Sample records for additional input parameters

  1. Practical input optimization for aircraft parameter estimation experiments. Ph.D. Thesis, 1990

    NASA Technical Reports Server (NTRS)

    Morelli, Eugene A.

    1993-01-01

    The object of this research was to develop an algorithm for the design of practical, optimal flight test inputs for aircraft parameter estimation experiments. A general, single pass technique was developed which allows global optimization of the flight test input design for parameter estimation using the principles of dynamic programming with the input forms limited to square waves only. Provision was made for practical constraints on the input, including amplitude constraints, control system dynamics, and selected input frequency range exclusions. In addition, the input design was accomplished while imposing output amplitude constraints required by model validity and considerations of safety during the flight test. The algorithm has multiple input design capability, with optional inclusion of a constraint that only one control move at a time, so that a human pilot can implement the inputs. It is shown that the technique can be used to design experiments for estimation of open loop model parameters from closed loop flight test data. The report includes a new formulation of the optimal input design problem, a description of a new approach to the solution, and a summary of the characteristics of the algorithm, followed by three example applications of the new technique which demonstrate the quality and expanded capabilities of the input designs produced by the new technique. In all cases, the new input design approach showed significant improvement over previous input design methods in terms of achievable parameter accuracies.

  2. Effects of control inputs on the estimation of stability and control parameters of a light airplane

    NASA Technical Reports Server (NTRS)

    Cannaday, R. L.; Suit, W. T.

    1977-01-01

    The maximum likelihood parameter estimation technique was used to determine the values of stability and control derivatives from flight test data for a low-wing, single-engine, light airplane. Several input forms were used during the tests to investigate the consistency of parameter estimates as it relates to inputs. These consistencies were compared by using the ensemble variance and estimated Cramer-Rao lower bound. In addition, the relationship between inputs and parameter correlations was investigated. Results from the stabilator inputs are inconclusive but the sequence of rudder input followed by aileron input or aileron followed by rudder gave more consistent estimates than did rudder or ailerons individually. Also, square-wave inputs appeared to provide slightly improved consistency in the parameter estimates when compared to sine-wave inputs.

  3. Macroscopic singlet oxygen model incorporating photobleaching as an input parameter

    NASA Astrophysics Data System (ADS)

    Kim, Michele M.; Finlay, Jarod C.; Zhu, Timothy C.

    2015-03-01

    A macroscopic singlet oxygen model for photodynamic therapy (PDT) has been used extensively to calculate the reacted singlet oxygen concentration for various photosensitizers. The four photophysical parameters (ξ, σ, β, δ) and threshold singlet oxygen dose ([1O2]r,sh) can be found for various drugs and drug-light intervals using a fitting algorithm. The input parameters for this model include the fluence, photosensitizer concentration, optical properties, and necrosis radius. An additional input variable of photobleaching was implemented in this study to optimize the results. Photobleaching was measured by using the pre-PDT and post-PDT sensitizer concentrations. Using the RIF model of murine fibrosarcoma, mice were treated with a linear source with fluence rates from 12 - 150 mW/cm and total fluences from 24 - 135 J/cm. The two main drugs investigated were benzoporphyrin derivative monoacid ring A (BPD) and 2-[1-hexyloxyethyl]-2-devinyl pyropheophorbide-a (HPPH). Previously published photophysical parameters were fine-tuned and verified using photobleaching as the additional fitting parameter. Furthermore, photobleaching can be used as an indicator of the robustness of the model for the particular mouse experiment by comparing the experimental and model-calculated photobleaching ratio.

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

    NASA Astrophysics Data System (ADS)

    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

  5. Flight Test Validation of Optimal Input Design and Comparison to Conventional Inputs

    NASA Technical Reports Server (NTRS)

    Morelli, Eugene A.

    1997-01-01

    A technique for designing optimal inputs for aerodynamic parameter estimation was flight tested on the F-18 High Angle of Attack Research Vehicle (HARV). Model parameter accuracies calculated from flight test data were compared on an equal basis for optimal input designs and conventional inputs at the same flight condition. In spite of errors in the a priori input design models and distortions of the input form by the feedback control system, the optimal inputs increased estimated parameter accuracies compared to conventional 3-2-1-1 and doublet inputs. In addition, the tests using optimal input designs demonstrated enhanced design flexibility, allowing the optimal input design technique to use a larger input amplitude to achieve further increases in estimated parameter accuracy without departing from the desired flight test condition. This work validated the analysis used to develop the optimal input designs, and demonstrated the feasibility and practical utility of the optimal input design technique.

  6. Estimation and impact assessment of input and parameter uncertainty in predicting groundwater flow with a fully distributed model

    NASA Astrophysics Data System (ADS)

    Touhidul Mustafa, Syed Md.; Nossent, Jiri; Ghysels, Gert; Huysmans, Marijke

    2017-04-01

    Transient numerical groundwater flow models have been used to understand and forecast groundwater flow systems under anthropogenic and climatic effects, but the reliability of the predictions is strongly influenced by different sources of uncertainty. Hence, researchers in hydrological sciences are developing and applying methods for uncertainty quantification. Nevertheless, spatially distributed flow models pose significant challenges for parameter and spatially distributed input estimation and uncertainty quantification. In this study, we present a general and flexible approach for input and parameter estimation and uncertainty analysis of groundwater models. The proposed approach combines a fully distributed groundwater flow model (MODFLOW) with the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm. To avoid over-parameterization, the uncertainty of the spatially distributed model input has been represented by multipliers. The posterior distributions of these multipliers and the regular model parameters were estimated using DREAM. The proposed methodology has been applied in an overexploited aquifer in Bangladesh where groundwater pumping and recharge data are highly uncertain. The results confirm that input uncertainty does have a considerable effect on the model predictions and parameter distributions. Additionally, our approach also provides a new way to optimize the spatially distributed recharge and pumping data along with the parameter values under uncertain input conditions. It can be concluded from our approach that considering model input uncertainty along with parameter uncertainty is important for obtaining realistic model predictions and a correct estimation of the uncertainty bounds.

  7. Evaluation of severe accident risks: Quantification of major input parameters: MAACS (MELCOR Accident Consequence Code System) input

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

    Sprung, J.L.; Jow, H-N; Rollstin, J.A.

    1990-12-01

    Estimation of offsite accident consequences is the customary final step in a probabilistic assessment of the risks of severe nuclear reactor accidents. Recently, the Nuclear Regulatory Commission reassessed the risks of severe accidents at five US power reactors (NUREG-1150). Offsite accident consequences for NUREG-1150 source terms were estimated using the MELCOR Accident Consequence Code System (MACCS). Before these calculations were performed, most MACCS input parameters were reviewed, and for each parameter reviewed, a best-estimate value was recommended. This report presents the results of these reviews. Specifically, recommended values and the basis for their selection are presented for MACCS atmospheric andmore » biospheric transport, emergency response, food pathway, and economic input parameters. Dose conversion factors and health effect parameters are not reviewed in this report. 134 refs., 15 figs., 110 tabs.« less

  8. 40 CFR 97.76 - Additional requirements to provide heat input data.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... heat input data. 97.76 Section 97.76 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY... Monitoring and Reporting § 97.76 Additional requirements to provide heat input data. The owner or operator of... a flow system shall also monitor and report heat input rate at the unit level using the procedures...

  9. 40 CFR 97.76 - Additional requirements to provide heat input data.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... heat input data. 97.76 Section 97.76 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY... Monitoring and Reporting § 97.76 Additional requirements to provide heat input data. The owner or operator of... a flow system shall also monitor and report heat input rate at the unit level using the procedures...

  10. 40 CFR 97.76 - Additional requirements to provide heat input data.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... heat input data. 97.76 Section 97.76 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY... Monitoring and Reporting § 97.76 Additional requirements to provide heat input data. The owner or operator of... a flow system shall also monitor and report heat input rate at the unit level using the procedures...

  11. 40 CFR 97.76 - Additional requirements to provide heat input data.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... heat input data. 97.76 Section 97.76 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY... Monitoring and Reporting § 97.76 Additional requirements to provide heat input data. The owner or operator of... a flow system shall also monitor and report heat input rate at the unit level using the procedures...

  12. 40 CFR 97.76 - Additional requirements to provide heat input data.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... heat input data. 97.76 Section 97.76 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY... Monitoring and Reporting § 97.76 Additional requirements to provide heat input data. The owner or operator of... a flow system shall also monitor and report heat input rate at the unit level using the procedures...

  13. Suggestions for CAP-TSD mesh and time-step input parameters

    NASA Technical Reports Server (NTRS)

    Bland, Samuel R.

    1991-01-01

    Suggestions for some of the input parameters used in the CAP-TSD (Computational Aeroelasticity Program-Transonic Small Disturbance) computer code are presented. These parameters include those associated with the mesh design and time step. The guidelines are based principally on experience with a one-dimensional model problem used to study wave propagation in the vertical direction.

  14. Distribution Development for STORM Ingestion Input Parameters

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

    Fulton, John

    The Sandia-developed Transport of Radioactive Materials (STORM) code suite is used as part of the Radioisotope Power System Launch Safety (RPSLS) program to perform statistical modeling of the consequences due to release of radioactive material given a launch accident. As part of this modeling, STORM samples input parameters from probability distributions with some parameters treated as constants. This report described the work done to convert four of these constant inputs (Consumption Rate, Average Crop Yield, Cropland to Landuse Database Ratio, and Crop Uptake Factor) to sampled values. Consumption rate changed from a constant value of 557.68 kg / yr tomore » a normal distribution with a mean of 102.96 kg / yr and a standard deviation of 2.65 kg / yr. Meanwhile, Average Crop Yield changed from a constant value of 3.783 kg edible / m 2 to a normal distribution with a mean of 3.23 kg edible / m 2 and a standard deviation of 0.442 kg edible / m 2 . The Cropland to Landuse Database ratio changed from a constant value of 0.0996 (9.96%) to a normal distribution with a mean value of 0.0312 (3.12%) and a standard deviation of 0.00292 (0.29%). Finally the crop uptake factor changed from a constant value of 6.37e -4 (Bq crop /kg)/(Bq soil /kg) to a lognormal distribution with a geometric mean value of 3.38e -4 (Bq crop /kg)/(Bq soil /kg) and a standard deviation value of 3.33 (Bq crop /kg)/(Bq soil /kg)« less

  15. 40 CFR 60.4176 - Additional requirements to provide heat input data.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 40 Protection of Environment 6 2011-07-01 2011-07-01 false Additional requirements to provide heat... requirements to provide heat input data. The owner or operator of a Hg Budget unit that monitors and reports Hg... monitor and report heat input rate at the unit level using the procedures set forth in part 75 of this...

  16. Net thrust calculation sensitivity of an afterburning turbofan engine to variations in input parameters

    NASA Technical Reports Server (NTRS)

    Hughes, D. L.; Ray, R. J.; Walton, J. T.

    1985-01-01

    The calculated value of net thrust of an aircraft powered by a General Electric F404-GE-400 afterburning turbofan engine was evaluated for its sensitivity to various input parameters. The effects of a 1.0-percent change in each input parameter on the calculated value of net thrust with two calculation methods are compared. This paper presents the results of these comparisons and also gives the estimated accuracy of the overall net thrust calculation as determined from the influence coefficients and estimated parameter measurement accuracies.

  17. Adaptive control of a quadrotor aerial vehicle with input constraints and uncertain parameters

    NASA Astrophysics Data System (ADS)

    Tran, Trong-Toan; Ge, Shuzhi Sam; He, Wei

    2018-05-01

    In this paper, we address the problem of adaptive bounded control for the trajectory tracking of a Quadrotor Aerial Vehicle (QAV) while the input saturations and uncertain parameters with the known bounds are simultaneously taken into account. First, to deal with the underactuated property of the QAV model, we decouple and construct the QAV model as a cascaded structure which consists of two fully actuated subsystems. Second, to handle the input constraints and uncertain parameters, we use a combination of the smooth saturation function and smooth projection operator in the control design. Third, to ensure the stability of the overall system of the QAV, we develop the technique for the cascaded system in the presence of both the input constraints and uncertain parameters. Finally, the region of stability of the closed-loop system is constructed explicitly, and our design ensures the asymptotic convergence of the tracking errors to the origin. The simulation results are provided to illustrate the effectiveness of the proposed method.

  18. RIPL - Reference Input Parameter Library for Calculation of Nuclear Reactions and Nuclear Data Evaluations

    NASA Astrophysics Data System (ADS)

    Capote, R.; Herman, M.; Obložinský, P.; Young, P. G.; Goriely, S.; Belgya, T.; Ignatyuk, A. V.; Koning, A. J.; Hilaire, S.; Plujko, V. A.; Avrigeanu, M.; Bersillon, O.; Chadwick, M. B.; Fukahori, T.; Ge, Zhigang; Han, Yinlu; Kailas, S.; Kopecky, J.; Maslov, V. M.; Reffo, G.; Sin, M.; Soukhovitskii, E. Sh.; Talou, P.

    2009-12-01

    We describe the physics and data included in the Reference Input Parameter Library, which is devoted to input parameters needed in calculations of nuclear reactions and nuclear data evaluations. Advanced modelling codes require substantial numerical input, therefore the International Atomic Energy Agency (IAEA) has worked extensively since 1993 on a library of validated nuclear-model input parameters, referred to as the Reference Input Parameter Library (RIPL). A final RIPL coordinated research project (RIPL-3) was brought to a successful conclusion in December 2008, after 15 years of challenging work carried out through three consecutive IAEA projects. The RIPL-3 library was released in January 2009, and is available on the Web through http://www-nds.iaea.org/RIPL-3/. This work and the resulting database are extremely important to theoreticians involved in the development and use of nuclear reaction modelling (ALICE, EMPIRE, GNASH, UNF, TALYS) both for theoretical research and nuclear data evaluations. The numerical data and computer codes included in RIPL-3 are arranged in seven segments: MASSES contains ground-state properties of nuclei for about 9000 nuclei, including three theoretical predictions of masses and the evaluated experimental masses of Audi et al. (2003). DISCRETE LEVELS contains 117 datasets (one for each element) with all known level schemes, electromagnetic and γ-ray decay probabilities available from ENSDF in October 2007. NEUTRON RESONANCES contains average resonance parameters prepared on the basis of the evaluations performed by Ignatyuk and Mughabghab. OPTICAL MODEL contains 495 sets of phenomenological optical model parameters defined in a wide energy range. When there are insufficient experimental data, the evaluator has to resort to either global parameterizations or microscopic approaches. Radial density distributions to be used as input for microscopic calculations are stored in the MASSES segment. LEVEL DENSITIES contains

  19. RIPL - Reference Input Parameter Library for Calculation of Nuclear Reactions and Nuclear Data Evaluations

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

    Capote, R.; Herman, M.; Oblozinsky, P.

    We describe the physics and data included in the Reference Input Parameter Library, which is devoted to input parameters needed in calculations of nuclear reactions and nuclear data evaluations. Advanced modelling codes require substantial numerical input, therefore the International Atomic Energy Agency (IAEA) has worked extensively since 1993 on a library of validated nuclear-model input parameters, referred to as the Reference Input Parameter Library (RIPL). A final RIPL coordinated research project (RIPL-3) was brought to a successful conclusion in December 2008, after 15 years of challenging work carried out through three consecutive IAEA projects. The RIPL-3 library was released inmore » January 2009, and is available on the Web through (http://www-nds.iaea.org/RIPL-3/). This work and the resulting database are extremely important to theoreticians involved in the development and use of nuclear reaction modelling (ALICE, EMPIRE, GNASH, UNF, TALYS) both for theoretical research and nuclear data evaluations. The numerical data and computer codes included in RIPL-3 are arranged in seven segments: MASSES contains ground-state properties of nuclei for about 9000 nuclei, including three theoretical predictions of masses and the evaluated experimental masses of Audi et al. (2003). DISCRETE LEVELS contains 117 datasets (one for each element) with all known level schemes, electromagnetic and {gamma}-ray decay probabilities available from ENSDF in October 2007. NEUTRON RESONANCES contains average resonance parameters prepared on the basis of the evaluations performed by Ignatyuk and Mughabghab. OPTICAL MODEL contains 495 sets of phenomenological optical model parameters defined in a wide energy range. When there are insufficient experimental data, the evaluator has to resort to either global parameterizations or microscopic approaches. Radial density distributions to be used as input for microscopic calculations are stored in the MASSES segment. LEVEL DENSITIES

  20. RIPL-Reference Input Parameter Library for Calculation of Nuclear Reactions and Nuclear Data Evaluations

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

    Capote, R.; Herman, M.; Capote,R.

    We describe the physics and data included in the Reference Input Parameter Library, which is devoted to input parameters needed in calculations of nuclear reactions and nuclear data evaluations. Advanced modelling codes require substantial numerical input, therefore the International Atomic Energy Agency (IAEA) has worked extensively since 1993 on a library of validated nuclear-model input parameters, referred to as the Reference Input Parameter Library (RIPL). A final RIPL coordinated research project (RIPL-3) was brought to a successful conclusion in December 2008, after 15 years of challenging work carried out through three consecutive IAEA projects. The RIPL-3 library was released inmore » January 2009, and is available on the Web through http://www-nds.iaea.org/RIPL-3/. This work and the resulting database are extremely important to theoreticians involved in the development and use of nuclear reaction modelling (ALICE, EMPIRE, GNASH, UNF, TALYS) both for theoretical research and nuclear data evaluations. The numerical data and computer codes included in RIPL-3 are arranged in seven segments: MASSES contains ground-state properties of nuclei for about 9000 nuclei, including three theoretical predictions of masses and the evaluated experimental masses of Audi et al. (2003). DISCRETE LEVELS contains 117 datasets (one for each element) with all known level schemes, electromagnetic and {gamma}-ray decay probabilities available from ENSDF in October 2007. NEUTRON RESONANCES contains average resonance parameters prepared on the basis of the evaluations performed by Ignatyuk and Mughabghab. OPTICAL MODEL contains 495 sets of phenomenological optical model parameters defined in a wide energy range. When there are insufficient experimental data, the evaluator has to resort to either global parameterizations or microscopic approaches. Radial density distributions to be used as input for microscopic calculations are stored in the MASSES segment. LEVEL DENSITIES contains

  1. Efficient Screening of Climate Model Sensitivity to a Large Number of Perturbed Input Parameters [plus supporting information

    DOE PAGES

    Covey, Curt; Lucas, Donald D.; Tannahill, John; ...

    2013-07-01

    Modern climate models contain numerous input parameters, each with a range of possible values. Since the volume of parameter space increases exponentially with the number of parameters N, it is generally impossible to directly evaluate a model throughout this space even if just 2-3 values are chosen for each parameter. Sensitivity screening algorithms, however, can identify input parameters having relatively little effect on a variety of output fields, either individually or in nonlinear combination.This can aid both model development and the uncertainty quantification (UQ) process. Here we report results from a parameter sensitivity screening algorithm hitherto untested in climate modeling,more » the Morris one-at-a-time (MOAT) method. This algorithm drastically reduces the computational cost of estimating sensitivities in a high dimensional parameter space because the sample size grows linearly rather than exponentially with N. It nevertheless samples over much of the N-dimensional volume and allows assessment of parameter interactions, unlike traditional elementary one-at-a-time (EOAT) parameter variation. We applied both EOAT and MOAT to the Community Atmosphere Model (CAM), assessing CAM’s behavior as a function of 27 uncertain input parameters related to the boundary layer, clouds, and other subgrid scale processes. For radiation balance at the top of the atmosphere, EOAT and MOAT rank most input parameters similarly, but MOAT identifies a sensitivity that EOAT underplays for two convection parameters that operate nonlinearly in the model. MOAT’s ranking of input parameters is robust to modest algorithmic variations, and it is qualitatively consistent with model development experience. Supporting information is also provided at the end of the full text of the article.« less

  2. 40 CFR 60.4176 - Additional requirements to provide heat input data.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 40 Protection of Environment 6 2010-07-01 2010-07-01 false Additional requirements to provide heat... Compliance Times for Coal-Fired Electric Steam Generating Units Monitoring and Reporting § 60.4176 Additional requirements to provide heat input data. The owner or operator of a Hg Budget unit that monitors and reports Hg...

  3. Gaze and Feet as Additional Input Modalities for Interacting with Geospatial Interfaces

    NASA Astrophysics Data System (ADS)

    Çöltekin, A.; Hempel, J.; Brychtova, A.; Giannopoulos, I.; Stellmach, S.; Dachselt, R.

    2016-06-01

    Geographic Information Systems (GIS) are complex software environments and we often work with multiple tasks and multiple displays when we work with GIS. However, user input is still limited to mouse and keyboard in most workplace settings. In this project, we demonstrate how the use of gaze and feet as additional input modalities can overcome time-consuming and annoying mode switches between frequently performed tasks. In an iterative design process, we developed gaze- and foot-based methods for zooming and panning of map visualizations. We first collected appropriate gestures in a preliminary user study with a small group of experts, and designed two interaction concepts based on their input. After the implementation, we evaluated the two concepts comparatively in another user study to identify strengths and shortcomings in both. We found that continuous foot input combined with implicit gaze input is promising for supportive tasks.

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

    NASA Astrophysics Data System (ADS)

    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.

  5. Evaluation of Uncertainty in Constituent Input Parameters for Modeling the Fate of RDX

    DTIC Science & Technology

    2015-07-01

    exercise was to evaluate the importance of chemical -specific model input parameters, the impacts of their uncertainty, and the potential benefits of... chemical -specific inputs for RDX that were determined to be sensitive with relatively high uncertainty: these included the soil-water linear...Koc for organic chemicals . The EFS values provided for log Koc of RDX were 1.72 and 1.95. OBJECTIVE: TREECS™ (http://el.erdc.usace.army.mil/treecs

  6. 6 DOF synchronized control for spacecraft formation flying with input constraint and parameter uncertainties.

    PubMed

    Lv, Yueyong; Hu, Qinglei; Ma, Guangfu; Zhou, Jiakang

    2011-10-01

    This paper treats the problem of synchronized control of spacecraft formation flying (SFF) in the presence of input constraint and parameter uncertainties. More specifically, backstepping based robust control is first developed for the total 6 DOF dynamic model of SFF with parameter uncertainties, in which the model consists of relative translation and attitude rotation. Then this controller is redesigned to deal with the input constraint problem by incorporating a command filter such that the generated control could be implementable even under physical or operating constraints on the control input. The convergence of the proposed control algorithms is proved by the Lyapunov stability theorem. Compared with conventional methods, illustrative simulations of spacecraft formation flying are conducted to verify the effectiveness of the proposed approach to achieve the spacecraft track the desired attitude and position trajectories in a synchronized fashion even in the presence of uncertainties, external disturbances and control saturation constraint. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

  7. DC servomechanism parameter identification: a Closed Loop Input Error approach.

    PubMed

    Garrido, Ruben; Miranda, Roger

    2012-01-01

    This paper presents a Closed Loop Input Error (CLIE) approach for on-line parametric estimation of a continuous-time model of a DC servomechanism functioning in closed loop. A standard Proportional Derivative (PD) position controller stabilizes the loop without requiring knowledge on the servomechanism parameters. The analysis of the identification algorithm takes into account the control law employed for closing the loop. The model contains four parameters that depend on the servo inertia, viscous, and Coulomb friction as well as on a constant disturbance. Lyapunov stability theory permits assessing boundedness of the signals associated to the identification algorithm. Experiments on a laboratory prototype allows evaluating the performance of the approach. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

  8. Modeling the cardiovascular system using a nonlinear additive autoregressive model with exogenous input

    NASA Astrophysics Data System (ADS)

    Riedl, M.; Suhrbier, A.; Malberg, H.; Penzel, T.; Bretthauer, G.; Kurths, J.; Wessel, N.

    2008-07-01

    The parameters of heart rate variability and blood pressure variability have proved to be useful analytical tools in cardiovascular physics and medicine. Model-based analysis of these variabilities additionally leads to new prognostic information about mechanisms behind regulations in the cardiovascular system. In this paper, we analyze the complex interaction between heart rate, systolic blood pressure, and respiration by nonparametric fitted nonlinear additive autoregressive models with external inputs. Therefore, we consider measurements of healthy persons and patients suffering from obstructive sleep apnea syndrome (OSAS), with and without hypertension. It is shown that the proposed nonlinear models are capable of describing short-term fluctuations in heart rate as well as systolic blood pressure significantly better than similar linear ones, which confirms the assumption of nonlinear controlled heart rate and blood pressure. Furthermore, the comparison of the nonlinear and linear approaches reveals that the heart rate and blood pressure variability in healthy subjects is caused by a higher level of noise as well as nonlinearity than in patients suffering from OSAS. The residue analysis points at a further source of heart rate and blood pressure variability in healthy subjects, in addition to heart rate, systolic blood pressure, and respiration. Comparison of the nonlinear models within and among the different groups of subjects suggests the ability to discriminate the cohorts that could lead to a stratification of hypertension risk in OSAS patients.

  9. Explicit least squares system parameter identification for exact differential input/output models

    NASA Technical Reports Server (NTRS)

    Pearson, A. E.

    1993-01-01

    The equation error for a class of systems modeled by input/output differential operator equations has the potential to be integrated exactly, given the input/output data on a finite time interval, thereby opening up the possibility of using an explicit least squares estimation technique for system parameter identification. The paper delineates the class of models for which this is possible and shows how the explicit least squares cost function can be obtained in a way that obviates dealing with unknown initial and boundary conditions. The approach is illustrated by two examples: a second order chemical kinetics model and a third order system of Lorenz equations.

  10. Defense Intelligence: Additional Steps Could Better Integrate Intelligence Input into DODs Acquisition of Major Weapon Systems

    DTIC Science & Technology

    2016-11-01

    DEFENSE INTELLIGENCE Additional Steps Could Better Integrate Intelligence Input into DOD’s Acquisition of Major Weapon...States Government Accountability Office Highlights of GAO-17-10, a report to congressional committees November 2016 DEFENSE INTELLIGENCE ...Additional Steps Could Better Integrate Intelligence Input into DOD’s Acquisition of Major Weapon Systems What GAO Found The Department of Defense (DOD

  11. Evaluation of Uncertainty in Constituent Input Parameters for Modeling the Fate of IMX 101 Components

    DTIC Science & Technology

    2017-05-01

    ER D C/ EL T R- 17 -7 Environmental Security Technology Certification Program (ESTCP) Evaluation of Uncertainty in Constituent Input...Environmental Security Technology Certification Program (ESTCP) ERDC/EL TR-17-7 May 2017 Evaluation of Uncertainty in Constituent Input Parameters...Environmental Evaluation and Characterization Sys- tem (TREECS™) was applied to a groundwater site and a surface water site to evaluate the sensitivity

  12. Finding identifiable parameter combinations in nonlinear ODE models and the rational reparameterization of their input-output equations.

    PubMed

    Meshkat, Nicolette; Anderson, Chris; Distefano, Joseph J

    2011-09-01

    When examining the structural identifiability properties of dynamic system models, some parameters can take on an infinite number of values and yet yield identical input-output data. These parameters and the model are then said to be unidentifiable. Finding identifiable combinations of parameters with which to reparameterize the model provides a means for quantitatively analyzing the model and computing solutions in terms of the combinations. In this paper, we revisit and explore the properties of an algorithm for finding identifiable parameter combinations using Gröbner Bases and prove useful theoretical properties of these parameter combinations. We prove a set of M algebraically independent identifiable parameter combinations can be found using this algorithm and that there exists a unique rational reparameterization of the input-output equations over these parameter combinations. We also demonstrate application of the procedure to a nonlinear biomodel. Copyright © 2011 Elsevier Inc. All rights reserved.

  13. Flight Test of Orthogonal Square Wave Inputs for Hybrid-Wing-Body Parameter Estimation

    NASA Technical Reports Server (NTRS)

    Taylor, Brian R.; Ratnayake, Nalin A.

    2011-01-01

    As part of an effort to improve emissions, noise, and performance of next generation aircraft, it is expected that future aircraft will use distributed, multi-objective control effectors in a closed-loop flight control system. Correlation challenges associated with parameter estimation will arise with this expected aircraft configuration. The research presented in this paper focuses on addressing the correlation problem with an appropriate input design technique in order to determine individual control surface effectiveness. This technique was validated through flight-testing an 8.5-percent-scale hybrid-wing-body aircraft demonstrator at the NASA Dryden Flight Research Center (Edwards, California). An input design technique that uses mutually orthogonal square wave inputs for de-correlation of control surfaces is proposed. Flight-test results are compared with prior flight-test results for a different maneuver style.

  14. Estimating unknown input parameters when implementing the NGA ground-motion prediction equations in engineering practice

    USGS Publications Warehouse

    Kaklamanos, James; Baise, Laurie G.; Boore, David M.

    2011-01-01

    The ground-motion prediction equations (GMPEs) developed as part of the Next Generation Attenuation of Ground Motions (NGA-West) project in 2008 are becoming widely used in seismic hazard analyses. However, these new models are considerably more complicated than previous GMPEs, and they require several more input parameters. When employing the NGA models, users routinely face situations in which some of the required input parameters are unknown. In this paper, we present a framework for estimating the unknown source, path, and site parameters when implementing the NGA models in engineering practice, and we derive geometrically-based equations relating the three distance measures found in the NGA models. Our intent is for the content of this paper not only to make the NGA models more accessible, but also to help with the implementation of other present or future GMPEs.

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

    NASA Astrophysics Data System (ADS)

    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

  16. Monte Carlo Solution to Find Input Parameters in Systems Design Problems

    NASA Astrophysics Data System (ADS)

    Arsham, Hossein

    2013-06-01

    Most engineering system designs, such as product, process, and service design, involve a framework for arriving at a target value for a set of experiments. This paper considers a stochastic approximation algorithm for estimating the controllable input parameter within a desired accuracy, given a target value for the performance function. Two different problems, what-if and goal-seeking problems, are explained and defined in an auxiliary simulation model, which represents a local response surface model in terms of a polynomial. A method of constructing this polynomial by a single run simulation is explained. An algorithm is given to select the design parameter for the local response surface model. Finally, the mean time to failure (MTTF) of a reliability subsystem is computed and compared with its known analytical MTTF value for validation purposes.

  17. Method of validating measurement data of a process parameter from a plurality of individual sensor inputs

    DOEpatents

    Scarola, Kenneth; Jamison, David S.; Manazir, Richard M.; Rescorl, Robert L.; Harmon, Daryl L.

    1998-01-01

    A method for generating a validated measurement of a process parameter at a point in time by using a plurality of individual sensor inputs from a scan of said sensors at said point in time. The sensor inputs from said scan are stored and a first validation pass is initiated by computing an initial average of all stored sensor inputs. Each sensor input is deviation checked by comparing each input including a preset tolerance against the initial average input. If the first deviation check is unsatisfactory, the sensor which produced the unsatisfactory input is flagged as suspect. It is then determined whether at least two of the inputs have not been flagged as suspect and are therefore considered good inputs. If two or more inputs are good, a second validation pass is initiated by computing a second average of all the good sensor inputs, and deviation checking the good inputs by comparing each good input including a present tolerance against the second average. If the second deviation check is satisfactory, the second average is displayed as the validated measurement and the suspect sensor as flagged as bad. A validation fault occurs if at least two inputs are not considered good, or if the second deviation check is not satisfactory. In the latter situation the inputs from each of all the sensors are compared against the last validated measurement and the value from the sensor input that deviates the least from the last valid measurement is displayed.

  18. Effect of input signal and filter parameters on patterning effect in a semiconductor optical amplifier

    NASA Astrophysics Data System (ADS)

    Hussain, Kamal; Pratap Singh, Satya; Kumar Datta, Prasanta

    2013-11-01

    A numerical investigation is presented to show the dependence of patterning effect (PE) of an amplified signal in a bulk semiconductor optical amplifier (SOA) and an optical bandpass filter based amplifier on various input signal and filter parameters considering both the cases of including and excluding intraband effects in the SOA model. The simulation shows that the variation of PE with input energy has a characteristic nature which is similar for both the cases. However the variation of PE with pulse width is quite different for the two cases, PE being independent of the pulse width when intraband effects are neglected in the model. We find a simple relationship between the PE and the signal pulse width. Using a simple treatment we study the effect of the amplified spontaneous emission (ASE) on PE and find that the ASE has almost no effect on the PE in the range of energy considered here. The optimum filter parameters are determined to obtain an acceptable extinction ratio greater than 10 dB and a PE less than 1 dB for the amplified signal over a wide range of input signal energy and bit-rate.

  19. Explicitly integrating parameter, input, and structure uncertainties into Bayesian Neural Networks for probabilistic hydrologic forecasting

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

    Zhang, Xuesong; Liang, Faming; Yu, Beibei

    2011-11-09

    Estimating uncertainty of hydrologic forecasting is valuable to water resources and other relevant decision making processes. Recently, Bayesian Neural Networks (BNNs) have been proved powerful tools for quantifying uncertainty of streamflow forecasting. In this study, we propose a Markov Chain Monte Carlo (MCMC) framework to incorporate the uncertainties associated with input, model structure, and parameter into BNNs. This framework allows the structure of the neural networks to change by removing or adding connections between neurons and enables scaling of input data by using rainfall multipliers. The results show that the new BNNs outperform the BNNs that only consider uncertainties associatedmore » with parameter and model structure. Critical evaluation of posterior distribution of neural network weights, number of effective connections, rainfall multipliers, and hyper-parameters show that the assumptions held in our BNNs are not well supported. Further understanding of characteristics of different uncertainty sources and including output error into the MCMC framework are expected to enhance the application of neural networks for uncertainty analysis of hydrologic forecasting.« less

  20. Assessment of food intake input distributions for use in probabilistic exposure assessments of food additives.

    PubMed

    Gilsenan, M B; Lambe, J; Gibney, M J

    2003-11-01

    A key component of a food chemical exposure assessment using probabilistic analysis is the selection of the most appropriate input distribution to represent exposure variables. The study explored the type of parametric distribution that could be used to model variability in food consumption data likely to be included in a probabilistic exposure assessment of food additives. The goodness-of-fit of a range of continuous distributions to observed data of 22 food categories expressed as average daily intakes among consumers from the North-South Ireland Food Consumption Survey was assessed using the BestFit distribution fitting program. The lognormal distribution was most commonly accepted as a plausible parametric distribution to represent food consumption data when food intakes were expressed as absolute intakes (16/22 foods) and as intakes per kg body weight (18/22 foods). Results from goodness-of-fit tests were accompanied by lognormal probability plots for a number of food categories. The influence on food additive intake of using a lognormal distribution to model food consumption input data was assessed by comparing modelled intake estimates with observed intakes. Results from the present study advise some level of caution about the use of a lognormal distribution as a mode of input for food consumption data in probabilistic food additive exposure assessments and the results highlight the need for further research in this area.

  1. Optimization of input parameters of acoustic-transfection for the intracellular delivery of macromolecules using FRET-based biosensors

    NASA Astrophysics Data System (ADS)

    Yoon, Sangpil; Wang, Yingxiao; Shung, K. K.

    2016-03-01

    Acoustic-transfection technique has been developed for the first time. We have developed acoustic-transfection by integrating a high frequency ultrasonic transducer and a fluorescence microscope. High frequency ultrasound with the center frequency over 150 MHz can focus acoustic sound field into a confined area with the diameter of 10 μm or less. This focusing capability was used to perturb lipid bilayer of cell membrane to induce intracellular delivery of macromolecules. Single cell level imaging was performed to investigate the behavior of a targeted single-cell after acoustic-transfection. FRET-based Ca2+ biosensor was used to monitor intracellular concentration of Ca2+ after acoustic-transfection and the fluorescence intensity of propidium iodide (PI) was used to observe influx of PI molecules. We changed peak-to-peak voltages and pulse duration to optimize the input parameters of an acoustic pulse. Input parameters that can induce strong perturbations on cell membrane were found and size dependent intracellular delivery of macromolecules was explored. To increase the amount of delivered molecules by acoustic-transfection, we applied several acoustic pulses and the intensity of PI fluorescence increased step wise. Finally, optimized input parameters of acoustic-transfection system were used to deliver pMax-E2F1 plasmid and GFP expression 24 hours after the intracellular delivery was confirmed using HeLa cells.

  2. 40 CFR 96.76 - Additional requirements to provide heat input data for allocations purposes.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... TRADING PROGRAMS FOR STATE IMPLEMENTATION PLANS Monitoring and Reporting § 96.76 Additional requirements... to monitor and report NOX Mass emissions using a NOX concentration system and a flow system shall... chapter for any source located in a state developing source allocations based upon heat input. (b) The...

  3. Program for User-Friendly Management of Input and Output Data Sets

    NASA Technical Reports Server (NTRS)

    Klimeck, Gerhard

    2003-01-01

    A computer program manages large, hierarchical sets of input and output (I/O) parameters (typically, sequences of alphanumeric data) involved in computational simulations in a variety of technological disciplines. This program represents sets of parameters as structures coded in object-oriented but otherwise standard American National Standards Institute C language. Each structure contains a group of I/O parameters that make sense as a unit in the simulation program with which this program is used. The addition of options and/or elements to sets of parameters amounts to the addition of new elements to data structures. By association of child data generated in response to a particular user input, a hierarchical ordering of input parameters can be achieved. Associated with child data structures are the creation and description mechanisms within the parent data structures. Child data structures can spawn further child data structures. In this program, the creation and representation of a sequence of data structures is effected by one line of code that looks for children of a sequence of structures until there are no more children to be found. A linked list of structures is created dynamically and is completely represented in the data structures themselves. Such hierarchical data presentation can guide users through otherwise complex setup procedures and it can be integrated within a variety of graphical representations.

  4. Blind Deconvolution for Distributed Parameter Systems with Unbounded Input and Output and Determining Blood Alcohol Concentration from Transdermal Biosensor Data.

    PubMed

    Rosen, I G; Luczak, Susan E; Weiss, Jordan

    2014-03-15

    We develop a blind deconvolution scheme for input-output systems described by distributed parameter systems with boundary input and output. An abstract functional analytic theory based on results for the linear quadratic control of infinite dimensional systems with unbounded input and output operators is presented. The blind deconvolution problem is then reformulated as a series of constrained linear and nonlinear optimization problems involving infinite dimensional dynamical systems. A finite dimensional approximation and convergence theory is developed. The theory is applied to the problem of estimating blood or breath alcohol concentration (respectively, BAC or BrAC) from biosensor-measured transdermal alcohol concentration (TAC) in the field. A distributed parameter model with boundary input and output is proposed for the transdermal transport of ethanol from the blood through the skin to the sensor. The problem of estimating BAC or BrAC from the TAC data is formulated as a blind deconvolution problem. A scheme to identify distinct drinking episodes in TAC data based on a Hodrick Prescott filter is discussed. Numerical results involving actual patient data are presented.

  5. Hydrological Relevant Parameters from Remote Sensing - Spatial Modelling Input and Validation Basis

    NASA Astrophysics Data System (ADS)

    Hochschild, V.

    2012-12-01

    This keynote paper will demonstrate how multisensoral remote sensing data is used as spatial input for mesoscale hydrological modeling as well as for sophisticated validation purposes. The tasks of Water Resources Management are subject as well as the role of remote sensing in regional catchment modeling. Parameters derived from remote sensing discussed in this presentation will be land cover, topographical information from digital elevation models, biophysical vegetation parameters, surface soil moisture, evapotranspiration estimations, lake level measurements, determination of snow covered area, lake ice cycles, soil erosion type, mass wasting monitoring, sealed area, flash flood estimation. The actual possibilities of recent satellite and airborne systems are discussed, as well as the data integration into GIS and hydrological modeling, scaling issues and quality assessment will be mentioned. The presentation will provide an overview of own research examples from Germany, Tibet and Africa (Ethiopia, South Africa) as well as other international research activities. Finally the paper gives an outlook on upcoming sensors and concludes the possibilities of remote sensing in hydrology.

  6. Application and optimization of input parameter spaces in mass flow modelling: a case study with r.randomwalk and r.ranger

    NASA Astrophysics Data System (ADS)

    Krenn, Julia; Zangerl, Christian; Mergili, Martin

    2017-04-01

    r.randomwalk is a GIS-based, multi-functional, conceptual open source model application for forward and backward analyses of the propagation of mass flows. It relies on a set of empirically derived, uncertain input parameters. In contrast to many other tools, r.randomwalk accepts input parameter ranges (or, in case of two or more parameters, spaces) in order to directly account for these uncertainties. Parameter spaces represent a possibility to withdraw from discrete input values which in most cases are likely to be off target. r.randomwalk automatically performs multiple calculations with various parameter combinations in a given parameter space, resulting in the impact indicator index (III) which denotes the fraction of parameter value combinations predicting an impact on a given pixel. Still, there is a need to constrain the parameter space used for a certain process type or magnitude prior to performing forward calculations. This can be done by optimizing the parameter space in terms of bringing the model results in line with well-documented past events. As most existing parameter optimization algorithms are designed for discrete values rather than for ranges or spaces, the necessity for a new and innovative technique arises. The present study aims at developing such a technique and at applying it to derive guiding parameter spaces for the forward calculation of rock avalanches through back-calculation of multiple events. In order to automatize the work flow we have designed r.ranger, an optimization and sensitivity analysis tool for parameter spaces which can be directly coupled to r.randomwalk. With r.ranger we apply a nested approach where the total value range of each parameter is divided into various levels of subranges. All possible combinations of subranges of all parameters are tested for the performance of the associated pattern of III. Performance indicators are the area under the ROC curve (AUROC) and the factor of conservativeness (FoC). This

  7. Signal Prediction With Input Identification

    NASA Technical Reports Server (NTRS)

    Juang, Jer-Nan; Chen, Ya-Chin

    1999-01-01

    A novel coding technique is presented for signal prediction with applications including speech coding, system identification, and estimation of input excitation. The approach is based on the blind equalization method for speech signal processing in conjunction with the geometric subspace projection theory to formulate the basic prediction equation. The speech-coding problem is often divided into two parts, a linear prediction model and excitation input. The parameter coefficients of the linear predictor and the input excitation are solved simultaneously and recursively by a conventional recursive least-squares algorithm. The excitation input is computed by coding all possible outcomes into a binary codebook. The coefficients of the linear predictor and excitation, and the index of the codebook can then be used to represent the signal. In addition, a variable-frame concept is proposed to block the same excitation signal in sequence in order to reduce the storage size and increase the transmission rate. The results of this work can be easily extended to the problem of disturbance identification. The basic principles are outlined in this report and differences from other existing methods are discussed. Simulations are included to demonstrate the proposed method.

  8. User's manual for a parameter identification technique. [with options for model simulation for fixed input forcing functions and identification from wind tunnel and flight measurements

    NASA Technical Reports Server (NTRS)

    Kanning, G.

    1975-01-01

    A digital computer program written in FORTRAN is presented that implements the system identification theory for deterministic systems using input-output measurements. The user supplies programs simulating the mathematical model of the physical plant whose parameters are to be identified. The user may choose any one of three options. The first option allows for a complete model simulation for fixed input forcing functions. The second option identifies up to 36 parameters of the model from wind tunnel or flight measurements. The third option performs a sensitivity analysis for up to 36 parameters. The use of each option is illustrated with an example using input-output measurements for a helicopter rotor tested in a wind tunnel.

  9. On the reliability of voltage and power as input parameters for the characterization of high power ultrasound applications

    NASA Astrophysics Data System (ADS)

    Haller, Julian; Wilkens, Volker

    2012-11-01

    For power levels up to 200 W and sonication times up to 60 s, the electrical power, the voltage and the electrical impedance (more exactly: the ratio of RMS voltage and RMS current) have been measured for a piezocomposite high intensity therapeutic ultrasound (HITU) transducer with integrated matching network, two piezoceramic HITU transducers with external matching networks and for a passive dummy 50 Ω load. The electrical power and the voltage were measured during high power application with an inline power meter and an RMS voltage meter, respectively, and the complex electrical impedance was indirectly measured with a current probe, a 100:1 voltage probe and a digital scope. The results clearly show that the input RMS voltage and the input RMS power change unequally during the application. Hence, the indication of only the electrical input power or only the voltage as the input parameter may not be sufficient for reliable characterizations of ultrasound transducers for high power applications in some cases.

  10. Optimal input shaping for Fisher identifiability of control-oriented lithium-ion battery models

    NASA Astrophysics Data System (ADS)

    Rothenberger, Michael J.

    This dissertation examines the fundamental challenge of optimally shaping input trajectories to maximize parameter identifiability of control-oriented lithium-ion battery models. Identifiability is a property from information theory that determines the solvability of parameter estimation for mathematical models using input-output measurements. This dissertation creates a framework that exploits the Fisher information metric to quantify the level of battery parameter identifiability, optimizes this metric through input shaping, and facilitates faster and more accurate estimation. The popularity of lithium-ion batteries is growing significantly in the energy storage domain, especially for stationary and transportation applications. While these cells have excellent power and energy densities, they are plagued with safety and lifespan concerns. These concerns are often resolved in the industry through conservative current and voltage operating limits, which reduce the overall performance and still lack robustness in detecting catastrophic failure modes. New advances in automotive battery management systems mitigate these challenges through the incorporation of model-based control to increase performance, safety, and lifespan. To achieve these goals, model-based control requires accurate parameterization of the battery model. While many groups in the literature study a variety of methods to perform battery parameter estimation, a fundamental issue of poor parameter identifiability remains apparent for lithium-ion battery models. This fundamental challenge of battery identifiability is studied extensively in the literature, and some groups are even approaching the problem of improving the ability to estimate the model parameters. The first approach is to add additional sensors to the battery to gain more information that is used for estimation. The other main approach is to shape the input trajectories to increase the amount of information that can be gained from input

  11. Computer program for single input-output, single-loop feedback systems

    NASA Technical Reports Server (NTRS)

    1976-01-01

    Additional work is reported on a completely automatic computer program for the design of single input/output, single loop feedback systems with parameter uncertainly, to satisfy time domain bounds on the system response to step commands and disturbances. The inputs to the program are basically the specified time-domain response bounds, the form of the constrained plant transfer function and the ranges of the uncertain parameters of the plant. The program output consists of the transfer functions of the two free compensation networks, in the form of the coefficients of the numerator and denominator polynomials, and the data on the prescribed bounds and the extremes actually obtained for the system response to commands and disturbances.

  12. F-18 High Alpha Research Vehicle (HARV) parameter identification flight test maneuvers for optimal input design validation and lateral control effectiveness

    NASA Technical Reports Server (NTRS)

    Morelli, Eugene A.

    1995-01-01

    Flight test maneuvers are specified for the F-18 High Alpha Research Vehicle (HARV). The maneuvers were designed for open loop parameter identification purposes, specifically for optimal input design validation at 5 degrees angle of attack, identification of individual strake effectiveness at 40 and 50 degrees angle of attack, and study of lateral dynamics and lateral control effectiveness at 40 and 50 degrees angle of attack. Each maneuver is to be realized by applying square wave inputs to specific control effectors using the On-Board Excitation System (OBES). Maneuver descriptions and complete specifications of the time/amplitude points define each input are included, along with plots of the input time histories.

  13. Simulation and Flight Evaluation of a Parameter Estimation Input Design Method for Hybrid-Wing-Body Aircraft

    NASA Technical Reports Server (NTRS)

    Taylor, Brian R.; Ratnayake, Nalin A.

    2010-01-01

    As part of an effort to improve emissions, noise, and performance of next generation aircraft, it is expected that future aircraft will make use of distributed, multi-objective control effectors in a closed-loop flight control system. Correlation challenges associated with parameter estimation will arise with this expected aircraft configuration. Research presented in this paper focuses on addressing the correlation problem with an appropriate input design technique and validating this technique through simulation and flight test of the X-48B aircraft. The X-48B aircraft is an 8.5 percent-scale hybrid wing body aircraft demonstrator designed by The Boeing Company (Chicago, Illinois, USA), built by Cranfield Aerospace Limited (Cranfield, Bedford, United Kingdom) and flight tested at the National Aeronautics and Space Administration Dryden Flight Research Center (Edwards, California, USA). Based on data from flight test maneuvers performed at Dryden Flight Research Center, aerodynamic parameter estimation was performed using linear regression and output error techniques. An input design technique that uses temporal separation for de-correlation of control surfaces is proposed, and simulation and flight test results are compared with the aerodynamic database. This paper will present a method to determine individual control surface aerodynamic derivatives.

  14. Antagonistic control of a dual-input mammalian gene switch by food additives.

    PubMed

    Xie, Mingqi; Ye, Haifeng; Hamri, Ghislaine Charpin-El; Fussenegger, Martin

    2014-08-01

    Synthetic biology has significantly advanced the design of mammalian trigger-inducible transgene-control devices that are able to programme complex cellular behaviour. Fruit-based benzoate derivatives licensed as food additives, such as flavours (e.g. vanillate) and preservatives (e.g. benzoate), are a particularly attractive class of trigger compounds for orthogonal mammalian transgene control devices because of their innocuousness, physiological compatibility and simple oral administration. Capitalizing on the genetic componentry of the soil bacterium Comamonas testosteroni, which has evolved to catabolize a variety of aromatic compounds, we have designed different mammalian gene expression systems that could be induced and repressed by the food additives benzoate and vanillate. When implanting designer cells engineered for gene switch-driven expression of the human placental secreted alkaline phosphatase (SEAP) into mice, blood SEAP levels of treated animals directly correlated with a benzoate-enriched drinking programme. Additionally, the benzoate-/vanillate-responsive device was compatible with other transgene control systems and could be assembled into higher-order control networks providing expression dynamics reminiscent of a lap-timing stopwatch. Designer gene switches using licensed food additives as trigger compounds to achieve antagonistic dual-input expression profiles and provide novel control topologies and regulation dynamics may advance future gene- and cell-based therapies. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  15. Level density inputs in nuclear reaction codes and the role of the spin cutoff parameter

    DOE PAGES

    Voinov, A. V.; Grimes, S. M.; Brune, C. R.; ...

    2014-09-03

    Here, the proton spectrum from the 57Fe(α,p) reaction has been measured and analyzed with the Hauser-Feshbach model of nuclear reactions. Different input level density models have been tested. It was found that the best description is achieved with either Fermi-gas or constant temperature model functions obtained by fitting them to neutron resonance spacing and to discrete levels and using the spin cutoff parameter with much weaker excitation energy dependence than it is predicted by the Fermi-gas model.

  16. A Bayesian approach to model structural error and input variability in groundwater modeling

    NASA Astrophysics Data System (ADS)

    Xu, T.; Valocchi, A. J.; Lin, Y. F. F.; Liang, F.

    2015-12-01

    Effective water resource management typically relies on numerical models to analyze groundwater flow and solute transport processes. Model structural error (due to simplification and/or misrepresentation of the "true" environmental system) and input forcing variability (which commonly arises since some inputs are uncontrolled or estimated with high uncertainty) are ubiquitous in groundwater models. Calibration that overlooks errors in model structure and input data can lead to biased parameter estimates and compromised predictions. We present a fully Bayesian approach for a complete assessment of uncertainty for spatially distributed groundwater models. The approach explicitly recognizes stochastic input and uses data-driven error models based on nonparametric kernel methods to account for model structural error. We employ exploratory data analysis to assist in specifying informative prior for error models to improve identifiability. The inference is facilitated by an efficient sampling algorithm based on DREAM-ZS and a parameter subspace multiple-try strategy to reduce the required number of forward simulations of the groundwater model. We demonstrate the Bayesian approach through a synthetic case study of surface-ground water interaction under changing pumping conditions. It is found that explicit treatment of errors in model structure and input data (groundwater pumping rate) has substantial impact on the posterior distribution of groundwater model parameters. Using error models reduces predictive bias caused by parameter compensation. In addition, input variability increases parametric and predictive uncertainty. The Bayesian approach allows for a comparison among the contributions from various error sources, which could inform future model improvement and data collection efforts on how to best direct resources towards reducing predictive uncertainty.

  17. Halogenation of Hydraulic Fracturing Additives in the Shale Well Parameter Space

    NASA Astrophysics Data System (ADS)

    Sumner, A. J.; Plata, D.

    2017-12-01

    Horizontal Drilling and Hydraulic fracturing (HDHF) involves the deep-well injection of a `fracking fluid' composed of diverse and numerous chemical additives designed to facilitate the release and collection of natural gas from shale plays. The potential impacts of HDHF operations on water resources and ecosystems are numerous, and analyses of flowback samples revealed organic compounds from both geogenic and anthropogenic sources. Furthermore, halogenated chemicals were also detected, and these compounds are rarely disclosed, suggesting the in situ halogenation of reactive additives. To test this transformation hypothesis, we designed and operated a novel high pressure and temperature reactor system to simulate the shale well parameter space and investigate the chemical reactivity of twelve commonly disclosed and functionally diverse HDHF additives. Early results revealed an unanticipated halogenation pathway of α-β unsaturated aldehyde, Cinnamaldehyde, in the presence of oxidant and concentrated brine. Ongoing experiments over a range of parameters informed a proposed mechanism, demonstrating the role of various shale-well specific parameters in enabling the demonstrated halogenation pathway. Ultimately, these results will inform a host of potentially unintended interactions of HDHF additives during the extreme conditions down-bore of a shale well during HDHF activities.

  18. On how to avoid input and structural uncertainties corrupt the inference of hydrological parameters using a Bayesian framework

    NASA Astrophysics Data System (ADS)

    Hernández, Mario R.; Francés, Félix

    2015-04-01

    One phase of the hydrological models implementation process, significantly contributing to the hydrological predictions uncertainty, is the calibration phase in which values of the unknown model parameters are tuned by optimizing an objective function. An unsuitable error model (e.g. Standard Least Squares or SLS) introduces noise into the estimation of the parameters. The main sources of this noise are the input errors and the hydrological model structural deficiencies. Thus, the biased calibrated parameters cause the divergence model phenomenon, where the errors variance of the (spatially and temporally) forecasted flows far exceeds the errors variance in the fitting period, and provoke the loss of part or all of the physical meaning of the modeled processes. In other words, yielding a calibrated hydrological model which works well, but not for the right reasons. Besides, an unsuitable error model yields a non-reliable predictive uncertainty assessment. Hence, with the aim of prevent all these undesirable effects, this research focuses on the Bayesian joint inference (BJI) of both the hydrological and error model parameters, considering a general additive (GA) error model that allows for correlation, non-stationarity (in variance and bias) and non-normality of model residuals. As hydrological model, it has been used a conceptual distributed model called TETIS, with a particular split structure of the effective model parameters. Bayesian inference has been performed with the aid of a Markov Chain Monte Carlo (MCMC) algorithm called Dream-ZS. MCMC algorithm quantifies the uncertainty of the hydrological and error model parameters by getting the joint posterior probability distribution, conditioned on the observed flows. The BJI methodology is a very powerful and reliable tool, but it must be used correctly this is, if non-stationarity in errors variance and bias is modeled, the Total Laws must be taken into account. The results of this research show that the

  19. Multiaxial Fatigue Damage Parameter and Life Prediction without Any Additional Material Constants

    PubMed Central

    Yu, Zheng-Yong; Liu, Qiang; Liu, Yunhan

    2017-01-01

    Based on the critical plane approach, a simple and efficient multiaxial fatigue damage parameter with no additional material constants is proposed for life prediction under uniaxial/multiaxial proportional and/or non-proportional loadings for titanium alloy TC4 and nickel-based superalloy GH4169. Moreover, two modified Ince-Glinka fatigue damage parameters are put forward and evaluated under different load paths. Results show that the generalized strain amplitude model provides less accurate life predictions in the high cycle life regime and is better for life prediction in the low cycle life regime; however, the generalized strain energy model is relatively better for high cycle life prediction and is conservative for low cycle life prediction under multiaxial loadings. In addition, the Fatemi–Socie model is introduced for model comparison and its additional material parameter k is found to not be a constant and its usage is discussed. Finally, model comparison and prediction error analysis are used to illustrate the superiority of the proposed damage parameter in multiaxial fatigue life prediction of the two aviation alloys under various loadings. PMID:28792487

  20. Multiaxial Fatigue Damage Parameter and Life Prediction without Any Additional Material Constants.

    PubMed

    Yu, Zheng-Yong; Zhu, Shun-Peng; Liu, Qiang; Liu, Yunhan

    2017-08-09

    Based on the critical plane approach, a simple and efficient multiaxial fatigue damage parameter with no additional material constants is proposed for life prediction under uniaxial/multiaxial proportional and/or non-proportional loadings for titanium alloy TC4 and nickel-based superalloy GH4169. Moreover, two modified Ince-Glinka fatigue damage parameters are put forward and evaluated under different load paths. Results show that the generalized strain amplitude model provides less accurate life predictions in the high cycle life regime and is better for life prediction in the low cycle life regime; however, the generalized strain energy model is relatively better for high cycle life prediction and is conservative for low cycle life prediction under multiaxial loadings. In addition, the Fatemi-Socie model is introduced for model comparison and its additional material parameter k is found to not be a constant and its usage is discussed. Finally, model comparison and prediction error analysis are used to illustrate the superiority of the proposed damage parameter in multiaxial fatigue life prediction of the two aviation alloys under various loadings.

  1. A data-input program (MFI2005) for the U.S. Geological Survey modular groundwater model (MODFLOW-2005) and parameter estimation program (UCODE_2005)

    USGS Publications Warehouse

    Harbaugh, Arien W.

    2011-01-01

    The MFI2005 data-input (entry) program was developed for use with the U.S. Geological Survey modular three-dimensional finite-difference groundwater model, MODFLOW-2005. MFI2005 runs on personal computers and is designed to be easy to use; data are entered interactively through a series of display screens. MFI2005 supports parameter estimation using the UCODE_2005 program for parameter estimation. Data for MODPATH, a particle-tracking program for use with MODFLOW-2005, also can be entered using MFI2005. MFI2005 can be used in conjunction with other data-input programs so that the different parts of a model dataset can be entered by using the most suitable program.

  2. Computational Process Modeling for Additive Manufacturing

    NASA Technical Reports Server (NTRS)

    Bagg, Stacey; Zhang, Wei

    2014-01-01

    Computational Process and Material Modeling of Powder Bed additive manufacturing of IN 718. Optimize material build parameters with reduced time and cost through modeling. Increase understanding of build properties. Increase reliability of builds. Decrease time to adoption of process for critical hardware. Potential to decrease post-build heat treatments. Conduct single-track and coupon builds at various build parameters. Record build parameter information and QM Meltpool data. Refine Applied Optimization powder bed AM process model using data. Report thermal modeling results. Conduct metallography of build samples. Calibrate STK models using metallography findings. Run STK models using AO thermal profiles and report STK modeling results. Validate modeling with additional build. Photodiode Intensity measurements highly linear with power input. Melt Pool Intensity highly correlated to Melt Pool Size. Melt Pool size and intensity increase with power. Applied Optimization will use data to develop powder bed additive manufacturing process model.

  3. Assessing the required additional organic inputs to soils to reach the 4 per 1000 objective at the global scale: a RothC project

    NASA Astrophysics Data System (ADS)

    Lutfalla, Suzanne; Skalsky, Rastislav; Martin, Manuel; Balkovic, Juraj; Havlik, Petr; Soussana, Jean-François

    2017-04-01

    The 4 per 1000 Initiative underlines the role of soil organic matter in addressing the three-fold challenge of food security, adaptation of the land sector to climate change, and mitigation of human-induced GHG emissions. It sets an ambitious global target of a 0.4% (4/1000) annual increase in top soil organic carbon (SOC) stock. The present collaborative project between the 4 per 1000 research program, INRA and IIASA aims at providing a first global assessment of the translation of this soil organic carbon sequestration target into the equivalent organic matter inputs target. Indeed, soil organic carbon builds up in the soil through different processes leading to an increased input of carbon to the system (by increasing returns to the soil for instance) or a decreased output of carbon from the system (mainly by biodegradation and mineralization processes). Here we answer the question of how much extra organic matter must be added to agricultural soils every year (in otherwise unchanged climatic conditions) in order to guarantee a 0.4% yearly increase of total soil organic carbon stocks (40cm soil depth is considered). We use the RothC model of soil organic matter turnover on a spatial grid over 10 years to model two situations for croplands: a first situation where soil organic carbon remains constant (system at equilibrium) and a second situation where soil organic matter increases by 0.4% every year. The model accounts for the effects of soil type, temperature, moisture content and plant cover on the turnover process, it is run on a monthly time step, and it can simulate the needed organic input to sustain a certain SOC stock (or evolution of SOC stock). These two SOC conditions lead to two average yearly plant inputs over 10 years. The difference between the two simulated inputs represent the additional yearly input needed to reach the 4 per 1000 objective (input_eq for inputs needed for SOC to remain constant; input_4/1000 for inputs needed for SOC to reach

  4. Multiple Input Design for Real-Time Parameter Estimation in the Frequency Domain

    NASA Technical Reports Server (NTRS)

    Morelli, Eugene

    2003-01-01

    A method for designing multiple inputs for real-time dynamic system identification in the frequency domain was developed and demonstrated. The designed inputs are mutually orthogonal in both the time and frequency domains, with reduced peak factors to provide good information content for relatively small amplitude excursions. The inputs are designed for selected frequency ranges, and therefore do not require a priori models. The experiment design approach was applied to identify linear dynamic models for the F-15 ACTIVE aircraft, which has multiple control effectors.

  5. 40 CFR 96.76 - Additional requirements to provide heat input data for allocations purposes.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... heat input data for allocations purposes. 96.76 Section 96.76 Protection of Environment ENVIRONMENTAL... to provide heat input data for allocations purposes. (a) The owner or operator of a unit that elects... also monitor and report heat input at the unit level using the procedures set forth in part 75 of this...

  6. 40 CFR 96.76 - Additional requirements to provide heat input data for allocations purposes.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... heat input data for allocations purposes. 96.76 Section 96.76 Protection of Environment ENVIRONMENTAL... to provide heat input data for allocations purposes. (a) The owner or operator of a unit that elects... also monitor and report heat input at the unit level using the procedures set forth in part 75 of this...

  7. 40 CFR 96.76 - Additional requirements to provide heat input data for allocations purposes.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... heat input data for allocations purposes. 96.76 Section 96.76 Protection of Environment ENVIRONMENTAL... to provide heat input data for allocations purposes. (a) The owner or operator of a unit that elects... also monitor and report heat input at the unit level using the procedures set forth in part 75 of this...

  8. 40 CFR 96.76 - Additional requirements to provide heat input data for allocations purposes.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... heat input data for allocations purposes. 96.76 Section 96.76 Protection of Environment ENVIRONMENTAL... to provide heat input data for allocations purposes. (a) The owner or operator of a unit that elects... also monitor and report heat input at the unit level using the procedures set forth in part 75 of this...

  9. Parametric analysis of parameters for electrical-load forecasting using artificial neural networks

    NASA Astrophysics Data System (ADS)

    Gerber, William J.; Gonzalez, Avelino J.; Georgiopoulos, Michael

    1997-04-01

    Accurate total system electrical load forecasting is a necessary part of resource management for power generation companies. The better the hourly load forecast, the more closely the power generation assets of the company can be configured to minimize the cost. Automating this process is a profitable goal and neural networks should provide an excellent means of doing the automation. However, prior to developing such a system, the optimal set of input parameters must be determined. The approach of this research was to determine what those inputs should be through a parametric study of potentially good inputs. Input parameters tested were ambient temperature, total electrical load, the day of the week, humidity, dew point temperature, daylight savings time, length of daylight, season, forecast light index and forecast wind velocity. For testing, a limited number of temperatures and total electrical loads were used as a basic reference input parameter set. Most parameters showed some forecasting improvement when added individually to the basic parameter set. Significantly, major improvements were exhibited with the day of the week, dew point temperatures, additional temperatures and loads, forecast light index and forecast wind velocity.

  10. Rheological parameters of dough with inulin addition and its effect on bread quality

    NASA Astrophysics Data System (ADS)

    Bojnanska, T.; Tokar, M.; Vollmannova, A.

    2015-04-01

    The rheological properties of enriched flour prepared with an addition of inulin were studied. The addition of inulin caused changes of the rheological parameters of the recorder curve. 10% and more addition significantly extended development time and on the farinogram were two peaks of consistency, what is a non-standard shape. With increasing addition of inulin resistance to deformation grows and dough is difficult to process, over 15% addition make dough short and unsuitable for making bread. Bread volume, the most important parameter, significantly decreased with inulin addition. Our results suggest a level of 5% inulin to produce a functional bread of high sensory acceptance and a level of 10% inulin produce a bread of satisfactory sensory acceptance. Bread with a level over 10% of inulin was unsatisfactory.

  11. Star Classification for the Kepler Input Catalog: From Images to Stellar Parameters

    NASA Astrophysics Data System (ADS)

    Brown, T. M.; Everett, M.; Latham, D. W.; Monet, D. G.

    2005-12-01

    The Stellar Classification Project is a ground-based effort to screen stars within the Kepler field of view, to allow removal of stars with large radii (and small potential transit signals) from the target list. Important components of this process are: (1) An automated photometry pipeline estimates observed magnitudes both for target stars and for stars in several calibration fields. (2) Data from calibration fields yield extinction-corrected AB magnitudes (with g, r, i, z magnitudes transformed to the SDSS system). We merge these with 2MASS J, H, K magnitudes. (3) The Basel grid of stellar atmosphere models yields synthetic colors, which are transformed to our photometric system by calibration against observations of stars in M67. (4) We combine the r magnitude and stellar galactic latitude with a simple model of interstellar extinction to derive a relation connecting {Teff, luminosity} to distance and reddening. For models satisfying this relation, we compute a chi-squared statistic describing the match between each model and the observed colors. (5) We create a merit function based on the chi-squared statistic, and on a Bayesian prior probability distribution which gives probability as a function of Teff, luminosity, log(Z), and height above the galactic plane. The stellar parameters ascribed to a star are those of the model that maximizes this merit function. (6) Parameter estimates are merged with positional and other information from extant catalogs to yield the Kepler Input Catalog, from which targets will be chosen. Testing and validation of this procedure are underway, with encouraging initial results.

  12. Impact of spatial and temporal aggregation of input parameters on the assessment of irrigation scheme performance

    NASA Astrophysics Data System (ADS)

    Lorite, I. J.; Mateos, L.; Fereres, E.

    2005-01-01

    SummaryThe simulations of dynamic, spatially distributed non-linear models are impacted by the degree of spatial and temporal aggregation of their input parameters and variables. This paper deals with the impact of these aggregations on the assessment of irrigation scheme performance by simulating water use and crop yield. The analysis was carried out on a 7000 ha irrigation scheme located in Southern Spain. Four irrigation seasons differing in rainfall patterns were simulated (from 1996/1997 to 1999/2000) with the actual soil parameters and with hypothetical soil parameters representing wider ranges of soil variability. Three spatial aggregation levels were considered: (I) individual parcels (about 800), (II) command areas (83) and (III) the whole irrigation scheme. Equally, five temporal aggregation levels were defined: daily, weekly, monthly, quarterly and annually. The results showed little impact of spatial aggregation in the predictions of irrigation requirements and of crop yield for the scheme. The impact of aggregation was greater in rainy years, for deep-rooted crops (sunflower) and in scenarios with heterogeneous soils. The highest impact on irrigation requirement estimations was in the scenario of most heterogeneous soil and in 1999/2000, a year with frequent rainfall during the irrigation season: difference of 7% between aggregation levels I and III was found. Equally, it was found that temporal aggregation had only significant impact on irrigation requirements predictions for time steps longer than 4 months. In general, simulated annual irrigation requirements decreased as the time step increased. The impact was greater in rainy years (specially with abundant and concentrated rain events) and in crops which cycles coincide in part with the rainy season (garlic, winter cereals and olive). It is concluded that in this case, average, representative values for the main inputs of the model (crop, soil properties and sowing dates) can generate results

  13. Anomalous neuronal responses to fluctuated inputs

    NASA Astrophysics Data System (ADS)

    Hosaka, Ryosuke; Sakai, Yutaka

    2015-10-01

    The irregular firing of a cortical neuron is thought to result from a highly fluctuating drive that is generated by the balance of excitatory and inhibitory synaptic inputs. A previous study reported anomalous responses of the Hodgkin-Huxley neuron to the fluctuated inputs where an irregularity of spike trains is inversely proportional to an input irregularity. In the current study, we investigated the origin of these anomalous responses with the Hindmarsh-Rose neuron model, map-based models, and a simple mixture of interspike interval distributions. First, we specified the parameter regions for the bifurcations in the Hindmarsh-Rose model, and we confirmed that the model reproduced the anomalous responses in the dynamics of the saddle-node and subcritical Hopf bifurcations. For both bifurcations, the Hindmarsh-Rose model shows bistability in the resting state and the repetitive firing state, which indicated that the bistability was the origin of the anomalous input-output relationship. Similarly, the map-based model that contained bistability reproduced the anomalous responses, while the model without bistability did not. These results were supported by additional findings that the anomalous responses were reproduced by mimicking the bistable firing with a mixture of two different interspike interval distributions. Decorrelation of spike trains is important for neural information processing. For such spike train decorrelation, irregular firing is key. Our results indicated that irregular firing can emerge from fluctuating drives, even weak ones, under conditions involving bistability. The anomalous responses, therefore, contribute to efficient processing in the brain.

