southwest.3.Tributaries increased the relative importance of terrestrial organic matter, particularly during the wet season below junctures of key tributaries. This contrasted with the algal-based food web present immediately below Glen Canyon Dam.4.Tributary inputs during the monsoon also increased trophic diversity and food chain length: food chain length peaked below the confluence with the largest tributary (by discharge) in Grand Canyon, increasing by >1 trophic level over a 4-5 kilometre reach possibly due to aquatic prey being flushed into the mainstem during heavy rain events.5.Our results illustrate that large tributaries can create seasonal discontinuities, influencing riverine food web structure in terms of allochthony, food web diversity, and food chain length.6.Synthesis and applications. Pulsed flows from unregulated tributaries following seasonal monsoon rains increase the importance of terrestrially-derived organic matter in large, regulated river food webs, increasing food chain length and trophic diversity downstream of tributary inputs. Protecting unregulated tributaries within hydropower cascades may be important if we are to mitigate food web structure alteration due to flow regulation by large dams. This is critical in the light of global hydropower development, especially in megadiverse, developing countries where dam placement (including completed and planned structures) is in tributaries.

  9. Approaches and Tools Used to Teach the Computer Input/Output Subsystem: A Survey

    Science.gov (United States)

    Larraza-Mendiluze, Edurne; Garay-Vitoria, Nestor

    2015-01-01

    This paper surveys how the computer input/output (I/O) subsystem is taught in introductory undergraduate courses. It is important to study the educational process of the computer I/O subsystem because, in the curricula recommendations, it is considered a core topic in the area of knowledge of computer architecture and organization (CAO). It is…

  10. PREPAR: a user-friendly preprocessor to create AIRDOS-EPA input data sets

    International Nuclear Information System (INIS)

    Sjoreen, A.L.; Miller, C.W.; Nelson, C.B.

    1984-01-01

    PREPAR is a FORTRAN program designed to simplify the preparation of input for the AIRDOS-EPA computer code. PREPAR was designed to provide a method for data entry that is both logical and flexible. It also provides default values for all variables, so the user needs only to enter those data for which the defaults should be changed. Data are entered either unformatted or via a user-selected format. A separate file of the nuclide-specific data needed by AIRDOS-EPA is read by PREPAR. Two utility programs, EXTRAC and RADLST, were written to create and list this file. PREPAR writes the file needed to run AIRDOS-EPA and writes a listing of that file

  11. Spatial and temporal variability of sediment deposition on artificial-lawn traps in a floodplain of the River Elbe

    Energy Technology Data Exchange (ETDEWEB)

    Baborowski, M. [Department of River Ecology, Helmholtz Centre for Environmental Research - UFZ, Brueckstrasse 3a, 39114 Magdeburg (Germany)]. E-mail: martina.baborowski@ufz.de; Buettner, O. [Department of Lake Research, Helmholtz Centre for Environmental Research - UFZ, Brueckstrasse 3a, 39114 Magdeburg (Germany); Morgenstern, P. [Department of Analytical Chemistry, Helmholtz Centre for Environmental Research - UFZ, Permoserstrasse 15, 04318 Leipzig (Germany); Krueger, F. [ELANA Boden Wasser Monitoring, Dorfstrasse 55, 39615 Falkenberg (Germany); Lobe, I. [Department of River Ecology, Helmholtz Centre for Environmental Research - UFZ, Brueckstrasse 3a, 39114 Magdeburg (Germany); Rupp, H. [Department of Soil Physics, Helmholtz Centre for Environmental Research - UFZ, Dorfstrasse 55, 39615 Falkenberg (Germany); Tuempling, W. v. [Department of River Ecology, Helmholtz Centre for Environmental Research - UFZ, Brueckstrasse 3a, 39114 Magdeburg (Germany)

    2007-08-15

    Artificial-lawn mats were used as sediment traps in floodplains to measure sediment input and composition during flood events. To estimate the natural variability, 10 traps were installed during two flood waves at three different morphological units in a meander loop of the River Elbe. The geochemical composition of deposited and suspended matter was compared. The sediment input showed weak correlations with concentration and composition of river water. It also correlated poorly with flood duration and level as well as distance of trap position from the main river. This is due to the high variability of the inundation, different morphological conditions and the variability of sources. The composition of the deposits and the suspended matter in the river water was comparable. Hence, for the investigated river reach, the expected pollution of the floodplain sediments can be derived from the pollution of the suspended matter in the river during the flood wave. - The deposition of polluted sediments on floodplains is characterised by a high local variability.

