Sample records for accurate input parameters

  1. 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

  2. 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.

  3. 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

  4. The Effects of Input-Enhanced Instruction on Iranian EFL Learners' Production of Appropriate and Accurate Suggestions

    ERIC Educational Resources Information Center

    Ghavamnia, M.; Eslami-Rasekh, A.; Vahid Dastjerdi, H.

    2018-01-01

    This study investigates the relative effectiveness of four types of input-enhanced instruction on the development of Iranian EFL learners' production of pragmatically appropriate and grammatically accurate suggestions. Over a 16-week course, input delivered through video clips was enhanced differently in four intact classes: (1) metapragmatic…

  5. 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

  6. A convenient and accurate parallel Input/Output USB device for E-Prime.

    PubMed

    Canto, Rosario; Bufalari, Ilaria; D'Ausilio, Alessandro

    2011-03-01

    Psychological and neurophysiological experiments require the accurate control of timing and synchrony for Input/Output signals. For instance, a typical Event-Related Potential (ERP) study requires an extremely accurate synchronization of stimulus delivery with recordings. This is typically done via computer software such as E-Prime, and fast communications are typically assured by the Parallel Port (PP). However, the PP is an old and disappearing technology that, for example, is no longer available on portable computers. Here we propose a convenient USB device enabling parallel I/O capabilities. We tested this device against the PP on both a desktop and a laptop machine in different stress tests. Our data demonstrate the accuracy of our system, which suggests that it may be a good substitute for the PP with E-Prime.

  7. 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.

  8. Technical Note: Using experimentally determined proton spot scanning timing parameters to accurately model beam delivery time.

    PubMed

    Shen, Jiajian; Tryggestad, Erik; Younkin, James E; Keole, Sameer R; Furutani, Keith M; Kang, Yixiu; Herman, Michael G; Bues, Martin

    2017-10-01

    To accurately model the beam delivery time (BDT) for a synchrotron-based proton spot scanning system using experimentally determined beam parameters. A model to simulate the proton spot delivery sequences was constructed, and BDT was calculated by summing times for layer switch, spot switch, and spot delivery. Test plans were designed to isolate and quantify the relevant beam parameters in the operation cycle of the proton beam therapy delivery system. These parameters included the layer switch time, magnet preparation and verification time, average beam scanning speeds in x- and y-directions, proton spill rate, and maximum charge and maximum extraction time for each spill. The experimentally determined parameters, as well as the nominal values initially provided by the vendor, served as inputs to the model to predict BDTs for 602 clinical proton beam deliveries. The calculated BDTs (T BDT ) were compared with the BDTs recorded in the treatment delivery log files (T Log ): ∆t = T Log -T BDT . The experimentally determined average layer switch time for all 97 energies was 1.91 s (ranging from 1.9 to 2.0 s for beam energies from 71.3 to 228.8 MeV), average magnet preparation and verification time was 1.93 ms, the average scanning speeds were 5.9 m/s in x-direction and 19.3 m/s in y-direction, the proton spill rate was 8.7 MU/s, and the maximum proton charge available for one acceleration is 2.0 ± 0.4 nC. Some of the measured parameters differed from the nominal values provided by the vendor. The calculated BDTs using experimentally determined parameters matched the recorded BDTs of 602 beam deliveries (∆t = -0.49 ± 1.44 s), which were significantly more accurate than BDTs calculated using nominal timing parameters (∆t = -7.48 ± 6.97 s). An accurate model for BDT prediction was achieved by using the experimentally determined proton beam therapy delivery parameters, which may be useful in modeling the interplay effect and patient throughput. The model may

  9. 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.

  10. 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.

  11. 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

  12. 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.

  13. 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.

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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.

  19. Machine Learning of Parameters for Accurate Semiempirical Quantum Chemical Calculations

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

    Dral, Pavlo O.; von Lilienfeld, O. Anatole; Thiel, Walter

    2015-05-12

    We investigate possible improvements in the accuracy of semiempirical quantum chemistry (SQC) methods through the use of machine learning (ML) models for the parameters. For a given class of compounds, ML techniques require sufficiently large training sets to develop ML models that can be used for adapting SQC parameters to reflect changes in molecular composition and geometry. The ML-SQC approach allows the automatic tuning of SQC parameters for individual molecules, thereby improving the accuracy without deteriorating transferability to molecules with molecular descriptors very different from those in the training set. The performance of this approach is demonstrated for the semiempiricalmore » OM2 method using a set of 6095 constitutional isomers C7H10O2, for which accurate ab initio atomization enthalpies are available. The ML-OM2 results show improved average accuracy and a much reduced error range compared with those of standard OM2 results, with mean absolute errors in atomization enthalpies dropping from 6.3 to 1.7 kcal/mol. They are also found to be superior to the results from specific OM2 reparameterizations (rOM2) for the same set of isomers. The ML-SQC approach thus holds promise for fast and reasonably accurate high-throughput screening of materials and molecules.« less

  20. Machine learning of parameters for accurate semiempirical quantum chemical calculations

    DOE PAGES

    Dral, Pavlo O.; von Lilienfeld, O. Anatole; Thiel, Walter

    2015-04-14

    We investigate possible improvements in the accuracy of semiempirical quantum chemistry (SQC) methods through the use of machine learning (ML) models for the parameters. For a given class of compounds, ML techniques require sufficiently large training sets to develop ML models that can be used for adapting SQC parameters to reflect changes in molecular composition and geometry. The ML-SQC approach allows the automatic tuning of SQC parameters for individual molecules, thereby improving the accuracy without deteriorating transferability to molecules with molecular descriptors very different from those in the training set. The performance of this approach is demonstrated for the semiempiricalmore » OM2 method using a set of 6095 constitutional isomers C 7H 10O 2, for which accurate ab initio atomization enthalpies are available. The ML-OM2 results show improved average accuracy and a much reduced error range compared with those of standard OM2 results, with mean absolute errors in atomization enthalpies dropping from 6.3 to 1.7 kcal/mol. They are also found to be superior to the results from specific OM2 reparameterizations (rOM2) for the same set of isomers. The ML-SQC approach thus holds promise for fast and reasonably accurate high-throughput screening of materials and molecules.« less

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. 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

  14. 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

  15. 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

  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. 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

  19. 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.

  20. 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

  1. Data Mining for Efficient and Accurate Large Scale Retrieval of Geophysical Parameters

    NASA Astrophysics Data System (ADS)

    Obradovic, Z.; Vucetic, S.; Peng, K.; Han, B.

    2004-12-01

    Our effort is devoted to developing data mining technology for improving efficiency and accuracy of the geophysical parameter retrievals by learning a mapping from observation attributes to the corresponding parameters within the framework of classification and regression. We will describe a method for efficient learning of neural network-based classification and regression models from high-volume data streams. The proposed procedure automatically learns a series of neural networks of different complexities on smaller data stream chunks and then properly combines them into an ensemble predictor through averaging. Based on the idea of progressive sampling the proposed approach starts with a very simple network trained on a very small chunk and then gradually increases the model complexity and the chunk size until the learning performance no longer improves. Our empirical study on aerosol retrievals from data obtained with the MISR instrument mounted at Terra satellite suggests that the proposed method is successful in learning complex concepts from large data streams with near-optimal computational effort. We will also report on a method that complements deterministic retrievals by constructing accurate predictive algorithms and applying them on appropriately selected subsets of observed data. The method is based on developing more accurate predictors aimed to catch global and local properties synthesized in a region. The procedure starts by learning the global properties of data sampled over the entire space, and continues by constructing specialized models on selected localized regions. The global and local models are integrated through an automated procedure that determines the optimal trade-off between the two components with the objective of minimizing the overall mean square errors over a specific region. Our experimental results on MISR data showed that the combined model can increase the retrieval accuracy significantly. The preliminary results on various

  2. Bayesian parameter estimation of a k-ε model for accurate jet-in-crossflow simulations

    DOE PAGES

    Ray, Jaideep; Lefantzi, Sophia; Arunajatesan, Srinivasan; ...

    2016-05-31

    Reynolds-averaged Navier–Stokes models are not very accurate for high-Reynolds-number compressible jet-in-crossflow interactions. The inaccuracy arises from the use of inappropriate model parameters and model-form errors in the Reynolds-averaged Navier–Stokes model. In this study, the hypothesis is pursued that Reynolds-averaged Navier–Stokes predictions can be significantly improved by using parameters inferred from experimental measurements of a supersonic jet interacting with a transonic crossflow.

  3. 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.

  4. 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.

  5. 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

  6. Robust and accurate vectorization of line drawings.

    PubMed

    Hilaire, Xavier; Tombre, Karl

    2006-06-01

    This paper presents a method for vectorizing the graphical parts of paper-based line drawings. The method consists of separating the input binary image into layers of homogeneous thickness, skeletonizing each layer, segmenting the skeleton by a method based on random sampling, and simplifying the result. The segmentation method is robust with a best bound of 50 percent noise reached for indefinitely long primitives. Accurate estimation of the recognized vector's parameters is enabled by explicitly computing their feasibility domains. Theoretical performance analysis and expression of the complexity of the segmentation method are derived. Experimental results and comparisons with other vectorization systems are also provided.

  7. Accurate estimation of motion blur parameters in noisy remote sensing image

    NASA Astrophysics Data System (ADS)

    Shi, Xueyan; Wang, Lin; Shao, Xiaopeng; Wang, Huilin; Tao, Zhong

    2015-05-01

    The relative motion between remote sensing satellite sensor and objects is one of the most common reasons for remote sensing image degradation. It seriously weakens image data interpretation and information extraction. In practice, point spread function (PSF) should be estimated firstly for image restoration. Identifying motion blur direction and length accurately is very crucial for PSF and restoring image with precision. In general, the regular light-and-dark stripes in the spectrum can be employed to obtain the parameters by using Radon transform. However, serious noise existing in actual remote sensing images often causes the stripes unobvious. The parameters would be difficult to calculate and the error of the result relatively big. In this paper, an improved motion blur parameter identification method to noisy remote sensing image is proposed to solve this problem. The spectrum characteristic of noisy remote sensing image is analyzed firstly. An interactive image segmentation method based on graph theory called GrabCut is adopted to effectively extract the edge of the light center in the spectrum. Motion blur direction is estimated by applying Radon transform on the segmentation result. In order to reduce random error, a method based on whole column statistics is used during calculating blur length. Finally, Lucy-Richardson algorithm is applied to restore the remote sensing images of the moon after estimating blur parameters. The experimental results verify the effectiveness and robustness of our algorithm.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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

    = 0.002, r = 0.570); kep, vp, and HPI between the two kinetic models were positively correlated (P = 0.001, r = 0.594; P = 0.0001, r = 0.686; P = 0.04, r = 0.391, respectively). In the dual input extended Tofts model, ve was significantly less than that in the dual input 2CXM (P = 0.004), and no significant correlation was seen between the two tracer kinetic models (P = 0.156, r = 0.276). Neither tumor size nor tumor stage was significantly correlated with any of the pharmacokinetic parameters obtained from the two models (P > 0.05). A dual-input two-compartment pharmacokinetic model (a dual-input extended Tofts model and a dual-input 2CXM) can be used in assessing the microvascular physiopathological properties before the treatment of advanced HCC. The dual-input extended Tofts model may be more stable in measuring the ve; however, the dual-input 2CXM may be more detailed and accurate in measuring microvascular permeability.

  20. Building accurate historic and future climate MEPDG input files for Louisiana DOTD : tech summary.

    DOT National Transportation Integrated Search

    2017-02-01

    The new pavement design process (originally MEPDG, then DARWin-ME, and now Pavement ME Design) requires two types : of inputs to infl uence the prediction of pavement distress for a selected set of pavement materials and structure. One input is : tra...

  1. 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.

  2. 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

  3. 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.

  4. 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

  5. Simple, accurate formula for the average bit error probability of multiple-input multiple-output free-space optical links over negative exponential turbulence channels.

    PubMed

    Peppas, Kostas P; Lazarakis, Fotis; Alexandridis, Antonis; Dangakis, Kostas

    2012-08-01

    In this Letter we investigate the error performance of multiple-input multiple-output free-space optical communication systems employing intensity modulation/direct detection and operating over strong atmospheric turbulence channels. Atmospheric-induced strong turbulence fading is modeled using the negative exponential distribution. For the considered system, an approximate yet accurate analytical expression for the average bit error probability is derived and an efficient method for its numerical evaluation is proposed. Numerically evaluated and computer simulation results are further provided to demonstrate the validity of the proposed mathematical analysis.

  6. Accurate path integration in continuous attractor network models of grid cells.

    PubMed

    Burak, Yoram; Fiete, Ila R

    2009-02-01

    Grid cells in the rat entorhinal cortex display strikingly regular firing responses to the animal's position in 2-D space and have been hypothesized to form the neural substrate for dead-reckoning. However, errors accumulate rapidly when velocity inputs are integrated in existing models of grid cell activity. To produce grid-cell-like responses, these models would require frequent resets triggered by external sensory cues. Such inadequacies, shared by various models, cast doubt on the dead-reckoning potential of the grid cell system. Here we focus on the question of accurate path integration, specifically in continuous attractor models of grid cell activity. We show, in contrast to previous models, that continuous attractor models can generate regular triangular grid responses, based on inputs that encode only the rat's velocity and heading direction. We consider the role of the network boundary in the integration performance of the network and show that both periodic and aperiodic networks are capable of accurate path integration, despite important differences in their attractor manifolds. We quantify the rate at which errors in the velocity integration accumulate as a function of network size and intrinsic noise within the network. With a plausible range of parameters and the inclusion of spike variability, our model networks can accurately integrate velocity inputs over a maximum of approximately 10-100 meters and approximately 1-10 minutes. These findings form a proof-of-concept that continuous attractor dynamics may underlie velocity integration in the dorsolateral medial entorhinal cortex. The simulations also generate pertinent upper bounds on the accuracy of integration that may be achieved by continuous attractor dynamics in the grid cell network. We suggest experiments to test the continuous attractor model and differentiate it from models in which single cells establish their responses independently of each other.

  7. Building accurate historic and future climate MEPDG input files for Louisiana DOTD.

    DOT National Transportation Integrated Search

    2017-02-01

    The pavement design process (originally MEPDG, then DARWin-ME, and now Pavement ME Design) requires a multi-year set of hourly : climate input data that influence pavement material properties. In Louisiana, the software provides nine locations with c...

  8. 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.

  9. Accurate Cold-Test Model of Helical TWT Slow-Wave Circuits

    NASA Technical Reports Server (NTRS)

    Kory, Carol L.; Dayton, James A., Jr.

    1997-01-01

    Recently, a method has been established to accurately calculate cold-test data for helical slow-wave structures using the three-dimensional electromagnetic computer code, MAFIA. Cold-test parameters have been calculated for several helical traveling-wave tube (TWT) slow-wave circuits possessing various support rod configurations, and results are presented here showing excellent agreement with experiment. The helical models include tape thickness, dielectric support shapes and material properties consistent with the actual circuits. The cold-test data from this helical model can be used as input into large-signal helical TWT interaction codes making it possible, for the first time, to design a complete TWT via computer simulation.

  10. Factors Affecting the Item Parameter Estimation and Classification Accuracy of the DINA Model

    ERIC Educational Resources Information Center

    de la Torre, Jimmy; Hong, Yuan; Deng, Weiling

    2010-01-01

    To better understand the statistical properties of the deterministic inputs, noisy "and" gate cognitive diagnosis (DINA) model, the impact of several factors on the quality of the item parameter estimates and classification accuracy was investigated. Results of the simulation study indicate that the fully Bayes approach is most accurate when the…

  11. Low-dimensional, morphologically accurate models of subthreshold membrane potential

    PubMed Central

    Kellems, Anthony R.; Roos, Derrick; Xiao, Nan; Cox, Steven J.

    2009-01-01

    The accurate simulation of a neuron’s ability to integrate distributed synaptic input typically requires the simultaneous solution of tens of thousands of ordinary differential equations. For, in order to understand how a cell distinguishes between input patterns we apparently need a model that is biophysically accurate down to the space scale of a single spine, i.e., 1 μm. We argue here that one can retain this highly detailed input structure while dramatically reducing the overall system dimension if one is content to accurately reproduce the associated membrane potential at a small number of places, e.g., at the site of action potential initiation, under subthreshold stimulation. The latter hypothesis permits us to approximate the active cell model with an associated quasi-active model, which in turn we reduce by both time-domain (Balanced Truncation) and frequency-domain (ℋ2 approximation of the transfer function) methods. We apply and contrast these methods on a suite of typical cells, achieving up to four orders of magnitude in dimension reduction and an associated speed-up in the simulation of dendritic democratization and resonance. We also append a threshold mechanism and indicate that this reduction has the potential to deliver an accurate quasi-integrate and fire model. PMID:19172386

  12. A Simple and Accurate Rate-Driven Infiltration Model

    NASA Astrophysics Data System (ADS)

    Cui, G.; Zhu, J.

    2017-12-01

    In this study, we develop a novel Rate-Driven Infiltration Model (RDIMOD) for simulating infiltration into soils. Unlike traditional methods, RDIMOD avoids numerically solving the highly non-linear Richards equation or simply modeling with empirical parameters. RDIMOD employs infiltration rate as model input to simulate one-dimensional infiltration process by solving an ordinary differential equation. The model can simulate the evolutions of wetting front, infiltration rate, and cumulative infiltration on any surface slope including vertical and horizontal directions. Comparing to the results from the Richards equation for both vertical infiltration and horizontal infiltration, RDIMOD simply and accurately predicts infiltration processes for any type of soils and soil hydraulic models without numerical difficulty. Taking into account the accuracy, capability, and computational effectiveness and stability, RDIMOD can be used in large-scale hydrologic and land-atmosphere modeling.

  13. 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

    physical parameters inputs affecting transfer of heat, momentum and soil moisture in land-surface process in MM5. Using base the accurate input datasets, we are able to have improved see the differences of predictions of ground temperatures, winds and even thunderstorm activities within boundary layer.

  14. 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.

  15. 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.

  16. Toward an inventory of nitrogen input to the United States

    EPA Science Inventory

    Accurate accounting of nitrogen inputs is increasingly necessary for policy decisions related to aquatic nutrient pollution. Here we synthesize available data to provide the first integrated estimates of the amount and uncertainty of nitrogen inputs to the United States. Abou...

  17. Evaluation of Piloted Inputs for Onboard Frequency Response Estimation

    NASA Technical Reports Server (NTRS)

    Grauer, Jared A.; Martos, Borja

    2013-01-01

    Frequency response estimation results are presented using piloted inputs and a real-time estimation method recently developed for multisine inputs. A nonlinear simulation of the F-16 and a Piper Saratoga research aircraft were subjected to different piloted test inputs while the short period stabilator/elevator to pitch rate frequency response was estimated. Results show that the method can produce accurate results using wide-band piloted inputs instead of multisines. A new metric is introduced for evaluating which data points to include in the analysis and recommendations are provided for applying this method with piloted inputs.

  18. 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.

  19. 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

  20. 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.

  1. 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

  2. Evaluating the sensitivity of agricultural model performance to different climate inputs

    PubMed Central

    Glotter, Michael J.; Moyer, Elisabeth J.; Ruane, Alex C.; Elliott, Joshua W.

    2017-01-01

    Projections of future food production necessarily rely on models, which must themselves be validated through historical assessments comparing modeled to observed yields. Reliable historical validation requires both accurate agricultural models and accurate climate inputs. Problems with either may compromise the validation exercise. Previous studies have compared the effects of different climate inputs on agricultural projections, but either incompletely or without a ground truth of observed yields that would allow distinguishing errors due to climate inputs from those intrinsic to the crop model. This study is a systematic evaluation of the reliability of a widely-used crop model for simulating U.S. maize yields when driven by multiple observational data products. The parallelized Decision Support System for Agrotechnology Transfer (pDSSAT) is driven with climate inputs from multiple sources – reanalysis, reanalysis bias-corrected with observed climate, and a control dataset – and compared to observed historical yields. The simulations show that model output is more accurate when driven by any observation-based precipitation product than when driven by un-bias-corrected reanalysis. The simulations also suggest, in contrast to previous studies, that biased precipitation distribution is significant for yields only in arid regions. However, some issues persist for all choices of climate inputs: crop yields appear oversensitive to precipitation fluctuations but undersensitive to floods and heat waves. These results suggest that the most important issue for agricultural projections may be not climate inputs but structural limitations in the crop models themselves. PMID:29097985

  3. A Weibull statistics-based lignocellulose saccharification model and a built-in parameter accurately predict lignocellulose hydrolysis performance.

    PubMed

    Wang, Mingyu; Han, Lijuan; Liu, Shasha; Zhao, Xuebing; Yang, Jinghua; Loh, Soh Kheang; Sun, Xiaomin; Zhang, Chenxi; Fang, Xu

    2015-09-01

    Renewable energy from lignocellulosic biomass has been deemed an alternative to depleting fossil fuels. In order to improve this technology, we aim to develop robust mathematical models for the enzymatic lignocellulose degradation process. By analyzing 96 groups of previously published and newly obtained lignocellulose saccharification results and fitting them to Weibull distribution, we discovered Weibull statistics can accurately predict lignocellulose saccharification data, regardless of the type of substrates, enzymes and saccharification conditions. A mathematical model for enzymatic lignocellulose degradation was subsequently constructed based on Weibull statistics. Further analysis of the mathematical structure of the model and experimental saccharification data showed the significance of the two parameters in this model. In particular, the λ value, defined the characteristic time, represents the overall performance of the saccharification system. This suggestion was further supported by statistical analysis of experimental saccharification data and analysis of the glucose production levels when λ and n values change. In conclusion, the constructed Weibull statistics-based model can accurately predict lignocellulose hydrolysis behavior and we can use the λ parameter to assess the overall performance of enzymatic lignocellulose degradation. Advantages and potential applications of the model and the λ value in saccharification performance assessment were discussed. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  4. Optimization of tissue physical parameters for accurate temperature estimation from finite-element simulation of radiofrequency ablation.

    PubMed

    Subramanian, Swetha; Mast, T Douglas

    2015-10-07

    Computational finite element models are commonly used for the simulation of radiofrequency ablation (RFA) treatments. However, the accuracy of these simulations is limited by the lack of precise knowledge of tissue parameters. In this technical note, an inverse solver based on the unscented Kalman filter (UKF) is proposed to optimize values for specific heat, thermal conductivity, and electrical conductivity resulting in accurately simulated temperature elevations. A total of 15 RFA treatments were performed on ex vivo bovine liver tissue. For each RFA treatment, 15 finite-element simulations were performed using a set of deterministically chosen tissue parameters to estimate the mean and variance of the resulting tissue ablation. The UKF was implemented as an inverse solver to recover the specific heat, thermal conductivity, and electrical conductivity corresponding to the measured area of the ablated tissue region, as determined from gross tissue histology. These tissue parameters were then employed in the finite element model to simulate the position- and time-dependent tissue temperature. Results show good agreement between simulated and measured temperature.

  5. 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

  6. 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.

  7. Field measurement of moisture-buffering model inputs for residential buildings

    DOE PAGES

    Woods, Jason; Winkler, Jon

    2016-02-05

    Moisture adsorption and desorption in building materials impact indoor humidity. This effect should be included in building-energy simulations, particularly when humidity is being investigated or controlled. Several models can calculate this moisture-buffering effect, but accurate ones require model inputs that are not always known to the user of the building-energy simulation. This research developed an empirical method to extract whole-house model inputs for the effective moisture penetration depth (EMPD) model. The experimental approach was to subject the materials in the house to a square-wave relative-humidity profile, measure all of the moisture-transfer terms (e.g., infiltration, air-conditioner condensate), and calculate the onlymore » unmeasured term—the moisture sorption into the materials. We validated this method with laboratory measurements, which we used to measure the EMPD model inputs of two houses. After deriving these inputs, we measured the humidity of the same houses during tests with realistic latent and sensible loads and demonstrated the accuracy of this approach. Furthermore, these results show that the EMPD model, when given reasonable inputs, is an accurate moisture-buffering model.« less

  8. 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

  9. Input-output analysis and the hospital budgeting process.

    PubMed Central

    Cleverly, W O

    1975-01-01

    Two hospitals budget systems, a conventional budget and an input-output budget, are compared to determine how they affect management decisions in pricing, output, planning, and cost control. Analysis of data from a 210-bed not-for-profit hospital indicates that adoption of the input-output budget could cause substantial changes in posted hospital rates in individual departments but probably would have no impact on hospital output determination. The input-output approach promises to be a more accurate system for cost control and planning because, unlike the conventional approach, it generates objective signals for investigating variances of expenses from budgeted levels. PMID:1205865

  10. 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

  11. 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.

  12. 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.

  13. 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.

  14. Modeling the impact of common noise inputs on the network activity of retinal ganglion cells

    PubMed Central

    Ahmadian, Yashar; Shlens, Jonathon; Pillow, Jonathan W.; Kulkarni, Jayant; Litke, Alan M.; Chichilnisky, E. J.; Simoncelli, Eero; Paninski, Liam

    2013-01-01

    Synchronized spontaneous firing among retinal ganglion cells (RGCs), on timescales faster than visual responses, has been reported in many studies. Two candidate mechanisms of synchronized firing include direct coupling and shared noisy inputs. In neighboring parasol cells of primate retina, which exhibit rapid synchronized firing that has been studied extensively, recent experimental work indicates that direct electrical or synaptic coupling is weak, but shared synaptic input in the absence of modulated stimuli is strong. However, previous modeling efforts have not accounted for this aspect of firing in the parasol cell population. Here we develop a new model that incorporates the effects of common noise, and apply it to analyze the light responses and synchronized firing of a large, densely-sampled network of over 250 simultaneously recorded parasol cells. We use a generalized linear model in which the spike rate in each cell is determined by the linear combination of the spatio-temporally filtered visual input, the temporally filtered prior spikes of that cell, and unobserved sources representing common noise. The model accurately captures the statistical structure of the spike trains and the encoding of the visual stimulus, without the direct coupling assumption present in previous modeling work. Finally, we examined the problem of decoding the visual stimulus from the spike train given the estimated parameters. The common-noise model produces Bayesian decoding performance as accurate as that of a model with direct coupling, but with significantly more robustness to spike timing perturbations. PMID:22203465

  15. Laser diode absorption spectroscopy for accurate CO(2) line parameters at 2 microm: consequences for space-based DIAL measurements and potential biases.

    PubMed

    Joly, Lilian; Marnas, Fabien; Gibert, Fabien; Bruneau, Didier; Grouiez, Bruno; Flamant, Pierre H; Durry, Georges; Dumelie, Nicolas; Parvitte, Bertrand; Zéninari, Virginie

    2009-10-10

    Space-based active sensing of CO(2) concentration is a very promising technique for the derivation of CO(2) surface fluxes. There is a need for accurate spectroscopic parameters to enable accurate space-based measurements to address global climatic issues. New spectroscopic measurements using laser diode absorption spectroscopy are presented for the preselected R30 CO(2) absorption line ((20(0)1)(III)<--(000) band) and four others. The line strength, air-broadening halfwidth, and its temperature dependence have been investigated. The results exhibit significant improvement for the R30 CO(2) absorption line: 0.4% on the line strength, 0.15% on the air-broadening coefficient, and 0.45% on its temperature dependence. Analysis of potential biases of space-based DIAL CO(2) mixing ratio measurements associated to spectroscopic parameter uncertainties are presented.

  16. 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.

  17. Cerebellar input configuration toward object model abstraction in manipulation tasks.

    PubMed

    Luque, Niceto R; Garrido, Jesus A; Carrillo, Richard R; Coenen, Olivier J-M D; Ros, Eduardo

    2011-08-01

    It is widely assumed that the cerebellum is one of the main nervous centers involved in correcting and refining planned movement and accounting for disturbances occurring during movement, for instance, due to the manipulation of objects which affect the kinematics and dynamics of the robot-arm plant model. In this brief, we evaluate a way in which a cerebellar-like structure can store a model in the granular and molecular layers. Furthermore, we study how its microstructure and input representations (context labels and sensorimotor signals) can efficiently support model abstraction toward delivering accurate corrective torque values for increasing precision during different-object manipulation. We also describe how the explicit (object-related input labels) and implicit state input representations (sensorimotor signals) complement each other to better handle different models and allow interpolation between two already stored models. This facilitates accurate corrections during manipulations of new objects taking advantage of already stored models.

  18. 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.

  19. 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.

  20. Adaptive optimal input design and parametric estimation of nonlinear dynamical systems: application to neuronal modeling.

    PubMed

    Madi, Mahmoud K; Karameh, Fadi N

    2018-05-11

    Many physical models of biological processes including neural systems are characterized by parametric nonlinear dynamical relations between driving inputs, internal states, and measured outputs of the process. Fitting such models using experimental data (data assimilation) is a challenging task since the physical process often operates in a noisy, possibly non-stationary environment; moreover, conducting multiple experiments under controlled and repeatable conditions can be impractical, time consuming or costly. The accuracy of model identification, therefore, is dictated principally by the quality and dynamic richness of collected data over single or few experimental sessions. Accordingly, it is highly desirable to design efficient experiments that, by exciting the physical process with smart inputs, yields fast convergence and increased accuracy of the model. We herein introduce an adaptive framework in which optimal input design is integrated with Square root Cubature Kalman Filters (OID-SCKF) to develop an online estimation procedure that first, converges significantly quicker, thereby permitting model fitting over shorter time windows, and second, enhances model accuracy when only few process outputs are accessible. The methodology is demonstrated on common nonlinear models and on a four-area neural mass model with noisy and limited measurements. Estimation quality (speed and accuracy) is benchmarked against high-performance SCKF-based methods that commonly employ dynamically rich informed inputs for accurate model identification. For all the tested models, simulated single-trial and ensemble averages showed that OID-SCKF exhibited (i) faster convergence of parameter estimates and (ii) lower dependence on inter-trial noise variability with gains up to around 1000 msec in speed and 81% increase in variability for the neural mass models. In terms of accuracy, OID-SCKF estimation was superior, and exhibited considerably less variability across experiments, in

  1. 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.

  2. 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

  3. 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

  4. Calculating the mounting parameters for Taylor Spatial Frame correction using computed tomography.

    PubMed

    Kucukkaya, Metin; Karakoyun, Ozgur; Armagan, Raffi; Kuzgun, Unal

    2011-07-01

    The Taylor Spatial Frame uses a computer program-based six-axis deformity analysis. However, there is often a residual deformity after the initial correction, especially in deformities with a rotational component. This problem can be resolved by recalculating the parameters and inputting all new deformity and mounting parameters. However, this may necessitate repeated x-rays and delay treatment. We believe that error in the mounting parameters is the main reason for most residual deformities. To prevent these problems, we describe a new calculation technique for determining the mounting parameters that uses computed tomography. This technique is especially advantageous for deformities with a rotational component. Using this technique, exact calculation of the mounting parameters is possible and the residual deformity and number of repeated x-rays can be minimized. This new technique is an alternative method to accurately calculating the mounting parameters.

  5. Evaluating the Sensitivity of Agricultural Model Performance to Different Climate Inputs: Supplemental Material

    NASA Technical Reports Server (NTRS)

    Glotter, Michael J.; Ruane, Alex C.; Moyer, Elisabeth J.; Elliott, Joshua W.

    2015-01-01

    Projections of future food production necessarily rely on models, which must themselves be validated through historical assessments comparing modeled and observed yields. Reliable historical validation requires both accurate agricultural models and accurate climate inputs. Problems with either may compromise the validation exercise. Previous studies have compared the effects of different climate inputs on agricultural projections but either incompletely or without a ground truth of observed yields that would allow distinguishing errors due to climate inputs from those intrinsic to the crop model. This study is a systematic evaluation of the reliability of a widely used crop model for simulating U.S. maize yields when driven by multiple observational data products. The parallelized Decision Support System for Agrotechnology Transfer (pDSSAT) is driven with climate inputs from multiple sources reanalysis, reanalysis that is bias corrected with observed climate, and a control dataset and compared with observed historical yields. The simulations show that model output is more accurate when driven by any observation-based precipitation product than when driven by non-bias-corrected reanalysis. The simulations also suggest, in contrast to previous studies, that biased precipitation distribution is significant for yields only in arid regions. Some issues persist for all choices of climate inputs: crop yields appear to be oversensitive to precipitation fluctuations but under sensitive to floods and heat waves. These results suggest that the most important issue for agricultural projections may be not climate inputs but structural limitations in the crop models themselves.