  14. Reconstruction of neuronal input through modeling single-neuron dynamics and computations

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

    Qin, Qing; Wang, Jiang; Yu, Haitao

    Mathematical models provide a mathematical description of neuron activity, which can better understand and quantify neural computations and corresponding biophysical mechanisms evoked by stimulus. In this paper, based on the output spike train evoked by the acupuncture mechanical stimulus, we present two different levels of models to describe the input-output system to achieve the reconstruction of neuronal input. The reconstruction process is divided into two steps: First, considering the neuronal spiking event as a Gamma stochastic process. The scale parameter and the shape parameter of Gamma process are, respectively, defined as two spiking characteristics, which are estimated by a state-spacemore » method. Then, leaky integrate-and-fire (LIF) model is used to mimic the response system and the estimated spiking characteristics are transformed into two temporal input parameters of LIF model, through two conversion formulas. We test this reconstruction method by three different groups of simulation data. All three groups of estimates reconstruct input parameters with fairly high accuracy. We then use this reconstruction method to estimate the non-measurable acupuncture input parameters. Results show that under three different frequencies of acupuncture stimulus conditions, estimated input parameters have an obvious difference. The higher the frequency of the acupuncture stimulus is, the higher the accuracy of reconstruction is.« less

  15. Reconstruction of neuronal input through modeling single-neuron dynamics and computations

    NASA Astrophysics Data System (ADS)

    Qin, Qing; Wang, Jiang; Yu, Haitao; Deng, Bin; Chan, Wai-lok

    2016-06-01

    Mathematical models provide a mathematical description of neuron activity, which can better understand and quantify neural computations and corresponding biophysical mechanisms evoked by stimulus. In this paper, based on the output spike train evoked by the acupuncture mechanical stimulus, we present two different levels of models to describe the input-output system to achieve the reconstruction of neuronal input. The reconstruction process is divided into two steps: First, considering the neuronal spiking event as a Gamma stochastic process. The scale parameter and the shape parameter of Gamma process are, respectively, defined as two spiking characteristics, which are estimated by a state-space method. Then, leaky integrate-and-fire (LIF) model is used to mimic the response system and the estimated spiking characteristics are transformed into two temporal input parameters of LIF model, through two conversion formulas. We test this reconstruction method by three different groups of simulation data. All three groups of estimates reconstruct input parameters with fairly high accuracy. We then use this reconstruction method to estimate the non-measurable acupuncture input parameters. Results show that under three different frequencies of acupuncture stimulus conditions, estimated input parameters have an obvious difference. The higher the frequency of the acupuncture stimulus is, the higher the accuracy of reconstruction is.

  16. System and method for motor parameter estimation

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

    Luhrs, Bin; Yan, Ting

    2014-03-18

    A system and method for determining unknown values of certain motor parameters includes a motor input device connectable to an electric motor having associated therewith values for known motor parameters and an unknown value of at least one motor parameter. The motor input device includes a processing unit that receives a first input from the electric motor comprising values for the known motor parameters for the electric motor and receive a second input comprising motor data on a plurality of reference motors, including values for motor parameters corresponding to the known motor parameters of the electric motor and values formore » motor parameters corresponding to the at least one unknown motor parameter value of the electric motor. The processor determines the unknown value of the at least one motor parameter from the first input and the second input and determines a motor management strategy for the electric motor based thereon.« less

  17. Incorporating uncertainty in RADTRAN 6.0 input files.

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

    Dennis, Matthew L.; Weiner, Ruth F.; Heames, Terence John

    Uncertainty may be introduced into RADTRAN analyses by distributing input parameters. The MELCOR Uncertainty Engine (Gauntt and Erickson, 2004) has been adapted for use in RADTRAN to determine the parameter shape and minimum and maximum of the distribution, to sample on the distribution, and to create an appropriate RADTRAN batch file. Coupling input parameters is not possible in this initial application. It is recommended that the analyst be very familiar with RADTRAN and able to edit or create a RADTRAN input file using a text editor before implementing the RADTRAN Uncertainty Analysis Module. Installation of the MELCOR Uncertainty Engine ismore » required for incorporation of uncertainty into RADTRAN. Gauntt and Erickson (2004) provides installation instructions as well as a description and user guide for the uncertainty engine.« less

  18. Global Nitrous Oxide Emissions from Agricultural Soils: Magnitude and Uncertainties Associated with Input Data and Model Parameters

    NASA Astrophysics Data System (ADS)

    Xu, R.; Tian, H.; Pan, S.; Yang, J.; Lu, C.; Zhang, B.

    2016-12-01

    Human activities have caused significant perturbations of the nitrogen (N) cycle, resulting in about 21% increase of atmospheric N2O concentration since the pre-industrial era. This large increase is mainly caused by intensive agricultural activities including the application of nitrogen fertilizer and the expansion of leguminous crops. Substantial efforts have been made to quantify the global and regional N2O emission from agricultural soils in the last several decades using a wide variety of approaches, such as ground-based observation, atmospheric inversion, and process-based model. However, large uncertainties exist in those estimates as well as methods themselves. In this study, we used a coupled biogeochemical model (DLEM) to estimate magnitude, spatial, and temporal patterns of N2O emissions from global croplands in the past five decades (1961-2012). To estimate uncertainties associated with input data and model parameters, we have implemented a number of simulation experiments with DLEM, accounting for key parameter values that affect calculation of N2O fluxes (i.e., maximum nitrification and denitrification rates, N fixation rate, and the adsorption coefficient for soil ammonium and nitrate), different sets of input data including climate, land management practices (i.e., nitrogen fertilizer types, application rates and timings, with/without irrigation), N deposition, and land use and land cover change. This work provides a robust estimate of global N2O emissions from agricultural soils as well as identifies key gaps and limitations in the existing model and data that need to be investigated in the future.

  19. Ionic micelles and aromatic additives: a closer look at the molecular packing parameter.

    PubMed

    Lutz-Bueno, Viviane; Isabettini, Stéphane; Walker, Franziska; Kuster, Simon; Liebi, Marianne; Fischer, Peter

    2017-08-16

    Wormlike micellar aggregates formed from the mixture of ionic surfactants with aromatic additives result in solutions with impressive viscoelastic properties. These properties are of high interest for numerous industrial applications and are often used as model systems for soft matter physics. However, robust and simple models for tailoring the viscoelastic response of the solution based on the molecular structure of the employed additive are required to fully exploit the potential of these systems. We address this shortcoming with a modified packing parameter based model, considering the additive-surfactant pair. The role of charge neutralization on anisotropic micellar growth was investigated with derivatives of sodium salicylate. The impact of the additives on the morphology of the micellar aggregates is explained from the molecular level to the macroscopic viscoelasticity. Changes in the micelle's volume, headgroup area and additive structure are explored to redefine the packing parameter. Uncharged additives penetrated deeper into the hydrophobic region of the micelle, whilst charged additives remained trapped in the polar region, as revealed by a combination of 1 H-NMR, SAXS and rheological measurements. A deeper penetration of the additives densified the hydrophobic core of the micelle and induced anisotropic growth by increasing the effective volume of the additive-surfactant pair. This phenomenon largely influenced the viscosity of the solutions. Partially penetrating additives reduced the electrostatic repulsions between surfactant headgroups and neighboring micelles. The resulting increased network density governed the elasticity of the solutions. Considering a packing parameter composed of the additive-surfactant pair proved to be a facile means of engineering the viscoelastic response of surfactant solutions. The self-assembly of the wormlike micellar aggregates could be tailored to desired morphologies resulting in a specific and predictable

  20. Hole-assisted fiber based fiber fuse terminator supporting 22 W input

    NASA Astrophysics Data System (ADS)

    Tsujikawa, Kyozo; Kurokawa, Kenji; Hanzawa, Nobutomo; Nozoe, Saki; Matsui, Takashi; Nakajima, Kazuhide

    2018-05-01

    We investigated the air hole structure in hole-assisted fiber (HAF) with the aim of terminating fiber fuse propagation. We focused on two structural parameters c/MFD and S1/S2, which are related respectively to the position and area of the air holes, and mapped their appropriate values for terminating fiber fuse propagation. Here, MFD is the mode field diameter, c is the diameter of an inscribed circle linking the air holes, S1 is the total area of the air holes, and S2 is the area of a circumscribed circle linking the air holes. On the basis of these results, we successfully realized a compact fiber fuse terminator consisting of a 1.35 mm-long HAF, which can terminate fiber fuse propagation even with a 22 W input. In addition, we observed fiber fuse termination using a high-speed camera. We additionally confirmed that the HAF-based fiber fuse terminator is effective under various input power conditions. The penetration length of the optical discharge in the HAF was only less than 300 μm when the input power was from 2 to 22 W.

  1. INDES User's guide multistep input design with nonlinear rotorcraft modeling

    NASA Technical Reports Server (NTRS)

    1979-01-01

    The INDES computer program, a multistep input design program used as part of a data processing technique for rotorcraft systems identification, is described. Flight test inputs base on INDES improve the accuracy of parameter estimates. The input design algorithm, program input, and program output are presented.

  2. Effect of Heat Input on Inclusion Evolution Behavior in Heat-Affected Zone of EH36 Shipbuilding Steel

    NASA Astrophysics Data System (ADS)

    Sun, Jincheng; Zou, Xiaodong; Matsuura, Hiroyuki; Wang, Cong

    2018-03-01

    The effects of heat input parameters on inclusion and microstructure characteristics have been investigated using welding thermal simulations. Inclusion features from heat-affected zones (HAZs) were profiled. It was found that, under heat input of 120 kJ/cm, Al-Mg-Ti-O-(Mn-S) composite inclusions can act effectively as nucleation sites for acicular ferrites. However, this ability disappears when the heat input is increased to 210 kJ/cm. In addition, confocal scanning laser microscopy (CSLM) was used to document possible inclusion-microstructure interactions, shedding light on how inclusions assist beneficial transformations toward property enhancement.

  3. Effect of Heat Input on Inclusion Evolution Behavior in Heat-Affected Zone of EH36 Shipbuilding Steel

    NASA Astrophysics Data System (ADS)

    Sun, Jincheng; Zou, Xiaodong; Matsuura, Hiroyuki; Wang, Cong

    2018-06-01

    The effects of heat input parameters on inclusion and microstructure characteristics have been investigated using welding thermal simulations. Inclusion features from heat-affected zones (HAZs) were profiled. It was found that, under heat input of 120 kJ/cm, Al-Mg-Ti-O-(Mn-S) composite inclusions can act effectively as nucleation sites for acicular ferrites. However, this ability disappears when the heat input is increased to 210 kJ/cm. In addition, confocal scanning laser microscopy (CSLM) was used to document possible inclusion-microstructure interactions, shedding light on how inclusions assist beneficial transformations toward property enhancement.

  4. Relative sensitivities of DCE-MRI pharmacokinetic parameters to arterial input function (AIF) scaling

    NASA Astrophysics Data System (ADS)

    Li, Xin; Cai, Yu; Moloney, Brendan; Chen, Yiyi; Huang, Wei; Woods, Mark; Coakley, Fergus V.; Rooney, William D.; Garzotto, Mark G.; Springer, Charles S.

    2016-08-01

    Dynamic-Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) has been used widely for clinical applications. Pharmacokinetic modeling of DCE-MRI data that extracts quantitative contrast reagent/tissue-specific model parameters is the most investigated method. One of the primary challenges in pharmacokinetic analysis of DCE-MRI data is accurate and reliable measurement of the arterial input function (AIF), which is the driving force behind all pharmacokinetics. Because of effects such as inflow and partial volume averaging, AIF measured from individual arteries sometimes require amplitude scaling for better representation of the blood contrast reagent (CR) concentration time-courses. Empirical approaches like blinded AIF estimation or reference tissue AIF derivation can be useful and practical, especially when there is no clearly visible blood vessel within the imaging field-of-view (FOV). Similarly, these approaches generally also require magnitude scaling of the derived AIF time-courses. Since the AIF varies among individuals even with the same CR injection protocol and the perfect scaling factor for reconstructing the ground truth AIF often remains unknown, variations in estimated pharmacokinetic parameters due to varying AIF scaling factors are of special interest. In this work, using simulated and real prostate cancer DCE-MRI data, we examined parameter variations associated with AIF scaling. Our results show that, for both the fast-exchange-limit (FXL) Tofts model and the water exchange sensitized fast-exchange-regime (FXR) model, the commonly fitted CR transfer constant (Ktrans) and the extravascular, extracellular volume fraction (ve) scale nearly proportionally with the AIF, whereas the FXR-specific unidirectional cellular water efflux rate constant, kio, and the CR intravasation rate constant, kep, are both AIF scaling insensitive. This indicates that, for DCE-MRI of prostate cancer and possibly other cancers, kio and kep may be more suitable imaging

  5. Relative sensitivities of DCE-MRI pharmacokinetic parameters to arterial input function (AIF) scaling.

    PubMed

    Li, Xin; Cai, Yu; Moloney, Brendan; Chen, Yiyi; Huang, Wei; Woods, Mark; Coakley, Fergus V; Rooney, William D; Garzotto, Mark G; Springer, Charles S

    2016-08-01

    Dynamic-Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) has been used widely for clinical applications. Pharmacokinetic modeling of DCE-MRI data that extracts quantitative contrast reagent/tissue-specific model parameters is the most investigated method. One of the primary challenges in pharmacokinetic analysis of DCE-MRI data is accurate and reliable measurement of the arterial input function (AIF), which is the driving force behind all pharmacokinetics. Because of effects such as inflow and partial volume averaging, AIF measured from individual arteries sometimes require amplitude scaling for better representation of the blood contrast reagent (CR) concentration time-courses. Empirical approaches like blinded AIF estimation or reference tissue AIF derivation can be useful and practical, especially when there is no clearly visible blood vessel within the imaging field-of-view (FOV). Similarly, these approaches generally also require magnitude scaling of the derived AIF time-courses. Since the AIF varies among individuals even with the same CR injection protocol and the perfect scaling factor for reconstructing the ground truth AIF often remains unknown, variations in estimated pharmacokinetic parameters due to varying AIF scaling factors are of special interest. In this work, using simulated and real prostate cancer DCE-MRI data, we examined parameter variations associated with AIF scaling. Our results show that, for both the fast-exchange-limit (FXL) Tofts model and the water exchange sensitized fast-exchange-regime (FXR) model, the commonly fitted CR transfer constant (K(trans)) and the extravascular, extracellular volume fraction (ve) scale nearly proportionally with the AIF, whereas the FXR-specific unidirectional cellular water efflux rate constant, kio, and the CR intravasation rate constant, kep, are both AIF scaling insensitive. This indicates that, for DCE-MRI of prostate cancer and possibly other cancers, kio and kep may be more suitable imaging

  6. Update on ɛK with lattice QCD inputs

    NASA Astrophysics Data System (ADS)

    Jang, Yong-Chull; Lee, Weonjong; Lee, Sunkyu; Leem, Jaehoon

    2018-03-01

    We report updated results for ɛK, the indirect CP violation parameter in neutral kaons, which is evaluated directly from the standard model with lattice QCD inputs. We use lattice QCD inputs to fix B\\hatk,|Vcb|,ξ0,ξ2,|Vus|, and mc(mc). Since Lattice 2016, the UTfit group has updated the Wolfenstein parameters in the angle-only-fit method, and the HFLAV group has also updated |Vcb|. Our results show that the evaluation of ɛK with exclusive |Vcb| (lattice QCD inputs) has 4.0σ tension with the experimental value, while that with inclusive |Vcb| (heavy quark expansion based on OPE and QCD sum rules) shows no tension.

  7. Soil Microbe Active Community Composition and Capability of Responding to Litter Addition after 12 Years of No Inputs

    PubMed Central

    Brewer, Elizabeth; Yarwood, Rockie; Lajtha, Kate; Myrold, David

    2013-01-01

    One explanation given for the high microbial diversity found in soils is that they contain a large inactive biomass that is able to persist in soils for long periods of time. This persistent microbial fraction may help to buffer the functionality of the soil community during times of low nutrients by providing a reservoir of specialized functions that can be reactivated when conditions improve. A study was designed to test the hypothesis: in soils lacking fresh root or detrital inputs, microbial community composition may persist relatively unchanged. Upon addition of new inputs, this community will be stimulated to grow and break down litter similarly to control soils. Soils from two of the Detrital Input and Removal Treatments (DIRT) at the H. J. Andrews Experimental Forest, the no-input and control treatment plots, were used in a microcosm experiment where Douglas-fir needles were added to soils. After 3 and 151 days of incubation, soil microbial DNA and RNA was extracted and characterized using quantitative PCR (qPCR) and 454 pyrosequencing. The abundance of 16S and 28S gene copies and RNA copies did not vary with soil type or amendment; however, treatment differences were observed in the abundance of archaeal ammonia-oxidizing amoA gene abundance. Analysis of ∼110,000 bacterial sequences showed a significant change in the active (RNA-based) community between day 3 and day 151, but microbial composition was similar between soil types. These results show that even after 12 years of plant litter exclusion, the legacy of community composition was well buffered against a dramatic disturbance. PMID:23263952

  8. Bayesian analysis of input uncertainty in hydrological modeling: 2. Application

    NASA Astrophysics Data System (ADS)

    Kavetski, Dmitri; Kuczera, George; Franks, Stewart W.

    2006-03-01

    The Bayesian total error analysis (BATEA) methodology directly addresses both input and output errors in hydrological modeling, requiring the modeler to make explicit, rather than implicit, assumptions about the likely extent of data uncertainty. This study considers a BATEA assessment of two North American catchments: (1) French Broad River and (2) Potomac basins. It assesses the performance of the conceptual Variable Infiltration Capacity (VIC) model with and without accounting for input (precipitation) uncertainty. The results show the considerable effects of precipitation errors on the predicted hydrographs (especially the prediction limits) and on the calibrated parameters. In addition, the performance of BATEA in the presence of severe model errors is analyzed. While BATEA allows a very direct treatment of input uncertainty and yields some limited insight into model errors, it requires the specification of valid error models, which are currently poorly understood and require further work. Moreover, it leads to computationally challenging highly dimensional problems. For some types of models, including the VIC implemented using robust numerical methods, the computational cost of BATEA can be reduced using Newton-type methods.

  9. The improved z-scan technique: potentialities of the additional right-angle scattering channel and the input polarization control

    NASA Astrophysics Data System (ADS)

    Volchkov, S. S.; Yuvchenko, S. A.; Zimnyakov, D. A.

    2018-04-01

    The theoretical possibility of retrieving the additional information on the dielectric properties of the nanoparticles material by single scattering in suspensions was studied. We have demonstrated a method of recreating the dielectric function of the material in the fundamental absorption band using the closed aperture z-scanning with the simultaneous Rayleigh scattering intensity measurements and the polarization control of an input laser beam. A possibility to recreate the form factor of the non-spherical particles or anisotropic nonlinear sensitivity for the sphere-like particles was also observed.

  10. Input design for identification of aircraft stability and control derivatives

    NASA Technical Reports Server (NTRS)

    Gupta, N. K.; Hall, W. E., Jr.

    1975-01-01

    An approach for designing inputs to identify stability and control derivatives from flight test data is presented. This approach is based on finding inputs which provide the maximum possible accuracy of derivative estimates. Two techniques of input specification are implemented for this objective - a time domain technique and a frequency domain technique. The time domain technique gives the control input time history and can be used for any allowable duration of test maneuver, including those where data lengths can only be of short duration. The frequency domain technique specifies the input frequency spectrum, and is best applied for tests where extended data lengths, much longer than the time constants of the modes of interest, are possible. These technqiues are used to design inputs to identify parameters in longitudinal and lateral linear models of conventional aircraft. The constraints of aircraft response limits, such as on structural loads, are realized indirectly through a total energy constraint on the input. Tests with simulated data and theoretical predictions show that the new approaches give input signals which can provide more accurate parameter estimates than can conventional inputs of the same total energy. Results obtained indicate that the approach has been brought to the point where it should be used on flight tests for further evaluation.

  11. Bilinearity in Spatiotemporal Integration of Synaptic Inputs

    PubMed Central

    Li, Songting; Liu, Nan; Zhang, Xiao-hui; Zhou, Douglas; Cai, David

    2014-01-01

    Neurons process information via integration of synaptic inputs from dendrites. Many experimental results demonstrate dendritic integration could be highly nonlinear, yet few theoretical analyses have been performed to obtain a precise quantitative characterization analytically. Based on asymptotic analysis of a two-compartment passive cable model, given a pair of time-dependent synaptic conductance inputs, we derive a bilinear spatiotemporal dendritic integration rule. The summed somatic potential can be well approximated by the linear summation of the two postsynaptic potentials elicited separately, plus a third additional bilinear term proportional to their product with a proportionality coefficient . The rule is valid for a pair of synaptic inputs of all types, including excitation-inhibition, excitation-excitation, and inhibition-inhibition. In addition, the rule is valid during the whole dendritic integration process for a pair of synaptic inputs with arbitrary input time differences and input locations. The coefficient is demonstrated to be nearly independent of the input strengths but is dependent on input times and input locations. This rule is then verified through simulation of a realistic pyramidal neuron model and in electrophysiological experiments of rat hippocampal CA1 neurons. The rule is further generalized to describe the spatiotemporal dendritic integration of multiple excitatory and inhibitory synaptic inputs. The integration of multiple inputs can be decomposed into the sum of all possible pairwise integration, where each paired integration obeys the bilinear rule. This decomposition leads to a graph representation of dendritic integration, which can be viewed as functionally sparse. PMID:25521832

  12. Inverse optimal design of input-to-state stabilisation for affine nonlinear systems with input delays

    NASA Astrophysics Data System (ADS)

    Cai, Xiushan; Meng, Lingxin; Zhang, Wei; Liu, Leipo

    2018-03-01

    We establish robustness of the predictor feedback control law to perturbations appearing at the system input for affine nonlinear systems with time-varying input delay and additive disturbances. Furthermore, it is shown that it is inverse optimal with respect to a differential game problem. All of the stability and inverse optimality proofs are based on the infinite-dimensional backstepping transformation and an appropriate Lyapunov functional. A single-link manipulator subject to input delays and disturbances is given to illustrate the validity of the proposed method.

  13. Rapid Debris Analysis Project Task 3 Final Report - Sensitivity of Fallout to Source Parameters, Near-Detonation Environment Material Properties, Topography, and Meteorology

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

    Goldstein, Peter

    2014-01-24

    This report describes the sensitivity of predicted nuclear fallout to a variety of model input parameters, including yield, height of burst, particle and activity size distribution parameters, wind speed, wind direction, topography, and precipitation. We investigate sensitivity over a wide but plausible range of model input parameters. In addition, we investigate a specific example with a relatively narrow range to illustrate the potential for evaluating uncertainties in predictions when there are more precise constraints on model parameters.

  14. Using model order tests to determine sensory inputs in a motion study

    NASA Technical Reports Server (NTRS)

    Repperger, D. W.; Junker, A. M.

    1977-01-01

    In the study of motion effects on tracking performance, a problem of interest is the determination of what sensory inputs a human uses in controlling his tracking task. In the approach presented here a simple canonical model (FID or a proportional, integral, derivative structure) is used to model the human's input-output time series. A study of significant changes in reduction of the output error loss functional is conducted as different permutations of parameters are considered. Since this canonical model includes parameters which are related to inputs to the human (such as the error signal, its derivatives and integration), the study of model order is equivalent to the study of which sensory inputs are being used by the tracker. The parameters are obtained which have the greatest effect on reducing the loss function significantly. In this manner the identification procedure converts the problem of testing for model order into the problem of determining sensory inputs.

  15. Master control data handling program uses automatic data input

    NASA Technical Reports Server (NTRS)

    Alliston, W.; Daniel, J.

    1967-01-01

    General purpose digital computer program is applicable for use with analysis programs that require basic data and calculated parameters as input. It is designed to automate input data preparation for flight control computer programs, but it is general enough to permit application in other areas.

  16. Influence of additive laser manufacturing parameters on surface using density of partially melted particles

    NASA Astrophysics Data System (ADS)

    Rosa, Benoit; Brient, Antoine; Samper, Serge; Hascoët, Jean-Yves

    2016-12-01

    Mastering the additive laser manufacturing surface is a real challenge and would allow functional surfaces to be obtained without finishing. Direct Metal Deposition (DMD) surfaces are composed by directional and chaotic textures that are directly linked to the process principles. The aim of this work is to obtain surface topographies by mastering the operating process parameters. Based on experimental investigation, the influence of operating parameters on the surface finish has been modeled. Topography parameters and multi-scale analysis have been used in order to characterize the DMD obtained surfaces. This study also proposes a methodology to characterize DMD chaotic texture through topography filtering and 3D image treatment. In parallel, a new parameter is proposed: density of particles (D p). Finally, this study proposes a regression modeling between process parameters and density of particles parameter.

  17. Genetic algorithm based input selection for a neural network function approximator with applications to SSME health monitoring

    NASA Technical Reports Server (NTRS)

    Peck, Charles C.; Dhawan, Atam P.; Meyer, Claudia M.

    1991-01-01

    A genetic algorithm is used to select the inputs to a neural network function approximator. In the application considered, modeling critical parameters of the space shuttle main engine (SSME), the functional relationship between measured parameters is unknown and complex. Furthermore, the number of possible input parameters is quite large. Many approaches have been used for input selection, but they are either subjective or do not consider the complex multivariate relationships between parameters. Due to the optimization and space searching capabilities of genetic algorithms they were employed to systematize the input selection process. The results suggest that the genetic algorithm can generate parameter lists of high quality without the explicit use of problem domain knowledge. Suggestions for improving the performance of the input selection process are also provided.

  18. Correlation of iodine uptake and perfusion parameters between dual-energy CT imaging and first-pass dual-input perfusion CT in lung cancer.

    PubMed

    Chen, Xiaoliang; Xu, Yanyan; Duan, Jianghui; Li, Chuandong; Sun, Hongliang; Wang, Wu

    2017-07-01

    To investigate the potential relationship between perfusion parameters from first-pass dual-input perfusion computed tomography (DI-PCT) and iodine uptake levels estimated from dual-energy CT (DE-CT).The pre-experimental part of this study included a dynamic DE-CT protocol in 15 patients to evaluate peak arterial enhancement of lung cancer based on time-attenuation curves, and the scan time of DE-CT was determined. In the prospective part of the study, 28 lung cancer patients underwent whole-volume perfusion CT and single-source DE-CT using 320-row CT. Pulmonary flow (PF, mL/min/100 mL), aortic flow (AF, mL/min/100 mL), and a perfusion index (PI = PF/[PF + AF]) were automatically generated by in-house commercial software using the dual-input maximum slope method for DI-PCT. For the dual-energy CT data, iodine uptake was estimated by the difference (λ) and the slope (λHU). λ was defined as the difference of CT values between 40 and 70 KeV monochromatic images in lung lesions. λHU was calculated by the following equation: λHU = |λ/(70 - 40)|. The DI-PCT and DE-CT parameters were analyzed by Pearson/Spearman correlation analysis, respectively.All subjects were pathologically proved as lung cancer patients (including 16 squamous cell carcinoma, 8 adenocarcinoma, and 4 small cell lung cancer) by surgery or CT-guided biopsy. Interobserver reproducibility in DI-PCT (PF, AF, PI) and DE-CT (λ, λHU) were relatively good to excellent (intraclass correlation coefficient [ICC]Inter = 0.8726-0.9255, ICCInter = 0.8179-0.8842; ICCInter = 0.8881-0.9177, ICCInter = 0.9820-0.9970, ICCInter = 0.9780-0.9971, respectively). Correlation coefficient between λ and AF, and PF were as follows: 0.589 (P < .01) and 0.383 (P < .05). Correlation coefficient between λHU and AF, and PF were as follows: 0.564 (P < .01) and 0.388 (P < .05).Both the single-source DE-CT and dual-input CT perfusion analysis method can be applied to

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

    PubMed

    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.

  20. The dynamics of integrate-and-fire: mean versus variance modulations and dependence on baseline parameters.

    PubMed

    Pressley, Joanna; Troyer, Todd W

    2011-05-01

    The leaky integrate-and-fire (LIF) is the simplest neuron model that captures the essential properties of neuronal signaling. Yet common intuitions are inadequate to explain basic properties of LIF responses to sinusoidal modulations of the input. Here we examine responses to low and moderate frequency modulations of both the mean and variance of the input current and quantify how these responses depend on baseline parameters. Across parameters, responses to modulations in the mean current are low pass, approaching zero in the limit of high frequencies. For very low baseline firing rates, the response cutoff frequency matches that expected from membrane integration. However, the cutoff shows a rapid, supralinear increase with firing rate, with a steeper increase in the case of lower noise. For modulations of the input variance, the gain at high frequency remains finite. Here, we show that the low-frequency responses depend strongly on baseline parameters and derive an analytic condition specifying the parameters at which responses switch from being dominated by low versus high frequencies. Additionally, we show that the resonant responses for variance modulations have properties not expected for common oscillatory resonances: they peak at frequencies higher than the baseline firing rate and persist when oscillatory spiking is disrupted by high noise. Finally, the responses to mean and variance modulations are shown to have a complementary dependence on baseline parameters at higher frequencies, resulting in responses to modulations of Poisson input rates that are independent of baseline input statistics.

  1. Optimisation of Ferrochrome Addition Using Multi-Objective Evolutionary and Genetic Algorithms for Stainless Steel Making via AOD Converter

    NASA Astrophysics Data System (ADS)

    Behera, Kishore Kumar; Pal, Snehanshu

    2018-03-01

    This paper describes a new approach towards optimum utilisation of ferrochrome added during stainless steel making in AOD converter. The objective of optimisation is to enhance end blow chromium content of steel and reduce the ferrochrome addition during refining. By developing a thermodynamic based mathematical model, a study has been conducted to compute the optimum trade-off between ferrochrome addition and end blow chromium content of stainless steel using a predator prey genetic algorithm through training of 100 dataset considering different input and output variables such as oxygen, argon, nitrogen blowing rate, duration of blowing, initial bath temperature, chromium and carbon content, weight of ferrochrome added during refining. Optimisation is performed within constrained imposed on the input parameters whose values fall within certain ranges. The analysis of pareto fronts is observed to generate a set of feasible optimal solution between the two conflicting objectives that provides an effective guideline for better ferrochrome utilisation. It is found out that after a certain critical range, further addition of ferrochrome does not affect the chromium percentage of steel. Single variable response analysis is performed to study the variation and interaction of all individual input parameters on output variables.

  2. Dimensionless numbers in additive manufacturing

    NASA Astrophysics Data System (ADS)

    Mukherjee, T.; Manvatkar, V.; De, A.; DebRoy, T.

    2017-02-01

    The effects of many process variables and alloy properties on the structure and properties of additively manufactured parts are examined using four dimensionless numbers. The structure and properties of components made from 316 Stainless steel, Ti-6Al-4V, and Inconel 718 powders for various dimensionless heat inputs, Peclet numbers, Marangoni numbers, and Fourier numbers are studied. Temperature fields, cooling rates, solidification parameters, lack of fusion defects, and thermal strains are examined using a well-tested three-dimensional transient heat transfer and fluid flow model. The results show that lack of fusion defects in the fabricated parts can be minimized by strengthening interlayer bonding using high values of dimensionless heat input. The formation of harmful intermetallics such as laves phases in Inconel 718 can be suppressed using low heat input that results in a small molten pool, a steep temperature gradient, and a fast cooling rate. Improved interlayer bonding can be achieved at high Marangoni numbers, which results in vigorous circulation of liquid metal, larger pool dimensions, and greater depth of penetration. A high Fourier number ensures rapid cooling, low thermal distortion, and a high ratio of temperature gradient to the solidification growth rate with a greater tendency of plane front solidification.

  3. The sensitivity of conduit flow models to basic input parameters: there is no need for magma trolls!

    NASA Astrophysics Data System (ADS)

    Thomas, M. E.; Neuberg, J. W.

    2012-04-01

    Many conduit flow models now exist and some of these models are becoming extremely complicated, conducted in three dimensions and incorporating the physics of compressible three phase fluids (magmas), intricate conduit geometries and fragmentation processes, to name but a few examples. These highly specialised models are being used to explain observations of the natural system, and there is a danger that possible explanations may be getting needlessly complex. It is coherent, for instance, to propose the involvement of sub-surface dwelling magma trolls as an explanation for the change in a volcanoes eruptive style, but assuming the simplest explanation would prevent such additions, unless they were absolutely necessary. While the understanding of individual, often small scale conduit processes is increasing rapidly, is this level of detail necessary? How sensitive are these models to small changes in the most basic of governing parameters? Can these changes be used to explain observed behaviour? Here we will examine the sensitivity of conduit flow models to changes in the melt viscosity, one of the fundamental inputs to any such model. However, even addressing this elementary issue is not straight forward. There are several viscosity models in existence, how do they differ? Can models that use different viscosity models be realistically compared? Each of these viscosity models is also heavily dependent on the magma composition and/or temperature, and how well are these variables constrained? Magma temperatures and water contents are often assumed as "ball-park" figures, and are very rarely exactly known for the periods of observation the models are attempting to explain, yet they exhibit a strong controlling factor on the melt viscosity. The role of both these variables will be discussed. For example, using one of the available viscosity models a 20 K decrease in temperature of the melt results in a greater than 100% increase in the melt viscosity. With changes of

  4. Dual-input two-compartment pharmacokinetic model of dynamic contrast-enhanced magnetic resonance imaging in hepatocellular carcinoma.

    PubMed

    Yang, Jian-Feng; Zhao, Zhen-Hua; Zhang, Yu; Zhao, Li; Yang, Li-Ming; Zhang, Min-Ming; Wang, Bo-Yin; Wang, Ting; Lu, Bao-Chun

    2016-04-07

    To investigate the feasibility of a dual-input two-compartment tracer kinetic model for evaluating tumorous microvascular properties in advanced hepatocellular carcinoma (HCC). From January 2014 to April 2015, we prospectively measured and analyzed pharmacokinetic parameters [transfer constant (Ktrans), plasma flow (Fp), permeability surface area product (PS), efflux rate constant (kep), extravascular extracellular space volume ratio (ve), blood plasma volume ratio (vp), and hepatic perfusion index (HPI)] using dual-input two-compartment tracer kinetic models [a dual-input extended Tofts model and a dual-input 2-compartment exchange model (2CXM)] in 28 consecutive HCC patients. A well-known consensus that HCC is a hypervascular tumor supplied by the hepatic artery and the portal vein was used as a reference standard. A paired Student's t-test and a nonparametric paired Wilcoxon rank sum test were used to compare the equivalent pharmacokinetic parameters derived from the two models, and Pearson correlation analysis was also applied to observe the correlations among all equivalent parameters. The tumor size and pharmacokinetic parameters were tested by Pearson correlation analysis, while correlations among stage, tumor size and all pharmacokinetic parameters were assessed by Spearman correlation analysis. The Fp value was greater than the PS value (FP = 1.07 mL/mL per minute, PS = 0.19 mL/mL per minute) in the dual-input 2CXM; HPI was 0.66 and 0.63 in the dual-input extended Tofts model and the dual-input 2CXM, respectively. There were no significant differences in the kep, vp, or HPI between the dual-input extended Tofts model and the dual-input 2CXM (P = 0.524, 0.569, and 0.622, respectively). All equivalent pharmacokinetic parameters, except for ve, were correlated in the two dual-input two-compartment pharmacokinetic models; both Fp and PS in the dual-input 2CXM were correlated with Ktrans derived from the dual-input extended Tofts model (P = 0.002, r = 0.566; P

  5. Inferring Nonlinear Neuronal Computation Based on Physiologically Plausible Inputs

    PubMed Central

    McFarland, James M.; Cui, Yuwei; Butts, Daniel A.

    2013-01-01

    The computation represented by a sensory neuron's response to stimuli is constructed from an array of physiological processes both belonging to that neuron and inherited from its inputs. Although many of these physiological processes are known to be nonlinear, linear approximations are commonly used to describe the stimulus selectivity of sensory neurons (i.e., linear receptive fields). Here we present an approach for modeling sensory processing, termed the Nonlinear Input Model (NIM), which is based on the hypothesis that the dominant nonlinearities imposed by physiological mechanisms arise from rectification of a neuron's inputs. Incorporating such ‘upstream nonlinearities’ within the standard linear-nonlinear (LN) cascade modeling structure implicitly allows for the identification of multiple stimulus features driving a neuron's response, which become directly interpretable as either excitatory or inhibitory. Because its form is analogous to an integrate-and-fire neuron receiving excitatory and inhibitory inputs, model fitting can be guided by prior knowledge about the inputs to a given neuron, and elements of the resulting model can often result in specific physiological predictions. Furthermore, by providing an explicit probabilistic model with a relatively simple nonlinear structure, its parameters can be efficiently optimized and appropriately regularized. Parameter estimation is robust and efficient even with large numbers of model components and in the context of high-dimensional stimuli with complex statistical structure (e.g. natural stimuli). We describe detailed methods for estimating the model parameters, and illustrate the advantages of the NIM using a range of example sensory neurons in the visual and auditory systems. We thus present a modeling framework that can capture a broad range of nonlinear response functions while providing physiologically interpretable descriptions of neural computation. PMID:23874185

  6. Robust Blind Learning Algorithm for Nonlinear Equalization Using Input Decision Information.

    PubMed

    Xu, Lu; Huang, Defeng David; Guo, Yingjie Jay

    2015-12-01

    In this paper, we propose a new blind learning algorithm, namely, the Benveniste-Goursat input-output decision (BG-IOD), to enhance the convergence performance of neural network-based equalizers for nonlinear channel equalization. In contrast to conventional blind learning algorithms, where only the output of the equalizer is employed for updating system parameters, the BG-IOD exploits a new type of extra information, the input decision information obtained from the input of the equalizer, to mitigate the influence of the nonlinear equalizer structure on parameters learning, thereby leading to improved convergence performance. We prove that, with the input decision information, a desirable convergence capability that the output symbol error rate (SER) is always less than the input SER if the input SER is below a threshold, can be achieved. Then, the BG soft-switching technique is employed to combine the merits of both input and output decision information, where the former is used to guarantee SER convergence and the latter is to improve SER performance. Simulation results show that the proposed algorithm outperforms conventional blind learning algorithms, such as stochastic quadratic distance and dual mode constant modulus algorithm, in terms of both convergence performance and SER performance, for nonlinear equalization.

  7. Numerically accurate computational techniques for optimal estimator analyses of multi-parameter models

    NASA Astrophysics Data System (ADS)

    Berger, Lukas; Kleinheinz, Konstantin; Attili, Antonio; Bisetti, Fabrizio; Pitsch, Heinz; Mueller, Michael E.

    2018-05-01

    Modelling unclosed terms in partial differential equations typically involves two steps: First, a set of known quantities needs to be specified as input parameters for a model, and second, a specific functional form needs to be defined to model the unclosed terms by the input parameters. Both steps involve a certain modelling error, with the former known as the irreducible error and the latter referred to as the functional error. Typically, only the total modelling error, which is the sum of functional and irreducible error, is assessed, but the concept of the optimal estimator enables the separate analysis of the total and the irreducible errors, yielding a systematic modelling error decomposition. In this work, attention is paid to the techniques themselves required for the practical computation of irreducible errors. Typically, histograms are used for optimal estimator analyses, but this technique is found to add a non-negligible spurious contribution to the irreducible error if models with multiple input parameters are assessed. Thus, the error decomposition of an optimal estimator analysis becomes inaccurate, and misleading conclusions concerning modelling errors may be drawn. In this work, numerically accurate techniques for optimal estimator analyses are identified and a suitable evaluation of irreducible errors is presented. Four different computational techniques are considered: a histogram technique, artificial neural networks, multivariate adaptive regression splines, and an additive model based on a kernel method. For multiple input parameter models, only artificial neural networks and multivariate adaptive regression splines are found to yield satisfactorily accurate results. Beyond a certain number of input parameters, the assessment of models in an optimal estimator analysis even becomes practically infeasible if histograms are used. The optimal estimator analysis in this paper is applied to modelling the filtered soot intermittency in large eddy

  8. Research on hysteresis loop considering the prestress effect and electrical input dynamics for a giant magnetostrictive actuator

    NASA Astrophysics Data System (ADS)

    Zhu, Yuchuan; Yang, Xulei; Wereley, Norman M.

    2016-08-01

    In this paper, focusing on the application-oriented giant magnetostrictive material (GMM)-based electro-hydrostatic actuator, which features an applied magnetic field at high frequency and high amplitude, and concentrating on the static and dynamic characteristics of a giant magnetostrictive actuator (GMA) considering the prestress effect on the GMM rod and the electrical input dynamics involving the power amplifier and the inductive coil, a methodology for studying the static and dynamic characteristics of a GMA using the hysteresis loop as a tool is developed. A GMA that can display the preforce on the GMM rod in real-time is designed, and a magnetostrictive model dependent on the prestress on a GMM rod instead of the existing quadratic domain rotation model is proposed. Additionally, an electrical input dynamics model to excite GMA is developed according to the simplified circuit diagram, and the corresponding parameters are identified by the experimental data. A dynamic magnetization model with the eddy current effect is deduced according to the Jiles-Atherton model and the Maxwell equations. Next, all of the parameters, including the electrical input characteristics, the dynamic magnetization and the mechanical structure of GMA, are identified by the experimental data from the current response, magnetization response and displacement response, respectively. Finally, a comprehensive comparison between the model results and experimental data is performed, and the results show that the test data agree well with the presented model results. An analysis on the relation between the GMA displacement response and the parameters from the electrical input dynamics, magnetization dynamics and mechanical structural dynamics is performed.

  9. Effect of Energy Input on the Characteristic of AISI H13 and D2 Tool Steels Deposited by a Directed Energy Deposition Process

    NASA Astrophysics Data System (ADS)

    Park, Jun Seok; Park, Joo Hyun; Lee, Min-Gyu; Sung, Ji Hyun; Cha, Kyoung Je; Kim, Da Hye

    2016-05-01

    Among the many additive manufacturing technologies, the directed energy deposition (DED) process has attracted significant attention because of the application of metal products. Metal deposited by the DED process has different properties than wrought metal because of the rapid solidification rate, the high thermal gradient between the deposited metal and substrate, etc. Additionally, many operating parameters, such as laser power, beam diameter, traverse speed, and powder mass flow rate, must be considered since the characteristics of the deposited metal are affected by the operating parameters. In the present study, the effect of energy input on the characteristics of H13 and D2 steels deposited by a direct metal tooling process based on the DED process was investigated. In particular, we report that the hardness of the deposited H13 and D2 steels decreased with increasing energy input, which we discuss by considering microstructural observations and thermodynamics.

  10. Input filter compensation for switching regulators

    NASA Technical Reports Server (NTRS)

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

    1983-01-01

    A novel input filter compensation scheme for a buck regulator that eliminates the interaction between the input filter output impedance and the regulator control loop is presented. The scheme is implemented using a feedforward loop that senses the input filter state variables and uses this information to modulate the duty cycle signal. The feedforward design process presented is seen to be straightforward and the feedforward easy to implement. Extensive experimental data supported by analytical results show that significant performance improvement is achieved with the use of feedforward in the following performance categories: loop stability, audiosusceptibility, output impedance and transient response. The use of feedforward results in isolating the switching regulator from its power source thus eliminating all interaction between the regulator and equipment upstream. In addition the use of feedforward removes some of the input filter design constraints and makes the input filter design process simpler thus making it possible to optimize the input filter. The concept of feedforward compensation can also be extended to other types of switching regulators.

  11. Sampling of Stochastic Input Parameters for Rockfall Calculations and for Structural Response Calculations Under Vibratory Ground Motion

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

    M. Gross

    2004-09-01

    The purpose of this scientific analysis is to define the sampled values of stochastic (random) input parameters for (1) rockfall calculations in the lithophysal and nonlithophysal zones under vibratory ground motions, and (2) structural response calculations for the drip shield and waste package under vibratory ground motions. This analysis supplies: (1) Sampled values of ground motion time history and synthetic fracture pattern for analysis of rockfall in emplacement drifts in nonlithophysal rock (Section 6.3 of ''Drift Degradation Analysis'', BSC 2004 [DIRS 166107]); (2) Sampled values of ground motion time history and rock mechanical properties category for analysis of rockfall inmore » emplacement drifts in lithophysal rock (Section 6.4 of ''Drift Degradation Analysis'', BSC 2004 [DIRS 166107]); (3) Sampled values of ground motion time history and metal to metal and metal to rock friction coefficient for analysis of waste package and drip shield damage to vibratory motion in ''Structural Calculations of Waste Package Exposed to Vibratory Ground Motion'' (BSC 2004 [DIRS 167083]) and in ''Structural Calculations of Drip Shield Exposed to Vibratory Ground Motion'' (BSC 2003 [DIRS 163425]). The sampled values are indices representing the number of ground motion time histories, number of fracture patterns and rock mass properties categories. These indices are translated into actual values within the respective analysis and model reports or calculations. This report identifies the uncertain parameters and documents the sampled values for these parameters. The sampled values are determined by GoldSim V6.04.007 [DIRS 151202] calculations using appropriate distribution types and parameter ranges. No software development or model development was required for these calculations. The calculation of the sampled values allows parameter uncertainty to be incorporated into the rockfall and structural response calculations that support development of the seismic scenario for

  12. Semi-globally input-to-state stable controller design for flexible spacecraft attitude stabilization under bounded disturbances

    NASA Astrophysics Data System (ADS)

    Hu, Qinglei

    2010-02-01

    Semi-globally input-to-state stable (ISS) control law is derived for flexible spacecraft attitude maneuvers in the presence of parameter uncertainties and external disturbances. The modified rodrigues parameters (MRP) are used as the kinematic variables since they are nonsingular for all possible rotations. This novel simple control is a proportional-plus-derivative (PD) type controller plus a sign function through a special Lyapunov function construction involving the sum of quadratic terms in the angular velocities, kinematic parameters, modal variables and the cross state weighting. A sufficient condition under which this nonlinear PD-type control law can render the system semi-globally input-to-state stable is provided such that the closed-loop system is robust with respect to any disturbance within a quantifiable restriction on the amplitude, as well as the set of initial conditions, if the control gains are designed appropriately. In addition to detailed derivations of the new controllers design and a rigorous sketch of all the associated stability and attitude convergence proofs, extensive simulation studies have been conducted to validate the design and the results are presented to highlight the ensuring closed-loop performance benefits when compared with the conventional control schemes.

  13. Parameter and input data uncertainty estimation for the assessment of water resources in two sub-basins of the Limpopo River Basin

    NASA Astrophysics Data System (ADS)

    Oosthuizen, Nadia; Hughes, Denis A.; Kapangaziwiri, Evison; Mwenge Kahinda, Jean-Marc; Mvandaba, Vuyelwa

    2018-05-01

    The demand for water resources is rapidly growing, placing more strain on access to water and its management. In order to appropriately manage water resources, there is a need to accurately quantify available water resources. Unfortunately, the data required for such assessment are frequently far from sufficient in terms of availability and quality, especially in southern Africa. In this study, the uncertainty related to the estimation of water resources of two sub-basins of the Limpopo River Basin - the Mogalakwena in South Africa and the Shashe shared between Botswana and Zimbabwe - is assessed. Input data (and model parameters) are significant sources of uncertainty that should be quantified. In southern Africa water use data are among the most unreliable sources of model input data because available databases generally consist of only licensed information and actual use is generally unknown. The study assesses how these uncertainties impact the estimation of surface water resources of the sub-basins. Data on farm reservoirs and irrigated areas from various sources were collected and used to run the model. Many farm dams and large irrigation areas are located in the upper parts of the Mogalakwena sub-basin. Results indicate that water use uncertainty is small. Nevertheless, the medium to low flows are clearly impacted. The simulated mean monthly flows at the outlet of the Mogalakwena sub-basin were between 22.62 and 24.68 Mm3 per month when incorporating only the uncertainty related to the main physical runoff generating parameters. The range of total predictive uncertainty of the model increased to between 22.15 and 24.99 Mm3 when water use data such as small farm and large reservoirs and irrigation were included. For the Shashe sub-basin incorporating only uncertainty related to the main runoff parameters resulted in mean monthly flows between 11.66 and 14.54 Mm3. The range of predictive uncertainty changed to between 11.66 and 17.72 Mm3 after the uncertainty

  14. How Sensitive Are Transdermal Transport Predictions by Microscopic Stratum Corneum Models to Geometric and Transport Parameter Input?

    PubMed

    Wen, Jessica; Koo, Soh Myoung; Lape, Nancy

    2018-02-01

    While predictive models of transdermal transport have the potential to reduce human and animal testing, microscopic stratum corneum (SC) model output is highly dependent on idealized SC geometry, transport pathway (transcellular vs. intercellular), and penetrant transport parameters (e.g., compound diffusivity in lipids). Most microscopic models are limited to a simple rectangular brick-and-mortar SC geometry and do not account for variability across delivery sites, hydration levels, and populations. In addition, these models rely on transport parameters obtained from pure theory, parameter fitting to match in vivo experiments, and time-intensive diffusion experiments for each compound. In this work, we develop a microscopic finite element model that allows us to probe model sensitivity to variations in geometry, transport pathway, and hydration level. Given the dearth of experimentally-validated transport data and the wide range in theoretically-predicted transport parameters, we examine the model's response to a variety of transport parameters reported in the literature. Results show that model predictions are strongly dependent on all aforementioned variations, resulting in order-of-magnitude differences in lag times and permeabilities for distinct structure, hydration, and parameter combinations. This work demonstrates that universally predictive models cannot fully succeed without employing experimentally verified transport parameters and individualized SC structures. Copyright © 2018 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

  15. Bayesian nonlinear structural FE model and seismic input identification for damage assessment of civil structures

    NASA Astrophysics Data System (ADS)

    Astroza, Rodrigo; Ebrahimian, Hamed; Li, Yong; Conte, Joel P.

    2017-09-01

    A methodology is proposed to update mechanics-based nonlinear finite element (FE) models of civil structures subjected to unknown input excitation. The approach allows to jointly estimate unknown time-invariant model parameters of a nonlinear FE model of the structure and the unknown time histories of input excitations using spatially-sparse output response measurements recorded during an earthquake event. The unscented Kalman filter, which circumvents the computation of FE response sensitivities with respect to the unknown model parameters and unknown input excitations by using a deterministic sampling approach, is employed as the estimation tool. The use of measurement data obtained from arrays of heterogeneous sensors, including accelerometers, displacement sensors, and strain gauges is investigated. Based on the estimated FE model parameters and input excitations, the updated nonlinear FE model can be interrogated to detect, localize, classify, and assess damage in the structure. Numerically simulated response data of a three-dimensional 4-story 2-by-1 bay steel frame structure with six unknown model parameters subjected to unknown bi-directional horizontal seismic excitation, and a three-dimensional 5-story 2-by-1 bay reinforced concrete frame structure with nine unknown model parameters subjected to unknown bi-directional horizontal seismic excitation are used to illustrate and validate the proposed methodology. The results of the validation studies show the excellent performance and robustness of the proposed algorithm to jointly estimate unknown FE model parameters and unknown input excitations.

  16. An efficient approach to ARMA modeling of biological systems with multiple inputs and delays

    NASA Technical Reports Server (NTRS)

    Perrott, M. H.; Cohen, R. J.

    1996-01-01

    This paper presents a new approach to AutoRegressive Moving Average (ARMA or ARX) modeling which automatically seeks the best model order to represent investigated linear, time invariant systems using their input/output data. The algorithm seeks the ARMA parameterization which accounts for variability in the output of the system due to input activity and contains the fewest number of parameters required to do so. The unique characteristics of the proposed system identification algorithm are its simplicity and efficiency in handling systems with delays and multiple inputs. We present results of applying the algorithm to simulated data and experimental biological data In addition, a technique for assessing the error associated with the impulse responses calculated from estimated ARMA parameterizations is presented. The mapping from ARMA coefficients to impulse response estimates is nonlinear, which complicates any effort to construct confidence bounds for the obtained impulse responses. Here a method for obtaining a linearization of this mapping is derived, which leads to a simple procedure to approximate the confidence bounds.

  17. Feed and manure use in low-N-input and high-N-input dairy cattle production systems

    NASA Astrophysics Data System (ADS)

    Powell, J. Mark

    2014-11-01

    In most parts of Sub-Saharan Africa fertilizers and feeds are costly, not readily available and used sparingly in agricultural production. In many parts of Western Europe, North America, and Oceania fertilizers and feeds are relatively inexpensive, readily available and used abundantly to maximize profitable agricultural production. A case study, dairy systems approach was used to illustrate how differences in feed and manure management in a low-N-input dairy cattle system (Niger, West Africa) and a high-N-input dairy production system (Wisconsin, USA) impact agricultural production and environmental N loss. In Niger, an additional daily feed N intake of 114 g per dairy animal unit (AU, 1000 kg live weight) could increase annual milk production from 560 to 1320 kg AU-1, and the additional manure N could greatly increase millet production. In Wisconsin, reductions in daily feed N intake of 100 g AU-1 would not greatly impact milk production but decrease urinary N excretion by 25% and ammonia and nitrous oxide emissions from manure by 18% to 30%. In Niger, compared to the practice of housing livestock and applying dung only onto fields, corralling cattle or sheep on cropland (to capture urinary N) increased millet yields by 25% to 95%. The additional millet grain due to dung applications or corralling would satisfy the annual food grain requirements of 2-5 persons; the additional forage would provide 120-300 more days of feed for a typical head of cattle; and 850 to 1600 kg ha-1 more biomass would be available for soil conservation. In Wisconsin, compared to application of barn manure only, corralling heifers in fields increased forage production by only 8% to 11%. The application of barn manure or corralling increased forage production by 20% to 70%. This additional forage would provide 350-580 more days of feed for a typical dairy heifer. Study results demonstrate how different approaches to feed and manure management in low-N-input and high-N-input dairy cattle

  18. Application of lab derived kinetic biodegradation parameters at the field scale

    NASA Astrophysics Data System (ADS)

    Schirmer, M.; Barker, J. F.; Butler, B. J.; Frind, E. O.

    2003-04-01

    Estimating the intrinsic remediation potential of an aquifer typically requires the accurate assessment of the biodegradation kinetics, the level of available electron acceptors and the flow field. Zero- and first-order degradation rates derived at the laboratory scale generally overpredict the rate of biodegradation when applied to the field scale, because limited electron acceptor availability and microbial growth are typically not considered. On the other hand, field estimated zero- and first-order rates are often not suitable to forecast plume development because they may be an oversimplification of the processes at the field scale and ignore several key processes, phenomena and characteristics of the aquifer. This study uses the numerical model BIO3D to link the laboratory and field scale by applying laboratory derived Monod kinetic degradation parameters to simulate a dissolved gasoline field experiment at Canadian Forces Base (CFB) Borden. All additional input parameters were derived from laboratory and field measurements or taken from the literature. The simulated results match the experimental results reasonably well without having to calibrate the model. An extensive sensitivity analysis was performed to estimate the influence of the most uncertain input parameters and to define the key controlling factors at the field scale. It is shown that the most uncertain input parameters have only a minor influence on the simulation results. Furthermore it is shown that the flow field, the amount of electron acceptor (oxygen) available and the Monod kinetic parameters have a significant influence on the simulated results. Under the field conditions modelled and the assumptions made for the simulations, it can be concluded that laboratory derived Monod kinetic parameters can adequately describe field scale degradation processes, if all controlling factors are incorporated in the field scale modelling that are not necessarily observed at the lab scale. In this way

  19. Graphene-assisted multiple-input high-base optical computing

    PubMed Central

    Hu, Xiao; Wang, Andong; Zeng, Mengqi; Long, Yun; Zhu, Long; Fu, Lei; Wang, Jian

    2016-01-01

    We propose graphene-assisted multiple-input high-base optical computing. We fabricate a nonlinear optical device based on a fiber pigtail cross-section coated with a single-layer graphene grown by chemical vapor deposition (CVD) method. An approach to implementing modulo 4 operations of three-input hybrid addition and subtraction of quaternary base numbers in the optical domain using multiple non-degenerate four-wave mixing (FWM) processes in graphene coated optical fiber device and (differential) quadrature phase-shift keying ((D)QPSK) signals is presented. We demonstrate 10-Gbaud modulo 4 operations of three-input quaternary hybrid addition and subtraction (A + B − C, A + C − B, B + C − A) in the experiment. The measured optical signal-to-noise ratio (OSNR) penalties for modulo 4 operations of three-input quaternary hybrid addition and subtraction (A + B − C, A + C − B, B + C − A) are measured to be less than 7 dB at a bit-error rate (BER) of 2 × 10−3. The BER performance as a function of the relative time offset between three signals (signal offset) is also evaluated showing favorable performance. PMID:27604866

  20. Input Shaping to Reduce Solar Array Structural Vibrations

    NASA Technical Reports Server (NTRS)

    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.

  1. Simulation Evaluation of Pilot Inputs for Real Time Modeling During Commercial Flight Operations

    NASA Technical Reports Server (NTRS)

    Martos, Borja; Ranaudo, Richard; Oltman, Ryan; Myhre, Nick

    2017-01-01

    Aircraft dynamics characteristics can only be identified from flight data when the aircraft dynamics are excited sufficiently. A preliminary study was conducted into what types and levels of manual piloted control excitation would be required for accurate Real-Time Parameter IDentification (RTPID) results by commercial airline pilots. This includes assessing the practicality for the pilot to provide this excitation when cued, and to further understand if pilot inputs during various phases of flight provide sufficient excitation naturally. An operationally representative task was evaluated by 5 commercial airline pilots using the NASA Ice Contamination Effects Flight Training Device (ICEFTD). Results showed that it is practical to use manual pilot inputs only as a means of achieving good RTPID in all phases of flight and in flight turbulence conditions. All pilots were effective in satisfying excitation requirements when cued. Much of the time, cueing was not even necessary, as just performing the required task provided enough excitation for accurate RTPID estimation. Pilot opinion surveys reported that the additional control inputs required when prompted by the excitation cueing were easy to make, quickly mastered, and required minimal training.

  2. Effect of Energy Input on Microstructure and Mechanical Properties of Titanium Aluminide Alloy Fabricated by the Additive Manufacturing Process of Electron Beam Melting

    PubMed Central

    Mohammad, Ashfaq; Alahmari, Abdulrahman M.; Mohammed, Muneer Khan; Renganayagalu, Ravi Kottan; Moiduddin, Khaja

    2017-01-01

    Titanium aluminides qualify adequately for advanced aero-engine applications in place of conventional nickel based superalloys. The combination of high temperature properties and lower density gives an edge to the titanium aluminide alloys. Nevertheless, challenges remain on how to process these essentially intermetallic alloys in to an actual product. Electron Beam Melting (EBM), an Additive Manufacturing Method, can build complex shaped solid parts from a given feedstock powder, thus overcoming the shortcomings of the conventional processing techniques such as machining and forging. The amount of energy supplied by the electron beam has considerable influence on the final build quality in the EBM process. Energy input is decided by the beam voltage, beam scan speed, beam current, and track offset distance. In the current work, beam current and track offset were varied to reflect three levels of energy input. Microstructural and mechanical properties were evaluated for these samples. The microstructure gradually coarsened from top to bottom along the build direction. Whereas higher energy favored lath microstructure, lower energy tended toward equiaxed grains. Computed tomography analysis revealed a greater amount of porosity in low energy samples. In addition, the lack of bonding defects led to premature failure in the tension test of low energy samples. Increase in energy to a medium level largely cancelled out the porosity, thereby increasing the strength. However, this trend did not continue with the high energy samples. Electron microscopy and X-ray diffraction investigations were carried out to understand this non-linear behavior of the strength in the three samples. Overall, the results of this work suggest that the input energy should be considered primarily whenever any new alloy system has to be processed through the EBM route. PMID:28772572

  3. Effect of Energy Input on Microstructure and Mechanical Properties of Titanium Aluminide Alloy Fabricated by the Additive Manufacturing Process of Electron Beam Melting.

    PubMed

    Mohammad, Ashfaq; Alahmari, Abdulrahman M; Mohammed, Muneer Khan; Renganayagalu, Ravi Kottan; Moiduddin, Khaja

    2017-02-21

    Titanium aluminides qualify adequately for advanced aero-engine applications in place of conventional nickel based superalloys. The combination of high temperature properties and lower density gives an edge to the titanium aluminide alloys. Nevertheless, challenges remain on how to process these essentially intermetallic alloys in to an actual product. Electron Beam Melting (EBM), an Additive Manufacturing Method, can build complex shaped solid parts from a given feedstock powder, thus overcoming the shortcomings of the conventional processing techniques such as machining and forging. The amount of energy supplied by the electron beam has considerable influence on the final build quality in the EBM process. Energy input is decided by the beam voltage, beam scan speed, beam current, and track offset distance. In the current work, beam current and track offset were varied to reflect three levels of energy input. Microstructural and mechanical properties were evaluated for these samples. The microstructure gradually coarsened from top to bottom along the build direction. Whereas higher energy favored lath microstructure, lower energy tended toward equiaxed grains. Computed tomography analysis revealed a greater amount of porosity in low energy samples. In addition, the lack of bonding defects led to premature failure in the tension test of low energy samples. Increase in energy to a medium level largely cancelled out the porosity, thereby increasing the strength. However, this trend did not continue with the high energy samples. Electron microscopy and X-ray diffraction investigations were carried out to understand this non-linear behavior of the strength in the three samples. Overall, the results of this work suggest that the input energy should be considered primarily whenever any new alloy system has to be processed through the EBM route.

  4. Guidance for Selecting Input Parameters in Modeling the Environmental Fate and Transport of Pesticides

    EPA Pesticide Factsheets

    Guidance to select and prepare input values for OPP's aquatic exposure models. Intended to improve the consistency in modeling the fate of pesticides in the environment and quality of OPP's aquatic risk assessments.

  5. Modeling clear-sky solar radiation across a range of elevations in Hawai‘i: Comparing the use of input parameters at different temporal resolutions

    NASA Astrophysics Data System (ADS)

    Longman, Ryan J.; Giambelluca, Thomas W.; Frazier, Abby G.

    2012-01-01

    Estimates of clear sky global solar irradiance using the parametric model SPCTRAL2 were tested against clear sky radiation observations at four sites in Hawai`i using daily, mean monthly, and 1 year mean model parameter settings. Atmospheric parameters in SPCTRAL2 and similar models are usually set at site-specific values and are not varied to represent the effects of fluctuating humidity, aerosol amount and type, or ozone concentration, because time-dependent atmospheric parameter estimates are not available at most sites of interest. In this study, we sought to determine the added value of using time dependent as opposed to fixed model input parameter settings. At the AERONET site, Mauna Loa Observatory (MLO) on the island of Hawai`i, where daily measurements of atmospheric optical properties and hourly solar radiation observations are available, use of daily rather than 1 year mean aerosol parameter values reduced mean bias error (MBE) from 18 to 10 W m-2 and root mean square error from 25 to 17 W m-2. At three stations in the HaleNet climate network, located at elevations of 960, 1640, and 2590 m on the island of Maui, where aerosol-related parameter settings were interpolated from observed values for AERONET sites at MLO (3397 m) and Lāna`i (20 m), and precipitable water was estimated using radiosonde-derived humidity profiles from nearby Hilo, the model performed best when using constant 1 year mean parameter values. At HaleNet Station 152, for example, MBE was 18, 10, and 8 W m-2 for daily, monthly, and 1 year mean parameters, respectively.

  6. Analysis of first and second order binary quantized digital phase-locked loops for ideal and white Gaussian noise inputs

    NASA Technical Reports Server (NTRS)

    Blasche, P. R.

    1980-01-01

    Specific configurations of first and second order all digital phase locked loops are analyzed for both ideal and additive white gaussian noise inputs. In addition, a design for a hardware digital phase locked loop capable of either first or second order operation is presented along with appropriate experimental data obtained from testing of the hardware loop. All parameters chosen for the analysis and the design of the digital phase locked loop are consistent with an application to an Omega navigation receiver although neither the analysis nor the design are limited to this application.

  7. Case study: Optimizing fault model input parameters using bio-inspired algorithms

    NASA Astrophysics Data System (ADS)

    Plucar, Jan; Grunt, Onřej; Zelinka, Ivan

    2017-07-01

    We present a case study that demonstrates a bio-inspired approach in the process of finding optimal parameters for GSM fault model. This model is constructed using Petri Nets approach it represents dynamic model of GSM network environment in the suburban areas of Ostrava city (Czech Republic). We have been faced with a task of finding optimal parameters for an application that requires high amount of data transfers between the application itself and secure servers located in datacenter. In order to find the optimal set of parameters we employ bio-inspired algorithms such as Differential Evolution (DE) or Self Organizing Migrating Algorithm (SOMA). In this paper we present use of these algorithms, compare results and judge their performance in fault probability mitigation.

  8. Modal Parameter Identification of a Flexible Arm System

    NASA Technical Reports Server (NTRS)

    Barrington, Jason; Lew, Jiann-Shiun; Korbieh, Edward; Wade, Montanez; Tantaris, Richard

    1998-01-01

    In this paper an experiment is designed for the modal parameter identification of a flexible arm system. This experiment uses a function generator to provide input signal and an oscilloscope to save input and output response data. For each vibrational mode, many sets of sine-wave inputs with frequencies close to the natural frequency of the arm system are used to excite the vibration of this mode. Then a least-squares technique is used to analyze the experimental input/output data to obtain the identified parameters for this mode. The identified results are compared with the analytical model obtained by applying finite element analysis.

  9. Extension of the PC version of VEPFIT with input and output routines running under Windows

    NASA Astrophysics Data System (ADS)

    Schut, H.; van Veen, A.

    1995-01-01

    The fitting program VEPFIT has been extended with applications running under the Microsoft-Windows environment facilitating the input and output of the VEPFIT fitting module. We have exploited the Microsoft-Windows graphical users interface by making use of dialog windows, scrollbars, command buttons, etc. The user communicates with the program simply by clicking and dragging with the mouse pointing device. Keyboard actions are limited to a minimum. Upon changing one or more input parameters the results of the modeling of the S-parameter and Ps fractions versus positron implantation energy are updated and displayed. This action can be considered as the first step in the fitting procedure upon which the user can decide to further adapt the input parameters or to forward these parameters as initial values to the fitting routine. The modeling step has proven to be helpful for designing positron beam experiments.

  10. Application of regional physically-based landslide early warning model: tuning of the input parameters and validation of the results

    NASA Astrophysics Data System (ADS)

    D'Ambrosio, Michele; Tofani, Veronica; Rossi, Guglielmo; Salvatici, Teresa; Tacconi Stefanelli, Carlo; Rosi, Ascanio; Benedetta Masi, Elena; Pazzi, Veronica; Vannocci, Pietro; Catani, Filippo; Casagli, Nicola

    2017-04-01

    The Aosta Valley region is located in North-West Alpine mountain chain. The geomorphology of the region is characterized by steep slopes, high climatic and altitude (ranging from 400 m a.s.l of Dora Baltea's river floodplain to 4810 m a.s.l. of Mont Blanc) variability. In the study area (zone B), located in Eastern part of Aosta Valley, heavy rainfall of about 800-900 mm per year is the main landslides trigger. These features lead to a high hydrogeological risk in all territory, as mass movements interest the 70% of the municipality areas (mainly shallow rapid landslides and rock falls). An in-depth study of the geotechnical and hydrological properties of hillslopes controlling shallow landslides formation was conducted, with the aim to improve the reliability of deterministic model, named HIRESS (HIgh REsolution Stability Simulator). In particular, two campaigns of on site measurements and laboratory experiments were performed. The data obtained have been studied in order to assess the relationships existing among the different parameters and the bedrock lithology. The analyzed soils in 12 survey points are mainly composed of sand and gravel, with highly variable contents of silt. The range of effective internal friction angle (from 25.6° to 34.3°) and effective cohesion (from 0 kPa to 9.3 kPa) measured and the median ks (10E-6 m/s) value are consistent with the average grain sizes (gravelly sand). The data collected contributes to generate input map of parameters for HIRESS (static data). More static data are: volume weight, residual water content, porosity and grain size index. In order to improve the original formulation of the model, the contribution of the root cohesion has been also taken into account based on the vegetation map and literature values. HIRESS is a physically based distributed slope stability simulator for analyzing shallow landslide triggering conditions in real time and in large areas using parallel computational techniques. The software

  11. Evaluation of Advanced Stirling Convertor Net Heat Input Correlation Methods Using a Thermal Standard

    NASA Technical Reports Server (NTRS)

    Briggs, Maxwell; Schifer, Nicholas

    2011-01-01

    Test hardware used to validate net heat prediction models. Problem: Net Heat Input cannot be measured directly during operation. Net heat input is a key parameter needed in prediction of efficiency for convertor performance. Efficiency = Electrical Power Output (Measured) divided by Net Heat Input (Calculated). Efficiency is used to compare convertor designs and trade technology advantages for mission planning.

  12. The Efficacy of Galaxy Shape Parameters in Photometric Redshift Estimation: A Neural Network Approach

    NASA Astrophysics Data System (ADS)

    Singal, J.; Shmakova, M.; Gerke, B.; Griffith, R. L.; Lotz, J.