  12. Spatial and temporal variability of sediment deposition on artificial-lawn traps in a floodplain of the River Elbe

    International Nuclear Information System (INIS)

    Baborowski, M.; Buettner, O.; Morgenstern, P.; Krueger, F.; Lobe, I.; Rupp, H.; Tuempling, W. v.

    2007-01-01

    Artificial-lawn mats were used as sediment traps in floodplains to measure sediment input and composition during flood events. To estimate the natural variability, 10 traps were installed during two flood waves at three different morphological units in a meander loop of the River Elbe. The geochemical composition of deposited and suspended matter was compared. The sediment input showed weak correlations with concentration and composition of river water. It also correlated poorly with flood duration and level as well as distance of trap position from the main river. This is due to the high variability of the inundation, different morphological conditions and the variability of sources. The composition of the deposits and the suspended matter in the river water was comparable. Hence, for the investigated river reach, the expected pollution of the floodplain sediments can be derived from the pollution of the suspended matter in the river during the flood wave. - The deposition of polluted sediments on floodplains is characterised by a high local variability

  13. Selection of input devices and controls for modern process control consoles

    International Nuclear Information System (INIS)

    Hasenfuss, O.; Zimmermann, R.

    1975-06-01

    In modern process control consoles man-machine communication is realized more and more by computer driven CRT displays, the most efficient communication system today. This paper describes the most important input devices and controls for such control consoles. A certain number of facts are given, which should be considered during the selection. The aptitude of the described devices for special tasks is discussed and recommendations are given for carrying out a selection. (orig.) [de

  14. Effectiveness of cattail ('Typha' spp. management techniques depends on exogenous nitrogen inputs

    Directory of Open Access Journals (Sweden)

    Kenneth J. Elgersma

    2017-05-01

    nutrient inputs is an important component of an effective management strategy.

  15. Effects of Input Data Content on the Uncertainty of Simulating Water Resources

    Directory of Open Access Journals (Sweden)

    Carla Camargos

    2018-05-01

    Full Text Available The widely used, partly-deterministic Soil and Water Assessment Tool (SWAT requires a large amount of spatial input data, such as a digital elevation model (DEM, land use, and soil maps. Modelers make an effort to apply the most specific data possible for the study area to reflect the heterogeneous characteristics of landscapes. Regional data, especially with fine resolution, is often preferred. However, such data is not always available and can be computationally demanding. Despite being coarser, global data are usually free and available to the public. Previous studies revealed the importance for single investigations of different input maps. However, it remains unknown whether higher-resolution data can lead to reliable results. This study investigates how global and regional input datasets affect parameter uncertainty when estimating river discharges. We analyze eight different setups for the SWAT model for a catchment in Luxembourg, combining different land-use, elevation, and soil input data. The Metropolis–Hasting Markov Chain Monte Carlo (MCMC algorithm is used to infer posterior model parameter uncertainty. We conclude that our higher resolved DEM improves the general model performance in reproducing low flows by 10%. The less detailed soil-map improved the fit of low flows by 25%. In addition, more detailed land-use maps reduce the bias of the model discharge simulations by 50%. Also, despite presenting similar parameter uncertainty (P-factor ranging from 0.34 to 0.41 and R-factor from 0.41 to 0.45 for all setups, the results show a disparate parameter posterior distribution. This indicates that no assessment of all sources of uncertainty simultaneously is compensated by the fitted parameter values. We conclude that our result can give some guidance for future SWAT applications in the selection of the degree of detail for input data.

  16. Multi-Input Convolutional Neural Network for Flower Grading

    Directory of Open Access Journals (Sweden)

    Yu Sun

    2017-01-01

    Full Text Available Flower grading is a significant task because it is extremely convenient for managing the flowers in greenhouse and market. With the development of computer vision, flower grading has become an interdisciplinary focus in both botany and computer vision. A new dataset named BjfuGloxinia contains three quality grades; each grade consists of 107 samples and 321 images. A multi-input convolutional neural network is designed for large scale flower grading. Multi-input CNN achieves a satisfactory accuracy of 89.6% on the BjfuGloxinia after data augmentation. Compared with a single-input CNN, the accuracy of multi-input CNN is increased by 5% on average, demonstrating that multi-input convolutional neural network is a promising model for flower grading. Although data augmentation contributes to the model, the accuracy is still limited by lack of samples diversity. Majority of misclassification is derived from the medium class. The image processing based bud detection is useful for reducing the misclassification, increasing the accuracy of flower grading to approximately 93.9%.