  6. Petermann I and II spot size: Accurate semi analytical description involving Nelder-Mead method of nonlinear unconstrained optimization and three parameter fundamental modal field

    NASA Astrophysics Data System (ADS)

    Roy Choudhury, Raja; Roy Choudhury, Arundhati; Kanti Ghose, Mrinal

    2013-01-01

    A semi-analytical model with three optimizing parameters and a novel non-Gaussian function as the fundamental modal field solution has been proposed to arrive at an accurate solution to predict various propagation parameters of graded-index fibers with less computational burden than numerical methods. In our semi analytical formulation the optimization of core parameter U which is usually uncertain, noisy or even discontinuous, is being calculated by Nelder-Mead method of nonlinear unconstrained minimizations as it is an efficient and compact direct search method and does not need any derivative information. Three optimizing parameters are included in the formulation of fundamental modal field of an optical fiber to make it more flexible and accurate than other available approximations. Employing variational technique, Petermann I and II spot sizes have been evaluated for triangular and trapezoidal-index fibers with the proposed fundamental modal field. It has been demonstrated that, the results of the proposed solution identically match with the numerical results over a wide range of normalized frequencies. This approximation can also be used in the study of doped and nonlinear fiber amplifier.

  7. The metallicity of M4: Accurate spectroscopic fundamental parameters for four giants

    NASA Technical Reports Server (NTRS)

    Drake, J. J.; Smith, V. V.; Suntzeff, N. B.

    1994-01-01

    High-quality spectra, covering the wavelength range 5480 to 7080 A, have been obtained for four giant stars in the intermediate-metallicity CN-bimodal globular cluster M4 (NGC 6121). We have employed a model atmosphere analysis that is entirely independent from cluster parameters, such as distance, age, and reddening, in order to derive accurate values for the stellar parameters effective temperature, surface gravity, and microturbulence, and for the abundance of iron relative to the Sun, (Fe/H), and of calcium, Ca/H, for each of the four stars. Detailed radiative transfer and statistical equilibrium calculations carried out for iron and calcium suggest that departures from local thermodynamic equilibrium are not significant for the purposes of our analysis. The spectroscopically derived effective temperatures for our program stars are hotter by about 200 K than existing photometric calibrations suggest. We conclude that this is due partly to the uncertain reddening of M4 and to the existing photometric temperature calibration for red giants being too cool by about 100 K. Comparison of our spectroscopic and existing photometric temperatures supports the prognosis of a significant east-west gradient in the reddening across M4. Our derived iron abundances are slightly higher than previous high-resolution studies suggested; the differences are most probably due to the different temperature scale and choice of microturbulent velocities adopted by earlier workers. The resulting value for the metallicity of M4 is (Fe/H )(sub M4) = -1.05 + or - 0.15. Based on this result, we suggest that metallicities derived in previous high-dispersion globular cluster abundance analyses could be too low by 0.2 to 0.3 dex. Our calcium abundances suggest an enhancement of calcium, an alpha element, over iron, relative to the Sun, in M4 of (Ca/H) = 0.23.

  8. 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.

  9. Capturing Revolute Motion and Revolute Joint Parameters with Optical Tracking

    NASA Astrophysics Data System (ADS)

    Antonya, C.

    2017-12-01

    Optical tracking of users and various technical systems are becoming more and more popular. It consists of analysing sequence of recorded images using video capturing devices and image processing algorithms. The returned data contains mainly point-clouds, coordinates of markers or coordinates of point of interest. These data can be used for retrieving information related to the geometry of the objects, but also to extract parameters for the analytical model of the system useful in a variety of computer aided engineering simulations. The parameter identification of joints deals with extraction of physical parameters (mainly geometric parameters) for the purpose of constructing accurate kinematic and dynamic models. The input data are the time-series of the marker’s position. The least square method was used for fitting the data into different geometrical shapes (ellipse, circle, plane) and for obtaining the position and orientation of revolute joins.

  10. 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

  11. 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.

  12. 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.

  13. Subsonic flight test evaluation of a propulsion system parameter estimation process for the F100 engine

    NASA Technical Reports Server (NTRS)

    Orme, John S.; Gilyard, Glenn B.

    1992-01-01

    Integrated engine-airframe optimal control technology may significantly improve aircraft performance. This technology requires a reliable and accurate parameter estimator to predict unmeasured variables. To develop this technology base, NASA Dryden Flight Research Facility (Edwards, CA), McDonnell Aircraft Company (St. Louis, MO), and Pratt & Whitney (West Palm Beach, FL) have developed and flight-tested an adaptive performance seeking control system which optimizes the quasi-steady-state performance of the F-15 propulsion system. This paper presents flight and ground test evaluations of the propulsion system parameter estimation process used by the performance seeking control system. The estimator consists of a compact propulsion system model and an extended Kalman filter. The extended Laman filter estimates five engine component deviation parameters from measured inputs. The compact model uses measurements and Kalman-filter estimates as inputs to predict unmeasured propulsion parameters such as net propulsive force and fan stall margin. The ability to track trends and estimate absolute values of propulsion system parameters was demonstrated. For example, thrust stand results show a good correlation, especially in trends, between the performance seeking control estimated and measured thrust.

  14. 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.

  15. 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

  16. 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.

  17. 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

  18. Intraocular lens power estimation by accurate ray tracing for eyes underwent previous refractive surgeries

    NASA Astrophysics Data System (ADS)

    Yang, Que; Wang, Shanshan; Wang, Kai; Zhang, Chunyu; Zhang, Lu; Meng, Qingyu; Zhu, Qiudong

    2015-08-01

    For normal eyes without history of any ocular surgery, traditional equations for calculating intraocular lens (IOL) power, such as SRK-T, Holladay, Higis, SRK-II, et al., all were relativley accurate. However, for eyes underwent refractive surgeries, such as LASIK, or eyes diagnosed as keratoconus, these equations may cause significant postoperative refractive error, which may cause poor satisfaction after cataract surgery. Although some methods have been carried out to solve this problem, such as Hagis-L equation[1], or using preoperative data (data before LASIK) to estimate K value[2], no precise equations were available for these eyes. Here, we introduced a novel intraocular lens power estimation method by accurate ray tracing with optical design software ZEMAX. Instead of using traditional regression formula, we adopted the exact measured corneal elevation distribution, central corneal thickness, anterior chamber depth, axial length, and estimated effective lens plane as the input parameters. The calculation of intraocular lens power for a patient with keratoconus and another LASIK postoperative patient met very well with their visual capacity after cataract surgery.

  19. Using input feature information to improve ultraviolet retrieval in neural networks

    NASA Astrophysics Data System (ADS)

    Sun, Zhibin; Chang, Ni-Bin; Gao, Wei; Chen, Maosi; Zempila, Melina

    2017-09-01

    In neural networks, the training/predicting accuracy and algorithm efficiency can be improved significantly via accurate input feature extraction. In this study, some spatial features of several important factors in retrieving surface ultraviolet (UV) are extracted. An extreme learning machine (ELM) is used to retrieve the surface UV of 2014 in the continental United States, using the extracted features. The results conclude that more input weights can improve the learning capacities of neural networks.

  20. 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

  1. Anisotropic Effects on Constitutive Model Parameters of Aluminum Alloys

    DTIC Science & Technology

    2012-01-01

    constants are required input to computer codes (LS-DYNA, DYNA3D or SPH ) to accurately simulate fragment impact on structural components made of high...different temperatures. These model constants are required input to computer codes (LS-DYNA, DYNA3D or SPH ) to accurately simulate fragment impact on...ADDRESS(ES) Naval Surface Warfare Center,4104Evans Way Suite 102,Indian Head,MD,20640 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING/MONITORING

  2. Parameter Extraction Method for the Electrical Model of a Silicon Photomultiplier

    NASA Astrophysics Data System (ADS)

    Licciulli, Francesco; Marzocca, Cristoforo

    2016-10-01

    The availability of an effective electrical model, able to accurately reproduce the signals generated by a Silicon Photo-Multiplier coupled to the front-end electronics, is mandatory when the performance of a detection system based on this kind of detector has to be evaluated by means of reliable simulations. We propose a complete extraction procedure able to provide the whole set of the parameters involved in a well-known model of the detector, which includes the substrate ohmic resistance. The technique allows achieving very good quality of the fit between simulation results provided by the model and experimental data, thanks to accurate discrimination between the quenching and substrate resistances, which results in a realistic set of extracted parameters. The extraction procedure has been applied to a commercial device considering a wide range of different conditions in terms of input resistance of the front-end electronics and interconnection parasitics. In all the considered situations, very good correspondence has been found between simulations and measurements, especially for what concerns the leading edge of the current pulses generated by the detector, which strongly affects the timing performance of the detection system, thus confirming the effectiveness of the model and the associated parameter extraction technique.

  3. Proton dissociation properties of arylphosphonates: Determination of accurate Hammett equation parameters.

    PubMed

    Dargó, Gergő; Bölcskei, Adrienn; Grün, Alajos; Béni, Szabolcs; Szántó, Zoltán; Lopata, Antal; Keglevich, György; Balogh, György T

    2017-09-05

    Determination of the proton dissociation constants of several arylphosphonic acid derivatives was carried out to investigate the accuracy of the Hammett equations available for this family of compounds. For the measurement of the pK a values modern, accurate methods, such as the differential potentiometric titration and NMR-pH titration were used. We found our results significantly different from the pK a values reported before (pK a1 : MAE = 0.16 pK a2 : MAE=0.59). Based on our recently measured pK a values, refined Hammett equations were determined that might be used for predicting highly accurate ionization constants of newly synthesized compounds (pK a1 =1.70-0.894σ, pK a2 =6.92-0.934σ). Copyright © 2017 Elsevier B.V. All rights reserved.

  4. High Frequency QRS ECG Accurately Detects Cardiomyopathy

    NASA Technical Reports Server (NTRS)

    Schlegel, Todd T.; Arenare, Brian; Poulin, Gregory; Moser, Daniel R.; Delgado, Reynolds

    2005-01-01

    High frequency (HF, 150-250 Hz) analysis over the entire QRS interval of the ECG is more sensitive than conventional ECG for detecting myocardial ischemia. However, the accuracy of HF QRS ECG for detecting cardiomyopathy is unknown. We obtained simultaneous resting conventional and HF QRS 12-lead ECGs in 66 patients with cardiomyopathy (EF = 23.2 plus or minus 6.l%, mean plus or minus SD) and in 66 age- and gender-matched healthy controls using PC-based ECG software recently developed at NASA. The single most accurate ECG parameter for detecting cardiomyopathy was an HF QRS morphological score that takes into consideration the total number and severity of reduced amplitude zones (RAZs) present plus the clustering of RAZs together in contiguous leads. This RAZ score had an area under the receiver operator curve (ROC) of 0.91, and was 88% sensitive, 82% specific and 85% accurate for identifying cardiomyopathy at optimum score cut-off of 140 points. Although conventional ECG parameters such as the QRS and QTc intervals were also significantly longer in patients than controls (P less than 0.001, BBBs excluded), these conventional parameters were less accurate (area under the ROC = 0.77 and 0.77, respectively) than HF QRS morphological parameters for identifying underlying cardiomyopathy. The total amplitude of the HF QRS complexes, as measured by summed root mean square voltages (RMSVs), also differed between patients and controls (33.8 plus or minus 11.5 vs. 41.5 plus or minus 13.6 mV, respectively, P less than 0.003), but this parameter was even less accurate in distinguishing the two groups (area under ROC = 0.67) than the HF QRS morphologic and conventional ECG parameters. Diagnostic accuracy was optimal (86%) when the RAZ score from the HF QRS ECG and the QTc interval from the conventional ECG were used simultaneously with cut-offs of greater than or equal to 40 points and greater than or equal to 445 ms, respectively. In conclusion 12-lead HF QRS ECG employing

  5. 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.

  6. SATe-II: very fast and accurate simultaneous estimation of multiple sequence alignments and phylogenetic trees.

    PubMed

    Liu, Kevin; Warnow, Tandy J; Holder, Mark T; Nelesen, Serita M; Yu, Jiaye; Stamatakis, Alexandros P; Linder, C Randal

    2012-01-01

    Highly accurate estimation of phylogenetic trees for large data sets is difficult, in part because multiple sequence alignments must be accurate for phylogeny estimation methods to be accurate. Coestimation of alignments and trees has been attempted but currently only SATé estimates reasonably accurate trees and alignments for large data sets in practical time frames (Liu K., Raghavan S., Nelesen S., Linder C.R., Warnow T. 2009b. Rapid and accurate large-scale coestimation of sequence alignments and phylogenetic trees. Science. 324:1561-1564). Here, we present a modification to the original SATé algorithm that improves upon SATé (which we now call SATé-I) in terms of speed and of phylogenetic and alignment accuracy. SATé-II uses a different divide-and-conquer strategy than SATé-I and so produces smaller more closely related subsets than SATé-I; as a result, SATé-II produces more accurate alignments and trees, can analyze larger data sets, and runs more efficiently than SATé-I. Generally, SATé is a metamethod that takes an existing multiple sequence alignment method as an input parameter and boosts the quality of that alignment method. SATé-II-boosted alignment methods are significantly more accurate than their unboosted versions, and trees based upon these improved alignments are more accurate than trees based upon the original alignments. Because SATé-I used maximum likelihood (ML) methods that treat gaps as missing data to estimate trees and because we found a correlation between the quality of tree/alignment pairs and ML scores, we explored the degree to which SATé's performance depends on using ML with gaps treated as missing data to determine the best tree/alignment pair. We present two lines of evidence that using ML with gaps treated as missing data to optimize the alignment and tree produces very poor results. First, we show that the optimization problem where a set of unaligned DNA sequences is given and the output is the tree and alignment of

  7. Investigation of dynamic SPECT measurements of the arterial input function in human subjects using simulation, phantom and human studies

    NASA Astrophysics Data System (ADS)

    Winant, Celeste D.; Aparici, Carina Mari; Zelnik, Yuval R.; Reutter, Bryan W.; Sitek, Arkadiusz; Bacharach, Stephen L.; Gullberg, Grant T.

    2012-01-01

    Computer simulations, a phantom study and a human study were performed to determine whether a slowly rotating single-photon computed emission tomography (SPECT) system could provide accurate arterial input functions for quantification of myocardial perfusion imaging using kinetic models. The errors induced by data inconsistency associated with imaging with slow camera rotation during tracer injection were evaluated with an approach called SPECT/P (dynamic SPECT from positron emission tomography (PET)) and SPECT/D (dynamic SPECT from database of SPECT phantom projections). SPECT/P simulated SPECT-like dynamic projections using reprojections of reconstructed dynamic 94Tc-methoxyisobutylisonitrile (94Tc-MIBI) PET images acquired in three human subjects (1 min infusion). This approach was used to evaluate the accuracy of estimating myocardial wash-in rate parameters K1 for rotation speeds providing 180° of projection data every 27 or 54 s. Blood input and myocardium tissue time-activity curves (TACs) were estimated using spatiotemporal splines. These were fit to a one-compartment perfusion model to obtain wash-in rate parameters K1. For the second method (SPECT/D), an anthropomorphic cardiac torso phantom was used to create real SPECT dynamic projection data of a tracer distribution derived from 94Tc-MIBI PET scans in the blood pool, myocardium, liver and background. This method introduced attenuation, collimation and scatter into the modeling of dynamic SPECT projections. Both approaches were used to evaluate the accuracy of estimating myocardial wash-in parameters for rotation speeds providing 180° of projection data every 27 and 54 s. Dynamic cardiac SPECT was also performed in a human subject at rest using a hybrid SPECT/CT scanner. Dynamic measurements of 99mTc-tetrofosmin in the myocardium were obtained using an infusion time of 2 min. Blood input, myocardium tissue and liver TACs were estimated using the same spatiotemporal splines. The spatiotemporal maximum

  8. Using Whole-House Field Tests to Empirically Derive Moisture Buffering Model Inputs

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

    Woods, J.; Winkler, J.; Christensen, D.

    2014-08-01

    Building energy simulations can be used to predict a building's interior conditions, along with the energy use associated with keeping these conditions comfortable. These models simulate the loads on the building (e.g., internal gains, envelope heat transfer), determine the operation of the space conditioning equipment, and then calculate the building's temperature and humidity throughout the year. The indoor temperature and humidity are affected not only by the loads and the space conditioning equipment, but also by the capacitance of the building materials, which buffer changes in temperature and humidity. This research developed an empirical method to extract whole-house model inputsmore » for use with a more accurate moisture capacitance model (the effective moisture penetration depth model). The experimental approach was to subject the materials in the house to a square-wave relative humidity profile, measure all of the moisture transfer terms (e.g., infiltration, air conditioner condensate) and calculate the only unmeasured term: the moisture absorption into the materials. After validating the method with laboratory measurements, we performed the tests in a field house. A least-squares fit of an analytical solution to the measured moisture absorption curves was used to determine the three independent model parameters representing the moisture buffering potential of this house and its furnishings. Follow on tests with realistic latent and sensible loads showed good agreement with the derived parameters, especially compared to the commonly-used effective capacitance approach. These results show that the EMPD model, once the inputs are known, is an accurate moisture buffering model.« less

  9. 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.

  10. 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

  11. 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.

  12. 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

  13. 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

  14. An improved method to estimate reflectance parameters for high dynamic range imaging

    NASA Astrophysics Data System (ADS)

    Li, Shiying; Deguchi, Koichiro; Li, Renfa; Manabe, Yoshitsugu; Chihara, Kunihiro

    2008-01-01

    Two methods are described to accurately estimate diffuse and specular reflectance parameters for colors, gloss intensity and surface roughness, over the dynamic range of the camera used to capture input images. Neither method needs to segment color areas on an image, or to reconstruct a high dynamic range (HDR) image. The second method improves on the first, bypassing the requirement for specific separation of diffuse and specular reflection components. For the latter method, diffuse and specular reflectance parameters are estimated separately, using the least squares method. Reflection values are initially assumed to be diffuse-only reflection components, and are subjected to the least squares method to estimate diffuse reflectance parameters. Specular reflection components, obtained by subtracting the computed diffuse reflection components from reflection values, are then subjected to a logarithmically transformed equation of the Torrance-Sparrow reflection model, and specular reflectance parameters for gloss intensity and surface roughness are finally estimated using the least squares method. Experiments were carried out using both methods, with simulation data at different saturation levels, generated according to the Lambert and Torrance-Sparrow reflection models, and the second method, with spectral images captured by an imaging spectrograph and a moving light source. Our results show that the second method can estimate the diffuse and specular reflectance parameters for colors, gloss intensity and surface roughness more accurately and faster than the first one, so that colors and gloss can be reproduced more efficiently for HDR imaging.

  15. 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

  16. 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

  17. 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.

  18. Significance of accurate diffraction corrections for the second harmonic wave in determining the acoustic nonlinearity parameter

    NASA Astrophysics Data System (ADS)

    Jeong, Hyunjo; Zhang, Shuzeng; Barnard, Dan; Li, Xiongbing

    2015-09-01

    The accurate measurement of acoustic nonlinearity parameter β for fluids or solids generally requires making corrections for diffraction effects due to finite size geometry of transmitter and receiver. These effects are well known in linear acoustics, while those for second harmonic waves have not been well addressed and therefore not properly considered in previous studies. In this work, we explicitly define the attenuation and diffraction corrections using the multi-Gaussian beam (MGB) equations which were developed from the quasilinear solutions of the KZK equation. The effects of making these corrections are examined through the simulation of β determination in water. Diffraction corrections are found to have more significant effects than attenuation corrections, and the β values of water can be estimated experimentally with less than 5% errors when the exact second harmonic diffraction corrections are used together with the negligible attenuation correction effects on the basis of linear frequency dependence between attenuation coefficients, α2 ≃ 2α1.

  19. 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.

  20. Vision drives accurate approach behavior during prey capture in laboratory mice

    PubMed Central

    Hoy, Jennifer L.; Yavorska, Iryna; Wehr, Michael; Niell, Cristopher M.

    2016-01-01

    Summary The ability to genetically identify and manipulate neural circuits in the mouse is rapidly advancing our understanding of visual processing in the mammalian brain [1,2]. However, studies investigating the circuitry that underlies complex ethologically-relevant visual behaviors in the mouse have been primarily restricted to fear responses [3–5]. Here, we show that a laboratory strain of mouse (Mus musculus, C57BL/6J) robustly pursues, captures and consumes live insect prey, and that vision is necessary for mice to perform the accurate orienting and approach behaviors leading to capture. Specifically, we differentially perturbed visual or auditory input in mice and determined that visual input is required for accurate approach, allowing maintenance of bearing to within 11 degrees of the target on average during pursuit. While mice were able to capture prey without vision, the accuracy of their approaches and capture rate dramatically declined. To better explore the contribution of vision to this behavior, we developed a simple assay that isolated visual cues and simplified analysis of the visually guided approach. Together, our results demonstrate that laboratory mice are capable of exhibiting dynamic and accurate visually-guided approach behaviors, and provide a means to estimate the visual features that drive behavior within an ethological context. PMID:27773567

  1. 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.

  2. Directional hearing by linear summation of binaural inputs at the medial superior olive

    PubMed Central

    van der Heijden, Marcel; Lorteije, Jeannette A. M.; Plauška, Andrius; Roberts, Michael T.; Golding, Nace L.; Borst, J. Gerard G.

    2013-01-01

    SUMMARY Neurons in the medial superior olive (MSO) enable sound localization by their remarkable sensitivity to submillisecond interaural time differences (ITDs). Each MSO neuron has its own “best ITD” to which it responds optimally. A difference in physical path length of the excitatory inputs from both ears cannot fully account for the ITD tuning of MSO neurons. As a result, it is still debated how these inputs interact and whether the segregation of inputs to opposite dendrites, well-timed synaptic inhibition, or asymmetries in synaptic potentials or cellular morphology further optimize coincidence detection or ITD tuning. Using in vivo whole-cell and juxtacellular recordings, we show here that ITD tuning of MSO neurons is determined by the timing of their excitatory inputs. The inputs from both ears sum linearly, whereas spike probability depends nonlinearly on the size of synaptic inputs. This simple coincidence detection scheme thus makes accurate sound localization possible. PMID:23764292

  3. Uncertainties in Parameters Estimated with Neural Networks: Application to Strong Gravitational Lensing

    NASA Astrophysics Data System (ADS)

    Perreault Levasseur, Laurence; Hezaveh, Yashar D.; Wechsler, Risa H.

    2017-11-01

    In Hezaveh et al. we showed that deep learning can be used for model parameter estimation and trained convolutional neural networks to determine the parameters of strong gravitational-lensing systems. Here we demonstrate a method for obtaining the uncertainties of these parameters. We review the framework of variational inference to obtain approximate posteriors of Bayesian neural networks and apply it to a network trained to estimate the parameters of the Singular Isothermal Ellipsoid plus external shear and total flux magnification. We show that the method can capture the uncertainties due to different levels of noise in the input data, as well as training and architecture-related errors made by the network. To evaluate the accuracy of the resulting uncertainties, we calculate the coverage probabilities of marginalized distributions for each lensing parameter. By tuning a single variational parameter, the dropout rate, we obtain coverage probabilities approximately equal to the confidence levels for which they were calculated, resulting in accurate and precise uncertainty estimates. Our results suggest that the application of approximate Bayesian neural networks to astrophysical modeling problems can be a fast alternative to Monte Carlo Markov Chains, allowing orders of magnitude improvement in speed.

  4. Image-derived input function with factor analysis and a-priori information.

    PubMed

    Simončič, Urban; Zanotti-Fregonara, Paolo

    2015-02-01

    Quantitative PET studies often require the cumbersome and invasive procedure of arterial cannulation to measure the input function. This study sought to minimize the number of necessary blood samples by developing a factor-analysis-based image-derived input function (IDIF) methodology for dynamic PET brain studies. IDIF estimation was performed as follows: (a) carotid and background regions were segmented manually on an early PET time frame; (b) blood-weighted and tissue-weighted time-activity curves (TACs) were extracted with factor analysis; (c) factor analysis results were denoised and scaled using the voxels with the highest blood signal; (d) using population data and one blood sample at 40 min, whole-blood TAC was estimated from postprocessed factor analysis results; and (e) the parent concentration was finally estimated by correcting the whole-blood curve with measured radiometabolite concentrations. The methodology was tested using data from 10 healthy individuals imaged with [(11)C](R)-rolipram. The accuracy of IDIFs was assessed against full arterial sampling by comparing the area under the curve of the input functions and by calculating the total distribution volume (VT). The shape of the image-derived whole-blood TAC matched the reference arterial curves well, and the whole-blood area under the curves were accurately estimated (mean error 1.0±4.3%). The relative Logan-V(T) error was -4.1±6.4%. Compartmental modeling and spectral analysis gave less accurate V(T) results compared with Logan. A factor-analysis-based IDIF for [(11)C](R)-rolipram brain PET studies that relies on a single blood sample and population data can be used for accurate quantification of Logan-V(T) values.

  5. Input-variable sensitivity assessment for sediment transport relations

    NASA Astrophysics Data System (ADS)

    Fernández, Roberto; Garcia, Marcelo H.

    2017-09-01

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

  6. A linear and non-linear polynomial neural network modeling of dissolved oxygen content in surface water: Inter- and extrapolation performance with inputs' significance analysis.

    PubMed

    Šiljić Tomić, Aleksandra; Antanasijević, Davor; Ristić, Mirjana; Perić-Grujić, Aleksandra; Pocajt, Viktor

    2018-01-01

    Accurate prediction of water quality parameters (WQPs) is an important task in the management of water resources. Artificial neural networks (ANNs) are frequently applied for dissolved oxygen (DO) prediction, but often only their interpolation performance is checked. The aims of this research, beside interpolation, were the determination of extrapolation performance of ANN model, which was developed for the prediction of DO content in the Danube River, and the assessment of relationship between the significance of inputs and prediction error in the presence of values which were of out of the range of training. The applied ANN is a polynomial neural network (PNN) which performs embedded selection of most important inputs during learning, and provides a model in the form of linear and non-linear polynomial functions, which can then be used for a detailed analysis of the significance of inputs. Available dataset that contained 1912 monitoring records for 17 water quality parameters was split into a "regular" subset that contains normally distributed and low variability data, and an "extreme" subset that contains monitoring records with outlier values. The results revealed that the non-linear PNN model has good interpolation performance (R 2 =0.82), but it was not robust in extrapolation (R 2 =0.63). The analysis of extrapolation results has shown that the prediction errors are correlated with the significance of inputs. Namely, the out-of-training range values of the inputs with low importance do not affect significantly the PNN model performance, but their influence can be biased by the presence of multi-outlier monitoring records. Subsequently, linear PNN models were successfully applied to study the effect of water quality parameters on DO content. It was observed that DO level is mostly affected by temperature, pH, biological oxygen demand (BOD) and phosphorus concentration, while in extreme conditions the importance of alkalinity and bicarbonates rises over p

  7. Cycle accurate and cycle reproducible memory for an FPGA based hardware accelerator

    DOEpatents

    Asaad, Sameh W.; Kapur, Mohit

    2016-03-15

    A method, system and computer program product are disclosed for using a Field Programmable Gate Array (FPGA) to simulate operations of a device under test (DUT). The DUT includes a device memory having a number of input ports, and the FPGA is associated with a target memory having a second number of input ports, the second number being less than the first number. In one embodiment, a given set of inputs is applied to the device memory at a frequency Fd and in a defined cycle of time, and the given set of inputs is applied to the target memory at a frequency Ft. Ft is greater than Fd and cycle accuracy is maintained between the device memory and the target memory. In an embodiment, a cycle accurate model of the DUT memory is created by separating the DUT memory interface protocol from the target memory storage array.

  8. Experimental design and efficient parameter estimation in preclinical pharmacokinetic studies.

    PubMed

    Ette, E I; Howie, C A; Kelman, A W; Whiting, B

    1995-05-01

    Monte Carlo simulation technique used to evaluate the effect of the arrangement of concentrations on the efficiency of estimation of population pharmacokinetic parameters in the preclinical setting is described. Although the simulations were restricted to the one compartment model with intravenous bolus input, they provide the basis of discussing some structural aspects involved in designing a destructive ("quantic") preclinical population pharmacokinetic study with a fixed sample size as is usually the case in such studies. The efficiency of parameter estimation obtained with sampling strategies based on the three and four time point designs were evaluated in terms of the percent prediction error, design number, individual and joint confidence intervals coverage for parameter estimates approaches, and correlation analysis. The data sets contained random terms for both inter- and residual intra-animal variability. The results showed that the typical population parameter estimates for clearance and volume were efficiently (accurately and precisely) estimated for both designs, while interanimal variability (the only random effect parameter that could be estimated) was inefficiently (inaccurately and imprecisely) estimated with most sampling schedules of the two designs. The exact location of the third and fourth time point for the three and four time point designs, respectively, was not critical to the efficiency of overall estimation of all population parameters of the model. However, some individual population pharmacokinetic parameters were sensitive to the location of these times.

  9. Accurate monoenergetic electron parameters of laser wakefield in a bubble model

    NASA Astrophysics Data System (ADS)

    Raheli, A.; Rahmatallahpur, S. H.

    2012-11-01

    A reliable analytical expression for the potential of plasma waves with phase velocities near the speed of light is derived. The presented spheroid cavity model is more consistent than the previous spherical and ellipsoidal model and it explains the mono-energetic electron trajectory more accurately, especially at the relativistic region. As a result, the quasi-mono-energetic electrons output beam interacting with the laser plasma can be more appropriately described with this model.

  10. 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.

  11. Enhancement of regional wet deposition estimates based on modeled precipitation inputs

    Treesearch

    James A. Lynch; Jeffery W. Grimm; Edward S. Corbett

    1996-01-01

    Application of a variety of two-dimensional interpolation algorithms to precipitation chemistry data gathered at scattered monitoring sites for the purpose of estimating precipitation- born ionic inputs for specific points or regions have failed to produce accurate estimates. The accuracy of these estimates is particularly poor in areas of high topographic relief....

  12. Analysis of the Impact of Realistic Wind Size Parameter on the Delft3D Model

    NASA Astrophysics Data System (ADS)

    Washington, M. H.; Kumar, S.

    2017-12-01

    The wind size parameter, which is the distance from the center of the storm to the location of the maximum winds, is currently a constant in the Delft3D model. As a result, the Delft3D model's output prediction of the water levels during a storm surge are inaccurate compared to the observed data. To address these issues, an algorithm to calculate a realistic wind size parameter for a given hurricane was designed and implemented using the observed water-level data for Hurricane Matthew. A performance evaluation experiment was conducted to demonstrate the accuracy of the model's prediction of water levels using the realistic wind size input parameter compared to the default constant wind size parameter for Hurricane Matthew, with the water level data observed from October 4th, 2016 to October 9th, 2016 from National Oceanic and Atmospheric Administration (NOAA) as a baseline. The experimental results demonstrate that the Delft3D water level output for the realistic wind size parameter, compared to the default constant size parameter, matches more accurately with the NOAA reference water level data.

  13. Development of wavelet-ANN models to predict water quality parameters in Hilo Bay, Pacific Ocean.

    PubMed

    Alizadeh, Mohamad Javad; Kavianpour, Mohamad Reza

    2015-09-15

    The main objective of this study is to apply artificial neural network (ANN) and wavelet-neural network (WNN) models for predicting a variety of ocean water quality parameters. In this regard, several water quality parameters in Hilo Bay, Pacific Ocean, are taken under consideration. Different combinations of water quality parameters are applied as input variables to predict daily values of salinity, temperature and DO as well as hourly values of DO. The results demonstrate that the WNN models are superior to the ANN models. Also, the hourly models developed for DO prediction outperform the daily models of DO. For the daily models, the most accurate model has R equal to 0.96, while for the hourly model it reaches up to 0.98. Overall, the results show the ability of the model to monitor the ocean parameters, in condition with missing data, or when regular measurement and monitoring are impossible. Copyright © 2015 Elsevier Ltd. All rights reserved.