    2011-05-01

    We present a determination of the effects of including galaxy morphological parameters in photometric redshift estimation with an artificial neural network method. Neural networks, which recognize patterns in the information content of data in an unbiased way, can be a useful estimator of the additional information contained in extra parameters, such as those describing morphology, if the input data are treated on an equal footing. We use imaging and five band photometric magnitudes from the All-wavelength Extended Groth Strip International Survey (AEGIS). It is shown that certain principal components of the morphology information are correlated with galaxy type. However, we find that for the data used the inclusion of morphological information does not have a statistically significant benefit for photometric redshift estimation with the techniques employed here. The inclusion of these parameters may result in a tradeoff between extra information and additional noise, with the additional noise becoming more dominant as more parameters are added.

  13. Effects of various experimental parameters on errors in triangulation solution of elongated object in space. [barium ion cloud

    NASA Technical Reports Server (NTRS)

    Long, S. A. T.

    1975-01-01

    The effects of various experimental parameters on the displacement errors in the triangulation solution of an elongated object in space due to pointing uncertainties in the lines of sight have been determined. These parameters were the number and location of observation stations, the object's location in latitude and longitude, and the spacing of the input data points on the azimuth-elevation image traces. The displacement errors due to uncertainties in the coordinates of a moving station have been determined as functions of the number and location of the stations. The effects of incorporating the input data from additional cameras at one of the stations were also investigated.

  14. Modeling and Analysis of CNC Milling Process Parameters on Al3030 based Composite

    NASA Astrophysics Data System (ADS)

    Gupta, Anand; Soni, P. K.; Krishna, C. M.

    2018-04-01

    The machining of Al3030 based composites on Computer Numerical Control (CNC) high speed milling machine have assumed importance because of their wide application in aerospace industries, marine industries and automotive industries etc. Industries mainly focus on surface irregularities; material removal rate (MRR) and tool wear rate (TWR) which usually depends on input process parameters namely cutting speed, feed in mm/min, depth of cut and step over ratio. Many researchers have carried out researches in this area but very few have taken step over ratio or radial depth of cut also as one of the input variables. In this research work, the study of characteristics of Al3030 is carried out at high speed CNC milling machine over the speed range of 3000 to 5000 r.p.m. Step over ratio, depth of cut and feed rate are other input variables taken into consideration in this research work. A total nine experiments are conducted according to Taguchi L9 orthogonal array. The machining is carried out on high speed CNC milling machine using flat end mill of diameter 10mm. Flatness, MRR and TWR are taken as output parameters. Flatness has been measured using portable Coordinate Measuring Machine (CMM). Linear regression models have been developed using Minitab 18 software and result are validated by conducting selected additional set of experiments. Selection of input process parameters in order to get best machining outputs is the key contributions of this research work.

  15. Modeling Input Errors to Improve Uncertainty Estimates for Sediment Transport Model Predictions

    NASA Astrophysics Data System (ADS)

    Jung, J. Y.; Niemann, J. D.; Greimann, B. P.

    2016-12-01

    Bayesian methods using Markov chain Monte Carlo algorithms have recently been applied to sediment transport models to assess the uncertainty in the model predictions due to the parameter values. Unfortunately, the existing approaches can only attribute overall uncertainty to the parameters. This limitation is critical because no model can produce accurate forecasts if forced with inaccurate input data, even if the model is well founded in physical theory. In this research, an existing Bayesian method is modified to consider the potential errors in input data during the uncertainty evaluation process. The input error is modeled using Gaussian distributions, and the means and standard deviations are treated as uncertain parameters. The proposed approach is tested by coupling it to the Sedimentation and River Hydraulics - One Dimension (SRH-1D) model and simulating a 23-km reach of the Tachia River in Taiwan. The Wu equation in SRH-1D is used for computing the transport capacity for a bed material load of non-cohesive material. Three types of input data are considered uncertain: (1) the input flowrate at the upstream boundary, (2) the water surface elevation at the downstream boundary, and (3) the water surface elevation at a hydraulic structure in the middle of the reach. The benefits of modeling the input errors in the uncertainty analysis are evaluated by comparing the accuracy of the most likely forecast and the coverage of the observed data by the credible intervals to those of the existing method. The results indicate that the internal boundary condition has the largest uncertainty among those considered. Overall, the uncertainty estimates from the new method are notably different from those of the existing method for both the calibration and forecast periods.

  16. Input Variability Facilitates Unguided Subcategory Learning in Adults

    PubMed Central

    Eidsvåg, Sunniva Sørhus; Austad, Margit; 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 of the participants were familiarized with 32 different root words in a high-variability condition. The other half were familiarized with 16 different root words, each repeated twice for a total of 32 presentations in a high-repetition condition. Participants were tested on untrained members of the category to assess generalization. Familiarization and testing was completed 2 additional times. Results Only participants in the high-variability group showed evidence of learning after an initial period of familiarization. Participants in the high-repetition group were able to learn after additional input. Both groups benefited when words included 2 cues to gender compared to a single cue. Conclusions The results demonstrate that the degree of input variability can influence learners' ability to generalize a grammatical subcategory (noun gender) from a natural language. In addition, the presence of multiple cues to linguistic subcategory facilitated learning independent of variability condition. PMID:25680081

  17. Input Variability Facilitates Unguided Subcategory Learning in Adults.

    PubMed

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

    2015-06-01

    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. Forty adults (20 men, 20 women) were familiarized with examples of masculine and feminine Russian words. Half of the participants were familiarized with 32 different root words in a high-variability condition. The other half were familiarized with 16 different root words, each repeated twice for a total of 32 presentations in a high-repetition condition. Participants were tested on untrained members of the category to assess generalization. Familiarization and testing was completed 2 additional times. Only participants in the high-variability group showed evidence of learning after an initial period of familiarization. Participants in the high-repetition group were able to learn after additional input. Both groups benefited when words included 2 cues to gender compared to a single cue. The results demonstrate that the degree of input variability can influence learners' ability to generalize a grammatical subcategory (noun gender) from a natural language. In addition, the presence of multiple cues to linguistic subcategory facilitated learning independent of variability condition.

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

    NASA Astrophysics Data System (ADS)

    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.

  19. Cryptographic Boolean Functions with Biased Inputs

    DTIC Science & Technology

    2015-07-31

    theory of random graphs developed by Erdős and Rényi [2]. The graph properties in a random graph expressed as such Boolean functions are used by...distributed Bernoulli variates with the parameter p. Since our scope is within the area of cryptography , we initiate an analysis of cryptographic...Boolean functions with biased inputs, which we refer to as µp-Boolean functions, is a common generalization of Boolean functions which stems from the

  20. Determination of Process Parameters for High-Density, Ti-6Al-4V Parts Using Additive Manufacturing

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

    Kamath, C.

    In our earlier work, we described an approach for determining the process parameters that re- sult in high-density parts manufactured using the additive-manufacturing process of selective laser melting (SLM). Our approach, which combines simple simulations and experiments, was demon- strated using 316L stainless steel. We have also used the approach successfully for several other materials. This short note summarizes the results of our work in determining process parameters for Ti-6Al-4V using a Concept Laser M2 system.

  1. Additive Manufacturing of Fuel Injectors

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

    Sadek Tadros, Dr. Alber Alphonse; Ritter, Dr. George W.; Drews, Charles Donald

    Additive manufacturing (AM), also known as 3D-printing, has been shifting from a novelty prototyping paradigm to a legitimate manufacturing tool capable of creating components for highly complex engineered products. An emerging AM technology for producing metal parts is the laser powder bed fusion (L-PBF) process; however, industry manufacturing specifications and component design practices for L-PBF have not yet been established. Solar Turbines Incorporated (Solar), an industrial gas turbine manufacturer, has been evaluating AM technology for development and production applications with the desire to enable accelerated product development cycle times, overall turbine efficiency improvements, and supply chain flexibility relative to conventionalmore » manufacturing processes (casting, brazing, welding). Accordingly, Solar teamed with EWI on a joint two-and-a-half-year project with the goal of developing a production L-PBF AM process capable of consistently producing high-nickel alloy material suitable for high temperature gas turbine engine fuel injector components. The project plan tasks were designed to understand the interaction of the process variables and their combined impact on the resultant AM material quality. The composition of the high-nickel alloy powders selected for this program met the conventional cast Hastelloy X compositional limits and were commercially available in different particle size distributions (PSD) from two suppliers. Solar produced all the test articles and both EWI and Solar shared responsibility for analyzing them. The effects of powder metal input stock, laser parameters, heat treatments, and post-finishing methods were evaluated. This process knowledge was then used to generate tensile, fatigue, and creep material properties data curves suitable for component design activities. The key process controls for ensuring consistent material properties were documented in AM powder and process specifications. The basic components of the

  2. Electron-impact excitation of He: Dependence of electron-photon coherence parameters on the principal quantum number

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

    Hammond, P.; Khakoo, M.A.; McConkey, J.W.

    1987-12-01

    Measurements are presented representing a complete set of electron-photon polarization correlation parameters for the excitation of n /sup 1/P states of He at an incident energy of 80 eV and an electron scattering angle of 20/sup 0/. The data support the predictions of a recent theoretical paper that these parameters should exhibit little variation with n. However, disagreement in absolute values between experiment and theory indicates the need for additional theoretical input into the problem.

  3. Smart mobility solution with multiple input Output interface.

    PubMed

    Sethi, Aartika; Deb, Sujay; Ranjan, Prabhat; Sardar, Arghya

    2017-07-01

    Smart wheelchairs are commonly used to provide solution for mobility impairment. However their usage is limited primarily due to high cost owing from sensors required for giving input, lack of adaptability for different categories of input and limited functionality. In this paper we propose a smart mobility solution using smartphone with inbuilt sensors (accelerometer, camera and speaker) as an input interface. An Emotiv EPOC+ is also used for motor imagery based input control synced with facial expressions in cases of extreme disability. Apart from traction, additional functions like home security and automation are provided using Internet of Things (IoT) and web interfaces. Although preliminary, our results suggest that this system can be used as an integrated and efficient solution for people suffering from mobility impairment. The results also indicate a decent accuracy is obtained for the overall system.

  4. The series product for gaussian quantum input processes

    NASA Astrophysics Data System (ADS)

    Gough, John E.; James, Matthew R.

    2017-02-01

    We present a theory for connecting quantum Markov components into a network with quantum input processes in a Gaussian state (including thermal and squeezed). One would expect on physical grounds that the connection rules should be independent of the state of the input to the network. To compute statistical properties, we use a version of Wicks' theorem involving fictitious vacuum fields (Fock space based representation of the fields) and while this aids computation, and gives a rigorous formulation, the various representations need not be unitarily equivalent. In particular, a naive application of the connection rules would lead to the wrong answer. We establish the correct interconnection rules, and show that while the quantum stochastic differential equations of motion display explicitly the covariances (thermal and squeezing parameters) of the Gaussian input fields we introduce the Wick-Stratonovich form which leads to a way of writing these equations that does not depend on these covariances and so corresponds to the universal equations written in terms of formal quantum input processes. We show that a wholly consistent theory of quantum open systems in series can be developed in this way, and as required physically, is universal and in particular representation-free.

  5. Can Simulation Credibility Be Improved Using Sensitivity Analysis to Understand Input Data Effects on Model Outcome?

    NASA Technical Reports Server (NTRS)

    Myers, Jerry G.; Young, M.; Goodenow, Debra A.; Keenan, A.; Walton, M.; Boley, L.

    2015-01-01

    Model and simulation (MS) credibility is defined as, the quality to elicit belief or trust in MS results. NASA-STD-7009 [1] delineates eight components (Verification, Validation, Input Pedigree, Results Uncertainty, Results Robustness, Use History, MS Management, People Qualifications) that address quantifying model credibility, and provides guidance to the model developers, analysts, and end users for assessing the MS credibility. Of the eight characteristics, input pedigree, or the quality of the data used to develop model input parameters, governing functions, or initial conditions, can vary significantly. These data quality differences have varying consequences across the range of MS application. NASA-STD-7009 requires that the lowest input data quality be used to represent the entire set of input data when scoring the input pedigree credibility of the model. This requirement provides a conservative assessment of model inputs, and maximizes the communication of the potential level of risk of using model outputs. Unfortunately, in practice, this may result in overly pessimistic communication of the MS output, undermining the credibility of simulation predictions to decision makers. This presentation proposes an alternative assessment mechanism, utilizing results parameter robustness, also known as model input sensitivity, to improve the credibility scoring process for specific simulations.

  6. Calculating the sensitivity of wind turbine loads to wind inputs using response surfaces

    NASA Astrophysics Data System (ADS)

    Rinker, Jennifer M.

    2016-09-01

    This paper presents a methodology to calculate wind turbine load sensitivities to turbulence parameters through the use of response surfaces. A response surface is a highdimensional polynomial surface that can be calibrated to any set of input/output data and then used to generate synthetic data at a low computational cost. Sobol sensitivity indices (SIs) can then be calculated with relative ease using the calibrated response surface. The proposed methodology is demonstrated by calculating the total sensitivity of the maximum blade root bending moment of the WindPACT 5 MW reference model to four turbulence input parameters: a reference mean wind speed, a reference turbulence intensity, the Kaimal length scale, and a novel parameter reflecting the nonstationarity present in the inflow turbulence. The input/output data used to calibrate the response surface were generated for a previous project. The fit of the calibrated response surface is evaluated in terms of error between the model and the training data and in terms of the convergence. The Sobol SIs are calculated using the calibrated response surface, and the convergence is examined. The Sobol SIs reveal that, of the four turbulence parameters examined in this paper, the variance caused by the Kaimal length scale and nonstationarity parameter are negligible. Thus, the findings in this paper represent the first systematic evidence that stochastic wind turbine load response statistics can be modeled purely by mean wind wind speed and turbulence intensity.

  7. Improvement of Meteorological Inputs for TexAQS-II Air Quality Simulations

    NASA Astrophysics Data System (ADS)

    Ngan, F.; Byun, D.; Kim, H.; Cheng, F.; Kim, S.; Lee, D.

    2008-12-01

    An air quality forecasting system (UH-AQF) for Eastern Texas, which is in operation by the Institute for Multidimensional Air Quality Studies (IMAQS) at the University of Houston, uses the Fifth-Generation PSU/NCAR Mesoscale Model MM5 model as the meteorological driver for modeling air quality with the Community Multiscale Air Quality (CMAQ) model. While the forecasting system was successfully used for the planning and implementation of various measurement activities, evaluations of the forecasting results revealed a few systematic problems in the numerical simulations. From comparison with observations, we observe some times over-prediction of northerly winds caused by inaccurate synoptic inputs and other times too strong southerly winds caused by local sea breeze development. Discrepancies in maximum and minimum temperature are also seen for certain days. Precipitation events, as well as clouds, are simulated at the incorrect locations and times occasionally. Model simulatednrealistic thunderstorms are simulated, causing sometimes cause unrealistically strong outflows. To understand physical and chemical processes influencing air quality measures, a proper description of real world meteorological conditions is essential. The objective of this study is to generate better meteorological inputs than the AQF results to support the chemistry modeling. We utilized existing objective analysis and nudging tools in the MM5 system to develop the MUltiscale Nest-down Data Assimilation System (MUNDAS), which incorporates extensive meteorological observations available in the simulated domain for the retrospective simulation of the TexAQS-II period. With the re-simulated meteorological input, we are able to better predict ozone events during TexAQS-II period. In addition, base datasets in MM5 such as land use/land cover, vegetation fraction, soil type and sea surface temperature are updated by satellite data to represent the surface features more accurately. They are key

  8. Calibration of discrete element model parameters: soybeans

    NASA Astrophysics Data System (ADS)

    Ghodki, Bhupendra M.; Patel, Manish; Namdeo, Rohit; Carpenter, Gopal

    2018-05-01

    Discrete element method (DEM) simulations are broadly used to get an insight of flow characteristics of granular materials in complex particulate systems. DEM input parameters for a model are the critical prerequisite for an efficient simulation. Thus, the present investigation aims to determine DEM input parameters for Hertz-Mindlin model using soybeans as a granular material. To achieve this aim, widely acceptable calibration approach was used having standard box-type apparatus. Further, qualitative and quantitative findings such as particle profile, height of kernels retaining the acrylic wall, and angle of repose of experiments and numerical simulations were compared to get the parameters. The calibrated set of DEM input parameters includes the following (a) material properties: particle geometric mean diameter (6.24 mm); spherical shape; particle density (1220 kg m^{-3} ), and (b) interaction parameters such as particle-particle: coefficient of restitution (0.17); coefficient of static friction (0.26); coefficient of rolling friction (0.08), and particle-wall: coefficient of restitution (0.35); coefficient of static friction (0.30); coefficient of rolling friction (0.08). The results may adequately be used to simulate particle scale mechanics (grain commingling, flow/motion, forces, etc) of soybeans in post-harvest machinery and devices.

  9. Attaining insight into interactions between hydrologic model parameters and geophysical attributes for national-scale model parameter estimation

    NASA Astrophysics Data System (ADS)

    Mizukami, N.; Clark, M. P.; Newman, A. J.; Wood, A.; Gutmann, E. D.

    2017-12-01

    Estimating spatially distributed model parameters is a grand challenge for large domain hydrologic modeling, especially in the context of hydrologic model applications such as streamflow forecasting. Multi-scale Parameter Regionalization (MPR) is a promising technique that accounts for the effects of fine-scale geophysical attributes (e.g., soil texture, land cover, topography, climate) on model parameters and nonlinear scaling effects on model parameters. MPR computes model parameters with transfer functions (TFs) that relate geophysical attributes to model parameters at the native input data resolution and then scales them using scaling functions to the spatial resolution of the model implementation. One of the biggest challenges in the use of MPR is identification of TFs for each model parameter: both functional forms and geophysical predictors. TFs used to estimate the parameters of hydrologic models typically rely on previous studies or were derived in an ad-hoc, heuristic manner, potentially not utilizing maximum information content contained in the geophysical attributes for optimal parameter identification. Thus, it is necessary to first uncover relationships among geophysical attributes, model parameters, and hydrologic processes (i.e., hydrologic signatures) to obtain insight into which and to what extent geophysical attributes are related to model parameters. We perform multivariate statistical analysis on a large-sample catchment data set including various geophysical attributes as well as constrained VIC model parameters at 671 unimpaired basins over the CONUS. We first calibrate VIC model at each catchment to obtain constrained parameter sets. Additionally, parameter sets sampled during the calibration process are used for sensitivity analysis using various hydrologic signatures as objectives to understand the relationships among geophysical attributes, parameters, and hydrologic processes.

  10. Parameter extraction with neural networks

    NASA Astrophysics Data System (ADS)

    Cazzanti, Luca; Khan, Mumit; Cerrina, Franco

    1998-06-01

    In semiconductor processing, the modeling of the process is becoming more and more important. While the ultimate goal is that of developing a set of tools for designing a complete process (Technology CAD), it is also necessary to have modules to simulate the various technologies and, in particular, to optimize specific steps. This need is particularly acute in lithography, where the continuous decrease in CD forces the technologies to operate near their limits. In the development of a 'model' for a physical process, we face several levels of challenges. First, it is necessary to develop a 'physical model,' i.e. a rational description of the process itself on the basis of know physical laws. Second, we need an 'algorithmic model' to represent in a virtual environment the behavior of the 'physical model.' After a 'complete' model has been developed and verified, it becomes possible to do performance analysis. In many cases the input parameters are poorly known or not accessible directly to experiment. It would be extremely useful to obtain the values of these 'hidden' parameters from experimental results by comparing model to data. This is particularly severe, because the complexity and costs associated with semiconductor processing make a simple 'trial-and-error' approach infeasible and cost- inefficient. Even when computer models of the process already exists, obtaining data through simulations may be time consuming. Neural networks (NN) are powerful computational tools to predict the behavior of a system from an existing data set. They are able to adaptively 'learn' input/output mappings and to act as universal function approximators. In this paper we use artificial neural networks to build a mapping from the input parameters of the process to output parameters which are indicative of the performance of the process. Once the NN has been 'trained,' it is also possible to observe the process 'in reverse,' and to extract the values of the inputs which yield outputs

  11. The effects of the sequential addition of synthesis parameters on the performance of alkali activated fly ash mortar

    NASA Astrophysics Data System (ADS)

    Dassekpo, Jean-Baptiste Mawulé; Zha, Xiaoxiong; Zhan, Jiapeng; Ning, Jiaqian

    Geopolymer is an energy efficient and sustainable material that is currently used in construction industry as an alternative for Portland cement. As a new material, specific mix design method is essential and efforts have been made to develop a mix design procedure with the main focus on achieving better compressive strength and economy. In this paper, a sequential addition of synthesis parameters such as fly ash-sand, alkaline liquids, plasticizer and additional water at well-defined time intervals was investigated. A total of 4 mix procedures were used to study the compressive performance on fly ash-based geopolymer mortar and the results of each method were analyzed and discussed. Experimental results show that the sequential addition of sodium hydroxide (NaOH), sodium silicate (Na2SiO3), plasticizer (PL), followed by adding water (WA) increases considerably the compressive strengths of the geopolymer-based mortar. These results clearly demonstrate the high significant influence of sequential addition of synthesis parameters on geopolymer materials compressive properties, and also provide a new mixing method for the preparation of geopolymer paste, mortar and concrete.

  12. Application of Model Based Parameter Estimation for Fast Frequency Response Calculations of Input Characteristics of Cavity-Backed Aperture Antennas Using Hybrid FEM/MoM Technique

    NASA Technical Reports Server (NTRS)

    Reddy C. J.

    1998-01-01

    Model Based Parameter Estimation (MBPE) is presented in conjunction with the hybrid Finite Element Method (FEM)/Method of Moments (MoM) technique for fast computation of the input characteristics of cavity-backed aperture antennas over a frequency range. The hybrid FENI/MoM technique is used to form an integro-partial- differential equation to compute the electric field distribution of a cavity-backed aperture antenna. In MBPE, the electric field is expanded in a rational function of two polynomials. The coefficients of the rational function are obtained using the frequency derivatives of the integro-partial-differential equation formed by the hybrid FEM/ MoM technique. Using the rational function approximation, the electric field is obtained over a frequency range. Using the electric field at different frequencies, the input characteristics of the antenna are obtained over a wide frequency range. Numerical results for an open coaxial line, probe-fed coaxial cavity and cavity-backed microstrip patch antennas are presented. Good agreement between MBPE and the solutions over individual frequencies is observed.

  13. Preparation of the CARMENES Input Catalogue: Mining Public Archives for Stellar Parameters and Spectra of M Dwarfs with Master Thesis Students

    NASA Astrophysics Data System (ADS)

    Montes, D.; Caballero, J. A.; Alonso-Floriano, F. J.; Cortes Contreras, M.; Gonzalez-Alvarez, E.; Hidalgo, D.; Holgado, G.; Llamas, M.; Martinez-Rodriguez, H.; Sanz-Forcada, J.

    2015-01-01

    We help compiling the most comprehensive database of M dwarfs ever built, CARMENCITA, the CARMENES Cool dwarf Information and daTa Archive, which will be the CARMENES `input catalogue'. In addition to the science preparation with low- and high-resolution spectrographs and lucky imagers (see the other contributions in this volume), we compile a huge pile of public data on over 2100 M dwarfs, and analyze them, mostly using virtual-observatory tools. Here we describe four specific actions carried out by master and grade students. They mine public archives for additional high-resolution spectroscopy (UVES, FEROS and HARPS), multi-band photometry (FUV-NUV-u-B-g-V-r-R-i-J-H-Ks-W1-W2-W3-W4), X-ray data (ROSAT, XMM-Newton and Chandra), periods, rotational velocities and Hα pseudo-equivalent widths. As described, there are many interdependences between all these data.

  14. Double-input compartmental modeling and spectral analysis for the quantification of positron emission tomography data in oncology

    NASA Astrophysics Data System (ADS)

    Tomasi, G.; Kimberley, S.; Rosso, L.; Aboagye, E.; Turkheimer, F.

    2012-04-01

    In positron emission tomography (PET) studies involving organs different from the brain, ignoring the metabolite contribution to the tissue time-activity curves (TAC), as in the standard single-input (SI) models, may compromise the accuracy of the estimated parameters. We employed here double-input (DI) compartmental modeling (CM), previously used for [11C]thymidine, and a novel DI spectral analysis (SA) approach on the tracers 5-[18F]fluorouracil (5-[18F]FU) and [18F]fluorothymidine ([18F]FLT). CM and SA were performed initially with a SI approach using the parent plasma TAC as an input function. These methods were then employed using a DI approach with the metabolite plasma TAC as an additional input function. Regions of interest (ROIs) corresponding to healthy liver, kidneys and liver metastases for 5-[18F]FU and to tumor, vertebra and liver for [18F]FLT were analyzed. For 5-[18F]FU, the improvement of the fit quality with the DI approaches was remarkable; in CM, the Akaike information criterion (AIC) always selected the DI over the SI model. Volume of distribution estimates obtained with DI CM and DI SA were in excellent agreement, for both parent 5-[18F]FU (R2 = 0.91) and metabolite [18F]FBAL (R2 = 0.99). For [18F]FLT, the DI methods provided notable improvements but less substantial than for 5-[18F]FU due to the lower rate of metabolism of [18F]FLT. On the basis of the AIC values, agreement between [18F]FLT Ki estimated with the SI and DI models was good (R2 = 0.75) for the ROIs where the metabolite contribution was negligible, indicating that the additional input did not bias the parent tracer only-related estimates. When the AIC suggested a substantial contribution of the metabolite [18F]FLT-glucuronide, on the other hand, the change in the parent tracer only-related parameters was significant (R2 = 0.33 for Ki). Our results indicated that improvements of DI over SI approaches can range from moderate to substantial and are more significant for tracers with

  15. Double-input compartmental modeling and spectral analysis for the quantification of positron emission tomography data in oncology.

    PubMed

    Tomasi, G; Kimberley, S; Rosso, L; Aboagye, E; Turkheimer, F

    2012-04-07

    In positron emission tomography (PET) studies involving organs different from the brain, ignoring the metabolite contribution to the tissue time-activity curves (TAC), as in the standard single-input (SI) models, may compromise the accuracy of the estimated parameters. We employed here double-input (DI) compartmental modeling (CM), previously used for [¹¹C]thymidine, and a novel DI spectral analysis (SA) approach on the tracers 5-[¹⁸F]fluorouracil (5-[¹⁸F]FU) and [¹⁸F]fluorothymidine ([¹⁸F]FLT). CM and SA were performed initially with a SI approach using the parent plasma TAC as an input function. These methods were then employed using a DI approach with the metabolite plasma TAC as an additional input function. Regions of interest (ROIs) corresponding to healthy liver, kidneys and liver metastases for 5-[¹⁸F]FU and to tumor, vertebra and liver for [¹⁸F]FLT were analyzed. For 5-[¹⁸F]FU, the improvement of the fit quality with the DI approaches was remarkable; in CM, the Akaike information criterion (AIC) always selected the DI over the SI model. Volume of distribution estimates obtained with DI CM and DI SA were in excellent agreement, for both parent 5-[¹⁸F]FU (R(2) = 0.91) and metabolite [¹⁸F]FBAL (R(2) = 0.99). For [¹⁸F]FLT, the DI methods provided notable improvements but less substantial than for 5-[¹⁸F]FU due to the lower rate of metabolism of [¹⁸F]FLT. On the basis of the AIC values, agreement between [¹⁸F]FLT K(i) estimated with the SI and DI models was good (R² = 0.75) for the ROIs where the metabolite contribution was negligible, indicating that the additional input did not bias the parent tracer only-related estimates. When the AIC suggested a substantial contribution of the metabolite [¹⁸F]FLT-glucuronide, on the other hand, the change in the parent tracer only-related parameters was significant (R² = 0.33 for K(i)). Our results indicated that improvements of DI over SI approaches can range from moderate to

  16. An analysis of input errors in precipitation-runoff models using regression with errors in the independent variables

    USGS Publications Warehouse

    Troutman, Brent M.

    1982-01-01

    Errors in runoff prediction caused by input data errors are analyzed by treating precipitation-runoff models as regression (conditional expectation) models. Independent variables of the regression consist of precipitation and other input measurements; the dependent variable is runoff. In models using erroneous input data, prediction errors are inflated and estimates of expected storm runoff for given observed input variables are biased. This bias in expected runoff estimation results in biased parameter estimates if these parameter estimates are obtained by a least squares fit of predicted to observed runoff values. The problems of error inflation and bias are examined in detail for a simple linear regression of runoff on rainfall and for a nonlinear U.S. Geological Survey precipitation-runoff model. Some implications for flood frequency analysis are considered. A case study using a set of data from Turtle Creek near Dallas, Texas illustrates the problems of model input errors.

  17. Ensemble Kalman Filter for Dynamic State Estimation of Power Grids Stochastically Driven by Time-correlated Mechanical Input Power

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

    Rosenthal, William Steven; Tartakovsky, Alex; Huang, Zhenyu

    State and parameter estimation of power transmission networks is important for monitoring power grid operating conditions and analyzing transient stability. Wind power generation depends on fluctuating input power levels, which are correlated in time and contribute to uncertainty in turbine dynamical models. The ensemble Kalman filter (EnKF), a standard state estimation technique, uses a deterministic forecast and does not explicitly model time-correlated noise in parameters such as mechanical input power. However, this uncertainty affects the probability of fault-induced transient instability and increased prediction bias. Here a novel approach is to model input power noise with time-correlated stochastic fluctuations, and integratemore » them with the network dynamics during the forecast. While the EnKF has been used to calibrate constant parameters in turbine dynamical models, the calibration of a statistical model for a time-correlated parameter has not been investigated. In this study, twin experiments on a standard transmission network test case are used to validate our time-correlated noise model framework for state estimation of unsteady operating conditions and transient stability analysis, and a methodology is proposed for the inference of the mechanical input power time-correlation length parameter using time-series data from PMUs monitoring power dynamics at generator buses.« less

  18. Ensemble Kalman Filter for Dynamic State Estimation of Power Grids Stochastically Driven by Time-correlated Mechanical Input Power

    DOE PAGES

    Rosenthal, William Steven; Tartakovsky, Alex; Huang, Zhenyu

    2017-10-31

    State and parameter estimation of power transmission networks is important for monitoring power grid operating conditions and analyzing transient stability. Wind power generation depends on fluctuating input power levels, which are correlated in time and contribute to uncertainty in turbine dynamical models. The ensemble Kalman filter (EnKF), a standard state estimation technique, uses a deterministic forecast and does not explicitly model time-correlated noise in parameters such as mechanical input power. However, this uncertainty affects the probability of fault-induced transient instability and increased prediction bias. Here a novel approach is to model input power noise with time-correlated stochastic fluctuations, and integratemore » them with the network dynamics during the forecast. While the EnKF has been used to calibrate constant parameters in turbine dynamical models, the calibration of a statistical model for a time-correlated parameter has not been investigated. In this study, twin experiments on a standard transmission network test case are used to validate our time-correlated noise model framework for state estimation of unsteady operating conditions and transient stability analysis, and a methodology is proposed for the inference of the mechanical input power time-correlation length parameter using time-series data from PMUs monitoring power dynamics at generator buses.« less

  19. Local Sensitivity of Predicted CO 2 Injectivity and Plume Extent to Model Inputs for the FutureGen 2.0 site

    DOE PAGES

    Zhang, Z. Fred; White, Signe K.; Bonneville, Alain; ...

    2014-12-31

    Numerical simulations have been used for estimating CO2 injectivity, CO2 plume extent, pressure distribution, and Area of Review (AoR), and for the design of CO2 injection operations and monitoring network for the FutureGen project. The simulation results are affected by uncertainties associated with numerous input parameters, the conceptual model, initial and boundary conditions, and factors related to injection operations. Furthermore, the uncertainties in the simulation results also vary in space and time. The key need is to identify those uncertainties that critically impact the simulation results and quantify their impacts. We introduce an approach to determine the local sensitivity coefficientmore » (LSC), defined as the response of the output in percent, to rank the importance of model inputs on outputs. The uncertainty of an input with higher sensitivity has larger impacts on the output. The LSC is scalable by the error of an input parameter. The composite sensitivity of an output to a subset of inputs can be calculated by summing the individual LSC values. We propose a local sensitivity coefficient method and applied it to the FutureGen 2.0 Site in Morgan County, Illinois, USA, to investigate the sensitivity of input parameters and initial conditions. The conceptual model for the site consists of 31 layers, each of which has a unique set of input parameters. The sensitivity of 11 parameters for each layer and 7 inputs as initial conditions is then investigated. For CO2 injectivity and plume size, about half of the uncertainty is due to only 4 or 5 of the 348 inputs and 3/4 of the uncertainty is due to about 15 of the inputs. The initial conditions and the properties of the injection layer and its neighbour layers contribute to most of the sensitivity. Overall, the simulation outputs are very sensitive to only a small fraction of the inputs. However, the parameters that are important for controlling CO2 injectivity are not the same as those controlling

  20. An update of input instructions to TEMOD

    NASA Technical Reports Server (NTRS)

    1973-01-01

    The theory and operation of a FORTRAN 4 computer code, designated as TEMOD, used to calcuate tubular thermoelectric generator performance is described in WANL-TME-1906. The original version of TEMOD was developed in 1969. A description is given of additions to the mathematical model and an update of the input instructions to the code. Although the basic mathematical model described in WANL-TME-1906 has remained unchanged, a substantial number of input/output options were added to allow completion of module performance parametrics as required in support of the compact thermoelectric converter system technology program.

  1. NetMOD Version 2.0 Parameters

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

    Merchant, Bion J.

    2015-08-01

    NetMOD ( Net work M onitoring for O ptimal D etection) is a Java-based software package for conducting simulation of seismic, hydroacoustic and infrasonic networks. Network simulations have long been used to study network resilience to station outages and to determine where additional stations are needed to reduce monitoring thresholds. NetMOD makes use of geophysical models to determine the source characteristics, signal attenuation along the path between the source and station, and the performance and noise properties of the station. These geophysical models are combined to simulate the relative amplitudes of signal and noise that are observed at each ofmore » the stations. From these signal-to-noise ratios (SNR), the probability of detection can be computed given a detection threshold. This document describes the parameters that are used to configure the NetMOD tool and the input and output parameters that make up the simulation definitions.« less

  2. Probabilistic Density Function Method for Stochastic ODEs of Power Systems with Uncertain Power Input

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

    Wang, Peng; Barajas-Solano, David A.; Constantinescu, Emil

    Wind and solar power generators are commonly described by a system of stochastic ordinary differential equations (SODEs) where random input parameters represent uncertainty in wind and solar energy. The existing methods for SODEs are mostly limited to delta-correlated random parameters (white noise). Here we use the Probability Density Function (PDF) method for deriving a closed-form deterministic partial differential equation (PDE) for the joint probability density function of the SODEs describing a power generator with time-correlated power input. The resulting PDE is solved numerically. A good agreement with Monte Carlo Simulations shows accuracy of the PDF method.

  3. Evaluation of limited blood sampling population input approaches for kinetic quantification of [18F]fluorothymidine PET data.

    PubMed

    Contractor, Kaiyumars B; Kenny, Laura M; Coombes, Charles R; Turkheimer, Federico E; Aboagye, Eric O; Rosso, Lula

    2012-03-24

    Quantification of kinetic parameters of positron emission tomography (PET) imaging agents normally requires collecting arterial blood samples which is inconvenient for patients and difficult to implement in routine clinical practice. The aim of this study was to investigate whether a population-based input function (POP-IF) reliant on only a few individual discrete samples allows accurate estimates of tumour proliferation using [18F]fluorothymidine (FLT). Thirty-six historical FLT-PET data with concurrent arterial sampling were available for this study. A population average of baseline scans blood data was constructed using leave-one-out cross-validation for each scan and used in conjunction with individual blood samples. Three limited sampling protocols were investigated including, respectively, only seven (POP-IF7), five (POP-IF5) and three (POP-IF3) discrete samples of the historical dataset. Additionally, using the three-point protocol, we derived a POP-IF3M, the only input function which was not corrected for the fraction of radiolabelled metabolites present in blood. The kinetic parameter for net FLT retention at steady state, Ki, was derived using the modified Patlak plot and compared with the original full arterial set for validation. Small percentage differences in the area under the curve between all the POP-IFs and full arterial sampling IF was found over 60 min (4.2%-5.7%), while there were, as expected, larger differences in the peak position and peak height.A high correlation between Ki values calculated using the original arterial input function and all the population-derived IFs was observed (R2 = 0.85-0.98). The population-based input showed good intra-subject reproducibility of Ki values (R2 = 0.81-0.94) and good correlation (R2 = 0.60-0.85) with Ki-67. Input functions generated using these simplified protocols over scan duration of 60 min estimate net PET-FLT retention with reasonable accuracy.

  4. Quantification of the Effect of Shuttling on Computed Tomography Perfusion Parameters by Investigation of Aortic Inputs on Different Table Positions From Shuttle-Mode Scans of Lung and Liver Tumors.

    PubMed

    Ghosh, Payel; Chandler, Adam G; Hobbs, Brian P; Sun, Jia; Rong, John; Hong, David; Subbiah, Vivek; Janku, Filip; Naing, Aung; Hwu, Wen-Jen; Ng, Chaan S

    The aim of this study was to quantify the effect of shuttling on computed tomography perfusion (CTp) parameters derived from shuttle-mode body CT images using aortic inputs from different table positions. Axial shuttle-mode CT scans were acquired from 6 patients (10 phases, 2 nonoverlapping table positions 1.4 seconds apart) after contrast agent administration. Artifacts resulting from the shuttling motion were corrected with nonrigid registration before computing CTp maps from 4 aortic levels chosen from the most superior and inferior slices of each table position scan. The effect of shuttling on CTp parameters was estimated by mean differences in mappings obtained from aortic inputs in different table positions. Shuttling effect was also quantified using 95% limits of agreement of CTp parameter differences within-table and between-table aortic positions from the interaortic mean CTp values. Blood flow, permeability surface, and hepatic arterial fraction differences were insignificant (P > 0.05) for both within-table and between-table comparisons. The 95% limits of agreement for within-table blood volume (BV) value deviations obtained from lung tumor regions were less than 4.7% (P = 0.18) compared with less than 12.2% (P = 0.003) for between-table BV value deviations. The 95% limits of agreement of within-table deviations for liver tumor regions were less than 1.9% (P = 0.55) for BV and less than 3.2% (P = 0.23) for mean transit time, whereas between-table BV and mean transit time deviations were less than 11.7% (P < 0.01) and less than 14.6% (P < 0.01), respectively. Values for normal liver tissue regions were concordant. Computed tomography perfusion parameters acquired from aortic levels within-table positions generally yielded higher agreement than mappings obtained from aortic levels between-table positions indicating differences due to shuttling effect.

  5. Translating landfill methane generation parameters among first-order decay models.

    PubMed

    Krause, Max J; Chickering, Giles W; Townsend, Timothy G

    2016-11-01

    Landfill gas (LFG) generation is predicted by a first-order decay (FOD) equation that incorporates two parameters: a methane generation potential (L 0 ) and a methane generation rate (k). Because non-hazardous waste landfills may accept many types of waste streams, multiphase models have been developed in an attempt to more accurately predict methane generation from heterogeneous waste streams. The ability of a single-phase FOD model to predict methane generation using weighted-average methane generation parameters and tonnages translated from multiphase models was assessed in two exercises. In the first exercise, waste composition from four Danish landfills represented by low-biodegradable waste streams was modeled in the Afvalzorg Multiphase Model and methane generation was compared to the single-phase Intergovernmental Panel on Climate Change (IPCC) Waste Model and LandGEM. In the second exercise, waste composition represented by IPCC waste components was modeled in the multiphase IPCC and compared to single-phase LandGEM and Australia's Solid Waste Calculator (SWC). In both cases, weight-averaging of methane generation parameters from waste composition data in single-phase models was effective in predicting cumulative methane generation from -7% to +6% of the multiphase models. The results underscore the understanding that multiphase models will not necessarily improve LFG generation prediction because the uncertainty of the method rests largely within the input parameters. A unique method of calculating the methane generation rate constant by mass of anaerobically degradable carbon was presented (k c ) and compared to existing methods, providing a better fit in 3 of 8 scenarios. Generally, single phase models with weighted-average inputs can accurately predict methane generation from multiple waste streams with varied characteristics; weighted averages should therefore be used instead of regional default values when comparing models. Translating multiphase

  6. StePar: an automatic code for stellar parameter determination

    NASA Astrophysics Data System (ADS)

    Tabernero, H. M.; González Hernández, J. I.; Montes, D.

    2013-05-01

    We introduce a new automatic code (StePar) for determinig stellar atmospheric parameters (T_{eff}, log{g}, ξ and [Fe/H]) in an automated way. StePar employs the 2002 version of the MOOG code (Sneden 1973) and a grid of Kurucz ATLAS9 plane-paralell model atmospheres (Kurucz 1993). The atmospheric parameters are obtained from the EWs of 263 Fe I and 36 Fe II lines (obtained from Sousa et al. 2008, A&A, 487, 373) iterating until the excitation and ionization equilibrium are fullfilled. StePar uses a Downhill Simplex method that minimizes a quadratic form composed by the excitation and ionization equilibrium conditions. Atmospheric parameters determined by StePar are independent of the stellar parameters initial-guess for the problem star, therefore we employ the canonical solar values as initial input. StePar can only deal with FGK stars from F6 to K4, also it can not work with fast rotators, veiled spectra, very metal poor stars or Signal to noise ratio below 30. Optionally StePar can operate with MARCS models (Gustafson et al. 2008, A&A, 486, 951) instead of Kurucz ATLAS9 models, additionally Turbospectrum (Alvarez & Plez 1998, A&A, 330, 1109) can replace the MOOG code and play its role during the parameter determination. StePar has been used to determine stellar parameters for some studies (Tabernero et al. 2012, A&A, 547, A13; Wisniewski et al. 2012, AJ, 143, 107). In addition StePar is being used to obtain parameters for FGK stars from the GAIA-ESO Survey.

  7. Multi-Response Optimization of WEDM Process Parameters Using Taguchi Based Desirability Function Analysis

    NASA Astrophysics Data System (ADS)

    Majumder, Himadri; Maity, Kalipada

    2018-03-01

    Shape memory alloy has a unique capability to return to its original shape after physical deformation by applying heat or thermo-mechanical or magnetic load. In this experimental investigation, desirability function analysis (DFA), a multi-attribute decision making was utilized to find out the optimum input parameter setting during wire electrical discharge machining (WEDM) of Ni-Ti shape memory alloy. Four critical machining parameters, namely pulse on time (TON), pulse off time (TOFF), wire feed (WF) and wire tension (WT) were taken as machining inputs for the experiments to optimize three interconnected responses like cutting speed, kerf width, and surface roughness. Input parameter combination TON = 120 μs., TOFF = 55 μs., WF = 3 m/min. and WT = 8 kg-F were found to produce the optimum results. The optimum process parameters for each desired response were also attained using Taguchi’s signal-to-noise ratio. Confirmation test has been done to validate the optimum machining parameter combination which affirmed DFA was a competent approach to select optimum input parameters for the ideal response quality for WEDM of Ni-Ti shape memory alloy.

  8. Reduced basis ANOVA methods for partial differential equations with high-dimensional random inputs

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

    Liao, Qifeng, E-mail: liaoqf@shanghaitech.edu.cn; Lin, Guang, E-mail: guanglin@purdue.edu

    2016-07-15

    In this paper we present a reduced basis ANOVA approach for partial deferential equations (PDEs) with random inputs. The ANOVA method combined with stochastic collocation methods provides model reduction in high-dimensional parameter space through decomposing high-dimensional inputs into unions of low-dimensional inputs. In this work, to further reduce the computational cost, we investigate spatial low-rank structures in the ANOVA-collocation method, and develop efficient spatial model reduction techniques using hierarchically generated reduced bases. We present a general mathematical framework of the methodology, validate its accuracy and demonstrate its efficiency with numerical experiments.

  9. Unsteady hovering wake parameters identified from dynamic model tests, part 1

    NASA Technical Reports Server (NTRS)

    Hohenemser, K. H.; Crews, S. T.

    1977-01-01

    The development of a 4-bladed model rotor is reported that can be excited with a simple eccentric mechanism in progressing and regressing modes with either harmonic or transient inputs. Parameter identification methods were applied to the problem of extracting parameters for linear perturbation models, including rotor dynamic inflow effects, from the measured blade flapping responses to transient pitch stirring excitations. These perturbation models were then used to predict blade flapping response to other pitch stirring transient inputs, and rotor wake and blade flapping responses to harmonic inputs. The viability and utility of using parameter identification methods for extracting the perturbation models from transients are demonstrated through these combined analytical and experimental studies.

  10. Organic and low input farming: Pros and cons for soil health

    USDA-ARS?s Scientific Manuscript database

    Organic and low input farming practices have both advantages and disadvantages in building soil health and maintaining productivity. Examining the effects of farming practices on soil health parameters can aid in developing whole system strategies that promote sustainability. Application of specific...

  11. Ecophysiological parameters for Pacific Northwest trees.

    Treesearch

    Amy E. Hessl; Cristina Milesi; Michael A. White; David L. Peterson; Robert E. Keane

    2004-01-01

    We developed a species- and location-specific database of published ecophysiological variables typically used as input parameters for biogeochemical models of coniferous and deciduous forested ecosystems in the Western United States. Parameters are based on the requirements of Biome-BGC, a widely used biogeochemical model that was originally parameterized for the...

  12. Effect of Heat Input on Geometry of Austenitic Stainless Steel Weld Bead on Low Carbon Steel

    NASA Astrophysics Data System (ADS)

    Saha, Manas Kumar; Hazra, Ritesh; Mondal, Ajit; Das, Santanu

    2018-05-01

    Among different weld cladding processes, gas metal arc welding (GMAW) cladding becomes a cost effective, user friendly, versatile method for protecting the surface of relatively lower grade structural steels from corrosion and/or erosion wear by depositing high grade stainless steels onto them. The quality of cladding largely depends upon the bead geometry of the weldment deposited. Weld bead geometry parameters, like bead width, reinforcement height, depth of penetration, and ratios like reinforcement form factor (RFF) and penetration shape factor (PSF) determine the quality of the weld bead geometry. Various process parameters of gas metal arc welding like heat input, current, voltage, arc travel speed, mode of metal transfer, etc. influence formation of bead geometry. In the current experimental investigation, austenite stainless steel (316) weld beads are formed on low alloy structural steel (E350) by GMAW using 100% CO2 as the shielding gas. Different combinations of current, voltage and arc travel speed are chosen so that heat input increases from 0.35 to 0.75 kJ/mm. Nine number of weld beads are deposited and replicated twice. The observations show that weld bead width increases linearly with increase in heat input, whereas reinforcement height and depth of penetration do not increase with increase in heat input. Regression analysis is done to establish the relationship between heat input and different geometrical parameters of weld bead. The regression models developed agrees well with the experimental data. Within the domain of the present experiment, it is observed that at higher heat input, the weld bead gets wider having little change in penetration and reinforcement; therefore, higher heat input may be recommended for austenitic stainless steel cladding on low alloy steel.

  13. Identification of single-input-single-output quantum linear systems

    NASA Astrophysics Data System (ADS)

    Levitt, Matthew; GuÅ£ǎ, Mǎdǎlin

    2017-03-01

    The purpose of this paper is to investigate system identification for single-input-single-output general (active or passive) quantum linear systems. For a given input we address the following questions: (1) Which parameters can be identified by measuring the output? (2) How can we construct a system realization from sufficient input-output data? We show that for time-dependent inputs, the systems which cannot be distinguished are related by symplectic transformations acting on the space of system modes. This complements a previous result of Guţă and Yamamoto [IEEE Trans. Autom. Control 61, 921 (2016), 10.1109/TAC.2015.2448491] for passive linear systems. In the regime of stationary quantum noise input, the output is completely determined by the power spectrum. We define the notion of global minimality for a given power spectrum, and characterize globally minimal systems as those with a fully mixed stationary state. We show that in the case of systems with a cascade realization, the power spectrum completely fixes the transfer function, so the system can be identified up to a symplectic transformation. We give a method for constructing a globally minimal subsystem direct from the power spectrum. Restricting to passive systems the analysis simplifies so that identifiability may be completely understood from the eigenvalues of a particular system matrix.

  14. A neural network-based input shaping for swing suppression of an overhead crane under payload hoisting and mass variations

    NASA Astrophysics Data System (ADS)

    Ramli, Liyana; Mohamed, Z.; Jaafar, H. I.

    2018-07-01

    This paper proposes an improved input shaping for minimising payload swing of an overhead crane with payload hoisting and payload mass variations. A real time unity magnitude zero vibration (UMZV) shaper is designed by using an artificial neural network trained by particle swarm optimisation. The proposed technique could predict and directly update the shaper's parameters in real time to handle the effects of time-varying parameters during the crane operation with hoisting. To evaluate the performances of the proposed method, experiments are conducted on a laboratory overhead crane with a payload hoisting, different payload masses and two different crane motions. The superiority of the proposed method is confirmed by reductions of at least 38.9% and 91.3% in the overall and residual swing responses, respectively over a UMZV shaper designed using an average operating frequency and a robust shaper namely Zero Vibration Derivative-Derivative (ZVDD). The proposed method also demonstrates a significant residual swing suppression as compared to a ZVDD shaper designed based on varying frequency. In addition, the significant reductions are achieved with a less shaper duration resulting in a satisfactory speed of response. It is envisaged that the proposed method can be used for designing effective input shapers for payload swing suppression of a crane with time-varying parameters and for a crane that employ finite actuation states.

  15. Joint analysis of input and parametric uncertainties in watershed water quality modeling: A formal Bayesian approach

    NASA Astrophysics Data System (ADS)

    Han, Feng; Zheng, Yi

    2018-06-01

    Significant Input uncertainty is a major source of error in watershed water quality (WWQ) modeling. It remains challenging to address the input uncertainty in a rigorous Bayesian framework. This study develops the Bayesian Analysis of Input and Parametric Uncertainties (BAIPU), an approach for the joint analysis of input and parametric uncertainties through a tight coupling of Markov Chain Monte Carlo (MCMC) analysis and Bayesian Model Averaging (BMA). The formal likelihood function for this approach is derived considering a lag-1 autocorrelated, heteroscedastic, and Skew Exponential Power (SEP) distributed error model. A series of numerical experiments were performed based on a synthetic nitrate pollution case and on a real study case in the Newport Bay Watershed, California. The Soil and Water Assessment Tool (SWAT) and Differential Evolution Adaptive Metropolis (DREAM(ZS)) were used as the representative WWQ model and MCMC algorithm, respectively. The major findings include the following: (1) the BAIPU can be implemented and used to appropriately identify the uncertain parameters and characterize the predictive uncertainty; (2) the compensation effect between the input and parametric uncertainties can seriously mislead the modeling based management decisions, if the input uncertainty is not explicitly accounted for; (3) the BAIPU accounts for the interaction between the input and parametric uncertainties and therefore provides more accurate calibration and uncertainty results than a sequential analysis of the uncertainties; and (4) the BAIPU quantifies the credibility of different input assumptions on a statistical basis and can be implemented as an effective inverse modeling approach to the joint inference of parameters and inputs.

  16. Uncertainty Analysis and Parameter Estimation For Nearshore Hydrodynamic Models

    NASA Astrophysics Data System (ADS)

    Ardani, S.; Kaihatu, J. M.

    2012-12-01

    Numerical models represent deterministic approaches used for the relevant physical processes in the nearshore. Complexity of the physics of the model and uncertainty involved in the model inputs compel us to apply a stochastic approach to analyze the robustness of the model. The Bayesian inverse problem is one powerful way to estimate the important input model parameters (determined by apriori sensitivity analysis) and can be used for uncertainty analysis of the outputs. Bayesian techniques can be used to find the range of most probable parameters based on the probability of the observed data and the residual errors. In this study, the effect of input data involving lateral (Neumann) boundary conditions, bathymetry and off-shore wave conditions on nearshore numerical models are considered. Monte Carlo simulation is applied to a deterministic numerical model (the Delft3D modeling suite for coupled waves and flow) for the resulting uncertainty analysis of the outputs (wave height, flow velocity, mean sea level and etc.). Uncertainty analysis of outputs is performed by random sampling from the input probability distribution functions and running the model as required until convergence to the consistent results is achieved. The case study used in this analysis is the Duck94 experiment, which was conducted at the U.S. Army Field Research Facility at Duck, North Carolina, USA in the fall of 1994. The joint probability of model parameters relevant for the Duck94 experiments will be found using the Bayesian approach. We will further show that, by using Bayesian techniques to estimate the optimized model parameters as inputs and applying them for uncertainty analysis, we can obtain more consistent results than using the prior information for input data which means that the variation of the uncertain parameter will be decreased and the probability of the observed data will improve as well. Keywords: Monte Carlo Simulation, Delft3D, uncertainty analysis, Bayesian techniques

  17. Assessment of input uncertainty by seasonally categorized latent variables using SWAT

    USDA-ARS?s Scientific Manuscript database

    Watershed processes have been explored with sophisticated simulation models for the past few decades. It has been stated that uncertainty attributed to alternative sources such as model parameters, forcing inputs, and measured data should be incorporated during the simulation process. Among varyin...

  18. Spatiotemporal coding of inputs for a system of globally coupled phase oscillators

    NASA Astrophysics Data System (ADS)

    Wordsworth, John; Ashwin, Peter

    2008-12-01

    We investigate the spatiotemporal coding of low amplitude inputs to a simple system of globally coupled phase oscillators with coupling function g(ϕ)=-sin(ϕ+α)+rsin(2ϕ+β) that has robust heteroclinic cycles (slow switching between cluster states). The inputs correspond to detuning of the oscillators. It was recently noted that globally coupled phase oscillators can encode their frequencies in the form of spatiotemporal codes of a sequence of cluster states [P. Ashwin, G. Orosz, J. Wordsworth, and S. Townley, SIAM J. Appl. Dyn. Syst. 6, 728 (2007)]. Concentrating on the case of N=5 oscillators we show in detail how the spatiotemporal coding can be used to resolve all of the information that relates the individual inputs to each other, providing that a long enough time series is considered. We investigate robustness to the addition of noise and find a remarkable stability, especially of the temporal coding, to the addition of noise even for noise of a comparable magnitude to the inputs.

  19. Design and optimization of input shapers for liquid slosh suppression

    NASA Astrophysics Data System (ADS)

    Aboel-Hassan, Ameen; Arafa, Mustafa; Nassef, Ashraf

    2009-02-01

    The need for fast maneuvering and accurate positioning of flexible structures poses a control challenge. The inherent flexibility in these lightly damped systems creates large undesirable residual vibrations in response to rapid excitations. Several control approaches have been proposed to tackle this class of problems, of which the input shaping technique is appealing in many aspects. While input shaping has been widely investigated to attenuate residual vibrations in flexible structures, less attention was granted to expand its viability in further applications. The aim of this work is to develop a methodology for applying input shaping techniques to suppress sloshing effects in open moving containers to facilitate safe and fast point-to-point movements. The liquid behavior is modeled using finite element analysis. The input shaper parameters are optimized to find the commands that would result in minimum residual vibration. Other objectives, such as improved robustness, and motion constraints such as deflection limiting are also addressed in the optimization scheme. Numerical results are verified on an experimental setup consisting of a small motor-driven water tank undergoing rectilinear motion, while measuring both the tank motion and free surface displacement of the water. The results obtained suggest that input shaping is an effective method for liquid slosh suppression.

  20. Effect of Burnishing Parameters on Surface Finish

    NASA Astrophysics Data System (ADS)

    Shirsat, Uddhav; Ahuja, Basant; Dhuttargaon, Mukund

    2017-08-01

    Burnishing is cold working process in which hard balls are pressed against the surface, resulting in improved surface finish. The surface gets compressed and then plasticized. This is a highly finishing process which is becoming more popular. Surface quality of the product improves its aesthetic appearance. The product made up of aluminum material is subjected to burnishing process during which kerosene is used as a lubricant. In this study factors affecting burnishing process such as burnishing force, speed, feed, work piece diameter and ball diameter are considered as input parameters while surface finish is considered as an output parameter In this study, experiments are designed using 25 factorial design in order to analyze the relationship between input and output parameters. The ANOVA technique and F-test are used for further analysis.

  1. On Markov parameters in system identification

    NASA Technical Reports Server (NTRS)

    Phan, Minh; Juang, Jer-Nan; Longman, Richard W.

    1991-01-01

    A detailed discussion of Markov parameters in system identification is given. Different forms of input-output representation of linear discrete-time systems are reviewed and discussed. Interpretation of sampled response data as Markov parameters is presented. Relations between the state-space model and particular linear difference models via the Markov parameters are formulated. A generalization of Markov parameters to observer and Kalman filter Markov parameters for system identification is explained. These extended Markov parameters play an important role in providing not only a state-space realization, but also an observer/Kalman filter for the system of interest.

  2. Stochastic control system parameter identifiability

    NASA Technical Reports Server (NTRS)

    Lee, C. H.; Herget, C. J.

    1975-01-01

    The parameter identification problem of general discrete time, nonlinear, multiple input/multiple output dynamic systems with Gaussian white distributed measurement errors is considered. The knowledge of the system parameterization was assumed to be known. Concepts of local parameter identifiability and local constrained maximum likelihood parameter identifiability were established. A set of sufficient conditions for the existence of a region of parameter identifiability was derived. A computation procedure employing interval arithmetic was provided for finding the regions of parameter identifiability. If the vector of the true parameters is locally constrained maximum likelihood (CML) identifiable, then with probability one, the vector of true parameters is a unique maximal point of the maximum likelihood function in the region of parameter identifiability and the constrained maximum likelihood estimation sequence will converge to the vector of true parameters.

  3. Combined input shaping and feedback control for double-pendulum systems

    NASA Astrophysics Data System (ADS)

    Mar, Robert; Goyal, Anurag; Nguyen, Vinh; Yang, Tianle; Singhose, William

    2017-02-01

    A control system combining input shaping and feedback is developed for double-pendulum systems subjected to external disturbances. The proposed control method achieves fast point-to-point response similar to open-loop input-shaping control. It also minimizes transient deflections during the motion of the system, and disturbance-induced residual swing using the feedback control. Effects of parameter variations such as the mass ratio of the double pendulum, the suspension length ratio, and the move distance were studied via numerical simulation. The most important results were also verified with experiments on a small-scale crane. The controller effectively suppresses the disturbances and is robust to modelling uncertainties and task variations.

  4. Neurons in the pontomedullary reticular formation receive converging inputs from the hindlimb and labyrinth.

    PubMed

    Miller, Derek M; DeMayo, William M; Bourdages, George H; Wittman, Samuel R; Yates, Bill J; McCall, Andrew A

    2017-04-01

    The integration of inputs from vestibular and proprioceptive sensors within the central nervous system is critical to postural regulation. We recently demonstrated in both decerebrate and conscious cats that labyrinthine and hindlimb inputs converge onto vestibular nucleus neurons. The pontomedullary reticular formation (pmRF) also plays a key role in postural control, and additionally participates in regulating locomotion. Thus, we hypothesized that like vestibular nucleus neurons, pmRF neurons integrate inputs from the limb and labyrinth. To test this hypothesis, we recorded the responses of pmRF neurons to passive ramp-and-hold movements of the hindlimb and to whole-body tilts, in both decerebrate and conscious felines. We found that pmRF neuronal activity was modulated by hindlimb movement in the rostral-caudal plane. Most neurons in both decerebrate (83% of units) and conscious (61% of units) animals encoded both flexion and extension movements of the hindlimb. In addition, hindlimb somatosensory inputs converged with vestibular inputs onto pmRF neurons in both preparations. Pontomedullary reticular formation neurons receiving convergent vestibular and limb inputs likely participate in balance control by governing reticulospinal outflow.

  5. Epistasis interaction of QTL effects as a genetic parameter influencing estimation of the genetic additive effect.

    PubMed

    Bocianowski, Jan

    2013-03-01

    Epistasis, an additive-by-additive interaction between quantitative trait loci, has been defined as a deviation from the sum of independent effects of individual genes. Epistasis between QTLs assayed in populations segregating for an entire genome has been found at a frequency close to that expected by chance alone. Recently, epistatic effects have been considered by many researchers as important for complex traits. In order to understand the genetic control of complex traits, it is necessary to clarify additive-by-additive interactions among genes. Herein we compare estimates of a parameter connected with the additive gene action calculated on the basis of two models: a model excluding epistasis and a model with additive-by-additive interaction effects. In this paper two data sets were analysed: 1) 150 barley doubled haploid lines derived from the Steptoe × Morex cross, and 2) 145 DH lines of barley obtained from the Harrington × TR306 cross. The results showed that in cases when the effect of epistasis was different from zero, the coefficient of determination was larger for the model with epistasis than for the one excluding epistasis. These results indicate that epistatic interaction plays an important role in controlling the expression of complex traits.

  6. Differential inputs to striatal cholinergic and parvalbumin interneurons imply functional distinctions

    PubMed Central

    Klug, Jason R; Engelhardt, Max D; Cadman, Cara N; Li, Hao; Smith, Jared B; Ayala, Sarah; Williams, Elora W; Hoffman, Hilary

    2018-01-01

    Striatal cholinergic (ChAT) and parvalbumin (PV) interneurons exert powerful influences on striatal function in health and disease, yet little is known about the organization of their inputs. Here using rabies tracing, electrophysiology and genetic tools, we compare the whole-brain inputs to these two types of striatal interneurons and dissect their functional connectivity in mice. ChAT interneurons receive a substantial cortical input from associative regions of cortex, such as the orbitofrontal cortex. Amongst subcortical inputs, a previously unknown inhibitory thalamic reticular nucleus input to striatal PV interneurons is identified. Additionally, the external segment of the globus pallidus targets striatal ChAT interneurons, which is sufficient to inhibit tonic ChAT interneuron firing. Finally, we describe a novel excitatory pathway from the pedunculopontine nucleus that innervates ChAT interneurons. These results establish the brain-wide direct inputs of two major types of striatal interneurons and allude to distinct roles in regulating striatal activity and controlling behavior. PMID:29714166

  7. Robust Fault Detection for Switched Fuzzy Systems With Unknown Input.

    PubMed

    Han, Jian; Zhang, Huaguang; Wang, Yingchun; Sun, Xun

    2017-10-03

    This paper investigates the fault detection problem for a class of switched nonlinear systems in the T-S fuzzy framework. The unknown input is considered in the systems. A novel fault detection unknown input observer design method is proposed. Based on the proposed observer, the unknown input can be removed from the fault detection residual. The weighted H∞ performance level is considered to ensure the robustness. In addition, the weighted H₋ performance level is introduced, which can increase the sensibility of the proposed detection method. To verify the proposed scheme, a numerical simulation example and an electromechanical system simulation example are provided at the end of this paper.

  8. Evaluation of FEM engineering parameters from insitu tests

    DOT National Transportation Integrated Search

    2001-12-01

    The study looked critically at insitu test methods (SPT, CPT, DMT, and PMT) as a means for developing finite element constitutive model input parameters. The first phase of the study examined insitu test derived parameters with laboratory triaxial te...

  9. High input impedance amplifier

    NASA Technical Reports Server (NTRS)

    Kleinberg, Leonard L.

    1995-01-01

    High input impedance amplifiers are provided which reduce the input impedance solely to a capacitive reactance, or, in a somewhat more complex design, provide an extremely high essentially infinite, capacitive reactance. In one embodiment, where the input impedance is reduced in essence, to solely a capacitive reactance, an operational amplifier in a follower configuration is driven at its non-inverting input and a resistor with a predetermined magnitude is connected between the inverting and non-inverting inputs. A second embodiment eliminates the capacitance from the input by adding a second stage to the first embodiment. The second stage is a second operational amplifier in a non-inverting gain-stage configuration where the output of the first follower stage drives the non-inverting input of the second stage and the output of the second stage is fed back to the non-inverting input of the first stage through a capacitor of a predetermined magnitude. These amplifiers, while generally useful, are very useful as sensor buffer amplifiers that may eliminate significant sources of error.

  10. Handling Input and Output for COAMPS

    NASA Technical Reports Server (NTRS)

    Fitzpatrick, Patrick; Tran, Nam; Li, Yongzuo; Anantharaj, Valentine

    2007-01-01

    Two suites of software have been developed to handle the input and output of the Coupled Ocean Atmosphere Prediction System (COAMPS), which is a regional atmospheric model developed by the Navy for simulating and predicting weather. Typically, the initial and boundary conditions for COAMPS are provided by a flat-file representation of the Navy s global model. Additional algorithms are needed for running the COAMPS software using global models. One of the present suites satisfies this need for running COAMPS using the Global Forecast System (GFS) model of the National Oceanic and Atmospheric Administration. The first step in running COAMPS downloading of GFS data from an Internet file-transfer-protocol (FTP) server computer of the National Centers for Environmental Prediction (NCEP) is performed by one of the programs (SSC-00273) in this suite. The GFS data, which are in gridded binary (GRIB) format, are then changed to a COAMPS-compatible format by another program in the suite (SSC-00278). Once a forecast is complete, still another program in the suite (SSC-00274) sends the output data to a different server computer. The second suite of software (SSC- 00275) addresses the need to ingest up-to-date land-use-and-land-cover (LULC) data into COAMPS for use in specifying typical climatological values of such surface parameters as albedo, aerodynamic roughness, and ground wetness. This suite includes (1) a program to process LULC data derived from observations by the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard NASA s Terra and Aqua satellites, (2) programs to derive new climatological parameters for the 17-land-use-category MODIS data; and (3) a modified version of a FORTRAN subroutine to be used by COAMPS. The MODIS data files are processed to reformat them into a compressed American Standard Code for Information Interchange (ASCII) format used by COAMPS for efficient processing.

  11. Comparisons of Solar Wind Coupling Parameters with Auroral Energy Deposition Rates

    NASA Technical Reports Server (NTRS)

    Elsen, R.; Brittnacher, M. J.; Fillingim, M. O.; Parks, G. K.; Germany G. A.; Spann, J. F., Jr.

    1997-01-01

    Measurement of the global rate of energy deposition in the ionosphere via auroral particle precipitation is one of the primary goals of the Polar UVI program and is an important component of the ISTP program. The instantaneous rate of energy deposition for the entire month of January 1997 has been calculated by applying models to the UVI images and is presented by Fillingim et al. In this session. A number of parameters that predict the rate of coupling of solar wind energy into the magnetosphere have been proposed in the last few decades. Some of these parameters, such as the epsilon parameter of Perrault and Akasofu, depend on the instantaneous values in the solar wind. Other parameters depend on the integrated values of solar wind parameters, especially IMF Bz, e.g. applied flux which predicts the net transfer of magnetic flux to the tail. While these parameters have often been used successfully with substorm studies, their validity in terms of global energy input has not yet been ascertained, largely because data such as that supplied by the ISTP program was lacking. We have calculated these and other energy coupling parameters for January 1997 using solar wind data provided by WIND and other solar wind monitors. The rates of energy input predicted by these parameters are compared to those measured through UVI data and correlations are sought. Whether these parameters are better at providing an instantaneous rate of energy input or an average input over some time period is addressed. We also study if either type of parameter may provide better correlations if a time delay is introduced; if so, this time delay may provide a characteristic time for energy transport in the coupled solar wind-magnetosphere-ionosphere system.

  12. Partial and total actuator faults accommodation for input-affine nonlinear process plants.

    PubMed

    Mihankhah, Amin; Salmasi, Farzad R; Salahshoor, Karim

    2013-05-01

    In this paper, a new fault-tolerant control system is proposed for input-affine nonlinear plants based on Model Reference Adaptive System (MRAS) structure. The proposed method has the capability to accommodate both partial and total actuator failures along with bounded external disturbances. In this methodology, the conventional MRAS control law is modified by augmenting two compensating terms. One of these terms is added to eliminate the nonlinear dynamic, while the other is reinforced to compensate the distractive effects of the total actuator faults and external disturbances. In addition, no Fault Detection and Diagnosis (FDD) unit is needed in the proposed method. Moreover, the control structure has good robustness capability against the parameter variation. The performance of this scheme is evaluated using a CSTR system and the results were satisfactory. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

  13. Combining control input with flight path data to evaluate pilot performance in transport aircraft.

    PubMed

    Ebbatson, Matt; Harris, Don; Huddlestone, John; Sears, Rodney

    2008-11-01

    When deriving an objective assessment of piloting performance from flight data records, it is common to employ metrics which purely evaluate errors in flight path parameters. The adequacy of pilot performance is evaluated from the flight path of the aircraft. However, in large jet transport aircraft these measures may be insensitive and require supplementing with frequency-based measures of control input parameters. Flight path and control input data were collected from pilots undertaking a jet transport aircraft conversion course during a series of symmetric and asymmetric approaches in a flight simulator. The flight path data were analyzed for deviations around the optimum flight path while flying an instrument landing approach. Manipulation of the flight controls was subject to analysis using a series of power spectral density measures. The flight path metrics showed no significant differences in performance between the symmetric and asymmetric approaches. However, control input frequency domain measures revealed that the pilots employed highly different control strategies in the pitch and yaw axes. The results demonstrate that to evaluate pilot performance fully in large aircraft, it is necessary to employ performance metrics targeted at both the outer control loop (flight path) and the inner control loop (flight control) parameters in parallel, evaluating both the product and process of a pilot's performance.