  17. Fertilizing growth: Agricultural inputs and their effects in economic development.

    Science.gov (United States)

    McArthur, John W; McCord, Gordon C

    2017-07-01

    This paper estimates the role of agronomic inputs in cereal yield improvements and the consequences for countries' processes of structural change. The results suggest a clear role for fertilizer, modern seeds and water in boosting yields. We then test for respective empirical links between agricultural yields and economic growth, labor share in agriculture and non-agricultural value added per worker. The identification strategy includes a novel instrumental variable that exploits the unique economic geography of fertilizer production and transport costs to countries' agricultural heartlands. We estimate that a half ton increase in staple yields generates a 14 to 19 percent higher GDP per capita and a 4.6 to 5.6 percentage point lower labor share in agriculture five years later. The results suggest a strong role for agricultural productivity as a driver of structural change.

  18. Effect of Climate Variability on Crop Income in Central Ethiopia

    Directory of Open Access Journals (Sweden)

    Arega Shumetie Ademe

    2017-12-01

    Full Text Available Ethiopian agriculture is a vulnerable sector from effects of climate variability. This study identified how strong is the effect of climate variability on smallholders’ crop income in Central highlands and Arssi grain plough farming systems of the country. The unbalanced panel data (1994-2014 of the study collected for eight rounds analysed through fixed effect regression. The model result shows that successive increment of crop season rainfall keeping the temperature constant has negative and significant effect on households’ crop income in the study area. The crop income responds similarly for temperature increment if the rainfall remains constant. Given this, simultaneous increment of the two climate related inputs has positive and significant effect on crop income. Other variables like flood, frost, storm, and rainfall inconsistency in the onset and cessation time affected households’ crop income negatively and significantly. Similarly, draught power and human labour, which are critical inputs in the crop production of Ethiopian smallholders, have positive and significant effect on crop income as to the model result. Thus, this study recommended that there should be supplementing the rainfall through irrigation, check dam and other activities to have consistent water supply for the crop production that enable smallholders to collect better income. Additionally, negative effect of temperature increment should be curved through adopting long lasting strategies like afforestation.

  19. Input Shaping to Reduce Solar Array Structural Vibrations

    Science.gov (United States)

    Doherty, Michael J.; Tolson, Robert J.

    1998-01-01

    Structural vibrations induced by actuators can be minimized using input shaping. Input shaping is a feedforward method in which actuator commands are convolved with shaping functions to yield a shaped set of commands. These commands are designed to perform the maneuver while minimizing the residual structural vibration. In this report, input shaping is extended to stepper motor actuators. As a demonstration, an input-shaping technique based on pole-zero cancellation was used to modify the Solar Array Drive Assembly (SADA) actuator commands for the Lewis satellite. A series of impulses were calculated as the ideal SADA output for vibration control. These impulses were then discretized for use by the SADA stepper motor actuator and simulated actuator outputs were used to calculate the structural response. The effectiveness of input shaping is limited by the accuracy of the knowledge of the modal frequencies. Assuming perfect knowledge resulted in significant vibration reduction. Errors of 10% in the modal frequencies caused notably higher levels of vibration. Controller robustness was improved by incorporating additional zeros in the shaping function. The additional zeros did not require increased performance from the actuator. Despite the identification errors, the resulting feedforward controller reduced residual vibrations to the level of the exactly modeled input shaper and well below the baseline cases. These results could be easily applied to many other vibration-sensitive applications involving stepper motor actuators.

  20. An Approach to Sensorless Detection of Human Input Torque and Its Application to Power Assist Motion in Electric Wheelchair

    Science.gov (United States)

    Kaida, Yukiko; Murakami, Toshiyuki

    A wheelchair is an important apparatus of mobility for people with disability. Power-assist motion in an electric wheelchair is to expand the operator's field of activities. This paper describes force sensorless detection of human input torque. Reaction torque estimation observer calculates the total disturbance torque first. Then, the human input torque is extracted from the estimated disturbance. In power-assist motion, assist torque is synthesized according to the product of assist gain and the average torque of the right and left input torque. Finally, the proposed method is verified through the experiments of power-assist motion.