  14. 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.

  15. 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.

  16. Aerodynamic Parameters of a UK City Derived from Morphological Data

    NASA Astrophysics Data System (ADS)

    Millward-Hopkins, J. T.; Tomlin, A. S.; Ma, L.; Ingham, D. B.; Pourkashanian, M.

    2013-03-01

    Detailed three-dimensional building data and a morphometric model are used to estimate the aerodynamic roughness length z 0 and displacement height d over a major UK city (Leeds). Firstly, using an adaptive grid, the city is divided into neighbourhood regions that are each of a relatively consistent geometry throughout. Secondly, for each neighbourhood, a number of geometric parameters are calculated. Finally, these are used as input into a morphometric model that considers the influence of height variability to predict aerodynamic roughness length and displacement height. Predictions are compared with estimations made using standard tables of aerodynamic parameters. The comparison suggests that the accuracy of plan-area-density based tables is likely to be limited, and that height-based tables of aerodynamic parameters may be more accurate for UK cities. The displacement heights in the standard tables are shown to be lower than the current predictions. The importance of geometric details in determining z 0 and d is then explored. Height variability is observed to greatly increase the predicted values. However, building footprint shape only has a significant influence upon the predictions when height variability is not considered. Finally, we develop simple relations to quantify the influence of height variation upon predicted z 0 and d via the standard deviation of building heights. The difference in these predictions compared to the more complex approach highlights the importance of considering the specific shape of the building-height distributions. Collectively, these results suggest that to accurately predict aerodynamic parameters of real urban areas, height variability must be considered in detail, but it may be acceptable to make simple assumptions about building layout and footprint shape.

  17. 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.

  18. Input Shaping enhanced Active Disturbance Rejection Control for a twin rotor multi-input multi-output system (TRMS).

    PubMed

    Yang, Xiaoyan; Cui, Jianwei; Lao, Dazhong; Li, Donghai; Chen, Junhui

    2016-05-01

    In this paper, a composite control based on Active Disturbance Rejection Control (ADRC) and Input Shaping is presented for TRMS with two degrees of freedom (DOF). The control tasks consist of accurately tracking desired trajectories and obtaining disturbance rejection in both horizontal and vertical planes. Due to un-measurable states as well as uncertainties stemming from modeling uncertainty and unknown disturbance torques, ADRC is employed, and feed-forward Input Shaping is used to improve the dynamical response. In the proposed approach, because the coupling effects are maintained in controller derivation, there is no requirement to decouple the TRMS into horizontal and vertical subsystems, which is usually performed in the literature. Finally, the proposed method is implemented on the TRMS platform, and the results are compared with those of PID and ADRC in a similar structure. The experimental results demonstrate the effectiveness of the proposed method. The operation of the controller allows for an excellent set-point tracking behavior and disturbance rejection with system nonlinearity and complex coupling conditions. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  19. 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.

  20. 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.

  1. Accurate reliability analysis method for quantum-dot cellular automata circuits

    NASA Astrophysics Data System (ADS)

    Cui, Huanqing; Cai, Li; Wang, Sen; Liu, Xiaoqiang; Yang, Xiaokuo

    2015-10-01

    Probabilistic transfer matrix (PTM) is a widely used model in the reliability research of circuits. However, PTM model cannot reflect the impact of input signals on reliability, so it does not completely conform to the mechanism of the novel field-coupled nanoelectronic device which is called quantum-dot cellular automata (QCA). It is difficult to get accurate results when PTM model is used to analyze the reliability of QCA circuits. To solve this problem, we present the fault tree models of QCA fundamental devices according to different input signals. After that, the binary decision diagram (BDD) is used to quantitatively investigate the reliability of two QCA XOR gates depending on the presented models. By employing the fault tree models, the impact of input signals on reliability can be identified clearly and the crucial components of a circuit can be found out precisely based on the importance values (IVs) of components. So this method is contributive to the construction of reliable QCA circuits.

  2. 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

  3. 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.

  4. Population-based input function and image-derived input function for [¹¹C](R)-rolipram PET imaging: methodology, validation and application to the study of major depressive disorder.

    PubMed

    Zanotti-Fregonara, Paolo; Hines, Christina S; Zoghbi, Sami S; Liow, Jeih-San; Zhang, Yi; Pike, Victor W; Drevets, Wayne C; Mallinger, Alan G; Zarate, Carlos A; Fujita, Masahiro; Innis, Robert B

    2012-11-15

    Quantitative PET studies of neuroreceptor tracers typically require that arterial input function be measured. The aim of this study was to explore the use of a population-based input function (PBIF) and an image-derived input function (IDIF) for [(11)C](R)-rolipram kinetic analysis, with the goal of reducing - and possibly eliminating - the number of arterial blood samples needed to measure parent radioligand concentrations. A PBIF was first generated using [(11)C](R)-rolipram parent time-activity curves from 12 healthy volunteers (Group 1). Both invasive (blood samples) and non-invasive (body weight, body surface area, and lean body mass) scaling methods for PBIF were tested. The scaling method that gave the best estimate of the Logan-V(T) values was then used to determine the test-retest variability of PBIF in Group 1 and then prospectively applied to another population of 25 healthy subjects (Group 2), as well as to a population of 26 patients with major depressive disorder (Group 3). Results were also compared to those obtained with an image-derived input function (IDIF) from the internal carotid artery. In some subjects, we measured arteriovenous differences in [(11)C](R)-rolipram concentration to see whether venous samples could be used instead of arterial samples. Finally, we assessed the ability of IDIF and PBIF to discriminate depressed patients (MDD) and healthy subjects. Arterial blood-scaled PBIF gave better results than any non-invasive scaling technique. Excellent results were obtained when the blood-scaled PBIF was prospectively applied to the subjects in Group 2 (V(T) ratio 1.02±0.05; mean±SD) and Group 3 (V(T) ratio 1.03±0.04). Equally accurate results were obtained for two subpopulations of subjects drawn from Groups 2 and 3 who had very differently shaped (i.e. "flatter" or "steeper") input functions compared to PBIF (V(T) ratio 1.07±0.04 and 0.99±0.04, respectively). Results obtained via PBIF were equivalent to those obtained via IDIF (V

  5. Effects of input device and motion type on a cursor-positioning task.

    PubMed

    Yau, Yi-Jan; Hwang, Sheue-Ling; Chao, Chin-Jung

    2008-02-01

    Many studies have investigated the performance of using nonkey-board input devices under static situations, but few have considered the effects of motion type on manipulating these input devices. In this study comparison of 12 mens' performance using four input devices (three trackballs: currently used, trackman wheel, and erectly held trackballs, as well as a touch screen) under five motion types of static, heave, roll, pitch, and random movements was conducted. The input device and motion type significantly affected movement speed and accuracy, and their interaction significantly affected the movement speed. The touch screen was the fastest but the least accurate input device. The erectly held trackball was the slowest, whereas the error rate of the currently used trackball was the lowest. Impairments of the random motion on movement time and error rate were larger than those of other motion types. Considering objective and subjective evaluations, the trackman wheel and currently used trackball were more efficient in operation than the erectly held trackball and touch screen under the motion environments.

  6. Sensitive and accurate identification of protein–DNA binding events in ChIP-chip assays using higher order derivative analysis

    PubMed Central

    Barrett, Christian L.; Cho, Byung-Kwan

    2011-01-01

    Immuno-precipitation of protein–DNA complexes followed by microarray hybridization is a powerful and cost-effective technology for discovering protein–DNA binding events at the genome scale. It is still an unresolved challenge to comprehensively, accurately and sensitively extract binding event information from the produced data. We have developed a novel strategy composed of an information-preserving signal-smoothing procedure, higher order derivative analysis and application of the principle of maximum entropy to address this challenge. Importantly, our method does not require any input parameters to be specified by the user. Using genome-scale binding data of two Escherichia coli global transcription regulators for which a relatively large number of experimentally supported sites are known, we show that ∼90% of known sites were resolved to within four probes, or ∼88 bp. Over half of the sites were resolved to within two probes, or ∼38 bp. Furthermore, we demonstrate that our strategy delivers significant quantitative and qualitative performance gains over available methods. Such accurate and sensitive binding site resolution has important consequences for accurately reconstructing transcriptional regulatory networks, for motif discovery, for furthering our understanding of local and non-local factors in protein–DNA interactions and for extending the usefulness horizon of the ChIP-chip platform. PMID:21051353

  7. Inhibitory control in mind and brain 2.0: Blocked-input models of saccadic countermanding

    PubMed Central

    Logan, Gordon D.; Yamaguchi, Motonori; Schall, Jeffrey D.; Palmeri, Thomas J.

    2015-01-01

    The interactive race model of saccadic countermanding assumes that response inhibition results from an interaction between a go unit, identified with gaze-shifting neurons, and a stop unit, identified with gaze-holding neurons, in which activation of the stop unit inhibits the growth of activation in the go unit to prevent it from reaching threshold. The interactive race model accounts for behavioral data and predicts physiological data in monkeys performing the stop-signal task. We propose an alternative model that assumes that response inhibition results from blocking the input to the go unit. We show that the blocked-input model accounts for behavioral data as accurately as the original interactive race model and predicts aspects of the physiological data more accurately. We extend the models to address the steady-state fixation period before the go stimulus is presented and find that the blocked-input model fits better than the interactive race model. We consider a model in which fixation activity is boosted when a stop signal occurs and find that it fits as well as the blocked input model but predicts very high steady-state fixation activity after the response is inhibited. We discuss the alternative linking propositions that connect computational models to neural mechanisms, the lessons to be learned from model mimicry, and generalization from countermanding saccades to countermanding other kinds of responses. PMID:25706403

  8. DREAM-3D and the importance of model inputs and boundary conditions

    NASA Astrophysics Data System (ADS)

    Friedel, Reiner; Tu, Weichao; Cunningham, Gregory; Jorgensen, Anders; Chen, Yue

    2015-04-01

    Recent work on radiation belt 3D diffusion codes such as the Los Alamos "DREAM-3D" code have demonstrated the ability of such codes to reproduce realistic magnetospheric storm events in the relativistic electron dynamics - as long as sufficient "event-oriented" boundary conditions and code inputs such as wave powers, low energy boundary conditions, background plasma densities, and last closed drift shell (outer boundary) are available. In this talk we will argue that the main limiting factor in our modeling ability is no longer our inability to represent key physical processes that govern the dynamics of the radiation belts (radial, pitch angle and energy diffusion) but rather our limitations in specifying accurate boundary conditions and code inputs. We use here DREAM-3D runs to show the sensitivity of the modeled outcomes to these boundary conditions and inputs, and also discuss alternate "proxy" approaches to obtain the required inputs from other (ground-based) sources.

  9. Influence of Population Variation of Physiological Parameters in Computational Models of Space Physiology

    NASA Technical Reports Server (NTRS)

    Myers, J. G.; Feola, A.; Werner, C.; Nelson, E. S.; Raykin, J.; Samuels, B.; Ethier, C. R.

    2016-01-01

    The earliest manifestations of Visual Impairment and Intracranial Pressure (VIIP) syndrome become evident after months of spaceflight and include a variety of ophthalmic changes, including posterior globe flattening and distension of the optic nerve sheath. Prevailing evidence links the occurrence of VIIP to the cephalic fluid shift induced by microgravity and the subsequent pressure changes around the optic nerve and eye. Deducing the etiology of VIIP is challenging due to the wide range of physiological parameters that may be influenced by spaceflight and are required to address a realistic spectrum of physiological responses. Here, we report on the application of an efficient approach to interrogating physiological parameter space through computational modeling. Specifically, we assess the influence of uncertainty in input parameters for two models of VIIP syndrome: a lumped-parameter model (LPM) of the cardiovascular and central nervous systems, and a finite-element model (FEM) of the posterior eye, optic nerve head (ONH) and optic nerve sheath. Methods: To investigate the parameter space in each model, we employed Latin hypercube sampling partial rank correlation coefficient (LHSPRCC) strategies. LHS techniques outperform Monte Carlo approaches by enforcing efficient sampling across the entire range of all parameters. The PRCC method estimates the sensitivity of model outputs to these parameters while adjusting for the linear effects of all other inputs. The LPM analysis addressed uncertainties in 42 physiological parameters, such as initial compartmental volume and nominal compartment percentage of total cardiac output in the supine state, while the FEM evaluated the effects on biomechanical strain from uncertainties in 23 material and pressure parameters for the ocular anatomy. Results and Conclusion: The LPM analysis identified several key factors including high sensitivity to the initial fluid distribution. The FEM study found that intraocular pressure and

  10. Multiple-Input Subject-Specific Modeling of Plasma Glucose Concentration for Feedforward Control.

    PubMed

    Kotz, Kaylee; Cinar, Ali; Mei, Yong; Roggendorf, Amy; Littlejohn, Elizabeth; Quinn, Laurie; Rollins, Derrick K

    2014-11-26

    The ability to accurately develop subject-specific, input causation models, for blood glucose concentration (BGC) for large input sets can have a significant impact on tightening control for insulin dependent diabetes. More specifically, for Type 1 diabetics (T1Ds), it can lead to an effective artificial pancreas (i.e., an automatic control system that delivers exogenous insulin) under extreme changes in critical disturbances. These disturbances include food consumption, activity variations, and physiological stress changes. Thus, this paper presents a free-living, outpatient, multiple-input, modeling method for BGC with strong causation attributes that is stable and guards against overfitting to provide an effective modeling approach for feedforward control (FFC). This approach is a Wiener block-oriented methodology, which has unique attributes for meeting critical requirements for effective, long-term, FFC.

  11. Uncertainties in Parameters Estimated with Neural Networks: Application to Strong Gravitational Lensing

    DOE PAGES

    Perreault Levasseur, Laurence; Hezaveh, Yashar D.; Wechsler, Risa H.

    2017-11-15

    In Hezaveh et al. (2017) we showed that deep learning can be used for model parameter estimation and trained convolutional neural networks to determine the parameters of strong gravitational lensing systems. Here we demonstrate a method for obtaining the uncertainties of these parameters. We review the framework of variational inference to obtain approximate posteriors of Bayesian neural networks and apply it to a network trained to estimate the parameters of the Singular Isothermal Ellipsoid plus external shear and total flux magnification. We show that the method can capture the uncertainties due to different levels of noise in the input data,more » as well as training and architecture-related errors made by the network. To evaluate the accuracy of the resulting uncertainties, we calculate the coverage probabilities of marginalized distributions for each lensing parameter. By tuning a single hyperparameter, the dropout rate, we obtain coverage probabilities approximately equal to the confidence levels for which they were calculated, resulting in accurate and precise uncertainty estimates. Our results suggest that neural networks can be a fast alternative to Monte Carlo Markov Chains for parameter uncertainty estimation in many practical applications, allowing more than seven orders of magnitude improvement in speed.« less

  12. Uncertainties in Parameters Estimated with Neural Networks: Application to Strong Gravitational Lensing

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

    Perreault Levasseur, Laurence; Hezaveh, Yashar D.; Wechsler, Risa H.

    In Hezaveh et al. (2017) we showed that deep learning can be used for model parameter estimation and trained convolutional neural networks to determine the parameters of strong gravitational lensing systems. Here we demonstrate a method for obtaining the uncertainties of these parameters. We review the framework of variational inference to obtain approximate posteriors of Bayesian neural networks and apply it to a network trained to estimate the parameters of the Singular Isothermal Ellipsoid plus external shear and total flux magnification. We show that the method can capture the uncertainties due to different levels of noise in the input data,more » as well as training and architecture-related errors made by the network. To evaluate the accuracy of the resulting uncertainties, we calculate the coverage probabilities of marginalized distributions for each lensing parameter. By tuning a single hyperparameter, the dropout rate, we obtain coverage probabilities approximately equal to the confidence levels for which they were calculated, resulting in accurate and precise uncertainty estimates. Our results suggest that neural networks can be a fast alternative to Monte Carlo Markov Chains for parameter uncertainty estimation in many practical applications, allowing more than seven orders of magnitude improvement in speed.« less

  13. Accurate reconstruction of the optical parameter distribution in participating medium based on the frequency-domain radiative transfer equation

    NASA Astrophysics Data System (ADS)

    Qiao, Yao-Bin; Qi, Hong; Zhao, Fang-Zhou; Ruan, Li-Ming

    2016-12-01

    Reconstructing the distribution of optical parameters in the participating medium based on the frequency-domain radiative transfer equation (FD-RTE) to probe the internal structure of the medium is investigated in the present work. The forward model of FD-RTE is solved via the finite volume method (FVM). The regularization term formatted by the generalized Gaussian Markov random field model is used in the objective function to overcome the ill-posed nature of the inverse problem. The multi-start conjugate gradient (MCG) method is employed to search the minimum of the objective function and increase the efficiency of convergence. A modified adjoint differentiation technique using the collimated radiative intensity is developed to calculate the gradient of the objective function with respect to the optical parameters. All simulation results show that the proposed reconstruction algorithm based on FD-RTE can obtain the accurate distributions of absorption and scattering coefficients. The reconstructed images of the scattering coefficient have less errors than those of the absorption coefficient, which indicates the former are more suitable to probing the inner structure. Project supported by the National Natural Science Foundation of China (Grant No. 51476043), the Major National Scientific Instruments and Equipment Development Special Foundation of China (Grant No. 51327803), and the Foundation for Innovative Research Groups of the National Natural Science Foundation of China (Grant No. 51121004).

  14. An Optimal Strategy for Accurate Bulge-to-disk Decomposition of Disk Galaxies

    NASA Astrophysics Data System (ADS)

    Gao, Hua; Ho, Luis C.

    2017-08-01

    The development of two-dimensional (2D) bulge-to-disk decomposition techniques has shown their advantages over traditional one-dimensional (1D) techniques, especially for galaxies with non-axisymmetric features. However, the full potential of 2D techniques has yet to be fully exploited. Secondary morphological features in nearby disk galaxies, such as bars, lenses, rings, disk breaks, and spiral arms, are seldom accounted for in 2D image decompositions, even though some image-fitting codes, such as GALFIT, are capable of handling them. We present detailed, 2D multi-model and multi-component decomposition of high-quality R-band images of a representative sample of nearby disk galaxies selected from the Carnegie-Irvine Galaxy Survey, using the latest version of GALFIT. The sample consists of five barred and five unbarred galaxies, spanning Hubble types from S0 to Sc. Traditional 1D decomposition is also presented for comparison. In detailed case studies of the 10 galaxies, we successfully model the secondary morphological features. Through a comparison of best-fit parameters obtained from different input surface brightness models, we identify morphological features that significantly impact bulge measurements. We show that nuclear and inner lenses/rings and disk breaks must be properly taken into account to obtain accurate bulge parameters, whereas outer lenses/rings and spiral arms have a negligible effect. We provide an optimal strategy to measure bulge parameters of typical disk galaxies, as well as prescriptions to estimate realistic uncertainties of them, which will benefit subsequent decomposition of a larger galaxy sample.

  15. An Optimal Strategy for Accurate Bulge-to-disk Decomposition of Disk Galaxies

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

    Gao Hua; Ho, Luis C.

    The development of two-dimensional (2D) bulge-to-disk decomposition techniques has shown their advantages over traditional one-dimensional (1D) techniques, especially for galaxies with non-axisymmetric features. However, the full potential of 2D techniques has yet to be fully exploited. Secondary morphological features in nearby disk galaxies, such as bars, lenses, rings, disk breaks, and spiral arms, are seldom accounted for in 2D image decompositions, even though some image-fitting codes, such as GALFIT, are capable of handling them. We present detailed, 2D multi-model and multi-component decomposition of high-quality R -band images of a representative sample of nearby disk galaxies selected from the Carnegie-Irvine Galaxymore » Survey, using the latest version of GALFIT. The sample consists of five barred and five unbarred galaxies, spanning Hubble types from S0 to Sc. Traditional 1D decomposition is also presented for comparison. In detailed case studies of the 10 galaxies, we successfully model the secondary morphological features. Through a comparison of best-fit parameters obtained from different input surface brightness models, we identify morphological features that significantly impact bulge measurements. We show that nuclear and inner lenses/rings and disk breaks must be properly taken into account to obtain accurate bulge parameters, whereas outer lenses/rings and spiral arms have a negligible effect. We provide an optimal strategy to measure bulge parameters of typical disk galaxies, as well as prescriptions to estimate realistic uncertainties of them, which will benefit subsequent decomposition of a larger galaxy sample.« less

  16. 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.

  17. Modeling the Meteoroid Input Function at Mid-Latitude Using Meteor Observations by the MU Radar

    NASA Technical Reports Server (NTRS)

    Pifko, Steven; Janches, Diego; Close, Sigrid; Sparks, Jonathan; Nakamura, Takuji; Nesvorny, David

    2012-01-01

    The Meteoroid Input Function (MIF) model has been developed with the purpose of understanding the temporal and spatial variability of the meteoroid impact in the atmosphere. This model includes the assessment of potential observational biases, namely through the use of empirical measurements to characterize the minimum detectable radar cross-section (RCS) for the particular High Power Large Aperture (HPLA) radar utilized. This RCS sensitivity threshold allows for the characterization of the radar system s ability to detect particles at a given mass and velocity. The MIF has been shown to accurately predict the meteor detection rate of several HPLA radar systems, including the Arecibo Observatory (AO) and the Poker Flat Incoherent Scatter Radar (PFISR), as well as the seasonal and diurnal variations of the meteor flux at various geographic locations. In this paper, the MIF model is used to predict several properties of the meteors observed by the Middle and Upper atmosphere (MU) radar, including the distributions of meteor areal density, speed, and radiant location. This study offers new insight into the accuracy of the MIF, as it addresses the ability of the model to predict meteor observations at middle geographic latitudes and for a radar operating frequency in the low VHF band. Furthermore, the interferometry capability of the MU radar allows for the assessment of the model s ability to capture information about the fundamental input parameters of meteoroid source and speed. This paper demonstrates that the MIF is applicable to a wide range of HPLA radar instruments and increases the confidence of using the MIF as a global model, and it shows that the model accurately considers the speed and sporadic source distributions for the portion of the meteoroid population observable by MU.

  18. Practical approximation method for firing-rate models of coupled neural networks with correlated inputs

    NASA Astrophysics Data System (ADS)

    Barreiro, Andrea K.; Ly, Cheng

    2017-08-01

    Rapid experimental advances now enable simultaneous electrophysiological recording of neural activity at single-cell resolution across large regions of the nervous system. Models of this neural network activity will necessarily increase in size and complexity, thus increasing the computational cost of simulating them and the challenge of analyzing them. Here we present a method to approximate the activity and firing statistics of a general firing rate network model (of the Wilson-Cowan type) subject to noisy correlated background inputs. The method requires solving a system of transcendental equations and is fast compared to Monte Carlo simulations of coupled stochastic differential equations. We implement the method with several examples of coupled neural networks and show that the results are quantitatively accurate even with moderate coupling strengths and an appreciable amount of heterogeneity in many parameters. This work should be useful for investigating how various neural attributes qualitatively affect the spiking statistics of coupled neural networks.

  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. Enhancing e-waste estimates: improving data quality by multivariate Input-Output Analysis.

    PubMed

    Wang, Feng; Huisman, Jaco; Stevels, Ab; Baldé, Cornelis Peter

    2013-11-01

    Waste electrical and electronic equipment (or e-waste) is one of the fastest growing waste streams, which encompasses a wide and increasing spectrum of products. Accurate estimation of e-waste generation is difficult, mainly due to lack of high quality data referred to market and socio-economic dynamics. This paper addresses how to enhance e-waste estimates by providing techniques to increase data quality. An advanced, flexible and multivariate Input-Output Analysis (IOA) method is proposed. It links all three pillars in IOA (product sales, stock and lifespan profiles) to construct mathematical relationships between various data points. By applying this method, the data consolidation steps can generate more accurate time-series datasets from available data pool. This can consequently increase the reliability of e-waste estimates compared to the approach without data processing. A case study in the Netherlands is used to apply the advanced IOA model. As a result, for the first time ever, complete datasets of all three variables for estimating all types of e-waste have been obtained. The result of this study also demonstrates significant disparity between various estimation models, arising from the use of data under different conditions. It shows the importance of applying multivariate approach and multiple sources to improve data quality for modelling, specifically using appropriate time-varying lifespan parameters. Following the case study, a roadmap with a procedural guideline is provided to enhance e-waste estimation studies. Copyright © 2013 Elsevier Ltd. All rights reserved.

  1. A rapid and accurate method, ventilated chamber C-history method, of measuring the emission characteristic parameters of formaldehyde/VOCs in building materials.

    PubMed

    Huang, Shaodan; Xiong, Jianyin; Zhang, Yinping

    2013-10-15

    The indoor pollution caused by formaldehyde and volatile organic compounds (VOCs) emitted from building materials poses an adverse effect on people's health. It is necessary to understand and control the behaviors of the emission sources. Based on detailed mass transfer analysis on the emission process in a ventilated chamber, this paper proposes a novel method of measuring the three emission characteristic parameters, i.e., the initial emittable concentration, the diffusion coefficient and the partition coefficient. A linear correlation between the logarithm of dimensionless concentration and time is derived. The three parameters can then be calculated from the intercept and slope of the correlation. Compared with the closed chamber C-history method, the test is performed under ventilated condition thus some commonly-used measurement instruments (e.g., GC/MS, HPLC) can be applied. While compared with other methods, the present method can rapidly and accurately measure the three parameters, with experimental time less than 12h and R(2) ranging from 0.96 to 0.99 for the cases studied. Independent experiment was carried out to validate the developed method, and good agreement was observed between the simulations based on the determined parameters and experiments. The present method should prove useful for quick characterization of formaldehyde/VOC emissions from indoor materials. Copyright © 2013 Elsevier B.V. All rights reserved.

  2. 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.

  3. Consistency of VDJ Rearrangement and Substitution Parameters Enables Accurate B Cell Receptor Sequence Annotation.

    PubMed

    Ralph, Duncan K; Matsen, Frederick A

    2016-01-01

    VDJ rearrangement and somatic hypermutation work together to produce antibody-coding B cell receptor (BCR) sequences for a remarkable diversity of antigens. It is now possible to sequence these BCRs in high throughput; analysis of these sequences is bringing new insight into how antibodies develop, in particular for broadly-neutralizing antibodies against HIV and influenza. A fundamental step in such sequence analysis is to annotate each base as coming from a specific one of the V, D, or J genes, or from an N-addition (a.k.a. non-templated insertion). Previous work has used simple parametric distributions to model transitions from state to state in a hidden Markov model (HMM) of VDJ recombination, and assumed that mutations occur via the same process across sites. However, codon frame and other effects have been observed to violate these parametric assumptions for such coding sequences, suggesting that a non-parametric approach to modeling the recombination process could be useful. In our paper, we find that indeed large modern data sets suggest a model using parameter-rich per-allele categorical distributions for HMM transition probabilities and per-allele-per-position mutation probabilities, and that using such a model for inference leads to significantly improved results. We present an accurate and efficient BCR sequence annotation software package using a novel HMM "factorization" strategy. This package, called partis (https://github.com/psathyrella/partis/), is built on a new general-purpose HMM compiler that can perform efficient inference given a simple text description of an HMM.

  4. Feature Selection and Parameters Optimization of SVM Using Particle Swarm Optimization for Fault Classification in Power Distribution Systems.

    PubMed

    Cho, Ming-Yuan; Hoang, Thi Thom

    2017-01-01

    Fast and accurate fault classification is essential to power system operations. In this paper, in order to classify electrical faults in radial distribution systems, a particle swarm optimization (PSO) based support vector machine (SVM) classifier has been proposed. The proposed PSO based SVM classifier is able to select appropriate input features and optimize SVM parameters to increase classification accuracy. Further, a time-domain reflectometry (TDR) method with a pseudorandom binary sequence (PRBS) stimulus has been used to generate a dataset for purposes of classification. The proposed technique has been tested on a typical radial distribution network to identify ten different types of faults considering 12 given input features generated by using Simulink software and MATLAB Toolbox. The success rate of the SVM classifier is over 97%, which demonstrates the effectiveness and high efficiency of the developed method.

  5. 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.

  6. Integrative neural networks model for prediction of sediment rating curve parameters for ungauged basins

    NASA Astrophysics Data System (ADS)

    Atieh, M.; Mehltretter, S. L.; Gharabaghi, B.; Rudra, R.

    2015-12-01

    One of the most uncertain modeling tasks in hydrology is the prediction of ungauged stream sediment load and concentration statistics. This study presents integrated artificial neural networks (ANN) models for prediction of sediment rating curve parameters (rating curve coefficient α and rating curve exponent β) for ungauged basins. The ANN models integrate a comprehensive list of input parameters to improve the accuracy achieved; the input parameters used include: soil, land use, topographic, climatic, and hydrometric data sets. The ANN models were trained on the randomly selected 2/3 of the dataset of 94 gauged streams in Ontario, Canada and validated on the remaining 1/3. The developed models have high correlation coefficients of 0.92 and 0.86 for α and β, respectively. The ANN model for the rating coefficient α is directly proportional to rainfall erosivity factor, soil erodibility factor, and apportionment entropy disorder index, whereas it is inversely proportional to vegetation cover and mean annual snowfall. The ANN model for the rating exponent β is directly proportional to mean annual precipitation, the apportionment entropy disorder index, main channel slope, standard deviation of daily discharge, and inversely proportional to the fraction of basin area covered by wetlands and swamps. Sediment rating curves are essential tools for the calculation of sediment load, concentration-duration curve (CDC), and concentration-duration-frequency (CDF) analysis for more accurate assessment of water quality for ungauged basins.

  7. Set Theory Applied to Uniquely Define the Inputs to Territorial Systems in Emergy Analyses

    EPA Science Inventory

    The language of set theory can be utilized to represent the emergy involved in all processes. In this paper we use set theory in an emergy evaluation to ensure an accurate representation of the inputs to territorial systems. We consider a generic territorial system and we describ...

  8. 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.

  9. A robust and accurate center-frequency estimation (RACE) algorithm for improving motion estimation performance of SinMod on tagged cardiac MR images without known tagging parameters.

    PubMed

    Liu, Hong; Wang, Jie; Xu, Xiangyang; Song, Enmin; Wang, Qian; Jin, Renchao; Hung, Chih-Cheng; Fei, Baowei

    2014-11-01

    A robust and accurate center-frequency (CF) estimation (RACE) algorithm for improving the performance of the local sine-wave modeling (SinMod) method, which is a good motion estimation method for tagged cardiac magnetic resonance (MR) images, is proposed in this study. The RACE algorithm can automatically, effectively and efficiently produce a very appropriate CF estimate for the SinMod method, under the circumstance that the specified tagging parameters are unknown, on account of the following two key techniques: (1) the well-known mean-shift algorithm, which can provide accurate and rapid CF estimation; and (2) an original two-direction-combination strategy, which can further enhance the accuracy and robustness of CF estimation. Some other available CF estimation algorithms are brought out for comparison. Several validation approaches that can work on the real data without ground truths are specially designed. Experimental results on human body in vivo cardiac data demonstrate the significance of accurate CF estimation for SinMod, and validate the effectiveness of RACE in facilitating the motion estimation performance of SinMod. Copyright © 2014 Elsevier Inc. All rights reserved.

  10. 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.

  11. 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.