  14. HEAT INPUT AND POST WELD HEAT TREATMENT EFFECTS ON REDUCED-ACTIVATION FERRITIC/MARTENSITIC STEEL FRICTION STIR WELDS

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

    Tang, Wei; Chen, Gaoqiang; Chen, Jian

    Reduced-activation ferritic/martensitic (RAFM) steels are an important class of structural materials for fusion reactor internals developed in recent years because of their improved irradiation resistance. However, they can suffer from welding induced property degradations. In this paper, a solid phase joining technology friction stir welding (FSW) was adopted to join a RAFM steel Eurofer 97 and different FSW parameters/heat input were chosen to produce welds. FSW response parameters, joint microstructures and microhardness were investigated to reveal relationships among welding heat input, weld structure characterization and mechanical properties. In general, FSW heat input results in high hardness inside the stir zonemore » mostly due to a martensitic transformation. It is possible to produce friction stir welds similar to but not with exactly the same base metal hardness when using low power input because of other hardening mechanisms. Further, post weld heat treatment (PWHT) is a very effective way to reduce FSW stir zone hardness values.« less

  15. Sensitivity analysis of a sound absorption model with correlated inputs

    NASA Astrophysics Data System (ADS)

    Chai, W.; Christen, J.-L.; Zine, A.-M.; Ichchou, M.

    2017-04-01

    Sound absorption in porous media is a complex phenomenon, which is usually addressed with homogenized models, depending on macroscopic parameters. Since these parameters emerge from the structure at microscopic scale, they may be correlated. This paper deals with sensitivity analysis methods of a sound absorption model with correlated inputs. Specifically, the Johnson-Champoux-Allard model (JCA) is chosen as the objective model with correlation effects generated by a secondary micro-macro semi-empirical model. To deal with this case, a relatively new sensitivity analysis method Fourier Amplitude Sensitivity Test with Correlation design (FASTC), based on Iman's transform, is taken into application. This method requires a priori information such as variables' marginal distribution functions and their correlation matrix. The results are compared to the Correlation Ratio Method (CRM) for reference and validation. The distribution of the macroscopic variables arising from the microstructure, as well as their correlation matrix are studied. Finally the results of tests shows that the correlation has a very important impact on the results of sensitivity analysis. Assessment of correlation strength among input variables on the sensitivity analysis is also achieved.

  16. Logarithmic and power law input-output relations in sensory systems with fold-change detection.

    PubMed

    Adler, Miri; Mayo, Avi; Alon, Uri

    2014-08-01

    Two central biophysical laws describe sensory responses to input signals. One is a logarithmic relationship between input and output, and the other is a power law relationship. These laws are sometimes called the Weber-Fechner law and the Stevens power law, respectively. The two laws are found in a wide variety of human sensory systems including hearing, vision, taste, and weight perception; they also occur in the responses of cells to stimuli. However the mechanistic origin of these laws is not fully understood. To address this, we consider a class of biological circuits exhibiting a property called fold-change detection (FCD). In these circuits the response dynamics depend only on the relative change in input signal and not its absolute level, a property which applies to many physiological and cellular sensory systems. We show analytically that by changing a single parameter in the FCD circuits, both logarithmic and power-law relationships emerge; these laws are modified versions of the Weber-Fechner and Stevens laws. The parameter that determines which law is found is the steepness (effective Hill coefficient) of the effect of the internal variable on the output. This finding applies to major circuit architectures found in biological systems, including the incoherent feed-forward loop and nonlinear integral feedback loops. Therefore, if one measures the response to different fold changes in input signal and observes a logarithmic or power law, the present theory can be used to rule out certain FCD mechanisms, and to predict their cooperativity parameter. We demonstrate this approach using data from eukaryotic chemotaxis signaling.

  17. Parameter Estimation for Thurstone Choice Models

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

    Vojnovic, Milan; Yun, Seyoung

    We consider the estimation accuracy of individual strength parameters of a Thurstone choice model when each input observation consists of a choice of one item from a set of two or more items (so called top-1 lists). This model accommodates the well-known choice models such as the Luce choice model for comparison sets of two or more items and the Bradley-Terry model for pair comparisons. We provide a tight characterization of the mean squared error of the maximum likelihood parameter estimator. We also provide similar characterizations for parameter estimators defined by a rank-breaking method, which amounts to deducing one ormore » more pair comparisons from a comparison of two or more items, assuming independence of these pair comparisons, and maximizing a likelihood function derived under these assumptions. We also consider a related binary classification problem where each individual parameter takes value from a set of two possible values and the goal is to correctly classify all items within a prescribed classification error. The results of this paper shed light on how the parameter estimation accuracy depends on given Thurstone choice model and the structure of comparison sets. In particular, we found that for unbiased input comparison sets of a given cardinality, when in expectation each comparison set of given cardinality occurs the same number of times, for a broad class of Thurstone choice models, the mean squared error decreases with the cardinality of comparison sets, but only marginally according to a diminishing returns relation. On the other hand, we found that there exist Thurstone choice models for which the mean squared error of the maximum likelihood parameter estimator can decrease much faster with the cardinality of comparison sets. We report empirical evaluation of some claims and key parameters revealed by theory using both synthetic and real-world input data from some popular sport competitions and online labor platforms.« less

  18. Additional deleterious effects of alcohol consumption on sperm parameters and DNA integrity in diabetic mice.

    PubMed

    Pourentezari, M; Talebi, A R; Mangoli, E; Anvari, M; Rahimipour, M

    2016-06-01

    The aim of this study was to survey the impact of alcohol consumption on sperm parameters and DNA integrity in experimentally induced diabetic mice. A total of 32 adult male mice were divided into four groups: mice of group 1 served as control fed on basal diet, group 2 received streptozotocin (STZ) (200 mg kg(-1) , single dose, intraperitoneal) and basal diet, group 3 received alcohol (10 mg kg(-1) , water soluble) and basal diet, and group 4 received STZ and alcohol for 35 days. The cauda epididymidis of each mouse was dissected and placed in 1 ml of pre-warm Ham's F10 culture medium for 30 min. The swim-out spermatozoa were analysed for count, motility, morphology and viability. Sperm chromatin quality was evaluated with aniline blue, toluidine blue, acridine orange and chromomycin A3 staining. The results showed that all sperm parameters had significant differences (P < 0.05), also when sperm chromatin was assessed with cytochemical tests. There were significant differences (P < 0.001) between the groups. According to our results, alcohol and diabetes can cause abnormalities in sperm parameters and chromatin quality. In addition, alcohol consumption in diabetic mice can intensify sperm chromatin/DNA damage. © 2015 Blackwell Verlag GmbH.

  19. Probabilistic Parameter Uncertainty Analysis of Single Input Single Output Control Systems

    NASA Technical Reports Server (NTRS)

    Smith, Brett A.; Kenny, Sean P.; Crespo, Luis G.

    2005-01-01

    The current standards for handling uncertainty in control systems use interval bounds for definition of the uncertain parameters. This approach gives no information about the likelihood of system performance, but simply gives the response bounds. When used in design, current methods of m-analysis and can lead to overly conservative controller design. With these methods, worst case conditions are weighted equally with the most likely conditions. This research explores a unique approach for probabilistic analysis of control systems. Current reliability methods are examined showing the strong areas of each in handling probability. A hybrid method is developed using these reliability tools for efficiently propagating probabilistic uncertainty through classical control analysis problems. The method developed is applied to classical response analysis as well as analysis methods that explore the effects of the uncertain parameters on stability and performance metrics. The benefits of using this hybrid approach for calculating the mean and variance of responses cumulative distribution functions are shown. Results of the probabilistic analysis of a missile pitch control system, and a non-collocated mass spring system, show the added information provided by this hybrid analysis.

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

    NASA Astrophysics Data System (ADS)

    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

  1. Input-output model for MACCS nuclear accident impacts estimation¹

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

    Outkin, Alexander V.; Bixler, Nathan E.; Vargas, Vanessa N

    Since the original economic model for MACCS was developed, better quality economic data (as well as the tools to gather and process it) and better computational capabilities have become available. The update of the economic impacts component of the MACCS legacy model will provide improved estimates of business disruptions through the use of Input-Output based economic impact estimation. This paper presents an updated MACCS model, bases on Input-Output methodology, in which economic impacts are calculated using the Regional Economic Accounting analysis tool (REAcct) created at Sandia National Laboratories. This new GDP-based model allows quick and consistent estimation of gross domesticmore » product (GDP) losses due to nuclear power plant accidents. This paper outlines the steps taken to combine the REAcct Input-Output-based model with the MACCS code, describes the GDP loss calculation, and discusses the parameters and modeling assumptions necessary for the estimation of long-term effects of nuclear power plant accidents.« less

  2. Input-current shaped ac to dc converters

    NASA Technical Reports Server (NTRS)

    1986-01-01

    The problem of achieving near unity power factor while supplying power to a dc load from a single phase ac source of power is examined. Power processors for this application must perform three functions: input current shaping, energy storage, and output voltage regulation. The methods available for performing each of these three functions are reviewed. Input current shaping methods are either active or passive, with the active methods divided into buck-like and boost-like techniques. In addition to large reactances, energy storage methods include resonant filters, active filters, and active storage schemes. Fast voltage regulation can be achieved by post regulation or by supplementing the current shaping topology with an extra switch. Some indications of which methods are best suited for particular applications concludes the discussion.

  3. Temporal rainfall estimation using input data reduction and model inversion

    NASA Astrophysics Data System (ADS)

    Wright, A. J.; Vrugt, J. A.; Walker, J. P.; Pauwels, V. R. N.

    2016-12-01

    Floods are devastating natural hazards. To provide accurate, precise and timely flood forecasts there is a need to understand the uncertainties associated with temporal rainfall and model parameters. The estimation of temporal rainfall and model parameter distributions from streamflow observations in complex dynamic catchments adds skill to current areal rainfall estimation methods, allows for the uncertainty of rainfall input to be considered when estimating model parameters and provides the ability to estimate rainfall from poorly gauged catchments. Current methods to estimate temporal rainfall distributions from streamflow are unable to adequately explain and invert complex non-linear hydrologic systems. This study uses the Discrete Wavelet Transform (DWT) to reduce rainfall dimensionality for the catchment of Warwick, Queensland, Australia. The reduction of rainfall to DWT coefficients allows the input rainfall time series to be simultaneously estimated along with model parameters. The estimation process is conducted using multi-chain Markov chain Monte Carlo simulation with the DREAMZS algorithm. The use of a likelihood function that considers both rainfall and streamflow error allows for model parameter and temporal rainfall distributions to be estimated. Estimation of the wavelet approximation coefficients of lower order decomposition structures was able to estimate the most realistic temporal rainfall distributions. These rainfall estimates were all able to simulate streamflow that was superior to the results of a traditional calibration approach. It is shown that the choice of wavelet has a considerable impact on the robustness of the inversion. The results demonstrate that streamflow data contains sufficient information to estimate temporal rainfall and model parameter distributions. The extent and variance of rainfall time series that are able to simulate streamflow that is superior to that simulated by a traditional calibration approach is a

  4. Robust synergetic control design under inputs and states constraints

    NASA Astrophysics Data System (ADS)

    Rastegar, Saeid; Araújo, Rui; Sadati, Jalil

    2018-03-01

    In this paper, a novel robust-constrained control methodology for discrete-time linear parameter-varying (DT-LPV) systems is proposed based on a synergetic control theory (SCT) approach. It is shown that in DT-LPV systems without uncertainty, and for any unmeasured bounded additive disturbance, the proposed controller accomplishes the goal of stabilising the system by asymptotically driving the error of the controlled variable to a bounded set containing the origin and then maintaining it there. Moreover, given an uncertain DT-LPV system jointly subject to unmeasured and constrained additive disturbances, and constraints in states, input commands and reference signals (set points), then invariant set theory is used to find an appropriate polyhedral robust invariant region in which the proposed control framework is guaranteed to robustly stabilise the closed-loop system. Furthermore, this is achieved even for the case of varying non-zero control set points in such uncertain DT-LPV systems. The controller is characterised to have a simple structure leading to an easy implementation, and a non-complex design process. The effectiveness of the proposed method and the implications of the controller design on feasibility and closed-loop performance are demonstrated through application examples on the temperature control on a continuous-stirred tank reactor plant, on the control of a real-coupled DC motor plant, and on an open-loop unstable system example.

  5. Cost-effectiveness of additional catheter-directed thrombolysis for deep vein thrombosis.

    PubMed

    Enden, T; Resch, S; White, C; Wik, H S; Kløw, N E; Sandset, P M

    2013-06-01

    Additional treatment with catheter-directed thrombolysis (CDT) has recently been shown to reduce post-thrombotic syndrome (PTS). To estimate the cost effectiveness of additional CDT compared with standard treatment alone. Using a Markov decision model, we compared the two treatment strategies in patients with a high proximal deep vein thrombosis (DVT) and a low risk of bleeding. The model captured the development of PTS, recurrent venous thromboembolism and treatment-related adverse events within a lifetime horizon and the perspective of a third-party payer. Uncertainty was assessed with one-way and probabilistic sensitivity analyzes. Model inputs from the CaVenT study included PTS development, major bleeding from CDT and utilities for post DVT states including PTS. The remaining clinical inputs were obtained from the literature. Costs obtained from the CaVenT study, hospital accounts and the literature are expressed in US dollars ($); effects in quality adjusted life years (QALY). In base case analyzes, additional CDT accumulated 32.31 QALYs compared with 31.68 QALYs after standard treatment alone. Direct medical costs were $64,709 for additional CDT and $51,866 for standard treatment. The incremental cost-effectiveness ratio (ICER) was $20,429/QALY gained. One-way sensitivity analysis showed model sensitivity to the clinical efficacy of both strategies, but the ICER remained < $55,000/QALY over the full range of all parameters. The probability that CDT is cost effective was 82% at a willingness to pay threshold of $50,000/QALY gained. Additional CDT is likely to be a cost-effective alternative to the standard treatment for patients with a high proximal DVT and a low risk of bleeding. © 2013 International Society on Thrombosis and Haemostasis.

  6. Cost-effectiveness of additional catheter-directed thrombolysis for deep vein thrombosis

    PubMed Central

    ENDEN, T.; RESCH, S.; WHITE, C.; WIK, H. S.; KLØW, N. E.; SANDSET, P. M.

    2013-01-01

    Summary Background Additional treatment with catheter-directed thrombolysis (CDT) has recently been shown to reduce post-thrombotic syndrome (PTS). Objectives To estimate the cost effectiveness of additional CDT compared with standard treatment alone. Methods Using a Markov decision model, we compared the two treatment strategies in patients with a high proximal deep vein thrombosis (DVT) and a low risk of bleeding. The model captured the development of PTS, recurrent venous thromboembolism and treatment-related adverse events within a lifetime horizon and the perspective of a third-party payer. Uncertainty was assessed with one-way and probabilistic sensitivity analyzes. Model inputs from the CaVenT study included PTS development, major bleeding from CDT and utilities for post DVT states including PTS. The remaining clinical inputs were obtained from the literature. Costs obtained from the CaVenT study, hospital accounts and the literature are expressed in US dollars ($); effects in quality adjusted life years (QALY). Results In base case analyzes, additional CDT accumulated 32.31 QALYs compared with 31.68 QALYs after standard treatment alone. Direct medical costs were $64 709 for additional CDT and $51 866 for standard treatment. The incremental cost-effectiveness ratio (ICER) was $20 429/QALY gained. One-way sensitivity analysis showed model sensitivity to the clinical efficacy of both strategies, but the ICER remained < $55 000/QALY over the full range of all parameters. The probability that CDT is cost effective was 82% at a willingness to pay threshold of $50 000/QALY gained. Conclusions Additional CDT is likely to be a cost-effective alternative to the standard treatment for patients with a high proximal DVT and a low risk of bleeding. PMID:23452204

  7. Neurons in the pontomedullary reticular formation receive converging inputs from the hindlimb and labyrinth

    PubMed Central

    Miller, Derek M.; DeMayo, William M.; Bourdages, George H.; Wittman, Samuel; Yates, Bill J.; McCall, Andrew A.

    2017-01-01

    The integration of inputs from vestibular and proprioceptive sensors within the central nervous system is critical to postural regulation. We recently demonstrated in both decerebrate and conscious cats that labyrinthine and hindlimb inputs converge onto vestibular nucleus neurons. The pontomedullary reticular formation (pmRF) also plays a key role in postural control, and additionally participates in regulating locomotion. Thus, we hypothesized that like vestibular nucleus neurons, pmRF neurons integrate inputs from the limb and labyrinth. To test this hypothesis, we recorded the responses of pmRF neurons to passive ramp-and-hold movements of the hindlimb and to whole-body tilts, in both decerebrate and conscious felines. We found that pmRF neuronal activity was modulated by hindlimb movement in the rostral-caudal plane. Most neurons in both decerebrate (83% of units) and conscious (61% of units) animals encoded both flexion and extension movements of the hindlimb. Additionally, hindlimb somatosensory inputs converged with vestibular inputs onto pmRF neurons in both preparations. Pontomedullary reticular formation neurons receiving convergent vestibular and limb inputs likely participate in balance control by governing reticulospinal outflow. PMID:28188328

  8. Forecasting Kp from solar wind data: input parameter study using 3-hour averages and 3-hour range values

    NASA Astrophysics Data System (ADS)

    Wintoft, Peter; Wik, Magnus; Matzka, Jürgen; Shprits, Yuri

    2017-11-01

    We have developed neural network models that predict Kp from upstream solar wind data. We study the importance of various input parameters, starting with the magnetic component Bz, particle density n, and velocity V and then adding total field B and the By component. As we also notice a seasonal and UT variation in average Kp we include functions of day-of-year and UT. Finally, as Kp is a global representation of the maximum range of geomagnetic variation over 3-hour UT intervals we conclude that sudden changes in the solar wind can have a big effect on Kp, even though it is a 3-hour value. Therefore, 3-hour solar wind averages will not always appropriately represent the solar wind condition, and we introduce 3-hour maxima and minima values to some degree address this problem. We find that introducing total field B and 3-hour maxima and minima, derived from 1-minute solar wind data, have a great influence on the performance. Due to the low number of samples for high Kp values there can be considerable variation in predicted Kp for different networks with similar validation errors. We address this issue by using an ensemble of networks from which we use the median predicted Kp. The models (ensemble of networks) provide prediction lead times in the range 20-90 min given by the time it takes a solar wind structure to travel from L1 to Earth. Two models are implemented that can be run with real time data: (1) IRF-Kp-2017-h3 uses the 3-hour averages of the solar wind data and (2) IRF-Kp-2017 uses in addition to the averages, also the minima and maxima values. The IRF-Kp-2017 model has RMS error of 0.55 and linear correlation of 0.92 based on an independent test set with final Kp covering 2 years using ACE Level 2 data. The IRF-Kp-2017-h3 model has RMSE = 0.63 and correlation = 0.89. We also explore the errors when tested on another two-year period with real-time ACE data which gives RMSE = 0.59 for IRF-Kp-2017 and RMSE = 0.73 for IRF-Kp-2017-h3. The errors as function

  9. Electroacoustics modeling of piezoelectric welders for ultrasonic additive manufacturing processes

    NASA Astrophysics Data System (ADS)

    Hehr, Adam; Dapino, Marcelo J.

    2016-04-01

    Ultrasonic additive manufacturing (UAM) is a recent 3D metal printing technology which utilizes ultrasonic vibrations from high power piezoelectric transducers to additively weld similar and dissimilar metal foils. CNC machining is used intermittent of welding to create internal channels, embed temperature sensitive components, sensors, and materials, and for net shaping parts. Structural dynamics of the welder and work piece influence the performance of the welder and part quality. To understand the impact of structural dynamics on UAM, a linear time-invariant model is used to relate system shear force and electric current inputs to the system outputs of welder velocity and voltage. Frequency response measurements are combined with in-situ operating measurements of the welder to identify model parameters and to verify model assumptions. The proposed LTI model can enhance process consistency, performance, and guide the development of improved quality monitoring and control strategies.

  10. Quantum theory of multiple-input-multiple-output Markovian feedback with diffusive measurements

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

    Chia, A.; Wiseman, H. M.

    2011-07-15

    Feedback control engineers have been interested in multiple-input-multiple-output (MIMO) extensions of single-input-single-output (SISO) results of various kinds due to its rich mathematical structure and practical applications. An outstanding problem in quantum feedback control is the extension of the SISO theory of Markovian feedback by Wiseman and Milburn [Phys. Rev. Lett. 70, 548 (1993)] to multiple inputs and multiple outputs. Here we generalize the SISO homodyne-mediated feedback theory to allow for multiple inputs, multiple outputs, and arbitrary diffusive quantum measurements. We thus obtain a MIMO framework which resembles the SISO theory and whose additional mathematical structure is highlighted by the extensivemore » use of vector-operator algebra.« less

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

    USGS Publications Warehouse

    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.

  12. Identification of modal parameters including unmeasured forces and transient effects

    NASA Astrophysics Data System (ADS)

    Cauberghe, B.; Guillaume, P.; Verboven, P.; Parloo, E.

    2003-08-01

    In this paper, a frequency-domain method to estimate modal parameters from short data records with known input (measured) forces and unknown input forces is presented. The method can be used for an experimental modal analysis, an operational modal analysis (output-only data) and the combination of both. A traditional experimental and operational modal analysis in the frequency domain starts respectively, from frequency response functions and spectral density functions. To estimate these functions accurately sufficient data have to be available. The technique developed in this paper estimates the modal parameters directly from the Fourier spectra of the outputs and the known input. Instead of using Hanning windows on these short data records the transient effects are estimated simultaneously with the modal parameters. The method is illustrated, tested and validated by Monte Carlo simulations and experiments. The presented method to process short data sequences leads to unbiased estimates with a small variance in comparison to the more traditional approaches.

  13. Impact of input field characteristics on vibrational femtosecond coherent anti-Stokes Raman scattering thermometry.

    PubMed

    Yang, Chao-Bo; He, Ping; Escofet-Martin, David; Peng, Jiang-Bo; Fan, Rong-Wei; Yu, Xin; Dunn-Rankin, Derek

    2018-01-10

    In this paper, three ultrashort-pulse coherent anti-Stokes Raman scattering (CARS) thermometry approaches are summarized with a theoretical time-domain model. The difference between the approaches can be attributed to variations in the input field characteristics of the time-domain model. That is, all three approaches of ultrashort-pulse (CARS) thermometry can be simulated with the unified model by only changing the input fields features. As a specific example, the hybrid femtosecond/picosecond CARS is assessed for its use in combustion flow diagnostics; thus, the examination of the input field has an impact on thermometry focuses on vibrational hybrid femtosecond/picosecond CARS. Beginning with the general model of ultrashort-pulse CARS, the spectra with different input field parameters are simulated. To analyze the temperature measurement error brought by the input field impacts, the spectra are fitted and compared to fits, with the model neglecting the influence introduced by the input fields. The results demonstrate that, however the input pulses are depicted, temperature errors still would be introduced during an experiment. With proper field characterization, however, the significance of the error can be reduced.

  14. Format( )MEDIC( )Input

    NASA Astrophysics Data System (ADS)

    Foster, K.

    1994-09-01

    This document is a description of a computer program called Format( )MEDIC( )Input. The purpose of this program is to allow the user to quickly reformat wind velocity data in the Model Evaluation Database (MEDb) into a reasonable 'first cut' set of MEDIC input files (MEDIC.nml, StnLoc.Met, and Observ.Met). The user is cautioned that these resulting input files must be reviewed for correctness and completeness. This program will not format MEDb data into a Problem Station Library or Problem Metdata File. A description of how the program reformats the data is provided, along with a description of the required and optional user input and a description of the resulting output files. A description of the MEDb is not provided here but can be found in the RAS Division Model Evaluation Database Description document.

  15. Transformation of Galilean satellite parameters to J2000

    NASA Astrophysics Data System (ADS)

    Lieske, J. H.

    1998-09-01

    The so-called galsat software has the capability of computing Earth-equatorial coordinates of Jupiter's Galilean satellies in an arbitrary reference frame, not just that of B1950. The 50 parameters which define the theory of motion of the Galilean satellites (Lieske 1977, Astron. Astrophys. 56, 333--352) could also be transformed in a manner such that the same galsat computer program can be employed to compute rectangular coordinates with their values being in the J2000 system. One of the input parameters (varepsilon_ {27}) is related to the obliquity of the ecliptic and its value is normally zero in the B1950 frame. If that parameter is changed from 0 to -0.0002771, and if other input parameters are changed in a prescribed manner, then the same galsat software can be employed to produce ephemerides on the J2000 system for any of the ephemerides which employ the galsat parameters, such as those of Arlot (1982), Vasundhara (1994) and Lieske. In this paper we present the parameters whose values must be altered in order for the software to produce coordinates directly in the J2000 system.

  16. Modern control concepts in hydrology. [parameter identification in adaptive stochastic control approach

    NASA Technical Reports Server (NTRS)

    Duong, N.; Winn, C. B.; Johnson, G. R.

    1975-01-01

    Two approaches to an identification problem in hydrology are presented, based upon concepts from modern control and estimation theory. The first approach treats the identification of unknown parameters in a hydrologic system subject to noisy inputs as an adaptive linear stochastic control problem; the second approach alters the model equation to account for the random part in the inputs, and then uses a nonlinear estimation scheme to estimate the unknown parameters. Both approaches use state-space concepts. The identification schemes are sequential and adaptive and can handle either time-invariant or time-dependent parameters. They are used to identify parameters in the Prasad model of rainfall-runoff. The results obtained are encouraging and confirm the results from two previous studies; the first using numerical integration of the model equation along with a trial-and-error procedure, and the second using a quasi-linearization technique. The proposed approaches offer a systematic way of analyzing the rainfall-runoff process when the input data are imbedded in noise.

  17. Non-input analysis for incomplete trapping irreversible tracer with PET.

    PubMed

    Ohya, Tomoyuki; Kikuchi, Tatsuya; Fukumura, Toshimitsu; Zhang, Ming-Rong; Irie, Toshiaki

    2013-07-01

    When using metabolic trapping type tracers, the tracers are not always trapped in the target tissue; i.e., some are completely trapped in the target, but others can be eliminated from the target tissue at a measurable rate. The tracers that can be eliminated are termed 'incomplete trapping irreversible tracers'. These incomplete trapping irreversible tracers may be clinically useful when the tracer β-value, the ratio of the tracer (metabolite) elimination rate to the tracer efflux rate, is under approximately 0.1. In this study, we propose a non-input analysis for incomplete trapping irreversible tracers based on the shape analysis (Shape), a non-input analysis used for irreversible tracers. A Monte Carlo simulation study based on experimental monkey data with two actual PET tracers (a complete trapping irreversible tracer [(11)C]MP4A and an incomplete trapping irreversible tracer [(18)F]FEP-4MA) was performed to examine the effects of the environmental error and the tracer elimination rate on the estimation of the k3-parameter (corresponds to metabolic rate) using Shape (original) and modified Shape (M-Shape) analysis. The simulation results were also compared with the experimental results obtained with the two PET tracers. When the tracer β-value was over 0.03, the M-Shape method was superior to the Shape method for the estimation of the k3-parameter. The simulation results were also in reasonable agreement with the experimental ones. M-Shape can be used as the non-input analysis of incomplete trapping irreversible tracers for PET study. Copyright © 2013 Elsevier Inc. All rights reserved.

  18. Postponed bifurcations of a ring-laser model with a swept parameter and additive colored noise

    NASA Astrophysics Data System (ADS)

    Mannella, R.; Moss, Frank; McClintock, P. V. E.

    1987-03-01

    The paper presents measurements of the time evolution of the statistical densities of both amplitude and field intensity obtained from a colored-noise-driven electronic circuit model of a ring laser, as the bifurcation parameter is swept through its critical values. The time-dependent second moments (intensities) were obtained from the densities. In addition, the individual stochastic trajectories were available from which the distribution of bifurcation times was constructed. For short-correlation-time (quasiwhite) noise the present results are in quantitative agreement with the recent calculations of Bogi, Colombo, Lugiato, and Mandel (1986). New results for long noise correlation times are obtained.

  19. The Absolute Stability Analysis in Fuzzy Control Systems with Parametric Uncertainties and Reference Inputs

    NASA Astrophysics Data System (ADS)

    Wu, Bing-Fei; Ma, Li-Shan; Perng, Jau-Woei

    This study analyzes the absolute stability in P and PD type fuzzy logic control systems with both certain and uncertain linear plants. Stability analysis includes the reference input, actuator gain and interval plant parameters. For certain linear plants, the stability (i.e. the stable equilibriums of error) in P and PD types is analyzed with the Popov or linearization methods under various reference inputs and actuator gains. The steady state errors of fuzzy control systems are also addressed in the parameter plane. The parametric robust Popov criterion for parametric absolute stability based on Lur'e systems is also applied to the stability analysis of P type fuzzy control systems with uncertain plants. The PD type fuzzy logic controller in our approach is a single-input fuzzy logic controller and is transformed into the P type for analysis. In our work, the absolute stability analysis of fuzzy control systems is given with respect to a non-zero reference input and an uncertain linear plant with the parametric robust Popov criterion unlike previous works. Moreover, a fuzzy current controlled RC circuit is designed with PSPICE models. Both numerical and PSPICE simulations are provided to verify the analytical results. Furthermore, the oscillation mechanism in fuzzy control systems is specified with various equilibrium points of view in the simulation example. Finally, the comparisons are also given to show the effectiveness of the analysis method.

  20. Transfer of the nationwide Czech soil survey data to a foreign soil classification - generating input parameters for a process-based soil erosion modelling approach

    NASA Astrophysics Data System (ADS)

    Beitlerová, Hana; Hieke, Falk; Žížala, Daniel; Kapička, Jiří; Keiser, Andreas; Schmidt, Jürgen; Schindewolf, Marcus

    2017-04-01

    Process-based erosion modelling is a developing and adequate tool to assess, simulate and understand the complex mechanisms of soil loss due to surface runoff. While the current state of available models includes powerful approaches, a major drawback is given by complex parametrization. A major input parameter for the physically based soil loss and deposition model EROSION 3D is represented by soil texture. However, as the model has been developed in Germany it is dependent on the German soil classification. To exploit data generated during a massive nationwide soil survey campaign taking place in the 1960s across the entire Czech Republic, a transfer from the Czech to the German or at least international (e.g. WRB) system is mandatory. During the survey the internal differentiation of grain sizes was realized in a two fractions approach, separating texture into solely above and below 0.01 mm rather than into clayey, silty and sandy textures. Consequently, the Czech system applies a classification of seven different textures based on the respective percentage of large and small particles, while in Germany 31 groups are essential. The followed approach of matching Czech soil survey data to the German system focusses on semi-logarithmic interpolation of the cumulative soil texture curve additionally on a regression equation based on a recent database of 128 soil pits. Furthermore, for each of the seven Czech texture classes a group of typically suitable classes of the German system was derived. A GIS-based spatial analysis to test approaches of interpolation the soil texture was carried out. First results show promising matches and pave the way to a Czech model application of EROSION 3D.

  1. Simplifying BRDF input data for optical signature modeling

    NASA Astrophysics Data System (ADS)

    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.

  2. Vastly accelerated linear least-squares fitting with numerical optimization for dual-input delay-compensated quantitative liver perfusion mapping.

    PubMed

    Jafari, Ramin; Chhabra, Shalini; Prince, Martin R; Wang, Yi; Spincemaille, Pascal

    2018-04-01

    To propose an efficient algorithm to perform dual input compartment modeling for generating perfusion maps in the liver. We implemented whole field-of-view linear least squares (LLS) to fit a delay-compensated dual-input single-compartment model to very high temporal resolution (four frames per second) contrast-enhanced 3D liver data, to calculate kinetic parameter maps. Using simulated data and experimental data in healthy subjects and patients, whole-field LLS was compared with the conventional voxel-wise nonlinear least-squares (NLLS) approach in terms of accuracy, performance, and computation time. Simulations showed good agreement between LLS and NLLS for a range of kinetic parameters. The whole-field LLS method allowed generating liver perfusion maps approximately 160-fold faster than voxel-wise NLLS, while obtaining similar perfusion parameters. Delay-compensated dual-input liver perfusion analysis using whole-field LLS allows generating perfusion maps with a considerable speedup compared with conventional voxel-wise NLLS fitting. Magn Reson Med 79:2415-2421, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

  3. Sensitivity of Rainfall-runoff Model Parametrization and Performance to Potential Evaporation Inputs

    NASA Astrophysics Data System (ADS)

    Jayathilake, D. I.; Smith, T. J.

    2017-12-01

    Many watersheds of interest are confronted with insufficient data and poor process understanding. Therefore, understanding the relative importance of input data types and the impact of different qualities on model performance, parameterization, and fidelity is critically important to improving hydrologic models. In this paper, the change in model parameterization and performance are explored with respect to four different potential evapotranspiration (PET) products of varying quality. For each PET product, two widely used, conceptual rainfall-runoff models are calibrated with multiple objective functions to a sample of 20 basins included in the MOPEX data set and analyzed to understand how model behavior varied. Model results are further analyzed by classifying catchments as energy- or water-limited using the Budyko framework. The results demonstrated that model fit was largely unaffected by the quality of the PET inputs. However, model parameterizations were clearly sensitive to PET inputs, as their production parameters adjusted to counterbalance input errors. Despite this, changes in model robustness were not observed for either model across the four PET products, although robustness was affected by model structure.

  4. Developing a Novel Parameter Estimation Method for Agent-Based Model in Immune System Simulation under the Framework of History Matching: A Case Study on Influenza A Virus Infection

    PubMed Central

    Li, Tingting; Cheng, Zhengguo; Zhang, Le

    2017-01-01

    Since they can provide a natural and flexible description of nonlinear dynamic behavior of complex system, Agent-based models (ABM) have been commonly used for immune system simulation. However, it is crucial for ABM to obtain an appropriate estimation for the key parameters of the model by incorporating experimental data. In this paper, a systematic procedure for immune system simulation by integrating the ABM and regression method under the framework of history matching is developed. A novel parameter estimation method by incorporating the experiment data for the simulator ABM during the procedure is proposed. First, we employ ABM as simulator to simulate the immune system. Then, the dimension-reduced type generalized additive model (GAM) is employed to train a statistical regression model by using the input and output data of ABM and play a role as an emulator during history matching. Next, we reduce the input space of parameters by introducing an implausible measure to discard the implausible input values. At last, the estimation of model parameters is obtained using the particle swarm optimization algorithm (PSO) by fitting the experiment data among the non-implausible input values. The real Influeza A Virus (IAV) data set is employed to demonstrate the performance of our proposed method, and the results show that the proposed method not only has good fitting and predicting accuracy, but it also owns favorable computational efficiency. PMID:29194393

  5. Developing a Novel Parameter Estimation Method for Agent-Based Model in Immune System Simulation under the Framework of History Matching: A Case Study on Influenza A Virus Infection.

    PubMed

    Li, Tingting; Cheng, Zhengguo; Zhang, Le

    2017-12-01

    Since they can provide a natural and flexible description of nonlinear dynamic behavior of complex system, Agent-based models (ABM) have been commonly used for immune system simulation. However, it is crucial for ABM to obtain an appropriate estimation for the key parameters of the model by incorporating experimental data. In this paper, a systematic procedure for immune system simulation by integrating the ABM and regression method under the framework of history matching is developed. A novel parameter estimation method by incorporating the experiment data for the simulator ABM during the procedure is proposed. First, we employ ABM as simulator to simulate the immune system. Then, the dimension-reduced type generalized additive model (GAM) is employed to train a statistical regression model by using the input and output data of ABM and play a role as an emulator during history matching. Next, we reduce the input space of parameters by introducing an implausible measure to discard the implausible input values. At last, the estimation of model parameters is obtained using the particle swarm optimization algorithm (PSO) by fitting the experiment data among the non-implausible input values. The real Influeza A Virus (IAV) data set is employed to demonstrate the performance of our proposed method, and the results show that the proposed method not only has good fitting and predicting accuracy, but it also owns favorable computational efficiency.

  6. Toolpath Strategy and Optimum Combination of Machining Parameter during Pocket Mill Process of Plastic Mold Steels Material

    NASA Astrophysics Data System (ADS)

    Wibowo, Y. T.; Baskoro, S. Y.; Manurung, V. A. T.

    2018-02-01

    Plastic based products spread all over the world in many aspects of life. The ability to substitute other materials is getting stronger and wider. The use of plastic materials increases and become unavoidable. Plastic based mass production requires injection process as well Mold. The milling process of plastic mold steel material was done using HSS End Mill cutting tool that is widely used in a small and medium enterprise for the reason of its ability to be re sharpened and relatively inexpensive. Study on the effect of the geometry tool states that it has an important effect on the quality improvement. Cutting speed, feed rate, depth of cut and radii are input parameters beside to the tool path strategy. This paper aims to investigate input parameter and cutting tools behaviors within some different tool path strategy. For the reason of experiments efficiency Taguchi method and ANOVA were used. Response studied is surface roughness and cutting behaviors. By achieving the expected quality, no more additional process is required. Finally, the optimal combination of machining parameters will deliver the expected roughness and of course totally reduced cutting time. However actually, SMEs do not optimally use this data for cost reduction.

  7. SDR input power estimation algorithms

    NASA Astrophysics Data System (ADS)

    Briones, J. C.; Nappier, J. M.

    The General Dynamics (GD) S-Band software defined radio (SDR) in the Space Communications and Navigation (SCAN) Testbed on the International Space Station (ISS) provides experimenters an opportunity to develop and demonstrate experimental waveforms in space. The SDR has an analog and a digital automatic gain control (AGC) and the response of the AGCs to changes in SDR input power and temperature was characterized prior to the launch and installation of the SCAN Testbed on the ISS. The AGCs were used to estimate the SDR input power and SNR of the received signal and the characterization results showed a nonlinear response to SDR input power and temperature. In order to estimate the SDR input from the AGCs, three algorithms were developed and implemented on the ground software of the SCAN Testbed. The algorithms include a linear straight line estimator, which used the digital AGC and the temperature to estimate the SDR input power over a narrower section of the SDR input power range. There is a linear adaptive filter algorithm that uses both AGCs and the temperature to estimate the SDR input power over a wide input power range. Finally, an algorithm that uses neural networks was designed to estimate the input power over a wide range. This paper describes the algorithms in detail and their associated performance in estimating the SDR input power.

  8. SDR Input Power Estimation Algorithms

    NASA Technical Reports Server (NTRS)

    Nappier, Jennifer M.; Briones, Janette C.

    2013-01-01

    The General Dynamics (GD) S-Band software defined radio (SDR) in the Space Communications and Navigation (SCAN) Testbed on the International Space Station (ISS) provides experimenters an opportunity to develop and demonstrate experimental waveforms in space. The SDR has an analog and a digital automatic gain control (AGC) and the response of the AGCs to changes in SDR input power and temperature was characterized prior to the launch and installation of the SCAN Testbed on the ISS. The AGCs were used to estimate the SDR input power and SNR of the received signal and the characterization results showed a nonlinear response to SDR input power and temperature. In order to estimate the SDR input from the AGCs, three algorithms were developed and implemented on the ground software of the SCAN Testbed. The algorithms include a linear straight line estimator, which used the digital AGC and the temperature to estimate the SDR input power over a narrower section of the SDR input power range. There is a linear adaptive filter algorithm that uses both AGCs and the temperature to estimate the SDR input power over a wide input power range. Finally, an algorithm that uses neural networks was designed to estimate the input power over a wide range. This paper describes the algorithms in detail and their associated performance in estimating the SDR input power.

  9. Organic Matter and Water Addition Enhance Soil Respiration in an Arid Region

    PubMed Central

    Lai, Liming; Wang, Jianjian; Tian, Yuan; Zhao, Xuechun; Jiang, Lianhe; Chen, Xi; Gao, Yong; Wang, Shaoming; Zheng, Yuanrun

    2013-01-01

    Climate change is generally predicted to increase net primary production, which could lead to additional C input to soil. In arid central Asia, precipitation has increased and is predicted to increase further. To assess the combined effects of these changes on soil CO2 efflux in arid land, a two factorial manipulation experiment in the shrubland of an arid region in northwest China was conducted. The experiment used a nested design with fresh organic matter and water as the two controlled parameters. It was found that both fresh organic matter and water enhanced soil respiration, and there was a synergistic effect of these two treatments on soil respiration increase. Water addition not only enhanced soil C emission, but also regulated soil C sequestration by fresh organic matter addition. The results indicated that the soil CO2 flux of the shrubland is likely to increase with climate change, and precipitation played a dominant role in regulating soil C balance in the shrubland of an arid region. PMID:24204907

  10. Optimizing microwave photodetection: input-output theory

    NASA Astrophysics Data System (ADS)

    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.

  11. Seasonal variation in coat characteristics, tick loads, cortisol levels, some physiological parameters and temperature humidity index on Nguni cows raised in low- and high-input farms

    NASA Astrophysics Data System (ADS)

    Katiyatiya, C. L. F.; Muchenje, V.; Mushunje, A.

    2015-06-01

    Seasonal variations in hair length, tick loads, cortisol levels, haematological parameters (HP) and temperature humidity index (THI) in Nguni cows of different colours raised in two low-input farms, and a commercial stud was determined. The sites were chosen based on their production systems, climatic characteristics and geographical locations. Zazulwana and Komga are low-input, humid-coastal areas, while Honeydale is a high-input, dry-inland Nguni stud farm. A total of 103 cows, grouped according to parity, location and coat colour, were used in the study. The effects of location, coat colour, hair length and season were used to determine tick loads on different body parts, cortisol levels and HP in blood from Nguni cows. Highest tick loads were recorded under the tail and the lowest on the head of each of the animals ( P < 0.05). Zazulwana cows recorded the highest tick loads under the tails of all the cows used in the study from the three farms ( P < 0.05). High tick loads were recorded for cows with long hairs. Hair lengths were longest during the winter season in the coastal areas of Zazulwana and Honeydale ( P < 0.05). White and brown-white patched cows had significantly longer ( P < 0.05) hair strands than those having a combination of red, black and white colour. Cortisol and THI were significantly lower ( P < 0.05) in summer season. Red blood cells, haematoglobin, haematocrit, mean cell volumes, white blood cells, neutrophils, lymphocytes, eosinophils and basophils were significantly different ( P < 0.05) as some associated with age across all seasons and correlated to THI. It was concluded that the location, coat colour and season had effects on hair length, cortisol levels, THI, HP and tick loads on different body parts and heat stress in Nguni cows.

  12. Mathematical Model for a Simplified Calculation of the Input Momentum Coefficient for AFC Purposes

    NASA Astrophysics Data System (ADS)

    Hirsch, Damian; Gharib, Morteza

    2016-11-01

    Active Flow Control (AFC) is an emerging technology which aims at enhancing the aerodynamic performance of flight vehicles (i.e., to save fuel). A viable AFC system must consider the limited resources available on a plane for attaining performance goals. A higher performance goal (i.e., airplane incremental lift) demands a higher input fluidic requirement (i.e., mass flow rate). Therefore, the key requirement for a successful and practical design is to minimize power input while maximizing performance to achieve design targets. One of the most used design parameters is the input momentum coefficient Cμ. The difficulty associated with Cμ lies in obtaining the parameters for its calculation. In the literature two main approaches can be found, which both have their own disadvantages (assumptions, difficult measurements). A new, much simpler calculation approach will be presented that is based on a mathematical model that can be applied to most jet designs (i.e., steady or sweeping jets). The model-incorporated assumptions will be justified theoretically as well as experimentally. Furthermore, the model's capabilities are exploited to give new insight to the AFC technology and its physical limitations. Supported by Boeing.

  13. Biological 2-Input Decoder Circuit in Human Cells

    PubMed Central

    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

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

    PubMed

    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.

  15. Input-output mapping reconstruction of spike trains at dorsal horn evoked by manual acupuncture

    NASA Astrophysics Data System (ADS)

    Wei, Xile; Shi, Dingtian; Yu, Haitao; Deng, Bin; Lu, Meili; Han, Chunxiao; Wang, Jiang

    2016-12-01

    In this study, a generalized linear model (GLM) is used to reconstruct mapping from acupuncture stimulation to spike trains driven by action potential data. The electrical signals are recorded in spinal dorsal horn after manual acupuncture (MA) manipulations with different frequencies being taken at the “Zusanli” point of experiment rats. Maximum-likelihood method is adopted to estimate the parameters of GLM and the quantified value of assumed model input. Through validating the accuracy of firings generated from the established GLM, it is found that the input-output mapping of spike trains evoked by acupuncture can be successfully reconstructed for different frequencies. Furthermore, via comparing the performance of several GLMs based on distinct inputs, it suggests that input with the form of half-sine with noise can well describe the generator potential induced by acupuncture mechanical action. Particularly, the comparison of reproducing the experiment spikes for five selected inputs is in accordance with the phenomenon found in Hudgkin-Huxley (H-H) model simulation, which indicates the mapping from half-sine with noise input to experiment spikes meets the real encoding scheme to some extent. These studies provide us a new insight into coding processes and information transfer of acupuncture.

  16. Gaussian-input Gaussian mixture model for representing density maps and atomic models.

    PubMed

    Kawabata, Takeshi

    2018-07-01

    A new Gaussian mixture model (GMM) has been developed for better representations of both atomic models and electron microscopy 3D density maps. The standard GMM algorithm employs an EM algorithm to determine the parameters. It accepted a set of 3D points with weights, corresponding to voxel or atomic centers. Although the standard algorithm worked reasonably well; however, it had three problems. First, it ignored the size (voxel width or atomic radius) of the input, and thus it could lead to a GMM with a smaller spread than the input. Second, the algorithm had a singularity problem, as it sometimes stopped the iterative procedure due to a Gaussian function with almost zero variance. Third, a map with a large number of voxels required a long computation time for conversion to a GMM. To solve these problems, we have introduced a Gaussian-input GMM algorithm, which considers the input atoms or voxels as a set of Gaussian functions. The standard EM algorithm of GMM was extended to optimize the new GMM. The new GMM has identical radius of gyration to the input, and does not suddenly stop due to the singularity problem. For fast computation, we have introduced a down-sampled Gaussian functions (DSG) by merging neighboring voxels into an anisotropic Gaussian function. It provides a GMM with thousands of Gaussian functions in a short computation time. We also have introduced a DSG-input GMM: the Gaussian-input GMM with the DSG as the input. This new algorithm is much faster than the standard algorithm. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

  17. Branch Input Resistance and Steady Attenuation for Input to One Branch of a Dendritic Neuron Model

    PubMed Central

    Rall, Wilfrid; Rinzel, John

    1973-01-01

    Mathematical solutions and numerical illustrations are presented for the steady-state distribution of membrane potential in an extensively branched neuron model, when steady electric current is injected into only one dendritic branch. Explicit expressions are obtained for input resistance at the branch input site and for voltage attenuation from the input site to the soma; expressions for AC steady-state input impedance and attenuation are also presented. The theoretical model assumes passive membrane properties and the equivalent cylinder constraint on branch diameters. Numerical examples illustrate how branch input resistance and steady attenuation depend upon the following: the number of dendritic trees, the orders of dendritic branching, the electrotonic length of the dendritic trees, the location of the dendritic input site, and the input resistance at the soma. The application to cat spinal motoneurons, and to other neuron types, is discussed. The effect of a large dendritic input resistance upon the amount of local membrane depolarization at the synaptic site, and upon the amount of depolarization reaching the soma, is illustrated and discussed; simple proportionality with input resistance does not hold, in general. Also, branch input resistance is shown to exceed the input resistance at the soma by an amount that is always less than the sum of core resistances along the path from the input site to the soma. PMID:4715583

  18. Input Forces Estimation for Nonlinear Systems by Applying a Square-Root Cubature Kalman Filter.

    PubMed

    Song, Xuegang; Zhang, Yuexin; Liang, Dakai

    2017-10-10

    This work presents a novel inverse algorithm to estimate time-varying input forces in nonlinear beam systems. With the system parameters determined, the input forces can be estimated in real-time from dynamic responses, which can be used for structural health monitoring. In the process of input forces estimation, the Runge-Kutta fourth-order algorithm was employed to discretize the state equations; a square-root cubature Kalman filter (SRCKF) was employed to suppress white noise; the residual innovation sequences, a priori state estimate, gain matrix, and innovation covariance generated by SRCKF were employed to estimate the magnitude and location of input forces by using a nonlinear estimator. The nonlinear estimator was based on the least squares method. Numerical simulations of a large deflection beam and an experiment of a linear beam constrained by a nonlinear spring were employed. The results demonstrated accuracy of the nonlinear algorithm.

  19. Dependence of quantitative accuracy of CT perfusion imaging on system parameters

    NASA Astrophysics Data System (ADS)

    Li, Ke; Chen, Guang-Hong

    2017-03-01

    Deconvolution is a popular method to calculate parametric perfusion parameters from four dimensional CT perfusion (CTP) source images. During the deconvolution process, the four dimensional space is squeezed into three-dimensional space by removing the temporal dimension, and a prior knowledge is often used to suppress noise associated with the process. These additional complexities confound the understanding about deconvolution-based CTP imaging system and how its quantitative accuracy depends on parameters and sub-operations involved in the image formation process. Meanwhile, there has been a strong clinical need in answering this question, as physicians often rely heavily on the quantitative values of perfusion parameters to make diagnostic decisions, particularly during an emergent clinical situation (e.g. diagnosis of acute ischemic stroke). The purpose of this work was to develop a theoretical framework that quantitatively relates the quantification accuracy of parametric perfusion parameters with CTP acquisition and post-processing parameters. This goal was achieved with the help of a cascaded systems analysis for deconvolution-based CTP imaging systems. Based on the cascaded systems analysis, the quantitative relationship between regularization strength, source image noise, arterial input function, and the quantification accuracy of perfusion parameters was established. The theory could potentially be used to guide developments of CTP imaging technology for better quantification accuracy and lower radiation dose.

  20. Imposition of physical parameters in dissipative particle dynamics

    NASA Astrophysics Data System (ADS)

    Mai-Duy, N.; Phan-Thien, N.; Tran-Cong, T.

    2017-12-01

    In the mesoscale simulations by the dissipative particle dynamics (DPD), the motion of a fluid is modelled by a set of particles interacting in a pairwise manner, and it has been shown to be governed by the Navier-Stokes equation, with its physical properties, such as viscosity, Schmidt number, isothermal compressibility, relaxation and inertia time scales, in fact its whole rheology resulted from the choice of the DPD model parameters. In this work, we will explore the response of a DPD fluid with respect to its parameter space, where the model input parameters can be chosen in advance so that (i) the ratio between the relaxation and inertia time scales is fixed; (ii) the isothermal compressibility of water at room temperature is enforced; and (iii) the viscosity and Schmidt number can be specified as inputs. These impositions are possible with some extra degrees of freedom in the weighting functions for the conservative and dissipative forces. Numerical experiments show an improvement in the solution quality over conventional DPD parameters/weighting functions, particularly for the number density distribution and computed stresses.

  1. Direct quantification of long-term rock nitrogen inputs to temperate forest ecosystems.

    PubMed

    Morford, Scott L; Houlton, Benjamin Z; Dahlgren, Randy A

    2016-01-01

    Sedimentary and metasedimentary rocks contain large reservoirs of fixed nitrogen (N), but questions remain over the importance of rock N weathering inputs in terrestrial ecosystems. Here we provide direct evidence for rock N weathering (i.e., loss of N from rock) in three temperate forest sites residing on a N-rich parent material (820-1050 mg N kg(-1); mica schist) in the Klamath Mountains (northern California and southern Oregon), USA. Our method combines a mass balance model of element addition/ depletion with a procedure for quantifying fixed N in rock minerals, enabling quantification of rock N inputs to bioavailable reservoirs in soil and regolith. Across all sites, -37% to 48% of the initial bedrock N content has undergone long-term weathering in the soil. Combined with regional denudation estimates (sum of physical + chemical erosion), these weathering fractions translate to 1.6-10.7 kg x ha(-1) x yr(-1) of rock N input to these forest ecosystems. These N input fluxes are substantial in light of estimates for atmospheric sources in these sites (4.5-7.0 kg x ha(-1) x yr(-1)). In addition, N depletion from rock minerals was greater than sodium, suggesting active biologically mediated weathering of growth-limiting nutrients compared to nonessential elements. These results point to regional tectonics, biologically mediated weathering effects, and rock N chemistry in shaping the magnitude of rock N inputs to the forest ecosystems examined.

  2. Development of advanced techniques for rotorcraft state estimation and parameter identification

    NASA Technical Reports Server (NTRS)

    Hall, W. E., Jr.; Bohn, J. G.; Vincent, J. H.

    1980-01-01

    An integrated methodology for rotorcraft system identification consists of rotorcraft mathematical modeling, three distinct data processing steps, and a technique for designing inputs to improve the identifiability of the data. These elements are as follows: (1) a Kalman filter smoother algorithm which estimates states and sensor errors from error corrupted data. Gust time histories and statistics may also be estimated; (2) a model structure estimation algorithm for isolating a model which adequately explains the data; (3) a maximum likelihood algorithm for estimating the parameters and estimates for the variance of these estimates; and (4) an input design algorithm, based on a maximum likelihood approach, which provides inputs to improve the accuracy of parameter estimates. Each step is discussed with examples to both flight and simulated data cases.

  3. Three-input majority logic gate and multiple input logic circuit based on DNA strand displacement.

    PubMed

    Li, Wei; Yang, Yang; Yan, Hao; Liu, Yan

    2013-06-12

    In biomolecular programming, the properties of biomolecules such as proteins and nucleic acids are harnessed for computational purposes. The field has gained considerable attention due to the possibility of exploiting the massive parallelism that is inherent in natural systems to solve computational problems. DNA has already been used to build complex molecular circuits, where the basic building blocks are logic gates that produce single outputs from one or more logical inputs. We designed and experimentally realized a three-input majority gate based on DNA strand displacement. One of the key features of a three-input majority gate is that the three inputs have equal priority, and the output will be true if any of the two inputs are true. Our design consists of a central, circular DNA strand with three unique domains between which are identical joint sequences. Before inputs are introduced to the system, each domain and half of each joint is protected by one complementary ssDNA that displays a toehold for subsequent displacement by the corresponding input. With this design the relationship between any two domains is analogous to the relationship between inputs in a majority gate. Displacing two or more of the protection strands will expose at least one complete joint and return a true output; displacing none or only one of the protection strands will not expose a complete joint and will return a false output. Further, we designed and realized a complex five-input logic gate based on the majority gate described here. By controlling two of the five inputs the complex gate can realize every combination of OR and AND gates of the other three inputs.

  4. Transient analysis of intercalation electrodes for parameter estimation

    NASA Astrophysics Data System (ADS)

    Devan, Sheba

    An essential part of integrating batteries as power sources in any application, be it a large scale automotive application or a small scale portable application, is an efficient Battery Management System (BMS). The combination of a battery with the microprocessor based BMS (called "smart battery") helps prolong the life of the battery by operating in the optimal regime and provides accurate information regarding the battery to the end user. The main purposes of BMS are cell protection, monitoring and control, and communication between different components. These purposes are fulfilled by tracking the change in the parameters of the intercalation electrodes in the batteries. Consequently, the functions of the BMS should be prompt, which requires the methodology of extracting the parameters to be efficient in time. The traditional transient techniques applied so far may not be suitable due to reasons such as the inability to apply these techniques when the battery is under operation, long experimental time, etc. The primary aim of this research work is to design a fast, accurate and reliable technique that can be used to extract parameter values of the intercalation electrodes. A methodology based on analysis of the short time response to a sinusoidal input perturbation, in the time domain is demonstrated using a porous electrode model for an intercalation electrode. It is shown that the parameters associated with the interfacial processes occurring in the electrode can be determined rapidly, within a few milliseconds, by measuring the response in the transient region. The short time analysis in the time domain is then extended to a single particle model that involves bulk diffusion in the solid phase in addition to interfacial processes. A systematic procedure for sequential parameter estimation using sensitivity analysis is described. Further, the short time response and the input perturbation are transformed into the frequency domain using Fast Fourier Transform

  5. PAR -- Interface to the ADAM Parameter System

    NASA Astrophysics Data System (ADS)

    Currie, Malcolm J.; Chipperfield, Alan J.

    PAR is a library of Fortran subroutines that provides convenient mechanisms for applications to exchange information with the outside world, through input-output channels called parameters. Parameters enable a user to control an application's behaviour. PAR supports numeric, character, and logical parameters, and is currently implemented only on top of the ADAM parameter system. The PAR library permits parameter values to be obtained, without or with a variety of constraints. Results may be put into parameters to be passed onto other applications. Other facilities include setting a prompt string, and suggested defaults. This document also introduces a preliminary C interface for the PAR library -- this may be subject to change in the light of experience.

  6. The IVS data input to ITRF2014

    NASA Astrophysics Data System (ADS)

    Nothnagel, Axel; Alef, Walter; Amagai, Jun; Andersen, Per Helge; Andreeva, Tatiana; Artz, Thomas; Bachmann, Sabine; Barache, Christophe; Baudry, Alain; Bauernfeind, Erhard; Baver, Karen; Beaudoin, Christopher; Behrend, Dirk; Bellanger, Antoine; Berdnikov, Anton; Bergman, Per; Bernhart, Simone; Bertarini, Alessandra; Bianco, Giuseppe; Bielmaier, Ewald; Boboltz, David; Böhm, Johannes; Böhm, Sigrid; Boer, Armin; Bolotin, Sergei; Bougeard, Mireille; Bourda, Geraldine; Buttaccio, Salvo; Cannizzaro, Letizia; Cappallo, Roger; Carlson, Brent; Carter, Merri Sue; Charlot, Patrick; Chen, Chenyu; Chen, Maozheng; Cho, Jungho; Clark, Thomas; Collioud, Arnaud; Colomer, Francisco; Colucci, Giuseppe; Combrinck, Ludwig; Conway, John; Corey, Brian; Curtis, Ronald; Dassing, Reiner; Davis, Maria; de-Vicente, Pablo; De Witt, Aletha; Diakov, Alexey; Dickey, John; Diegel, Irv; Doi, Koichiro; Drewes, Hermann; Dube, Maurice; Elgered, Gunnar; Engelhardt, Gerald; Evangelista, Mark; Fan, Qingyuan; Fedotov, Leonid; Fey, Alan; Figueroa, Ricardo; Fukuzaki, Yoshihiro; Gambis, Daniel; Garcia-Espada, Susana; Gaume, Ralph; Gaylard, Michael; Geiger, Nicole; Gipson, John; Gomez, Frank; Gomez-Gonzalez, Jesus; Gordon, David; Govind, Ramesh; Gubanov, Vadim; Gulyaev, Sergei; Haas, Ruediger; Hall, David; Halsig, Sebastian; Hammargren, Roger; Hase, Hayo; Heinkelmann, Robert; Helldner, Leif; Herrera, Cristian; Himwich, Ed; Hobiger, Thomas; Holst, Christoph; Hong, Xiaoyu; Honma, Mareki; Huang, Xinyong; Hugentobler, Urs; Ichikawa, Ryuichi; Iddink, Andreas; Ihde, Johannes; Ilijin, Gennadiy; Ipatov, Alexander; Ipatova, Irina; Ishihara, Misao; Ivanov, D. V.; Jacobs, Chris; Jike, Takaaki; Johansson, Karl-Ake; Johnson, Heidi; Johnston, Kenneth; Ju, Hyunhee; Karasawa, Masao; Kaufmann, Pierre; Kawabata, Ryoji; Kawaguchi, Noriyuki; Kawai, Eiji; Kaydanovsky, Michael; Kharinov, Mikhail; Kobayashi, Hideyuki; Kokado, Kensuke; Kondo, Tetsuro; Korkin, Edward; Koyama, Yasuhiro; Krasna, Hana; Kronschnabl, Gerhard; Kurdubov, Sergey; Kurihara, Shinobu; Kuroda, Jiro; Kwak, Younghee; La Porta, Laura; Labelle, Ruth; Lamb, Doug; Lambert, Sébastien; Langkaas, Line; Lanotte, Roberto; Lavrov, Alexey; Le Bail, Karine; Leek, Judith; Li, Bing; Li, Huihua; Li, Jinling; Liang, Shiguang; Lindqvist, Michael; Liu, Xiang; Loesler, Michael; Long, Jim; Lonsdale, Colin; Lovell, Jim; Lowe, Stephen; Lucena, Antonio; Luzum, Brian; Ma, Chopo; Ma, Jun; Maccaferri, Giuseppe; Machida, Morito; MacMillan, Dan; Madzak, Matthias; Malkin, Zinovy; Manabe, Seiji; Mantovani, Franco; Mardyshkin, Vyacheslav; Marshalov, Dmitry; Mathiassen, Geir; Matsuzaka, Shigeru; McCarthy, Dennis; Melnikov, Alexey; Michailov, Andrey; Miller, Natalia; Mitchell, Donald; Mora-Diaz, Julian Andres; Mueskens, Arno; Mukai, Yasuko; Nanni, Mauro; Natusch, Tim; Negusini, Monia; Neidhardt, Alexander; Nickola, Marisa; Nicolson, George; Niell, Arthur; Nikitin, Pavel; Nilsson, Tobias; Ning, Tong; Nishikawa, Takashi; Noll, Carey; Nozawa, Kentarou; Ogaja, Clement; Oh, Hongjong; Olofsson, Hans; Opseth, Per Erik; Orfei, Sandro; Pacione, Rosa; Pazamickas, Katherine; Petrachenko, William; Pettersson, Lars; Pino, Pedro; Plank, Lucia; Ploetz, Christian; Poirier, Michael; Poutanen, Markku; Qian, Zhihan; Quick, Jonathan; Rahimov, Ismail; Redmond, Jay; Reid, Brett; Reynolds, John; Richter, Bernd; Rioja, Maria; Romero-Wolf, Andres; Ruszczyk, Chester; Salnikov, Alexander; Sarti, Pierguido; Schatz, Raimund; Scherneck, Hans-Georg; Schiavone, Francesco; Schreiber, Ulrich; Schuh, Harald; Schwarz, Walter; Sciarretta, Cecilia; Searle, Anthony; Sekido, Mamoru; Seitz, Manuela; Shao, Minghui; Shibuya, Kazuo; Shu, Fengchun; Sieber, Moritz; Skjaeveland, Asmund; Skurikhina, Elena; Smolentsev, Sergey; Smythe, Dan; Sousa, Don; Sovers, Ojars; Stanford, Laura; Stanghellini, Carlo; Steppe, Alan; Strand, Rich; Sun, Jing; Surkis, Igor; Takashima, Kazuhiro; Takefuji, Kazuhiro; Takiguchi, Hiroshi; Tamura, Yoshiaki; Tanabe, Tadashi; Tanir, Emine; Tao, An; Tateyama, Claudio; Teke, Kamil; Thomas, Cynthia; Thorandt, Volkmar; Thornton, Bruce; Tierno Ros, Claudia; Titov, Oleg; Titus, Mike; Tomasi, Paolo; Tornatore, Vincenza; Trigilio, Corrado; Trofimov, Dmitriy; Tsutsumi, Masanori; Tuccari, Gino; Tzioumis, Tasso; Ujihara, Hideki; Ullrich, Dieter; Uunila, Minttu; Venturi, Tiziana; Vespe, Francesco; Vityazev, Veniamin; Volvach, Alexandr; Vytnov, Alexander; Wang, Guangli; Wang, Jinqing; Wang, Lingling; Wang, Na; Wang, Shiqiang; Wei, Wenren; Weston, Stuart; Whitney, Alan; Wojdziak, Reiner; Yatskiv, Yaroslav; Yang, Wenjun; Ye, Shuhua; Yi, Sangoh; Yusup, Aili; Zapata, Octavio; Zeitlhoefler, Reinhard; Zhang, Hua; Zhang, Ming; Zhang, Xiuzhong; Zhao, Rongbing; Zheng, Weimin; Zhou, Ruixian; Zubko, Nataliya

    2015-01-01

    Very Long Baseline Interferometry (VLBI) is a primary space-geodetic technique for determining precise coordinates on the Earth, for monitoring the variable Earth rotation and orientation with highest precision, and for deriving many other parameters of the Earth system. The International VLBI Service for Geodesy and Astrometry (IVS, http://ivscc.gsfc.nasa.gov/) is a service of the International Association of Geodesy (IAG) and the International Astronomical Union (IAU). The datasets published here are the results of individual Very Long Baseline Interferometry (VLBI) sessions in the form of normal equations in SINEX 2.0 format (http://www.iers.org/IERS/EN/Organization/AnalysisCoordinator/SinexFormat/sinex.html, the SINEX 2.0 description is attached as pdf) provided by IVS as the input for the next release of the International Terrestrial Reference System (ITRF): ITRF2014. This is a new version of the ITRF2008 release (Bockmann et al., 2009). For each session/ file, the normal equation systems contain elements for the coordinate components of all stations having participated in the respective session as well as for the Earth orientation parameters (x-pole, y-pole, UT1 and its time derivatives plus offset to the IAU2006 precession-nutation components dX, dY (https://www.iau.org/static/resolutions/IAU2006_Resol1.pdf). The terrestrial part is free of datum. The data sets are the result of a weighted combination of the input of several IVS Analysis Centers. The IVS contribution for ITRF2014 is described in Bachmann et al (2015), Schuh and Behrend (2012) provide a general overview on the VLBI method, details on the internal data handling can be found at Behrend (2013).

  7. Machine learning classifiers for glaucoma diagnosis based on classification of retinal nerve fibre layer thickness parameters measured by Stratus OCT.

    PubMed

    Bizios, Dimitrios; Heijl, Anders; Hougaard, Jesper Leth; Bengtsson, Boel

    2010-02-01

    To compare the performance of two machine learning classifiers (MLCs), artificial neural networks (ANNs) and support vector machines (SVMs), with input based on retinal nerve fibre layer thickness (RNFLT) measurements by optical coherence tomography (OCT), on the diagnosis of glaucoma, and to assess the effects of different input parameters. We analysed Stratus OCT data from 90 healthy persons and 62 glaucoma patients. Performance of MLCs was compared using conventional OCT RNFLT parameters plus novel parameters such as minimum RNFLT values, 10th and 90th percentiles of measured RNFLT, and transformations of A-scan measurements. For each input parameter and MLC, the area under the receiver operating characteristic curve (AROC) was calculated. There were no statistically significant differences between ANNs and SVMs. The best AROCs for both ANN (0.982, 95%CI: 0.966-0.999) and SVM (0.989, 95% CI: 0.979-1.0) were based on input of transformed A-scan measurements. Our SVM trained on this input performed better than ANNs or SVMs trained on any of the single RNFLT parameters (p < or = 0.038). The performance of ANNs and SVMs trained on minimum thickness values and the 10th and 90th percentiles were at least as good as ANNs and SVMs with input based on the conventional RNFLT parameters. No differences between ANN and SVM were observed in this study. Both MLCs performed very well, with similar diagnostic performance. Input parameters have a larger impact on diagnostic performance than the type of machine classifier. Our results suggest that parameters based on transformed A-scan thickness measurements of the RNFL processed by machine classifiers can improve OCT-based glaucoma diagnosis.

  8. Hybrid supervisory control using recurrent fuzzy neural network for tracking periodic inputs.

    PubMed

    Lin, F J; Wai, R J; Hong, C M

    2001-01-01

    A hybrid supervisory control system using a recurrent fuzzy neural network (RFNN) is proposed to control the mover of a permanent magnet linear synchronous motor (PMLSM) servo drive for the tracking of periodic reference inputs. First, the field-oriented mechanism is applied to formulate the dynamic equation of the PMLSM. Then, a hybrid supervisory control system, which combines a supervisory control system and an intelligent control system, is proposed to control the mover of the PMLSM for periodic motion. The supervisory control law is designed based on the uncertainty bounds of the controlled system to stabilize the system states around a predefined bound region. Since the supervisory control law will induce excessive and chattering control effort, the intelligent control system is introduced to smooth and reduce the control effort when the system states are inside the predefined bound region. In the intelligent control system, the RFNN control is the main tracking controller which is used to mimic a idea control law and a compensated control is proposed to compensate the difference between the idea control law and the RFNN control. The RFNN has the merits of fuzzy inference, dynamic mapping and fast convergence speed, In addition, an online parameter training methodology, which is derived using the Lyapunov stability theorem and the gradient descent method, is proposed to increase the learning capability of the RFNN. The proposed hybrid supervisory control system using RFNN can track various periodic reference inputs effectively with robust control performance.

  9. Impact of the hard-coded parameters on the hydrologic fluxes of the land surface model Noah-MP

    NASA Astrophysics Data System (ADS)

    Cuntz, Matthias; Mai, Juliane; Samaniego, Luis; Clark, Martyn; Wulfmeyer, Volker; Attinger, Sabine; Thober, Stephan

    2016-04-01

    Land surface models incorporate a large number of processes, described by physical, chemical and empirical equations. The process descriptions contain a number of parameters that can be soil or plant type dependent and are typically read from tabulated input files. Land surface models may have, however, process descriptions that contain fixed, hard-coded numbers in the computer code, which are not identified as model parameters. Here we searched for hard-coded parameters in the computer code of the land surface model Noah with multiple process options (Noah-MP) to assess the importance of the fixed values on restricting the model's agility during parameter estimation. We found 139 hard-coded values in all Noah-MP process options, which are mostly spatially constant values. This is in addition to the 71 standard parameters of Noah-MP, which mostly get distributed spatially by given vegetation and soil input maps. We performed a Sobol' global sensitivity analysis of Noah-MP to variations of the standard and hard-coded parameters for a specific set of process options. 42 standard parameters and 75 hard-coded parameters were active with the chosen process options. The sensitivities of the hydrologic output fluxes latent heat and total runoff as well as their component fluxes were evaluated. These sensitivities were evaluated at twelve catchments of the Eastern United States with very different hydro-meteorological regimes. Noah-MP's hydrologic output fluxes are sensitive to two thirds of its standard parameters. The most sensitive parameter is, however, a hard-coded value in the formulation of soil surface resistance for evaporation, which proved to be oversensitive in other land surface models as well. Surface runoff is sensitive to almost all hard-coded parameters of the snow processes and the meteorological inputs. These parameter sensitivities diminish in total runoff. Assessing these parameters in model calibration would require detailed snow observations or the

  10. Carbon and nitrogen inputs affect soil microbial community structure and function

    NASA Astrophysics Data System (ADS)

    Liu, X. J. A.; Mau, R. L.; Hayer, M.; Finley, B. K.; Schwartz, E.; Dijkstra, P.; Hungate, B. A.

    2016-12-01

    Climate change has been projected to increase energy and nutrient inputs to soils, affecting soil organic matter (SOM) decomposition (priming effect) and microbial communities. However, many important questions remain: how do labile C and/or N inputs affect priming and microbial communities? What is the relationship between them? To address these questions, we applied N (NH4NO3 ; 100 µg N g-1 wk-1), C (13C glucose; 1000 µg C g-1 wk-1), C+N to four different soils for five weeks. We found: 1) N showed no effect, whereas C induced the greatest priming, and C+N had significantly lower priming than C. 2) C and C+N additions increased the relative abundance of actinobacteria, proteobacteria, and firmicutes, but reduced relative abundance of acidobacteria, chloroflexi, verrucomicrobia, planctomycetes, and gemmatimonadetes. 3) Actinobacteria and proteobacteria increased relative abundance over time, but most others decreased over time. 4) substrate additions (N, C, C+N) significantly reduced microbial alpha diversity, which also decreased over time. 5) For beta diversity, C and C+N formed significantly different communities compare to the control and N treatments. Overtime, microbial community structure significantly altered. Four soils have drastically different community structures. These results indicate amounts of substrate C were determinant factors in modulating the rate of SOM decomposition and microbial communities. Variable responses of different microbial communities to labile C and N inputs indicate that complex relationships between priming and microbial functions. In general, we demonstrate that energy inputs can quickly accelerate SOM decomposition whereas extra N input can slow this process, though both had similar microbial community responses.

  11. The role of remediation, natural alkalinity sources and physical stream parameters in stream recovery.

    PubMed

    Kruse, Natalie A; DeRose, Lisa; Korenowsky, Rebekah; Bowman, Jennifer R; Lopez, Dina; Johnson, Kelly; Rankin, Edward

    2013-10-15

    Acid mine drainage (AMD) negatively impacts not only stream chemistry, but also aquatic biology. The ultimate goal of AMD treatment is restoration of the biological community, but that goal is rarely explicit in treatment system design. Hewett Fork in Raccoon Creek Watershed, Ohio, has been impacted by historic coal mining and has been treated with a calcium oxide doser in the headwaters of the watershed since 2004. All of the acidic inputs are isolated to a 1.5 km stretch of stream in the headwaters of the Hewett Fork watershed. The macroinvertebrate and fish communities have begun to recover and it is possible to distinguish three zones downstream of the doser: an impaired zone, a transition zone and a recovered zone. Alkalinity from both the doser and natural sources and physical stream parameters play a role in stream restoration. In Hewett Fork, natural alkaline additions downstream are higher than those from the doser. Both, alkaline additions and stream velocity drive sediment and metal deposition. Metal deposition occurs in several patterns; aluminum tends to deposit in regions of low stream velocity, while iron tends to deposit once sufficient alkalinity is added to the system downstream of mining inputs. The majority of metal deposition occurs upstream of the recovered zone. Both the physical stream parameters and natural alkalinity sources influence biological recovery in treated AMD streams and should be considered in remediation plans. Copyright © 2013 Elsevier Ltd. All rights reserved.

  12. Experimental Studies of Nuclear Physics Input for γ -Process Nucleosynthesis

    NASA Astrophysics Data System (ADS)

    Scholz, Philipp; Heim, Felix; Mayer, Jan; Netterdon, Lars; Zilges, Andreas

    The predictions of reaction rates for the γ process in the scope of the Hauser-Feshbach statistical model crucially depend on nuclear physics input-parameters as optical-model potentials (OMP) or γ -ray strength functions. Precise cross-section measurements at astrophysically relevant energies help to constrain adopted models and, therefore, to reduce the uncertainties in the theoretically predicted reaction rates. During the last years, several cross-sections of charged-particle induced reactions on heavy nuclei have been measured at the University of Cologne. Either by means of the in-beam method at the HORUS γ -ray spectrometer or the activation technique using the Cologne Clover Counting Setup, total and partial cross-sections could be used to further constrain different models for nuclear physics input-parameters. It could be shown that modifications on the α -OMP in the case of the 112Sn(α , γ ) reaction also improve the description of the recently measured cross sections of the 108Cd(α , γ ) and 108Cd(α , n) reaction and other reactions as well. Partial cross-sections of the 92Mo(p, γ ) reaction were used to improve the γ -strength function model in 93Tc in the same way as it was done for the 89Y(p, γ ) reaction.

  13. Feedforward Inhibition Allows Input Summation to Vary in Recurrent Cortical Networks

    PubMed Central

    2018-01-01

    Abstract Brain computations depend on how neurons transform inputs to spike outputs. Here, to understand input-output transformations in cortical networks, we recorded spiking responses from visual cortex (V1) of awake mice of either sex while pairing sensory stimuli with optogenetic perturbation of excitatory and parvalbumin-positive inhibitory neurons. We found that V1 neurons’ average responses were primarily additive (linear). We used a recurrent cortical network model to determine whether these data, as well as past observations of nonlinearity, could be described by a common circuit architecture. Simulations showed that cortical input-output transformations can be changed from linear to sublinear with moderate (∼20%) strengthening of connections between inhibitory neurons, but this change away from linear scaling depends on the presence of feedforward inhibition. Simulating a variety of recurrent connection strengths showed that, compared with when input arrives only to excitatory neurons, networks produce a wider range of output spiking responses in the presence of feedforward inhibition. PMID:29682603

  14. Approximation of discrete-time LQG compensators for distributed systems with boundary input and unbounded measurement

    NASA Technical Reports Server (NTRS)

    Gibson, J. S.; Rosen, I. G.

    1987-01-01

    The approximation of optimal discrete-time linear quadratic Gaussian (LQG) compensators for distributed parameter control systems with boundary input and unbounded measurement is considered. The approach applies to a wide range of problems that can be formulated in a state space on which both the discrete-time input and output operators are continuous. Approximating compensators are obtained via application of the LQG theory and associated approximation results for infinite dimensional discrete-time control systems with bounded input and output. Numerical results for spline and modal based approximation schemes used to compute optimal compensators for a one dimensional heat equation with either Neumann or Dirichlet boundary control and pointwise measurement of temperature are presented and discussed.

  15. Fully probabilistic control for stochastic nonlinear control systems with input dependent noise.

    PubMed

    Herzallah, Randa

    2015-03-01

    Robust controllers for nonlinear stochastic systems with functional uncertainties can be consistently designed using probabilistic control methods. In this paper a generalised probabilistic controller design for the minimisation of the Kullback-Leibler divergence between the actual joint probability density function (pdf) of the closed loop control system, and an ideal joint pdf is presented emphasising how the uncertainty can be systematically incorporated in the absence of reliable systems models. To achieve this objective all probabilistic models of the system are estimated from process data using mixture density networks (MDNs) where all the parameters of the estimated pdfs are taken to be state and control input dependent. Based on this dependency of the density parameters on the input values, explicit formulations to the construction of optimal generalised probabilistic controllers are obtained through the techniques of dynamic programming and adaptive critic methods. Using the proposed generalised probabilistic controller, the conditional joint pdfs can be made to follow the ideal ones. A simulation example is used to demonstrate the implementation of the algorithm and encouraging results are obtained. Copyright © 2014 Elsevier Ltd. All rights reserved.

  16. Reconstruction of an input function from a dynamic PET water image using multiple tissue curves

    NASA Astrophysics Data System (ADS)

    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  <8% and the calculated CBF values showed a tight correlation (r  =  0.97). The simulation showed that errors associated with the assumed parameters were  <10%, and that the optimal number of tissue curves to be used was around 500. Our results demonstrate that IDIF can be reconstructed directly from tissue curves obtained through {{\\text{H}}2} 15O PET imaging. This suggests the possibility of using a completely non-invasive technique to assess CBF in patho-physiological studies.

  17. About influence of input rate random part of nonstationary queue system on statistical estimates of its macroscopic indicators

    NASA Astrophysics Data System (ADS)

    Korelin, Ivan A.; Porshnev, Sergey V.

    2018-05-01

    A model of the non-stationary queuing system (NQS) is described. The input of this model receives a flow of requests with input rate λ = λdet (t) + λrnd (t), where λdet (t) is a deterministic function depending on time; λrnd (t) is a random function. The parameters of functions λdet (t), λrnd (t) were identified on the basis of statistical information on visitor flows collected from various Russian football stadiums. The statistical modeling of NQS is carried out and the average statistical dependences are obtained: the length of the queue of requests waiting for service, the average wait time for the service, the number of visitors entered to the stadium on the time. It is shown that these dependencies can be characterized by the following parameters: the number of visitors who entered at the time of the match; time required to service all incoming visitors; the maximum value; the argument value when the studied dependence reaches its maximum value. The dependences of these parameters on the energy ratio of the deterministic and random component of the input rate are investigated.

  18. Systems and methods for reconfiguring input devices

    NASA Technical Reports Server (NTRS)

    Lancaster, Jeff (Inventor); De Mers, Robert E. (Inventor)

    2012-01-01

    A system includes an input device having first and second input members configured to be activated by a user. The input device is configured to generate activation signals associated with activation of the first and second input members, and each of the first and second input members are associated with an input function. A processor is coupled to the input device and configured to receive the activation signals. A memory coupled to the processor, and includes a reconfiguration module configured to store the input functions assigned to the first and second input members and, upon execution of the processor, to reconfigure the input functions assigned to the input members when the first input member is inoperable.

  19. Disaggregated seismic hazard and the elastic input energy spectrum: An approach to design earthquake selection

    NASA Astrophysics Data System (ADS)

    Chapman, Martin Colby

    1998-12-01

    The design earthquake selection problem is fundamentally probabilistic. Disaggregation of a probabilistic model of the seismic hazard offers a rational and objective approach that can identify the most likely earthquake scenario(s) contributing to hazard. An ensemble of time series can be selected on the basis of the modal earthquakes derived from the disaggregation. This gives a useful time-domain realization of the seismic hazard, to the extent that a single motion parameter captures the important time-domain characteristics. A possible limitation to this approach arises because most currently available motion prediction models for peak ground motion or oscillator response are essentially independent of duration, and modal events derived using the peak motions for the analysis may not represent the optimal characterization of the hazard. The elastic input energy spectrum is an alternative to the elastic response spectrum for these types of analyses. The input energy combines the elements of amplitude and duration into a single parameter description of the ground motion that can be readily incorporated into standard probabilistic seismic hazard analysis methodology. This use of the elastic input energy spectrum is examined. Regression analysis is performed using strong motion data from Western North America and consistent data processing procedures for both the absolute input energy equivalent velocity, (Vsbea), and the elastic pseudo-relative velocity response (PSV) in the frequency range 0.5 to 10 Hz. The results show that the two parameters can be successfully fit with identical functional forms. The dependence of Vsbea and PSV upon (NEHRP) site classification is virtually identical. The variance of Vsbea is uniformly less than that of PSV, indicating that Vsbea can be predicted with slightly less uncertainty as a function of magnitude, distance and site classification. The effects of site class are important at frequencies less than a few Hertz. The regression

  20. Blurring the Inputs: A Natural Language Approach to Sensitivity Analysis

    NASA Technical Reports Server (NTRS)

    Kleb, William L.; Thompson, Richard A.; Johnston, Christopher O.

    2007-01-01

    To document model parameter uncertainties and to automate sensitivity analyses for numerical simulation codes, a natural-language-based method to specify tolerances has been developed. With this new method, uncertainties are expressed in a natural manner, i.e., as one would on an engineering drawing, namely, 5.25 +/- 0.01. This approach is robust and readily adapted to various application domains because it does not rely on parsing the particular structure of input file formats. Instead, tolerances of a standard format are added to existing fields within an input file. As a demonstration of the power of this simple, natural language approach, a Monte Carlo sensitivity analysis is performed for three disparate simulation codes: fluid dynamics (LAURA), radiation (HARA), and ablation (FIAT). Effort required to harness each code for sensitivity analysis was recorded to demonstrate the generality and flexibility of this new approach.

  1. Multiple-Input Multiple-Output (MIMO) Linear Systems Extreme Inputs/Outputs

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

    Smallwood, David O.

    2007-01-01

    A linear structure is excited at multiple points with a stationary normal random process. The response of the structure is measured at multiple outputs. If the autospectral densities of the inputs are specified, the phase relationships between the inputs are derived that will minimize or maximize the trace of the autospectral density matrix of the outputs. If the autospectral densities of the outputs are specified, the phase relationships between the outputs that will minimize or maximize the trace of the input autospectral density matrix are derived. It is shown that other phase relationships and ordinary coherence less than one willmore » result in a trace intermediate between these extremes. Least favorable response and some classes of critical response are special cases of the development. It is shown that the derivation for stationary random waveforms can also be applied to nonstationary random, transients, and deterministic waveforms.« less

  2. PLEXOS Input Data Generator

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

    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.

  3. Calibrating binary lumped parameter models

    NASA Astrophysics Data System (ADS)

    Morgenstern, Uwe; Stewart, Mike

    2017-04-01

    Groundwater at its discharge point is a mixture of water from short and long flowlines, and therefore has a distribution of ages rather than a single age. Various transfer functions describe the distribution of ages within the water sample. Lumped parameter models (LPMs), which are mathematical models of water transport based on simplified aquifer geometry and flow configuration can account for such mixing of groundwater of different age, usually representing the age distribution with two parameters, the mean residence time, and the mixing parameter. Simple lumped parameter models can often match well the measured time varying age tracer concentrations, and therefore are a good representation of the groundwater mixing at these sites. Usually a few tracer data (time series and/or multi-tracer) can constrain both parameters. With the building of larger data sets of age tracer data throughout New Zealand, including tritium, SF6, CFCs, and recently Halon-1301, and time series of these tracers, we realised that for a number of wells the groundwater ages using a simple lumped parameter model were inconsistent between the different tracer methods. Contamination or degradation of individual tracers is unlikely because the different tracers show consistent trends over years and decades. This points toward a more complex mixing of groundwaters with different ages for such wells than represented by the simple lumped parameter models. Binary (or compound) mixing models are able to represent a more complex mixing, with mixing of water of two different age distributions. The problem related to these models is that they usually have 5 parameters which makes them data-hungry and therefore difficult to constrain all parameters. Two or more age tracers with different input functions, with multiple measurements over time, can provide the required information to constrain the parameters of the binary mixing model. We obtained excellent results using tritium time series encompassing

  4. The application of Global Sensitivity Analysis to quantify the dominant input factors for hydraulic model simulations

    NASA Astrophysics Data System (ADS)

    Savage, James; Pianosi, Francesca; Bates, Paul; Freer, Jim; Wagener, Thorsten

    2015-04-01

    inundation indicators and flood wave travel time in addition to temporally and spatially variable indicators. This enables us to assess whether the sensitivity of the model to various input factors is stationary in both time and space. Furthermore, competing models are assessed against observations of water depths from a historical flood event. Consequently we are able to determine which of the input factors has the most influence on model performance. Initial findings suggest the sensitivity of the model to different input factors varies depending on the type of model output assessed and at what stage during the flood hydrograph the model output is assessed. We have also found that initial decisions regarding the characterisation of the input factors, for example defining the upper and lower bounds of the parameter sample space, can be significant in influencing the implied sensitivities.

  5. Hands-on parameter search for neural simulations by a MIDI-controller.

    PubMed

    Eichner, Hubert; Borst, Alexander

    2011-01-01

    Computational neuroscientists frequently encounter the challenge of parameter fitting--exploring a usually high dimensional variable space to find a parameter set that reproduces an experimental data set. One common approach is using automated search algorithms such as gradient descent or genetic algorithms. However, these approaches suffer several shortcomings related to their lack of understanding the underlying question, such as defining a suitable error function or getting stuck in local minima. Another widespread approach is manual parameter fitting using a keyboard or a mouse, evaluating different parameter sets following the users intuition. However, this process is often cumbersome and time-intensive. Here, we present a new method for manual parameter fitting. A MIDI controller provides input to the simulation software, where model parameters are then tuned according to the knob and slider positions on the device. The model is immediately updated on every parameter change, continuously plotting the latest results. Given reasonably short simulation times of less than one second, we find this method to be highly efficient in quickly determining good parameter sets. Our approach bears a close resemblance to tuning the sound of an analog synthesizer, giving the user a very good intuition of the problem at hand, such as immediate feedback if and how results are affected by specific parameter changes. In addition to be used in research, our approach should be an ideal teaching tool, allowing students to interactively explore complex models such as Hodgkin-Huxley or dynamical systems.

  6. Hands-On Parameter Search for Neural Simulations by a MIDI-Controller

    PubMed Central

    Eichner, Hubert; Borst, Alexander

    2011-01-01

    Computational neuroscientists frequently encounter the challenge of parameter fitting – exploring a usually high dimensional variable space to find a parameter set that reproduces an experimental data set. One common approach is using automated search algorithms such as gradient descent or genetic algorithms. However, these approaches suffer several shortcomings related to their lack of understanding the underlying question, such as defining a suitable error function or getting stuck in local minima. Another widespread approach is manual parameter fitting using a keyboard or a mouse, evaluating different parameter sets following the users intuition. However, this process is often cumbersome and time-intensive. Here, we present a new method for manual parameter fitting. A MIDI controller provides input to the simulation software, where model parameters are then tuned according to the knob and slider positions on the device. The model is immediately updated on every parameter change, continuously plotting the latest results. Given reasonably short simulation times of less than one second, we find this method to be highly efficient in quickly determining good parameter sets. Our approach bears a close resemblance to tuning the sound of an analog synthesizer, giving the user a very good intuition of the problem at hand, such as immediate feedback if and how results are affected by specific parameter changes. In addition to be used in research, our approach should be an ideal teaching tool, allowing students to interactively explore complex models such as Hodgkin-Huxley or dynamical systems. PMID:22066027

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

    NASA Astrophysics Data System (ADS)

    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.

  8. Upper bounds on sequential decoding performance parameters

    NASA Technical Reports Server (NTRS)

    Jelinek, F.

    1974-01-01

    This paper presents the best obtainable random coding and expurgated upper bounds on the probabilities of undetectable error, of t-order failure (advance to depth t into an incorrect subset), and of likelihood rise in the incorrect subset, applicable to sequential decoding when the metric bias G is arbitrary. Upper bounds on the Pareto exponent are also presented. The G-values optimizing each of the parameters of interest are determined, and are shown to lie in intervals that in general have nonzero widths. The G-optimal expurgated bound on undetectable error is shown to agree with that for maximum likelihood decoding of convolutional codes, and that on failure agrees with the block code expurgated bound. Included are curves evaluating the bounds for interesting choices of G and SNR for a binary-input quantized-output Gaussian additive noise channel.

  9. Parvalbumin-producing cortical interneurons receive inhibitory inputs on proximal portions and cortical excitatory inputs on distal dendrites.

    PubMed

    Kameda, Hiroshi; Hioki, Hiroyuki; Tanaka, Yasuyo H; Tanaka, Takuma; Sohn, Jaerin; Sonomura, Takahiro; Furuta, Takahiro; Fujiyama, Fumino; Kaneko, Takeshi

    2012-03-01

    To examine inputs to parvalbumin (PV)-producing interneurons, we generated transgenic mice expressing somatodendritic membrane-targeted green fluorescent protein specifically in the interneurons, and completely visualized their dendrites and somata. Using immunolabeling for vesicular glutamate transporter (VGluT)1, VGluT2, and vesicular GABA transporter, we found that VGluT1-positive terminals made contacts 4- and 3.1-fold more frequently with PV-producing interneurons than VGluT2-positive and GABAergic terminals, respectively, in the primary somatosensory cortex. Even in layer 4, where VGluT2-positive terminals were most densely distributed, VGluT1-positive inputs to PV-producing interneurons were 2.4-fold more frequent than VGluT2-positive inputs. Furthermore, although GABAergic inputs to PV-producing interneurons were as numerous as VGluT2-positive inputs in most cortical layers, GABAergic inputs clearly preferred the proximal dendrites and somata of the interneurons, indicating that the sites of GABAergic inputs were more optimized than those of VGluT2-positive inputs. Simulation analysis with a PV-producing interneuron model compatible with the present morphological data revealed a plausible reason for this observation, by showing that GABAergic and glutamatergic postsynaptic potentials evoked by inputs to distal dendrites were attenuated to 60 and 87%, respectively, of those evoked by somatic inputs. As VGluT1-positive and VGluT2-positive axon terminals were presumed to be cortical and thalamic glutamatergic inputs, respectively, cortical excitatory inputs to PV-producing interneurons outnumbered the thalamic excitatory and intrinsic inhibitory inputs more than two-fold in any cortical layer. Although thalamic inputs are known to evoke about two-fold larger unitary excitatory postsynaptic potentials than cortical ones, the present results suggest that cortical inputs control PV-producing interneurons at least as strongly as thalamic inputs. © 2012 The

  10. A PC-based single-ADC multi-parameter data acquisition system

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

    Woodring, M.; Kegel, G.H.R.; Egan, J.J.

    1995-10-01

    A personal computer (PC) based mult parameter data acquisition system using the Microsoft Window operating environment has been designed and constructed. An IBI AT compatible personal computer with an Intel 486DX5 microprocessor was combined with a National Instruments ATIDIO 32 digital I/O card, a single Canberra 8713 ADC with 13-bit resolution and a modified Canberra 8223 8-input analog multiplexer to acquil data from experiments carried out at the UML Van de Graa accelerator. The accelerator data acquisition (ADAC) computer environment was programmed in Microsoft Visual BASIC for use i Windows. ADAC allows event-mode data acquisition with up to eight parametersmore » (modifiable to 64) and the simultaneous display parameters during acquisition. Additional features of ADAC include replay of event-mode data and graphical analysis/display of data. TV ADAC environment is easy to upgrade or expand, inexpensive 1 implement, and is specifically designed to meet the needs of nuclei spectroscopy.« less

  11. Optimizing Input/Output Using Adaptive File System Policies

    NASA Technical Reports Server (NTRS)

    Madhyastha, Tara M.; Elford, Christopher L.; Reed, Daniel A.

    1996-01-01

    Parallel input/output characterization studies and experiments with flexible resource management algorithms indicate that adaptivity is crucial to file system performance. In this paper we propose an automatic technique for selecting and refining file system policies based on application access patterns and execution environment. An automatic classification framework allows the file system to select appropriate caching and pre-fetching policies, while performance sensors provide feedback used to tune policy parameters for specific system environments. To illustrate the potential performance improvements possible using adaptive file system policies, we present results from experiments involving classification-based and performance-based steering.

  12. Intensive Input in Language Acquisition.

    ERIC Educational Resources Information Center

    Trimino, Andy; Ferguson, Nancy

    This paper discusses the role of input as one of the universals in second language acquisition theory. Considerations include how language instructors can best organize and present input and when certain kinds of input are more important. A self-administered program evaluation exercise using relevant theoretical and methodological contributions…

  13. A Voice and Mouse Input Interface for 3D Virtual Environments

    NASA Technical Reports Server (NTRS)

    Kao, David L.; Bryson, Steve T.

    2003-01-01

    There have been many successful stories on how 3D input devices can be fully integrated into an immersive virtual environment. Electromagnetic trackers, optical trackers, gloves, and flying mice are just some of these input devices. Though we can use existing 3D input devices that are commonly used for VR applications, there are several factors that prevent us from choosing these input devices for our applications. One main factor is that most of these tracking devices are not suitable for prolonged use due to human fatigue associated with using them. A second factor is that many of them would occupy additional office space. Another factor is that many of the 3D input devices are expensive due to the unusual hardware that are required. For our VR applications, we want a user interface that would work naturally with standard equipment. In this paper, we demonstrate applications or our proposed muitimodal interface using a 3D dome display. We also show that effective data analysis can be achieved while the scientists view their data rendered inside the dome display and perform user interactions simply using the mouse and voice input. Though the sphere coordinate grid seems to be ideal for interaction using a 3D dome display, we can also use other non-spherical grids as well.

  14. Theoretic aspects of the identification of the parameters in the optimal control model

    NASA Technical Reports Server (NTRS)

    Vanwijk, R. A.; Kok, J. J.

    1977-01-01

    The identification of the parameters of the optimal control model from input-output data of the human operator is considered. Accepting the basic structure of the model as a cascade of a full-order observer and a feedback law, and suppressing the inherent optimality of the human controller, the parameters to be identified are the feedback matrix, the observer gain matrix, and the intensity matrices of the observation noise and the motor noise. The identification of the parameters is a statistical problem, because the system and output are corrupted by noise, and therefore the solution must be based on the statistics (probability density function) of the input and output data of the human operator. However, based on the statistics of the input-output data of the human operator, no distinction can be made between the observation and the motor noise, which shows that the model suffers from overparameterization.

  15. Nonlinear control of linear parameter varying systems with applications to hypersonic vehicles

    NASA Astrophysics Data System (ADS)

    Wilcox, Zachary Donald

    The focus of this dissertation is to design a controller for linear parameter varying (LPV) systems, apply it specifically to air-breathing hypersonic vehicles, and examine the interplay between control performance and the structural dynamics design. Specifically a Lyapunov-based continuous robust controller is developed that yields exponential tracking of a reference model, despite the presence of bounded, nonvanishing disturbances. The hypersonic vehicle has time varying parameters, specifically temperature profiles, and its dynamics can be reduced to an LPV system with additive disturbances. Since the HSV can be modeled as an LPV system the proposed control design is directly applicable. The control performance is directly examined through simulations. A wide variety of applications exist that can be effectively modeled as LPV systems. In particular, flight systems have historically been modeled as LPV systems and associated control tools have been applied such as gain-scheduling, linear matrix inequalities (LMIs), linear fractional transformations (LFT), and mu-types. However, as the type of flight environments and trajectories become more demanding, the traditional LPV controllers may no longer be sufficient. In particular, hypersonic flight vehicles (HSVs) present an inherently difficult problem because of the nonlinear aerothermoelastic coupling effects in the dynamics. HSV flight conditions produce temperature variations that can alter both the structural dynamics and flight dynamics. Starting with the full nonlinear dynamics, the aerothermoelastic effects are modeled by a temperature dependent, parameter varying state-space representation with added disturbances. The model includes an uncertain parameter varying state matrix, an uncertain parameter varying non-square (column deficient) input matrix, and an additive bounded disturbance. In this dissertation, a robust dynamic controller is formulated for a uncertain and disturbed LPV system. The developed

  16. High Input Voltage, Silicon Carbide Power Processing Unit Performance Demonstration

    NASA Technical Reports Server (NTRS)

    Bozak, Karin E.; Pinero, Luis R.; Scheidegger, Robert J.; Aulisio, Michael V.; Gonzalez, Marcelo C.; Birchenough, Arthur G.

    2015-01-01

    A silicon carbide brassboard power processing unit has been developed by the NASA Glenn Research Center in Cleveland, Ohio. The power processing unit operates from two sources - a nominal 300-Volt high voltage input bus and a nominal 28-Volt low voltage input bus. The design of the power processing unit includes four low voltage, low power supplies that provide power to the thruster auxiliary supplies, and two parallel 7.5 kilowatt power supplies that are capable of providing up to 15 kilowatts of total power at 300-Volts to 500-Volts to the thruster discharge supply. Additionally, the unit contains a housekeeping supply, high voltage input filter, low voltage input filter, and master control board, such that the complete brassboard unit is capable of operating a 12.5 kilowatt Hall Effect Thruster. The performance of unit was characterized under both ambient and thermal vacuum test conditions, and the results demonstrate the exceptional performance with full power efficiencies exceeding 97. With a space-qualified silicon carbide or similar high voltage, high efficiency power device, this design could evolve into a flight design for future missions that require high power electric propulsion systems.

  17. Regression with Small Data Sets: A Case Study using Code Surrogates in Additive Manufacturing

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

    Kamath, C.; Fan, Y. J.

    There has been an increasing interest in recent years in the mining of massive data sets whose sizes are measured in terabytes. While it is easy to collect such large data sets in some application domains, there are others where collecting even a single data point can be very expensive, so the resulting data sets have only tens or hundreds of samples. For example, when complex computer simulations are used to understand a scientific phenomenon, we want to run the simulation for many different values of the input parameters and analyze the resulting output. The data set relating the simulationmore » inputs and outputs is typically quite small, especially when each run of the simulation is expensive. However, regression techniques can still be used on such data sets to build an inexpensive \\surrogate" that could provide an approximate output for a given set of inputs. A good surrogate can be very useful in sensitivity analysis, uncertainty analysis, and in designing experiments. In this paper, we compare different regression techniques to determine how well they predict melt-pool characteristics in the problem domain of additive manufacturing. Our analysis indicates that some of the commonly used regression methods do perform quite well even on small data sets.« less

  18. The role of size of input box, location of input box, input method and display size in Chinese handwriting performance and preference on mobile devices.

    PubMed

    Chen, Zhe; Rau, Pei-Luen Patrick

    2017-03-01

    This study presented two experiments on Chinese handwriting performance (time, accuracy, the number of protruding strokes and number of rewritings) and subjective ratings (mental workload, satisfaction, and preference) on mobile devices. Experiment 1 evaluated the effects of size of the input box, input method and display size on Chinese handwriting performance and preference. It was indicated that the optimal input sizes were 30.8 × 30.8 mm, 46.6 × 46.6 mm, 58.9 × 58.9 mm and 84.6 × 84.6 mm for devices with 3.5-inch, 5.5-inch, 7.0-inch and 9.7-inch display sizes, respectively. Experiment 2 proved the significant effects of location of the input box, input method and display size on Chinese handwriting performance and subjective ratings. It was suggested that the optimal location was central regardless of display size and input method. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. Modeling of Ionosphere Effects of Geomagnetic Storm Sequence on September 9-14, 2005 in View of Solar Flares and Dependence of Model Input Parameters from AE-and Kp-indices

    NASA Astrophysics Data System (ADS)

    Klimenko, Maxim; Klimenko, Vladimir; Ratovsky, Konstantin; Goncharenko, Larisa

    Earlier by Klimenko et al., 2009 under carrying out the calculations of the ionospheric effects of storm sequence on September 9-14, 2005 the model input parameters (potential difference through polar caps, field-aligned currents of the second region and particle precipitation fluxes and energy) were set as function of Kp-index of geomagnetic activity. The analyses of obtained results show that the reasons of quantitative distinctions of calculation results and observations can be: the use of 3 hour Kp-index at the setting of time dependence of model input parameters; the dipole approach of geomagnetic field; the absence in model calculations the effects of the solar flares, which were taken place during the considered period. In the given study the model input parameters were set as function of AE-and Kp-indices of geomagnetic activity according to different empirical models and morphological representations Feshchenko and Maltsev, 2003; Cheng et al., 2008; Zhang and Paxton, 2008. At that, we taken into account the shift of field-aligned currents of the second region to the lower latitudes as by Sojka et al., 1994 and 30 min. time delay of variations of the field-aligned currents of second region relative to the variations of the potential difference through polar caps at the storm sudden commencement phase. Also we taken into account the ionospheric effects of solar flares. Calculation of ionospheric effects of storm sequence has been carried out with use of the Global Self-Consistent Model of the Thermosphere, Ionosphere and Protonosphere (GSM TIP) developed in WD IZMIRAN (Nam-galadze et al., 1988). We carried out the comparison of calculation results with experimental data. This study is supported by RFBR grant 08-05-00274. References Cheng Z.W., Shi J.K., Zhang T.L., Dunlop M. and Liu Z.X. Relationship between FAC at plasma sheet boundary layers and AE index during storms from August to October, 2001. Sci. China Ser. E-Tech. Sci., 2008, Vol. 51, No. 7, 842

  20. Interfield dysbalances in research input and output benchmarking: Visualisation by density equalizing procedures

    PubMed Central

    Groneberg-Kloft, Beatrix; Kreiter, Carolin; Welte, Tobias; Fischer, Axel; Quarcoo, David; Scutaru, Cristian

    2008-01-01

    Background Historical, social and economic reasons can lead to major differences in the allocation of health system resources and research funding. These differences might endanger the progress in diagnostic and therapeutic approaches of socio-economic important diseases. The present study aimed to assess different benchmarking approaches that might be used to analyse these disproportions. Research in two categories was analysed for various output parameters and compared to input parameters. Germany was used as a high income model country. For the areas of cardiovascular and respiratory medicine density equalizing mapping procedures visualized major geographical differences in both input and output markers. Results An imbalance in the state financial input was present with 36 cardiovascular versus 8 respiratory medicine state-financed full clinical university departments at the C4/W3 salary level. The imbalance in financial input is paralleled by an imbalance in overall quantitative output figures: The 36 cardiology chairs published 2708 articles in comparison to 453 articles published by the 8 respiratory medicine chairs in the period between 2002 and 2006. This is a ratio of 75.2 articles per cardiology chair and 56.63 articles per respiratory medicine chair. A similar trend is also present in the qualitative measures. Here, the 2708 cardiology publications were cited 48337 times (7290 times for respiratory medicine) which is an average citation of 17.85 per publication vs. 16.09 for respiratory medicine. The average number of citations per cardiology chair was 1342.69 in contrast to 911.25 citations per respiratory medicine chair. Further comparison of the contribution of the 16 different German states revealed major geographical differences concerning numbers of chairs, published items, total number of citations and average citations. Conclusion Despite similar significances of cardiovascular and respiratory diseases for the global burden of disease, large

  1. Non-intrusive parameter identification procedure user's guide

    NASA Technical Reports Server (NTRS)

    Hanson, G. D.; Jewell, W. F.

    1983-01-01

    Written in standard FORTRAN, NAS is capable of identifying linear as well as nonlinear relations between input and output parameters; the only restriction is that the input/output relation be linear with respect to the unknown coefficients of the estimation equations. The output of the identification algorithm can be specified to be in either the time domain (i.e., the estimation equation coefficients) or in the frequency domain (i.e., a frequency response of the estimation equation). The frame length ("window") over which the identification procedure is to take place can be specified to be any portion of the input time history, thereby allowing the freedom to start and stop the identification procedure within a time history. There also is an option which allows a sliding window, which gives a moving average over the time history. The NAS software also includes the ability to identify several assumed solutions simultaneously for the same or different input data.

  2. Rapid Airplane Parametric Input Design (RAPID)

    NASA Technical Reports Server (NTRS)

    Smith, Robert E.

    1995-01-01

    RAPID is a methodology and software system to define a class of airplane configurations and directly evaluate surface grids, volume grids, and grid sensitivity on and about the configurations. A distinguishing characteristic which separates RAPID from other airplane surface modellers is that the output grids and grid sensitivity are directly applicable in CFD analysis. A small set of design parameters and grid control parameters govern the process which is incorporated into interactive software for 'real time' visual analysis and into batch software for the application of optimization technology. The computed surface grids and volume grids are suitable for a wide range of Computational Fluid Dynamics (CFD) simulation. The general airplane configuration has wing, fuselage, horizontal tail, and vertical tail components. The double-delta wing and tail components are manifested by solving a fourth order partial differential equation (PDE) subject to Dirichlet and Neumann boundary conditions. The design parameters are incorporated into the boundary conditions and therefore govern the shapes of the surfaces. The PDE solution yields a smooth transition between boundaries. Surface grids suitable for CFD calculation are created by establishing an H-type topology about the configuration and incorporating grid spacing functions in the PDE equation for the lifting components and the fuselage definition equations. User specified grid parameters govern the location and degree of grid concentration. A two-block volume grid about a configuration is calculated using the Control Point Form (CPF) technique. The interactive software, which runs on Silicon Graphics IRIS workstations, allows design parameters to be continuously varied and the resulting surface grid to be observed in real time. The batch software computes both the surface and volume grids and also computes the sensitivity of the output grid with respect to the input design parameters by applying the precompiler tool

  3. CBM First-level Event Selector Input Interface Demonstrator

    NASA Astrophysics Data System (ADS)

    Hutter, Dirk; de Cuveland, Jan; Lindenstruth, Volker

    2017-10-01

    CBM is a heavy-ion experiment at the future FAIR facility in Darmstadt, Germany. Featuring self-triggered front-end electronics and free-streaming read-out, event selection will exclusively be done by the First Level Event Selector (FLES). Designed as an HPC cluster with several hundred nodes its task is an online analysis and selection of the physics data at a total input 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, potentially overlapping processing intervals and distributes them to compute nodes. Partitioning the input data streams into specialized containers allows performing this task very efficiently. The FLES Input Interface defines the linkage between the FEE and the FLES data transport framework. A custom FPGA PCIe board, the FLES Interface Board (FLIB), is used to receive data via optical links and transfer them via DMA to the host’s memory. The current prototype of the FLIB features a Kintex-7 FPGA and provides up to eight 10 GBit/s optical links. A custom FPGA design has been developed for this board. DMA transfers and data structures are optimized for subsequent timeslice building. Index tables generated by the FPGA enable fast random access to the written data containers. In addition the DMA target buffers can directly serve as InfiniBand RDMA source buffers without copying the data. The usage of POSIX shared memory for these buffers allows data access from multiple processes. An accompanying HDL module has been developed to integrate the FLES link into the front-end FPGA designs. It implements the front-end logic interface as well as the link protocol. Prototypes of all Input Interface components have been implemented and integrated into the FLES test framework. This allows the implementation and evaluation of the foreseen CBM read-out chain.

  4. Relationship between fatigue of generation II image intensifier and input illumination

    NASA Astrophysics Data System (ADS)

    Chen, Qingyou

    1995-09-01

    If there is fatigue for an image intesifier, then it has an effect on the imaging property of the night vision system. In this paper, using the principle of Joule Heat, we derive a mathematical formula for the generated heat of semiconductor photocathode. We describe the relationship among the various parameters in the formula. We also discuss reasons for the fatigue of Generation II image intensifier caused by bigger input illumination.

  5. Sensor fault diagnosis of singular delayed LPV systems with inexact parameters: an uncertain system approach

    NASA Astrophysics Data System (ADS)

    Hassanabadi, Amir Hossein; Shafiee, Masoud; Puig, Vicenc

    2018-01-01

    In this paper, sensor fault diagnosis of a singular delayed linear parameter varying (LPV) system is considered. In the considered system, the model matrices are dependent on some parameters which are real-time measurable. The case of inexact parameter measurements is considered which is close to real situations. Fault diagnosis in this system is achieved via fault estimation. For this purpose, an augmented system is created by including sensor faults as additional system states. Then, an unknown input observer (UIO) is designed which estimates both the system states and the faults in the presence of measurement noise, disturbances and uncertainty induced by inexact measured parameters. Error dynamics and the original system constitute an uncertain system due to inconsistencies between real and measured values of the parameters. Then, the robust estimation of the system states and the faults are achieved with H∞ performance and formulated with a set of linear matrix inequalities (LMIs). The designed UIO is also applicable for fault diagnosis of singular delayed LPV systems with unmeasurable scheduling variables. The efficiency of the proposed approach is illustrated with an example.

  6. Chemical sensors are hybrid-input memristors

    NASA Astrophysics Data System (ADS)

    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.

  7. Extrapolation of sonic boom pressure signatures by the waveform parameter method

    NASA Technical Reports Server (NTRS)

    Thomas, C. L.

    1972-01-01

    The waveform parameter method of sonic boom extrapolation is derived and shown to be equivalent to the F-function method. A computer program based on the waveform parameter method is presented and discussed, with a sample case demonstrating program input and output.

  8. Enhanced Sensitivity to Rapid Input Fluctuations by Nonlinear Threshold Dynamics in Neocortical Pyramidal Neurons.

    PubMed

    Mensi, Skander; Hagens, Olivier; Gerstner, Wulfram; Pozzorini, Christian

    2016-02-01

    The way in which single neurons transform input into output spike trains has fundamental consequences for network coding. Theories and modeling studies based on standard Integrate-and-Fire models implicitly assume that, in response to increasingly strong inputs, neurons modify their coding strategy by progressively reducing their selective sensitivity to rapid input fluctuations. Combining mathematical modeling with in vitro experiments, we demonstrate that, in L5 pyramidal neurons, the firing threshold dynamics adaptively adjust the effective timescale of somatic integration in order to preserve sensitivity to rapid signals over a broad range of input statistics. For that, a new Generalized Integrate-and-Fire model featuring nonlinear firing threshold dynamics and conductance-based adaptation is introduced that outperforms state-of-the-art neuron models in predicting the spiking activity of neurons responding to a variety of in vivo-like fluctuating currents. Our model allows for efficient parameter extraction and can be analytically mapped to a Generalized Linear Model in which both the input filter--describing somatic integration--and the spike-history filter--accounting for spike-frequency adaptation--dynamically adapt to the input statistics, as experimentally observed. Overall, our results provide new insights on the computational role of different biophysical processes known to underlie adaptive coding in single neurons and support previous theoretical findings indicating that the nonlinear dynamics of the firing threshold due to Na+-channel inactivation regulate the sensitivity to rapid input fluctuations.

  9. Enhanced Sensitivity to Rapid Input Fluctuations by Nonlinear Threshold Dynamics in Neocortical Pyramidal Neurons

    PubMed Central

    Mensi, Skander; Hagens, Olivier; Gerstner, Wulfram; Pozzorini, Christian

    2016-01-01

    The way in which single neurons transform input into output spike trains has fundamental consequences for network coding. Theories and modeling studies based on standard Integrate-and-Fire models implicitly assume that, in response to increasingly strong inputs, neurons modify their coding strategy by progressively reducing their selective sensitivity to rapid input fluctuations. Combining mathematical modeling with in vitro experiments, we demonstrate that, in L5 pyramidal neurons, the firing threshold dynamics adaptively adjust the effective timescale of somatic integration in order to preserve sensitivity to rapid signals over a broad range of input statistics. For that, a new Generalized Integrate-and-Fire model featuring nonlinear firing threshold dynamics and conductance-based adaptation is introduced that outperforms state-of-the-art neuron models in predicting the spiking activity of neurons responding to a variety of in vivo-like fluctuating currents. Our model allows for efficient parameter extraction and can be analytically mapped to a Generalized Linear Model in which both the input filter—describing somatic integration—and the spike-history filter—accounting for spike-frequency adaptation—dynamically adapt to the input statistics, as experimentally observed. Overall, our results provide new insights on the computational role of different biophysical processes known to underlie adaptive coding in single neurons and support previous theoretical findings indicating that the nonlinear dynamics of the firing threshold due to Na+-channel inactivation regulate the sensitivity to rapid input fluctuations. PMID:26907675

  10. Mapping an operator's perception of a parameter space

    NASA Technical Reports Server (NTRS)

    Pew, R. W.; Jagacinski, R. J.

    1972-01-01

    Operators monitored the output of two versions of the crossover model having a common random input. Their task was to make discrete, real-time adjustments of the parameters k and tau of one of the models to make its output time history converge to that of the other, fixed model. A plot was obtained of the direction of parameter change as a function of position in the (tau, k) parameter space relative to the nominal value. The plot has a great deal of structure and serves as one form of representation of the operator's perception of the parameter space.

  11. Observer-based perturbation extremum seeking control with input constraints for direct-contact membrane distillation process

    NASA Astrophysics Data System (ADS)

    Eleiwi, Fadi; Laleg-Kirati, Taous Meriem

    2018-06-01

    An observer-based perturbation extremum seeking control is proposed for a direct-contact membrane distillation (DCMD) process. The process is described with a dynamic model that is based on a 2D advection-diffusion equation model which has pump flow rates as process inputs. The objective of the controller is to optimise the trade-off between the permeate mass flux and the energy consumption by the pumps inside the process. Cases of single and multiple control inputs are considered through the use of only the feed pump flow rate or both the feed and the permeate pump flow rates. A nonlinear Lyapunov-based observer is designed to provide an estimation for the temperature distribution all over the designated domain of the DCMD process. Moreover, control inputs are constrained with an anti-windup technique to be within feasible and physical ranges. Performance of the proposed structure is analysed, and simulations based on real DCMD process parameters for each control input are provided.

  12. The SLH framework for modeling quantum input-output networks

    DOE PAGES

    Combes, Joshua; Kerckhoff, Joseph; Sarovar, Mohan

    2017-09-04

    Here, many emerging quantum technologies demand precise engineering and control over networks consisting of quantum mechanical degrees of freedom connected by propagating electromagnetic fields, or quantum input-output networks. Here we review recent progress in theory and experiment related to such quantum input-output networks, with a focus on the SLH framework, a powerful modeling framework for networked quantum systems that is naturally endowed with properties such as modularity and hierarchy. We begin by explaining the physical approximations required to represent any individual node of a network, e.g. atoms in cavity or a mechanical oscillator, and its coupling to quantum fields bymore » an operator triple ( S,L,H). Then we explain how these nodes can be composed into a network with arbitrary connectivity, including coherent feedback channels, using algebraic rules, and how to derive the dynamics of network components and output fields. The second part of the review discusses several extensions to the basic SLH framework that expand its modeling capabilities, and the prospects for modeling integrated implementations of quantum input-output networks. In addition to summarizing major results and recent literature, we discuss the potential applications and limitations of the SLH framework and quantum input-output networks, with the intention of providing context to a reader unfamiliar with the field.« less

  13. The SLH framework for modeling quantum input-output networks

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

    Combes, Joshua; Kerckhoff, Joseph; Sarovar, Mohan

    Here, many emerging quantum technologies demand precise engineering and control over networks consisting of quantum mechanical degrees of freedom connected by propagating electromagnetic fields, or quantum input-output networks. Here we review recent progress in theory and experiment related to such quantum input-output networks, with a focus on the SLH framework, a powerful modeling framework for networked quantum systems that is naturally endowed with properties such as modularity and hierarchy. We begin by explaining the physical approximations required to represent any individual node of a network, e.g. atoms in cavity or a mechanical oscillator, and its coupling to quantum fields bymore » an operator triple ( S,L,H). Then we explain how these nodes can be composed into a network with arbitrary connectivity, including coherent feedback channels, using algebraic rules, and how to derive the dynamics of network components and output fields. The second part of the review discusses several extensions to the basic SLH framework that expand its modeling capabilities, and the prospects for modeling integrated implementations of quantum input-output networks. In addition to summarizing major results and recent literature, we discuss the potential applications and limitations of the SLH framework and quantum input-output networks, with the intention of providing context to a reader unfamiliar with the field.« less

  14. Reactor performance of a 750 m(3) anaerobic digestion plant: varied substrate input conditions impacting methanogenic community.

    PubMed

    Wagner, Andreas Otto; Malin, Cornelia; Lins, Philipp; Gstraunthaler, Gudrun; Illmer, Paul

    2014-10-01

    A 750 m(3) anaerobic digester was studied over a half year period including a shift from good reactor performance to a reduced one. Various abiotic parameters like volatile fatty acids (VFA) (formic-, acetic-, propionic-, (iso-)butyric-, (iso-)valeric-, lactic acid), total C, total N, NH4 -N, and total proteins, as well as the organic matter content and dry mass were determined. In addition several process parameters such as temperature, pH, retention time and input of substrate and the concentrations of CH4, H2, CO2 and H2S within the reactor were monitored continuously. The present study aimed at the investigation of the abundance of acetogens and total cell numbers and the microbial methanogenic community as derived from PCR-dHPLC analysis in order to put it into context with the determined abiotic parameters. An influence of substrate quantity on the efficiency of the anaerobic digestion process was found as well as a shift from a hydrogenotrophic in times of good reactor performance towards an acetoclastic dominated methanogenic community in times of reduced reactor performance. After the change in substrate conditions it took the methano-archaeal community about 5-6 weeks to be affected but then changes occurred quickly. Copyright © 2014 Elsevier Ltd. All rights reserved.

  15. Effects of treadmill training with load addition on non-paretic lower limb on gait parameters after stroke: A randomized controlled clinical trial.

    PubMed

    Ribeiro, Tatiana S; Silva, Emília M G S; Silva, Isaíra A P; Costa, Mayara F P; Cavalcanti, Fabrícia A C; Lindquist, Ana R

    2017-05-01

    The addition of load on the non-paretic lower limb for the purpose of restraining this limb and stimulating the use of the paretic limb has been suggested to improve hemiparetic gait. However, the results are conflicting and only short-term effects have been observed. This study aims to investigate the effects of adding load on non-paretic lower limb during treadmill gait training as a multisession intervention on kinematic gait parameters after stroke. With this aim, 38 subacute stroke patients (mean time since stroke: 4.5 months) were randomly divided into two groups: treadmill training with load (equivalent to 5% of body weight) on the non-paretic ankle (experimental group) and treadmill training without load (control group). Both groups performed treadmill training during 30min per day, for two consecutive weeks (nine sessions). Spatiotemporal and angular gait parameters were assessed by a motion system analysis at baseline, post-training (at the end of 9days of interventions) and follow-up (40days after the end of interventions). Several post-training effects were demonstrated: patients walked faster and with longer paretic and non-paretic steps compared to baseline, and maintained these gains at follow-up. In addition, patients exhibited greater hip and knee joint excursion in both limbs at post-training, while maintaining most of these benefits at follow-up. All these improvements were observed in both groups. Although the proposal gait training program has provided better gait parameters for these subacute stroke patients, our data indicate that load addition used as a restraint may not provide additional benefits to gait training. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. Approach for Input Uncertainty Propagation and Robust Design in CFD Using Sensitivity Derivatives

    NASA Technical Reports Server (NTRS)

    Putko, Michele M.; Taylor, Arthur C., III; Newman, Perry A.; Green, Lawrence L.

    2002-01-01

    An implementation of the approximate statistical moment method for uncertainty propagation and robust optimization for quasi 3-D Euler CFD code is presented. Given uncertainties in statistically independent, random, normally distributed input variables, first- and second-order statistical moment procedures are performed to approximate the uncertainty in the CFD output. Efficient calculation of both first- and second-order sensitivity derivatives is required. In order to assess the validity of the approximations, these moments are compared with statistical moments generated through Monte Carlo simulations. The uncertainties in the CFD input variables are also incorporated into a robust optimization procedure. For this optimization, statistical moments involving first-order sensitivity derivatives appear in the objective function and system constraints. Second-order sensitivity derivatives are used in a gradient-based search to successfully execute a robust optimization. The approximate methods used throughout the analyses are found to be valid when considering robustness about input parameter mean values.

  17. Input Decimated Ensembles

    NASA Technical Reports Server (NTRS)

    Tumer, Kagan; Oza, Nikunj C.; Clancy, Daniel (Technical Monitor)

    2001-01-01

    Using an ensemble of classifiers instead of a single classifier has been shown to improve generalization performance in many pattern recognition problems. However, the extent of such improvement depends greatly on the amount of correlation among the errors of the base classifiers. Therefore, reducing those correlations while keeping the classifiers' performance levels high is an important area of research. In this article, we explore input decimation (ID), a method which selects feature subsets for their ability to discriminate among the classes and uses them to decouple the base classifiers. We provide a summary of the theoretical benefits of correlation reduction, along with results of our method on two underwater sonar data sets, three benchmarks from the Probenl/UCI repositories, and two synthetic data sets. The results indicate that input decimated ensembles (IDEs) outperform ensembles whose base classifiers use all the input features; randomly selected subsets of features; and features created using principal components analysis, on a wide range of domains.

  18. Adaptive control of Parkinson's state based on a nonlinear computational model with unknown parameters.

    PubMed

    Su, Fei; Wang, Jiang; Deng, Bin; Wei, Xi-Le; Chen, Ying-Yuan; Liu, Chen; Li, Hui-Yan

    2015-02-01

    The objective here is to explore the use of adaptive input-output feedback linearization method to achieve an improved deep brain stimulation (DBS) algorithm for closed-loop control of Parkinson's state. The control law is based on a highly nonlinear computational model of Parkinson's disease (PD) with unknown parameters. The restoration of thalamic relay reliability is formulated as the desired outcome of the adaptive control methodology, and the DBS waveform is the control input. The control input is adjusted in real time according to estimates of unknown parameters as well as the feedback signal. Simulation results show that the proposed adaptive control algorithm succeeds in restoring the relay reliability of the thalamus, and at the same time achieves accurate estimation of unknown parameters. Our findings point to the potential value of adaptive control approach that could be used to regulate DBS waveform in more effective treatment of PD.

  19. Robust image retrieval from noisy inputs using lattice associative memories

    NASA Astrophysics Data System (ADS)

    Urcid, Gonzalo; Nieves-V., José Angel; García-A., Anmi; Valdiviezo-N., Juan Carlos

    2009-02-01

    Lattice associative memories also known as morphological associative memories are fully connected feedforward neural networks with no hidden layers, whose computation at each node is carried out with lattice algebra operations. These networks are a relatively recent development in the field of associative memories that has proven to be an alternative way to work with sets of pattern pairs for which the storage and retrieval stages use minimax algebra. Different associative memory models have been proposed to cope with the problem of pattern recall under input degradations, such as occlusions or random noise, where input patterns can be composed of binary or real valued entries. In comparison to these and other artificial neural network memories, lattice algebra based memories display better performance for storage and recall capability; however, the computational techniques devised to achieve that purpose require additional processing or provide partial success when inputs are presented with undetermined noise levels. Robust retrieval capability of an associative memory model is usually expressed by a high percentage of perfect recalls from non-perfect input. The procedure described here uses noise masking defined by simple lattice operations together with appropriate metrics, such as the normalized mean squared error or signal to noise ratio, to boost the recall performance of either the min or max lattice auto-associative memories. Using a single lattice associative memory, illustrative examples are given that demonstrate the enhanced retrieval of correct gray-scale image associations from inputs corrupted with random noise.

  20. Intraglomerular inhibition maintains mitral cell response contrast across input frequencies.

    PubMed

    Shao, Zuoyi; Puche, Adam C; Shipley, Michael T

    2013-11-01

    Odor signals are transmitted to the olfactory bulb by olfactory nerve (ON) synapses onto mitral/tufted cells (MTCs) and external tufted cells (ETCs); ETCs provide additional feed-forward excitation to MTCs. Both are strongly regulated by intraglomerular inhibition that can last up to 1 s and, when blocked, dramatically increases ON-evoked MC spiking. Intraglomerular inhibition thus limits the magnitude and duration of MC spike responses to sensory input. In vivo, sensory input is repetitive, dictated by sniffing rates from 1 to 8 Hz, potentially summing intraglomerular inhibition. To investigate this, we recorded MTC responses to 1- to 8-Hz ON stimulation in slices. Inhibitory postsynaptic current area (charge) following each ON stimulation was unchanged from 1 to 5 Hz and modestly paired-pulse attenuated at 8 Hz, suggesting there is no summation and only limited decrement at the highest input frequencies. Next, we investigated frequency independence of intraglomerular inhibition on MC spiking. MCs respond to single ON shocks with an initial spike burst followed by reduced spiking decaying to baseline. Upon repetitive ON stimulation peak spiking is identical across input frequencies but the ratio of peak-to-minimum rate before the stimulus (max-min) diminishes from 30:1 at 1 Hz to 15:1 at 8 Hz. When intraglomerular inhibition is selectively blocked, peak spike rate is unchanged but trough spiking increases markedly decreasing max-min firing ratios from 30:1 at 1 Hz to 2:1 at 8 Hz. Together, these results suggest intraglomerular inhibition is relatively frequency independent and can "sharpen" MC responses to input across the range of frequencies. This suggests that glomerular circuits can maintain "contrast" in MC encoding during sniff-sampled inputs.

  1. The assessment of body sway and the choice of the stability parameter(s).

    PubMed

    Raymakers, J A; Samson, M M; Verhaar, H J J

    2005-01-01

    This methodological study aims at comparison of the practical usefulness of several parameters of body sway derived from recordings of the center of pressure (CoP) with the aid of a static force platform as proposed in the literature. These included: mean displacement velocity, maximal range of movement along x- and y-co-ordinates, movement area, planar deviation, phase plane parameter of Riley and the parameters of the diffusion stabilogram according to Collins. They were compared in over 850 experiments in a group of young healthy subjects (n = 10, age 21-45 years), a group of elderly healthy (n = 38, age 61-78 years) and two groups of elderly subjects (n = 10 and n = 21, age 65-89 years) with stability problems under different conditions known to interfere with stability as compared to standing with open eyes fixing a visual anchoring point: closing the eyes, standing on plastic foam in stead of a firm surface and performing a cognitive task: the modified stroop test. A force platform (Kistler) was used and co-ordinates of the body's center of pressure were recorded during 60 s of quiet barefoot standing with a sampling frequency of 10 Hz. In general, the results show important overlapping among groups and test conditions. Mean displacement velocity shows the most consistent differences between test situations, health conditions and age ranges, but is not affected by an extra cognitive task in healthy old people. Mean maximal sideways sway range is different among groups and test conditions except for the cognitive task in young and elderly subjects. Standardised displacement parameters such as standard deviations of displacements and planar deviation discriminate less well than the actual range of motion or the velocity. The critical time interval derived from the diffusion stabilogram according to Collins et al. seems to add a specific type of information since it shows significant influence from addition of a cognitive task in old subjects standing on a firm

  2. PM(10) emission forecasting using artificial neural networks and genetic algorithm input variable optimization.

    PubMed

    Antanasijević, Davor Z; Pocajt, Viktor V; Povrenović, Dragan S; Ristić, Mirjana Đ; Perić-Grujić, Aleksandra A

    2013-01-15

    This paper describes the development of an artificial neural network (ANN) model for the forecasting of annual PM(10) emissions at the national level, using widely available sustainability and economical/industrial parameters as inputs. The inputs for the model were selected and optimized using a genetic algorithm and the ANN was trained using the following variables: gross domestic product, gross inland energy consumption, incineration of wood, motorization rate, production of paper and paperboard, sawn wood production, production of refined copper, production of aluminum, production of pig iron and production of crude steel. The wide availability of the input parameters used in this model can overcome a lack of data and basic environmental indicators in many countries, which can prevent or seriously impede PM emission forecasting. The model was trained and validated with the data for 26 EU countries for the period from 1999 to 2006. PM(10) emission data, collected through the Convention on Long-range Transboundary Air Pollution - CLRTAP and the EMEP Programme or as emission estimations by the Regional Air Pollution Information and Simulation (RAINS) model, were obtained from Eurostat. The ANN model has shown very good performance and demonstrated that the forecast of PM(10) emission up to two years can be made successfully and accurately. The mean absolute error for two-year PM(10) emission prediction was only 10%, which is more than three times better than the predictions obtained from the conventional multi-linear regression and principal component regression models that were trained and tested using the same datasets and input variables. Copyright © 2012 Elsevier B.V. All rights reserved.

  3. Research of misalignment between dithered ring laser gyro angle rate input axis and dither axis

    NASA Astrophysics Data System (ADS)

    Li, Geng; Wu, Wenqi; FAN, Zhenfang; LU, Guangfeng; Hu, Shaomin; Luo, Hui; Long, Xingwu

    2014-12-01

    The strap-down inertial navigation system (SINS), especially the SINS composed by dithered ring laser gyroscope (DRLG) is a kind of equipment, which providing high reliability and performance for moving vehicles. However, the mechanical dither which is used to eliminate the "Lock-In" effect can cause vibration disturbance to the INS and lead to dithering coupling problem in the inertial measurement unit (IMU) gyroscope triad, so its further application is limited. Among DRLG errors between the true gyro rotation rate and the measured rotation rate, the frequently considered one is the input axis misalignment between input reference axis which is perpendicular to the mounting surface and gyro angular rate input axis. But the misalignment angle between DRLG dither axis and gyro angular rate input axis is often ignored by researchers, which is amplified by dither coupling problem and that would lead to negative effects especially in high accuracy SINS. In order to study the problem more clearly, the concept of misalignment between DRLG dither axis and gyro angle rate input axis is researched. Considering the error of misalignment is of the order of 10-3 rad. or even smaller, the best way to measure it is using DRLG itself by means of an angle exciter as an auxiliary. In this paper, the concept of dither axis misalignment is explained explicitly firstly, based on this, the frequency of angle exciter is induced as reference parameter, when DRLG is mounted on the angle exciter in a certain angle, the projections of angle exciter rotation rate and mechanical oscillation rate on the gyro input axis are both sensed by DRLG. If the dither axis has misalignment error with the gyro input axis, there will be four major frequencies detected: the frequency of angle exciter, the dither mechanical frequency, sum and difference frequencies of the former two frequencies. Then the amplitude spectrum of DRLG output signal obtained by the using LabVIEW program. if there are only angle

  4. Sensitivity analysis of respiratory parameter uncertainties: impact of criterion function form and constraints.

    PubMed

    Lutchen, K R

    1990-08-01

    A sensitivity analysis based on weighted least-squares regression is presented to evaluate alternative methods for fitting lumped-parameter models to respiratory impedance data. The goal is to maintain parameter accuracy simultaneously with practical experiment design. The analysis focuses on predicting parameter uncertainties using a linearized approximation for joint confidence regions. Applications are with four-element parallel and viscoelastic models for 0.125- to 4-Hz data and a six-element model with separate tissue and airway properties for input and transfer impedance data from 2-64 Hz. The criterion function form was evaluated by comparing parameter uncertainties when data are fit as magnitude and phase, dynamic resistance and compliance, or real and imaginary parts of input impedance. The proper choice of weighting can make all three criterion variables comparable. For the six-element model, parameter uncertainties were predicted when both input impedance and transfer impedance are acquired and fit simultaneously. A fit to both data sets from 4 to 64 Hz could reduce parameter estimate uncertainties considerably from those achievable by fitting either alone. For the four-element models, use of an independent, but noisy, measure of static compliance was assessed as a constraint on model parameters. This may allow acceptable parameter uncertainties for a minimum frequency of 0.275-0.375 Hz rather than 0.125 Hz. This reduces data acquisition requirements from a 16- to a 5.33- to 8-s breath holding period. These results are approximations, and the impact of using the linearized approximation for the confidence regions is discussed.

  5. MDS MIC Catalog Inputs

    NASA Technical Reports Server (NTRS)

    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.

  6. High Input Voltage, Silicon Carbide Power Processing Unit Performance Demonstration

    NASA Technical Reports Server (NTRS)

    Bozak, Karin E.; Pinero, Luis R.; Scheidegger, Robert J.; Aulisio, Michael V.; Gonzalez, Marcelo C.; Birchenough, Arthur G.

    2015-01-01

    A silicon carbide brassboard power processing unit has been developed by the NASA Glenn Research Center in Cleveland, Ohio. The power processing unit operates from two sources: a nominal 300 Volt high voltage input bus and a nominal 28 Volt low voltage input bus. The design of the power processing unit includes four low voltage, low power auxiliary supplies, and two parallel 7.5 kilowatt (kW) discharge power supplies that are capable of providing up to 15 kilowatts of total power at 300 to 500 Volts (V) to the thruster. Additionally, the unit contains a housekeeping supply, high voltage input filter, low voltage input filter, and master control board, such that the complete brassboard unit is capable of operating a 12.5 kilowatt Hall effect thruster. The performance of the unit was characterized under both ambient and thermal vacuum test conditions, and the results demonstrate exceptional performance with full power efficiencies exceeding 97%. The unit was also tested with a 12.5kW Hall effect thruster to verify compatibility and output filter specifications. With space-qualified silicon carbide or similar high voltage, high efficiency power devices, this would provide a design solution to address the need for high power electric propulsion systems.

  7. GABAergic circuits control input-spike coupling in the piriform cortex.

    PubMed

    Luna, Victor M; Schoppa, Nathan E

    2008-08-27

    Odor coding in mammals is widely believed to involve synchronized gamma frequency (30-70 Hz) oscillations in the first processing structure, the olfactory bulb. How such inputs are read in downstream cortical structures however is not known. Here we used patch-clamp recordings in rat piriform cortex slices to examine cellular mechanisms that shape how the cortex integrates inputs from bulb mitral cells. Electrical stimulation of mitral cell axons in the lateral olfactory tract (LOT) resulted in excitation of pyramidal cells (PCs), which was followed approximately 10 ms later by inhibition that was highly reproducible between trials in its onset time. This inhibition was somatic in origin and appeared to be driven through a feedforward mechanism, wherein GABAergic interneurons were directly excited by mitral cell axons. The precise inhibition affected action potential firing in PCs in two distinct ways. First, by abruptly terminating PC excitation, it limited the PC response to each EPSP to exactly one, precisely timed action potential. In addition, inhibition limited the summation of EPSPs across time, such that PCs fired action potentials in strong preference for synchronized inputs arriving in a time window of <5 ms. Both mechanisms would help ensure that PCs respond faithfully and selectively to mitral cell inputs arriving as a synchronized gamma frequency pattern.

  8. Financial analysis of biogas utilization : input cattle, pig feces and coffee waste in Karo, Indonesia

    NASA Astrophysics Data System (ADS)

    Ginting, N.; Zuhri, F.; Hasnudi; Mirwandhono, E.; Sembiring, I.; Daulay, A. H.

    2018-02-01

    The community's need for renewable energy was very urgent. In addition, efforts to preserve the environment from waste caused biogas technology feasible to apply. This study aims to provide biogas technology with minimal cost and utilize agricultural waste that were coffee and livestock waste. The study was conducted from July to October 2016. The theoretical and empirical methods used in this study were included data from officials resources, field survey on 16 biogas locations, focus group discussion and interview with stake holders. Data were tabulated by Excel Program which then were analysed by SAS. Parameters were included Production Cost, Production Result, Profit Loss Analysis, Revenue Cost Ratio (R/C Ratio), Return On Investment (ROI), Net B/C, and IRR. The result of this research showed that the application of bioplastic gas with cow dung and coffee waste as bioplasticgas input cause the best results.

  9. Sinusoidal input describing function for hysteresis followed by elementary backlash

    NASA Technical Reports Server (NTRS)

    Ringland, R. F.

    1976-01-01

    The author proposes a new sinusoidal input describing function which accounts for the serial combination of hysteresis followed by elementary backlash in a single nonlinear element. The output of the hysteresis element drives the elementary backlash element. Various analytical forms of the describing function are given, depending on the a/A ratio, where a is the half width of the hysteresis band or backlash gap, and A is the amplitude of the assumed input sinusoid, and on the value of the parameter representing the fraction of a attributed to the backlash characteristic. The negative inverse describing function is plotted on a gain-phase plot, and it is seen that a relatively small amount of backlash leads to domination of the backlash character in the describing function. The extent of the region of the gain-phase plane covered by the describing function is such as to guarantee some form of limit cycle behavior in most closed-loop systems.

  10. Visual exploration of parameter influence on phylogenetic trees.

    PubMed

    Hess, Martin; Bremm, Sebastian; Weissgraeber, Stephanie; Hamacher, Kay; Goesele, Michael; Wiemeyer, Josef; von Landesberger, Tatiana

    2014-01-01

    Evolutionary relationships between organisms are frequently derived as phylogenetic trees inferred from multiple sequence alignments (MSAs). The MSA parameter space is exponentially large, so tens of thousands of potential trees can emerge for each dataset. A proposed visual-analytics approach can reveal the parameters' impact on the trees. Given input trees created with different parameter settings, it hierarchically clusters the trees according to their structural similarity. The most important clusters of similar trees are shown together with their parameters. This view offers interactive parameter exploration and automatic identification of relevant parameters. Biologists applied this approach to real data of 16S ribosomal RNA and protein sequences of ion channels. It revealed which parameters affected the tree structures. This led to a more reliable selection of the best trees.