  12. Fuzzy Stochastic Petri Nets for Modeling Biological Systems with Uncertain Kinetic Parameters

    PubMed Central

    Liu, Fei; Heiner, Monika; Yang, Ming

    2016-01-01

    Stochastic Petri nets (SPNs) have been widely used to model randomness which is an inherent feature of biological systems. However, for many biological systems, some kinetic parameters may be uncertain due to incomplete, vague or missing kinetic data (often called fuzzy uncertainty), or naturally vary, e.g., between different individuals, experimental conditions, etc. (often called variability), which has prevented a wider application of SPNs that require accurate parameters. Considering the strength of fuzzy sets to deal with uncertain information, we apply a specific type of stochastic Petri nets, fuzzy stochastic Petri nets (FSPNs), to model and analyze biological systems with uncertain kinetic parameters. FSPNs combine SPNs and fuzzy sets, thereby taking into account both randomness and fuzziness of biological systems. For a biological system, SPNs model the randomness, while fuzzy sets model kinetic parameters with fuzzy uncertainty or variability by associating each parameter with a fuzzy number instead of a crisp real value. We introduce a simulation-based analysis method for FSPNs to explore the uncertainties of outputs resulting from the uncertainties associated with input parameters, which works equally well for bounded and unbounded models. We illustrate our approach using a yeast polarization model having an infinite state space, which shows the appropriateness of FSPNs in combination with simulation-based analysis for modeling and analyzing biological systems with uncertain information. PMID:26910830

  13. 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

  14. 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.

  15. Accurate estimation of seismic source parameters of induced seismicity by a combined approach of generalized inversion and genetic algorithm: Application to The Geysers geothermal area, California

    NASA Astrophysics Data System (ADS)

    Picozzi, M.; Oth, A.; Parolai, S.; Bindi, D.; De Landro, G.; Amoroso, O.

    2017-05-01

    The accurate determination of stress drop, seismic efficiency, and how source parameters scale with earthquake size is an important issue for seismic hazard assessment of induced seismicity. We propose an improved nonparametric, data-driven strategy suitable for monitoring induced seismicity, which combines the generalized inversion technique together with genetic algorithms. In the first step of the analysis the generalized inversion technique allows for an effective correction of waveforms for attenuation and site contributions. Then, the retrieved source spectra are inverted by a nonlinear sensitivity-driven inversion scheme that allows accurate estimation of source parameters. We therefore investigate the earthquake source characteristics of 633 induced earthquakes (Mw 2-3.8) recorded at The Geysers geothermal field (California) by a dense seismic network (i.e., 32 stations, more than 17.000 velocity records). We find a nonself-similar behavior, empirical source spectra that require an ωγ source model with γ > 2 to be well fit and small radiation efficiency ηSW. All these findings suggest different dynamic rupture processes for smaller and larger earthquakes and that the proportion of high-frequency energy radiation and the amount of energy required to overcome the friction or for the creation of new fractures surface changes with earthquake size. Furthermore, we observe also two distinct families of events with peculiar source parameters that in one case suggests the reactivation of deep structures linked to the regional tectonics, while in the other supports the idea of an important role of steeply dipping faults in the fluid pressure diffusion.

  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. General methodology for nonlinear modeling of neural systems with Poisson point-process inputs.

    PubMed

    Marmarelis, V Z; Berger, T W

    2005-07-01

    This paper presents a general methodological framework for the practical modeling of neural systems with point-process inputs (sequences of action potentials or, more broadly, identical events) based on the Volterra and Wiener theories of functional expansions and system identification. The paper clarifies the distinctions between Volterra and Wiener kernels obtained from Poisson point-process inputs. It shows that only the Wiener kernels can be estimated via cross-correlation, but must be defined as zero along the diagonals. The Volterra kernels can be estimated far more accurately (and from shorter data-records) by use of the Laguerre expansion technique adapted to point-process inputs, and they are independent of the mean rate of stimulation (unlike their P-W counterparts that depend on it). The Volterra kernels can also be estimated for broadband point-process inputs that are not Poisson. Useful applications of this modeling approach include cases where we seek to determine (model) the transfer characteristics between one neuronal axon (a point-process 'input') and another axon (a point-process 'output') or some other measure of neuronal activity (a continuous 'output', such as population activity) with which a causal link exists.

  20. 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

  1. Sensitivity derivatives for advanced CFD algorithm and viscous modelling parameters via automatic differentiation

    NASA Technical Reports Server (NTRS)

    Green, Lawrence L.; Newman, Perry A.; Haigler, Kara J.

    1993-01-01

    The computational technique of automatic differentiation (AD) is applied to a three-dimensional thin-layer Navier-Stokes multigrid flow solver to assess the feasibility and computational impact of obtaining exact sensitivity derivatives typical of those needed for sensitivity analyses. Calculations are performed for an ONERA M6 wing in transonic flow with both the Baldwin-Lomax and Johnson-King turbulence models. The wing lift, drag, and pitching moment coefficients are differentiated with respect to two different groups of input parameters. The first group consists of the second- and fourth-order damping coefficients of the computational algorithm, whereas the second group consists of two parameters in the viscous turbulent flow physics modelling. Results obtained via AD are compared, for both accuracy and computational efficiency with the results obtained with divided differences (DD). The AD results are accurate, extremely simple to obtain, and show significant computational advantage over those obtained by DD for some cases.

  2. Automated determination of arterial input function for DCE-MRI of the prostate

    NASA Astrophysics Data System (ADS)

    Zhu, Yingxuan; Chang, Ming-Ching; Gupta, Sandeep

    2011-03-01

    Prostate cancer is one of the commonest cancers in the world. Dynamic contrast enhanced MRI (DCE-MRI) provides an opportunity for non-invasive diagnosis, staging, and treatment monitoring. Quantitative analysis of DCE-MRI relies on determination of an accurate arterial input function (AIF). Although several methods for automated AIF detection have been proposed in literature, none are optimized for use in prostate DCE-MRI, which is particularly challenging due to large spatial signal inhomogeneity. In this paper, we propose a fully automated method for determining the AIF from prostate DCE-MRI. Our method is based on modeling pixel uptake curves as gamma variate functions (GVF). First, we analytically compute bounds on GVF parameters for more robust fitting. Next, we approximate a GVF for each pixel based on local time domain information, and eliminate the pixels with false estimated AIFs using the deduced upper and lower bounds. This makes the algorithm robust to signal inhomogeneity. After that, according to spatial information such as similarity and distance between pixels, we formulate the global AIF selection as an energy minimization problem and solve it using a message passing algorithm to further rule out the weak pixels and optimize the detected AIF. Our method is fully automated without training or a priori setting of parameters. Experimental results on clinical data have shown that our method obtained promising detection accuracy (all detected pixels inside major arteries), and a very good match with expert traced manual AIF.

  3. Polynomial Fitting of DT-MRI Fiber Tracts Allows Accurate Estimation of Muscle Architectural Parameters

    PubMed Central

    Damon, Bruce M.; Heemskerk, Anneriet M.; Ding, Zhaohua

    2012-01-01

    Fiber curvature is a functionally significant muscle structural property, but its estimation from diffusion-tensor MRI fiber tracking data may be confounded by noise. The purpose of this study was to investigate the use of polynomial fitting of fiber tracts for improving the accuracy and precision of fiber curvature (κ) measurements. Simulated image datasets were created in order to provide data with known values for κ and pennation angle (θ). Simulations were designed to test the effects of increasing inherent fiber curvature (3.8, 7.9, 11.8, and 15.3 m−1), signal-to-noise ratio (50, 75, 100, and 150), and voxel geometry (13.8 and 27.0 mm3 voxel volume with isotropic resolution; 13.5 mm3 volume with an aspect ratio of 4.0) on κ and θ measurements. In the originally reconstructed tracts, θ was estimated accurately under most curvature and all imaging conditions studied; however, the estimates of κ were imprecise and inaccurate. Fitting the tracts to 2nd order polynomial functions provided accurate and precise estimates of κ for all conditions except very high curvature (κ=15.3 m−1), while preserving the accuracy of the θ estimates. Similarly, polynomial fitting of in vivo fiber tracking data reduced the κ values of fitted tracts from those of unfitted tracts and did not change the θ values. Polynomial fitting of fiber tracts allows accurate estimation of physiologically reasonable values of κ, while preserving the accuracy of θ estimation. PMID:22503094

  4. 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.

  5. Accurate Ray-tracing of Realistic Neutron Star Atmospheres for Constraining Their Parameters

    NASA Astrophysics Data System (ADS)

    Vincent, Frederic H.; Bejger, Michał; Różańska, Agata; Straub, Odele; Paumard, Thibaut; Fortin, Morgane; Madej, Jerzy; Majczyna, Agnieszka; Gourgoulhon, Eric; Haensel, Paweł; Zdunik, Leszek; Beldycki, Bartosz

    2018-03-01

    Thermal-dominated X-ray spectra of neutron stars in quiescent, transient X-ray binaries and neutron stars that undergo thermonuclear bursts are sensitive to mass and radius. The mass–radius relation of neutron stars depends on the equation of state (EoS) that governs their interior. Constraining this relation accurately is therefore of fundamental importance to understand the nature of dense matter. In this context, we introduce a pipeline to calculate realistic model spectra of rotating neutron stars with hydrogen and helium atmospheres. An arbitrarily fast-rotating neutron star with a given EoS generates the spacetime in which the atmosphere emits radiation. We use the LORENE/NROTSTAR code to compute the spacetime numerically and the ATM24 code to solve the radiative transfer equations self-consistently. Emerging specific intensity spectra are then ray-traced through the neutron star’s spacetime from the atmosphere to a distant observer with the GYOTO code. Here, we present and test our fully relativistic numerical pipeline. To discuss and illustrate the importance of realistic atmosphere models, we compare our model spectra to simpler models like the commonly used isotropic color-corrected blackbody emission. We highlight the importance of considering realistic model-atmosphere spectra together with relativistic ray-tracing to obtain accurate predictions. We also insist upon the crucial impact of the star’s rotation on the observables. Finally, we close a controversy that has been ongoing in the literature in the recent years, regarding the validity of the ATM24 code.

  6. Multi-level emulation of a volcanic ash transport and dispersion model to quantify sensitivity to uncertain parameters

    NASA Astrophysics Data System (ADS)

    Harvey, Natalie J.; Huntley, Nathan; Dacre, Helen F.; Goldstein, Michael; Thomson, David; Webster, Helen

    2018-01-01

    ensemble of simulations. The use of an emulator also identifies the input and internal parameters that do not contribute significantly to simulator uncertainty. Finally, the analysis highlights that the faster, less accurate, configuration of NAME can, on its own, provide useful information for the problem of predicting average column load over large areas.

  7. Anisotropic Effects on Constitutive Model Parameters of Aluminum Alloys

    NASA Astrophysics Data System (ADS)

    Brar, Nachhatter; Joshi, Vasant

    2011-06-01

    Simulation of low velocity impact on structures or high velocity penetration in armor materials heavily rely on constitutive material models. The model constants are required input to computer codes (LS-DYNA, DYNA3D or SPH) to accurately simulate fragment impact on structural components made of high strength 7075-T651 aluminum alloys. Johnson-Cook model constants determined for Al7075-T651 alloy bar material failed to simulate correctly the penetration into 1' thick Al-7075-T651plates. When simulations go well beyond minor parameter tweaking and experimental results are drastically different it is important to determine constitutive parameters from the actual material used in impact/penetration experiments. To investigate anisotropic effects on the yield/flow stress of this alloy we performed quasi-static and high strain rate tensile tests on specimens fabricated in the longitudinal, transverse, and thickness directions of 1' thick Al7075-T651 plate. Flow stresses at a strain rate of ~1100/s in the longitudinal and transverse direction are similar around 670MPa and decreases to 620 MPa in the thickness direction. These data are lower than the flow stress of 760 MPa measured in Al7075-T651 bar stock.

  8. SPEX: a highly accurate spectropolarimeter for atmospheric aerosol characterization

    NASA Astrophysics Data System (ADS)

    Rietjens, J. H. H.; Smit, J. M.; di Noia, A.; Hasekamp, O. P.; van Harten, G.; Snik, F.; Keller, C. U.

    2017-11-01

    Global characterization of atmospheric aerosol in terms of the microphysical properties of the particles is essential for understanding the role aerosols in Earth climate [1]. For more accurate predictions of future climate the uncertainties of the net radiative forcing of aerosols in the Earth's atmosphere must be reduced [2]. Essential parameters that are needed as input in climate models are not only the aerosol optical thickness (AOT), but also particle specific properties such as the aerosol mean size, the single scattering albedo (SSA) and the complex refractive index. The latter can be used to discriminate between absorbing and non-absorbing aerosol types, and between natural and anthropogenic aerosol. Classification of aerosol types is also very important for air-quality and health-related issues [3]. Remote sensing from an orbiting satellite platform is the only way to globally characterize atmospheric aerosol at a relevant timescale of 1 day [4]. One of the few methods that can be employed for measuring the microphysical properties of aerosols is to observe both radiance and degree of linear polarization of sunlight scattered in the Earth atmosphere under different viewing directions [5][6][7]. The requirement on the absolute accuracy of the degree of linear polarization PL is very stringent: the absolute error in PL must be smaller then 0.001+0.005.PL in order to retrieve aerosol parameters with sufficient accuracy to advance climate modelling and to enable discrimination of aerosol types based on their refractive index for air-quality studies [6][7]. In this paper we present the SPEX instrument, which is a multi-angle spectropolarimeter that can comply with the polarimetric accuracy needed for characterizing aerosols in the Earth's atmosphere. We describe the implementation of spectral polarization modulation in a prototype instrument of SPEX and show results of ground based measurements from which aerosol microphysical properties are retrieved.

  9. 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.

  10. 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.

  11. 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.

  12. Effective moisture penetration depth model for residential buildings: Sensitivity analysis and guidance on model inputs

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

    Woods, Jason; Winkler, Jon

    Moisture buffering of building materials has a significant impact on the building's indoor humidity, and building energy simulations need to model this buffering to accurately predict the humidity. Researchers requiring a simple moisture-buffering approach typically rely on the effective-capacitance model, which has been shown to be a poor predictor of actual indoor humidity. This paper describes an alternative two-layer effective moisture penetration depth (EMPD) model and its inputs. While this model has been used previously, there is a need to understand the sensitivity of this model to uncertain inputs. In this paper, we use the moisture-adsorbent materials exposed to themore » interior air: drywall, wood, and carpet. We use a global sensitivity analysis to determine which inputs are most influential and how the model's prediction capability degrades due to uncertainty in these inputs. We then compare the model's humidity prediction with measured data from five houses, which shows that this model, and a set of simple inputs, can give reasonable prediction of the indoor humidity.« less

  13. Effective moisture penetration depth model for residential buildings: Sensitivity analysis and guidance on model inputs

    DOE PAGES

    Woods, Jason; Winkler, Jon

    2018-01-31

    Moisture buffering of building materials has a significant impact on the building's indoor humidity, and building energy simulations need to model this buffering to accurately predict the humidity. Researchers requiring a simple moisture-buffering approach typically rely on the effective-capacitance model, which has been shown to be a poor predictor of actual indoor humidity. This paper describes an alternative two-layer effective moisture penetration depth (EMPD) model and its inputs. While this model has been used previously, there is a need to understand the sensitivity of this model to uncertain inputs. In this paper, we use the moisture-adsorbent materials exposed to themore » interior air: drywall, wood, and carpet. We use a global sensitivity analysis to determine which inputs are most influential and how the model's prediction capability degrades due to uncertainty in these inputs. We then compare the model's humidity prediction with measured data from five houses, which shows that this model, and a set of simple inputs, can give reasonable prediction of the indoor humidity.« less

  14. 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.

  15. 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...

  16. 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...

  17. 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.

  18. Analysis of blind identification methods for estimation of kinetic parameters in dynamic medical imaging

    NASA Astrophysics Data System (ADS)

    Riabkov, Dmitri

    Compartment modeling of dynamic medical image data implies that the concentration of the tracer over time in a particular region of the organ of interest is well-modeled as a convolution of the tissue response with the tracer concentration in the blood stream. The tissue response is different for different tissues while the blood input is assumed to be the same for different tissues. The kinetic parameters characterizing the tissue responses can be estimated by blind identification methods. These algorithms use the simultaneous measurements of concentration in separate regions of the organ; if the regions have different responses, the measurement of the blood input function may not be required. In this work it is shown that the blind identification problem has a unique solution for two-compartment model tissue response. For two-compartment model tissue responses in dynamic cardiac MRI imaging conditions with gadolinium-DTPA contrast agent, three blind identification algorithms are analyzed here to assess their utility: Eigenvector-based Algorithm for Multichannel Blind Deconvolution (EVAM), Cross Relations (CR), and Iterative Quadratic Maximum Likelihood (IQML). Comparisons of accuracy with conventional (not blind) identification techniques where the blood input is known are made as well. The statistical accuracies of estimation for the three methods are evaluated and compared for multiple parameter sets. The results show that the IQML method gives more accurate estimates than the other two blind identification methods. A proof is presented here that three-compartment model blind identification is not unique in the case of only two regions. It is shown that it is likely unique for the case of more than two regions, but this has not been proved analytically. For the three-compartment model the tissue responses in dynamic FDG PET imaging conditions are analyzed with the blind identification algorithms EVAM and Separable variables Least Squares (SLS). A method of

  19. 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.

  20. Reactive nitrogen inputs to US lands and waterways: how certain are we about sources and fluxes?

    EPA Science Inventory

    An overabundance of reactive nitrogen (N) as a result of anthropogenic activities has led to multiple human health and environmental concerns. Efforts to address these concerns require an accurate accounting of N inputs. Here, we present a novel synthesis of data describing N inp...

  1. Comparison of K-means and fuzzy c-means algorithm performance for automated determination of the arterial input function.

    PubMed

    Yin, Jiandong; Sun, Hongzan; Yang, Jiawen; Guo, Qiyong

    2014-01-01

    The arterial input function (AIF) plays a crucial role in the quantification of cerebral perfusion parameters. The traditional method for AIF detection is based on manual operation, which is time-consuming and subjective. Two automatic methods have been reported that are based on two frequently used clustering algorithms: fuzzy c-means (FCM) and K-means. However, it is still not clear which is better for AIF detection. Hence, we compared the performance of these two clustering methods using both simulated and clinical data. The results demonstrate that K-means analysis can yield more accurate and robust AIF results, although it takes longer to execute than the FCM method. We consider that this longer execution time is trivial relative to the total time required for image manipulation in a PACS setting, and is acceptable if an ideal AIF is obtained. Therefore, the K-means method is preferable to FCM in AIF detection.

  2. Integrated circuits for accurate linear analogue electric signal processing

    NASA Astrophysics Data System (ADS)

    Huijsing, J. H.

    1981-11-01

    The main lines in the design of integrated circuits for accurate analog linear electric signal processing in a frequency range including DC are investigated. A categorization of universal active electronic devices is presented on the basis of the connections of one of the terminals of the input and output ports to the common ground potential. The means for quantifying the attributes of four types of universal active electronic devices are included. The design of integrated operational voltage amplifiers (OVA) is discussed. Several important applications in the field of general instrumentation are numerically evaluated, and the design of operatinal floating amplifiers is presented.

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

    NASA Astrophysics Data System (ADS)

    Hao, Wenrui; Lu, Zhenzhou; Li, Luyi

    2013-05-01

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

  4. 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

  5. Accurate Modeling Method for Cu Interconnect

    NASA Astrophysics Data System (ADS)

    Yamada, Kenta; Kitahara, Hiroshi; Asai, Yoshihiko; Sakamoto, Hideo; Okada, Norio; Yasuda, Makoto; Oda, Noriaki; Sakurai, Michio; Hiroi, Masayuki; Takewaki, Toshiyuki; Ohnishi, Sadayuki; Iguchi, Manabu; Minda, Hiroyasu; Suzuki, Mieko

    This paper proposes an accurate modeling method of the copper interconnect cross-section in which the width and thickness dependence on layout patterns and density caused by processes (CMP, etching, sputtering, lithography, and so on) are fully, incorporated and universally expressed. In addition, we have developed specific test patterns for the model parameters extraction, and an efficient extraction flow. We have extracted the model parameters for 0.15μm CMOS using this method and confirmed that 10%τpd error normally observed with conventional LPE (Layout Parameters Extraction) was completely dissolved. Moreover, it is verified that the model can be applied to more advanced technologies (90nm, 65nm and 55nm CMOS). Since the interconnect delay variations due to the processes constitute a significant part of what have conventionally been treated as random variations, use of the proposed model could enable one to greatly narrow the guardbands required to guarantee a desired yield, thereby facilitating design closure.

  6. Interacting with notebook input devices: an analysis of motor performance and users' expertise.

    PubMed

    Sutter, Christine; Ziefle, Martina

    2005-01-01

    In the present study the usability of two different types of notebook input devices was examined. The independent variables were input device (touchpad vs. mini-joystick) and user expertise (expert vs. novice state). There were 30 participants, of whom 15 were touchpad experts and the other 15 were mini-joystick experts. The experimental tasks were a point-click task (Experiment 1) and a point-drag-drop task (Experiment 2). Dependent variables were the time and accuracy of cursor control. To assess carryover effects, we had the participants complete both experiments, using not only the input device for which they were experts but also the device for which they were novices. Results showed the touchpad performance to be clearly superior to mini-joystick performance. Overall, experts showed better performance than did novices. The significant interaction of input device and expertise showed that the use of an unknown device is difficult, but only for touchpad experts, who were remarkably slower and less accurate when using a mini-joystick. Actual and potential applications of this research include an evaluation of current notebook input devices. The outcomes allow ergonomic guidelines to be derived for optimized usage and design of the mini-joystick and touchpad devices.

  7. 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...

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. Accurate parameters of the oldest known rocky-exoplanet hosting system: Kepler-10 revisited

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

    Fogtmann-Schulz, Alexandra; Hinrup, Brian; Van Eylen, Vincent

    2014-02-01

    Since the discovery of Kepler-10, the system has received considerable interest because it contains a small, rocky planet which orbits the star in less than a day. The system's parameters, announced by the Kepler team and subsequently used in further research, were based on only five months of data. We have reanalyzed this system using the full span of 29 months of Kepler photometric data, and obtained improved information about its star and the planets. A detailed asteroseismic analysis of the extended time series provides a significant improvement on the stellar parameters: not only can we state that Kepler-10 ismore » the oldest known rocky-planet-harboring system at 10.41 ± 1.36 Gyr, but these parameters combined with improved planetary parameters from new transit fits gives us the radius of Kepler-10b to within just 125 km. A new analysis of the full planetary phase curve leads to new estimates on the planetary temperature and albedo, which remain degenerate in the Kepler band. Our modeling suggests that the flux level during the occultation is slightly lower than at the transit wings, which would imply that the nightside of this planet has a non-negligible temperature.« less

  14. Highly accurate quantitative spectroscopy of massive stars in the Galaxy

    NASA Astrophysics Data System (ADS)

    Nieva, María-Fernanda; Przybilla, Norbert

    2017-11-01

    Achieving high accuracy and precision in stellar parameter and chemical composition determinations is challenging in massive star spectroscopy. On one hand, the target selection for an unbiased sample build-up is complicated by several types of peculiarities that can occur in individual objects. On the other hand, composite spectra are often not recognized as such even at medium-high spectral resolution and typical signal-to-noise ratios, despite multiplicity among massive stars is widespread. In particular, surveys that produce large amounts of automatically reduced data are prone to oversight of details that turn hazardous for the analysis with techniques that have been developed for a set of standard assumptions applicable to a spectrum of a single star. Much larger systematic errors than anticipated may therefore result because of the unrecognized true nature of the investigated objects, or much smaller sample sizes of objects for the analysis than initially planned, if recognized. More factors to be taken care of are the multiple steps from the choice of instrument over the details of the data reduction chain to the choice of modelling code, input data, analysis technique and the selection of the spectral lines to be analyzed. Only when avoiding all the possible pitfalls, a precise and accurate characterization of the stars in terms of fundamental parameters and chemical fingerprints can be achieved that form the basis for further investigations regarding e.g. stellar structure and evolution or the chemical evolution of the Galaxy. The scope of the present work is to provide the massive star and also other astrophysical communities with criteria to evaluate the quality of spectroscopic investigations of massive stars before interpreting them in a broader context. The discussion is guided by our experiences made in the course of over a decade of studies of massive star spectroscopy ranging from the simplest single objects to multiple systems.

  15. Determination of well flat band condition in thin film FDSOI transistors using C-V measurement for accurate parameter extraction

    NASA Astrophysics Data System (ADS)

    Mohamad, B.; Leroux, C.; Reimbold, G.; Ghibaudo, G.

    2018-01-01

    For advanced gate stacks, effective work function (WFeff) and equivalent oxide thickness (EOT) are fundamental parameters for technology optimization. On FDSOI transistors, and contrary to the bulk technologies, while EOT can still be extracted at strong inversion from the typical gate-to-channel capacitance (Cgc), it is no longer the case for WFeff due to the disappearance of an observable flat band condition on capacitance characteristics. In this work, a new experimental method, the Cbg(VBG) characteristic, is proposed in order to extract the well flat band condition (VFB, W). This characteristic enables an accurate and direct evaluation of WFeff. Moreover, using the previous extraction of the gate oxide (tfox), and buried oxide (tbox) from typical capacitance characteristics (Cgc and Cbc), it allows the extraction of the channel thickness (tch). Furthermore, the measurement of the well flat band condition on Cbg(VBG) characteristics for two different Si and SiGe channel also proves the existence of a dipole at the SiGe/SiO2 interface.

  16. 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...

  17. 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

  18. 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.

  19. Determination of power system component parameters using nonlinear dead beat estimation method

    NASA Astrophysics Data System (ADS)

    Kolluru, Lakshmi

    Power systems are considered the most complex man-made wonders in existence today. In order to effectively supply the ever increasing demands of the consumers, power systems are required to remain stable at all times. Stability and monitoring of these complex systems are achieved by strategically placed computerized control centers. State and parameter estimation is an integral part of these facilities, as they deal with identifying the unknown states and/or parameters of the systems. Advancements in measurement technologies and the introduction of phasor measurement units (PMU) provide detailed and dynamic information of all measurements. Accurate availability of dynamic measurements provides engineers the opportunity to expand and explore various possibilities in power system dynamic analysis/control. This thesis discusses the development of a parameter determination algorithm for nonlinear power systems, using dynamic data obtained from local measurements. The proposed algorithm was developed by observing the dead beat estimator used in state space estimation of linear systems. The dead beat estimator is considered to be very effective as it is capable of obtaining the required results in a fixed number of steps. The number of steps required is related to the order of the system and the number of parameters to be estimated. The proposed algorithm uses the idea of dead beat estimator and nonlinear finite difference methods to create an algorithm which is user friendly and can determine the parameters fairly accurately and effectively. The proposed algorithm is based on a deterministic approach, which uses dynamic data and mathematical models of power system components to determine the unknown parameters. The effectiveness of the algorithm is tested by implementing it to identify the unknown parameters of a synchronous machine. MATLAB environment is used to create three test cases for dynamic analysis of the system with assumed known parameters. Faults are

  20. Accurate modelling of unsteady flows in collapsible tubes.

    PubMed

    Marchandise, Emilie; Flaud, Patrice

    2010-01-01

    The context of this paper is the development of a general and efficient numerical haemodynamic tool to help clinicians and researchers in understanding of physiological flow phenomena. We propose an accurate one-dimensional Runge-Kutta discontinuous Galerkin (RK-DG) method coupled with lumped parameter models for the boundary conditions. The suggested model has already been successfully applied to haemodynamics in arteries and is now extended for the flow in collapsible tubes such as veins. The main difference with cardiovascular simulations is that the flow may become supercritical and elastic jumps may appear with the numerical consequence that scheme may not remain monotone if no limiting procedure is introduced. We show that our second-order RK-DG method equipped with an approximate Roe's Riemann solver and a slope-limiting procedure allows us to capture elastic jumps accurately. Moreover, this paper demonstrates that the complex physics associated with such flows is more accurately modelled than with traditional methods such as finite difference methods or finite volumes. We present various benchmark problems that show the flexibility and applicability of the numerical method. Our solutions are compared with analytical solutions when they are available and with solutions obtained using other numerical methods. Finally, to illustrate the clinical interest, we study the emptying process in a calf vein squeezed by contracting skeletal muscle in a normal and pathological subject. We compare our results with experimental simulations and discuss the sensitivity to parameters of our model.

  1. 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.

  2. Accurate motion parameter estimation for colonoscopy tracking using a regression method

    NASA Astrophysics Data System (ADS)

    Liu, Jianfei; Subramanian, Kalpathi R.; Yoo, Terry S.

    2010-03-01

    Co-located optical and virtual colonoscopy images have the potential to provide important clinical information during routine colonoscopy procedures. In our earlier work, we presented an optical flow based algorithm to compute egomotion from live colonoscopy video, permitting navigation and visualization of the corresponding patient anatomy. In the original algorithm, motion parameters were estimated using the traditional Least Sum of squares(LS) procedure which can be unstable in the context of optical flow vectors with large errors. In the improved algorithm, we use the Least Median of Squares (LMS) method, a robust regression method for motion parameter estimation. Using the LMS method, we iteratively analyze and converge toward the main distribution of the flow vectors, while disregarding outliers. We show through three experiments the improvement in tracking results obtained using the LMS method, in comparison to the LS estimator. The first experiment demonstrates better spatial accuracy in positioning the virtual camera in the sigmoid colon. The second and third experiments demonstrate the robustness of this estimator, resulting in longer tracked sequences: from 300 to 1310 in the ascending colon, and 410 to 1316 in the transverse colon.

  3. Reliable and accurate point-based prediction of cumulative infiltration using soil readily available characteristics: A comparison between GMDH, ANN, and MLR

    NASA Astrophysics Data System (ADS)

    Rahmati, Mehdi

    2017-08-01

    Developing accurate and reliable pedo-transfer functions (PTFs) to predict soil non-readily available characteristics is one of the most concerned topic in soil science and selecting more appropriate predictors is a crucial factor in PTFs' development. Group method of data handling (GMDH), which finds an approximate relationship between a set of input and output variables, not only provide an explicit procedure to select the most essential PTF input variables, but also results in more accurate and reliable estimates than other mostly applied methodologies. Therefore, the current research was aimed to apply GMDH in comparison with multivariate linear regression (MLR) and artificial neural network (ANN) to develop several PTFs to predict soil cumulative infiltration point-basely at specific time intervals (0.5-45 min) using soil readily available characteristics (RACs). In this regard, soil infiltration curves as well as several soil RACs including soil primary particles (clay (CC), silt (Si), and sand (Sa)), saturated hydraulic conductivity (Ks), bulk (Db) and particle (Dp) densities, organic carbon (OC), wet-aggregate stability (WAS), electrical conductivity (EC), and soil antecedent (θi) and field saturated (θfs) water contents were measured at 134 different points in Lighvan watershed, northwest of Iran. Then, applying GMDH, MLR, and ANN methodologies, several PTFs have been developed to predict cumulative infiltrations using two sets of selected soil RACs including and excluding Ks. According to the test data, results showed that developed PTFs by GMDH and MLR procedures using all soil RACs including Ks resulted in more accurate (with E values of 0.673-0.963) and reliable (with CV values lower than 11 percent) predictions of cumulative infiltrations at different specific time steps. In contrast, ANN procedure had lower accuracy (with E values of 0.356-0.890) and reliability (with CV values up to 50 percent) compared to GMDH and MLR. The results also revealed

  4. Variable input observer for structural health monitoring of high-rate systems

    NASA Astrophysics Data System (ADS)

    Hong, Jonathan; Laflamme, Simon; Cao, Liang; Dodson, Jacob

    2017-02-01

    The development of high-rate structural health monitoring methods is intended to provide damage detection on timescales of 10 µs -10ms where speed of detection is critical to maintain structural integrity. Here, a novel Variable Input Observer (VIO) coupled with an adaptive observer is proposed as a potential solution for complex high-rate problems. The VIO is designed to adapt its input space based on real-time identification of the system's essential dynamics. By selecting appropriate time-delayed coordinates defined by both a time delay and an embedding dimension, the proper input space is chosen which allows more accurate estimations of the current state and a reduction of the convergence rate. The optimal time-delay is estimated based on mutual information, and the embedding dimension is based on false nearest neighbors. A simulation of the VIO is conducted on a two degree-of-freedom system with simulated damage. Results are compared with an adaptive Luenberger observer, a fixed time-delay observer, and a Kalman Filter. Under its preliminary design, the VIO converges significantly faster than the Luenberger and fixed observer. It performed similarly to the Kalman Filter in terms of convergence, but with greater accuracy.