  11. An open tool for input function estimation and quantification of dynamic PET FDG brain scans.

    PubMed

    Bertrán, Martín; Martínez, Natalia; Carbajal, Guillermo; Fernández, Alicia; Gómez, Álvaro

    2016-08-01

    Positron emission tomography (PET) analysis of clinical studies is mostly restricted to qualitative evaluation. Quantitative analysis of PET studies is highly desirable to be able to compute an objective measurement of the process of interest in order to evaluate treatment response and/or compare patient data. But implementation of quantitative analysis generally requires the determination of the input function: the arterial blood or plasma activity which indicates how much tracer is available for uptake in the brain. The purpose of our work was to share with the community an open software tool that can assist in the estimation of this input function, and the derivation of a quantitative map from the dynamic PET study. Arterial blood sampling during the PET study is the gold standard method to get the input function, but is uncomfortable and risky for the patient so it is rarely used in routine studies. To overcome the lack of a direct input function, different alternatives have been devised and are available in the literature. These alternatives derive the input function from the PET image itself (image-derived input function) or from data gathered from previous similar studies (population-based input function). In this article, we present ongoing work that includes the development of a software tool that integrates several methods with novel strategies for the segmentation of blood pools and parameter estimation. The tool is available as an extension to the 3D Slicer software. Tests on phantoms were conducted in order to validate the implemented methods. We evaluated the segmentation algorithms over a range of acquisition conditions and vasculature size. Input function estimation algorithms were evaluated against ground truth of the phantoms, as well as on their impact over the final quantification map. End-to-end use of the tool yields quantification maps with [Formula: see text] relative error in the estimated influx versus ground truth on phantoms. The main

  12. A variational approach to parameter estimation in ordinary differential equations.

    PubMed

    Kaschek, Daniel; Timmer, Jens

    2012-08-14

    Ordinary differential equations are widely-used in the field of systems biology and chemical engineering to model chemical reaction networks. Numerous techniques have been developed to estimate parameters like rate constants, initial conditions or steady state concentrations from time-resolved data. In contrast to this countable set of parameters, the estimation of entire courses of network components corresponds to an innumerable set of parameters. The approach presented in this work is able to deal with course estimation for extrinsic system inputs or intrinsic reactants, both not being constrained by the reaction network itself. Our method is based on variational calculus which is carried out analytically to derive an augmented system of differential equations including the unconstrained components as ordinary state variables. Finally, conventional parameter estimation is applied to the augmented system resulting in a combined estimation of courses and parameters. The combined estimation approach takes the uncertainty in input courses correctly into account. This leads to precise parameter estimates and correct confidence intervals. In particular this implies that small motifs of large reaction networks can be analysed independently of the rest. By the use of variational methods, elements from control theory and statistics are combined allowing for future transfer of methods between the two fields.

  13. Optimization of multilayer neural network parameters for speaker recognition

    NASA Astrophysics Data System (ADS)

    Tovarek, Jaromir; Partila, Pavol; Rozhon, Jan; Voznak, Miroslav; Skapa, Jan; Uhrin, Dominik; Chmelikova, Zdenka

    2016-05-01

    This article discusses the impact of multilayer neural network parameters for speaker identification. The main task of speaker identification is to find a specific person in the known set of speakers. It means that the voice of an unknown speaker (wanted person) belongs to a group of reference speakers from the voice database. One of the requests was to develop the text-independent system, which means to classify wanted person regardless of content and language. Multilayer neural network has been used for speaker identification in this research. Artificial neural network (ANN) needs to set parameters like activation function of neurons, steepness of activation functions, learning rate, the maximum number of iterations and a number of neurons in the hidden and output layers. ANN accuracy and validation time are directly influenced by the parameter settings. Different roles require different settings. Identification accuracy and ANN validation time were evaluated with the same input data but different parameter settings. The goal was to find parameters for the neural network with the highest precision and shortest validation time. Input data of neural networks are a Mel-frequency cepstral coefficients (MFCC). These parameters describe the properties of the vocal tract. Audio samples were recorded for all speakers in a laboratory environment. Training, testing and validation data set were split into 70, 15 and 15 %. The result of the research described in this article is different parameter setting for the multilayer neural network for four speakers.

  14. Verification Techniques for Parameter Selection and Bayesian Model Calibration Presented for an HIV Model

    NASA Astrophysics Data System (ADS)

    Wentworth, Mami Tonoe

    Uncertainty quantification plays an important role when making predictive estimates of model responses. In this context, uncertainty quantification is defined as quantifying and reducing uncertainties, and the objective is to quantify uncertainties in parameter, model and measurements, and propagate the uncertainties through the model, so that one can make a predictive estimate with quantified uncertainties. Two of the aspects of uncertainty quantification that must be performed prior to propagating uncertainties are model calibration and parameter selection. There are several efficient techniques for these processes; however, the accuracy of these methods are often not verified. This is the motivation for our work, and in this dissertation, we present and illustrate verification frameworks for model calibration and parameter selection in the context of biological and physical models. First, HIV models, developed and improved by [2, 3, 8], describe the viral infection dynamics of an HIV disease. These are also used to make predictive estimates of viral loads and T-cell counts and to construct an optimal control for drug therapy. Estimating input parameters is an essential step prior to uncertainty quantification. However, not all the parameters are identifiable, implying that they cannot be uniquely determined by the observations. These unidentifiable parameters can be partially removed by performing parameter selection, a process in which parameters that have minimal impacts on the model response are determined. We provide verification techniques for Bayesian model calibration and parameter selection for an HIV model. As an example of a physical model, we employ a heat model with experimental measurements presented in [10]. A steady-state heat model represents a prototypical behavior for heat conduction and diffusion process involved in a thermal-hydraulic model, which is a part of nuclear reactor models. We employ this simple heat model to illustrate verification

  15. The effect of word prediction settings (frequency of use) on text input speed in persons with cervical spinal cord injury: a prospective study.

    PubMed

    Pouplin, Samuel; Roche, Nicolas; Antoine, Jean-Yves; Vaugier, Isabelle; Pottier, Sandra; Figere, Marjorie; Bensmail, Djamel

    2017-06-01

    To determine whether activation of the frequency of use and automatic learning parameters of word prediction software has an impact on text input speed. Forty-five participants with cervical spinal cord injury between C4 and C8 Asia A or B accepted to participate to this study. Participants were separated in two groups: a high lesion group for participants with lesion level is at or above C5 Asia AIS A or B and a low lesion group for participants with lesion is between C6 and C8 Asia AIS A or B. A single evaluation session was carried out for each participant. Text input speed was evaluated during three copying tasks: • without word prediction software (WITHOUT condition) • with automatic learning of words and frequency of use deactivated (NOT_ACTIV condition) • with automatic learning of words and frequency of use activated (ACTIV condition) Results: Text input speed was significantly higher in the WITHOUT than the NOT_ACTIV (p< 0.001) or ACTIV conditions (p = 0.02) for participants with low lesions. Text input speed was significantly higher in the ACTIV than in the NOT_ACTIV (p = 0.002) or WITHOUT (p < 0.001) conditions for participants with high lesions. Use of word prediction software with the activation of frequency of use and automatic learning increased text input speed in participants with high-level tetraplegia. For participants with low-level tetraplegia, the use of word prediction software with frequency of use and automatic learning activated only decreased the number of errors. Implications in rehabilitation   Access to technology can be difficult for persons with disabilities such as cervical spinal cord injury (SCI). Several methods have been developed to increase text input speed such as word prediction software.This study show that parameter of word prediction software (frequency of use) affected text input speed in persons with cervical SCI and differed according to the level of the lesion. • For persons with high

  16. Input filter compensation for switching regulators

    NASA Technical Reports Server (NTRS)

    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.

  17. A one-model approach based on relaxed combinations of inputs for evaluating input congestion in DEA

    NASA Astrophysics Data System (ADS)

    Khodabakhshi, Mohammad

    2009-08-01

    This paper provides a one-model approach of input congestion based on input relaxation model developed in data envelopment analysis (e.g. [G.R. Jahanshahloo, M. Khodabakhshi, Suitable combination of inputs for improving outputs in DEA with determining input congestion -- Considering textile industry of China, Applied Mathematics and Computation (1) (2004) 263-273; G.R. Jahanshahloo, M. Khodabakhshi, Determining assurance interval for non-Archimedean ele improving outputs model in DEA, Applied Mathematics and Computation 151 (2) (2004) 501-506; M. Khodabakhshi, A super-efficiency model based on improved outputs in data envelopment analysis, Applied Mathematics and Computation 184 (2) (2007) 695-703; M. Khodabakhshi, M. Asgharian, An input relaxation measure of efficiency in stochastic data analysis, Applied Mathematical Modelling 33 (2009) 2010-2023]. This approach reduces solving three problems with the two-model approach introduced in the first of the above-mentioned reference to two problems which is certainly important from computational point of view. The model is applied to a set of data extracted from ISI database to estimate input congestion of 12 Canadian business schools.

  18. Hydrological model parameter dimensionality is a weak measure of prediction uncertainty

    NASA Astrophysics Data System (ADS)

    Pande, S.; Arkesteijn, L.; Savenije, H.; Bastidas, L. A.

    2015-04-01

    This paper shows that instability of hydrological system representation in response to different pieces of information and associated prediction uncertainty is a function of model complexity. After demonstrating the connection between unstable model representation and model complexity, complexity is analyzed in a step by step manner. This is done measuring differences between simulations of a model under different realizations of input forcings. Algorithms are then suggested to estimate model complexity. Model complexities of the two model structures, SAC-SMA (Sacramento Soil Moisture Accounting) and its simplified version SIXPAR (Six Parameter Model), are computed on resampled input data sets from basins that span across the continental US. The model complexities for SIXPAR are estimated for various parameter ranges. It is shown that complexity of SIXPAR increases with lower storage capacity and/or higher recession coefficients. Thus it is argued that a conceptually simple model structure, such as SIXPAR, can be more complex than an intuitively more complex model structure, such as SAC-SMA for certain parameter ranges. We therefore contend that magnitudes of feasible model parameters influence the complexity of the model selection problem just as parameter dimensionality (number of parameters) does and that parameter dimensionality is an incomplete indicator of stability of hydrological model selection and prediction problems.

  19. Information processing in dendrites I. Input pattern generalisation.

    PubMed

    Gurney, K N

    2001-10-01

    In this paper and its companion, we address the question as to whether there are any general principles underlying information processing in the dendritic trees of biological neurons. In order to address this question, we make two assumptions. First, the key architectural feature of dendrites responsible for many of their information processing abilities is the existence of independent sub-units performing local non-linear processing. Second, any general functional principles operate at a level of abstraction in which neurons are modelled by Boolean functions. To accommodate these assumptions, we therefore define a Boolean model neuron-the multi-cube unit (MCU)-which instantiates the notion of the discrete functional sub-unit. We then use this model unit to explore two aspects of neural functionality: generalisation (in this paper) and processing complexity (in its companion). Generalisation is dealt with from a geometric viewpoint and is quantified using a new metric-the set of order parameters. These parameters are computed for threshold logic units (TLUs), a class of random Boolean functions, and MCUs. Our interpretation of the order parameters is consistent with our knowledge of generalisation in TLUs and with the lack of generalisation in randomly chosen functions. Crucially, the order parameters for MCUs imply that these functions possess a range of generalisation behaviour. We argue that this supports the general thesis that dendrites facilitate input pattern generalisation despite any local non-linear processing within functionally isolated sub-units.

  20. Stochastic multi-objective auto-optimization for resource allocation decision-making in fixed-input health systems.

    PubMed

    Bastian, Nathaniel D; Ekin, Tahir; Kang, Hyojung; Griffin, Paul M; Fulton, Lawrence V; Grannan, Benjamin C

    2017-06-01

    The management of hospitals within fixed-input health systems such as the U.S. Military Health System (MHS) can be challenging due to the large number of hospitals, as well as the uncertainty in input resources and achievable outputs. This paper introduces a stochastic multi-objective auto-optimization model (SMAOM) for resource allocation decision-making in fixed-input health systems. The model can automatically identify where to re-allocate system input resources at the hospital level in order to optimize overall system performance, while considering uncertainty in the model parameters. The model is applied to 128 hospitals in the three services (Air Force, Army, and Navy) in the MHS using hospital-level data from 2009 - 2013. The results are compared to the traditional input-oriented variable returns-to-scale Data Envelopment Analysis (DEA) model. The application of SMAOM to the MHS increases the expected system-wide technical efficiency by 18 % over the DEA model while also accounting for uncertainty of health system inputs and outputs. The developed method is useful for decision-makers in the Defense Health Agency (DHA), who have a strategic level objective of integrating clinical and business processes through better sharing of resources across the MHS and through system-wide standardization across the services. It is also less sensitive to data outliers or sampling errors than traditional DEA methods.

  1. Intraglomerular inhibition maintains mitral cell response contrast across input frequencies

    PubMed Central

    Shao, Zuoyi; Puche, Adam C.

    2013-01-01

    Odor signals are transmitted to the olfactory bulb by olfactory nerve (ON) synapses onto mitral/tufted cells (MTCs) and external tufted cells (ETCs); ETCs provide additional feed-forward excitation to MTCs. Both are strongly regulated by intraglomerular inhibition that can last up to 1 s and, when blocked, dramatically increases ON-evoked MC spiking. Intraglomerular inhibition thus limits the magnitude and duration of MC spike responses to sensory input. In vivo, sensory input is repetitive, dictated by sniffing rates from 1 to 8 Hz, potentially summing intraglomerular inhibition. To investigate this, we recorded MTC responses to 1- to 8-Hz ON stimulation in slices. Inhibitory postsynaptic current area (charge) following each ON stimulation was unchanged from 1 to 5 Hz and modestly paired-pulse attenuated at 8 Hz, suggesting there is no summation and only limited decrement at the highest input frequencies. Next, we investigated frequency independence of intraglomerular inhibition on MC spiking. MCs respond to single ON shocks with an initial spike burst followed by reduced spiking decaying to baseline. Upon repetitive ON stimulation peak spiking is identical across input frequencies but the ratio of peak-to-minimum rate before the stimulus (max-min) diminishes from 30:1 at 1 Hz to 15:1 at 8 Hz. When intraglomerular inhibition is selectively blocked, peak spike rate is unchanged but trough spiking increases markedly decreasing max-min firing ratios from 30:1 at 1 Hz to 2:1 at 8 Hz. Together, these results suggest intraglomerular inhibition is relatively frequency independent and can “sharpen” MC responses to input across the range of frequencies. This suggests that glomerular circuits can maintain “contrast” in MC encoding during sniff-sampled inputs. PMID:23926045

  2. Agricultural management affects below ground carbon input estimations

    NASA Astrophysics Data System (ADS)

    Hirte, Juliane; Leifeld, Jens; Abiven, Samuel; Oberholzer, Hans-Rudolf; Mayer, Jochen

    2017-04-01

    Root biomass and rhizodeposition carbon (C release by living roots) are among the most relevant root parameters for studies of plant response to environmental change, soil C modelling or estimations of soil C sequestration. Below ground C inputs of agricultural crops are typically estimated from above ground biomass or yield, thereby implying constant below to above ground C ratios. Agricultural management practices affect above ground biomass considerably; however, their effects on below ground C inputs are only poorly understood. Our aims were therefore to (i) quantify root biomass C and rhizodeposition C of maize and wheat grown in agricultural management systems with different fertilization intensities and (ii) determine management effects on below/above ground C ratios and vertical distribution of below ground C inputs into soil. We conducted a comprehensive field study on two Swiss long-term field trials, DOK (Basel) and ZOFE (Zurich), with silage (DOK) and grain (ZOFE) maize in 2013 and winter wheat in 2014 (ZOFE) and 2015 (DOK). Three treatments in DOK (2 bio-organic, 1 mixed conventional) and 4 treatments in ZOFE (1 without, 1 manure, 2 mineral fertilization) reflected increasing fertilization intensities. In each of 4 replicated field plots per treatment, one microplot (steel tube of 0.5m depth) was inserted into soil, covering an area of 0.1m2. The microplot plants were pulse-labelled with 13C-CO2 in weekly intervals throughout the respective growing season. After harvest, the microplot soil was sampled in three soil depths (0 - 0.25, 0.25 - 0.5, 0.5 - 0.75m), roots were separated from soil by picking and wet sieving, and root and soil samples were analysed for their δ13C values by IRMS. Carbon rhizodeposition was calculated from 13C-excess values in bulk soil and roots. (i) Average root biomasses of maize and wheat were 1.9 and 1.4 tha 1, respectively, in DOK and 0.9 and 1.1 tha 1, respectively, in ZOFE. Average amounts of C rhizodeposition of maize

  3. Effective time closures: quantifying the conservation benefits of input control for the Pacific chub mackerel fishery.

    PubMed

    Ichinokawa, Momoko; Okamura, Hiroshi; Watanabe, Chikako; Kawabata, Atsushi; Oozeki, Yoshioki

    2015-09-01

    Restricting human access to a specific wildlife species, community, or ecosystem, i.e., input control, is one of the most popular tools to control human impacts for natural resource management and wildlife conservation. However, quantitative evaluations of input control are generally difficult, because it is unclear how much human impacts can actually be reduced by the control. We present a model framework to quantify the effectiveness of input control using day closures to reduce actual fishing impact by considering the observed fishery dynamics. The model framework was applied to the management of the Pacific stock of the chub mackerel (Scomber japonicus) fishery, in which fishing was suspended for one day following any day when the total mackerel catch exceeded a threshold level. We evaluated the management measure according to the following steps: (1) we fitted the daily observed catch and fishing effort data to a generalized linear model (GLM) or generalized autoregressive state-space model (GASSM), (2) we conducted population dynamics simulations based on annual catches randomly generated from the parameters estimated in the first step, (3) we quantified the effectiveness of day closures by comparing the results of two simulation scenarios with and without day closures, and (4) we conducted additional simulations based on different sets of explanatory variables and statistical models (sensitivity analysis). In the first step, we found that the GASSM explained the observed data far better than the simple GLM. The model parameterized with the estimates from the GASSM demonstrated that the day closures implemented from 2004 to 2009 would have decreased exploitation fractions by ~10% every year and increased the 2009 stock biomass by 37-46% (median), relative to the values without day closures. The sensitivity analysis revealed that the effectiveness of day closures was particularly influenced by autoregressive processes in the fishery data and by positive

  4. Optimization of mass spectrometry acquisition parameters for determination of polycarbonate additives, degradation products, and colorants migrating from food contact materials to chocolate.

    PubMed

    Bignardi, Chiara; Cavazza, Antonella; Laganà, Carmen; Salvadeo, Paola; Corradini, Claudio

    2018-01-01

    The interest towards "substances of emerging concerns" referred to objects intended to come into contact with food is recently growing. Such substances can be found in traces in simulants and in food products put in contact with plastic materials. In this context, it is important to set up analytical systems characterized by high sensitivity and to improve detection parameters to enhance signals. This work was aimed at optimizing a method based on UHPLC coupled to high resolution mass spectrometry to quantify the most common plastic additives, and able to detect the presence of polymers degradation products and coloring agents migrating from plastic re-usable containers. The optimization of mass spectrometric parameter settings for quantitative analysis of additives has been achieved by a chemometric approach, using a full factorial and d-optimal experimental designs, allowing to evaluate possible interactions between the investigated parameters. Results showed that the optimized method was characterized by improved features in terms of sensitivity respect to existing methods and was successfully applied to the analysis of a complex model food system such as chocolate put in contact with 14 polycarbonate tableware samples. A new procedure for sample pre-treatment was carried out and validated, showing high reliability. Results reported, for the first time, the presence of several molecules migrating to chocolate, in particular belonging to plastic additives, such Cyasorb UV5411, Tinuvin 234, Uvitex OB, and oligomers, whose amount was found to be correlated to age and degree of damage of the containers. Copyright © 2017 John Wiley & Sons, Ltd.

  5. World Input-Output Network

    PubMed Central

    Cerina, Federica; Zhu, Zhen; Chessa, Alessandro; Riccaboni, Massimo

    2015-01-01

    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. PMID:26222389

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

    NASA Astrophysics Data System (ADS)

    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

  7. Input Devices for Young Handicapped Children.

    ERIC Educational Resources Information Center

    Morris, Karen

    The versatility of the computer can be expanded considerably for young handicapped children by using input devices other than the typewriter-style keyboard. Input devices appropriate for young children can be classified into four categories: alternative keyboards, contact switches, speech input devices, and cursor control devices. Described are…

  8. Real-Time Parameter Estimation in the Frequency Domain

    NASA Technical Reports Server (NTRS)

    Morelli, Eugene A.

    2000-01-01

    A method for real-time estimation of parameters in a linear dynamic state-space model was developed and studied. The application is aircraft dynamic model parameter estimation from measured data in flight. Equation error in the frequency domain was used with a recursive Fourier transform for the real-time data analysis. Linear and nonlinear simulation examples and flight test data from the F-18 High Alpha Research Vehicle were used to demonstrate that the technique produces accurate model parameter estimates with appropriate error bounds. Parameter estimates converged in less than one cycle of the dominant dynamic mode, using no a priori information, with control surface inputs measured in flight during ordinary piloted maneuvers. The real-time parameter estimation method has low computational requirements and could be implemented

  9. Parameter identifiability of linear dynamical systems

    NASA Technical Reports Server (NTRS)

    Glover, K.; Willems, J. C.

    1974-01-01

    It is assumed that the system matrices of a stationary linear dynamical system were parametrized by a set of unknown parameters. The question considered here is, when can such a set of unknown parameters be identified from the observed data? Conditions for the local identifiability of a parametrization are derived in three situations: (1) when input/output observations are made, (2) when there exists an unknown feedback matrix in the system and (3) when the system is assumed to be driven by white noise and only output observations are made. Also a sufficient condition for global identifiability is derived.

  10. A novel feedforward compensation canceling input filter-regulator interaction

    NASA Technical Reports Server (NTRS)

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

    1983-01-01

    The interaction between the input and the control loop of switching regulators often results in deterimental effects, such as loop instability, degradation of transient response, and audiosusceptibility, etc. The concept of pole-zero cancelation is employed to mitigate some of these detrimental effects and is implemented using a novel feedforward loop, in addition to existing feedback loops of a buck regulator. Experimental results are presented which show excellent correlation with theory.

  11. Observer-Based Adaptive NN Control for a Class of Uncertain Nonlinear Systems With Nonsymmetric Input Saturation.

    PubMed

    Yong-Feng Gao; Xi-Ming Sun; Changyun Wen; Wei Wang

    2017-07-01

    This paper is concerned with the problem of adaptive tracking control for a class of uncertain nonlinear systems with nonsymmetric input saturation and immeasurable states. The radial basis function of neural network (NN) is employed to approximate unknown functions, and an NN state observer is designed to estimate the immeasurable states. To analyze the effect of input saturation, an auxiliary system is employed. By the aid of adaptive backstepping technique, an adaptive tracking control approach is developed. Under the proposed adaptive tracking controller, the boundedness of all the signals in the closed-loop system is achieved. Moreover, distinct from most of the existing references, the tracking error can be bounded by an explicit function of design parameters and saturation input error. Finally, an example is given to show the effectiveness of the proposed method.

  12. The effect of changes in space shuttle parameters on the NASA/MSFC multilayer diffusion model predictions of surface HCl concentrations

    NASA Technical Reports Server (NTRS)

    Glasser, M. E.; Rundel, R. D.

    1978-01-01

    A method for formulating these changes into the model input parameters using a preprocessor program run on a programed data processor was implemented. The results indicate that any changes in the input parameters are small enough to be negligible in comparison to meteorological inputs and the limitations of the model and that such changes will not substantially increase the number of meteorological cases for which the model will predict surface hydrogen chloride concentrations exceeding public safety levels.

  13. Land and Water Use Characteristics and Human Health Input Parameters for use in Environmental Dosimetry and Risk Assessments at the Savannah River Site. 2016 Update

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

    Jannik, G. Tim; Hartman, Larry; Stagich, Brooke

    Operations at the Savannah River Site (SRS) result in releases of small amounts of radioactive materials to the atmosphere and to the Savannah River. For regulatory compliance purposes, potential offsite radiological doses are estimated annually using computer models that follow U.S. Nuclear Regulatory Commission (NRC) regulatory guides. Within the regulatory guides, default values are provided for many of the dose model parameters, but the use of applicant site-specific values is encouraged. Detailed surveys of land-use and water-use parameters were conducted in 1991 and 2010. They are being updated in this report. These parameters include local characteristics of meat, milk andmore » vegetable production; river recreational activities; and meat, milk and vegetable consumption rates, as well as other human usage parameters required in the SRS dosimetry models. In addition, the preferred elemental bioaccumulation factors and transfer factors (to be used in human health exposure calculations at SRS) are documented. The intent of this report is to establish a standardized source for these parameters that is up to date with existing data, and that is maintained via review of future-issued national references (to evaluate the need for changes as new information is released). These reviews will continue to be added to this document by revision.« less

  14. Study on the effect of hydrogen addition on the variation of plasma parameters of argon-oxygen magnetron glow discharge for synthesis of TiO{sub 2} films

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

    Saikia, Partha, E-mail: partha.008@gmail.com; Institute of Physics, Pontificia Universidad Católica de Chile, Av. Vicuña Mackenna 4860, Santiago; Saikia, Bipul Kumar

    2016-04-15

    We report the effect of hydrogen addition on plasma parameters of argon-oxygen magnetron glow discharge plasma in the synthesis of H-doped TiO{sub 2} films. The parameters of the hydrogen-added Ar/O{sub 2} plasma influence the properties and the structural phases of the deposited TiO{sub 2} film. Therefore, the variation of plasma parameters such as electron temperature (T{sub e}), electron density (n{sub e}), ion density (n{sub i}), degree of ionization of Ar and degree of dissociation of H{sub 2} as a function of hydrogen content in the discharge is studied. Langmuir probe and Optical emission spectroscopy are used to characterize the plasma.more » On the basis of the different reactions in the gas phase of the magnetron discharge, the variation of plasma parameters and sputtering rate are explained. It is observed that the electron and heavy ion density decline with gradual addition of hydrogen in the discharge. Hydrogen addition significantly changes the degree of ionization of Ar which influences the structural phases of the TiO{sub 2} film.« less

  15. Estimating parameters with pre-specified accuracies in distributed parameter systems using optimal experiment design

    NASA Astrophysics Data System (ADS)

    Potters, M. G.; Bombois, X.; Mansoori, M.; Hof, Paul M. J. Van den

    2016-08-01

    Estimation of physical parameters in dynamical systems driven by linear partial differential equations is an important problem. In this paper, we introduce the least costly experiment design framework for these systems. It enables parameter estimation with an accuracy that is specified by the experimenter prior to the identification experiment, while at the same time minimising the cost of the experiment. We show how to adapt the classical framework for these systems and take into account scaling and stability issues. We also introduce a progressive subdivision algorithm that further generalises the experiment design framework in the sense that it returns the lowest cost by finding the optimal input signal, and optimal sensor and actuator locations. Our methodology is then applied to a relevant problem in heat transfer studies: estimation of conductivity and diffusivity parameters in front-face experiments. We find good correspondence between numerical and theoretical results.

  16. Drivers from the deep: the contribution of collicular input to thalamocortical processing.

    PubMed

    Wurtz, Robert H; Sommer, Marc A; Cavanaugh, James

    2005-01-01

    A traditional view of the thalamus is that it is a relay station which receives sensory input and conveys this information to cortex. This sensory input determines most of the properties of first order thalamic neurons, and so is said to drive, rather than modulate, these neurons. This holds as a rule for first order thalamic nuclei, but in contrast, higher order thalamic nuclei receive much of their driver input back from cerebral cortex. In addition, higher order thalamic neurons receive inputs from subcortical movement-related centers. In the terminology popularized from studies of the sensory system, can we consider these ascending motor inputs to thalamus from subcortical structures to be modulators, subtly influencing the activity of their target neurons, or drivers, dictating the activity of their target neurons? This chapter summarizes relevant evidence from neuronal recording, inactivation, and stimulation of pathways projecting from the superior colliculus through thalamus to cerebral cortex. The study concludes that many inputs to the higher order nuclei of the thalamus from subcortical oculomotor areas - from the superior colliculus and probably other midbrain and pontine regions - should be regarded as motor drivers analogous to the sensory drivers at the first order thalamic nuclei. These motor drivers at the thalamus are viewed as being at the top of a series of feedback loops that provide information on impending actions, just as sensory drivers provide information about the external environment.

  17. Concept of modernization of input device of oil and gas separator

    NASA Astrophysics Data System (ADS)

    Feodorov, A. B.; Afanasov, V. I.; Miroshnikov, R. S.; Bogachev, V. V.

    2017-10-01

    The process of defoaming in oil production is discussed. This technology is important in oil and gas fields. Today, the technology of separating the gas fraction is based on chemical catalysis. The use of mechanical technologies improves the economics of the process. Modernization of the separator input device is based on the use of long thin tubes. The chosen length of the tubes is two orders of magnitude larger than the diameter. The separation problem is solved by creating a high centrifugal acceleration. The tubes of the input device are connected in parallel and divide the input stream into several arms. The separated fluid flows are directed tangentially into the working tubes to create a vortex motion. The number of tubes connected in parallel is calculated in accordance with the flow rate of the fluid. The connection of the working tubes to the supply line is made in the form of a flange. This connection allows carrying out maintenance without stopping the flow of fluid. An important feature of this device is its high potential for further modernization. It is concerned with the determination of the parameters of the tubes and the connection geometry in the construction of a single product.

  18. Investigation, sensitivity analysis, and multi-objective optimization of effective parameters on temperature and force in robotic drilling cortical bone.

    PubMed

    Tahmasbi, Vahid; Ghoreishi, Majid; Zolfaghari, Mojtaba

    2017-11-01

    The bone drilling process is very prominent in orthopedic surgeries and in the repair of bone fractures. It is also very common in dentistry and bone sampling operations. Due to the complexity of bone and the sensitivity of the process, bone drilling is one of the most important and sensitive processes in biomedical engineering. Orthopedic surgeries can be improved using robotic systems and mechatronic tools. The most crucial problem during drilling is an unwanted increase in process temperature (higher than 47 °C), which causes thermal osteonecrosis or cell death and local burning of the bone tissue. Moreover, imposing higher forces to the bone may lead to breaking or cracking and consequently cause serious damage. In this study, a mathematical second-order linear regression model as a function of tool drilling speed, feed rate, tool diameter, and their effective interactions is introduced to predict temperature and force during the bone drilling process. This model can determine the maximum speed of surgery that remains within an acceptable temperature range. Moreover, for the first time, using designed experiments, the bone drilling process was modeled, and the drilling speed, feed rate, and tool diameter were optimized. Then, using response surface methodology and applying a multi-objective optimization, drilling force was minimized to sustain an acceptable temperature range without damaging the bone or the surrounding tissue. In addition, for the first time, Sobol statistical sensitivity analysis is used to ascertain the effect of process input parameters on process temperature and force. The results show that among all effective input parameters, tool rotational speed, feed rate, and tool diameter have the highest influence on process temperature and force, respectively. The behavior of each output parameters with variation in each input parameter is further investigated. Finally, a multi-objective optimization has been performed considering all the

  19. Particle parameter analyzing system. [x-y plotter circuits and display

    NASA Technical Reports Server (NTRS)

    Hansen, D. O.; Roy, N. L. (Inventor)

    1969-01-01

    An X-Y plotter circuit apparatus is described which displays an input pulse representing particle parameter information, that would ordinarily appear on the screen of an oscilloscope as a rectangular pulse, as a single dot positioned on the screen where the upper right hand corner of the input pulse would have appeared. If another event occurs, and it is desired to display this event, the apparatus is provided to replace the dot with a short horizontal line.

  20. A New Metamodeling Approach for Time-dependent Reliability of Dynamic Systems with Random Parameters Excited by Input Random Processes

    DTIC Science & Technology

    2014-04-09

    Excited by Input Random Processes Igor Baseski1,2, Dorin Drignei3, Zissimos P. Mourelatos1, Monica Majcher1 Oakland University, Rochester MI 48309 1...CONTRACT NUMBER W56HZV-04-2-0001 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Igor Baseski; Dorin Drignei; Zissimos Mourelatos; Monica

  1. Lower limits of spin detection efficiency for two-parameter two-qubit (TPTQ) states with non-ideal ferromagnetic detectors

    NASA Astrophysics Data System (ADS)

    Majd, Nayereh; Ghasemi, Zahra

    2016-10-01

    We have investigated a TPTQ state as an input state of a non-ideal ferromagnetic detectors. Minimal spin polarization required to demonstrate spin entanglement according to entanglement witness and CHSH inequality with respect to (w.r.t.) their two free parameters have been found, and we have numerically shown that the entanglement witness is less stringent than the direct tests of Bell's inequality in the form of CHSH in the entangled limits of its free parameters. In addition, the lower limits of spin detection efficiency fulfilling secure cryptographic key against eavesdropping have been derived. Finally, we have considered TPTQ state as an output of spin decoherence channel and the region of ballistic transmission time w.r.t. spin relaxation time and spin dephasing time has been found.

  2. Bayesian inference to identify parameters in viscoelasticity

    NASA Astrophysics Data System (ADS)

    Rappel, Hussein; Beex, Lars A. A.; Bordas, Stéphane P. A.

    2017-08-01

    This contribution discusses Bayesian inference (BI) as an approach to identify parameters in viscoelasticity. The aims are: (i) to show that the prior has a substantial influence for viscoelasticity, (ii) to show that this influence decreases for an increasing number of measurements and (iii) to show how different types of experiments influence the identified parameters and their uncertainties. The standard linear solid model is the material description of interest and a relaxation test, a constant strain-rate test and a creep test are the tensile experiments focused on. The experimental data are artificially created, allowing us to make a one-to-one comparison between the input parameters and the identified parameter values. Besides dealing with the aforementioned issues, we believe that this contribution forms a comprehensible start for those interested in applying BI in viscoelasticity.

  3. A parameter estimation subroutine package

    NASA Technical Reports Server (NTRS)

    Bierman, G. J.; Nead, W. M.

    1977-01-01

    Linear least squares estimation and regression analyses continue to play a major role in orbit determination and related areas. FORTRAN subroutines have been developed to facilitate analyses of a variety of parameter estimation problems. Easy to use multipurpose sets of algorithms are reported that are reasonably efficient and which use a minimal amount of computer storage. Subroutine inputs, outputs, usage and listings are given, along with examples of how these routines can be used.

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

    NASA Astrophysics Data System (ADS)

    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.

  5. Parameter identification for nonlinear aerodynamic systems

    NASA Technical Reports Server (NTRS)

    Pearson, Allan E.

    1990-01-01

    Parameter identification for nonlinear aerodynamic systems is examined. It is presumed that the underlying model can be arranged into an input/output (I/O) differential operator equation of a generic form. The algorithm estimation is especially efficient since the equation error can be integrated exactly given any I/O pair to obtain an algebraic function of the parameters. The algorithm for parameter identification was extended to the order determination problem for linear differential system. The degeneracy in a least squares estimate caused by feedback was addressed. A method of frequency analysis for determining the transfer function G(j omega) from transient I/O data was formulated using complex valued Fourier based modulating functions in contrast with the trigonometric modulating functions for the parameter estimation problem. A simulation result of applying the algorithm is given under noise-free conditions for a system with a low pass transfer function.

  6. On the fusion of tuning parameters of fuzzy rules and neural network

    NASA Astrophysics Data System (ADS)

    Mamuda, Mamman; Sathasivam, Saratha

    2017-08-01

    Learning fuzzy rule-based system with neural network can lead to a precise valuable empathy of several problems. Fuzzy logic offers a simple way to reach at a definite conclusion based upon its vague, ambiguous, imprecise, noisy or missing input information. Conventional learning algorithm for tuning parameters of fuzzy rules using training input-output data usually end in a weak firing state, this certainly powers the fuzzy rule and makes it insecure for a multiple-input fuzzy system. In this paper, we introduce a new learning algorithm for tuning the parameters of the fuzzy rules alongside with radial basis function neural network (RBFNN) in training input-output data based on the gradient descent method. By the new learning algorithm, the problem of weak firing using the conventional method was addressed. We illustrated the efficiency of our new learning algorithm by means of numerical examples. MATLAB R2014(a) software was used in simulating our result The result shows that the new learning method has the best advantage of training the fuzzy rules without tempering with the fuzzy rule table which allowed a membership function of the rule to be used more than one time in the fuzzy rule base.

  7. Piloted Parameter Identification Flight Test Maneuvers for Closed Loop Modeling of the F-18 High Alpha Research Vehicle (HARV)

    NASA Technical Reports Server (NTRS)

    Morelli, Eugene A.

    1996-01-01

    Flight test maneuvers are specified for the F-18 High Alpha Research Vehicle (HARV). The maneuvers were designed for closed loop parameter identification purposes, specifically for longitudinal and lateral linear model parameter estimation at 5, 20, 30, 45, and 60 degrees angle of attack, using the NASA 1A control law. Each maneuver is to be realized by the pilot applying square wave inputs to specific pilot station controls. Maneuver descriptions and complete specifications of the time/amplitude points defining each input are included, along with plots of the input time histories.

  8. Road simulation for four-wheel vehicle whole input power spectral density

    NASA Astrophysics Data System (ADS)

    Wang, Jiangbo; Qiang, Baomin

    2017-05-01

    As the vibration of running vehicle mainly comes from road and influence vehicle ride performance. So the road roughness power spectral density simulation has great significance to analyze automobile suspension vibration system parameters and evaluate ride comfort. Firstly, this paper based on the mathematical model of road roughness power spectral density, established the integral white noise road random method. Then in the MATLAB/Simulink environment, according to the research method of automobile suspension frame from simple two degree of freedom single-wheel vehicle model to complex multiple degrees of freedom vehicle model, this paper built the simple single incentive input simulation model. Finally the spectrum matrix was used to build whole vehicle incentive input simulation model. This simulation method based on reliable and accurate mathematical theory and can be applied to the random road simulation of any specified spectral which provides pavement incentive model and foundation to vehicle ride performance research and vibration simulation.

  9. TIM Version 3.0 beta Technical Description and User Guide - Appendix B - Example input file for TIMv3.0

    EPA Pesticide Factsheets

    Terrestrial Investigation Model, TIM, has several appendices to its user guide. This is the appendix that includes an example input file in its preserved format. Both parameters and comments defining them are included.

  10. Effects of Manipulated Above- and Belowground Organic Matter Input on Soil Respiration in a Chinese Pine Plantation

    PubMed Central

    Zhao, Bo; Wu, Lianhai; Zhang, Chunyu; Zhao, Xiuhai; Gadow, Klaus v.

    2015-01-01

    Alteration in the amount of soil organic matter input can have profound effect on carbon dynamics in forest soils. The objective of our research was to determine the response in soil respiration to above- and belowground organic matter manipulation in a Chinese pine (Pinus tabulaeformis) plantation. Five organic matter treatments were applied during a 2-year experiment: both litter removal and root trenching (LRRT), only litter removal (LR), control (CK), only root trenching (RT) and litter addition (LA). We found that either aboveground litter removal or root trenching decreased soil respiration. On average, soil respiration rate was significantly decreased in the LRRT treatment, by about 38.93% ± 2.01% compared to the control. Soil respiration rate in the LR treatment was 30.65% ± 1.87% and in the RT treatment 17.65% ± 1.95% lower than in the control. Litter addition significantly increased soil respiration rate by about 25.82% ± 2.44% compared to the control. Soil temperature and soil moisture were the main factors affecting seasonal variation in soil respiration. Up to the 59.7% to 82.9% seasonal variation in soil respiration is explained by integrating soil temperature and soil moisture within each of the various organic matter treatments. The temperature sensitivity parameter, Q 10, was higher in the RT (2.72) and LA (3.19) treatments relative to the control (2.51), but lower in the LRRT (1.52) and LR treatments (1.36). Our data suggest that manipulation of soil organic matter input can not only alter soil CO2 efflux, but also have profound effect on the temperature sensitivity of organic carbon decomposition in a temperate pine forest. PMID:25970791

  11. Effects of manipulated above- and belowground organic matter input on soil respiration in a Chinese pine plantation.

    PubMed

    Fan, Juan; Wang, Jinsong; Zhao, Bo; Wu, Lianhai; Zhang, Chunyu; Zhao, Xiuhai; Gadow, Klaus V

    2015-01-01

    Alteration in the amount of soil organic matter input can have profound effect on carbon dynamics in forest soils. The objective of our research was to determine the response in soil respiration to above- and belowground organic matter manipulation in a Chinese pine (Pinus tabulaeformis) plantation. Five organic matter treatments were applied during a 2-year experiment: both litter removal and root trenching (LRRT), only litter removal (LR), control (CK), only root trenching (RT) and litter addition (LA). We found that either aboveground litter removal or root trenching decreased soil respiration. On average, soil respiration rate was significantly decreased in the LRRT treatment, by about 38.93% ± 2.01% compared to the control. Soil respiration rate in the LR treatment was 30.65% ± 1.87% and in the RT treatment 17.65% ± 1.95% lower than in the control. Litter addition significantly increased soil respiration rate by about 25.82% ± 2.44% compared to the control. Soil temperature and soil moisture were the main factors affecting seasonal variation in soil respiration. Up to the 59.7% to 82.9% seasonal variation in soil respiration is explained by integrating soil temperature and soil moisture within each of the various organic matter treatments. The temperature sensitivity parameter, Q10, was higher in the RT (2.72) and LA (3.19) treatments relative to the control (2.51), but lower in the LRRT (1.52) and LR treatments (1.36). Our data suggest that manipulation of soil organic matter input can not only alter soil CO2 efflux, but also have profound effect on the temperature sensitivity of organic carbon decomposition in a temperate pine forest.

  12. Land and Water Use Characteristics and Human Health Input Parameters for use in Environmental Dosimetry and Risk Assessments at the Savannah River Site 2017 Update

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

    Jannik, T.; Stagich, B.

    Operations at the Savannah River Site (SRS) result in releases of relatively small amounts of radioactive materials to the atmosphere and to the Savannah River. For regulatory compliance purposes, potential offsite radiological doses are estimated annually using computer models that follow U.S. Nuclear Regulatory Commission (NRC) regulatory guides. Within the regulatory guides, default values are provided for many of the dose model parameters, but the use of site-specific values is encouraged. Detailed surveys of land-use and water-use parameters were conducted in 1991, 2008, 2010, and 2016 and are being concurred with or updated in this report. These parameters include localmore » characteristics of meat, milk, and vegetable production; river recreational activities; and meat, milk, and vegetable consumption rates, as well as other human usage parameters required in the SRS dosimetry models. In addition, the preferred elemental bioaccumulation factors and transfer factors (to be used in human health exposure calculations at SRS) are documented. The intent of this report is to establish a standardized source for these parameters that is up to date with existing data, and that is maintained via review of future-issued national references (to evaluate the need for changes as new information is released). These reviews will continue to be added to this document by revision.« less

  13. Effects of ambient temperature and dietary glycerol addition on growth performance, blood parameters and immune cell populations of Korean cattle steers

    PubMed Central

    Kang, Hyeok Joong; Piao, Min Yu; Lee, In Kyu; Kim, Hyun Jin; Gu, Min Jeong; Yun, Cheol-Heui; Seo, Jagyeom; Baik, Myunggi

    2017-01-01

    Objective This study was performed to evaluate whether ambient temperature and dietary glycerol addition affect growth performance, and blood metabolic and immunological parameters, in beef cattle. Methods Twenty Korean cattle steers (405.1±7.11 kg of body weight [BW], 14.2±0.15 months of age) were divided into a conventional control diet group (n = 10) and a 2% glycerol- added group (n = 10). Steers were fed 1.6% BW of a concentrate diet and 0.75% BW of a timothy hay diet for 8 weeks (4 weeks from July 28th to August 26th and 4 weeks from August 27th to September 26th). Blood was collected four times on July 28th, August 11th, August 27th, and September 26th. Results The maximum indoor ambient temperature-humidity index in August (75.8) was higher (p<0.001) than that in September (70.0), and in August was within the mild heat stress (HS) category range previously reported for dairy cattle. The average daily gain (ADG; p = 0.03) and feed efficiency (p<0.001) were higher in hotter August than in September. Glycerol addition did not affect ADG and feed efficiency. Neither month nor glycerol addition affected blood concentrations of cortisol, triglyceride, or non-esterified fatty acid. Blood concentrations of cholesterol, low-density lipoprotein, high-density lipoprotein, glucose, and albumin were lower (p<0.05) on August 27th than on September 26 th, and blood phosphorus, calcium and magnesium concentrations were also lower on August 27th than on September 27th. Glycerol addition did not affect these blood parameters. Percentages of CD4+ T cells and CD8+ T cells were higher (p<0.05) on July 28th than on August 27th and September 26th. The blood CD8+ T cell population was lower in the glycerol supplemented-group compared to the control group on July 28th and August 27th. Conclusion Korean cattle may not be significantly affected by mild HS, considering that growth performance of cattle was better in hotter conditions, although some changes in blood metabolic and

  14. The advanced LIGO input optics

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

    Mueller, Chris L., E-mail: cmueller@phys.ufl.edu; Arain, Muzammil A.; Ciani, Giacomo

    The advanced LIGO gravitational wave detectors are nearing their design sensitivity and should begin taking meaningful astrophysical data in the fall of 2015. These resonant optical interferometers will have unprecedented sensitivity to the strains caused by passing gravitational waves. The input optics play a significant part in allowing these devices to reach such sensitivities. Residing between the pre-stabilized laser and the main interferometer, the input optics subsystem is tasked with preparing the laser beam for interferometry at the sub-attometer level while operating at continuous wave input power levels ranging from 100 mW to 150 W. These extreme operating conditions requiredmore » every major component to be custom designed. These designs draw heavily on the experience and understanding gained during the operation of Initial LIGO and Enhanced LIGO. In this article, we report on how the components of the input optics were designed to meet their stringent requirements and present measurements showing how well they have lived up to their design.« less

  15. Teaching Additional Languages. Educational Practices Series 6.

    ERIC Educational Resources Information Center

    Judd, Elliot L.; Tan, Lihua; Walberg, Herbert J.

    This booklet describes key principles of and research on teaching additional languages. The 10 chapters focus on the following: (1) "Comprehensible Input" (learners need exposure to meaningful, understandable language); (2) "Language Opportunities" (classroom activities should let students use natural and meaningful language with their…

  16. Analysis of network motifs in cellular regulation: Structural similarities, input-output relations and signal integration.

    PubMed

    Straube, Ronny

    2017-12-01

    Much of the complexity of regulatory networks derives from the necessity to integrate multiple signals and to avoid malfunction due to cross-talk or harmful perturbations. Hence, one may expect that the input-output behavior of larger networks is not necessarily more complex than that of smaller network motifs which suggests that both can, under certain conditions, be described by similar equations. In this review, we illustrate this approach by discussing the similarities that exist in the steady state descriptions of a simple bimolecular reaction, covalent modification cycles and bacterial two-component systems. Interestingly, in all three systems fundamental input-output characteristics such as thresholds, ultrasensitivity or concentration robustness are described by structurally similar equations. Depending on the system the meaning of the parameters can differ ranging from protein concentrations and affinity constants to complex parameter combinations which allows for a quantitative understanding of signal integration in these systems. We argue that this approach may also be extended to larger regulatory networks. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. Input filter compensation for switching regulators

    NASA Technical Reports Server (NTRS)

    Lee, F. C.

    1984-01-01

    Problems caused by input filter interaction and conventional input filter design techniques are discussed. The concept of feedforward control is modeled with an input filter and a buck regulator. Experimental measurement and comparison to the analytical predictions is carried out. Transient response and the use of a feedforward loop to stabilize the regulator system is described. Other possible applications for feedforward control are included.

  18. Additivity of nonsimultaneous masking for short Gaussian-shaped sinusoids.

    PubMed

    Laback, Bernhard; Balazs, Peter; Necciari, Thibaud; Savel, Sophie; Ystad, Solvi; Meunier, Sabine; Kronland-Martinet, Richard

    2011-02-01

    The additivity of nonsimultaneous masking was studied using Gaussian-shaped tone pulses (referred to as Gaussians) as masker and target stimuli. Combinations of up to four temporally separated Gaussian maskers with an equivalent rectangular bandwidth of 600 Hz and an equivalent rectangular duration of 1.7 ms were tested. Each masker was level-adjusted to produce approximately 8 dB of masking. Excess masking (exceeding linear additivity) was generally stronger than reported in the literature for longer maskers and comparable target levels. A model incorporating a compressive input/output function, followed by a linear summation stage, underestimated excess masking when using an input/output function derived from literature data for longer maskers and comparable target levels. The data could be predicted with a more compressive input/output function. Stronger compression may be explained by assuming that the Gaussian stimuli were too short to evoke the medial olivocochlear reflex (MOCR), whereas for longer maskers tested previously the MOCR caused reduced compression. Overall, the interpretation of the data suggests strong basilar membrane compression for very short stimuli.

  19. A computer simulation of an adaptive noise canceler with a single input

    NASA Astrophysics Data System (ADS)

    Albert, Stuart D.

    1991-06-01

    A description of an adaptive noise canceler using Widrows' LMS algorithm is presented. A computer simulation of canceler performance (adaptive convergence time and frequency transfer function) was written for use as a design tool. The simulations, assumptions, and input parameters are described in detail. The simulation is used in a design example to predict the performance of an adaptive noise canceler in the simultaneous presence of both strong and weak narrow-band signals (a cosited frequency hopping radio scenario). On the basis of the simulation results, it is concluded that the simulation is suitable for use as an adaptive noise canceler design tool; i.e., it can be used to evaluate the effect of design parameter changes on canceler performance.

  20. Effects of Processing Parameters on Surface Roughness of Additive Manufactured Ti-6Al-4V via Electron Beam Melting

    PubMed Central

    Sin, Wai Jack; Nai, Mui Ling Sharon; Wei, Jun

    2017-01-01

    As one of the powder bed fusion additive manufacturing technologies, electron beam melting (EBM) is gaining more and more attention due to its near-net-shape production capacity with low residual stress and good mechanical properties. These characteristics also allow EBM built parts to be used as produced without post-processing. However, the as-built rough surface introduces a detrimental influence on the mechanical properties of metallic alloys. Thereafter, understanding the effects of processing parameters on the part’s surface roughness, in turn, becomes critical. This paper has focused on varying the processing parameters of two types of contouring scanning strategies namely, multispot and non-multispot, in EBM. The results suggest that the beam current and speed function are the most significant processing parameters for non-multispot contouring scanning strategy. While for multispot contouring scanning strategy, the number of spots, spot time, and spot overlap have greater effects than focus offset and beam current. The improved surface roughness has been obtained in both contouring scanning strategies. Furthermore, non-multispot contouring scanning strategy gives a lower surface roughness value and poorer geometrical accuracy than the multispot counterpart under the optimized conditions. These findings could be used as a guideline for selecting the contouring type used for specific industrial parts that are built using EBM. PMID:28937638

  1. Design, Fabrication, and Modeling of a Novel Dual-Axis Control Input PZT Gyroscope.

    PubMed

    Chang, Cheng-Yang; Chen, Tsung-Lin

    2017-10-31

    Conventional gyroscopes are equipped with a single-axis control input, limiting their performance. Although researchers have proposed control algorithms with dual-axis control inputs to improve gyroscope performance, most have verified the control algorithms through numerical simulations because they lacked practical devices with dual-axis control inputs. The aim of this study was to design a piezoelectric gyroscope equipped with a dual-axis control input so that researchers may experimentally verify those control algorithms in future. Designing a piezoelectric gyroscope with a dual-axis control input is more difficult than designing a conventional gyroscope because the control input must be effective over a broad frequency range to compensate for imperfections, and the multiple mode shapes in flexural deformations complicate the relation between flexural deformation and the proof mass position. This study solved these problems by using a lead zirconate titanate (PZT) material, introducing additional electrodes for shielding, developing an optimal electrode pattern, and performing calibrations of undesired couplings. The results indicated that the fabricated device could be operated at 5.5±1 kHz to perform dual-axis actuations and position measurements. The calibration of the fabricated device was completed by system identifications of a new dynamic model including gyroscopic motions, electromechanical coupling, mechanical coupling, electrostatic coupling, and capacitive output impedance. Finally, without the assistance of control algorithms, the "open loop sensitivity" of the fabricated gyroscope was 1.82 μV/deg/s with a nonlinearity of 9.5% full-scale output. This sensitivity is comparable with those of other PZT gyroscopes with single-axis control inputs.

  2. Defining a procedure for predicting the duration of the approximately isothermal segments within the proposed drying regime as a function of the drying air parameters

    NASA Astrophysics Data System (ADS)

    Vasić, M.; Radojević, Z.

    2017-08-01

    One of the main disadvantages of the recently reported method, for setting up the drying regime based on the theory of moisture migration during drying, lies in a fact that it is based on a large number of isothermal experiments. In addition each isothermal experiment requires the use of different drying air parameters. The main goal of this paper was to find a way how to reduce the number of isothermal experiments without affecting the quality of the previously proposed calculation method. The first task was to define the lower and upper inputs as well as the output of the “black box” which will be used in the Box-Wilkinson’s orthogonal multi-factorial experimental design. Three inputs (drying air temperature, humidity and velocity) were used within the experimental design. The output parameter of the model represents the time interval between any two chosen characteristic points presented on the Deff - t. The second task was to calculate the output parameter for each planed experiments. The final output of the model is the equation which can predict the time interval between any two chosen characteristic points as a function of the drying air parameters. This equation is valid for any value of the drying air parameters which are within the defined area designated with lower and upper limiting values.

  3. Learner Involvement and Comprehensible Input.

    ERIC Educational Resources Information Center

    Tsui, Amy B. M.

    1991-01-01

    Studies on comprehensible input generally emphasize how input is made comprehensible to the nonnative speaker by examining native speaker speech or teacher talk in the classroom. This paper uses Hong Kong secondary school data to show that only when modification devices involve learner participation do they serve as indicators of comprehensible…

  4. Nestly--a framework for running software with nested parameter choices and aggregating results.

    PubMed

    McCoy, Connor O; Gallagher, Aaron; Hoffman, Noah G; Matsen, Frederick A

    2013-02-01

    The execution of a software application or pipeline using various combinations of parameters and inputs is a common task in bioinformatics. In the absence of a specialized tool to organize, streamline and formalize this process, scientists must write frequently complex scripts to perform these tasks. We present nestly, a Python package to facilitate running tools with nested combinations of parameters and inputs. nestly provides three components. First, a module to build nested directory structures corresponding to choices of parameters. Second, the nestrun script to run a given command using each set of parameter choices. Third, the nestagg script to aggregate results of the individual runs into a CSV file, as well as support for more complex aggregation. We also include a module for easily specifying nested dependencies for the SCons build tool, enabling incremental builds. Source, documentation and tutorial examples are available at http://github.com/fhcrc/nestly. nestly can be installed from the Python Package Index via pip; it is open source (MIT license).

  5. Analysis of Discontinuity Induced Bifurcations in a Dual Input DC-DC Converter

    NASA Astrophysics Data System (ADS)

    Giaouris, Damian; Banerjee, Soumitro; Mandal, Kuntal; Al-Hindawi, Mohammed M.; Abusorrah, Abdullah; Al-Turki, Yusuf; El Aroudi, Abdelali

    DC-DC power converters with multiple inputs and a single output are used in numerous applications where multiple sources, e.g. two or more renewable energy sources and/or a battery, feed a single load. In this work, a classical boost converter topology with two input branches connected to two different sources is chosen, with each branch independently being controlled by a separate peak current mode controller. We demonstrate for the first time that even though this converter is similar to other well known topologies that have been studied before, it exhibits many complex nonlinear behaviors that are not found in any other standard PWM controlled power converter. The system undergoes period incrementing cascade as a parameter is varied, with discontinuous hard transitions between consecutive periodicities. We show that the system can be described by a discontinuous map, which explains the observed bifurcation phenomena. The results have been experimentally validated.

  6. Coincidence detection in the medial superior olive: mechanistic implications of an analysis of input spiking patterns

    PubMed Central

    Franken, Tom P.; Bremen, Peter; Joris, Philip X.

    2014-01-01

    Coincidence detection by binaural neurons in the medial superior olive underlies sensitivity to interaural time difference (ITD) and interaural correlation (ρ). It is unclear whether this process is akin to a counting of individual coinciding spikes, or rather to a correlation of membrane potential waveforms resulting from converging inputs from each side. We analyzed spike trains of axons of the cat trapezoid body (TB) and auditory nerve (AN) in a binaural coincidence scheme. ITD was studied by delaying “ipsi-” vs. “contralateral” inputs; ρ was studied by using responses to different noises. We varied the number of inputs; the monaural and binaural threshold and the coincidence window duration. We examined physiological plausibility of output “spike trains” by comparing their rate and tuning to ITD and ρ to those of binaural cells. We found that multiple inputs are required to obtain a plausible output spike rate. In contrast to previous suggestions, monaural threshold almost invariably needed to exceed binaural threshold. Elevation of the binaural threshold to values larger than 2 spikes caused a drastic decrease in rate for a short coincidence window. Longer coincidence windows allowed a lower number of inputs and higher binaural thresholds, but decreased the depth of modulation. Compared to AN fibers, TB fibers allowed higher output spike rates for a low number of inputs, but also generated more monaural coincidences. We conclude that, within the parameter space explored, the temporal patterns of monaural fibers require convergence of multiple inputs to achieve physiological binaural spike rates; that monaural coincidences have to be suppressed relative to binaural ones; and that the neuron has to be sensitive to single binaural coincidences of spikes, for a number of excitatory inputs per side of 10 or less. These findings suggest that the fundamental operation in the mammalian binaural circuit is coincidence counting of single binaural input

  7. Possibility of controlling nonregulated prices in the electricity market by means of varying the parameters of a power system

    NASA Astrophysics Data System (ADS)

    Vaskovskaya, T. A.

    2014-12-01

    This paper offers a new approach to the analysis of price signals from the wholesale electricity and capacity market that is based on the analysis of the influence exerted by input data used in the problem of optimization of the power system operating conditions, namely: parameters of a power grid and power-receiving equipment that might vary under the effect of control devices. It is shown that it would be possible to control nonregulated prices for electricity in the wholesale electricity market by varying the parameters of control devices and energy-receiving equipment. An increase in the effectiveness of power transmission and the cost-effective use of fuel-and-energy resources (energy saving) can become an additional effect of controlling the nonregulated prices.

  8. Parameter Estimation in Atmospheric Data Sets

    NASA Technical Reports Server (NTRS)

    Wenig, Mark; Colarco, Peter

    2004-01-01

    In this study the structure tensor technique is used to estimate dynamical parameters in atmospheric data sets. The structure tensor is a common tool for estimating motion in image sequences. This technique can be extended to estimate other dynamical parameters such as diffusion constants or exponential decay rates. A general mathematical framework was developed for the direct estimation of the physical parameters that govern the underlying processes from image sequences. This estimation technique can be adapted to the specific physical problem under investigation, so it can be used in a variety of applications in trace gas, aerosol, and cloud remote sensing. As a test scenario this technique will be applied to modeled dust data. In this case vertically integrated dust concentrations were used to derive wind information. Those results can be compared to the wind vector fields which served as input to the model. Based on this analysis, a method to compute atmospheric data parameter fields will be presented. .

  9. Measuring UV Curing Parameters of Commercial Photopolymers used in Additive Manufacturing.

    PubMed

    Bennett, Joe

    2017-12-01

    A testing methodology was developed to expose photopolymer resins and measure the cured material to determine two key parameters related to the photopolymerization process: E c (critical energy to initiate polymerization) and D p (penetration depth of curing light). Five commercially available resins were evaluated under exposure from 365 nm and 405 nm light at varying power densities and energies. Three different methods for determining the thickness of the cured resin were evaluated. Caliper measurements, stylus profilometry, and confocal laser scanning microscopy showed similar results for hard materials while caliper measurement of a soft, elastomeric material proved inaccurate. Working curves for the five photopolymers showed unique behavior both within and among the resins as a function of curing light wavelength. E c and D p for the five resins showed variations as large as 10×. Variations of this magnitude, if unknown to the user and not controlled for, will clearly affect printed part quality. This points to the need for a standardized approach for determining and disseminating these, and perhaps, other key parameters.

  10. Investigation of Multi-Input Multi-Output Robust Control Methods to Handle Parametric Uncertainties in Autopilot Design.

    PubMed

    Kasnakoğlu, Coşku

    2016-01-01

    Some level of uncertainty is unavoidable in acquiring the mass, geometry parameters and stability derivatives of an aerial vehicle. In certain instances tiny perturbations of these could potentially cause considerable variations in flight characteristics. This research considers the impact of varying these parameters altogether. This is a generalization of examining the effects of particular parameters on selected modes present in existing literature. Conventional autopilot designs commonly assume that each flight channel is independent and develop single-input single-output (SISO) controllers for every one, that are utilized in parallel for actual flight. It is demonstrated that an attitude controller built like this can function flawlessly on separate nominal cases, but can become unstable with a perturbation no more than 2%. Two robust multi-input multi-output (MIMO) design strategies, specifically loop-shaping and μ-synthesis are outlined as potential substitutes and are observed to handle large parametric changes of 30% while preserving decent performance. Duplicating the loop-shaping procedure for the outer loop, a complete flight control system is formed. It is confirmed through software-in-the-loop (SIL) verifications utilizing blade element theory (BET) that the autopilot is capable of navigation and landing exposed to high parametric variations and powerful winds.

  11. Investigation of Multi-Input Multi-Output Robust Control Methods to Handle Parametric Uncertainties in Autopilot Design

    PubMed Central

    Kasnakoğlu, Coşku

    2016-01-01

    Some level of uncertainty is unavoidable in acquiring the mass, geometry parameters and stability derivatives of an aerial vehicle. In certain instances tiny perturbations of these could potentially cause considerable variations in flight characteristics. This research considers the impact of varying these parameters altogether. This is a generalization of examining the effects of particular parameters on selected modes present in existing literature. Conventional autopilot designs commonly assume that each flight channel is independent and develop single-input single-output (SISO) controllers for every one, that are utilized in parallel for actual flight. It is demonstrated that an attitude controller built like this can function flawlessly on separate nominal cases, but can become unstable with a perturbation no more than 2%. Two robust multi-input multi-output (MIMO) design strategies, specifically loop-shaping and μ-synthesis are outlined as potential substitutes and are observed to handle large parametric changes of 30% while preserving decent performance. Duplicating the loop-shaping procedure for the outer loop, a complete flight control system is formed. It is confirmed through software-in-the-loop (SIL) verifications utilizing blade element theory (BET) that the autopilot is capable of navigation and landing exposed to high parametric variations and powerful winds. PMID:27783706

  12. A robust interpolation procedure for producing tidal current ellipse inputs for regional and coastal ocean numerical models

    NASA Astrophysics Data System (ADS)

    Byun, Do-Seong; Hart, Deirdre E.

    2017-04-01

    Regional and/or coastal ocean models can use tidal current harmonic forcing, together with tidal harmonic forcing along open boundaries in order to successfully simulate tides and tidal currents. These inputs can be freely generated using online open-access data, but the data produced are not always at the resolution required for regional or coastal models. Subsequent interpolation procedures can produce tidal current forcing data errors for parts of the world's coastal ocean where tidal ellipse inclinations and phases move across the invisible mathematical "boundaries" between 359° and 0° degrees (or 179° and 0°). In nature, such "boundaries" are in fact smooth transitions, but if these mathematical "boundaries" are not treated correctly during interpolation, they can produce inaccurate input data and hamper the accurate simulation of tidal currents in regional and coastal ocean models. These avoidable errors arise due to procedural shortcomings involving vector embodiment problems (i.e., how a vector is represented mathematically, for example as velocities or as coordinates). Automated solutions for producing correct tidal ellipse parameter input data are possible if a series of steps are followed correctly, including the use of Cartesian coordinates during interpolation. This note comprises the first published description of scenarios where tidal ellipse parameter interpolation errors can arise, and of a procedure to successfully avoid these errors when generating tidal inputs for regional and/or coastal ocean numerical models. We explain how a straightforward sequence of data production, format conversion, interpolation, and format reconversion steps may be used to check for the potential occurrence and avoidance of tidal ellipse interpolation and phase errors. This sequence is demonstrated via a case study of the M2 tidal constituent in the seas around Korea but is designed to be universally applicable. We also recommend employing tidal ellipse parameter

  13. Measuring Input Thresholds on an Existing Board

    NASA Technical Reports Server (NTRS)

    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. Observations of the directional distribution of the wind energy input function over swell waves

    NASA Astrophysics Data System (ADS)

    Shabani, Behnam; Babanin, Alex V.; Baldock, Tom E.

    2016-02-01

    Field measurements of wind stress over shallow water swell traveling in different directions relative to the wind are presented. The directional distribution of the measured stresses is used to confirm the previously proposed but unverified directional distribution of the wind energy input function. The observed wind energy input function is found to follow a much narrower distribution (β∝cos⁡3.6θ) than the Plant (1982) cosine distribution. The observation of negative stress angles at large wind-wave angles, however, indicates that the onset of negative wind shearing occurs at about θ≈ 50°, and supports the use of the Snyder et al. (1981) directional distribution. Taking into account the reverse momentum transfer from swell to the wind, Snyder's proposed parameterization is found to perform exceptionally well in explaining the observed narrow directional distribution of the wind energy input function, and predicting the wind drag coefficients. The empirical coefficient (ɛ) in Snyder's parameterization is hypothesised to be a function of the wave shape parameter, with ɛ value increasing as the wave shape changes between sinusoidal, sawtooth, and sharp-crested shoaling waves.

  15. Parameter screening: the use of a dummy parameter to identify non-influential parameters in a global sensitivity analysis

    NASA Astrophysics Data System (ADS)

    Khorashadi Zadeh, Farkhondeh; Nossent, Jiri; van Griensven, Ann; Bauwens, Willy

    2017-04-01

    Parameter estimation is a major concern in hydrological modeling, which may limit the use of complex simulators with a large number of parameters. To support the selection of parameters to include in or exclude from the calibration process, Global Sensitivity Analysis (GSA) is widely applied in modeling practices. Based on the results of GSA, the influential and the non-influential parameters are identified (i.e. parameters screening). Nevertheless, the choice of the screening threshold below which parameters are considered non-influential is a critical issue, which has recently received more attention in GSA literature. In theory, the sensitivity index of a non-influential parameter has a value of zero. However, since numerical approximations, rather than analytical solutions, are utilized in GSA methods to calculate the sensitivity indices, small but non-zero indices may be obtained for the indices of non-influential parameters. In order to assess the threshold that identifies non-influential parameters in GSA methods, we propose to calculate the sensitivity index of a "dummy parameter". This dummy parameter has no influence on the model output, but will have a non-zero sensitivity index, representing the error due to the numerical approximation. Hence, the parameters whose indices are above the sensitivity index of the dummy parameter can be classified as influential, whereas the parameters whose indices are below this index are within the range of the numerical error and should be considered as non-influential. To demonstrated the effectiveness of the proposed "dummy parameter approach", 26 parameters of a Soil and Water Assessment Tool (SWAT) model are selected to be analyzed and screened, using the variance-based Sobol' and moment-independent PAWN methods. The sensitivity index of the dummy parameter is calculated from sampled data, without changing the model equations. Moreover, the calculation does not even require additional model evaluations for the Sobol

  16. Dynamic Contrast-enhanced MR Imaging in Renal Cell Carcinoma: Reproducibility of Histogram Analysis on Pharmacokinetic Parameters

    PubMed Central

    Wang, Hai-yi; Su, Zi-hua; Xu, Xiao; Sun, Zhi-peng; Duan, Fei-xue; Song, Yuan-yuan; Li, Lu; Wang, Ying-wei; Ma, Xin; Guo, Ai-tao; Ma, Lin; Ye, Hui-yi

    2016-01-01

    Pharmacokinetic parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) have been increasingly used to evaluate the permeability of tumor vessel. Histogram metrics are a recognized promising method of quantitative MR imaging that has been recently introduced in analysis of DCE-MRI pharmacokinetic parameters in oncology due to tumor heterogeneity. In this study, 21 patients with renal cell carcinoma (RCC) underwent paired DCE-MRI studies on a 3.0 T MR system. Extended Tofts model and population-based arterial input function were used to calculate kinetic parameters of RCC tumors. Mean value and histogram metrics (Mode, Skewness and Kurtosis) of each pharmacokinetic parameter were generated automatically using ImageJ software. Intra- and inter-observer reproducibility and scan–rescan reproducibility were evaluated using intra-class correlation coefficients (ICCs) and coefficient of variation (CoV). Our results demonstrated that the histogram method (Mode, Skewness and Kurtosis) was not superior to the conventional Mean value method in reproducibility evaluation on DCE-MRI pharmacokinetic parameters (K trans & Ve) in renal cell carcinoma, especially for Skewness and Kurtosis which showed lower intra-, inter-observer and scan-rescan reproducibility than Mean value. Our findings suggest that additional studies are necessary before wide incorporation of histogram metrics in quantitative analysis of DCE-MRI pharmacokinetic parameters. PMID:27380733

  17. Preliminary investigation of the effects of eruption source parameters on volcanic ash transport and dispersion modeling using HYSPLIT

    NASA Astrophysics Data System (ADS)

    Stunder, B.