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. Automatic Adaptation to Fast Input Changes in a Time-Invariant Neural Circuit

    PubMed Central

    Bharioke, Arjun; Chklovskii, Dmitri B.

    2015-01-01

    Neurons must faithfully encode signals that can vary over many orders of magnitude despite having only limited dynamic ranges. For a correlated signal, this dynamic range constraint can be relieved by subtracting away components of the signal that can be predicted from the past, a strategy known as predictive coding, that relies on learning the input statistics. However, the statistics of input natural signals can also vary over very short time scales e.g., following saccades across a visual scene. To maintain a reduced transmission cost to signals with rapidly varying statistics, neuronal circuits implementing predictive coding must also rapidly adapt their properties. Experimentally, in different sensory modalities, sensory neurons have shown such adaptations within 100 ms of an input change. Here, we show first that linear neurons connected in a feedback inhibitory circuit can implement predictive coding. We then show that adding a rectification nonlinearity to such a feedback inhibitory circuit allows it to automatically adapt and approximate the performance of an optimal linear predictive coding network, over a wide range of inputs, while keeping its underlying temporal and synaptic properties unchanged. We demonstrate that the resulting changes to the linearized temporal filters of this nonlinear network match the fast adaptations observed experimentally in different sensory modalities, in different vertebrate species. Therefore, the nonlinear feedback inhibitory network can provide automatic adaptation to fast varying signals, maintaining the dynamic range necessary for accurate neuronal transmission of natural inputs. PMID:26247884

  10. 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

  11. Comparison of K-Means and Fuzzy c-Means Algorithm Performance for Automated Determination of the Arterial Input Function

    PubMed Central

    Yin, Jiandong; Sun, Hongzan; Yang, Jiawen; Guo, Qiyong

    2014-01-01

    The arterial input function (AIF) plays a crucial role in the quantification of cerebral perfusion parameters. The traditional method for AIF detection is based on manual operation, which is time-consuming and subjective. Two automatic methods have been reported that are based on two frequently used clustering algorithms: fuzzy c-means (FCM) and K-means. However, it is still not clear which is better for AIF detection. Hence, we compared the performance of these two clustering methods using both simulated and clinical data. The results demonstrate that K-means analysis can yield more accurate and robust AIF results, although it takes longer to execute than the FCM method. We consider that this longer execution time is trivial relative to the total time required for image manipulation in a PACS setting, and is acceptable if an ideal AIF is obtained. Therefore, the K-means method is preferable to FCM in AIF detection. PMID:24503700

  12. An Accurate and Dynamic Computer Graphics Muscle Model

    NASA Technical Reports Server (NTRS)

    Levine, David Asher

    1997-01-01

    A computer based musculo-skeletal model was developed at the University in the departments of Mechanical and Biomedical Engineering. This model accurately represents human shoulder kinematics. The result of this model is the graphical display of bones moving through an appropriate range of motion based on inputs of EMGs and external forces. The need existed to incorporate a geometric muscle model in the larger musculo-skeletal model. Previous muscle models did not accurately represent muscle geometries, nor did they account for the kinematics of tendons. This thesis covers the creation of a new muscle model for use in the above musculo-skeletal model. This muscle model was based on anatomical data from the Visible Human Project (VHP) cadaver study. Two-dimensional digital images from the VHP were analyzed and reconstructed to recreate the three-dimensional muscle geometries. The recreated geometries were smoothed, reduced, and sliced to form data files defining the surfaces of each muscle. The muscle modeling function opened these files during run-time and recreated the muscle surface. The modeling function applied constant volume limitations to the muscle and constant geometry limitations to the tendons.

  13. 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.

  14. 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

  15. 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

  16. Accurate costs of blood transfusion: a microcosting of administering blood products in the United Kingdom National Health Service.

    PubMed

    Stokes, Elizabeth A; Wordsworth, Sarah; Staves, Julie; Mundy, Nicola; Skelly, Jane; Radford, Kelly; Stanworth, Simon J

    2018-04-01

    In an environment of limited health care resources, it is crucial for health care systems which provide blood transfusion to have accurate and comprehensive information on the costs of transfusion, incorporating not only the costs of blood products, but also their administration. Unfortunately, in many countries accurate costs for administering blood are not available. Our study aimed to generate comprehensive estimates of the costs of administering transfusions for the UK National Health Service. A detailed microcosting study was used to cost two key inputs into transfusion: transfusion laboratory and nursing inputs. For each input, data collection forms were developed to capture staff time, equipment, and consumables associated with each step in the transfusion process. Costing results were combined with costs of blood product wastage to calculate the cost per unit transfused, separately for different blood products. Data were collected in 2014/15 British pounds and converted to US dollars. A total of 438 data collection forms were completed by 74 staff. The cost of administering blood was $71 (£49) per unit for red blood cells, $84 (£58) for platelets, $55 (£38) for fresh-frozen plasma, and $72 (£49) for cryoprecipitate. Blood administration costs add substantially to the costs of the blood products themselves. These are frequently incurred costs; applying estimates to the blood components supplied to UK hospitals in 2015, the annual cost of blood administration, excluding blood products, exceeds $175 (£120) million. These results provide more accurate estimates of the total costs of transfusion than those previously available. © 2018 AABB.

  17. Accurate Nanoscale Crystallography in Real-Space Using Scanning Transmission Electron Microscopy.

    PubMed

    Dycus, J Houston; Harris, Joshua S; Sang, Xiahan; Fancher, Chris M; Findlay, Scott D; Oni, Adedapo A; Chan, Tsung-Ta E; Koch, Carl C; Jones, Jacob L; Allen, Leslie J; Irving, Douglas L; LeBeau, James M

    2015-08-01

    Here, we report reproducible and accurate measurement of crystallographic parameters using scanning transmission electron microscopy. This is made possible by removing drift and residual scan distortion. We demonstrate real-space lattice parameter measurements with <0.1% error for complex-layered chalcogenides Bi2Te3, Bi2Se3, and a Bi2Te2.7Se0.3 nanostructured alloy. Pairing the technique with atomic resolution spectroscopy, we connect local structure with chemistry and bonding. Combining these results with density functional theory, we show that the incorporation of Se into Bi2Te3 causes charge redistribution that anomalously increases the van der Waals gap between building blocks of the layered structure. The results show that atomic resolution imaging with electrons can accurately and robustly quantify crystallography at the nanoscale.

  18. Method for accurate growth of vertical-cavity surface-emitting lasers

    DOEpatents

    Chalmers, Scott A.; Killeen, Kevin P.; Lear, Kevin L.

    1995-01-01

    We report a method for accurate growth of vertical-cavity surface-emitting lasers (VCSELs). The method uses a single reflectivity spectrum measurement to determine the structure of the partially completed VCSEL at a critical point of growth. This information, along with the extracted growth rates, allows imprecisions in growth parameters to be compensated for during growth of the remaining structure, which can then be completed with very accurate critical dimensions. Using this method, we can now routinely grow lasing VCSELs with Fabry-Perot cavity resonance wavelengths controlled to within 0.5%.

  19. Method for accurate growth of vertical-cavity surface-emitting lasers

    DOEpatents

    Chalmers, S.A.; Killeen, K.P.; Lear, K.L.

    1995-03-14

    The authors report a method for accurate growth of vertical-cavity surface-emitting lasers (VCSELs). The method uses a single reflectivity spectrum measurement to determine the structure of the partially completed VCSEL at a critical point of growth. This information, along with the extracted growth rates, allows imprecisions in growth parameters to be compensated for during growth of the remaining structure, which can then be completed with very accurate critical dimensions. Using this method, they can now routinely grow lasing VCSELs with Fabry-Perot cavity resonance wavelengths controlled to within 0.5%. 4 figs.

  20. Parameter extraction using global particle swarm optimization approach and the influence of polymer processing temperature on the solar cell parameters

    NASA Astrophysics Data System (ADS)

    Kumar, S.; Singh, A.; Dhar, A.

    2017-08-01

    The accurate estimation of the photovoltaic parameters is fundamental to gain an insight of the physical processes occurring inside a photovoltaic device and thereby to optimize its design, fabrication processes, and quality. A simulative approach of accurately determining the device parameters is crucial for cell array and module simulation when applied in practical on-field applications. In this work, we have developed a global particle swarm optimization (GPSO) approach to estimate the different solar cell parameters viz., ideality factor (η), short circuit current (Isc), open circuit voltage (Voc), shunt resistant (Rsh), and series resistance (Rs) with wide a search range of over ±100 % for each model parameter. After validating the accurateness and global search power of the proposed approach with synthetic and noisy data, we applied the technique to the extract the PV parameters of ZnO/PCDTBT based hybrid solar cells (HSCs) prepared under different annealing conditions. Further, we examine the variation of extracted model parameters to unveil the physical processes occurring when different annealing temperatures are employed during the device fabrication and establish the role of improved charge transport in polymer films from independent FET measurements. The evolution of surface morphology, optical absorption, and chemical compositional behaviour of PCDTBT co-polymer films as a function of processing temperature has also been captured in the study and correlated with the findings from the PV parameters extracted using GPSO approach.

  1. An integrated approach for the knowledge discovery in computer simulation models with a multi-dimensional parameter space

    NASA Astrophysics Data System (ADS)

    Khawli, Toufik Al; Gebhardt, Sascha; Eppelt, Urs; Hermanns, Torsten; Kuhlen, Torsten; Schulz, Wolfgang

    2016-06-01

    In production industries, parameter identification, sensitivity analysis and multi-dimensional visualization are vital steps in the planning process for achieving optimal designs and gaining valuable information. Sensitivity analysis and visualization can help in identifying the most-influential parameters and quantify their contribution to the model output, reduce the model complexity, and enhance the understanding of the model behavior. Typically, this requires a large number of simulations, which can be both very expensive and time consuming when the simulation models are numerically complex and the number of parameter inputs increases. There are three main constituent parts in this work. The first part is to substitute the numerical, physical model by an accurate surrogate model, the so-called metamodel. The second part includes a multi-dimensional visualization approach for the visual exploration of metamodels. In the third part, the metamodel is used to provide the two global sensitivity measures: i) the Elementary Effect for screening the parameters, and ii) the variance decomposition method for calculating the Sobol indices that quantify both the main and interaction effects. The application of the proposed approach is illustrated with an industrial application with the goal of optimizing a drilling process using a Gaussian laser beam.

  2. An accurate metric for the spacetime around rotating neutron stars

    NASA Astrophysics Data System (ADS)

    Pappas, George

    2017-04-01

    The problem of having an accurate description of the spacetime around rotating neutron stars is of great astrophysical interest. For astrophysical applications, one needs to have a metric that captures all the properties of the spacetime around a rotating neutron star. Furthermore, an accurate appropriately parametrized metric, I.e. a metric that is given in terms of parameters that are directly related to the physical structure of the neutron star, could be used to solve the inverse problem, which is to infer the properties of the structure of a neutron star from astrophysical observations. In this work, we present such an approximate stationary and axisymmetric metric for the exterior of rotating neutron stars, which is constructed using the Ernst formalism and is parametrized by the relativistic multipole moments of the central object. This metric is given in terms of an expansion on the Weyl-Papapetrou coordinates with the multipole moments as free parameters and is shown to be extremely accurate in capturing the physical properties of a neutron star spacetime as they are calculated numerically in general relativity. Because the metric is given in terms of an expansion, the expressions are much simpler and easier to implement, in contrast to previous approaches. For the parametrization of the metric in general relativity, the recently discovered universal 3-hair relations are used to produce a three-parameter metric. Finally, a straightforward extension of this metric is given for scalar-tensor theories with a massless scalar field, which also admit a formulation in terms of an Ernst potential.

  3. Improved parameter extraction and classification for dynamic contrast enhanced MRI of prostate

    NASA Astrophysics Data System (ADS)

    Haq, Nandinee Fariah; Kozlowski, Piotr; Jones, Edward C.; Chang, Silvia D.; Goldenberg, S. Larry; Moradi, Mehdi

    2014-03-01

    Magnetic resonance imaging (MRI), particularly dynamic contrast enhanced (DCE) imaging, has shown great potential in prostate cancer diagnosis and prognosis. The time course of the DCE images provides measures of the contrast agent uptake kinetics. Also, using pharmacokinetic modelling, one can extract parameters from the DCE-MR images that characterize the tumor vascularization and can be used to detect cancer. A requirement for calculating the pharmacokinetic DCE parameters is estimating the Arterial Input Function (AIF). One needs an accurate segmentation of the cross section of the external femoral artery to obtain the AIF. In this work we report a semi-automatic method for segmentation of the cross section of the femoral artery, using circular Hough transform, in the sequence of DCE images. We also report a machine-learning framework to combine pharmacokinetic parameters with the model-free contrast agent uptake kinetic parameters extracted from the DCE time course into a nine-dimensional feature vector. This combination of features is used with random forest and with support vector machine classi cation for cancer detection. The MR data is obtained from patients prior to radical prostatectomy. After the surgery, wholemount histopathology analysis is performed and registered to the DCE-MR images as the diagnostic reference. We show that the use of a combination of pharmacokinetic parameters and the model-free empirical parameters extracted from the time course of DCE results in improved cancer detection compared to the use of each group of features separately. We also validate the proposed method for calculation of AIF based on comparison with the manual method.

  4. How the type of input function affects the dynamic response of conducting polymer actuators

    NASA Astrophysics Data System (ADS)

    Xiang, Xingcan; Alici, Gursel; Mutlu, Rahim; Li, Weihua

    2014-10-01

    There has been a growing interest in smart actuators typified by conducting polymer actuators, especially in their (i) fabrication, modeling and control with minimum external data and (ii) applications in bio-inspired devices, robotics and mechatronics. Their control is a challenging research problem due to the complex and nonlinear properties of these actuators, which cannot be predicted accurately. Based on an input-shaping technique, we propose a new method to improve the conducting polymer actuators’ command-following ability, while minimizing their electric power consumption. We applied four input functions with smooth characteristics to a trilayer conducting polymer actuator to experimentally evaluate its command-following ability under an open-loop control strategy and a simulated feedback control strategy, and, more importantly, to quantify how the type of input function affects the dynamic response of this class of actuators. We have found that the four smooth inputs consume less electrical power than sharp inputs such as a step input with discontinuous higher-order derivatives. We also obtained an improved transient response performance from the smooth inputs, especially under the simulated feedback control strategy, which we have proposed previously [X Xiang, R Mutlu, G Alici, and W Li, 2014 “Control of conducting polymer actuators without physical feedback: simulated feedback control approach with particle swarm optimization’, Journal of Smart Materials and Structure, 23]. The idea of using a smooth input command, which results in lower power consumption and better control performance, can be extended to other smart actuators. Consuming less electrical energy or power will have a direct effect on enhancing the operational life of these actuators.

  5. A Reexamination of the Emergy Input to a System from the ...

    EPA Pesticide Factsheets

    The wind energy absorbed in the global boundary layer (GBL, 900 mb surface) is the basis for calculating the wind emergy input for any system on the Earth’s surface. Estimates of the wind emergy input to a system depend on the amount of wind energy dissipated, which can have a range of magnitudes for a given velocity depending on surface drag and atmospheric stability at the location and time period under study. In this study, we develop a method to consider this complexity in estimating the emergy input to a system from the wind. A new calculation of the transformity of the wind energy dissipated in the GBL (900 mb surface) based on general models of atmospheric circulation in the planetary boundary layer (PBL, 100 mb surface) is presented and expressed on the 12.0E+24 seJ y-1 geobiosphere baseline to complete the information needed to calculate the emergy input from the wind to the GBL of any system. The average transformity of wind energy dissipated in the GBL (below 900 mb) was 1241±650 sej J-1. The analysis showed that the transformity of the wind varies over the course of a year such that summer processes may require a different wind transformity than processes occurring with a winter or annual time boundary. This is a paper in the proceedings of Emergy Synthesis 9, thus it will be available online for those interested in this subject. The paper describes a new and more accurate way to estimate the wind energy input to any system. It also has a new cal

  6. 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.

  7. Local polynomial chaos expansion for linear differential equations with high dimensional random inputs

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

    Chen, Yi; Jakeman, John; Gittelson, Claude

    2015-01-08

    In this paper we present a localized polynomial chaos expansion for partial differential equations (PDE) with random inputs. In particular, we focus on time independent linear stochastic problems with high dimensional random inputs, where the traditional polynomial chaos methods, and most of the existing methods, incur prohibitively high simulation cost. Furthermore, the local polynomial chaos method employs a domain decomposition technique to approximate the stochastic solution locally. In each subdomain, a subdomain problem is solved independently and, more importantly, in a much lower dimensional random space. In a postprocesing stage, accurate samples of the original stochastic problems are obtained frommore » the samples of the local solutions by enforcing the correct stochastic structure of the random inputs and the coupling conditions at the interfaces of the subdomains. Overall, the method is able to solve stochastic PDEs in very large dimensions by solving a collection of low dimensional local problems and can be highly efficient. In our paper we present the general mathematical framework of the methodology and use numerical examples to demonstrate the properties of the method.« less

  8. Standardized residual as response function for order identification of multi input intervention analysis

    NASA Astrophysics Data System (ADS)

    Suhartono, Lee, Muhammad Hisyam; Rezeki, Sri

    2017-05-01

    Intervention analysis is a statistical model in the group of time series analysis which is widely used to describe the effect of an intervention caused by external or internal factors. An example of external factors that often occurs in Indonesia is a disaster, both natural or man-made disaster. The main purpose of this paper is to provide the results of theoretical studies on identification step for determining the order of multi inputs intervention analysis for evaluating the magnitude and duration of the impact of interventions on time series data. The theoretical result showed that the standardized residuals could be used properly as response function for determining the order of multi inputs intervention model. Then, these results are applied for evaluating the impact of a disaster on a real case in Indonesia, i.e. the magnitude and duration of the impact of the Lapindo mud on the volume of vehicles on the highway. Moreover, the empirical results showed that the multi inputs intervention model can describe and explain accurately the magnitude and duration of the impact of disasters on a time series data.

  9. Influence of current input-output and age of first exposure on phonological acquisition in early bilingual Spanish-English-speaking kindergarteners.

    PubMed

    Ruiz-Felter, Roxanna; Cooperson, Solaman J; Bedore, Lisa M; Peña, Elizabeth D

    2016-07-01

    Although some investigations of phonological development have found that segmental accuracy is comparable in monolingual children and their bilingual peers, there is evidence that language use affects segmental accuracy in both languages. To investigate the influence of age of first exposure to English and the amount of current input-output on phonological accuracy in English and Spanish in early bilingual Spanish-English kindergarteners. Also whether parent and teacher ratings of the children's intelligibility are correlated with phonological accuracy and the amount of experience with each language. Data for 91 kindergarteners (mean age = 5;6 years) were selected from a larger dataset focusing on Spanish-English bilingual language development. All children were from Central Texas, spoke a Mexican Spanish dialect and were learning American English. Children completed a single-word phonological assessment with separate forms for English and Spanish. The assessment was analyzed for segmental accuracy: percentage of consonants and vowels correct and percentage of early-, middle- and late-developing (EML) sounds correct were calculated. Children were more accurate on vowel production than consonant production and showed a decrease in accuracy from early to middle to late sounds. The amount of current input-output explained more of the variance in phonological accuracy than age of first English exposure. Although greater current input-output of a language was associated with greater accuracy in that language, English-dominant children were only significantly more accurate in English than Spanish on late sounds, whereas Spanish-dominant children were only significantly more accurate in Spanish than English on early sounds. Higher parent and teacher ratings of intelligibility in Spanish were correlated with greater consonant accuracy in Spanish, but the same did not hold for English. Higher intelligibility ratings in English were correlated with greater current English

  10. 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.

  11. Simple and accurate wavemeter implemented with a polarization interferometer.

    PubMed

    Dimmick, T E

    1997-12-20

    A simple and accurate wavemeter for measuring the wavelength of monochromatic light is described. The device uses the wavelength-dependent phase lag between principal polarization states of a length of birefringent material (retarder) as the basis for the measurement of the optical wavelength. The retarder is sandwiched between a polarizer and a polarizing beam splitter and is oriented such that its principal axes are 45 deg to the axis of the polarizer and the principal axes of the beam splitter. As a result of the disparity in propagation velocities between the principal polarization states of the retarder, the ratio of the optical power exiting the two ports of the polarizing beam splitter is wavelength dependent. If the input wavelength is known to be within a specified range, the measurement of the power ratio uniquely determines the input wavelength. The device offers the advantage of trading wavelength coverage for increased resolution simply through the choice of the retarder length. Implementations of the device employing both bulk-optic components and fiber-optic components are described, and the results of a laboratory test of a fiber-optic prototype are presented. The prototype had a wavelength accuracy of +/-0.03 nm.

  12. Fast and Accurate Circuit Design Automation through Hierarchical Model Switching.

    PubMed

    Huynh, Linh; Tagkopoulos, Ilias

    2015-08-21

    In computer-aided biological design, the trifecta of characterized part libraries, accurate models and optimal design parameters is crucial for producing reliable designs. As the number of parts and model complexity increase, however, it becomes exponentially more difficult for any optimization method to search the solution space, hence creating a trade-off that hampers efficient design. To address this issue, we present a hierarchical computer-aided design architecture that uses a two-step approach for biological design. First, a simple model of low computational complexity is used to predict circuit behavior and assess candidate circuit branches through branch-and-bound methods. Then, a complex, nonlinear circuit model is used for a fine-grained search of the reduced solution space, thus achieving more accurate results. Evaluation with a benchmark of 11 circuits and a library of 102 experimental designs with known characterization parameters demonstrates a speed-up of 3 orders of magnitude when compared to other design methods that provide optimality guarantees.

  13. Convergence in parameters and predictions using computational experimental design.

    PubMed

    Hagen, David R; White, Jacob K; Tidor, Bruce

    2013-08-06

    Typically, biological models fitted to experimental data suffer from significant parameter uncertainty, which can lead to inaccurate or uncertain predictions. One school of thought holds that accurate estimation of the true parameters of a biological system is inherently problematic. Recent work, however, suggests that optimal experimental design techniques can select sets of experiments whose members probe complementary aspects of a biochemical network that together can account for its full behaviour. Here, we implemented an experimental design approach for selecting sets of experiments that constrain parameter uncertainty. We demonstrated with a model of the epidermal growth factor-nerve growth factor pathway that, after synthetically performing a handful of optimal experiments, the uncertainty in all 48 parameters converged below 10 per cent. Furthermore, the fitted parameters converged to their true values with a small error consistent with the residual uncertainty. When untested experimental conditions were simulated with the fitted models, the predicted species concentrations converged to their true values with errors that were consistent with the residual uncertainty. This paper suggests that accurate parameter estimation is achievable with complementary experiments specifically designed for the task, and that the resulting parametrized models are capable of accurate predictions.

  14. 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.

  15. Accurate Time-Dependent Traveling-Wave Tube Model Developed for Computational Bit-Error-Rate Testing

    NASA Technical Reports Server (NTRS)

    Kory, Carol L.

    2001-01-01

    The phenomenal growth of the satellite communications industry has created a large demand for traveling-wave tubes (TWT's) operating with unprecedented specifications requiring the design and production of many novel devices in record time. To achieve this, the TWT industry heavily relies on computational modeling. However, the TWT industry's computational modeling capabilities need to be improved because there are often discrepancies between measured TWT data and that predicted by conventional two-dimensional helical TWT interaction codes. This limits the analysis and design of novel devices or TWT's with parameters differing from what is conventionally manufactured. In addition, the inaccuracy of current computational tools limits achievable TWT performance because optimized designs require highly accurate models. To address these concerns, a fully three-dimensional, time-dependent, helical TWT interaction model was developed using the electromagnetic particle-in-cell code MAFIA (Solution of MAxwell's equations by the Finite-Integration-Algorithm). The model includes a short section of helical slow-wave circuit with excitation fed by radiofrequency input/output couplers, and an electron beam contained by periodic permanent magnet focusing. A cutaway view of several turns of the three-dimensional helical slow-wave circuit with input/output couplers is shown. This has been shown to be more accurate than conventionally used two-dimensional models. The growth of the communications industry has also imposed a demand for increased data rates for the transmission of large volumes of data. To achieve increased data rates, complex modulation and multiple access techniques are employed requiring minimum distortion of the signal as it is passed through the TWT. Thus, intersymbol interference (ISI) becomes a major consideration, as well as suspected causes such as reflections within the TWT. To experimentally investigate effects of the physical TWT on ISI would be

  16. Line shape parameters of the 22-GHz water line for accurate modeling in atmospheric applications

    NASA Astrophysics Data System (ADS)

    Koshelev, M. A.; Golubiatnikov, G. Yu.; Vilkov, I. N.; Tretyakov, M. Yu.

    2018-01-01

    The paper concerns refining parameters of one of the major atmospheric diagnostic lines of water vapor at 22 GHz. Two high resolution microwave spectrometers based on different principles of operation covering together the pressure range from a few milliTorr up to a few Torr were used. Special efforts were made to minimize possible sources of systematic measurement errors. Satisfactory self-consistency of the obtained data was achieved ensuring reliability of the obtained parameters. Collisional broadening and shifting parameters of the line in pure water vapor and in its mixture with air were determined at room temperature. Comparative analysis of the obtained parameters with previous data is given. The speed dependence effect impact on the line shape was evaluated.

  17. 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.

  18. Ensemble MD simulations restrained via crystallographic data: Accurate structure leads to accurate dynamics

    PubMed Central

    Xue, Yi; Skrynnikov, Nikolai R

    2014-01-01

    Currently, the best existing molecular dynamics (MD) force fields cannot accurately reproduce the global free-energy minimum which realizes the experimental protein structure. As a result, long MD trajectories tend to drift away from the starting coordinates (e.g., crystallographic structures). To address this problem, we have devised a new simulation strategy aimed at protein crystals. An MD simulation of protein crystal is essentially an ensemble simulation involving multiple protein molecules in a crystal unit cell (or a block of unit cells). To ensure that average protein coordinates remain correct during the simulation, we introduced crystallography-based restraints into the MD protocol. Because these restraints are aimed at the ensemble-average structure, they have only minimal impact on conformational dynamics of the individual protein molecules. So long as the average structure remains reasonable, the proteins move in a native-like fashion as dictated by the original force field. To validate this approach, we have used the data from solid-state NMR spectroscopy, which is the orthogonal experimental technique uniquely sensitive to protein local dynamics. The new method has been tested on the well-established model protein, ubiquitin. The ensemble-restrained MD simulations produced lower crystallographic R factors than conventional simulations; they also led to more accurate predictions for crystallographic temperature factors, solid-state chemical shifts, and backbone order parameters. The predictions for 15N R1 relaxation rates are at least as accurate as those obtained from conventional simulations. Taken together, these results suggest that the presented trajectories may be among the most realistic protein MD simulations ever reported. In this context, the ensemble restraints based on high-resolution crystallographic data can be viewed as protein-specific empirical corrections to the standard force fields. PMID:24452989

  19. Combined inverse-forward artificial neural networks for fast and accurate estimation of the diffusion coefficients of cartilage based on multi-physics models.

    PubMed

    Arbabi, Vahid; Pouran, Behdad; Weinans, Harrie; Zadpoor, Amir A

    2016-09-06

    Analytical and numerical methods have been used to extract essential engineering parameters such as elastic modulus, Poisson׳s ratio, permeability and diffusion coefficient from experimental data in various types of biological tissues. The major limitation associated with analytical techniques is that they are often only applicable to problems with simplified assumptions. Numerical multi-physics methods, on the other hand, enable minimizing the simplified assumptions but require substantial computational expertise, which is not always available. In this paper, we propose a novel approach that combines inverse and forward artificial neural networks (ANNs) which enables fast and accurate estimation of the diffusion coefficient of cartilage without any need for computational modeling. In this approach, an inverse ANN is trained using our multi-zone biphasic-solute finite-bath computational model of diffusion in cartilage to estimate the diffusion coefficient of the various zones of cartilage given the concentration-time curves. Robust estimation of the diffusion coefficients, however, requires introducing certain levels of stochastic variations during the training process. Determining the required level of stochastic variation is performed by coupling the inverse ANN with a forward ANN that receives the diffusion coefficient as input and returns the concentration-time curve as output. Combined together, forward-inverse ANNs enable computationally inexperienced users to obtain accurate and fast estimation of the diffusion coefficients of cartilage zones. The diffusion coefficients estimated using the proposed approach are compared with those determined using direct scanning of the parameter space as the optimization approach. It has been shown that both approaches yield comparable results. Copyright © 2016 Elsevier Ltd. All rights reserved.

  20. Improvement of Galilean refractive beam shaping system for accurately generating near-diffraction-limited flattop beam with arbitrary beam size.

    PubMed

    Ma, Haotong; Liu, Zejin; Jiang, Pengzhi; Xu, Xiaojun; Du, Shaojun

    2011-07-04

    We propose and demonstrate the improvement of conventional Galilean refractive beam shaping system for accurately generating near-diffraction-limited flattop beam with arbitrary beam size. Based on the detailed study of the refractive beam shaping system, we found that the conventional Galilean beam shaper can only work well for the magnifying beam shaping. Taking the transformation of input beam with Gaussian irradiance distribution into target beam with high order Fermi-Dirac flattop profile as an example, the shaper can only work well at the condition that the size of input and target beam meets R(0) ≥ 1.3 w(0). For the improvement, the shaper is regarded as the combination of magnifying and demagnifying beam shaping system. The surface and phase distributions of the improved Galilean beam shaping system are derived based on Geometric and Fourier Optics. By using the improved Galilean beam shaper, the accurate transformation of input beam with Gaussian irradiance distribution into target beam with flattop irradiance distribution is realized. The irradiance distribution of the output beam is coincident with that of the target beam and the corresponding phase distribution is maintained. The propagation performance of the output beam is greatly improved. Studies of the influences of beam size and beam order on the improved Galilean beam shaping system show that restriction of beam size has been greatly reduced. This improvement can also be used to redistribute the input beam with complicated irradiance distribution into output beam with complicated irradiance distribution.

  1. Accurate RNA consensus sequencing for high-fidelity detection of transcriptional mutagenesis-induced epimutations.

    PubMed

    Reid-Bayliss, Kate S; Loeb, Lawrence A

    2017-08-29

    Transcriptional mutagenesis (TM) due to misincorporation during RNA transcription can result in mutant RNAs, or epimutations, that generate proteins with altered properties. TM has long been hypothesized to play a role in aging, cancer, and viral and bacterial evolution. However, inadequate methodologies have limited progress in elucidating a causal association. We present a high-throughput, highly accurate RNA sequencing method to measure epimutations with single-molecule sensitivity. Accurate RNA consensus sequencing (ARC-seq) uniquely combines RNA barcoding and generation of multiple cDNA copies per RNA molecule to eliminate errors introduced during cDNA synthesis, PCR, and sequencing. The stringency of ARC-seq can be scaled to accommodate the quality of input RNAs. We apply ARC-seq to directly assess transcriptome-wide epimutations resulting from RNA polymerase mutants and oxidative stress.

  2. 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.

  3. 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.

  4. 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.

  5. Studies of HZE particle interactions and transport for space radiation protection purposes

    NASA Technical Reports Server (NTRS)

    Townsend, Lawrence W.; Wilson, John W.; Schimmerling, Walter; Wong, Mervyn

    1987-01-01

    The main emphasis is on developing general methods for accurately predicting high-energy heavy ion (HZE) particle interactions and transport for use by researchers in mission planning studies, in evaluating astronaut self-shielding factors, and in spacecraft shield design and optimization studies. The two research tasks are: (1) to develop computationally fast and accurate solutions to the Boltzmann (transport) equation; and (2) to develop accurate HZE interaction models, from fundamental physical considerations, for use as inputs into these transport codes. Accurate solutions to the HZE transport problem have been formulated through a combination of analytical and numerical techniques. In addition, theoretical models for the input interaction parameters are under development: stopping powers, nuclear absorption cross sections, and fragmentation parameters.