    2009-12-01

    Atmospheric transport and dispersion (ATD) models are used in real-time at Volcanic Ash Advisory Centers to predict the location of airborne volcanic ash at a future time because of the hazardous nature of volcanic ash. Transport and dispersion models usually do not include eruption column physics, but start with an idealized eruption column. Eruption source parameters (ESP) input to the models typically include column top, eruption start time and duration, volcano latitude and longitude, ash particle size distribution, and total mass emission. An example based on the Okmok, Alaska, eruption of July 12-14, 2008, was used to qualitatively estimate the effect of various model inputs on transport and dispersion simulations using the NOAA HYSPLIT model. Variations included changing the ash column top and bottom, eruption start time and duration, particle size specifications, simulations with and without gravitational settling, and the effect of different meteorological model data. Graphical ATD model output of ash concentration from the various runs was qualitatively compared. Some parameters such as eruption duration and ash column depth had a large effect, while simulations using only small particles or changing the particle shape factor had much less of an effect. Some other variations such as using only large particles had a small effect for the first day or so after the eruption, then a larger effect on subsequent days. Example probabilistic output will be shown for an ensemble of dispersion model runs with various model inputs. Model output such as this may be useful as a means to account for some of the uncertainties in the model input. To improve volcanic ash ATD models, a reference database for volcanic eruptions is needed, covering many volcanoes. The database should include three major components: (1) eruption source, (2) ash observations, and (3) analyses meteorology. In addition, information on aggregation or other ash particle transformation processes

  18. Dynamics of ultrasonic additive manufacturing.

    PubMed

    Hehr, Adam; Dapino, Marcelo J

    2017-01-01

    Ultrasonic additive manufacturing (UAM) is a solid-state technology for joining similar and dissimilar metal foils near room temperature by scrubbing them together with ultrasonic vibrations under pressure. Structural dynamics of the welding assembly and work piece influence how energy is transferred during the process and ultimately, part quality. To understand the effect of structural dynamics during UAM, a linear time-invariant model is proposed to relate the inputs of shear force and electric current to resultant welder velocity and voltage. Measured frequency response and operating performance of the welder under no load is used to identify model parameters. Using this model and in-situ measurements, shear force and welder efficiency are estimated to be near 2000N and 80% when welding Al 6061-H18 weld foil, respectively. Shear force and welder efficiency have never been estimated before in UAM. The influence of processing conditions, i.e., welder amplitude, normal force, and weld speed, on shear force and welder efficiency are investigated. Welder velocity was found to strongly influence the shear force magnitude and efficiency while normal force and weld speed showed little to no influence. The proposed model is used to describe high frequency harmonic content in the velocity response of the welder during welding operations and coupling of the UAM build with the welder. Copyright © 2016 Elsevier B.V. All rights reserved.

  19. Regional Hospital Input Price Indexes

    PubMed Central

    Freeland, Mark S.; Schendler, Carol Ellen; Anderson, Gerard

    1981-01-01

    This paper describes the development of regional hospital input price indexes that is consistent with the general methodology used for the National Hospital Input Price Index. The feasibility of developing regional indexes was investigated because individuals inquired whether different regions experienced different rates of increase in hospital input prices. The regional indexes incorporate variations in cost-share weights (the amount an expense category contributes to total spending) associated with hospital type and location, and variations in the rate of input price increases for various regions. We found that between 1972 and 1979 none of the regional price indexes increased at average annual rates significantly different from the national rate. For the more recent period 1977 through 1979, the increase in one Census Region was significantly below the national rate. Further analyses indicated that variations in cost-share weights for various types of hospitals produced no substantial variations in the regional price indexes relative to the national index. We consider these findings preliminary because of limitations in the availability of current, relevant, and reliable data, especially for local area wage rate increases. PMID:10309557

  20. Groundwater-derived nutrient inputs to the Upper Gulf of Thailand

    NASA Astrophysics Data System (ADS)

    Burnett, William C.; Wattayakorn, Gullaya; Taniguchi, Makoto; Dulaiova, Henrieta; Sojisuporn, Pramot; Rungsupa, Sompop; Ishitobi, Tomotoshi

    2007-01-01

    We report here the first direct measurements of nutrient fluxes via groundwater discharge into the Upper Gulf of Thailand. Nutrient and standard oceanographic surveys were conducted during the wet and dry seasons along the Chao Phraya River, Estuary and out into the Upper Gulf of Thailand. Additional measurements in selected near-shore regions of the Gulf included manual and automatic seepage meter deployments, as well as nutrient evaluations of seepage and coastal waters. The river transects characterized the distribution of biogeochemical parameters in this highly contaminated urban environment. Seepage flux measurements together with nutrient analyses of seepage fluids were used to estimate nutrient fluxes via groundwater pathways for comparison to riverine fluxes. Our findings show that disseminated seepage of nutrient-rich mostly saline groundwater into the Upper Gulf of Thailand is significant. Estimated fluxes of dissolved inorganic nitrogen (DIN) supplied via groundwater discharge were 40-50% of that delivered by the Chao Phraya River, inorganic phosphate was 60-70%, and silica was 15-40%. Dissolved organic nitrogen (DON) and phosphorus (DOP) groundwater fluxes were also high at 30-40% and 30-130% of the river inputs, respectively. These observations are especially impressive since the comparison is being made to the river that is the largest source of fresh water into the Gulf of Thailand and flows directly through the megacity of Bangkok with high nutrient loadings from industrial and domestic sources.

  1. Parameter Identification Flight Test Maneuvers for Closed Loop Modeling of the F-18 High Alpha Research Vehicle (HARV)

    NASA Technical Reports Server (NTRS)

    Batterson, James G. (Technical Monitor); Morelli, E. A.

    1996-01-01

    Flight test maneuvers are specified for the F-18 High Alpha Research Vehicle (HARV). The maneuvers were designed for closed loop parameter identification purposes, specifically for longitudinal and lateral linear model parameter estimation at 5,20,30,45, and 60 degrees angle of attack, using the Actuated Nose Strakes for Enhanced Rolling (ANSER) control law in Thrust Vectoring (TV) mode. Each maneuver is to be realized by applying square wave inputs to specific pilot station controls using the On-Board Excitation System (OBES). Maneuver descriptions and complete specifications of the time / amplitude points defining each input are included, along with plots of the input time histories.

  2. Optimum systems design with random input and output applied to solar water heating

    NASA Astrophysics Data System (ADS)

    Abdel-Malek, L. L.

    1980-03-01

    Solar water heating systems are evaluated. Models were developed to estimate the percentage of energy supplied from the Sun to a household. Since solar water heating systems have random input and output queueing theory, birth and death processes were the major tools in developing the models of evaluation. Microeconomics methods help in determining the optimum size of the solar water heating system design parameters, i.e., the water tank volume and the collector area.

  3. Robust fault-tolerant tracking control design for spacecraft under control input saturation.

    PubMed

    Bustan, Danyal; Pariz, Naser; Sani, Seyyed Kamal Hosseini

    2014-07-01

    In this paper, a continuous globally stable tracking control algorithm is proposed for a spacecraft in the presence of unknown actuator failure, control input saturation, uncertainty in inertial matrix and external disturbances. The design method is based on variable structure control and has the following properties: (1) fast and accurate response in the presence of bounded disturbances; (2) robust to the partial loss of actuator effectiveness; (3) explicit consideration of control input saturation; and (4) robust to uncertainty in inertial matrix. In contrast to traditional fault-tolerant control methods, the proposed controller does not require knowledge of the actuator faults and is implemented without explicit fault detection and isolation processes. In the proposed controller a single parameter is adjusted dynamically in such a way that it is possible to prove that both attitude and angular velocity errors will tend to zero asymptotically. The stability proof is based on a Lyapunov analysis and the properties of the singularity free quaternion representation of spacecraft dynamics. Results of numerical simulations state that the proposed controller is successful in achieving high attitude performance in the presence of external disturbances, actuator failures, and control input saturation. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

  4. Recycled grains in lunar soils as an additional, necessary, regolith evolution parameter

    NASA Technical Reports Server (NTRS)

    Basu, A.

    1990-01-01

    Recycled lunar soil grains are defined as those soil grains that have been a part of either regolith breccias or agglutinates; thus, mineral grains, rock fragments, older agglutinates, and volcanic glass spherules, if dislodged from an agglutinate or a regolith breccia, would all qualify as recycled grains. This paper shows that it is possible to estimate the proportion of recycled material in lunar soils. Optical data from 12 soils in the Apollo 16 core 64001/2 were collected to estimate the proportion (W) of recycled crystalline grains in each of these soils. The W values show a correspondence with other independently derived parameters and the history of the core soils, indicating that W can be used as a valid soil-evolution parameter.

  5. [Involvement of scientific societies in early benefit assessment: Simulated participation or valuable additional input?

    PubMed

    Bleß, Hans-Holger; Seidlitz, Cornelia; Ohlmeier, Christoph; de Millas, Christoph

    2018-02-01

    The German framework of early benefit assessment (EBA) of drugs also provides for the participation of scientific medical societies. The aim of their inclusion is to assure that care providers can critically assess all aspects of the EBA and provide insights into relevant aspects regarding the provision of care. This study systematically reviews the frequency of participation of the scientific medical societies (FGs) and the Drug Commission of the German Medical Association (AkdÄ) within the scope of the EBA. In addition, the positioning of AkdÄ/FG is compared to the Institute for Quality and Efficiency in Health Care (IQWiG) and the Federal Joint Committee (G-BA) with a focus on antidiabetic drugs and cancer drugs. A literature analysis was performed based on the comprehensive documentation of benefit assessments published by G-BA. All proceedings of antidiabetic drugs and cancer drugs were included, for which a decision was published by August 6, 2015. In addition, statements of FGs or AkdÄ were identified by an exploratory literature review and included in the analysis. The statements considered were assessed with regard to three categories: (1) additional benefit, (2) appropriate comparator (ZVT) and (3) suitability of the endpoints. For each procedure and category, it was assessed whether there was agreement or disagreement between IGWiG/G-BA and AkdÄ/FGs statements. Regarding the additional benefit, a deviating position was further differentiated according to the level of additional benefit (higher/lower). Afterwards, the proportion of favorable and unfavorable positions was calculated, stratified by FGs and AkdÄ and, separately, for proceedings of antidiabetics and cancer drugs. The literature review revealed 41 proceedings of cancer drugs and 21 proceedings of antidiabetic drugs which were included in the analyses. Statements by AkdÄ/FGs were identified in 90 % of the proceedings for antidiabetic drugs and in 98 % of the proceedings for cancer drugs

  6. Net anthropogenic nitrogen inputs and nitrogen fluxes from Indian watersheds: An initial assessment

    NASA Astrophysics Data System (ADS)

    Swaney, D. P.; Hong, B.; Paneer Selvam, A.; Howarth, R. W.; Ramesh, R.; Purvaja, R.

    2015-01-01

    In this paper, we apply an established methodology for estimating Net Anthropogenic Nitrogen Inputs (NANI) to India and its major watersheds. Our primary goal here is to provide initial estimates of major nitrogen inputs of NANI for India, at the country level and for major Indian watersheds, including data sources and parameter estimates, making some assumptions as needed in areas of limited data availability. Despite data limitations, we believe that it is clear that the main anthropogenic N source is agricultural fertilizer, which is being produced and applied at a growing rate, followed by N fixation associated with rice, leguminous crops, and sugar cane. While India appears to be a net exporter of N in food/feed as reported elsewhere (Lassaletta et al., 2013b), the balance of N associated with exports and imports of protein in food and feedstuffs is sensitive to protein content and somewhat uncertain. While correlating watershed N inputs with riverine N fluxes is problematic due in part to limited available riverine data, we have assembled some data for comparative purposes. We also suggest possible improvements in methods for future studies, and the potential for estimating riverine N fluxes to coastal waters.

  7. MODFLOW-2000, the U.S. Geological Survey modular ground-water model; user guide to the observation, sensitivity, and parameter-estimation processes and three post-processing programs

    USGS Publications Warehouse

    Hill, Mary C.; Banta, E.R.; Harbaugh, A.W.; Anderman, E.R.

    2000-01-01

    This report documents the Observation, Sensitivity, and Parameter-Estimation Processes of the ground-water modeling computer program MODFLOW-2000. The Observation Process generates model-calculated values for comparison with measured, or observed, quantities. A variety of statistics is calculated to quantify this comparison, including a weighted least-squares objective function. In addition, a number of files are produced that can be used to compare the values graphically. The Sensitivity Process calculates the sensitivity of hydraulic heads throughout the model with respect to specified parameters using the accurate sensitivity-equation method. These are called grid sensitivities. If the Observation Process is active, it uses the grid sensitivities to calculate sensitivities for the simulated values associated with the observations. These are called observation sensitivities. Observation sensitivities are used to calculate a number of statistics that can be used (1) to diagnose inadequate data, (2) to identify parameters that probably cannot be estimated by regression using the available observations, and (3) to evaluate the utility of proposed new data. The Parameter-Estimation Process uses a modified Gauss-Newton method to adjust values of user-selected input parameters in an iterative procedure to minimize the value of the weighted least-squares objective function. Statistics produced by the Parameter-Estimation Process can be used to evaluate estimated parameter values; statistics produced by the Observation Process and post-processing program RESAN-2000 can be used to evaluate how accurately the model represents the actual processes; statistics produced by post-processing program YCINT-2000 can be used to quantify the uncertainty of model simulated values. Parameters are defined in the Ground-Water Flow Process input files and can be used to calculate most model inputs, such as: for explicitly defined model layers, horizontal hydraulic conductivity

  8. Optimization of process parameters in drilling of fibre hybrid composite using Taguchi and grey relational analysis

    NASA Astrophysics Data System (ADS)

    Vijaya Ramnath, B.; Sharavanan, S.; Jeykrishnan, J.

    2017-03-01

    Nowadays quality plays a vital role in all the products. Hence, the development in manufacturing process focuses on the fabrication of composite with high dimensional accuracy and also incurring low manufacturing cost. In this work, an investigation on machining parameters has been performed on jute-flax hybrid composite. Here, the two important responses characteristics like surface roughness and material removal rate are optimized by employing 3 machining input parameters. The input variables considered are drill bit diameter, spindle speed and feed rate. Machining is done on CNC vertical drilling machine at different levels of drilling parameters. Taguchi’s L16 orthogonal array is used for optimizing individual tool parameters. Analysis Of Variance is used to find the significance of individual parameters. The simultaneous optimization of the process parameters is done by grey relational analysis. The results of this investigation shows that, spindle speed and drill bit diameter have most effect on material removal rate and surface roughness followed by feed rate.

  9. Microbial respiration, but not biomass, responded linearly to increasing light fraction organic matter input: Consequences for carbon sequestration.

    PubMed

    Rui, Yichao; Murphy, Daniel V; Wang, Xiaoli; Hoyle, Frances C

    2016-10-18

    Rebuilding 'lost' soil carbon (C) is a priority in mitigating climate change and underpinning key soil functions that support ecosystem services. Microorganisms determine if fresh C input is converted into stable soil organic matter (SOM) or lost as CO 2 . Here we quantified if microbial biomass and respiration responded positively to addition of light fraction organic matter (LFOM, representing recent inputs of plant residue) in an infertile semi-arid agricultural soil. Field trial soil with different historical plant residue inputs [soil C content: control (tilled) = 9.6 t C ha -1 versus tilled + plant residue treatment (tilled + OM) = 18.0 t C ha -1 ] were incubated in the laboratory with a gradient of LFOM equivalent to 0 to 3.8 t C ha -1 (0 to 500% LFOM). Microbial biomass C significantly declined under increased rates of LFOM addition while microbial respiration increased linearly, leading to a decrease in the microbial C use efficiency. We hypothesise this was due to insufficient nutrients to form new microbial biomass as LFOM input increased the ratio of C to nitrogen, phosphorus and sulphur of soil. Increased CO 2 efflux but constrained microbial growth in response to LFOM input demonstrated the difficulty for C storage in this environment.

  10. Six axis force feedback input device

    NASA Technical Reports Server (NTRS)

    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.

  11. Input current shaped ac-to-dc converters

    NASA Technical Reports Server (NTRS)

    1985-01-01

    Input current shaping techniques for ac-to-dc converters were investigated. Input frequencies much higher than normal, up to 20 kHz were emphasized. Several methods of shaping the input current waveform in ac-to-dc converters were reviewed. The simplest method is the LC filter following the rectifier. The next simplest method is the resistor emulation approach in which the inductor size is determined by the converter switching frequency and not by the line input frequency. Other methods require complicated switch drive algorithms to construct the input current waveshape. For a high-frequency line input, on the order of 20 kHz, the simple LC cannot be discarded so peremptorily, since the inductor size can be compared with that for the resistor emulation method. In fact, since a dc regulator will normally be required after the filter anyway, the total component count is almost the same as for the resistor emulation method, in which the filter is effectively incorporated into the regulator.

  12. Modeling long correlation times using additive binary Markov chains: Applications to wind generation time series.

    PubMed

    Weber, Juliane; Zachow, Christopher; Witthaut, Dirk

    2018-03-01

    Wind power generation exhibits a strong temporal variability, which is crucial for system integration in highly renewable power systems. Different methods exist to simulate wind power generation but they often cannot represent the crucial temporal fluctuations properly. We apply the concept of additive binary Markov chains to model a wind generation time series consisting of two states: periods of high and low wind generation. The only input parameter for this model is the empirical autocorrelation function. The two-state model is readily extended to stochastically reproduce the actual generation per period. To evaluate the additive binary Markov chain method, we introduce a coarse model of the electric power system to derive backup and storage needs. We find that the temporal correlations of wind power generation, the backup need as a function of the storage capacity, and the resting time distribution of high and low wind events for different shares of wind generation can be reconstructed.

  13. Modeling long correlation times using additive binary Markov chains: Applications to wind generation time series

    NASA Astrophysics Data System (ADS)

    Weber, Juliane; Zachow, Christopher; Witthaut, Dirk

    2018-03-01

    Wind power generation exhibits a strong temporal variability, which is crucial for system integration in highly renewable power systems. Different methods exist to simulate wind power generation but they often cannot represent the crucial temporal fluctuations properly. We apply the concept of additive binary Markov chains to model a wind generation time series consisting of two states: periods of high and low wind generation. The only input parameter for this model is the empirical autocorrelation function. The two-state model is readily extended to stochastically reproduce the actual generation per period. To evaluate the additive binary Markov chain method, we introduce a coarse model of the electric power system to derive backup and storage needs. We find that the temporal correlations of wind power generation, the backup need as a function of the storage capacity, and the resting time distribution of high and low wind events for different shares of wind generation can be reconstructed.

  14. High-frequency matrix converter with square wave input

    DOEpatents

    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.

  15. Microbial Communities Model Parameter Calculation for TSPA/SR

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

    D. Jolley

    2001-07-16

    This calculation has several purposes. First the calculation reduces the information contained in ''Committed Materials in Repository Drifts'' (BSC 2001a) to useable parameters required as input to MING V1.O (CRWMS M&O 1998, CSCI 30018 V1.O) for calculation of the effects of potential in-drift microbial communities as part of the microbial communities model. The calculation is intended to replace the parameters found in Attachment II of the current In-Drift Microbial Communities Model revision (CRWMS M&O 2000c) with the exception of Section 11-5.3. Second, this calculation provides the information necessary to supercede the following DTN: M09909SPAMING1.003 and replace it with a newmore » qualified dataset (see Table 6.2-1). The purpose of this calculation is to create the revised qualified parameter input for MING that will allow {Delta}G (Gibbs Free Energy) to be corrected for long-term changes to the temperature of the near-field environment. Calculated herein are the quadratic or second order regression relationships that are used in the energy limiting calculations to potential growth of microbial communities in the in-drift geochemical environment. Third, the calculation performs an impact review of a new DTN: M00012MAJIONIS.000 that is intended to replace the currently cited DTN: GS9809083 12322.008 for water chemistry data used in the current ''In-Drift Microbial Communities Model'' revision (CRWMS M&O 2000c). Finally, the calculation updates the material lifetimes reported on Table 32 in section 6.5.2.3 of the ''In-Drift Microbial Communities'' AMR (CRWMS M&O 2000c) based on the inputs reported in BSC (2001a). Changes include adding new specified materials and updating old materials information that has changed.« less

  16. A record of hydrocarbon input to San Francisco Bay as traced by biomarker profiles in surface sediment and sediment cores

    USGS Publications Warehouse

    Hostettler, F.D.; Pereira, W.E.; Kvenvolden, K.A.; VanGeen, A.; Luoma, S.N.; Fuller, C.C.; Anima, R.

    1999-01-01

    San Francisco Bay is one of the world's largest urbanized estuarine systems. Its water and sediment receive organic input from a wide variety of sources; much of this organic material is anthropogenically derived. To document the spatial and historical record of the organic contaminant input, surficial sediment from 17 sites throughout San Francisco Bay and sediment cores from two locations Richardson Bay and San Pablo Bay were analyzed for biomarker constituents. Biomarkers, that is, 'molecular fossils', primarily hopanes, steranes, and n-alkanes, provide information on anthropogenic contamination, especially that related to petrogenic sources, as well as on recent input of biogenic material. The biomarker parameters from the surficial sediment and the upper horizons of the cores show a dominance of anthropogenic input, whereas the biomarker profiles at the lower horizons of the cores indicate primarily biogenic input. In the Richardson Bay core the gradual upcore transition from lower maturity background organics to a dominance of anthropogenic contamination occurred about 70-100 years ago and corresponds to the industrial development of the San Francisco Bay area. In San Pablo Bay, the transition was very abrupt, reflecting the complex depositional history of the area. This sharp transition, perhaps indicating a depositional hiatus or erosional period, dated at pre-1952, is clearly visible. Below, the hiatus the biomarker parameters are immature; above, they are mature and show an anthropogenic overlay. Higher concentrations of terrigenous n-alkanes in the upper horizons in this core are indicative of an increase in terrigenous organic matter input in San Pablo Bay, possibly a result of water diversion projects and changes in the fresh water flow into the Bay from the Delta. Alternatively, it could reflect a dilution of organic material in the lower core sections with hydraulic mining debris.

  17. Atmospheric Inputs of Nitrogen, Carbon, and Phosphorus across an Urban Area: Unaccounted Fluxes and Canopy Influences

    NASA Astrophysics Data System (ADS)

    Decina, Stephen M.; Templer, Pamela H.; Hutyra, Lucy R.

    2018-02-01

    Rates of atmospheric deposition are declining across the United States, yet urban areas remain hotspots of atmospheric deposition. While past studies show elevated rates of inorganic nitrogen (N) deposition in cities, less is known about atmospheric inputs of organic N, organic carbon (C), and organic and inorganic phosphorus (P), all of which can affect ecosystem processes, water quality, and air quality. Further, the effect of the tree canopy on amounts and forms of nutrients reaching urban ground surfaces is not well-characterized. We measured growing season rates of total N, organic C, and total P in bulk atmospheric inputs, throughfall, and soil solution around the greater Boston area. We found that organic N constitutes a third of total N inputs, organic C inputs are comparable to rural inputs, and inorganic P inputs are 1.2 times higher than those in sewage effluent. Atmospheric inputs are enhanced two-to-eight times in late spring and are elevated beneath tree canopies, suggesting that trees augment atmospheric inputs to ground surfaces. Additionally, throughfall inputs may directly enter runoff when trees extend above impervious surfaces, as is the case with 26.1% of Boston's tree canopy. Our results indicate that the urban atmosphere is a significant source of elemental inputs that may impact urban ecosystems and efforts to improve water quality, particularly in terms of P. Further, as cities create policies encouraging tree planting to provide ecosystem services, locating trees above permeable surfaces to reduce runoff nutrient loads may be essential to managing urban biogeochemical cycling and water quality.

  18. Influence of asymmetric attenuation of single and paired dendritic inputs on summation of synaptic potentials and initiation of action potentials.

    PubMed

    Fortier, Pierre A; Bray, Chelsea

    2013-04-16

    the synaptic input. Exploration of the parameter space showed how the gradient of voltage-gated channel densities and input resistances along a dendrite could draw the action potential onset away from the stimulation site. The attraction of action potential onset toward the higher density of voltage-gated channels in the soma during stimulation of the proximal dendrite was, however, reduced after the addition of synaptic noise. Copyright © 2012 IBRO. Published by Elsevier Ltd. All rights reserved.

  19. Textual Enhancement of Input: Issues and Possibilities

    ERIC Educational Resources Information Center

    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.…

  20. C-SWAT: The Soil and Water Assessment Tool with consolidated input files in alleviating computational burden of recursive simulations

    USDA-ARS?s Scientific Manuscript database

    The temptation to include model parameters and high resolution input data together with the availability of powerful optimization and uncertainty analysis algorithms has significantly enhanced the complexity of hydrologic and water quality modeling. However, the ability to take advantage of sophist...

  1. Input variable selection and calibration data selection for storm water quality regression models.

    PubMed

    Sun, Siao; Bertrand-Krajewski, Jean-Luc

    2013-01-01

    Storm water quality models are useful tools in storm water management. Interest has been growing in analyzing existing data for developing models for urban storm water quality evaluations. It is important to select appropriate model inputs when many candidate explanatory variables are available. Model calibration and verification are essential steps in any storm water quality modeling. This study investigates input variable selection and calibration data selection in storm water quality regression models. The two selection problems are mutually interacted. A procedure is developed in order to fulfil the two selection tasks in order. The procedure firstly selects model input variables using a cross validation method. An appropriate number of variables are identified as model inputs to ensure that a model is neither overfitted nor underfitted. Based on the model input selection results, calibration data selection is studied. Uncertainty of model performances due to calibration data selection is investigated with a random selection method. An approach using the cluster method is applied in order to enhance model calibration practice based on the principle of selecting representative data for calibration. The comparison between results from the cluster selection method and random selection shows that the former can significantly improve performances of calibrated models. It is found that the information content in calibration data is important in addition to the size of calibration data.

  2. Statistical plant set estimation using Schroeder-phased multisinusoidal input design

    NASA Technical Reports Server (NTRS)

    Bayard, D. S.

    1992-01-01

    A frequency domain method is developed for plant set estimation. The estimation of a plant 'set' rather than a point estimate is required to support many methods of modern robust control design. The approach here is based on using a Schroeder-phased multisinusoid input design which has the special property of placing input energy only at the discrete frequency points used in the computation. A detailed analysis of the statistical properties of the frequency domain estimator is given, leading to exact expressions for the probability distribution of the estimation error, and many important properties. It is shown that, for any nominal parametric plant estimate, one can use these results to construct an overbound on the additive uncertainty to any prescribed statistical confidence. The 'soft' bound thus obtained can be used to replace 'hard' bounds presently used in many robust control analysis and synthesis methods.

  3. Higher order visual input to the mushroom bodies in the bee, Bombus impatiens.

    PubMed

    Paulk, Angelique C; Gronenberg, Wulfila

    2008-11-01

    To produce appropriate behaviors based on biologically relevant associations, sensory pathways conveying different modalities are integrated by higher-order central brain structures, such as insect mushroom bodies. To address this function of sensory integration, we characterized the structure and response of optic lobe (OL) neurons projecting to the calyces of the mushroom bodies in bees. Bees are well known for their visual learning and memory capabilities and their brains possess major direct visual input from the optic lobes to the mushroom bodies. To functionally characterize these visual inputs to the mushroom bodies, we recorded intracellularly from neurons in bumblebees (Apidae: Bombus impatiens) and a single neuron in a honeybee (Apidae: Apis mellifera) while presenting color and motion stimuli. All of the mushroom body input neurons were color sensitive while a subset was motion sensitive. Additionally, most of the mushroom body input neurons would respond to the first, but not to subsequent, presentations of repeated stimuli. In general, the medulla or lobula neurons projecting to the calyx signaled specific chromatic, temporal, and motion features of the visual world to the mushroom bodies, which included sensory information required for the biologically relevant associations bees form during foraging tasks.

  4. Parameters Selection for Bivariate Multiscale Entropy Analysis of Postural Fluctuations in Fallers and Non-Fallers Older Adults.

    PubMed

    Ramdani, Sofiane; Bonnet, Vincent; Tallon, Guillaume; Lagarde, Julien; Bernard, Pierre Louis; Blain, Hubert

    2016-08-01

    Entropy measures are often used to quantify the regularity of postural sway time series. Recent methodological developments provided both multivariate and multiscale approaches allowing the extraction of complexity features from physiological signals; see "Dynamical complexity of human responses: A multivariate data-adaptive framework," in Bulletin of Polish Academy of Science and Technology, vol. 60, p. 433, 2012. The resulting entropy measures are good candidates for the analysis of bivariate postural sway signals exhibiting nonstationarity and multiscale properties. These methods are dependant on several input parameters such as embedding parameters. Using two data sets collected from institutionalized frail older adults, we numerically investigate the behavior of a recent multivariate and multiscale entropy estimator; see "Multivariate multiscale entropy: A tool for complexity analysis of multichannel data," Physics Review E, vol. 84, p. 061918, 2011. We propose criteria for the selection of the input parameters. Using these optimal parameters, we statistically compare the multivariate and multiscale entropy values of postural sway data of non-faller subjects to those of fallers. These two groups are discriminated by the resulting measures over multiple time scales. We also demonstrate that the typical parameter settings proposed in the literature lead to entropy measures that do not distinguish the two groups. This last result confirms the importance of the selection of appropriate input parameters.

  5. Effect of deep pressure input on parasympathetic system in patients with wisdom tooth surgery.

    PubMed

    Chen, Hsin-Yung; Yang, Hsiang; Meng, Ling-Fu; Chan, Pei-Ying Sarah; Yang, Chia-Yen; Chen, Hsin-Ming

    2016-10-01

    Deep pressure input is used to normalize physiological arousal due to stress. Wisdom tooth surgery is an invasive dental procedure with high stress levels, and an alleviation strategy is rarely applied during extraction. In this study, we investigated the effects of deep pressure input on autonomic responses to wisdom tooth extraction in healthy adults. A randomized, controlled, crossover design was used for dental patients who were allocated to experimental and control groups that received treatment with or without deep pressure input, respectively. Autonomic indicators, namely the heart rate (HR), percentage of low-frequency (LF) HR variability (LF-HRV), percentage of high-frequency (HF) HRV (HF-HRV), and LF/HF HRV ratio (LF/HF-HRV), were assessed at the baseline, during wisdom tooth extraction, and in the posttreatment phase. Wisdom tooth extraction caused significant autonomic parameter changes in both groups; however, differential response patterns were observed between the two groups. In particular, deep pressure input in the experimental group was associated with higher HF-HRV and lower LF/HF-HRV during extraction compared with those in the control group. LF/HF-HRV measurement revealed balanced sympathovagal activation in response to deep pressure application. The results suggest that the application of deep pressure alters the response of HF-HRV and facilitates maintaining sympathovagal balance during wisdom tooth extraction. Copyright © 2016. Published by Elsevier B.V.

  6. Prediction of Chl-a concentrations in an eutrophic lake using ANN models with hybrid inputs

    NASA Astrophysics Data System (ADS)

    Aksoy, A.; Yuzugullu, O.

    2017-12-01

    Chlorophyll-a (Chl-a) concentrations in water bodies exhibit both spatial and temporal variations. As a result, frequent sampling is required with higher number of samples. This motivates the use of remote sensing as a monitoring tool. Yet, prediction performances of models that convert radiance values into Chl-a concentrations can be poor in shallow lakes. In this study, Chl-a concentrations in Lake Eymir, a shallow eutrophic lake in Ankara (Turkey), are determined using artificial neural network (ANN) models that use hybrid inputs composed of water quality and meteorological data as well as remotely sensed radiance values to improve prediction performance. Following a screening based on multi-collinearity and principal component analysis (PCA), dissolved-oxygen concentration (DO), pH, turbidity, and humidity were selected among several parameters as the constituents of the hybrid input dataset. Radiance values were obtained from QuickBird-2 satellite. Conversion of the hybrid input into Chl-a concentrations were studied for two different periods in the lake. ANN models were successful in predicting Chl-a concentrations. Yet, prediction performance declined for low Chl-a concentrations in the lake. In general, models with hybrid inputs were superior over the ones that solely used remotely sensed data.

  7. Energy-positive sewage sludge pre-treatment with a novel ultrasonic flatbed reactor at low energy input.

    PubMed

    Lippert, Thomas; Bandelin, Jochen; Musch, Alexandra; Drewes, Jörg E; Koch, Konrad

    2018-05-20

    The performance of a novel ultrasonic flatbed reactor for sewage sludge pre-treatment was assessed for three different waste activated sludges. The study systematically investigated the impact of specific energy input (200 - 3,000 kJ/kg TS ) on the degree of disintegration (DD COD , i.e. ratio between ultrasonically and maximum chemically solubilized COD) and methane production enhancement. Relationship between DD COD and energy input was linear, for all sludges tested. Methane yields were significantly increased for both low (200 kJ/kg TS ) and high (2,000 - 3,000 kJ/kg TS ) energy inputs, while intermediate inputs (400 - 1,000 kJ/kg TS ) showed no significant improvement. High inputs additionally accelerated reaction kinetics, but were limited to similar gains as low inputs (max. 12%), despite the considerably higher DD COD values. Energy balance was only positive for 200 kJ/kg TS -treatments, with a maximum energy recovery of 122%. Results suggest that floc deagglomeration rather than cell lysis (DD COD =1% - 5% at 200 kJ/kg TS ) is the key principle of energy-positive sludge sonication. Copyright © 2018 Elsevier Ltd. All rights reserved.

  8. Significance of Input Correlations in Striatal Function

    PubMed Central

    Yim, Man Yi; Aertsen, Ad; Kumar, Arvind

    2011-01-01

    The striatum is the main input station of the basal ganglia and is strongly associated with motor and cognitive functions. Anatomical evidence suggests that individual striatal neurons are unlikely to share their inputs from the cortex. Using a biologically realistic large-scale network model of striatum and cortico-striatal projections, we provide a functional interpretation of the special anatomical structure of these projections. Specifically, we show that weak pairwise correlation within the pool of inputs to individual striatal neurons enhances the saliency of signal representation in the striatum. By contrast, correlations among the input pools of different striatal neurons render the signal representation less distinct from background activity. We suggest that for the network architecture of the striatum, there is a preferred cortico-striatal input configuration for optimal signal representation. It is further enhanced by the low-rate asynchronous background activity in striatum, supported by the balance between feedforward and feedback inhibitions in the striatal network. Thus, an appropriate combination of rates and correlations in the striatal input sets the stage for action selection presumably implemented in the basal ganglia. PMID:22125480

  9. Wireless, relative-motion computer input device

    DOEpatents

    Holzrichter, John F.; Rosenbury, Erwin T.

    2004-05-18

    The present invention provides a system for controlling a computer display in a workspace using an input unit/output unit. A train of EM waves are sent out to flood the workspace. EM waves are reflected from the input unit/output unit. A relative distance moved information signal is created using the EM waves that are reflected from the input unit/output unit. Algorithms are used to convert the relative distance moved information signal to a display signal. The computer display is controlled in response to the display signal.

  10. Sensitivity of predicted bioaerosol exposure from open windrow composting facilities to ADMS dispersion model parameters.

    PubMed

    Douglas, P; Tyrrel, S F; Kinnersley, R P; Whelan, M; Longhurst, P J; Walsh, K; Pollard, S J T; Drew, G H

    2016-12-15

    Bioaerosols are released in elevated quantities from composting facilities and are associated with negative health effects, although dose-response relationships are not well understood, and require improved exposure classification. Dispersion modelling has great potential to improve exposure classification, but has not yet been extensively used or validated in this context. We present a sensitivity analysis of the ADMS dispersion model specific to input parameter ranges relevant to bioaerosol emissions from open windrow composting. This analysis provides an aid for model calibration by prioritising parameter adjustment and targeting independent parameter estimation. Results showed that predicted exposure was most sensitive to the wet and dry deposition modules and the majority of parameters relating to emission source characteristics, including pollutant emission velocity, source geometry and source height. This research improves understanding of the accuracy of model input data required to provide more reliable exposure predictions. Copyright © 2016. Published by Elsevier Ltd.

  11. Effects of hypothermically reduced plantar skin inputs on anticipatory and compensatory balance responses.

    PubMed

    Germano, Andresa M C; Schmidt, Daniel; Milani, Thomas L

    2016-06-29

    Anticipatory and compensatory balance responses are used by the central nervous system (CNS) to preserve balance, hence they significantly contribute to the understanding of physiological mechanisms of postural control. It is well established that various sensory systems contribute to the regulation of balance. However, it is still unclear which role each individual sensory system (e.g. plantar mechanoreceptors) plays in balance regulation. This becomes also evident in various patient populations, for instance in diabetics with reduced plantar sensitivity. To investigate these sensory mechanisms, approaches like hypothermia to deliberately reduce plantar afferent input have been applied. But there are some limitations regarding hypothermic procedures in previous studies: Not only plantar aspects of the feet might be affected and maintaining the hypothermic effect during data collection. Therefore, the aim of the present study was to induce a permanent and controlled plantar hypothermia and to examine its effects on anticipatory and compensatory balance responses. We hypothesized deteriorations in anticipatory and compensatory balance responses as increased center of pressure excursions (COP) and electromyographic activity (EMG) in response to the hypothermic plantar procedure. 52 healthy and young subjects (23.6 ± 3.0 years) performed balance tests (unexpected perturbations). Subjects' foot soles were exposed to three temperatures while standing upright: 25, 12 and 0 °C. COP and EMG were analyzed during two intervals of anticipatory and one interval of compensatory balance responses (intervals 0, 1 and 2, respectively). Similar plantar temperatures confirmed the successful implementation of the thermal platform. No significant COP and EMG differences were found for the anticipatory responses (intervals 0 and 1) under the hyperthermia procedure. Parameters in interval 2 showed generally decreased values in response to cooling. No changes in anticipatory

  12. Retrieving high-resolution surface solar radiation with cloud parameters derived by combining MODIS and MTSAT data

    NASA Astrophysics Data System (ADS)

    Tang, Wenjun; Qin, Jun; Yang, Kun; Liu, Shaomin; Lu, Ning; Niu, Xiaolei

    2016-03-01

    Cloud parameters (cloud mask, effective particle radius, and liquid/ice water path) are the important inputs in estimating surface solar radiation (SSR). These parameters can be derived from MODIS with high accuracy, but their temporal resolution is too low to obtain high-temporal-resolution SSR retrievals. In order to obtain hourly cloud parameters, an artificial neural network (ANN) is applied in this study to directly construct a functional relationship between MODIS cloud products and Multifunctional Transport Satellite (MTSAT) geostationary satellite signals. In addition, an efficient parameterization model for SSR retrieval is introduced and, when driven with MODIS atmospheric and land products, its root mean square error (RMSE) is about 100 W m-2 for 44 Baseline Surface Radiation Network (BSRN) stations. Once the estimated cloud parameters and other information (such as aerosol, precipitable water, ozone) are input to the model, we can derive SSR at high spatiotemporal resolution. The retrieved SSR is first evaluated against hourly radiation data at three experimental stations in the Haihe River basin of China. The mean bias error (MBE) and RMSE in hourly SSR estimate are 12.0 W m-2 (or 3.5 %) and 98.5 W m-2 (or 28.9 %), respectively. The retrieved SSR is also evaluated against daily radiation data at 90 China Meteorological Administration (CMA) stations. The MBEs are 9.8 W m-2 (or 5.4 %); the RMSEs in daily and monthly mean SSR estimates are 34.2 W m-2 (or 19.1 %) and 22.1 W m-2 (or 12.3 %), respectively. The accuracy is comparable to or even higher than two other radiation products (GLASS and ISCCP-FD), and the present method is more computationally efficient and can produce hourly SSR data at a spatial resolution of 5 km.

  13. Effect of input compression and input frequency response on music perception in cochlear implant users.

    PubMed

    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.

  14. Input integration around the dendritic branches in hippocampal dentate granule cells.

    PubMed

    Kamijo, Tadanobu Chuyo; Hayakawa, Hirofumi; Fukushima, Yasuhiro; Kubota, Yoshiyuki; Isomura, Yoshikazu; Tsukada, Minoru; Aihara, Takeshi

    2014-08-01

    Recent studies have shown that the dendrites of several neurons are not simple translators but are crucial facilitators of excitatory postsynaptic potential (EPSP) propagation and summation of synaptic inputs to compensate for inherent voltage attenuation. Granule cells (GCs)are located at the gateway for valuable information arriving at the hippocampus from the entorhinal cortex. However, the underlying mechanisms of information integration along the dendrites of GCs in the hippocampus are still unclear. In this study, we investigated the input integration around dendritic branches of GCs in the rat hippocampus. We applied differential spatiotemporal stimulations to the dendrites using a high-speed glutamate-uncaging laser. Our results showed that when two sites close to and equidistant from a branching point were simultaneously stimulated, a nonlinear summation of EPSPs was observed at the soma. In addition, nonlinear summation (facilitation) depended on the stimulus location and was significantly blocked by the application of a voltage-dependent Ca(2+) channel antagonist. These findings suggest that the nonlinear summation of EPSPs around the dendritic branches of hippocampal GCs is a result of voltage-dependent Ca(2+) channel activation and may play a crucial role in the integration of input information.

  15. Blind identification of the kinetic parameters in three-compartment models

    NASA Astrophysics Data System (ADS)

    Riabkov, Dmitri Y.; Di Bella, Edward V. R.

    2004-03-01

    Quantified knowledge of tissue kinetic parameters in the regions of the brain and other organs can offer information useful in clinical and research applications. Dynamic medical imaging with injection of radioactive or paramagnetic tracer can be used for this measurement. The kinetics of some widely used tracers such as [18F]2-fluoro-2-deoxy-D-glucose can be described by a three-compartment physiological model. The kinetic parameters of the tissue can be estimated from dynamically acquired images. Feasibility of estimation by blind identification, which does not require knowledge of the blood input, is considered analytically and numerically in this work for the three-compartment type of tissue response. The non-uniqueness of the two-region case for blind identification of kinetic parameters in three-compartment model is shown; at least three regions are needed for the blind identification to be unique. Numerical results for the accuracy of these blind identification methods in different conditions were considered. Both a separable variables least-squares (SLS) approach and an eigenvector-based algorithm for multichannel blind deconvolution approach were used. The latter showed poor accuracy. Modifications for non-uniform time sampling were also developed. Also, another method which uses a model for the blood input was compared. Results for the macroparameter K, which reflects the metabolic rate of glucose usage, using three regions with noise showed comparable accuracy for the separable variables least squares method and for the input model-based method, and slightly worse accuracy for SLS with the non-uniform sampling modification.

  16. Investigation of Thermophysical Parameters Properties for Enhancing Overpressure Mechanism Estimation. Case Study: Miri Area, West Baram Delta

    NASA Astrophysics Data System (ADS)

    Adha, Kurniawan; Yusoff, Wan Ismail Wan; Almanna Lubis, Luluan

    2017-10-01

    Determining the pore pressure data and overpressure zone is a compulsory part of oil and gas exploration in which the data can enhance the safety with profit and preventing the drilling hazards. Investigation of thermophysical parameters such as temperature and thermal conductivity can enhance the pore pressure estimation for overpressure mechanism determination. Since those parameters are dependent on rock properties, it may reflect the changes on the column of thermophysical parameters when there is abnormally in pore pressure. The study was conducted in “MRI 1” well offshore Sarawak, where a new approach method designed to determine the overpressure generation. The study was insisted the contribution of thermophysical parameters for supporting the velocity analysis method, petrophysical analysis were done in these studies. Four thermal facies were identified along the well. The overpressure developed below the thermal facies 4, where the pressure reached 38 Mpa and temperature was increasing significantly. The velocity and the thermal conductivity cross plots shows a linear relationship since the both parameters mainly are the function of the rock compaction. When the rock more compact, the particles were brought closer into contact and making the sound wave going faster while the thermal conductivity were increasing. In addition, the increment of temperature and high heat flow indicated the presence of fluid expansion mechanism. Since the shale sonic velocity and density analysis were the common methods in overpressure mechanism and pore pressure estimation. As the addition parameters for determining overpressure zone, the presence of thermophysical analysis was enhancing the current method, where the current method was the single function of velocity analysis. The presence of thermophysical analysis will improve the understanding in overpressure mechanism determination as the new input parameters. Thus, integrated of thermophysical technique and velocity

  17. User's manual for master: Modeling of aerodynamic surfaces by 3-dimensional explicit representation. [input to three dimensional computational fluid dynamics

    NASA Technical Reports Server (NTRS)

    Gibson, S. G.

    1983-01-01

    A system of computer programs was developed to model general three dimensional surfaces. Surfaces are modeled as sets of parametric bicubic patches. There are also capabilities to transform coordinates, to compute mesh/surface intersection normals, and to format input data for a transonic potential flow analysis. A graphical display of surface models and intersection normals is available. There are additional capabilities to regulate point spacing on input curves and to compute surface/surface intersection curves. Input and output data formats are described; detailed suggestions are given for user input. Instructions for execution are given, and examples are shown.

  18. Development code for sensitivity and uncertainty analysis of input on the MCNPX for neutronic calculation in PWR core

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

    Hartini, Entin, E-mail: entin@batan.go.id; Andiwijayakusuma, Dinan, E-mail: entin@batan.go.id

    2014-09-30

    This research was carried out on the development of code for uncertainty analysis is based on a statistical approach for assessing the uncertainty input parameters. In the butn-up calculation of fuel, uncertainty analysis performed for input parameters fuel density, coolant density and fuel temperature. This calculation is performed during irradiation using Monte Carlo N-Particle Transport. The Uncertainty method based on the probabilities density function. Development code is made in python script to do coupling with MCNPX for criticality and burn-up calculations. Simulation is done by modeling the geometry of PWR terrace, with MCNPX on the power 54 MW with fuelmore » type UO2 pellets. The calculation is done by using the data library continuous energy cross-sections ENDF / B-VI. MCNPX requires nuclear data in ACE format. Development of interfaces for obtaining nuclear data in the form of ACE format of ENDF through special process NJOY calculation to temperature changes in a certain range.« less

  19. Development code for sensitivity and uncertainty analysis of input on the MCNPX for neutronic calculation in PWR core

    NASA Astrophysics Data System (ADS)

    Hartini, Entin; Andiwijayakusuma, Dinan

    2014-09-01

    This research was carried out on the development of code for uncertainty analysis is based on a statistical approach for assessing the uncertainty input parameters. In the butn-up calculation of fuel, uncertainty analysis performed for input parameters fuel density, coolant density and fuel temperature. This calculation is performed during irradiation using Monte Carlo N-Particle Transport. The Uncertainty method based on the probabilities density function. Development code is made in python script to do coupling with MCNPX for criticality and burn-up calculations. Simulation is done by modeling the geometry of PWR terrace, with MCNPX on the power 54 MW with fuel type UO2 pellets. The calculation is done by using the data library continuous energy cross-sections ENDF / B-VI. MCNPX requires nuclear data in ACE format. Development of interfaces for obtaining nuclear data in the form of ACE format of ENDF through special process NJOY calculation to temperature changes in a certain range.

  20. Role of anaerobic fungi in wheat straw degradation and effects of plant feed additives on rumen fermentation parameters in vitro.

    PubMed

    Dagar, S S; Singh, N; Goel, N; Kumar, S; Puniya, A K

    2015-01-01

    In the present study, rumen microbial groups, i.e. total rumen microbes (TRM), total anaerobic fungi (TAF), avicel enriched bacteria (AEB) and neutral detergent fibre enriched bacteria (NEB) were evaluated for wheat straw (WS) degradability and different fermentation parameters in vitro. Highest WS degradation was shown for TRM, followed by TAF, NEB and least by AEB. Similar patterns were observed with total gas production and short chain fatty acid profiles. Overall, TAF emerged as the most potent individual microbial group. In order to enhance the fibrolytic and rumen fermentation potential of TAF, we evaluated 18 plant feed additives in vitro. Among these, six plant additives namely Albizia lebbeck, Alstonia scholaris, Bacopa monnieri, Lawsonia inermis, Psidium guajava and Terminalia arjuna considerably improved WS degradation by TAF. Further evaluation showed A. lebbeck as best feed additive. The study revealed that TAF plays a significant role in WS degradation and their fibrolytic activities can be improved by inclusion of A. lebbeck in fermentation medium. Further studies are warranted to elucidate its active constituents, effect on fungal population and in vivo potential in animal system.

  1. Takagi-Sugeno fuzzy model based robust dissipative control for uncertain flexible spacecraft with saturated time-delay input.

    PubMed

    Xu, Shidong; Sun, Guanghui; Sun, Weichao

    2017-01-01

    In this paper, the problem of robust dissipative control is investigated for uncertain flexible spacecraft based on Takagi-Sugeno (T-S) fuzzy model with saturated time-delay input. Different from most existing strategies, T-S fuzzy approximation approach is used to model the nonlinear dynamics of flexible spacecraft. Simultaneously, the physical constraints of system, like input delay, input saturation, and parameter uncertainties, are also taken care of in the fuzzy model. By employing Lyapunov-Krasovskii method and convex optimization technique, a novel robust controller is proposed to implement rest-to-rest attitude maneuver for flexible spacecraft, and the guaranteed dissipative performance enables the uncertain closed-loop system to reject the influence of elastic vibrations and external disturbances. Finally, an illustrative design example integrated with simulation results are provided to confirm the applicability and merits of the developed control strategy. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  2. Morphine disinhibits glutamatergic input to VTA dopamine neurons and promotes dopamine neuron excitation.

    PubMed

    Chen, Ming; Zhao, Yanfang; Yang, Hualan; Luan, Wenjie; Song, Jiaojiao; Cui, Dongyang; Dong, Yi; Lai, Bin; Ma, Lan; Zheng, Ping

    2015-07-24

    One reported mechanism for morphine activation of dopamine (DA) neurons of the ventral tegmental area (VTA) is the disinhibition model of VTA-DA neurons. Morphine inhibits GABA inhibitory neurons, which shifts the balance between inhibitory and excitatory input to VTA-DA neurons in favor of excitation and then leads to VTA-DA neuron excitation. However, it is not known whether morphine has an additional strengthening effect on excitatory input. Our results suggest that glutamatergic input to VTA-DA neurons is inhibited by GABAergic interneurons via GABAB receptors and that morphine promotes presynaptic glutamate release by removing this inhibition. We also studied the contribution of the morphine-induced disinhibitory effect on the presynaptic glutamate release to the overall excitatory effect of morphine on VTA-DA neurons and related behavior. Our results suggest that the disinhibitory action of morphine on presynaptic glutamate release might be the main mechanism for morphine-induced increase in VTA-DA neuron firing and related behaviors.

  3. Microbial respiration, but not biomass, responded linearly to increasing light fraction organic matter input: Consequences for carbon sequestration

    PubMed Central

    Rui, Yichao; Murphy, Daniel V.; Wang, Xiaoli; Hoyle, Frances C.

    2016-01-01

    Rebuilding ‘lost’ soil carbon (C) is a priority in mitigating climate change and underpinning key soil functions that support ecosystem services. Microorganisms determine if fresh C input is converted into stable soil organic matter (SOM) or lost as CO2. Here we quantified if microbial biomass and respiration responded positively to addition of light fraction organic matter (LFOM, representing recent inputs of plant residue) in an infertile semi-arid agricultural soil. Field trial soil with different historical plant residue inputs [soil C content: control (tilled) = 9.6 t C ha−1 versus tilled + plant residue treatment (tilled + OM) = 18.0 t C ha−1] were incubated in the laboratory with a gradient of LFOM equivalent to 0 to 3.8 t C ha−1 (0 to 500% LFOM). Microbial biomass C significantly declined under increased rates of LFOM addition while microbial respiration increased linearly, leading to a decrease in the microbial C use efficiency. We hypothesise this was due to insufficient nutrients to form new microbial biomass as LFOM input increased the ratio of C to nitrogen, phosphorus and sulphur of soil. Increased CO2 efflux but constrained microbial growth in response to LFOM input demonstrated the difficulty for C storage in this environment. PMID:27752083

  4. The nature of the language input affects brain activation during learning from a natural language

    PubMed Central

    Plante, Elena; Patterson, Dianne; Gómez, Rebecca; Almryde, Kyle R.; White, Milo G.; Asbjørnsen, Arve E.

    2015-01-01

    Artificial language studies have demonstrated that learners are able to segment individual word-like units from running speech using the transitional probability information. However, this skill has rarely been examined in the context of natural languages, where stimulus parameters can be quite different. In this study, two groups of English-speaking learners were exposed to Norwegian sentences over the course of three fMRI scans. One group was provided with input in which transitional probabilities predicted the presence of target words in the sentences. This group quickly learned to identify the target words and fMRI data revealed an extensive and highly dynamic learning network. These results were markedly different from activation seen for a second group of participants. This group was provided with highly similar input that was modified so that word learning based on syllable co-occurrences was not possible. These participants showed a much more restricted network. The results demonstrate that the nature of the input strongly influenced the nature of the network that learners employ to learn the properties of words in a natural language. PMID:26257471

  5. Sequential state estimation of nonlinear/non-Gaussian systems with stochastic input for turbine degradation estimation

    NASA Astrophysics Data System (ADS)

    Hanachi, Houman; Liu, Jie; Banerjee, Avisekh; Chen, Ying

    2016-05-01

    Health state estimation of inaccessible components in complex systems necessitates effective state estimation techniques using the observable variables of the system. The task becomes much complicated when the system is nonlinear/non-Gaussian and it receives stochastic input. In this work, a novel sequential state estimation framework is developed based on particle filtering (PF) scheme for state estimation of general class of nonlinear dynamical systems with stochastic input. Performance of the developed framework is then validated with simulation on a Bivariate Non-stationary Growth Model (BNGM) as a benchmark. In the next step, three-year operating data of an industrial gas turbine engine (GTE) are utilized to verify the effectiveness of the developed framework. A comprehensive thermodynamic model for the GTE is therefore developed to formulate the relation of the observable parameters and the dominant degradation symptoms of the turbine, namely, loss of isentropic efficiency and increase of the mass flow. The results confirm the effectiveness of the developed framework for simultaneous estimation of multiple degradation symptoms in complex systems with noisy measured inputs.

  6. Parameter estimation in spiking neural networks: a reverse-engineering approach.

    PubMed

    Rostro-Gonzalez, H; Cessac, B; Vieville, T

    2012-04-01

    This paper presents a reverse engineering approach for parameter estimation in spiking neural networks (SNNs). We consider the deterministic evolution of a time-discretized network with spiking neurons, where synaptic transmission has delays, modeled as a neural network of the generalized integrate and fire type. Our approach aims at by-passing the fact that the parameter estimation in SNN results in a non-deterministic polynomial-time hard problem when delays are to be considered. Here, this assumption has been reformulated as a linear programming (LP) problem in order to perform the solution in a polynomial time. Besides, the LP problem formulation makes the fact that the reverse engineering of a neural network can be performed from the observation of the spike times explicit. Furthermore, we point out how the LP adjustment mechanism is local to each neuron and has the same structure as a 'Hebbian' rule. Finally, we present a generalization of this approach to the design of input-output (I/O) transformations as a practical method to 'program' a spiking network, i.e. find a set of parameters allowing us to exactly reproduce the network output, given an input. Numerical verifications and illustrations are provided.

  7. Linking SOM Content, Chemistry, and Decomposition: Complex Responses to Input Manipulation and Long-term Incubation

    NASA Astrophysics Data System (ADS)

    Bridgham, S. D.; Reynolds, L. L.; Tfaily, M.; Roscioli, K.; Lajtha, K.; Bowden, R.; Johnson, B. R.

    2014-12-01

    The mechanisms of soil organic matter (SOM) protection and their relationship with carbon inputs and decomposition are poorly understood. We used Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) and Fourier transform infrared spectroscopy (FTIR) to characterize SOM in soils exposed to litter-input exclusion or addition for 20 years, and subsequently incubated for more than a year. Our aim was to describe shifts in SOM content and chemical composition due to the input manipulation and degree of decomposition, particularly in the light (i.e., free particulate, younger) versus the heavy (mineral-adsorbed, older) fractions of SOM, and to link these shifts to carbon mineralization rates. The soils were collected from a deciduous hardwood forest in Meadville, PA, one of the Detritus and Input Removal Treatment (DIRT) sites. They were subjected to either litter and root exclusion (NI), double litter (DL), or ambient inputs (CO) for 20 years and subsequently incubated at 35oC for 525 days. Soils from the beginning and end of the incubation were divided into light and heavy fractions using 1.8 g cm-3 sodium polytungstate. Bulk CO soils and heavy fractions of NI, DL, and CO soil were analyzed with FTICR-MS, while light and heavy fractions were analyzed with FTIR. Twenty years of input exclusion decreased the mineralization rate, the total carbon respired, and total carbon content, though litter addition had no significant effect (NI < CO = DL). The FTICR-MS and FTIR data reveal substantial differences in SOM chemistry among DIRT treatments, fractions, and before and after incubation. CO contained several classes of compounds, including alcohols and phenols, not detected in either DL or NI soils, and all samples showed an enrichment in aromatics between the light and heavy fractions. The heavy fraction DL soils were proportionally enriched in lipids compared to NI and CO soils, and these lipids were preferentially mineralized during incubation. Heavy

  8. Multiple-input multiple-output causal strategies for gene selection.

    PubMed

    Bontempi, Gianluca; Haibe-Kains, Benjamin; Desmedt, Christine; Sotiriou, Christos; Quackenbush, John

    2011-11-25

    Traditional strategies for selecting variables in high dimensional classification problems aim to find sets of maximally relevant variables able to explain the target variations. If these techniques may be effective in generalization accuracy they often do not reveal direct causes. The latter is essentially related to the fact that high correlation (or relevance) does not imply causation. In this study, we show how to efficiently incorporate causal information into gene selection by moving from a single-input single-output to a multiple-input multiple-output setting. We show in synthetic case study that a better prioritization of causal variables can be obtained by considering a relevance score which incorporates a causal term. In addition we show, in a meta-analysis study of six publicly available breast cancer microarray datasets, that the improvement occurs also in terms of accuracy. The biological interpretation of the results confirms the potential of a causal approach to gene selection. Integrating causal information into gene selection algorithms is effective both in terms of prediction accuracy and biological interpretation.

  9. Adaptive fuzzy predictive sliding control of uncertain nonlinear systems with bound-known input delay.

    PubMed

    Khazaee, Mostafa; Markazi, Amir H D; Omidi, Ehsan

    2015-11-01

    In this paper, a new Adaptive Fuzzy Predictive Sliding Mode Control (AFP-SMC) is presented for nonlinear systems with uncertain dynamics and unknown input delay. The control unit consists of a fuzzy inference system to approximate the ideal linearization control, together with a switching strategy to compensate for the estimation errors. Also, an adaptive fuzzy predictor is used to estimate the future values of the system states to compensate for the time delay. The adaptation laws are used to tune the controller and predictor parameters, which guarantee the stability based on a Lyapunov-Krasovskii functional. To evaluate the method effectiveness, the simulation and experiment on an overhead crane system are presented. According to the obtained results, AFP-SMC can effectively control the uncertain nonlinear systems, subject to input delays of known bound. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  10. Perturbed-input-data ensemble modeling of magnetospheric dynamics

    NASA Astrophysics Data System (ADS)

    Morley, S.; Steinberg, J. T.; Haiducek, J. D.; Welling, D. T.; Hassan, E.; Weaver, B. P.

    2017-12-01

    Many models of Earth's magnetospheric dynamics - including global magnetohydrodynamic models, reduced complexity models of substorms and empirical models - are driven by solar wind parameters. To provide consistent coverage of the upstream solar wind these measurements are generally taken near the first Lagrangian point (L1) and algorithmically propagated to the nose of Earth's bow shock. However, the plasma and magnetic field measured near L1 is a point measurement of an inhomogeneous medium, so the individual measurement may not be sufficiently representative of the broader region near L1. The measured plasma may not actually interact with the Earth, and the solar wind structure may evolve between L1 and the bow shock. To quantify uncertainties in simulations, as well as to provide probabilistic forecasts, it is desirable to use perturbed input ensembles of magnetospheric and space weather forecasting models. By using concurrent measurements of the solar wind near L1 and near the Earth, we construct a statistical model of the distributions of solar wind parameters conditioned on their upstream value. So that we can draw random variates from our model we specify the conditional probability distributions using Kernel Density Estimation. We demonstrate the utility of this approach using ensemble runs of selected models that can be used for space weather prediction.

  11. Analyzing the sensitivity of a flood risk assessment model towards its input data

    NASA Astrophysics Data System (ADS)

    Glas, Hanne; Deruyter, Greet; De Maeyer, Philippe; Mandal, Arpita; James-Williamson, Sherene

    2016-11-01

    The Small Island Developing States are characterized by an unstable economy and low-lying, densely populated cities, resulting in a high vulnerability to natural hazards. Flooding affects more people than any other hazard. To limit the consequences of these hazards, adequate risk assessments are indispensable. Satisfactory input data for these assessments are hard to acquire, especially in developing countries. Therefore, in this study, a methodology was developed and evaluated to test the sensitivity of a flood model towards its input data in order to determine a minimum set of indispensable data. In a first step, a flood damage assessment model was created for the case study of Annotto Bay, Jamaica. This model generates a damage map for the region based on the flood extent map of the 2001 inundations caused by Tropical Storm Michelle. Three damages were taken into account: building, road and crop damage. Twelve scenarios were generated, each with a different combination of input data, testing one of the three damage calculations for its sensitivity. One main conclusion was that population density, in combination with an average number of people per household, is a good parameter in determining the building damage when exact building locations are unknown. Furthermore, the importance of roads for an accurate visual result was demonstrated.

  12. Intelligent RF-Based Gesture Input Devices Implemented Using e-Textiles.

    PubMed

    Hughes, Dana; Profita, Halley; Radzihovsky, Sarah; Correll, Nikolaus

    2017-01-24

    We present an radio-frequency (RF)-based approach to gesture detection and recognition, using e-textile versions of common transmission lines used in microwave circuits. This approach allows for easy fabrication of input swatches that can detect a continuum of finger positions and similarly basic gestures, using a single measurement line. We demonstrate that the swatches can perform gesture detection when under thin layers of cloth or when weatherproofed, providing a high level of versatility not present with other types of approaches. Additionally, using small convolutional neural networks, low-level gestures can be identified with a high level of accuracy using a small, inexpensive microcontroller, allowing for an intelligent fabric that reports only gestures of interest, rather than a simple sensor requiring constant surveillance from an external computing device. The resulting e-textile smart composite has applications in controlling wearable devices by providing a simple, eyes-free mechanism to input simple gestures.

  13. Scaling of global input-output networks

    NASA Astrophysics Data System (ADS)

    Liang, Sai; Qi, Zhengling; Qu, Shen; Zhu, Ji; Chiu, Anthony S. F.; Jia, Xiaoping; Xu, Ming

    2016-06-01

    Examining scaling patterns of networks can help understand how structural features relate to the behavior of the networks. Input-output networks consist of industries as nodes and inter-industrial exchanges of products as links. Previous studies consider limited measures for node strengths and link weights, and also ignore the impact of dataset choice. We consider a comprehensive set of indicators in this study that are important in economic analysis, and also examine the impact of dataset choice, by studying input-output networks in individual countries and the entire world. Results show that Burr, Log-Logistic, Log-normal, and Weibull distributions can better describe scaling patterns of global input-output networks. We also find that dataset choice has limited impacts on the observed scaling patterns. Our findings can help examine the quality of economic statistics, estimate missing data in economic statistics, and identify key nodes and links in input-output networks to support economic policymaking.

  14. Auditory input modulates sleep: an intra-cochlear-implanted human model.

    PubMed

    Velluti, Ricardo A; Pedemonte, Marisa; Suárez, Hámlet; Bentancor, Claudia; Rodríguez-Servetti, Zulma

    2010-12-01

    To properly demonstrate the effect of auditory input on sleep of intra-cochlear-implanted patients, the following approach was developed. Four implanted deaf patients were recorded during four nights: two nights with the implant OFF, with no auditory input, and two nights with the implant ON, that is, with normal auditory input, being only the common night sounds present, without any additional auditory stimuli delivered. The sleep patterns of another five deaf people were used as controls, exhibiting normal sleep organization. Moreover, the four experimental patients with intra-cochlear devices and the implant OFF also showed normal sleep patterns. On comparison of the night recordings with the implant ON and OFF, a new sleep organization was observed for the recordings with the implant ON, suggesting that brain plasticity may produce changes in the sleep stage percentages while maintaining the ultradian rhythm. During sleep with the implant ON, the analysis of the electroencephalographic delta, theta and alpha bands in the frequency domain, using the Fast Fourier Transform, revealed a diversity of changes in the power originated in the contralateral cortical temporal region. Different power shifts were observed, perhaps related to the exact position of the implant inside the cochlea and the scalp electrode location. In conclusion, this pilot study shows that the auditory input in humans can introduce changes in central nervous system activity leading to shifts in sleep characteristics, as previously demonstrated in guinea pigs. We are postulating that an intra-cochlear-implanted deaf patient may have a better recovery if the implant is maintained ON during the night, that is, during sleep. © 2010 European Sleep Research Society.

  15. Effects of nitrogen and phosphorus additions on soil methane uptake in disturbed forests

    NASA Astrophysics Data System (ADS)

    Zheng, Mianhai; Zhang, Tao; Liu, Lei; Zhang, Wei; Lu, Xiankai; Mo, Jiangming

    2016-12-01

    Atmospheric nitrogen (N) deposition is generally thought to suppress soil methane (CH4) uptake in natural forests, and phosphorus (P) input may alleviate this negative effect. However, it remains unclear how N and P inputs control soil CH4 uptake in disturbed forests. In this study, soil CH4 uptake rates were measured in two disturbed forests, including a secondary forest (with previous, but not recent, disturbance) and a plantation forest (with recent continuous disturbance), in southern China for 34 months of N and/or P additions: control, N addition (150 kg N ha-1 yr-1), P addition (150 kg P ha-1 yr-1), and NP addition (150 kg N ha-1 yr-1 plus 150 kg P ha-1 yr-1). Mean CH4 uptake rate in control plots was significantly higher in the secondary forest (24.40 ± 0.81 µg CH4-C m-2 h-1) than in the plantation forest (17.07 ± 0.70 µg CH4-C m-2 h-1). CH4 uptake rate had negative relationships with soil water-filled pore space in both forests. In the secondary forest, N, P, and NP additions significantly decreased CH4 uptake by 39.7%, 27.8%, and 37.6%, respectively, but had no significant effects in the plantation forest, indicating that P input does not alleviate the suppression of CH4 uptake by N deposition. Taken together, our findings suggest that reducing anthropogenic disturbance, including harvesting of forest floor, and anthropogenic N and P inputs will increase soil CH4 uptake in disturbed forests, which is important in view of the increased trends in global warming during recent decades.

  16. Correlation between charge input and cycle life of MgNi electrode for Ni-MH batteries

    NASA Astrophysics Data System (ADS)

    Ruggeri, Stéphane; Roué, Lionel

    Amorphous MgNi material has been prepared by mechanically alloying magnesium and nickel powders for 10 h. Its cycle life as a negative electrode for nickel-metal hydride (Ni-MH) batteries has been studied with charge inputs varying from 0 to 600 mAh/g. For charge inputs lower than 400 mAh/g, the first cycle discharge capacity is superior to the charge input capacity. This surplus discharge capacity can be associated with the alloy oxidation to Mg(OH) 2 and Ni(OH) 2. For charge inputs higher than 400 mAh/g, the initial discharge capacity becomes inferior to the charge input capacity due to the progressive decrease of the charge efficiency related to the hydrogen evolution side reaction. From the second charge/discharge cycle, no additional discharge capacity appears and no discharge capacity degradation occurs for charge inputs inferior or equal to 233 mAh/g. In contrast, for higher charge input values, an important decay in the discharge capacity appears, which is accentuated with increasing charge input. The thresholds charge input of 233 mAh/g corresponds to an amount of hydrogen absorbed into the alloy of 0.8 wt.% (MgNiH 0.7). For higher absorbed hydrogen amounts, it is assumed that extended electrode pulverization occurs, which breaks the passive surface layer of Mg(OH) 2 formed during the first charge/discharge cycle. This creates unprotected fresh MgNi surfaces and consequently, leads to electrode capacity degradation. The stability of the MgNi electrode for absorbed hydrogen content lower than 0.8 wt.% may be related to its amorphous character, which favors a gradual volume expansion upon hydrogen absorption in contrast to crystalline compounds characterized by an abrupt α-to-β lattice expansion.

  17. MOESHA: A genetic algorithm for automatic calibration and estimation of parameter uncertainty and sensitivity of hydrologic models

    EPA Science Inventory

    Characterization of uncertainty and sensitivity of model parameters is an essential and often overlooked facet of hydrological modeling. This paper introduces an algorithm called MOESHA that combines input parameter sensitivity analyses with a genetic algorithm calibration routin...

  18. Aerodynamic Parameter Estimation for the X-43A (Hyper-X) from Flight Data

    NASA Technical Reports Server (NTRS)

    Morelli, Eugene A.; Derry, Stephen D.; Smith, Mark S.

    2005-01-01

    Aerodynamic parameters were estimated based on flight data from the third flight of the X-43A hypersonic research vehicle, also called Hyper-X. Maneuvers were flown using multiple orthogonal phase-optimized sweep inputs applied as simultaneous control surface perturbations at Mach 8, 7, 6, 5, 4, and 3 during the vehicle descent. Aerodynamic parameters, consisting of non-dimensional longitudinal and lateral stability and control derivatives, were estimated from flight data at each Mach number. Multi-step inputs at nearly the same flight conditions were also flown to assess the prediction capability of the identified models. Prediction errors were found to be comparable in magnitude to the modeling errors, which indicates accurate modeling. Aerodynamic parameter estimates were plotted as a function of Mach number, and compared with estimates from the pre-flight aerodynamic database, which was based on wind-tunnel tests and computational fluid dynamics. Agreement between flight estimates and values computed from the aerodynamic database was excellent overall.