  6. 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.

  7. 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.

  8. 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.

  9. Green-ampt infiltration parameters in riparian buffers

    Treesearch

    L.M. Stahr; D.E. Eisenhauer; M.J. Helmers; Mike G. Dosskey; T.G. Franti

    2004-01-01

    Riparian buffers can improve surface water quality by filtering contaminants from runoff before they enter streams. Infiltration is an important process in riparian buffers. Computer models are often used to assess the performance of riparian buffers. Accurate prediction of infiltration by these models is dependent upon accurate estimates of infiltration parameters....

  10. [Development of an analyzing system for soil parameters based on NIR spectroscopy].

    PubMed

    Zheng, Li-Hua; Li, Min-Zan; Sun, Hong

    2009-10-01

    A rapid estimation system for soil parameters based on spectral analysis was developed by using object-oriented (OO) technology. A class of SOIL was designed. The instance of the SOIL class is the object of the soil samples with the particular type, specific physical properties and spectral characteristics. Through extracting the effective information from the modeling spectral data of soil object, a map model was established between the soil parameters and its spectral data, while it was possible to save the mapping model parameters in the database of the model. When forecasting the content of any soil parameter, the corresponding prediction model of this parameter can be selected with the same soil type and the similar soil physical properties of objects. And after the object of target soil samples was carried into the prediction model and processed by the system, the accurate forecasting content of the target soil samples could be obtained. The system includes modules such as file operations, spectra pretreatment, sample analysis, calibrating and validating, and samples content forecasting. The system was designed to run out of equipment. The parameters and spectral data files (*.xls) of the known soil samples can be input into the system. Due to various data pretreatment being selected according to the concrete conditions, the results of predicting content will appear in the terminal and the forecasting model can be stored in the model database. The system reads the predicting models and their parameters are saved in the model database from the module interface, and then the data of the tested samples are transferred into the selected model. Finally the content of soil parameters can be predicted by the developed system. The system was programmed with Visual C++6.0 and Matlab 7.0. And the Access XP was used to create and manage the model database.

  11. 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.

  12. 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.

  13. An automatic scaling method for obtaining the trace and parameters from oblique ionogram based on hybrid genetic algorithm

    NASA Astrophysics Data System (ADS)

    Song, Huan; Hu, Yaogai; Jiang, Chunhua; Zhou, Chen; Zhao, Zhengyu; Zou, Xianjian

    2016-12-01

    Scaling oblique ionogram plays an important role in obtaining ionospheric structure at the midpoint of oblique sounding path. The paper proposed an automatic scaling method to extract the trace and parameters of oblique ionogram based on hybrid genetic algorithm (HGA). The extracted 10 parameters come from F2 layer and Es layer, such as maximum observation frequency, critical frequency, and virtual height. The method adopts quasi-parabolic (QP) model to describe F2 layer's electron density profile that is used to synthesize trace. And it utilizes secant theorem, Martyn's equivalent path theorem, image processing technology, and echoes' characteristics to determine seven parameters' best fit values, and three parameter's initial values in QP model to set up their searching spaces which are the needed input data of HGA. Then HGA searches the three parameters' best fit values from their searching spaces based on the fitness between the synthesized trace and the real trace. In order to verify the performance of the method, 240 oblique ionograms are scaled and their results are compared with manual scaling results and the inversion results of the corresponding vertical ionograms. The comparison results show that the scaling results are accurate or at least adequate 60-90% of the time.

  14. 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.

  15. How Accurate is Information that Patients Contribute to their Electronic Health Record?

    PubMed Central

    Wuerdeman, Lisa; Volk, Lynn; Pizziferri, Lisa; Tsurikova, Ruslana; Harris, Cathyann; Feygin, Raisa; Epstein, Marianna; Meyers, Kimberly; Wald, Jonathan S.; Lansky, David; Bates, David W.

    2005-01-01

    Increased patient interaction with medical records and the advent of personal health records (PHRs) may increase patients’ ability to contribute valid information to their Electronic Health Record (EHR) medical record. Patient input through a secure connection, whether it is a patient portal or PHR, will integrate many aspects of a patient’s health and may help lessen the information gap between patients and providers. Patient reported data should be considered a viable method of enhancing documentation but will not likely be as complete and accurate as more comprehensive data-exchange between providers. PMID:16779157

  16. Toward Accurate On-Ground Attitude Determination for the Gaia Spacecraft

    NASA Astrophysics Data System (ADS)

    Samaan, Malak A.

    2010-03-01

    The work presented in this paper concerns the accurate On-Ground Attitude (OGA) reconstruction for the astrometry spacecraft Gaia in the presence of disturbance and of control torques acting on the spacecraft. The reconstruction of the expected environmental torques which influence the spacecraft dynamics will be also investigated. The telemetry data from the spacecraft will include the on-board real-time attitude, which is of order of several arcsec. This raw attitude is the starting point for the further attitude reconstruction. The OGA will use the inputs from the field coordinates of known stars (attitude stars) and also the field coordinate differences of objects on the Sky Mapper (SM) and Astrometric Field (AF) payload instruments to improve this raw attitude. The on-board attitude determination uses a Kalman Filter (KF) to minimize the attitude errors and produce a more accurate attitude estimation than the pure star tracker measurement. Therefore the first approach for the OGA will be an adapted version of KF. Furthermore, we will design a batch least squares algorithm to investigate how to obtain a more accurate OGA estimation. Finally, a comparison between these different attitude determination techniques in terms of accuracy, robustness, speed and memory required will be evaluated in order to choose the best attitude algorithm for the OGA. The expected resulting accuracy for the OGA determination will be on the order of milli-arcsec.

  17. 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.

  18. 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.

  19. The human motor neuron pools receive a dominant slow‐varying common synaptic input

    PubMed Central

    Negro, Francesco; Yavuz, Utku Şükrü

    2016-01-01

    Key points Motor neurons in a pool receive both common and independent synaptic inputs, although the proportion and role of their common synaptic input is debated.Classic correlation techniques between motor unit spike trains do not measure the absolute proportion of common input and have limitations as a result of the non‐linearity of motor neurons.We propose a method that for the first time allows an accurate quantification of the absolute proportion of low frequency common synaptic input (<5 Hz) to motor neurons in humans.We applied the proposed method to three human muscles and determined experimentally that they receive a similar large amount (>60%) of common input, irrespective of their different functional and control properties.These results increase our knowledge about the role of common and independent input to motor neurons in force control. Abstract Motor neurons receive both common and independent synaptic inputs. This observation is classically based on the presence of a significant correlation between pairs of motor unit spike trains. The functional significance of different relative proportions of common input across muscles, individuals and conditions is still debated. One of the limitations in our understanding of correlated input to motor neurons is that it has not been possible so far to quantify the absolute proportion of common input with respect to the total synaptic input received by the motor neurons. Indeed, correlation measures of pairs of output spike trains only allow for relative comparisons. In the present study, we report for the first time an approach for measuring the proportion of common input in the low frequency bandwidth (<5 Hz) to a motor neuron pool in humans. This estimate is based on a phenomenological model and the theoretical fitting of the experimental values of coherence between the permutations of groups of motor unit spike trains. We demonstrate the validity of this theoretical estimate with several simulations

  20. 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

  1. 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

  2. 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.

  3. 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.

  4. A model-constrained Monte Carlo method for blind arterial input function estimation in dynamic contrast-enhanced MRI: II. In vivo results

    NASA Astrophysics Data System (ADS)

    Schabel, Matthias C.; DiBella, Edward V. R.; Jensen, Randy L.; Salzman, Karen L.

    2010-08-01

    Accurate quantification of pharmacokinetic model parameters in tracer kinetic imaging experiments requires correspondingly accurate determination of the arterial input function (AIF). Despite significant effort expended on methods of directly measuring patient-specific AIFs in modalities as diverse as dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), dynamic positron emission tomography (PET), and perfusion computed tomography (CT), fundamental and technical difficulties have made consistent and reliable achievement of that goal elusive. Here, we validate a new algorithm for AIF determination, the Monte Carlo blind estimation (MCBE) method (which is described in detail and characterized by extensive simulations in a companion paper), by comparing AIFs measured in DCE-MRI studies of eight brain tumor patients with results of blind estimation. Blind AIFs calculated with the MCBE method using a pool of concentration-time curves from a region of normal brain tissue were found to be quite similar to the measured AIFs, with statistically significant decreases in fit residuals observed in six of eight patients. Biases between the blind and measured pharmacokinetic parameters were the dominant source of error. Averaged over all eight patients, the mean biases were +7% in K trans, 0% in kep, -11% in vp and +10% in ve. Corresponding uncertainties (median absolute deviation from the best fit line) were 0.0043 min-1 in K trans, 0.0491 min-1 in kep, 0.29% in vp and 0.45% in ve. The use of a published population-averaged AIF resulted in larger mean biases in three of the four parameters (-23% in K trans, -22% in kep, -63% in vp), with the bias in ve unchanged, and led to larger uncertainties in all four parameters (0.0083 min-1 in K trans, 0.1038 min-1 in kep, 0.31% in vp and 0.95% in ve). When blind AIFs were calculated from a region of tumor tissue, statistically significant decreases in fit residuals were observed in all eight patients despite larger

  5. Transport, retention, and size perturbation of graphene oxide in saturated porous media: Effects of input concentration and grain size

    USDA-ARS?s Scientific Manuscript database

    Accurately predicting the fate and transport of graphene oxide (GO) in porous media is critical to assess its environmental impact. In this work, sand column experiments were conducted to determine the effect of input concentration and grain size on transport, retention, and size perturbation of GO ...

  6. 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

  7. Importance analysis for Hudson River PCB transport and fate model parameters using robust sensitivity studies

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

    Zhang, S.; Toll, J.; Cothern, K.

    1995-12-31

    The authors have performed robust sensitivity studies of the physico-chemical Hudson River PCB model PCHEPM to identify the parameters and process uncertainties contributing the most to uncertainty in predictions of water column and sediment PCB concentrations, over the time period 1977--1991 in one segment of the lower Hudson River. The term ``robust sensitivity studies`` refers to the use of several sensitivity analysis techniques to obtain a more accurate depiction of the relative importance of different sources of uncertainty. Local sensitivity analysis provided data on the sensitivity of PCB concentration estimates to small perturbations in nominal parameter values. Range sensitivity analysismore » provided information about the magnitude of prediction uncertainty associated with each input uncertainty. Rank correlation analysis indicated which parameters had the most dominant influence on model predictions. Factorial analysis identified important interactions among model parameters. Finally, term analysis looked at the aggregate influence of combinations of parameters representing physico-chemical processes. The authors scored the results of the local and range sensitivity and rank correlation analyses. The authors considered parameters that scored high on two of the three analyses to be important contributors to PCB concentration prediction uncertainty, and treated them probabilistically in simulations. They also treated probabilistically parameters identified in the factorial analysis as interacting with important parameters. The authors used the term analysis to better understand how uncertain parameters were influencing the PCB concentration predictions. The importance analysis allowed us to reduce the number of parameters to be modeled probabilistically from 16 to 5. This reduced the computational complexity of Monte Carlo simulations, and more importantly, provided a more lucid depiction of prediction uncertainty and its causes.« less

  8. 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.

  9. Optimization of the GBMV2 implicit solvent force field for accurate simulation of protein conformational equilibria.

    PubMed

    Lee, Kuo Hao; Chen, Jianhan

    2017-06-15

    Accurate treatment of solvent environment is critical for reliable simulations of protein conformational equilibria. Implicit treatment of solvation, such as using the generalized Born (GB) class of models arguably provides an optimal balance between computational efficiency and physical accuracy. Yet, GB models are frequently plagued by a tendency to generate overly compact structures. The physical origins of this drawback are relatively well understood, and the key to a balanced implicit solvent protein force field is careful optimization of physical parameters to achieve a sufficient level of cancellation of errors. The latter has been hampered by the difficulty of generating converged conformational ensembles of non-trivial model proteins using the popular replica exchange sampling technique. Here, we leverage improved sampling efficiency of a newly developed multi-scale enhanced sampling technique to re-optimize the generalized-Born with molecular volume (GBMV2) implicit solvent model with the CHARMM36 protein force field. Recursive optimization of key GBMV2 parameters (such as input radii) and protein torsion profiles (via the CMAP torsion cross terms) has led to a more balanced GBMV2 protein force field that recapitulates the structures and stabilities of both helical and β-hairpin model peptides. Importantly, this force field appears to be free of the over-compaction bias, and can generate structural ensembles of several intrinsically disordered proteins of various lengths that seem highly consistent with available experimental data. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  10. 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.

  11. Quantifying uncertainty and sensitivity in sea ice models

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

    Urrego Blanco, Jorge Rolando; Hunke, Elizabeth Clare; Urban, Nathan Mark

    The Los Alamos Sea Ice model has a number of input parameters for which accurate values are not always well established. We conduct a variance-based sensitivity analysis of hemispheric sea ice properties to 39 input parameters. The method accounts for non-linear and non-additive effects in the model.

  12. 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.

  13. SU-F-J-217: Accurate Dose Volume Parameters Calculation for Revealing Rectum Dose-Toxicity Effect Using Deformable Registration in Cervical Cancer Brachytherapy: A Pilot Study

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

    Zhen, X; Chen, H; Liao, Y

    Purpose: To study the feasibility of employing deformable registration methods for accurate rectum dose volume parameters calculation and their potentials in revealing rectum dose-toxicity between complication and non-complication cervical cancer patients with brachytherapy treatment. Method and Materials: Data from 60 patients treated with BT including planning images, treatment plans, and follow-up clinical exam were retrospectively collected. Among them, 12 patients complained about hematochezia were further examined with colonoscopy and scored as Grade 1–3 complication (CP). Meanwhile, another 12 non-complication (NCP) patients were selected as a reference group. To seek for potential gains in rectum toxicity prediction when fractional anatomical deformationsmore » are account for, the rectum dose volume parameters D0.1/1/2cc of the selected patients were retrospectively computed by three different approaches: the simple “worstcase scenario” (WS) addition method, an intensity-based deformable image registration (DIR) algorithm-Demons, and a more accurate, recent developed local topology preserved non-rigid point matching algorithm (TOP). Statistical significance of the differences between rectum doses of the CP group and the NCP group were tested by a two-tailed t-test and results were considered to be statistically significant if p < 0.05. Results: For the D0.1cc, no statistical differences are found between the CP and NCP group in all three methods. For the D1cc, dose difference is not detected by the WS method, however, statistical differences between the two groups are observed by both Demons and TOP, and more evident in TOP. For the D2cc, the CP and NCP cases are statistically significance of the difference for all three methods but more pronounced with TOP. Conclusion: In this study, we calculated the rectum D0.1/1/2cc by simple WS addition and two DIR methods and seek for gains in rectum toxicity prediction. The results favor the claim that

  14. Accurate Atmospheric Parameters at Moderate Resolution Using Spectral Indices: Preliminary Application to the MARVELS Survey

    NASA Astrophysics Data System (ADS)

    Ghezzi, Luan; Dutra-Ferreira, Letícia; Lorenzo-Oliveira, Diego; Porto de Mello, Gustavo F.; Santiago, Basílio X.; De Lee, Nathan; Lee, Brian L.; da Costa, Luiz N.; Maia, Marcio A. G.; Ogando, Ricardo L. C.; Wisniewski, John P.; González Hernández, Jonay I.; Stassun, Keivan G.; Fleming, Scott W.; Schneider, Donald P.; Mahadevan, Suvrath; Cargile, Phillip; Ge, Jian; Pepper, Joshua; Wang, Ji; Paegert, Martin

    2014-12-01

    Studies of Galactic chemical, and dynamical evolution in the solar neighborhood depend on the availability of precise atmospheric parameters (effective temperature T eff, metallicity [Fe/H], and surface gravity log g) for solar-type stars. Many large-scale spectroscopic surveys operate at low to moderate spectral resolution for efficiency in observing large samples, which makes the stellar characterization difficult due to the high degree of blending of spectral features. Therefore, most surveys employ spectral synthesis, which is a powerful technique, but relies heavily on the completeness and accuracy of atomic line databases and can yield possibly correlated atmospheric parameters. In this work, we use an alternative method based on spectral indices to determine the atmospheric parameters of a sample of nearby FGK dwarfs and subgiants observed by the MARVELS survey at moderate resolving power (R ~ 12,000). To avoid a time-consuming manual analysis, we have developed three codes to automatically normalize the observed spectra, measure the equivalent widths of the indices, and, through a comparison of those with values calculated with predetermined calibrations, estimate the atmospheric parameters of the stars. The calibrations were derived using a sample of 309 stars with precise stellar parameters obtained from the analysis of high-resolution FEROS spectra, permitting the low-resolution equivalent widths to be directly related to the stellar parameters. A validation test of the method was conducted with a sample of 30 MARVELS targets that also have reliable atmospheric parameters derived from the high-resolution spectra and spectroscopic analysis based on the excitation and ionization equilibria method. Our approach was able to recover the parameters within 80 K for T eff, 0.05 dex for [Fe/H], and 0.15 dex for log g, values that are lower than or equal to the typical external uncertainties found between different high-resolution analyses. An additional test was

  15. 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.

  16. 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.

  17. An integrated approach for the knowledge discovery in computer simulation models with a multi-dimensional parameter space

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

    Khawli, Toufik Al; Eppelt, Urs; Hermanns, Torsten

    2016-06-08

    In production industries, parameter identification, sensitivity analysis and multi-dimensional visualization are vital steps in the planning process for achieving optimal designs and gaining valuable information. Sensitivity analysis and visualization can help in identifying the most-influential parameters and quantify their contribution to the model output, reduce the model complexity, and enhance the understanding of the model behavior. Typically, this requires a large number of simulations, which can be both very expensive and time consuming when the simulation models are numerically complex and the number of parameter inputs increases. There are three main constituent parts in this work. The first part ismore » to substitute the numerical, physical model by an accurate surrogate model, the so-called metamodel. The second part includes a multi-dimensional visualization approach for the visual exploration of metamodels. In the third part, the metamodel is used to provide the two global sensitivity measures: i) the Elementary Effect for screening the parameters, and ii) the variance decomposition method for calculating the Sobol indices that quantify both the main and interaction effects. The application of the proposed approach is illustrated with an industrial application with the goal of optimizing a drilling process using a Gaussian laser beam.« less

  18. 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).

  19. Encoding of Spatio-Temporal Input Characteristics by a CA1 Pyramidal Neuron Model

    PubMed Central

    Pissadaki, Eleftheria Kyriaki; Sidiropoulou, Kyriaki; Reczko, Martin; Poirazi, Panayiota

    2010-01-01

    The in vivo activity of CA1 pyramidal neurons alternates between regular spiking and bursting, but how these changes affect information processing remains unclear. Using a detailed CA1 pyramidal neuron model, we investigate how timing and spatial arrangement variations in synaptic inputs to the distal and proximal dendritic layers influence the information content of model responses. We find that the temporal delay between activation of the two layers acts as a switch between excitability modes: short delays induce bursting while long delays decrease firing. For long delays, the average firing frequency of the model response discriminates spatially clustered from diffused inputs to the distal dendritic tree. For short delays, the onset latency and inter-spike-interval succession of model responses can accurately classify input signals as temporally close or distant and spatially clustered or diffused across different stimulation protocols. These findings suggest that a CA1 pyramidal neuron may be capable of encoding and transmitting presynaptic spatiotemporal information about the activity of the entorhinal cortex-hippocampal network to higher brain regions via the selective use of either a temporal or a rate code. PMID:21187899

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

    NASA Technical Reports Server (NTRS)

    Briggs, Maxwell H.; Schifer, Nicholas A.

    2012-01-01

    The U.S. Department of Energy (DOE) and Lockheed Martin Space Systems Company (LMSSC) have been developing the Advanced Stirling Radioisotope Generator (ASRG) for use as a power system for space science missions. This generator would use two high-efficiency Advanced Stirling Convertors (ASCs), developed by Sunpower Inc. and NASA Glenn Research Center (GRC). The ASCs convert thermal energy from a radioisotope heat source into electricity. As part of ground testing of these ASCs, different operating conditions are used to simulate expected mission conditions. These conditions require achieving a particular operating frequency, hot end and cold end temperatures, and specified electrical power output for a given net heat input. In an effort to improve net heat input predictions, numerous tasks have been performed which provided a more accurate value for net heat input into the ASCs, including testing validation hardware, known as the Thermal Standard, to provide a direct comparison to numerical and empirical models used to predict convertor net heat input. This validation hardware provided a comparison for scrutinizing and improving empirical correlations and numerical models of ASC-E2 net heat input. This hardware simulated the characteristics of an ASC-E2 convertor in both an operating and non-operating mode. This paper describes the Thermal Standard testing and the conclusions of the validation effort applied to the empirical correlation methods used by the Radioisotope Power System (RPS) team at NASA Glenn.

  1. 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.

  2. Accurate acoustic power measurement for low-intensity focused ultrasound using focal axial vibration velocity

    NASA Astrophysics Data System (ADS)

    Tao, Chenyang; Guo, Gepu; Ma, Qingyu; Tu, Juan; Zhang, Dong; Hu, Jimin

    2017-07-01

    Low-intensity focused ultrasound is a form of therapy that can have reversible acoustothermal effects on biological tissue, depending on the exposure parameters. The acoustic power (AP) should be chosen with caution for the sake of safety. To recover the energy of counteracted radial vibrations at the focal point, an accurate AP measurement method using the focal axial vibration velocity (FAVV) is proposed in explicit formulae and is demonstrated experimentally using a laser vibrometer. The experimental APs for two transducers agree well with theoretical calculations and numerical simulations, showing that AP is proportional to the square of the FAVV, with a fixed power gain determined by the physical parameters of the transducers. The favorable results suggest that the FAVV can be used as a valuable parameter for non-contact AP measurement, providing a new strategy for accurate power control for low-intensity focused ultrasound in biomedical engineering.

  3. Deriving stellar parameters with the SME software package

    NASA Astrophysics Data System (ADS)

    Piskunov, N.

    2017-09-01

    Photometry and spectroscopy are complementary tools for deriving accurate stellar parameters. Here I present one of the popular packages for stellar spectroscopy called SME with the emphasis on the latest developments and error assessment for the derived parameters.

  4. Accurate crop classification using hierarchical genetic fuzzy rule-based systems

    NASA Astrophysics Data System (ADS)

    Topaloglou, Charalampos A.; Mylonas, Stelios K.; Stavrakoudis, Dimitris G.; Mastorocostas, Paris A.; Theocharis, John B.

    2014-10-01

    This paper investigates the effectiveness of an advanced classification system for accurate crop classification using very high resolution (VHR) satellite imagery. Specifically, a recently proposed genetic fuzzy rule-based classification system (GFRBCS) is employed, namely, the Hierarchical Rule-based Linguistic Classifier (HiRLiC). HiRLiC's model comprises a small set of simple IF-THEN fuzzy rules, easily interpretable by humans. One of its most important attributes is that its learning algorithm requires minimum user interaction, since the most important learning parameters affecting the classification accuracy are determined by the learning algorithm automatically. HiRLiC is applied in a challenging crop classification task, using a SPOT5 satellite image over an intensively cultivated area in a lake-wetland ecosystem in northern Greece. A rich set of higher-order spectral and textural features is derived from the initial bands of the (pan-sharpened) image, resulting in an input space comprising 119 features. The experimental analysis proves that HiRLiC compares favorably to other interpretable classifiers of the literature, both in terms of structural complexity and classification accuracy. Its testing accuracy was very close to that obtained by complex state-of-the-art classification systems, such as the support vector machines (SVM) and random forest (RF) classifiers. Nevertheless, visual inspection of the derived classification maps shows that HiRLiC is characterized by higher generalization properties, providing more homogeneous classifications that the competitors. Moreover, the runtime requirements for producing the thematic map was orders of magnitude lower than the respective for the competitors.

  5. 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.

  6. 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.

  7. 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.

  8. Accurate ocean bottom seismometer positioning method inspired by multilateration technique

    USGS Publications Warehouse

    Benazzouz, Omar; Pinheiro, Luis M.; Matias, Luis M. A.; Afilhado, Alexandra; Herold, Daniel; Haines, Seth S.

    2018-01-01

    The positioning of ocean bottom seismometers (OBS) is a key step in the processing flow of OBS data, especially in the case of self popup types of OBS instruments. The use of first arrivals from airgun shots, rather than relying on the acoustic transponders mounted in the OBS, is becoming a trend and generally leads to more accurate positioning due to the statistics from a large number of shots. In this paper, a linearization of the OBS positioning problem via the multilateration technique is discussed. The discussed linear solution solves jointly for the average water layer velocity and the OBS position using only shot locations and first arrival times as input data.

  9. 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.

  10. An accurate halo model for fitting non-linear cosmological power spectra and baryonic feedback models

    NASA Astrophysics Data System (ADS)

    Mead, A. J.; Peacock, J. A.; Heymans, C.; Joudaki, S.; Heavens, A. F.

    2015-12-01

    We present an optimized variant of the halo model, designed to produce accurate matter power spectra well into the non-linear regime for a wide range of cosmological models. To do this, we introduce physically motivated free parameters into the halo-model formalism and fit these to data from high-resolution N-body simulations. For a variety of Λ cold dark matter (ΛCDM) and wCDM models, the halo-model power is accurate to ≃ 5 per cent for k ≤ 10h Mpc-1 and z ≤ 2. An advantage of our new halo model is that it can be adapted to account for the effects of baryonic feedback on the power spectrum. We demonstrate this by fitting the halo model to power spectra from the OWLS (OverWhelmingly Large Simulations) hydrodynamical simulation suite via parameters that govern halo internal structure. We are able to fit all feedback models investigated at the 5 per cent level using only two free parameters, and we place limits on the range of these halo parameters for feedback models investigated by the OWLS simulations. Accurate predictions to high k are vital for weak-lensing surveys, and these halo parameters could be considered nuisance parameters to marginalize over in future analyses to mitigate uncertainty regarding the details of feedback. Finally, we investigate how lensing observables predicted by our model compare to those from simulations and from HALOFIT for a range of k-cuts and feedback models and quantify the angular scales at which these effects become important. Code to calculate power spectra from the model presented in this paper can be found at https://github.com/alexander-mead/hmcode.

  11. 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.

  12. Development of an Input Suite for an Orthotropic Composite Material Model

    NASA Technical Reports Server (NTRS)

    Hoffarth, Canio; Shyamsunder, Loukham; Khaled, Bilal; Rajan, Subramaniam; Goldberg, Robert K.; Carney, Kelly S.; Dubois, Paul; Blankenhorn, Gunther

    2017-01-01

    An orthotropic three-dimensional material model suitable for use in modeling impact tests has been developed that has three major components elastic and inelastic deformations, damage and failure. The material model has been implemented as MAT213 into a special version of LS-DYNA and uses tabulated data obtained from experiments. The prominent features of the constitutive model are illustrated using a widely-used aerospace composite the T800S3900-2B[P2352W-19] BMS8-276 Rev-H-Unitape fiber resin unidirectional composite. The input for the deformation model consists of experimental data from 12 distinct experiments at a known temperature and strain rate: tension and compression along all three principal directions, shear in all three principal planes, and off axis tension or compression tests in all three principal planes, along with other material constants. There are additional input associated with the damage and failure models. The steps in using this model are illustrated composite characterization tests, verification tests and a validation test. The results show that the developed and implemented model is stable and yields acceptably accurate results.

  13. 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.

  14. 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.

  15. 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

  16. A novel AIF tracking method and comparison of DCE-MRI parameters using individual and population-based AIFs in human breast cancer

    NASA Astrophysics Data System (ADS)

    Li, Xia; Welch, E. Brian; Arlinghaus, Lori R.; Bapsi Chakravarthy, A.; Xu, Lei; Farley, Jaime; Loveless, Mary E.; Mayer, Ingrid A.; Kelley, Mark C.; Meszoely, Ingrid M.; Means-Powell, Julie A.; Abramson, Vandana G.; Grau, Ana M.; Gore, John C.; Yankeelov, Thomas E.

    2011-09-01

    Quantitative analysis of dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) data requires the accurate determination of the arterial input function (AIF). A novel method for obtaining the AIF is presented here and pharmacokinetic parameters derived from individual and population-based AIFs are then compared. A Philips 3.0 T Achieva MR scanner was used to obtain 20 DCE-MRI data sets from ten breast cancer patients prior to and after one cycle of chemotherapy. Using a semi-automated method to estimate the AIF from the axillary artery, we obtain the AIF for each patient, AIFind, and compute a population-averaged AIF, AIFpop. The extended standard model is used to estimate the physiological parameters using the two types of AIFs. The mean concordance correlation coefficient (CCC) for the AIFs segmented manually and by the proposed AIF tracking approach is 0.96, indicating accurate and automatic tracking of an AIF in DCE-MRI data of the breast is possible. Regarding the kinetic parameters, the CCC values for Ktrans, vp and ve as estimated by AIFind and AIFpop are 0.65, 0.74 and 0.31, respectively, based on the region of interest analysis. The average CCC values for the voxel-by-voxel analysis are 0.76, 0.84 and 0.68 for Ktrans, vp and ve, respectively. This work indicates that Ktrans and vp show good agreement between AIFpop and AIFind while there is a weak agreement on ve.

  17. 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.

  18. 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

  19. 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.

  20. 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

  1. 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.

  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

    2018-06-01

    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.

  3. 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.

  4. The effect of noise and lipid signals on determination of Gaussian and non-Gaussian diffusion parameters in skeletal muscle.

    PubMed

    Cameron, Donnie; Bouhrara, Mustapha; Reiter, David A; Fishbein, Kenneth W; Choi, Seongjin; Bergeron, Christopher M; Ferrucci, Luigi; Spencer, Richard G

    2017-07-01

    This work characterizes the effect of lipid and noise signals on muscle diffusion parameter estimation in several conventional and non-Gaussian models, the ultimate objectives being to characterize popular fat suppression approaches for human muscle diffusion studies, to provide simulations to inform experimental work and to report normative non-Gaussian parameter values. The models investigated in this work were the Gaussian monoexponential and intravoxel incoherent motion (IVIM) models, and the non-Gaussian kurtosis and stretched exponential models. These were evaluated via simulations, and in vitro and in vivo experiments. Simulations were performed using literature input values, modeling fat contamination as an additive baseline to data, whereas phantom studies used a phantom containing aliphatic and olefinic fats and muscle-like gel. Human imaging was performed in the hamstring muscles of 10 volunteers. Diffusion-weighted imaging was applied with spectral attenuated inversion recovery (SPAIR), slice-select gradient reversal and water-specific excitation fat suppression, alone and in combination. Measurement bias (accuracy) and dispersion (precision) were evaluated, together with intra- and inter-scan repeatability. Simulations indicated that noise in magnitude images resulted in <6% bias in diffusion coefficients and non-Gaussian parameters (α, K), whereas baseline fitting minimized fat bias for all models, except IVIM. In vivo, popular SPAIR fat suppression proved inadequate for accurate parameter estimation, producing non-physiological parameter estimates without baseline fitting and large biases when it was used. Combining all three fat suppression techniques and fitting data with a baseline offset gave the best results of all the methods studied for both Gaussian diffusion and, overall, for non-Gaussian diffusion. It produced consistent parameter estimates for all models, except IVIM, and highlighted non-Gaussian behavior perpendicular to muscle fibers (

  5. Molybdenum disulfide and water interaction parameters

    NASA Astrophysics Data System (ADS)

    Heiranian, Mohammad; Wu, Yanbin; Aluru, Narayana R.

    2017-09-01

    Understanding the interaction between water and molybdenum disulfide (MoS2) is of crucial importance to investigate the physics of various applications involving MoS2 and water interfaces. An accurate force field is required to describe water and MoS2 interactions. In this work, water-MoS2 force field parameters are derived using the high-accuracy random phase approximation (RPA) method and validated by comparing to experiments. The parameters obtained from the RPA method result in water-MoS2 interface properties (solid-liquid work of adhesion) in good comparison to the experimental measurements. An accurate description of MoS2-water interaction will facilitate the study of MoS2 in applications such as DNA sequencing, sea water desalination, and power generation.

  6. 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

  7. Increasing the productivity of glycopeptides analysis by using higher-energy collision dissociation-accurate mass-product-dependent electron transfer dissociation.

    PubMed

    Saba, Julian; Dutta, Sucharita; Hemenway, Eric; Viner, Rosa

    2012-01-01

    Currently, glycans are attracting attention from the scientific community as potential biomarkers or as posttranslational modifications (PTMs) of therapeutic proteins. However, structural characterization of glycoproteins and glycopeptides remains analytically challenging. Here, we report on the implementation of a novel acquisition strategy termed higher-energy collision dissociation-accurate mass-product-dependent electron transfer dissociation (HCD-PD-ETD) on a hybrid linear ion trap-orbitrap mass spectrometer. This acquisition strategy uses the complementary fragmentations of ETD and HCD for glycopeptides analysis in an intelligent fashion. Furthermore, the approach minimizes user input for optimizing instrumental parameters and enables straightforward detection of glycopeptides. ETD spectra are only acquired when glycan oxonium ions from MS/MS HCD are detected. The advantage of this approach is that it streamlines data analysis and improves dynamic range and duty cycle. Here, we present the benefits of HCD-PD-ETD relative to the traditional alternating HCD/ETD for a trainer set containing twelve-protein mixture with two glycoproteins: human serotransferrin, ovalbumin and contaminations of two other: bovine alpha 1 acid glycoprotein (bAGP) and bovine fetuin.

  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. Characterization of a signal recording system for accurate velocity estimation using a VISAR

    NASA Astrophysics Data System (ADS)

    Rav, Amit; Joshi, K. D.; Singh, Kulbhushan; Kaushik, T. C.

    2018-02-01

    The linearity of a signal recording system (SRS) in time as well as in amplitude are important for the accurate estimation of the free surface velocity history of a moving target during shock loading and unloading when measured using optical interferometers such as a velocity interferometer system for any reflector (VISAR). Signal recording being the first step in a long sequence of signal processes, the incorporation of errors due to nonlinearity, and low signal-to-noise ratio (SNR) affects the overall accuracy and precision of the estimation of velocity history. In shock experiments the small duration (a few µs) of loading/unloading, the reflectivity of moving target surface, and the properties of optical components, control the amount of input of light to the SRS of a VISAR and this in turn affects the linearity and SNR of the overall measurement. These factors make it essential to develop in situ procedures for (i) minimizing the effect of signal induced noise and (ii) determine the linear region of operation for the SRS. Here we report on a procedure for the optimization of SRS parameters such as photodetector gain, optical power, aperture etc, so as to achieve a linear region of operation with a high SNR. The linear region of operation so determined has been utilized successfully to estimate the temporal history of the free surface velocity of the moving target in shock experiments.

  10. A convenient and accurate wide-range parameter relationship between Buckingham and Morse potential energy functions

    NASA Astrophysics Data System (ADS)

    Lim, Teik-Cheng; Dawson, James Alexander

    2018-05-01

    This study explores the close-range, short-range and long-range relationships between the parameters of the Morse and Buckingham potential energy functions. The results show that the close-range and short-range relationships are valid for bond compression and for very small changes in bond length, respectively, while the long-range relationship is valid for bond stretching. A wide-range relationship is proposed to combine the comparative advantages of the close-range, short-range and long-range parameter relationships. The wide-range relationship is useful for replacing the close-range, short-range and long-range parameter relationships, thereby preventing the undesired effects of potential energy jumps resulting from functional switching between the close-range, short-range and long-range interaction energies.

  11. The quality of photometric information in the Hipparcos Input Catalog

    NASA Technical Reports Server (NTRS)

    Casertano, Stefano; Bell, David J.; Ratnatunga, Kavan U.; Yoss, Kenneth M.

    1993-01-01

    Comparison with independent photoelectric photometry is used to assess the quality of magnitudes and colors in the Hipparcos Input Catalog. These magnitudes and colors will play an important role in the luminosity calibration of Hipparcos stars. We conclude that photoelectric photometry, available for about 37 percent of the catalog, is of uniformly good quality, and the error estimates in the Catalog are very accurate. On the other hand, colors determined from poor spectral classes suffer from very significant errors, also correctly estimated in the Catalog, which make them essentially unsuited for the purpose of luminosity calibration. Only stars with either photoelectric colors or good 2D spectral classes can be used in a high-accuracy luminosity calibration.

  12. Accurate atomistic first-principles calculations of electronic stopping

    DOE PAGES

    Schleife, André; Kanai, Yosuke; Correa, Alfredo A.

    2015-01-20

    In this paper, we show that atomistic first-principles calculations based on real-time propagation within time-dependent density functional theory are capable of accurately describing electronic stopping of light projectile atoms in metal hosts over a wide range of projectile velocities. In particular, we employ a plane-wave pseudopotential scheme to solve time-dependent Kohn-Sham equations for representative systems of H and He projectiles in crystalline aluminum. This approach to simulate nonadiabatic electron-ion interaction provides an accurate framework that allows for quantitative comparison with experiment without introducing ad hoc parameters such as effective charges, or assumptions about the dielectric function. Finally, our work clearlymore » shows that this atomistic first-principles description of electronic stopping is able to disentangle contributions due to tightly bound semicore electrons and geometric aspects of the stopping geometry (channeling versus off-channeling) in a wide range of projectile velocities.« less

  13. Inverse methods for estimating primary input signals from time-averaged isotope profiles

    NASA Astrophysics Data System (ADS)

    Passey, Benjamin H.; Cerling, Thure E.; Schuster, Gerard T.; Robinson, Todd F.; Roeder, Beverly L.; Krueger, Stephen K.

    2005-08-01

    Mammalian teeth are invaluable archives of ancient seasonality because they record along their growth axes an isotopic record of temporal change in environment, plant diet, and animal behavior. A major problem with the intra-tooth method is that intra-tooth isotope profiles can be extremely time-averaged compared to the actual pattern of isotopic variation experienced by the animal during tooth formation. This time-averaging is a result of the temporal and spatial characteristics of amelogenesis (tooth enamel formation), and also results from laboratory sampling. This paper develops and evaluates an inverse method for reconstructing original input signals from time-averaged intra-tooth isotope profiles. The method requires that the temporal and spatial patterns of amelogenesis are known for the specific tooth and uses a minimum length solution of the linear system Am = d, where d is the measured isotopic profile, A is a matrix describing temporal and spatial averaging during amelogenesis and sampling, and m is the input vector that is sought. Accuracy is dependent on several factors, including the total measurement error and the isotopic structure of the measured profile. The method is shown to accurately reconstruct known input signals for synthetic tooth enamel profiles and the known input signal for a rabbit that underwent controlled dietary changes. Application to carbon isotope profiles of modern hippopotamus canines reveals detailed dietary histories that are not apparent from the measured data alone. Inverse methods show promise as an effective means of dealing with the time-averaging problem in studies of intra-tooth isotopic variation.

  14. Is 50 Hz high enough ECG sampling frequency for accurate HRV analysis?

    PubMed

    Mahdiani, Shadi; Jeyhani, Vala; Peltokangas, Mikko; Vehkaoja, Antti

    2015-01-01

    With the worldwide growth of mobile wireless technologies, healthcare services can be provided at anytime and anywhere. Usage of wearable wireless physiological monitoring system has been extensively increasing during the last decade. These mobile devices can continuously measure e.g. the heart activity and wirelessly transfer the data to the mobile phone of the patient. One of the significant restrictions for these devices is usage of energy, which leads to requiring low sampling rate. This article is presented in order to investigate the lowest adequate sampling frequency of ECG signal, for achieving accurate enough time domain heart rate variability (HRV) parameters. For this purpose the ECG signals originally measured with high 5 kHz sampling rate were down-sampled to simulate the measurement with lower sampling rate. Down-sampling loses information, decreases temporal accuracy, which was then restored by interpolating the signals to their original sampling rates. The HRV parameters obtained from the ECG signals with lower sampling rates were compared. The results represent that even when the sampling rate of ECG signal is equal to 50 Hz, the HRV parameters are almost accurate with a reasonable error.

  15. 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.

  16. 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…

  17. ACCURATE CHARACTERIZATION OF HIGH-DEGREE MODES USING MDI OBSERVATIONS

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

    Korzennik, S. G.; Rabello-Soares, M. C.; Schou, J.

    2013-08-01

    We present the first accurate characterization of high-degree modes, derived using the best Michelson Doppler Imager (MDI) full-disk full-resolution data set available. A 90 day long time series of full-disk 2 arcsec pixel{sup -1} resolution Dopplergrams was acquired in 2001, thanks to the high rate telemetry provided by the Deep Space Network. These Dopplergrams were spatially decomposed using our best estimate of the image scale and the known components of MDI's image distortion. A multi-taper power spectrum estimator was used to generate power spectra for all degrees and all azimuthal orders, up to l = 1000. We used a largemore » number of tapers to reduce the realization noise, since at high degrees the individual modes blend into ridges and thus there is no reason to preserve a high spectral resolution. These power spectra were fitted for all degrees and all azimuthal orders, between l = 100 and l = 1000, and for all the orders with substantial amplitude. This fitting generated in excess of 5.2 Multiplication-Sign 10{sup 6} individual estimates of ridge frequencies, line widths, amplitudes, and asymmetries (singlets), corresponding to some 5700 multiplets (l, n). Fitting at high degrees generates ridge characteristics, characteristics that do not correspond to the underlying mode characteristics. We used a sophisticated forward modeling to recover the best possible estimate of the underlying mode characteristics (mode frequencies, as well as line widths, amplitudes, and asymmetries). We describe in detail this modeling and its validation. The modeling has been extensively reviewed and refined, by including an iterative process to improve its input parameters to better match the observations. Also, the contribution of the leakage matrix on the accuracy of the procedure has been carefully assessed. We present the derived set of corrected mode characteristics, which includes not only frequencies, but line widths, asymmetries, and amplitudes. We present and

  18. Simple method for quick estimation of aquifer hydrogeological parameters

    NASA Astrophysics Data System (ADS)

    Ma, C.; Li, Y. Y.

    2017-08-01

    Development of simple and accurate methods to determine the aquifer hydrogeological parameters was of importance for groundwater resources assessment and management. Aiming at the present issue of estimating aquifer parameters based on some data of the unsteady pumping test, a fitting function of Theis well function was proposed using fitting optimization method and then a unitary linear regression equation was established. The aquifer parameters could be obtained by solving coefficients of the regression equation. The application of the proposed method was illustrated, using two published data sets. By the error statistics and analysis on the pumping drawdown, it showed that the method proposed in this paper yielded quick and accurate estimates of the aquifer parameters. The proposed method could reliably identify the aquifer parameters from long distance observed drawdowns and early drawdowns. It was hoped that the proposed method in this paper would be helpful for practicing hydrogeologists and hydrologists.

  19. Transmission Electron Microscope Measures Lattice Parameters

    NASA Technical Reports Server (NTRS)

    Pike, William T.

    1996-01-01

    Convergent-beam microdiffraction (CBM) in thermionic-emission transmission electron microscope (TEM) is technique for measuring lattice parameters of nanometer-sized specimens of crystalline materials. Lattice parameters determined by use of CBM accurate to within few parts in thousand. Technique developed especially for use in quantifying lattice parameters, and thus strains, in epitaxial mismatched-crystal-lattice multilayer structures in multiple-quantum-well and other advanced semiconductor electronic devices. Ability to determine strains in indivdual layers contributes to understanding of novel electronic behaviors of devices.

  20. Multiscale Methods for Accurate, Efficient, and Scale-Aware Models of the Earth System

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

    Goldhaber, Steve; Holland, Marika

    The major goal of this project was to contribute improvements to the infrastructure of an Earth System Model in order to support research in the Multiscale Methods for Accurate, Efficient, and Scale-Aware models of the Earth System project. In support of this, the NCAR team accomplished two main tasks: improving input/output performance of the model and improving atmospheric model simulation quality. Improvement of the performance and scalability of data input and diagnostic output within the model required a new infrastructure which can efficiently handle the unstructured grids common in multiscale simulations. This allows for a more computationally efficient model, enablingmore » more years of Earth System simulation. The quality of the model simulations was improved by reducing grid-point noise in the spectral element version of the Community Atmosphere Model (CAM-SE). This was achieved by running the physics of the model using grid-cell data on a finite-volume grid.« less

  1. On the use of published radiobiological parameters and the evaluation of NTCP models regarding lung pneumonitis in clinical breast radiotherapy.

    PubMed

    Svolos, Patricia; Tsougos, Ioannis; Kyrgias, Georgios; Kappas, Constantine; Theodorou, Kiki

    2011-04-01

    In this study we sought to evaluate and accent the importance of radiobiological parameter selection and implementation to the normal tissue complication probability (NTCP) models. The relative seriality (RS) and the Lyman-Kutcher-Burman (LKB) models were studied. For each model, a minimum and maximum set of radiobiological parameter sets was selected from the overall published sets applied in literature and a theoretical mean parameter set was computed. In order to investigate the potential model weaknesses in NTCP estimation and to point out the correct use of model parameters, these sets were used as input to the RS and the LKB model, estimating radiation induced complications for a group of 36 breast cancer patients treated with radiotherapy. The clinical endpoint examined was Radiation Pneumonitis. Each model was represented by a certain dose-response range when the selected parameter sets were applied. Comparing the models with their ranges, a large area of coincidence was revealed. If the parameter uncertainties (standard deviation) are included in the models, their area of coincidence might be enlarged, constraining even greater their predictive ability. The selection of the proper radiobiological parameter set for a given clinical endpoint is crucial. Published parameter values are not definite but should be accompanied by uncertainties, and one should be very careful when applying them to the NTCP models. Correct selection and proper implementation of published parameters provides a quite accurate fit of the NTCP models to the considered endpoint.

  2. 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.

  3. Neutron diffraction measurements and micromechanical modelling of temperature-dependent variations in TATB lattice parameters

    DOE PAGES

    Yeager, John D.; Luscher, Darby J.; Vogel, Sven C.; ...

    2016-02-02

    Triaminotrinitrobenzene (TATB) is a highly anisotropic molecular crystal used in several plastic-bonded explosive (PBX) formulations. TATB-based explosives exhibit irreversible volume expansion (“ratchet growth”) when thermally cycled. A theoretical understanding of the relationship between anisotropy of the crystal, crystal orientation distribution (texture) of polycrystalline aggregates, and the intergranular interactions leading to this irreversible growth is necessary to accurately develop physics-based predictive models for TATB-based PBXs under various thermal environments. In this work, TATB lattice parameters were measured using neutron diffraction during thermal cycling of loose powder and a pressed pellet. The measured lattice parameters help clarify conflicting reports in the literaturemore » as these new results are more consistent with one set of previous results than another. The lattice parameters of pressed TATB were also measured as a function of temperature, showing some differences from the powder. This data is used along with anisotropic single-crystal stiffness moduli reported in the literature to model the nominal stresses associated with intergranular constraints during thermal expansion. The texture of both specimens were characterized and the pressed pellet exhibits preferential orientation of (001) poles along the pressing direction, whereas no preferred orientation was found for the loose powder. Lastly, thermal strains for single-crystal TATB computed from lattice parameter data for the powder is input to a self-consistent micromechanical model, which predicts the lattice parameters of the constrained TATB crystals within the pellet. The agreement of these model results with the diffraction data obtained from the pellet is discussed along with future directions of research.« less

  4. 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.

  5. 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

  6. 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

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. Tracheo-bronchial soft tissue and cartilage resonances in the subglottal acoustic input impedance.

    PubMed

    Lulich, Steven M; Arsikere, Harish

    2015-06-01

    This paper offers a re-evaluation of the mechanical properties of the tracheo-bronchial soft tissues and cartilage and uses a model to examine their effects on the subglottal acoustic input impedance. It is shown that the values for soft tissue elastance and cartilage viscosity typically used in models of subglottal acoustics during phonation are not accurate, and corrected values are proposed. The calculated subglottal acoustic input impedance using these corrected values reveals clusters of weak resonances due to soft tissues (SgT) and cartilage (SgC) lining the walls of the trachea and large bronchi, which can be observed empirically in subglottal acoustic spectra. The model predicts that individuals may exhibit SgT and SgC resonances to variable degrees, depending on a number of factors including tissue mechanical properties and the dimensions of the trachea and large bronchi. Potential implications for voice production and large pulmonary airway tissue diseases are also discussed.

  12. Design and evaluation of nonverbal sound-based input for those with motor handicapped.

    PubMed

    Punyabukkana, Proadpran; Chanjaradwichai, Supadaech; Suchato, Atiwong

    2013-03-01

    Most personal computing interfaces rely on the users' ability to use their hand and arm movements to interact with on-screen graphical widgets via mainstream devices, including keyboards and mice. Without proper assistive devices, this style of input poses difficulties for motor-handicapped users. We propose a sound-based input scheme enabling users to operate Windows' Graphical User Interface by producing hums and fricatives through regular microphones. Hierarchically arranged menus are utilized so that only minimal numbers of different actions are required at a time. The proposed scheme was found to be accurate and capable of responding promptly compared to other sound-based schemes. Being able to select from multiple item-selecting modes helps reducing the average time duration needed for completing tasks in the test scenarios almost by half the time needed when the tasks were performed solely through cursor movements. Still, improvements on facilitating users to select the most appropriate modes for desired tasks should improve the overall usability of the proposed scheme.

  13. 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.

  14. 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.

  15. 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

  16. Constitutive parameter measurements of lossy materials

    NASA Technical Reports Server (NTRS)

    Dominek, A.; Park, A.

    1989-01-01

    The electrical constitutive parameters of lossy materials are considered. A discussion of the NRL arch for lossy coatings is presented involving analytical analyses of the reflected field using the geometrical theory of diffraction (GTD) and physical optics (PO). The actual values for these parameters can be obtained through a traditional transmission technique which is examined from an error analysis standpoint. Alternate sample geometries are suggested for this technique to reduce sample tolerance requirements for accurate parameter determination. The performance for one alternate geometry is given.

  17. Anisotropic effects on constitutive model parameters of aluminum alloys

    NASA Astrophysics Data System (ADS)

    Brar, Nachhatter S.; Joshi, Vasant S.

    2012-03-01

    Simulation of low velocity impact on structures or high velocity penetration in armor materials heavily rely on constitutive material models. Model constants are determined from tension, compression or torsion stress-strain at low and high strain rates at different temperatures. These model constants are required input to computer codes (LS-DYNA, DYNA3D or SPH) to accurately simulate fragment impact on structural components made of high strength 7075-T651 aluminum alloy. Johnson- Cook model constants determined for Al7075-T651 alloy bar material failed to simulate correctly the penetration into 1' thick Al-7075-T651plates. When simulation go well beyond minor parameter tweaking and experimental results show drastically different behavior it becomes important to determine constitutive parameters from the actual material used in impact/penetration experiments. To investigate anisotropic effects on the yield/flow stress of this alloy quasi-static and high strain rate tensile tests were performed on specimens fabricated in the longitudinal "L", transverse "T", and thickness "TH" directions of 1' thick Al7075 Plate. While flow stress at a strain rate of ~1/s as well as ~1100/s in the thickness and transverse directions are lower than the longitudinal direction. The flow stress in the bar was comparable to flow stress in the longitudinal direction of the plate. Fracture strain data from notched tensile specimens fabricated in the L, T, and Thickness directions of 1' thick plate are used to derive fracture constants.

  18. 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.

  19. 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.

  20. Selection of Wire Electrical Discharge Machining Process Parameters on Stainless Steel AISI Grade-304 using Design of Experiments Approach

    NASA Astrophysics Data System (ADS)

    Lingadurai, K.; Nagasivamuni, B.; Muthu Kamatchi, M.; Palavesam, J.

    2012-06-01

    Wire electrical discharge machining (WEDM) is a specialized thermal machining process capable of accurately machining parts of hard materials with complex shapes. Parts having sharp edges that pose difficulties to be machined by the main stream machining processes can be easily machined by WEDM process. Design of Experiments approach (DOE) has been reported in this work for stainless steel AISI grade-304 which is used in cryogenic vessels, evaporators, hospital surgical equipment, marine equipment, fasteners, nuclear vessels, feed water tubing, valves, refrigeration equipment, etc., is machined by WEDM with brass wire electrode. The DOE method is used to formulate the experimental layout, to analyze the effect of each parameter on the machining characteristics, and to predict the optimal choice for each WEDM parameter such as voltage, pulse ON, pulse OFF and wire feed. It is found that these parameters have a significant influence on machining characteristic such as metal removal rate (MRR), kerf width and surface roughness (SR). The analysis of the DOE reveals that, in general the pulse ON time significantly affects the kerf width and the wire feed rate affects SR, while, the input voltage mainly affects the MRR.

  1. Assessing the accuracy of subject-specific, muscle-model parameters determined by optimizing to match isometric strength.

    PubMed

    DeSmitt, Holly J; Domire, Zachary J

    2016-12-01

    Biomechanical models are sensitive to the choice of model parameters. Therefore, determination of accurate subject specific model parameters is important. One approach to generate these parameters is to optimize the values such that the model output will match experimentally measured strength curves. This approach is attractive as it is inexpensive and should provide an excellent match to experimentally measured strength. However, given the problem of muscle redundancy, it is not clear that this approach generates accurate individual muscle forces. The purpose of this investigation is to evaluate this approach using simulated data to enable a direct comparison. It is hypothesized that the optimization approach will be able to recreate accurate muscle model parameters when information from measurable parameters is given. A model of isometric knee extension was developed to simulate a strength curve across a range of knee angles. In order to realistically recreate experimentally measured strength, random noise was added to the modeled strength. Parameters were solved for using a genetic search algorithm. When noise was added to the measurements the strength curve was reasonably recreated. However, the individual muscle model parameters and force curves were far less accurate. Based upon this examination, it is clear that very different sets of model parameters can recreate similar strength curves. Therefore, experimental variation in strength measurements has a significant influence on the results. Given the difficulty in accurately recreating individual muscle parameters, it may be more appropriate to perform simulations with lumped actuators representing similar muscles.

  2. Accurate modeling of defects in graphene transport calculations

    NASA Astrophysics Data System (ADS)

    Linhart, Lukas; Burgdörfer, Joachim; Libisch, Florian

    2018-01-01

    We present an approach for embedding defect structures modeled by density functional theory into large-scale tight-binding simulations. We extract local tight-binding parameters for the vicinity of the defect site using Wannier functions. In the transition region between the bulk lattice and the defect the tight-binding parameters are continuously adjusted to approach the bulk limit far away from the defect. This embedding approach allows for an accurate high-level treatment of the defect orbitals using as many as ten nearest neighbors while keeping a small number of nearest neighbors in the bulk to render the overall computational cost reasonable. As an example of our approach, we consider an extended graphene lattice decorated with Stone-Wales defects, flower defects, double vacancies, or silicon substitutes. We predict distinct scattering patterns mirroring the defect symmetries and magnitude that should be experimentally accessible.

  3. THE HYPERFINE STRUCTURE OF THE ROTATIONAL SPECTRUM OF HDO AND ITS EXTENSION TO THE THz REGION: ACCURATE REST FREQUENCIES AND SPECTROSCOPIC PARAMETERS FOR ASTROPHYSICAL OBSERVATIONS

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

    Cazzoli, Gabriele; Lattanzi, Valerio; Puzzarini, Cristina

    2015-06-10

    The rotational spectrum of the mono-deuterated isotopologue of water, HD{sup 16}O, has been investigated in the millimeter- and submillimeter-wave frequency regions, up to 1.6 THz. The Lamb-dip technique has been exploited to obtain sub-Doppler resolution and to resolve the hyperfine (hf) structure due to the deuterium and hydrogen nuclei, thus enabling the accurate determination of the corresponding hf parameters. Their experimental determination has been supported by high-level quantum-chemical calculations. The Lamb-dip measurements have been supplemented by Doppler-limited measurements (weak high-J and high-frequency transitions) in order to extend the predictive capability of the available spectroscopic constants. The possibility of resolving hfmore » splittings in astronomical spectra has been discussed.« less

  4. Guidelines for the Selection of Near-Earth Thermal Environment Parameters for Spacecraft Design

    NASA Technical Reports Server (NTRS)

    Anderson, B. J.; Justus, C. G.; Batts, G. W.

    2001-01-01

    Thermal analysis and design of Earth orbiting systems requires specification of three environmental thermal parameters: the direct solar irradiance, Earth's local albedo, and outgoing longwave radiance (OLR). In the early 1990s data sets from the Earth Radiation Budget Experiment were analyzed on behalf of the Space Station Program to provide an accurate description of these parameters as a function of averaging time along the orbital path. This information, documented in SSP 30425 and, in more generic form in NASA/TM-4527, enabled the specification of the proper thermal parameters for systems of various thermal response time constants. However, working with the engineering community and SSP-30425 and TM-4527 products over a number of years revealed difficulties in interpretation and application of this material. For this reason it was decided to develop this guidelines document to help resolve these issues of practical application. In the process, the data were extensively reprocessed and a new computer code, the Simple Thermal Environment Model (STEM) was developed to simplify the process of selecting the parameters for input into extreme hot and cold thermal analyses and design specifications. In the process, greatly improved values for the cold case OLR values for high inclination orbits were derived. Thermal parameters for satellites in low, medium, and high inclination low-Earth orbit and with various system thermal time constraints are recommended for analysis of extreme hot and cold conditions. Practical information as to the interpretation and application of the information and an introduction to the STEM are included. Complete documentation for STEM is found in the user's manual, in preparation.

  5. 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.

  6. Pilot study of a novel tool for input-free automated identification of transition zone prostate tumors using T2- and diffusion-weighted signal and textural features.

    PubMed

    Stember, Joseph N; Deng, Fang-Ming; Taneja, Samir S; Rosenkrantz, Andrew B

    2014-08-01

    To present results of a pilot study to develop software that identifies regions suspicious for prostate transition zone (TZ) tumor, free of user input. Eight patients with TZ tumors were used to develop the model by training a Naïve Bayes classifier to detect tumors based on selection of most accurate predictors among various signal and textural features on T2-weighted imaging (T2WI) and apparent diffusion coefficient (ADC) maps. Features tested as inputs were: average signal, signal standard deviation, energy, contrast, correlation, homogeneity and entropy (all defined on T2WI); and average ADC. A forward selection scheme was used on the remaining 20% of training set supervoxels to identify important inputs. The trained model was tested on a different set of ten patients, half with TZ tumors. In training cases, the software tiled the TZ with 4 × 4-voxel "supervoxels," 80% of which were used to train the classifier. Each of 100 iterations selected T2WI energy and average ADC, which therefore were deemed the optimal model input. The two-feature model was applied blindly to the separate set of test patients, again without operator input of suspicious foci. The software correctly predicted presence or absence of TZ tumor in all test patients. Furthermore, locations of predicted tumors corresponded spatially with locations of biopsies that had confirmed their presence. Preliminary findings suggest that this tool has potential to accurately predict TZ tumor presence and location, without operator input. © 2013 Wiley Periodicals, Inc.

  7. Kalman filter data assimilation: targeting observations and parameter estimation.

    PubMed

    Bellsky, Thomas; Kostelich, Eric J; Mahalov, Alex

    2014-06-01

    This paper studies the effect of targeted observations on state and parameter estimates determined with Kalman filter data assimilation (DA) techniques. We first provide an analytical result demonstrating that targeting observations within the Kalman filter for a linear model can significantly reduce state estimation error as opposed to fixed or randomly located observations. We next conduct observing system simulation experiments for a chaotic model of meteorological interest, where we demonstrate that the local ensemble transform Kalman filter (LETKF) with targeted observations based on largest ensemble variance is skillful in providing more accurate state estimates than the LETKF with randomly located observations. Additionally, we find that a hybrid ensemble Kalman filter parameter estimation method accurately updates model parameters within the targeted observation context to further improve state estimation.

  8. 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.

  9. A comparison of numerical and machine-learning modeling of soil water content with limited input data

    NASA Astrophysics Data System (ADS)

    Karandish, Fatemeh; Šimůnek, Jiří

    2016-12-01

    Soil water content (SWC) is a key factor in optimizing the usage of water resources in agriculture since it provides information to make an accurate estimation of crop water demand. Methods for predicting SWC that have simple data requirements are needed to achieve an optimal irrigation schedule, especially for various water-saving irrigation strategies that are required to resolve both food and water security issues under conditions of water shortages. Thus, a two-year field investigation was carried out to provide a dataset to compare the effectiveness of HYDRUS-2D, a physically-based numerical model, with various machine-learning models, including Multiple Linear Regressions (MLR), Adaptive Neuro-Fuzzy Inference Systems (ANFIS), and Support Vector Machines (SVM), for simulating time series of SWC data under water stress conditions. SWC was monitored using TDRs during the maize growing seasons of 2010 and 2011. Eight combinations of six, simple, independent parameters, including pan evaporation and average air temperature as atmospheric parameters, cumulative growth degree days (cGDD) and crop coefficient (Kc) as crop factors, and water deficit (WD) and irrigation depth (In) as crop stress factors, were adopted for the estimation of SWCs in the machine-learning models. Having Root Mean Square Errors (RMSE) in the range of 0.54-2.07 mm, HYDRUS-2D ranked first for the SWC estimation, while the ANFIS and SVM models with input datasets of cGDD, Kc, WD and In ranked next with RMSEs ranging from 1.27 to 1.9 mm and mean bias errors of -0.07 to 0.27 mm, respectively. However, the MLR models did not perform well for SWC forecasting, mainly due to non-linear changes of SWCs under the irrigation process. The results demonstrated that despite requiring only simple input data, the ANFIS and SVM models could be favorably used for SWC predictions under water stress conditions, especially when there is a lack of data. However, process-based numerical models are undoubtedly a

  10. 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.

  11. Modeling methodology for the accurate and prompt prediction of symptomatic events in chronic diseases.

    PubMed

    Pagán, Josué; Risco-Martín, José L; Moya, José M; Ayala, José L

    2016-08-01

    Prediction of symptomatic crises in chronic diseases allows to take decisions before the symptoms occur, such as the intake of drugs to avoid the symptoms or the activation of medical alarms. The prediction horizon is in this case an important parameter in order to fulfill the pharmacokinetics of medications, or the time response of medical services. This paper presents a study about the prediction limits of a chronic disease with symptomatic crises: the migraine. For that purpose, this work develops a methodology to build predictive migraine models and to improve these predictions beyond the limits of the initial models. The maximum prediction horizon is analyzed, and its dependency on the selected features is studied. A strategy for model selection is proposed to tackle the trade off between conservative but robust predictive models, with respect to less accurate predictions with higher horizons. The obtained results show a prediction horizon close to 40min, which is in the time range of the drug pharmacokinetics. Experiments have been performed in a realistic scenario where input data have been acquired in an ambulatory clinical study by the deployment of a non-intrusive Wireless Body Sensor Network. Our results provide an effective methodology for the selection of the future horizon in the development of prediction algorithms for diseases experiencing symptomatic crises. Copyright © 2016 Elsevier Inc. All rights reserved.

  12. Study on Material Parameters Identification of Brain Tissue Considering Uncertainty of Friction Coefficient

    NASA Astrophysics Data System (ADS)

    Guan, Fengjiao; Zhang, Guanjun; Liu, Jie; Wang, Shujing; Luo, Xu; Zhu, Feng

    2017-10-01

    Accurate material parameters are critical to construct the high biofidelity finite element (FE) models. However, it is hard to obtain the brain tissue parameters accurately because of the effects of irregular geometry and uncertain boundary conditions. Considering the complexity of material test and the uncertainty of friction coefficient, a computational inverse method for viscoelastic material parameters identification of brain tissue is presented based on the interval analysis method. Firstly, the intervals are used to quantify the friction coefficient in the boundary condition. And then the inverse problem of material parameters identification under uncertain friction coefficient is transformed into two types of deterministic inverse problem. Finally the intelligent optimization algorithm is used to solve the two types of deterministic inverse problems quickly and accurately, and the range of material parameters can be easily acquired with no need of a variety of samples. The efficiency and convergence of this method are demonstrated by the material parameters identification of thalamus. The proposed method provides a potential effective tool for building high biofidelity human finite element model in the study of traffic accident injury.