  19. An improved state-parameter analysis of ecosystem models using data assimilation

    USGS Publications Warehouse

    Chen, M.; Liu, S.; Tieszen, L.L.; Hollinger, D.Y.

    2008-01-01

    Much of the effort spent in developing data assimilation methods for carbon dynamics analysis has focused on estimating optimal values for either model parameters or state variables. The main weakness of estimating parameter values alone (i.e., without considering state variables) is that all errors from input, output, and model structure are attributed to model parameter uncertainties. On the other hand, the accuracy of estimating state variables may be lowered if the temporal evolution of parameter values is not incorporated. This research develops a smoothed ensemble Kalman filter (SEnKF) by combining ensemble Kalman filter with kernel smoothing technique. SEnKF has following characteristics: (1) to estimate simultaneously the model states and parameters through concatenating unknown parameters and state variables into a joint state vector; (2) to mitigate dramatic, sudden changes of parameter values in parameter sampling and parameter evolution process, and control narrowing of parameter variance which results in filter divergence through adjusting smoothing factor in kernel smoothing algorithm; (3) to assimilate recursively data into the model and thus detect possible time variation of parameters; and (4) to address properly various sources of uncertainties stemming from input, output and parameter uncertainties. The SEnKF is tested by assimilating observed fluxes of carbon dioxide and environmental driving factor data from an AmeriFlux forest station located near Howland, Maine, USA, into a partition eddy flux model. Our analysis demonstrates that model parameters, such as light use efficiency, respiration coefficients, minimum and optimum temperatures for photosynthetic activity, and others, are highly constrained by eddy flux data at daily-to-seasonal time scales. The SEnKF stabilizes parameter values quickly regardless of the initial values of the parameters. Potential ecosystem light use efficiency demonstrates a strong seasonality. Results show that the

  20. Effects of Nitrogen Addition on Litter Decomposition and CO2 Release: Considering Changes in Litter Quantity

    PubMed Central

    Li, Hui-Chao; Hu, Ya-Lin; Mao, Rong; Zhao, Qiong; Zeng, De-Hui

    2015-01-01

    This study aims to evaluate the impacts of changes in litter quantity under simulated N deposition on litter decomposition, CO2 release, and soil C loss potential in a larch plantation in Northeast China. We conducted a laboratory incubation experiment using soil and litter collected from control and N addition (100 kg ha−1 year−1 for 10 years) plots. Different quantities of litter (0, 1, 2 and 4 g) were placed on 150 g soils collected from the same plots and incubated in microcosms for 270 days. We found that increased litter input strongly stimulated litter decomposition rate and CO2 release in both control and N fertilization microcosms, though reduced soil microbial biomass C (MBC) and dissolved inorganic N (DIN) concentration. Carbon input (C loss from litter decomposition) and carbon output (the cumulative C loss due to respiration) elevated with increasing litter input in both control and N fertilization microcosms. However, soil C loss potentials (C output–C input) reduced by 62% in control microcosms and 111% in N fertilization microcosms when litter addition increased from 1 g to 4 g, respectively. Our results indicated that increased litter input had a potential to suppress soil organic C loss especially for N addition plots. PMID:26657180

  1. Automatic selection of arterial input function using tri-exponential models

    NASA Astrophysics Data System (ADS)

    Yao, Jianhua; Chen, Jeremy; Castro, Marcelo; Thomasson, David

    2009-02-01

    Dynamic Contrast Enhanced MRI (DCE-MRI) is one method for drug and tumor assessment. Selecting a consistent arterial input function (AIF) is necessary to calculate tissue and tumor pharmacokinetic parameters in DCE-MRI. This paper presents an automatic and robust method to select the AIF. The first stage is artery detection and segmentation, where knowledge about artery structure and dynamic signal intensity temporal properties of DCE-MRI is employed. The second stage is AIF model fitting and selection. A tri-exponential model is fitted for every candidate AIF using the Levenberg-Marquardt method, and the best fitted AIF is selected. Our method has been applied in DCE-MRIs of four different body parts: breast, brain, liver and prostate. The success rates in artery segmentation for 19 cases are 89.6%+/-15.9%. The pharmacokinetic parameters computed from the automatically selected AIFs are highly correlated with those from manually determined AIFs (R2=0.946, P(T<=t)=0.09). Our imaging-based tri-exponential AIF model demonstrated significant improvement over a previously proposed bi-exponential model.

  2. Colored noise and a stochastic fractional model for correlated inputs and adaptation in neuronal firing.

    PubMed

    Pirozzi, Enrica

    2018-04-01

    High variability in the neuronal response to stimulations and the adaptation phenomenon cannot be explained by the standard stochastic leaky integrate-and-fire model. The main reason is that the uncorrelated inputs involved in the model are not realistic. There exists some form of dependency between the inputs, and it can be interpreted as memory effects. In order to include these physiological features in the standard model, we reconsider it with time-dependent coefficients and correlated inputs. Due to its hard mathematical tractability, we perform simulations of it for a wide investigation of its output. A Gauss-Markov process is constructed for approximating its non-Markovian dynamics. The first passage time probability density of such a process can be numerically evaluated, and it can be used to fit the histograms of simulated firing times. Some estimates of the moments of firing times are also provided. The effect of the correlation time of the inputs on firing densities and on firing rates is shown. An exponential probability density of the first firing time is estimated for low values of input current and high values of correlation time. For comparison, a simulation-based investigation is also carried out for a fractional stochastic model that allows to preserve the memory of the time evolution of the neuronal membrane potential. In this case, the memory parameter that affects the firing activity is the fractional derivative order. In both models an adaptation level of spike frequency is attained, even if along different modalities. Comparisons and discussion of the obtained results are provided.

  3. Designation of River Klina-Skenderaj Inputs, in the Absence of Measurements (Monitoring)-Kosova

    NASA Astrophysics Data System (ADS)

    Osmanaj, Lavdim; Karahoda, Dafina

    2009-11-01

    The territory of Republic of Kosova is divided in four catchment basins, such as: Basin of river Drini i Bardhë, river Ibri, river Morava of Binca and river Lepenci. [1]The river Klina is left part of the Drini i Bardhë basin.The inputs are designated by the following authors:a) GIANDOTT - VISSENTINb) GA VRILOVICc) THE METHOD OF TYPICALHYDROGRAMAs a result of this studies derive the following parameters: the surface of basin F=77.75km2, width of main flow L=22.00km', width of basin Wb=68.00km', highest quota of the basin Hqb=1750m.l.m, highest quota of inflow Hi=600.00m.l.m, average difference of height D=303.5m, maximal water input: Qmax100 years=112.00 m3/s, an average produce of Alluvium W=980.76m3/s, specific produce of Alluvium Gyears=35270.57 m3/s, secondary conveyance of Alluvium Qa=14.70 m3/s.

  4. Capacitance-type blade-tip clearance measurement system using a dual amplifier with ramp/dc inputs and integration

    NASA Technical Reports Server (NTRS)

    Sarma, Garimella R.; Barranger, John P.

    1992-01-01

    The analysis and prototype results of a dual-amplifier circuit for measuring blade-tip clearance in turbine engines are presented. The capacitance between the blade tip and mounted capacitance electrode within a guard ring of a probe forms one of the feedback elements of an operational amplifier (op amp). The differential equation governing the circuit taking into consideration the nonideal features of the op amp was formulated and solved for two types of inputs (ramp and dc) that are of interest for the application. Under certain time-dependent constraints, it is shown that (1) with a ramp input the circuit has an output voltage proportional to the static tip clearance capacitance, and (2) with a dc input, the output is proportional to the derivative of the clearance capacitance, and subsequent integration recovers the dynamic capacitance. The technique accommodates long cable lengths and environmentally induced changes in cable and probe parameters. System implementation for both static and dynamic measurements having the same high sensitivity is also presented.

  5. Capacitance-type blade-tip clearance measurement system using a dual amplifier with ramp/dc inputs and integration

    NASA Astrophysics Data System (ADS)

    Sarma, Garimella R.; Barranger, John P.

    1992-10-01

    The analysis and prototype results of a dual-amplifier circuit for measuring blade-tip clearance in turbine engines are presented. The capacitance between the blade tip and mounted capacitance electrode within a guard ring of a probe forms one of the feedback elements of an operational amplifier (op amp). The differential equation governing the circuit taking into consideration the nonideal features of the op amp was formulated and solved for two types of inputs (ramp and dc) that are of interest for the application. Under certain time-dependent constraints, it is shown that (1) with a ramp input the circuit has an output voltage proportional to the static tip clearance capacitance, and (2) with a dc input, the output is proportional to the derivative of the clearance capacitance, and subsequent integration recovers the dynamic capacitance. The technique accommodates long cable lengths and environmentally induced changes in cable and probe parameters. System implementation for both static and dynamic measurements having the same high sensitivity is also presented.

  6. New Uses for Sensitivity Analysis: How Different Movement Tasks Effect Limb Model Parameter Sensitivity

    NASA Technical Reports Server (NTRS)

    Winters, J. M.; Stark, L.

    1984-01-01

    Original results for a newly developed eight-order nonlinear limb antagonistic muscle model of elbow flexion and extension are presented. A wider variety of sensitivity analysis techniques are used and a systematic protocol is established that shows how the different methods can be used efficiently to complement one another for maximum insight into model sensitivity. It is explicitly shown how the sensitivity of output behaviors to model parameters is a function of the controller input sequence, i.e., of the movement task. When the task is changed (for instance, from an input sequence that results in the usual fast movement task to a slower movement that may also involve external loading, etc.) the set of parameters with high sensitivity will in general also change. Such task-specific use of sensitivity analysis techniques identifies the set of parameters most important for a given task, and even suggests task-specific model reduction possibilities.

  7. Effects of FeCl3 additives on optical parameters of PVA

    NASA Astrophysics Data System (ADS)

    Latif, Duha M. A.; Chiad, Sami S.; Erhayief, Muhssen S.; Abass, Khalid H.; Habubi, Nadir F.; Hussin, Hadi A.

    2018-05-01

    PVA doped FeCl3 have been deposited utilizing casting technique. Absorption spectrum was registered in the wavelengths (300-900 nm) utilizing UV-Visible spectrophotometer. Optical constants behavior such as, absorbance, absorption coefficient, and skin depth were studied. It was found these parameters were increased as Fe content increase. While the extinction coefficient and optical conductivity was decreased. The energy gap of PVA-Fe films were decreased from 4 eV for the PVA film to 3.5 eV for the PVA: 4 % Fe film.

  8. Characteristics of air-water upward intermittent flows with surfactant additive in a pipeline-riser system

    NASA Astrophysics Data System (ADS)

    Gao, Meng-chen; Xu, Jing-yu

    2018-04-01

    The effect of the surfactant additive on the upward intermittent flows in a pipeline-riser system is studied experimentally, in a 3 m long horizontal pipe connected to a Perspex pipe of 2.0 m long and 25 mm in diameter, inclined to the horizontal plane by 7°, followed by the vertical PVC riser of 3.5 m high and 25 mm in diameter, operating at the atmospheric end pressure. Based on the analysis of the pressure signal and the visual observation of the riser, it is shown that the additive of surfactant to the carrying liquid makes bubbles smaller in size but much larger in number in the upward intermittent flows. In addition, the additive of surfactant to a two-phase flow does not have a significant impact on the in-situ gas fraction, the pressure drop and the frequency of the liquid slug, but it reduces significantly the velocity of the liquid slug. When the superficial liquid velocity is set, an exponential relationship between the dimensionless velocity of the liquid slug and the Webber number can be obtained. These results might be used for estimating the characteristic parameters of the upward intermittent flow based upon the input operating conditions.

  9. EVALUATING THE SENSITIVITY OF A SUBSURFACE MULTICOMPONENT REACTIVE TRANSPORT MODEL WITH RESPECT TO TRANSPORT AND REACTION PARAMETERS

    EPA Science Inventory

    The input variables for a numerical model of reactive solute transport in groundwater include both transport parameters, such as hydraulic conductivity and infiltration, and reaction parameters that describe the important chemical and biological processes in the system. These pa...

  10. Input-dependent frequency modulation of cortical gamma oscillations shapes spatial synchronization and enables phase coding.

    PubMed

    Lowet, Eric; Roberts, Mark; Hadjipapas, Avgis; Peter, Alina; van der Eerden, Jan; De Weerd, Peter

    2015-02-01

    Fine-scale temporal organization of cortical activity in the gamma range (∼25-80Hz) may play a significant role in information processing, for example by neural grouping ('binding') and phase coding. Recent experimental studies have shown that the precise frequency of gamma oscillations varies with input drive (e.g. visual contrast) and that it can differ among nearby cortical locations. This has challenged theories assuming widespread gamma synchronization at a fixed common frequency. In the present study, we investigated which principles govern gamma synchronization in the presence of input-dependent frequency modulations and whether they are detrimental for meaningful input-dependent gamma-mediated temporal organization. To this aim, we constructed a biophysically realistic excitatory-inhibitory network able to express different oscillation frequencies at nearby spatial locations. Similarly to cortical networks, the model was topographically organized with spatially local connectivity and spatially-varying input drive. We analyzed gamma synchronization with respect to phase-locking, phase-relations and frequency differences, and quantified the stimulus-related information represented by gamma phase and frequency. By stepwise simplification of our models, we found that the gamma-mediated temporal organization could be reduced to basic synchronization principles of weakly coupled oscillators, where input drive determines the intrinsic (natural) frequency of oscillators. The gamma phase-locking, the precise phase relation and the emergent (measurable) frequencies were determined by two principal factors: the detuning (intrinsic frequency difference, i.e. local input difference) and the coupling strength. In addition to frequency coding, gamma phase contained complementary stimulus information. Crucially, the phase code reflected input differences, but not the absolute input level. This property of relative input-to-phase conversion, contrasting with latency codes

  11. Input-Dependent Frequency Modulation of Cortical Gamma Oscillations Shapes Spatial Synchronization and Enables Phase Coding

    PubMed Central

    Lowet, Eric; Roberts, Mark; Hadjipapas, Avgis; Peter, Alina; van der Eerden, Jan; De Weerd, Peter

    2015-01-01

    Fine-scale temporal organization of cortical activity in the gamma range (∼25–80Hz) may play a significant role in information processing, for example by neural grouping (‘binding’) and phase coding. Recent experimental studies have shown that the precise frequency of gamma oscillations varies with input drive (e.g. visual contrast) and that it can differ among nearby cortical locations. This has challenged theories assuming widespread gamma synchronization at a fixed common frequency. In the present study, we investigated which principles govern gamma synchronization in the presence of input-dependent frequency modulations and whether they are detrimental for meaningful input-dependent gamma-mediated temporal organization. To this aim, we constructed a biophysically realistic excitatory-inhibitory network able to express different oscillation frequencies at nearby spatial locations. Similarly to cortical networks, the model was topographically organized with spatially local connectivity and spatially-varying input drive. We analyzed gamma synchronization with respect to phase-locking, phase-relations and frequency differences, and quantified the stimulus-related information represented by gamma phase and frequency. By stepwise simplification of our models, we found that the gamma-mediated temporal organization could be reduced to basic synchronization principles of weakly coupled oscillators, where input drive determines the intrinsic (natural) frequency of oscillators. The gamma phase-locking, the precise phase relation and the emergent (measurable) frequencies were determined by two principal factors: the detuning (intrinsic frequency difference, i.e. local input difference) and the coupling strength. In addition to frequency coding, gamma phase contained complementary stimulus information. Crucially, the phase code reflected input differences, but not the absolute input level. This property of relative input-to-phase conversion, contrasting with latency

  12. Modeling the Effects of Irrigation on Land Surface Fluxes and States over the Conterminous United States: Sensitivity to Input Data and Model Parameters

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

    Leng, Guoyong; Huang, Maoyi; Tang, Qiuhong

    2013-09-16

    Previous studies on irrigation impacts on land surface fluxes/states were mainly conducted as sensitivity experiments, with limited analysis of uncertainties from the input data and model irrigation schemes used. In this study, we calibrated and evaluated the performance of irrigation water use simulated by the Community Land Model version 4 (CLM4) against observations from agriculture census. We investigated the impacts of irrigation on land surface fluxes and states over the conterminous United States (CONUS) and explored possible directions of improvement. Specifically, we found large uncertainty in the irrigation area data from two widely used sources and CLM4 tended to producemore » unrealistically large temporal variations of irrigation demand for applications at the water resources region scale over CONUS. At seasonal to interannual time scales, the effects of irrigation on surface energy partitioning appeared to be large and persistent, and more pronounced in dry than wet years. Even with model calibration to yield overall good agreement with the irrigation amounts from the National Agricultural Statistics Service (NASS), differences between the two irrigation area datasets still dominate the differences in the interannual variability of land surface response to irrigation. Our results suggest that irrigation amount simulated by CLM4 can be improved by (1) calibrating model parameter values to account for regional differences in irrigation demand and (2) accurate representation of the spatial distribution and intensity of irrigated areas.« less

  13. Input and Age-Dependent Variation in Second Language Learning: A Connectionist Account.

    PubMed

    Janciauskas, Marius; Chang, Franklin

    2017-07-26

    Language learning requires linguistic input, but several studies have found that knowledge of second language (L2) rules does not seem to improve with more language exposure (e.g., Johnson & Newport, 1989). One reason for this is that previous studies did not factor out variation due to the different rules tested. To examine this issue, we reanalyzed grammaticality judgment scores in Flege, Yeni-Komshian, and Liu's (1999) study of L2 learners using rule-related predictors and found that, in addition to the overall drop in performance due to a sensitive period, L2 knowledge increased with years of input. Knowledge of different grammar rules was negatively associated with input frequency of those rules. To better understand these effects, we modeled the results using a connectionist model that was trained using Korean as a first language (L1) and then English as an L2. To explain the sensitive period in L2 learning, the model's learning rate was reduced in an age-related manner. By assigning different learning rates for syntax and lexical learning, we were able to model the difference between early and late L2 learners in input sensitivity. The model's learning mechanism allowed transfer between the L1 and L2, and this helped to explain the differences between different rules in the grammaticality judgment task. This work demonstrates that an L1 model of learning and processing can be adapted to provide an explicit account of how the input and the sensitive period interact in L2 learning. © 2017 The Authors. Cognitive Science - A Multidisciplinary Journal published by Wiley Periodicals, Inc.

  14. Sound effects: Multimodal input helps infants find displaced objects.

    PubMed

    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

  15. Four-parameter model for polarization-resolved rough-surface BRDF.

    PubMed

    Renhorn, Ingmar G E; Hallberg, Tomas; Bergström, David; Boreman, Glenn D

    2011-01-17

    A modeling procedure is demonstrated, which allows representation of polarization-resolved BRDF data using only four parameters: the real and imaginary parts of an effective refractive index with an added parameter taking grazing incidence absorption into account and an angular-scattering parameter determined from the BRDF measurement of a chosen angle of incidence, preferably close to normal incidence. These parameters allow accurate predictions of s- and p-polarized BRDF for a painted rough surface, over three decades of variation in BRDF magnitude. To characterize any particular surface of interest, the measurements required to determine these four parameters are the directional hemispherical reflectance (DHR) for s- and p-polarized input radiation and the BRDF at a selected angle of incidence. The DHR data describes the angular and polarization dependence, as well as providing the overall normalization constraint. The resulting model conserves energy and fulfills the reciprocity criteria.

  16. Dependence of calculated postshock thermodynamic variables on vibrational equilibrium and input uncertainty

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

    Campbell, Matthew Frederick; Owen, Kyle G.; Davidson, David F.

    The purpose of this article is to explore the dependence of calculated postshock thermodynamic properties in shock tube experiments upon the vibrational state of the test gas and upon the uncertainties inherent to calculation inputs. This paper first offers a comparison between state variables calculated according to a Rankine–Hugoniot–equation-based algorithm, known as FROSH, and those derived from shock tube experiments on vibrationally nonequilibrated gases. It is shown that incorrect vibrational relaxation assumptions could lead to errors in temperature as large as 8% for 25% oxygen/argon mixtures at 3500 K. Following this demonstration, this article employs the algorithm to show themore » importance of correct vibrational equilibration assumptions, noting, for instance, that errors in temperature of up to about 2% at 3500 K may be generated for 10% nitrogen/argon mixtures if vibrational relaxation is not treated properly. Lastly, this article presents an extensive uncertainty analysis, showing that postshock temperatures can be calculated with root-of-sum-of-square errors of better than ±1% given sufficiently accurate experimentally measured input parameters.« less

  17. Dependence of calculated postshock thermodynamic variables on vibrational equilibrium and input uncertainty

    DOE PAGES

    Campbell, Matthew Frederick; Owen, Kyle G.; Davidson, David F.; ...

    2017-01-30

    The purpose of this article is to explore the dependence of calculated postshock thermodynamic properties in shock tube experiments upon the vibrational state of the test gas and upon the uncertainties inherent to calculation inputs. This paper first offers a comparison between state variables calculated according to a Rankine–Hugoniot–equation-based algorithm, known as FROSH, and those derived from shock tube experiments on vibrationally nonequilibrated gases. It is shown that incorrect vibrational relaxation assumptions could lead to errors in temperature as large as 8% for 25% oxygen/argon mixtures at 3500 K. Following this demonstration, this article employs the algorithm to show themore » importance of correct vibrational equilibration assumptions, noting, for instance, that errors in temperature of up to about 2% at 3500 K may be generated for 10% nitrogen/argon mixtures if vibrational relaxation is not treated properly. Lastly, this article presents an extensive uncertainty analysis, showing that postshock temperatures can be calculated with root-of-sum-of-square errors of better than ±1% given sufficiently accurate experimentally measured input parameters.« less

  18. Are Subject-Specific Musculoskeletal Models Robust to the Uncertainties in Parameter Identification?

    PubMed Central

    Valente, Giordano; Pitto, Lorenzo; Testi, Debora; Seth, Ajay; Delp, Scott L.; Stagni, Rita; Viceconti, Marco; Taddei, Fulvia

    2014-01-01

    Subject-specific musculoskeletal modeling can be applied to study musculoskeletal disorders, allowing inclusion of personalized anatomy and properties. Independent of the tools used for model creation, there are unavoidable uncertainties associated with parameter identification, whose effect on model predictions is still not fully understood. The aim of the present study was to analyze the sensitivity of subject-specific model predictions (i.e., joint angles, joint moments, muscle and joint contact forces) during walking to the uncertainties in the identification of body landmark positions, maximum muscle tension and musculotendon geometry. To this aim, we created an MRI-based musculoskeletal model of the lower limbs, defined as a 7-segment, 10-degree-of-freedom articulated linkage, actuated by 84 musculotendon units. We then performed a Monte-Carlo probabilistic analysis perturbing model parameters according to their uncertainty, and solving a typical inverse dynamics and static optimization problem using 500 models that included the different sets of perturbed variable values. Model creation and gait simulations were performed by using freely available software that we developed to standardize the process of model creation, integrate with OpenSim and create probabilistic simulations of movement. The uncertainties in input variables had a moderate effect on model predictions, as muscle and joint contact forces showed maximum standard deviation of 0.3 times body-weight and maximum range of 2.1 times body-weight. In addition, the output variables significantly correlated with few input variables (up to 7 out of 312) across the gait cycle, including the geometry definition of larger muscles and the maximum muscle tension in limited gait portions. Although we found subject-specific models not markedly sensitive to parameter identification, researchers should be aware of the model precision in relation to the intended application. In fact, force predictions could be

  19. Estimation and Simulation of Slow Crack Growth Parameters from Constant Stress Rate Data

    NASA Technical Reports Server (NTRS)

    Salem, Jonathan A.; Weaver, Aaron S.

    2003-01-01

    Closed form, approximate functions for estimating the variances and degrees-of-freedom associated with the slow crack growth parameters n, D, B, and A(sup *) as measured using constant stress rate ('dynamic fatigue') testing were derived by using propagation of errors. Estimates made with the resulting functions and slow crack growth data for a sapphire window were compared to the results of Monte Carlo simulations. The functions for estimation of the variances of the parameters were derived both with and without logarithmic transformation of the initial slow crack growth equations. The transformation was performed to make the functions both more linear and more normal. Comparison of the Monte Carlo results and the closed form expressions derived with propagation of errors indicated that linearization is not required for good estimates of the variances of parameters n and D by the propagation of errors method. However, good estimates variances of the parameters B and A(sup *) could only be made when the starting slow crack growth equation was transformed and the coefficients of variation of the input parameters were not too large. This was partially a result of the skewered distributions of B and A(sup *). Parametric variation of the input parameters was used to determine an acceptable range for using closed form approximate equations derived from propagation of errors.

  20. [Responses of forest soil carbon pool and carbon cycle to the changes of carbon input].

    PubMed

    Wang, Qing-kui

    2011-04-01

    Litters and plant roots are the main sources of forest soil organic carbon (C). This paper summarized the effects of the changes in C input on the forest soil C pool and C cycle, and analyzed the effects of these changes on the total soil C, microbial biomass C, dissoluble organic C, and soil respiration. Different forests in different regions had inconsistent responses to C input change, and the effects of litter removal or addition and of root exclusion or not differed with tree species and regions. Current researches mainly focused on soil respiration and C pool fractions, and scarce were about the effects of C input change on the changes of soil carbon structure and stability as well as the response mechanisms of soil organisms especially soil fauna, which should be strengthened in the future.

  1. Re-Assessing the Measurement of Fogwater Inputs to a Tropical Ecosystem

    NASA Astrophysics Data System (ADS)

    Burkard, R.; Eugster, W.; Holwerda, F.; Bruijnzeel, S.; Scatena, F.; Siegwolf, R.

    2002-12-01

    For several years the hydrological importance of the fog- and cloudwater deposition to ecosystems in the tropics has been of great interest. In earlier studies carried out in the humid tropics the amount of deposited cloudwater was estimated by indirect methods based on the physical characteristics of the utilized cloudwater collector. In the temperate climatic zone of central Europe most of the studies dealing with cloudwater focus on the additional chemical input due to cloudwater in relation to the amount of deposited rainwater. During our experiment in the Luquillo mountains of Puerto Rico the different aspects of the chemical and hydrological impacts of cloudwater deposition have been investigated. During 43 days, cloudwater fluxes were measured with an eddy covariance setup consisting of a Solent ultrasonic anemometer and a size-resolving cloud droplet spectrometer. Cloudwater samples were taken with a Caltech-type active strand cloudwater collector. Additionally, measurements of rain, throughfall and stemflow were performed. Samples of fog, rain, throughfall and stemflow were analyzed for inorganic ion and stabile isotope concentrations (δ18O and δ2H). First analysis of the hydrological input show that there exist some significant differences in the deposited amount of cloudwater as measured with our instruments in comparison with previous studies carried out at the same location: Mean liquid water content was 78.6 mg m-3 during situations with a visibility below 1000 m (84% of the entire field campaign). The deposition rate of cloudwater was 0.88 mm d-1. A mismatch was found regarding the water balance. We conclude from this that the rainfall amount and therefore also the chemical input by rain is strongly underestimated due to wind-driven rain, which is not measured by standard rain gauges. Depending on the reference value, we have to conclude that the deposition of cloudwater accounts for 6--11% of wet deposition.

  2. Noise facilitates transcriptional control under dynamic inputs.

    PubMed

    Kellogg, Ryan A; Tay, Savaş

    2015-01-29

    Cells must respond sensitively to time-varying inputs in complex signaling environments. To understand how signaling networks process dynamic inputs into gene expression outputs and the role of noise in cellular information processing, we studied the immune pathway NF-κB under periodic cytokine inputs using microfluidic single-cell measurements and stochastic modeling. We find that NF-κB dynamics in fibroblasts synchronize with oscillating TNF signal and become entrained, leading to significantly increased NF-κB oscillation amplitude and mRNA output compared to non-entrained response. Simulations show that intrinsic biochemical noise in individual cells improves NF-κB oscillation and entrainment, whereas cell-to-cell variability in NF-κB natural frequency creates population robustness, together enabling entrainment over a wider range of dynamic inputs. This wide range is confirmed by experiments where entrained cells were measured under all input periods. These results indicate that synergy between oscillation and noise allows cells to achieve efficient gene expression in dynamically changing signaling environments. Copyright © 2015 Elsevier Inc. All rights reserved.

  3. ESCHER: An interactive mesh-generating editor for preparing finite-element input

    NASA Technical Reports Server (NTRS)

    Oakes, W. R., Jr.

    1984-01-01

    ESCHER is an interactive mesh generation and editing program designed to help the user create a finite-element mesh, create additional input for finite-element analysis, including initial conditions, boundary conditions, and slidelines, and generate a NEUTRAL FILE that can be postprocessed for input into several finite-element codes, including ADINA, ADINAT, DYNA, NIKE, TSAAS, and ABUQUS. Two important ESCHER capabilities, interactive geometry creation and mesh archival storge are described in detail. Also described is the interactive command language and the use of interactive graphics. The archival storage and restart file is a modular, entity-based mesh data file. Modules of this file correspond to separate editing modes in the mesh editor, with data definition syntax preserved between the interactive commands and the archival storage file. Because ESCHER was expected to be highly interactive, extensive user documentation was provided in the form of an interactive HELP package.

  4. Computing Functions by Approximating the Input

    ERIC Educational Resources Information Center

    Goldberg, Mayer

    2012-01-01

    In computing real-valued functions, it is ordinarily assumed that the input to the function is known, and it is the output that we need to approximate. In this work, we take the opposite approach: we show how to compute the values of some transcendental functions by approximating the input to these functions, and obtaining exact answers for their…

  5. Design of Robust Controllers for a Multiple Input-Multiple Output Control System with Uncertain Parameters Application to the Lateral and Longitudinal Modes of the KC-135 Transport Aircraft

    DTIC Science & Technology

    1984-12-01

    input/output relationship. These are obtained from the design specifications (10:68i-684). Note that the first digit of the subscript of bkj refers...to the output and the second digit to the input. Thus, bkj is.a function of the response requirements on the output, Yk’ due to the input, r.. 169 . A...NXPMAX pNYPMAX, IPLOT) C C C* LIBARY OF PLOT SUBR(OUTINES PSNTCT NLIEPRINTER ONLY~ C* C C C SUP’ LPLOTS C C C DIMENSION IXY(101,71)918UF(100) COMMON /HOPY

  6. Measurement of myocardial blood flow by cardiovascular magnetic resonance perfusion: comparison of distributed parameter and Fermi models with single and dual bolus.

    PubMed

    Papanastasiou, Giorgos; Williams, Michelle C; Kershaw, Lucy E; Dweck, Marc R; Alam, Shirjel; Mirsadraee, Saeed; Connell, Martin; Gray, Calum; MacGillivray, Tom; Newby, David E; Semple, Scott Ik

    2015-02-17

    Mathematical modeling of cardiovascular magnetic resonance perfusion data allows absolute quantification of myocardial blood flow. Saturation of left ventricle signal during standard contrast administration can compromise the input function used when applying these models. This saturation effect is evident during application of standard Fermi models in single bolus perfusion data. Dual bolus injection protocols have been suggested to eliminate saturation but are much less practical in the clinical setting. The distributed parameter model can also be used for absolute quantification but has not been applied in patients with coronary artery disease. We assessed whether distributed parameter modeling might be less dependent on arterial input function saturation than Fermi modeling in healthy volunteers. We validated the accuracy of each model in detecting reduced myocardial blood flow in stenotic vessels versus gold-standard invasive methods. Eight healthy subjects were scanned using a dual bolus cardiac perfusion protocol at 3T. We performed both single and dual bolus analysis of these data using the distributed parameter and Fermi models. For the dual bolus analysis, a scaled pre-bolus arterial input function was used. In single bolus analysis, the arterial input function was extracted from the main bolus. We also performed analysis using both models of single bolus data obtained from five patients with coronary artery disease and findings were compared against independent invasive coronary angiography and fractional flow reserve. Statistical significance was defined as two-sided P value < 0.05. Fermi models overestimated myocardial blood flow in healthy volunteers due to arterial input function saturation in single bolus analysis compared to dual bolus analysis (P < 0.05). No difference was observed in these volunteers when applying distributed parameter-myocardial blood flow between single and dual bolus analysis. In patients, distributed parameter

  7. Optimization of Operating Parameters for Minimum Mechanical Specific Energy in Drilling

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

    Hamrick, Todd

    2011-01-01

    Efficiency in drilling is measured by Mechanical Specific Energy (MSE). MSE is the measure of the amount of energy input required to remove a unit volume of rock, expressed in units of energy input divided by volume removed. It can be expressed mathematically in terms of controllable parameters; Weight on Bit, Torque, Rate of Penetration, and RPM. It is well documented that minimizing MSE by optimizing controllable factors results in maximum Rate of Penetration. Current methods for computing MSE make it possible to minimize MSE in the field only through a trial-and-error process. This work makes it possible to computemore » the optimum drilling parameters that result in minimum MSE. The parameters that have been traditionally used to compute MSE are interdependent. Mathematical relationships between the parameters were established, and the conventional MSE equation was rewritten in terms of a single parameter, Weight on Bit, establishing a form that can be minimized mathematically. Once the optimum Weight on Bit was determined, the interdependent relationship that Weight on Bit has with Torque and Penetration per Revolution was used to determine optimum values for those parameters for a given drilling situation. The improved method was validated through laboratory experimentation and analysis of published data. Two rock types were subjected to four treatments each, and drilled in a controlled laboratory environment. The method was applied in each case, and the optimum parameters for minimum MSE were computed. The method demonstrated an accurate means to determine optimum drilling parameters of Weight on Bit, Torque, and Penetration per Revolution. A unique application of micro-cracking is also presented, which demonstrates that rock failure ahead of the bit is related to axial force more than to rotation speed.« less

  8. Heat input and accumulation for ultrashort pulse processing with high average power

    NASA Astrophysics Data System (ADS)

    Finger, Johannes; Bornschlegel, Benedikt; Reininghaus, Martin; Dohrn, Andreas; Nießen, Markus; Gillner, Arnold; Poprawe, Reinhart

    2018-05-01

    Materials processing using ultrashort pulsed laser radiation with pulse durations <10 ps is known to enable very precise processing with negligible thermal load. However, even for the application of picosecond and femtosecond laser radiation, not the full amount of the absorbed energy is converted into ablation products and a distinct fraction of the absorbed energy remains as residual heat in the processed workpiece. For low average power and power densities, this heat is usually not relevant for the processing results and dissipates into the workpiece. In contrast, when higher average powers and repetition rates are applied to increase the throughput and upscale ultrashort pulse processing, this heat input becomes relevant and significantly affects the achieved processing results. In this paper, we outline the relevance of heat input for ultrashort pulse processing, starting with the heat input of a single ultrashort laser pulse. Heat accumulation during ultrashort pulse processing with high repetition rate is discussed as well as heat accumulation for materials processing using pulse bursts. In addition, the relevance of heat accumulation with multiple scanning passes and processing with multiple laser spots is shown.

  9. Adaptive neuro-fuzzy inference system (ANFIS) to predict CI engine parameters fueled with nano-particles additive to diesel fuel

    NASA Astrophysics Data System (ADS)

    Ghanbari, M.; Najafi, G.; Ghobadian, B.; Mamat, R.; Noor, M. M.; Moosavian, A.

    2015-12-01

    This paper studies the use of adaptive neuro-fuzzy inference system (ANFIS) to predict the performance parameters and exhaust emissions of a diesel engine operating on nanodiesel blended fuels. In order to predict the engine parameters, the whole experimental data were randomly divided into training and testing data. For ANFIS modelling, Gaussian curve membership function (gaussmf) and 200 training epochs (iteration) were found to be optimum choices for training process. The results demonstrate that ANFIS is capable of predicting the diesel engine performance and emissions. In the experimental step, Carbon nano tubes (CNT) (40, 80 and 120 ppm) and nano silver particles (40, 80 and 120 ppm) with nanostructure were prepared and added as additive to the diesel fuel. Six cylinders, four-stroke diesel engine was fuelled with these new blended fuels and operated at different engine speeds. Experimental test results indicated the fact that adding nano particles to diesel fuel, increased diesel engine power and torque output. For nano-diesel it was found that the brake specific fuel consumption (bsfc) was decreased compared to the net diesel fuel. The results proved that with increase of nano particles concentrations (from 40 ppm to 120 ppm) in diesel fuel, CO2 emission increased. CO emission in diesel fuel with nano-particles was lower significantly compared to pure diesel fuel. UHC emission with silver nano-diesel blended fuel decreased while with fuels that contains CNT nano particles increased. The trend of NOx emission was inverse compared to the UHC emission. With adding nano particles to the blended fuels, NOx increased compared to the net diesel fuel. The tests revealed that silver & CNT nano particles can be used as additive in diesel fuel to improve combustion of the fuel and reduce the exhaust emissions significantly.

  10. Comparative analysis of environmental impacts of agricultural production systems, agricultural input efficiency, and food choice

    NASA Astrophysics Data System (ADS)

    Clark, Michael; Tilman, David

    2017-06-01

    Global agricultural feeds over 7 billion people, but is also a leading cause of environmental degradation. Understanding how alternative agricultural production systems, agricultural input efficiency, and food choice drive environmental degradation is necessary for reducing agriculture’s environmental impacts. A meta-analysis of life cycle assessments that includes 742 agricultural systems and over 90 unique foods produced primarily in high-input systems shows that, per unit of food, organic systems require more land, cause more eutrophication, use less energy, but emit similar greenhouse gas emissions (GHGs) as conventional systems; that grass-fed beef requires more land and emits similar GHG emissions as grain-feed beef; and that low-input aquaculture and non-trawling fisheries have much lower GHG emissions than trawling fisheries. In addition, our analyses show that increasing agricultural input efficiency (the amount of food produced per input of fertilizer or feed) would have environmental benefits for both crop and livestock systems. Further, for all environmental indicators and nutritional units examined, plant-based foods have the lowest environmental impacts; eggs, dairy, pork, poultry, non-trawling fisheries, and non-recirculating aquaculture have intermediate impacts; and ruminant meat has impacts ∼100 times those of plant-based foods. Our analyses show that dietary shifts towards low-impact foods and increases in agricultural input use efficiency would offer larger environmental benefits than would switches from conventional agricultural systems to alternatives such as organic agriculture or grass-fed beef.

  11. Existence conditions for unknown input functional observers

    NASA Astrophysics Data System (ADS)

    Fernando, T.; MacDougall, S.; Sreeram, V.; Trinh, H.

    2013-01-01

    This article presents necessary and sufficient conditions for the existence and design of an unknown input Functional observer. The existence of the observer can be verified by computing a nullspace of a known matrix and testing some matrix rank conditions. The existence of the observer does not require the satisfaction of the observer matching condition (i.e. Equation (16) in Hou and Muller 1992, 'Design of Observers for Linear Systems with Unknown Inputs', IEEE Transactions on Automatic Control, 37, 871-875), is not limited to estimating scalar functionals and allows for arbitrary pole placement. The proposed observer always exists when a state observer exists for the unknown input system, and furthermore, the proposed observer can exist even in some instances when an unknown input state observer does not exist.

  12. A modified NARMAX model-based self-tuner with fault tolerance for unknown nonlinear stochastic hybrid systems with an input-output direct feed-through term.

    PubMed

    Tsai, Jason S-H; Hsu, Wen-Teng; Lin, Long-Guei; Guo, Shu-Mei; Tann, Joseph W

    2014-01-01

    A modified nonlinear autoregressive moving average with exogenous inputs (NARMAX) model-based state-space self-tuner with fault tolerance is proposed in this paper for the unknown nonlinear stochastic hybrid system with a direct transmission matrix from input to output. Through the off-line observer/Kalman filter identification method, one has a good initial guess of modified NARMAX model to reduce the on-line system identification process time. Then, based on the modified NARMAX-based system identification, a corresponding adaptive digital control scheme is presented for the unknown continuous-time nonlinear system, with an input-output direct transmission term, which also has measurement and system noises and inaccessible system states. Besides, an effective state space self-turner with fault tolerance scheme is presented for the unknown multivariable stochastic system. A quantitative criterion is suggested by comparing the innovation process error estimated by the Kalman filter estimation algorithm, so that a weighting matrix resetting technique by adjusting and resetting the covariance matrices of parameter estimate obtained by the Kalman filter estimation algorithm is utilized to achieve the parameter estimation for faulty system recovery. Consequently, the proposed method can effectively cope with partially abrupt and/or gradual system faults and input failures by the fault detection. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

  13. Parameter uncertainty and variability in evaluative fate and exposure models

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

    Hertwich, E.G.; McKone, T.E.; Pease, W.S.

    The human toxicity potential, a weighting scheme used to evaluate toxic emissions for life cycle assessment and toxics release inventories, is based on potential dose calculations and toxicity factors. This paper evaluates the variance in potential dose calculations that can be attributed to the uncertainty in chemical-specific input parameters as well as the variability in exposure factors and landscape parameters. A knowledge of the uncertainty allows us to assess the robustness of a decision based on the toxicity potential; a knowledge of the sources of uncertainty allows one to focus resources if the uncertainty is to be reduced. The potentialmore » does of 236 chemicals was assessed. The chemicals were grouped by dominant exposure route, and a Monte Carlo analysis was conducted for one representative chemical in each group. The variance is typically one to two orders of magnitude. For comparison, the point estimates in potential dose for 236 chemicals span ten orders of magnitude. Most of the variance in the potential dose is due to chemical-specific input parameters, especially half-lives, although exposure factors such as fish intake and the source of drinking water can be important for chemicals whose dominant exposure is through indirect routes. Landscape characteristics are generally of minor importance.« less

  14. High-Voltage-Input Level Translator Using Standard CMOS

    NASA Technical Reports Server (NTRS)

    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

  15. The adaptive observer. [liapunov synthesis, single-input single-output, and reduced observers

    NASA Technical Reports Server (NTRS)

    Carroll, R. L.

    1973-01-01

    The simple generation of state from available measurements, for use in systems for which the criteria defining the acceptable state behavior mandates a control that is dependent upon unavailable measurement is described as an adaptive means for determining the state of a linear time invariant differential system having unknown parameters. A single input output adaptive observer and the reduced adaptive observer is developed. The basic ideas for both the adaptive observer and the nonadaptive observer are examined. A survey of the Liapunov synthesis technique is taken, and the technique is applied to adaptive algorithm for the adaptive observer.

  16. Dynamics of networks of excitatory and inhibitory neurons in response to time-dependent inputs.

    PubMed

    Ledoux, Erwan; Brunel, Nicolas

    2011-01-01

    We investigate the dynamics of recurrent networks of excitatory (E) and inhibitory (I) neurons in the presence of time-dependent inputs. The dynamics is characterized by the network dynamical transfer function, i.e., how the population firing rate is modulated by sinusoidal inputs at arbitrary frequencies. Two types of networks are studied and compared: (i) a Wilson-Cowan type firing rate model; and (ii) a fully connected network of leaky integrate-and-fire (LIF) neurons, in a strong noise regime. We first characterize the region of stability of the "asynchronous state" (a state in which population activity is constant in time when external inputs are constant) in the space of parameters characterizing the connectivity of the network. We then systematically characterize the qualitative behaviors of the dynamical transfer function, as a function of the connectivity. We find that the transfer function can be either low-pass, or with a single or double resonance, depending on the connection strengths and synaptic time constants. Resonances appear when the system is close to Hopf bifurcations, that can be induced by two separate mechanisms: the I-I connectivity and the E-I connectivity. Double resonances can appear when excitatory delays are larger than inhibitory delays, due to the fact that two distinct instabilities exist with a finite gap between the corresponding frequencies. In networks of LIF neurons, changes in external inputs and external noise are shown to be able to change qualitatively the network transfer function. Firing rate models are shown to exhibit the same diversity of transfer functions as the LIF network, provided delays are present. They can also exhibit input-dependent changes of the transfer function, provided a suitable static non-linearity is incorporated.

  17. Polishing tool and the resulting TIF for three variable machine parameters as input for the removal simulation

    NASA Astrophysics Data System (ADS)

    Schneider, Robert; Haberl, Alexander; Rascher, Rolf

    2017-06-01

    The trend in the optic industry shows, that it is increasingly important to be able to manufacture complex lens geometries on a high level of precision. From a certain limit on the required shape accuracy of optical workpieces, the processing is changed from the two-dimensional to point-shaped processing. It is very important that the process is as stable as possible during the in point-shaped processing. To ensure stability, usually only one process parameter is varied during processing. It is common that this parameter is the feed rate, which corresponds to the dwell time. In the research project ArenA-FOi (Application-oriented analysis of resource-saving and energy-efficient design of industrial facilities for the optical industry), a touching procedure is used in the point-attack, and in this case a close look is made as to whether a change of several process parameters is meaningful during a processing. The ADAPT tool in size R20 from Satisloh AG is used, which is also available for purchase. The behavior of the tool is tested under constant conditions in the MCP 250 CNC by OptoTech GmbH. A series of experiments should enable the TIF (tool influence function) to be determined using three variable parameters. Furthermore, the maximum error frequency that can be processed is calculated as an example for one parameter set and serves as an outlook for further investigations. The test results serve as the basic for the later removal simulation, which must be able to deal with a variable TIF. This topic has already been successfully implemented in another research project of the Institute for Precision Manufacturing and High-Frequency Technology (IPH) and thus this algorithm can be used. The next step is the useful implementation of the collected knowledge. The TIF must be selected on the basis of the measured data. It is important to know the error frequencies to select the optimal TIF. Thus, it is possible to compare the simulated results with real measurement

  18. A New Local Bipolar Autoassociative Memory Based on External Inputs of Discrete Recurrent Neural Networks With Time Delay.

    PubMed

    Zhou, Caigen; Zeng, Xiaoqin; Luo, Chaomin; Zhang, Huaguang

    In this paper, local bipolar auto-associative memories are presented based on discrete recurrent neural networks with a class of gain type activation function. The weight parameters of neural networks are acquired by a set of inequalities without the learning procedure. The global exponential stability criteria are established to ensure the accuracy of the restored patterns by considering time delays and external inputs. The proposed methodology is capable of effectively overcoming spurious memory patterns and achieving memory capacity. The effectiveness, robustness, and fault-tolerant capability are validated by simulated experiments.In this paper, local bipolar auto-associative memories are presented based on discrete recurrent neural networks with a class of gain type activation function. The weight parameters of neural networks are acquired by a set of inequalities without the learning procedure. The global exponential stability criteria are established to ensure the accuracy of the restored patterns by considering time delays and external inputs. The proposed methodology is capable of effectively overcoming spurious memory patterns and achieving memory capacity. The effectiveness, robustness, and fault-tolerant capability are validated by simulated experiments.

  19. L1 Adaptive Control Augmentation System with Application to the X-29 Lateral/Directional Dynamics: A Multi-Input Multi-Output Approach

    NASA Technical Reports Server (NTRS)

    Griffin, Brian Joseph; Burken, John J.; Xargay, Enric

    2010-01-01

    This paper presents an L(sub 1) adaptive control augmentation system design for multi-input multi-output nonlinear systems in the presence of unmatched uncertainties which may exhibit significant cross-coupling effects. A piecewise continuous adaptive law is adopted and extended for applicability to multi-input multi-output systems that explicitly compensates for dynamic cross-coupling. In addition, explicit use of high-fidelity actuator models are added to the L1 architecture to reduce uncertainties in the system. The L(sub 1) multi-input multi-output adaptive control architecture is applied to the X-29 lateral/directional dynamics and results are evaluated against a similar single-input single-output design approach.

  20. Influence of Choice of Null Network on Small-World Parameters of Structural Correlation Networks

    PubMed Central

    Hosseini, S. M. Hadi; Kesler, Shelli R.

    2013-01-01

    In recent years, coordinated variations in brain morphology (e.g., volume, thickness) have been employed as a measure of structural association between brain regions to infer large-scale structural correlation networks. Recent evidence suggests that brain networks constructed in this manner are inherently more clustered than random networks of the same size and degree. Thus, null networks constructed by randomizing topology are not a good choice for benchmarking small-world parameters of these networks. In the present report, we investigated the influence of choice of null networks on small-world parameters of gray matter correlation networks in healthy individuals and survivors of acute lymphoblastic leukemia. Three types of null networks were studied: 1) networks constructed by topology randomization (TOP), 2) networks matched to the distributional properties of the observed covariance matrix (HQS), and 3) networks generated from correlation of randomized input data (COR). The results revealed that the choice of null network not only influences the estimated small-world parameters, it also influences the results of between-group differences in small-world parameters. In addition, at higher network densities, the choice of null network influences the direction of group differences in network measures. Our data suggest that the choice of null network is quite crucial for interpretation of group differences in small-world parameters of structural correlation networks. We argue that none of the available null models is perfect for estimation of small-world parameters for correlation networks and the relative strengths and weaknesses of the selected model should be carefully considered with respect to obtained network measures. PMID:23840672

  1. Understanding the Impact of Charcoal Inputs to Soils and Sediments on Conventional Geochemical Markers

    NASA Astrophysics Data System (ADS)

    Kuo, L.; Louchouarn, P.; Herbert, B.

    2008-12-01

    Chars/charcoals are solid combustion residues derived from biomass burning. They represent one of the major classes in the pyrogenic organic residues, the so-called black carbon (BC), and have highly heterogeneous nature due to the highly variable combustion conditions during biomass burning. More and more attention has been given to characterize and quantify the inputs of charcoals to different environmental compartments since they also share the common features of BC, such as recalcitrant nature and strong sorption capacity on hydrophobic organic pollutants. Moreover, such inputs also imply the thermal alteration of terrestrial organic matter, as well as corresponding biomarkers such as lignin. Lignin is considered to be among the best-preserved components of vascular plants after deposition, due to its relative stability on biodegradation. This macropolymer is an important contributor to soil organic matter (SOM) and its presence in aquatic environments helps trace the input of terrigenous organic matter to such systems. The yields and specific ratios of lignin oxidation products (LOP) from alkaline cupric oxide (CuO) oxidation method have been extensively used to identify the structure of plant lignin and estimate inputs of plant carbon to soils and aquatic systems, as well as evaluate the diagenetic status of lignin. Although the fate of lignin under microbiological and photochemical degradation pathways have been thoroughly addressed in the literature, studies assessing the impact of thermal degradation on lignin structure and signature are scarce. In the present study, we used three suites of lab-made chars (honey mesquite, cordgrass, and loblolly pine) to study the impact of combustion on lignin and their commonly used parameters. Our results show that combustion can greatly decrease the yields of the eight major lignin phenols (vanillyl, syringyl, and cinnamyl phenols) with no lignin phenols detected in any synthetic char produced at ≥ 400°C. With

  2. Boolean Modeling of Neural Systems with Point-Process Inputs and Outputs. Part I: Theory and Simulations

    PubMed Central

    Marmarelis, Vasilis Z.; Zanos, Theodoros P.; Berger, Theodore W.

    2010-01-01

    This paper presents a new modeling approach for neural systems with point-process (spike) inputs and outputs that utilizes Boolean operators (i.e. modulo 2 multiplication and addition that correspond to the logical AND and OR operations respectively, as well as the AND_NOT logical operation representing inhibitory effects). The form of the employed mathematical models is akin to a “Boolean-Volterra” model that contains the product terms of all relevant input lags in a hierarchical order, where terms of order higher than first represent nonlinear interactions among the various lagged values of each input point-process or among lagged values of various inputs (if multiple inputs exist) as they reflect on the output. The coefficients of this Boolean-Volterra model are also binary variables that indicate the presence or absence of the respective term in each specific model/system. Simulations are used to explore the properties of such models and the feasibility of their accurate estimation from short data-records in the presence of noise (i.e. spurious spikes). The results demonstrate the feasibility of obtaining reliable estimates of such models, with excitatory and inhibitory terms, in the presence of considerable noise (spurious spikes) in the outputs and/or the inputs in a computationally efficient manner. A pilot application of this approach to an actual neural system is presented in the companion paper (Part II). PMID:19517238

  3. A Two-Stage Algorithm for Origin-Destination Matrices Estimation Considering Dynamic Dispersion Parameter for Route Choice

    PubMed Central

    Wang, Yong; Ma, Xiaolei; Liu, Yong; Gong, Ke; Henricakson, Kristian C.; Xu, Maozeng; Wang, Yinhai

    2016-01-01

    This paper proposes a two-stage algorithm to simultaneously estimate origin-destination (OD) matrix, link choice proportion, and dispersion parameter using partial traffic counts in a congested network. A non-linear optimization model is developed which incorporates a dynamic dispersion parameter, followed by a two-stage algorithm in which Generalized Least Squares (GLS) estimation and a Stochastic User Equilibrium (SUE) assignment model are iteratively applied until the convergence is reached. To evaluate the performance of the algorithm, the proposed approach is implemented in a hypothetical network using input data with high error, and tested under a range of variation coefficients. The root mean squared error (RMSE) of the estimated OD demand and link flows are used to evaluate the model estimation results. The results indicate that the estimated dispersion parameter theta is insensitive to the choice of variation coefficients. The proposed approach is shown to outperform two established OD estimation methods and produce parameter estimates that are close to the ground truth. In addition, the proposed approach is applied to an empirical network in Seattle, WA to validate the robustness and practicality of this methodology. In summary, this study proposes and evaluates an innovative computational approach to accurately estimate OD matrices using link-level traffic flow data, and provides useful insight for optimal parameter selection in modeling travelers’ route choice behavior. PMID:26761209

  4. Comprehensible Input and Second Language Acquisition: What Is the Relationship?

    ERIC Educational Resources Information Center

    Loschky, Lester

    1994-01-01

    Examined the influence of input and interactional modifications on second-language acquisition, assigning 41 learners of Japanese to 1 of 3 experimental groups: (1) unmodified input with no interaction; (2) premodified input with no interaction; and (3) unmodified input with the chance for negotiated input. Results indicated that comprehension was…

  5. 40 CFR 75.75 - Additional ozone season calculation procedures for special circumstances.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 40 Protection of Environment 16 2010-07-01 2010-07-01 false Additional ozone season calculation... § 75.75 Additional ozone season calculation procedures for special circumstances. (a) The owner or operator of a unit that is required to calculate ozone season heat input for purposes of providing data...

  6. 40 CFR 75.75 - Additional ozone season calculation procedures for special circumstances.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 40 Protection of Environment 16 2011-07-01 2011-07-01 false Additional ozone season calculation... § 75.75 Additional ozone season calculation procedures for special circumstances. (a) The owner or operator of a unit that is required to calculate ozone season heat input for purposes of providing data...

  7. 40 CFR 75.75 - Additional ozone season calculation procedures for special circumstances.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 40 Protection of Environment 17 2012-07-01 2012-07-01 false Additional ozone season calculation... § 75.75 Additional ozone season calculation procedures for special circumstances. (a) The owner or operator of a unit that is required to calculate ozone season heat input for purposes of providing data...

  8. 40 CFR 75.75 - Additional ozone season calculation procedures for special circumstances.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 40 Protection of Environment 17 2013-07-01 2013-07-01 false Additional ozone season calculation... § 75.75 Additional ozone season calculation procedures for special circumstances. (a) The owner or operator of a unit that is required to calculate ozone season heat input for purposes of providing data...

  9. 40 CFR 75.75 - Additional ozone season calculation procedures for special circumstances.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 40 Protection of Environment 17 2014-07-01 2014-07-01 false Additional ozone season calculation... § 75.75 Additional ozone season calculation procedures for special circumstances. (a) The owner or operator of a unit that is required to calculate ozone season heat input for purposes of providing data...

  10. Processing time of addition or withdrawal of single or combined balance-stabilizing haptic and visual information

    PubMed Central

    Honeine, Jean-Louis; Crisafulli, Oscar; Sozzi, Stefania

    2015-01-01

    We investigated the integration time of haptic and visual input and their interaction during stance stabilization. Eleven subjects performed four tandem-stance conditions (60 trials each). Vision, touch, and both vision and touch were added and withdrawn. Furthermore, vision was replaced with touch and vice versa. Body sway, tibialis anterior, and peroneus longus activity were measured. Following addition or withdrawal of vision or touch, an integration time period elapsed before the earliest changes in sway were observed. Thereafter, sway varied exponentially to a new steady-state while reweighting occurred. Latencies of sway changes on sensory addition ranged from 0.6 to 1.5 s across subjects, consistently longer for touch than vision, and were regularly preceded by changes in muscle activity. Addition of vision and touch simultaneously shortened the latencies with respect to vision or touch separately, suggesting cooperation between sensory modalities. Latencies following withdrawal of vision or touch or both simultaneously were shorter than following addition. When vision was replaced with touch or vice versa, adding one modality did not interfere with the effect of withdrawal of the other, suggesting that integration of withdrawal and addition were performed in parallel. The time course of the reweighting process to reach the new steady-state was also shorter on withdrawal than addition. The effects of different sensory inputs on posture stabilization illustrate the operation of a time-consuming, possibly supraspinal process that integrates and fuses modalities for accurate balance control. This study also shows the facilitatory interaction of visual and haptic inputs in integration and reweighting of stance-stabilizing inputs. PMID:26334013

  11. Electronic stopping in oxides beyond Bragg additivity

    NASA Astrophysics Data System (ADS)

    Sigmund, P.; Schinner, A.

    2018-01-01

    We present stopping cross sections calculated by our PASS code for several ions in metal oxides and SiO2 over a wide energy range. Input takes into account changes in the valence structure by assigning two additional electrons to the 2p shell of oxygen and removing the appropriate number of electrons from the outer shells of the metal atom. Results are compared with tabulated experimental values and with two versions of Bragg's additivity rule. Calculated stopping cross sections are applied in testing a recently-proposed scaling rule, which relates the stopping cross section to the number of oxygen atoms per molecule.

  12. LAND AND WATER USE CHARACTERISTICS AND HUMAN HEALTH INPUT PARAMETERS FOR USE IN ENVIRONMENTAL DOSIMETRY AND RISK ASSESSMENTS AT THE SAVANNAH RIVER SITE

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

    Jannik, T.; Karapatakis, D.; Lee, P.

    2010-08-06

    Operations at the Savannah River Site (SRS) result in releases of small amounts of radioactive materials to the atmosphere and to the Savannah River. For regulatory compliance purposes, potential offsite radiological doses are estimated annually using computer models that follow U.S. Nuclear Regulatory Commission (NRC) Regulatory Guides. Within the regulatory guides, default values are provided for many of the dose model parameters but the use of site-specific values by the applicant is encouraged. A detailed survey of land and water use parameters was conducted in 1991 and is being updated here. These parameters include local characteristics of meat, milk andmore » vegetable production; river recreational activities; and meat, milk and vegetable consumption rates as well as other human usage parameters required in the SRS dosimetry models. In addition, the preferred elemental bioaccumulation factors and transfer factors to be used in human health exposure calculations at SRS are documented. Based on comparisons to the 2009 SRS environmental compliance doses, the following effects are expected in future SRS compliance dose calculations: (1) Aquatic all-pathway maximally exposed individual doses may go up about 10 percent due to changes in the aquatic bioaccumulation factors; (2) Aquatic all-pathway collective doses may go up about 5 percent due to changes in the aquatic bioaccumulation factors that offset the reduction in average individual water consumption rates; (3) Irrigation pathway doses to the maximally exposed individual may go up about 40 percent due to increases in the element-specific transfer factors; (4) Irrigation pathway collective doses may go down about 50 percent due to changes in food productivity and production within the 50-mile radius of SRS; (5) Air pathway doses to the maximally exposed individual may go down about 10 percent due to the changes in food productivity in the SRS area and to the changes in element-specific transfer factors

  13. Control of Groundwater Remediation Process as Distributed Parameter System

    NASA Astrophysics Data System (ADS)

    Mendel, M.; Kovács, T.; Hulkó, G.

    2014-12-01

    Pollution of groundwater requires the implementation of appropriate solutions which can be deployed for several years. The case of local groundwater contamination and its subsequent spread may result in contamination of drinking water sources or other disasters. This publication aims to design and demonstrate control of pumping wells for a model task of groundwater remediation. The task consists of appropriately spaced soil with input parameters, pumping wells and control system. Model of controlled system is made in the program MODFLOW using the finitedifference method as distributed parameter system. Control problem is solved by DPS Blockset for MATLAB & Simulink.

  14. Effects of Nitrogen Inputs and Watershed Characteristics on ...

    EPA Pesticide Factsheets

    Nitrogen (N) inputs to the landscape have been linked previously to N loads exported from watersheds at the national scale; however, stream N concentration is arguably more relevant than N load for drinking water quality, freshwater biological responses and establishment of nutrient criteria. In this study, we combine national-scale anthropogenic N input data, including synthetic fertilizer, crop biological N fixation, manure applied to farmland, atmospheric N deposition, and point source inputs, with data from the 2008-09 National Rivers and Streams Assessment to quantify the relationship between N inputs and in-stream concentrations of total N (TN), dissolved inorganic N (DIN), and total organic N (TON) (calculated as TN – DIN). In conjunction with simple linear regression, we use multiple regression to understand how watershed and stream reach attributes modify the effect of N inputs on N concentrations. Median TN was 0.50 mg N L-1 with a maximum of 25.8 mg N L-1. Total N inputs to the watershed ranged from less than 1 to 196 kg N ha-1 y-1, with a median of 14.4 kg N ha-1 y-1. Atmospheric N deposition was the single largest anthropogenic N source in the majority of sites, but, agricultural sources generally dominate total N inputs in sites with elevated N concentrations. The sum of all N inputs were positively correlated with concentrations of all forms of N [r2 = 0.44, 0.43, and 0.18 for TN, DIN, and TON, respectively (all log-transformed), n = 1112], indi

  15. Influence of tool geometry and processing parameters on welding defects and mechanical properties for friction stir welding of 6061 Aluminium alloy

    NASA Astrophysics Data System (ADS)

    Daneji, A.; Ali, M.; Pervaiz, S.

    2018-04-01

    Friction stir welding (FSW) is a form of solid state welding process for joining metals, alloys, and selective composites. Over the years, FSW development has provided an improved way of producing welding joints, and consequently got accepted in numerous industries such as aerospace, automotive, rail and marine etc. In FSW, the base metal properties control the material’s plastic flow under the influence of a rotating tool whereas, the process and tool parameters play a vital role in the quality of weld. In the current investigation, an array of square butt joints of 6061 Aluminum alloy was to be welded under varying FSW process and tool geometry related parameters, after which the resulting weld was evaluated for the corresponding mechanical properties and welding defects. The study incorporates FSW process and tool parameters such as welding speed, pin height and pin thread pitch as input parameters. However, the weld quality related defects and mechanical properties were treated as output parameters. The experimentation paves way to investigate the correlation between the inputs and the outputs. The correlation between inputs and outputs were used as tool to predict the optimized FSW process and tool parameters for a desired weld output of the base metals under investigation. The study also provides reflection on the effect of said parameters on a welding defect such as wormhole.

  16. Effects of anodizing parameters and heat treatment on nanotopographical features, bioactivity, and cell culture response of additively manufactured porous titanium.

    PubMed

    Amin Yavari, S; Chai, Y C; Böttger, A J; Wauthle, R; Schrooten, J; Weinans, H; Zadpoor, A A

    2015-06-01

    Anodizing could be used for bio-functionalization of the surfaces of titanium alloys. In this study, we use anodizing for creating nanotubes on the surface of porous titanium alloy bone substitutes manufactured using selective laser melting. Different sets of anodizing parameters (voltage: 10 or 20V anodizing time: 30min to 3h) are used for anodizing porous titanium structures that were later heat treated at 500°C. The nanotopographical features are examined using electron microscopy while the bioactivity of anodized surfaces is measured using immersion tests in the simulated body fluid (SBF). Moreover, the effects of anodizing and heat treatment on the performance of one representative anodized porous titanium structures are evaluated using in vitro cell culture assays using human periosteum-derived cells (hPDCs). It has been shown that while anodizing with different anodizing parameters results in very different nanotopographical features, i.e. nanotubes in the range of 20 to 55nm, anodized surfaces have limited apatite-forming ability regardless of the applied anodizing parameters. The results of in vitro cell culture show that both anodizing, and thus generation of regular nanotopographical feature, and heat treatment improve the cell culture response of porous titanium. In particular, cell proliferation measured using metabolic activity and DNA content was improved for anodized and heat treated as well as for anodized but not heat-treated specimens. Heat treatment additionally improved the cell attachment of porous titanium surfaces and upregulated expression of osteogenic markers. Anodized but not heat-treated specimens showed some limited signs of upregulated expression of osteogenic markers. In conclusion, while varying the anodizing parameters creates different nanotube structure, it does not improve apatite-forming ability of porous titanium. However, both anodizing and heat treatment at 500°C improve the cell culture response of porous titanium

  17. Advantages of measuring the Q Stokes parameter in addition to the total radiance I in the detection of absorbing aerosols

    NASA Astrophysics Data System (ADS)

    Stamnes, Snorre; Fan, Yongzhen; Chen, Nan; Li, Wei; Tanikawa, Tomonori; Lin, Zhenyi; Liu, Xu; Burton, Sharon; Omar, Ali; Stamnes, Jakob J.; Cairns, Brian; Stamnes, Knut

    2018-05-01

    A simple but novel study was conducted to investigate whether an imager-type spectroradiometer instrument like MODIS, currently flying on board the Aqua and Terra satellites, or MERIS, which flew on board Envisat, could detect absorbing aerosols if they could measure the Q Stokes parameter in addition to the total radiance I, that is if they could also measure the linear polarization of the light. Accurate radiative transfer calculations were used to train a fast neural network forward model, which together with a simple statistical optimal estimation scheme was used to retrieve three aerosol parameters: aerosol optical depth at 869 nm, optical depth fraction of fine mode (absorbing) aerosols at 869 nm, and aerosol vertical location. The aerosols were assumed to be bimodal, each with a lognormal size distribution, located either between 0 and 2 km or between 2 and 4 km in the Earth's atmosphere. From simulated data with 3% random Gaussian measurement noise added for each Stokes parameter, it was found that by itself the total radiance I at the nine MODIS VIS channels was generally insufficient to accurately retrieve all three aerosol parameters (˜ 15% to 37% successful), but that together with the Q Stokes component it was possible to retrieve values of aerosol optical depth at 869 nm to ± 0.03, single-scattering albedo at 869 nm to ± 0.04, and vertical location in ˜ 65% of the cases. This proof-of-concept retrieval algorithm uses neural networks to overcome the computational burdens of using vector radiative transfer to accurately simulate top-of-atmosphere (TOA) total and polarized radiances, enabling optimal estimation techniques to exploit information from multiple channels. Therefore such an algorithm could, in concept, be readily implemented for operational retrieval of aerosol and ocean products from moderate or hyperspectral spectroradiometers.

  18. Research on Mechanisms and Controlling Methods of Macro Defects in TC4 Alloy Fabricated by Wire Additive Manufacturing.

    PubMed

    Ji, Lei; Lu, Jiping; Tang, Shuiyuan; Wu, Qianru; Wang, Jiachen; Ma, Shuyuan; Fan, Hongli; Liu, Changmeng

    2018-06-28

    Wire feeding additive manufacturing (WFAM) has broad application prospects because of its advantages of low cost and high efficiency. However, with the mode of lateral wire feeding, including wire and laser additive manufacturing, gas tungsten arc additive manufacturing etc., it is easy to generate macro defects on the surface of the components because of the anisotropy of melted wire, which limits the promotion and application of WFAM. In this work, gas tungsten arc additive manufacturing with lateral wire feeding is proposed to investigate the mechanisms of macro defects. The results illustrate that the defect forms mainly include side spatters, collapse, poor flatness, and unmelted wire. It was found that the heat input, layer thickness, tool path, and wire curvature can have an impact on the macro defects. Side spatters are the most serious defects, mainly because the droplets cannot be transferred to the center of the molten pool in the lateral wire feeding mode. This research indicates that the macro defects can be controlled by optimizing the process parameters. Finally, block parts without macro defects were fabricated, which is meaningful for the further application of WFAM.

  19. Remote media vision-based computer input device

    NASA Astrophysics Data System (ADS)

    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.

  20. A Full Dynamic Compound Inverse Method for output-only element-level system identification and input estimation from earthquake response signals

    NASA Astrophysics Data System (ADS)

    Pioldi, Fabio; Rizzi, Egidio

    2016-08-01

    This paper proposes a new output-only element-level system identification and input estimation technique, towards the simultaneous identification of modal parameters, input excitation time history and structural features at the element-level by adopting earthquake-induced structural response signals. The method, named Full Dynamic Compound Inverse Method (FDCIM), releases strong assumptions of earlier element-level techniques, by working with a two-stage iterative algorithm. Jointly, a Statistical Average technique, a modification process and a parameter projection strategy are adopted at each stage to achieve stronger convergence for the identified estimates. The proposed method works in a deterministic way and is completely developed in State-Space form. Further, it does not require continuous- to discrete-time transformations and does not depend on initialization conditions. Synthetic earthquake-induced response signals from different shear-type buildings are generated to validate the implemented procedure, also with noise-corrupted cases. The achieved results provide a necessary condition to demonstrate the effectiveness of the proposed identification method.