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

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

    Ganapathysubramanian, Baskar; Zabaras, Nicholas

    Stochastic analysis of random heterogeneous media (polycrystalline materials, porous media, functionally graded materials) provides information of significance only if realistic input models of the topology and property variations are used. This paper proposes a framework to construct such input stochastic models for the topology and thermal diffusivity variations in heterogeneous media using a data-driven strategy. Given a set of microstructure realizations (input samples) generated from given statistical information about the medium topology, the framework constructs a reduced-order stochastic representation of the thermal diffusivity. This problem of constructing a low-dimensional stochastic representation of property variations is analogous to the problem ofmore » manifold learning and parametric fitting of hyper-surfaces encountered in image processing and psychology. Denote by M the set of microstructures that satisfy the given experimental statistics. A non-linear dimension reduction strategy is utilized to map M to a low-dimensional region, A. We first show that M is a compact manifold embedded in a high-dimensional input space R{sup n}. An isometric mapping F from M to a low-dimensional, compact, connected set A is contained in R{sup d}(d<accurate, low-dimensional, data-driven representation of the property variations. The reduced-order model of the material topology and thermal diffusivity variations is subsequently used as an input in the solution of stochastic partial differential equations that describe the evolution of dependant variables. A sparse grid collocation strategy (Smolyak algorithm) is utilized to solve these stochastic equations efficiently. We

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

    NASA Astrophysics Data System (ADS)

    Ganapathysubramanian, Baskar; Zabaras, Nicholas

    2008-06-01

    Stochastic analysis of random heterogeneous media (polycrystalline materials, porous media, functionally graded materials) provides information of significance only if realistic input models of the topology and property variations are used. This paper proposes a framework to construct such input stochastic models for the topology and thermal diffusivity variations in heterogeneous media using a data-driven strategy. Given a set of microstructure realizations (input samples) generated from given statistical information about the medium topology, the framework constructs a reduced-order stochastic representation of the thermal diffusivity. This problem of constructing a low-dimensional stochastic representation of property variations is analogous to the problem of manifold learning and parametric fitting of hyper-surfaces encountered in image processing and psychology. Denote by M the set of microstructures that satisfy the given experimental statistics. A non-linear dimension reduction strategy is utilized to map M to a low-dimensional region, A. We first show that M is a compact manifold embedded in a high-dimensional input space Rn. An isometric mapping F from M to a low-dimensional, compact, connected set A⊂Rd(d≪n) is constructed. Given only a finite set of samples of the data, the methodology uses arguments from graph theory and differential geometry to construct the isometric transformation F:M→A. Asymptotic convergence of the representation of M by A is shown. This mapping F serves as an accurate, low-dimensional, data-driven representation of the property variations. The reduced-order model of the material topology and thermal diffusivity variations is subsequently used as an input in the solution of stochastic partial differential equations that describe the evolution of dependant variables. A sparse grid collocation strategy (Smolyak algorithm) is utilized to solve these stochastic equations efficiently. We showcase the methodology by constructing low

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. Accurate sub-millimetre rest frequencies for HOCO+ and DOCO+ ions

    NASA Astrophysics Data System (ADS)

    Bizzocchi, L.; Lattanzi, V.; Laas, J.; Spezzano, S.; Giuliano, B. M.; Prudenzano, D.; Endres, C.; Sipilä, O.; Caselli, P.

    2017-06-01

    Context. HOCO+ is a polar molecule that represents a useful proxy for its parent molecule CO2, which is not directly observable in the cold interstellar medium. This cation has been detected towards several lines of sight, including massive star forming regions, protostars, and cold cores. Despite the obvious astrochemical relevance, protonated CO2 and its deuterated variant, DOCO+, still lack an accurate spectroscopic characterisation. Aims: The aim of this work is to extend the study of the ground-state pure rotational spectra of HOCO+ and DOCO+ well into the sub-millimetre region. Methods: Ground-state transitions have been recorded in the laboratory using a frequency-modulation absorption spectrometer equipped with a free-space glow-discharge cell. The ions were produced in a low-density, magnetically confined plasma generated in a suitable gas mixture. The ground-state spectra of HOCO+ and DOCO+ have been investigated in the 213-967 GHz frequency range; 94 new rotational transitions have been detected. Additionally, 46 line positions taken from the literature have been accurately remeasured. Results: The newly measured lines have significantly enlarged the available data sets for HOCO+ and DOCO+, thus enabling the determination of highly accurate rotational and centrifugal distortion parameters. Our analysis shows that all HOCO+ lines with Ka ≥ 3 are perturbed by a ro-vibrational interaction that couples the ground state with the v5 = 1 vibrationally excited state. This resonance has been explicitly treated in the analysis in order to obtain molecular constants with clear physical meaning. Conclusions: The improved sets of spectroscopic parameters provide enhanced lists of very accurate sub-millimetre rest frequencies of HOCO+ and DOCO+ for astrophysical applications. These new data challenge a recent tentative identification of DOCO+ towards a pre-stellar core. Supplementary tables are only available at the CDS via anonymous ftp to http

  20. 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.

  1. 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

  2. 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.

  3. 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.

  4. Knowledge gaps in host-parasite interaction preclude accurate assessment of meat-borne exposure to Toxoplasma gondii.

    PubMed

    Crotta, M; Limon, G; Blake, D P; Guitian, J

    2017-11-16

    viable cyst resulted 1.14% and 9.97% indicating that the uncertainty and lack of data surrounding key input parameters of the model preclude accurate estimation of T. gondii exposure through consumption of meat products. The hypothetical model conceptualized here is coherent with current knowledge of the biology of the parasite. Simulation outputs clearly identify the key gaps in our knowledge of the host-parasite interaction that, when filled, will support quantitative assessments and much needed accurate estimates of the risk of human exposure. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. 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

  6. 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.

  7. Estimating winter wheat phenological parameters: Implications for crop modeling

    USDA-ARS?s Scientific Manuscript database

    Crop parameters, such as the timing of developmental events, are critical for accurate simulation results in crop simulation models, yet uncertainty often exists in determining the parameters. Factors contributing to the uncertainty include: a) sources of variation within a plant (i.e., within diffe...

  8. 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

  9. Accurate and robust brain image alignment using boundary-based registration.

    PubMed

    Greve, Douglas N; Fischl, Bruce

    2009-10-15

    The fine spatial scales of the structures in the human brain represent an enormous challenge to the successful integration of information from different images for both within- and between-subject analysis. While many algorithms to register image pairs from the same subject exist, visual inspection shows that their accuracy and robustness to be suspect, particularly when there are strong intensity gradients and/or only part of the brain is imaged. This paper introduces a new algorithm called Boundary-Based Registration, or BBR. The novelty of BBR is that it treats the two images very differently. The reference image must be of sufficient resolution and quality to extract surfaces that separate tissue types. The input image is then aligned to the reference by maximizing the intensity gradient across tissue boundaries. Several lower quality images can be aligned through their alignment with the reference. Visual inspection and fMRI results show that BBR is more accurate than correlation ratio or normalized mutual information and is considerably more robust to even strong intensity inhomogeneities. BBR also excels at aligning partial-brain images to whole-brain images, a domain in which existing registration algorithms frequently fail. Even in the limit of registering a single slice, we show the BBR results to be robust and accurate.

  10. 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.

  11. 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.

  12. Kalman filter data assimilation: Targeting observations and parameter estimation

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

    Bellsky, Thomas, E-mail: bellskyt@asu.edu; Kostelich, Eric J.; Mahalov, Alex

    2014-06-15

    This paper studies the effect of targeted observations on state and parameter estimates determined with Kalman filter data assimilation (DA) techniques. We first provide an analytical result demonstrating that targeting observations within the Kalman filter for a linear model can significantly reduce state estimation error as opposed to fixed or randomly located observations. We next conduct observing system simulation experiments for a chaotic model of meteorological interest, where we demonstrate that the local ensemble transform Kalman filter (LETKF) with targeted observations based on largest ensemble variance is skillful in providing more accurate state estimates than the LETKF with randomly locatedmore » observations. Additionally, we find that a hybrid ensemble Kalman filter parameter estimation method accurately updates model parameters within the targeted observation context to further improve state estimation.« less

  13. Evaluation of operational parameters role on the emission of fumes.

    PubMed

    Sajedifar, Javad; Kokabi, Amir Hossein; Farhang Dehghan, Somayeh; Mehri, Ahmad; Azam, Kamal; Golbabaei, Farideh

    2017-12-12

    Electric arc welding is a routine operation in the construction of metallic structures, but the fumes generated during the welding process can threaten the health of welders. Fumes are undesirable products of the majority of welding operations and may have various detrimental effects on health. The purpose of this study was to investigate the effect of operational parameters of the shielded metal arc welding (SMAW) process on the emission of fumes. A dust monitor was used to measure the number and mass concentration of fumes generated by SMAW. Measurements were made at the distances of 23cm (hood inlet) and 41cm (welder\\'s breathing zone) from the weld point, with different values assigned to three operational parameters, namely current intensity, travel speed, and heat input (HI). Number concentration (NC) decreased with the increase in particle size. The highest mass concentrations (MC) were observed for MC1 (0.35μm-0.5μm) and MC8 (Larger than 6.5μm). For reducing exposures to fumes, welders are recommended to use the lowest voltage and amperage and the highest travel speed to the extent that does not compromise in the quality of welds. For assessment of exposure to airborne particles in industrial workplaces and specially in welding operations, it is thought that taking, solely, mass concentration in to consideration and lack of attention to number concentration would not be able to reflect accurate assessment of the adverse effects of particles on the body organs.

  14. 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.

  15. 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.

  16. Accurate collision-induced line-coupling parameters for the fundamental band of CO in He - Close coupling and coupled states scattering calculations

    NASA Technical Reports Server (NTRS)

    Green, Sheldon; Boissoles, J.; Boulet, C.

    1988-01-01

    The first accurate theoretical values for off-diagonal (i.e., line-coupling) pressure-broadening cross sections are presented. Calculations were done for CO perturbed by He at thermal collision energies using an accurate ab initio potential energy surface. Converged close coupling, i.e., numerically exact values, were obtained for coupling to the R(0) and R(2) lines. These were used to test the coupled states (CS) and infinite order sudden (IOS) approximate scattering methods. CS was found to be of quantitative accuracy (a few percent) and has been used to obtain coupling values for lines to R(10). IOS values are less accurate, but, owing to their simplicity, may nonetheless prove useful as has been recently demonstrated.

  17. Remote sensing inputs to water demand modeling

    NASA Technical Reports Server (NTRS)

    Estes, J. E.; Jensen, J. R.; Tinney, L. R.; Rector, M.

    1975-01-01

    In an attempt to determine the ability of remote sensing techniques to economically generate data required by water demand models, the Geography Remote Sensing Unit, in conjunction with the Kern County Water Agency of California, developed an analysis model. As a result it was determined that agricultural cropland inventories utilizing both high altitude photography and LANDSAT imagery can be conducted cost effectively. In addition, by using average irrigation application rates in conjunction with cropland data, estimates of agricultural water demand can be generated. However, more accurate estimates are possible if crop type, acreage, and crop specific application rates are employed. An analysis of the effect of saline-alkali soils on water demand in the study area is also examined. Finally, reference is made to the detection and delineation of water tables that are perched near the surface by semi-permeable clay layers. Soil salinity prediction, automated crop identification on a by-field basis, and a potential input to the determination of zones of equal benefit taxation are briefly touched upon.

  18. 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.

  19. Measurement of drill grinding parameters using laser sensor

    NASA Astrophysics Data System (ADS)

    Yanping, Peng; Kumehara, Hiroyuki; Wei, Zhang; Nomura, Takashi

    2005-12-01

    To measure the grinding parameters and geometry parameters accurately for a drill point is essential to its design and reconditioning. In recent years, a number of non-contact coordinate measuring apparatuses, using CCD camera or laser sensors, are developed. But, a lot work is to be done for further improvement. This paper reports another kind of laser coordinate meter. As an example of its application, the method for geometry inspection of the drill flank surface is detailed. Measured data from laser scanning on the flank surface around some points with several 2-dimensional curves are analyzed with mathematical procedure. If one of these curves turns to be a straight line, it must be the generatrix of the grinding cone. Thus, the grinding parameters are determined by a set of three generatrices. Then, the measurement method and data processing procedure are proposed. Its validity is assessed by measuring a sample with given parameters. The point geometry measured agrees well with the known values. In comparison with other methods in the published literature, it is simpler in computation and more accurate in results.

  20. 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

  1. How accurate are the parametrized correlation energies of the uniform electron gas?

    NASA Astrophysics Data System (ADS)

    Bhattarai, Puskar; Patra, Abhirup; Shahi, Chandra; Perdew, John P.

    2018-05-01

    Density functional approximations to the exchange-correlation energy are designed to be exact for an electron gas of uniform density parameter rs and relative spin polarization ζ , requiring a parametrization of the correlation energy per electron ɛc(rs,ζ ) . We consider three widely used parametrizations [J. P. Perdew and A. Zunger, Phys. Rev. B 23, 5048 (1981), 10.1103/PhysRevB.23.5048 or PZ81, S. H. Vosko, L. Wilk, and M. Nusair, Can. J. Phys. 58, 1200 (1980), 10.1139/p80-159 or VWN80, and J. P. Perdew and Y. Wang, Phys. Rev. B 45, 13244 (1992), 10.1103/PhysRevB.45.13244 or PW92] that interpolate the quantum Monte Carlo (QMC) correlation energies of Ceperley-Alder [Phys. Rev. Lett. 45, 566 (1980), 10.1103/PhysRevLett.45.566], while extrapolating them to known high-(rs→0 ) and low- (rs→∞ ) density limits. For the physically important range 0.5 ≤rs≤20 , they agree closely with one another, with differences of 0.01 eV (0.5%) or less between the latter two. The density parameter interpolation (DPI), designed to predict these energies by interpolation between the known high- and low-density limits, with almost no other input (and none for ζ =0 ), is also reasonably close, both in its original version and with corrections for ζ ≠0 . Moreover, the DPI and PW92 at rs=0.5 are very close to the high-density expansion. The larger discrepancies with the QMC of Spink et al. [Phys. Rev. B 88, 085121 (2013), 10.1103/PhysRevB.88.085121], of order 0.1 eV (5%) at rs=0.5 , are thus surprising, suggesting that the constraint-based PW92 and VWN80 parametrizations are more accurate than the QMC for rs<2 . For rs>2 , however, the QMC of Spink et al. confirms the dependence upon relative spin polarization predicted by the parametrizations.

  2. 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

  3. 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…

  4. 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.

  5. Exploratory Study for Continuous-time Parameter Estimation of Ankle Dynamics

    NASA Technical Reports Server (NTRS)

    Kukreja, Sunil L.; Boyle, Richard D.

    2014-01-01

    Recently, a parallel pathway model to describe ankle dynamics was proposed. This model provides a relationship between ankle angle and net ankle torque as the sum of a linear and nonlinear contribution. A technique to identify parameters of this model in discrete-time has been developed. However, these parameters are a nonlinear combination of the continuous-time physiology, making insight into the underlying physiology impossible. The stable and accurate estimation of continuous-time parameters is critical for accurate disease modeling, clinical diagnosis, robotic control strategies, development of optimal exercise protocols for longterm space exploration, sports medicine, etc. This paper explores the development of a system identification technique to estimate the continuous-time parameters of ankle dynamics. The effectiveness of this approach is assessed via simulation of a continuous-time model of ankle dynamics with typical parameters found in clinical studies. The results show that although this technique improves estimates, it does not provide robust estimates of continuous-time parameters of ankle dynamics. Due to this we conclude that alternative modeling strategies and more advanced estimation techniques be considered for future work.

  6. 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.

  7. 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.

  8. A 3D Image Filter for Parameter-Free Segmentation of Macromolecular Structures from Electron Tomograms

    PubMed Central

    Ali, Rubbiya A.; Landsberg, Michael J.; Knauth, Emily; Morgan, Garry P.; Marsh, Brad J.; Hankamer, Ben

    2012-01-01

    3D image reconstruction of large cellular volumes by electron tomography (ET) at high (≤5 nm) resolution can now routinely resolve organellar and compartmental membrane structures, protein coats, cytoskeletal filaments, and macromolecules. However, current image analysis methods for identifying in situ macromolecular structures within the crowded 3D ultrastructural landscape of a cell remain labor-intensive, time-consuming, and prone to user-bias and/or error. This paper demonstrates the development and application of a parameter-free, 3D implementation of the bilateral edge-detection (BLE) algorithm for the rapid and accurate segmentation of cellular tomograms. The performance of the 3D BLE filter has been tested on a range of synthetic and real biological data sets and validated against current leading filters—the pseudo 3D recursive and Canny filters. The performance of the 3D BLE filter was found to be comparable to or better than that of both the 3D recursive and Canny filters while offering the significant advantage that it requires no parameter input or optimisation. Edge widths as little as 2 pixels are reproducibly detected with signal intensity and grey scale values as low as 0.72% above the mean of the background noise. The 3D BLE thus provides an efficient method for the automated segmentation of complex cellular structures across multiple scales for further downstream processing, such as cellular annotation and sub-tomogram averaging, and provides a valuable tool for the accurate and high-throughput identification and annotation of 3D structural complexity at the subcellular level, as well as for mapping the spatial and temporal rearrangement of macromolecular assemblies in situ within cellular tomograms. PMID:22479430

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. Accurate Magnetometer/Gyroscope Attitudes Using a Filter with Correlated Sensor Noise

    NASA Technical Reports Server (NTRS)

    Sedlak, J.; Hashmall, J.

    1997-01-01

    Magnetometers and gyroscopes have been shown to provide very accurate attitudes for a variety of spacecraft. These results have been obtained, however, using a batch-least-squares algorithm and long periods of data. For use in onboard applications, attitudes are best determined using sequential estimators such as the Kalman filter. When a filter is used to determine attitudes using magnetometer and gyroscope data for input, the resulting accuracy is limited by both the sensor accuracies and errors inherent in the Earth magnetic field model. The Kalman filter accounts for the random component by modeling the magnetometer and gyroscope errors as white noise processes. However, even when these tuning parameters are physically realistic, the rate biases (included in the state vector) have been found to show systematic oscillations. These are attributed to the field model errors. If the gyroscope noise is sufficiently small, the tuned filter 'memory' will be long compared to the orbital period. In this case, the variations in the rate bias induced by field model errors are substantially reduced. Mistuning the filter to have a short memory time leads to strongly oscillating rate biases and increased attitude errors. To reduce the effect of the magnetic field model errors, these errors are estimated within the filter and used to correct the reference model. An exponentially-correlated noise model is used to represent the filter estimate of the systematic error. Results from several test cases using in-flight data from the Compton Gamma Ray Observatory are presented. These tests emphasize magnetometer errors, but the method is generally applicable to any sensor subject to a combination of random and systematic noise.

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. Vascular input function correction of inflow enhancement for improved pharmacokinetic modeling of liver DCE-MRI.

    PubMed

    Ning, Jia; Schubert, Tilman; Johnson, Kevin M; Roldán-Alzate, Alejandro; Chen, Huijun; Yuan, Chun; Reeder, Scott B

    2018-06-01

    To propose a simple method to correct vascular input function (VIF) due to inflow effects and to test whether the proposed method can provide more accurate VIFs for improved pharmacokinetic modeling. A spoiled gradient echo sequence-based inflow quantification and contrast agent concentration correction method was proposed. Simulations were conducted to illustrate improvement in the accuracy of VIF estimation and pharmacokinetic fitting. Animal studies with dynamic contrast-enhanced MR scans were conducted before, 1 week after, and 2 weeks after portal vein embolization (PVE) was performed in the left portal circulation of pigs. The proposed method was applied to correct the VIFs for model fitting. Pharmacokinetic parameters fitted using corrected and uncorrected VIFs were compared between different lobes and visits. Simulation results demonstrated that the proposed method can improve accuracy of VIF estimation and pharmacokinetic fitting. In animal study results, pharmacokinetic fitting using corrected VIFs demonstrated changes in perfusion consistent with changes expected after PVE, whereas the perfusion estimates derived by uncorrected VIFs showed no significant changes. The proposed correction method improves accuracy of VIFs and therefore provides more precise pharmacokinetic fitting. This method may be promising in improving the reliability of perfusion quantification. Magn Reson Med 79:3093-3102, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

  19. 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.

  20. A Large-Scale, High-Resolution Hydrological Model Parameter Data Set for Climate Change Impact Assessment for the Conterminous US

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

    Oubeidillah, Abdoul A; Kao, Shih-Chieh; Ashfaq, Moetasim

    2014-01-01

    To extend geographical coverage, refine spatial resolution, and improve modeling efficiency, a computation- and data-intensive effort was conducted to organize a comprehensive hydrologic dataset with post-calibrated model parameters for hydro-climate impact assessment. Several key inputs for hydrologic simulation including meteorologic forcings, soil, land class, vegetation, and elevation were collected from multiple best-available data sources and organized for 2107 hydrologic subbasins (8-digit hydrologic units, HUC8s) in the conterminous United States at refined 1/24 (~4 km) spatial resolution. Using high-performance computing for intensive model calibration, a high-resolution parameter dataset was prepared for the macro-scale Variable Infiltration Capacity (VIC) hydrologic model. The VICmore » simulation was driven by DAYMET daily meteorological forcing and was calibrated against USGS WaterWatch monthly runoff observations for each HUC8. The results showed that this new parameter dataset may help reasonably simulate runoff at most US HUC8 subbasins. Based on this exhaustive calibration effort, it is now possible to accurately estimate the resources required for further model improvement across the entire conterminous United States. We anticipate that through this hydrologic parameter dataset, the repeated effort of fundamental data processing can be lessened, so that research efforts can emphasize the more challenging task of assessing climate change impacts. The pre-organized model parameter dataset will be provided to interested parties to support further hydro-climate impact assessment.« less

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. Estimating rainfall time series and model parameter distributions using model data reduction and inversion techniques

    NASA Astrophysics Data System (ADS)

    Wright, Ashley J.; Walker, Jeffrey P.; Pauwels, Valentijn R. N.

    2017-08-01

    Floods are devastating natural hazards. To provide accurate, precise, and timely flood forecasts, there is a need to understand the uncertainties associated within an entire rainfall time series, even when rainfall was not observed. The estimation of an entire rainfall time series and model parameter distributions from streamflow observations in complex dynamic catchments adds skill to current areal rainfall estimation methods, allows for the uncertainty of entire rainfall input time series to be considered when estimating model parameters, and provides the ability to improve rainfall estimates from poorly gauged catchments. Current methods to estimate entire rainfall time series from streamflow records are unable to adequately invert complex nonlinear hydrologic systems. This study aims to explore the use of wavelets in the estimation of rainfall time series from streamflow records. Using the Discrete Wavelet Transform (DWT) to reduce rainfall dimensionality for the catchment of Warwick, Queensland, Australia, it is shown that model parameter distributions and an entire rainfall time series can be estimated. Including rainfall in the estimation process improves streamflow simulations by a factor of up to 1.78. This is achieved while estimating an entire rainfall time series, inclusive of days when none was observed. It is shown that the choice of wavelet can have a considerable impact on the robustness of the inversion. Combining the use of a likelihood function that considers rainfall and streamflow errors with the use of the DWT as a model data reduction technique allows the joint inference of hydrologic model parameters along with rainfall.

  6. 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.

  7. The Use of Input-Output Control System Analysis for Sustainable Development of Multivariable Environmental Systems

    NASA Astrophysics Data System (ADS)

    Koliopoulos, T. C.; Koliopoulou, G.

    2007-10-01

    We present an input-output solution for simulating the associated behavior and optimized physical needs of an environmental system. The simulations and numerical analysis determined the accurate boundary loads and areas that were required to interact for the proper physical operation of a complicated environmental system. A case study was conducted to simulate the optimum balance of an environmental system based on an artificial intelligent multi-interacting input-output numerical scheme. The numerical results were focused on probable further environmental management techniques, with the objective of minimizing any risks and associated environmental impact to protect the quality of public health and the environment. Our conclusions allowed us to minimize the associated risks, focusing on probable cases in an emergency to protect the surrounded anthropogenic or natural environment. Therefore, the lining magnitude could be determined for any useful associated technical works to support the environmental system under examination, taking into account its particular boundary necessities and constraints.

  8. Modal survey of the space shuttle solid rocket motor using multiple input methods

    NASA Technical Reports Server (NTRS)

    Brillhart, Ralph; Hunt, David L.; Jensen, Brent M.; Mason, Donald R.

    1987-01-01

    The ability to accurately characterize propellant in a finite element model is a concern of engineers tasked with studying the dynamic response of the Space Shuttle Solid Rocket Motor (SRM). THe uncertainties arising from propellant characterization through specimem testing led to the decision to perform a model survey and model correlation of a single segment of the Shuttle SRM. Multiple input methods were used to excite and define case/propellant modes of both an inert segment and, later, a live propellant segment. These tests were successful at defining highly damped, flexible modes, several pairs of which occured with frequency spacing of less than two percent.

  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. 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.

  11. 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

  12. 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.

  13. Logic models to predict continuous outputs based on binary inputs with an application to personalized cancer therapy

    PubMed Central

    Knijnenburg, Theo A.; Klau, Gunnar W.; Iorio, Francesco; Garnett, Mathew J.; McDermott, Ultan; Shmulevich, Ilya; Wessels, Lodewyk F. A.

    2016-01-01

    Mining large datasets using machine learning approaches often leads to models that are hard to interpret and not amenable to the generation of hypotheses that can be experimentally tested. We present ‘Logic Optimization for Binary Input to Continuous Output’ (LOBICO), a computational approach that infers small and easily interpretable logic models of binary input features that explain a continuous output variable. Applying LOBICO to a large cancer cell line panel, we find that logic combinations of multiple mutations are more predictive of drug response than single gene predictors. Importantly, we show that the use of the continuous information leads to robust and more accurate logic models. LOBICO implements the ability to uncover logic models around predefined operating points in terms of sensitivity and specificity. As such, it represents an important step towards practical application of interpretable logic models. PMID:27876821

  14. Logic models to predict continuous outputs based on binary inputs with an application to personalized cancer therapy.

    PubMed

    Knijnenburg, Theo A; Klau, Gunnar W; Iorio, Francesco; Garnett, Mathew J; McDermott, Ultan; Shmulevich, Ilya; Wessels, Lodewyk F A

    2016-11-23

    Mining large datasets using machine learning approaches often leads to models that are hard to interpret and not amenable to the generation of hypotheses that can be experimentally tested. We present 'Logic Optimization for Binary Input to Continuous Output' (LOBICO), a computational approach that infers small and easily interpretable logic models of binary input features that explain a continuous output variable. Applying LOBICO to a large cancer cell line panel, we find that logic combinations of multiple mutations are more predictive of drug response than single gene predictors. Importantly, we show that the use of the continuous information leads to robust and more accurate logic models. LOBICO implements the ability to uncover logic models around predefined operating points in terms of sensitivity and specificity. As such, it represents an important step towards practical application of interpretable logic models.

  15. Advanced Method to Estimate Fuel Slosh Simulation Parameters

    NASA Technical Reports Server (NTRS)

    Schlee, Keith; Gangadharan, Sathya; Ristow, James; Sudermann, James; Walker, Charles; Hubert, Carl

    2005-01-01

    The nutation (wobble) of a spinning spacecraft in the presence of energy dissipation is a well-known problem in dynamics and is of particular concern for space missions. The nutation of a spacecraft spinning about its minor axis typically grows exponentially and the rate of growth is characterized by the Nutation Time Constant (NTC). For launch vehicles using spin-stabilized upper stages, fuel slosh in the spacecraft propellant tanks is usually the primary source of energy dissipation. For analytical prediction of the NTC this fuel slosh is commonly modeled using simple mechanical analogies such as pendulums or rigid rotors coupled to the spacecraft. Identifying model parameter values which adequately represent the sloshing dynamics is the most important step in obtaining an accurate NTC estimate. Analytic determination of the slosh model parameters has met with mixed success and is made even more difficult by the introduction of propellant management devices and elastomeric diaphragms. By subjecting full-sized fuel tanks with actual flight fuel loads to motion similar to that experienced in flight and measuring the forces experienced by the tanks these parameters can be determined experimentally. Currently, the identification of the model parameters is a laborious trial-and-error process in which the equations of motion for the mechanical analog are hand-derived, evaluated, and their results are compared with the experimental results. The proposed research is an effort to automate the process of identifying the parameters of the slosh model using a MATLAB/SimMechanics-based computer simulation of the experimental setup. Different parameter estimation and optimization approaches are evaluated and compared in order to arrive at a reliable and effective parameter identification process. To evaluate each parameter identification approach, a simple one-degree-of-freedom pendulum experiment is constructed and motion is induced using an electric motor. By applying the

  16. 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.

  17. FAST TRACK COMMUNICATION Accurate estimate of α variation and isotope shift parameters in Na and Mg+

    NASA Astrophysics Data System (ADS)

    Sahoo, B. K.

    2010-12-01

    We present accurate calculations of fine-structure constant variation coefficients and isotope shifts in Na and Mg+ using the relativistic coupled-cluster method. In our approach, we are able to discover the roles of various correlation effects explicitly to all orders in these calculations. Most of the results, especially for the excited states, are reported for the first time. It is possible to ascertain suitable anchor and probe lines for the studies of possible variation in the fine-structure constant by using the above results in the considered systems.

  18. Identifyability measures to select the parameters to be estimated in a solid-state fermentation distributed parameter model.

    PubMed

    da Silveira, Christian L; Mazutti, Marcio A; Salau, Nina P G

    2016-07-08

    Process modeling can lead to of advantages such as helping in process control, reducing process costs and product quality improvement. This work proposes a solid-state fermentation distributed parameter model composed by seven differential equations with seventeen parameters to represent the process. Also, parameters estimation with a parameters identifyability analysis (PIA) is performed to build an accurate model with optimum parameters. Statistical tests were made to verify the model accuracy with the estimated parameters considering different assumptions. The results have shown that the model assuming substrate inhibition better represents the process. It was also shown that eight from the seventeen original model parameters were nonidentifiable and better results were obtained with the removal of these parameters from the estimation procedure. Therefore, PIA can be useful to estimation procedure, since it may reduce the number of parameters that can be evaluated. Further, PIA improved the model results, showing to be an important procedure to be taken. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:905-917, 2016. © 2016 American Institute of Chemical Engineers.

  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. A Hippocampal Cognitive Prosthesis: Multi-Input, Multi-Output Nonlinear Modeling and VLSI Implementation

    PubMed Central

    Berger, Theodore W.; Song, Dong; Chan, Rosa H. M.; Marmarelis, Vasilis Z.; LaCoss, Jeff; Wills, Jack; Hampson, Robert E.; Deadwyler, Sam A.; Granacki, John J.

    2012-01-01

    This paper describes the development of a cognitive prosthesis designed to restore the ability to form new long-term memories typically lost after damage to the hippocampus. The animal model used is delayed nonmatch-to-sample (DNMS) behavior in the rat, and the “core” of the prosthesis is a biomimetic multi-input/multi-output (MIMO) nonlinear model that provides the capability for predicting spatio-temporal spike train output of hippocampus (CA1) based on spatio-temporal spike train inputs recorded presynaptically to CA1 (e.g., CA3). We demonstrate the capability of the MIMO model for highly accurate predictions of CA1 coded memories that can be made on a single-trial basis and in real-time. When hippocampal CA1 function is blocked and long-term memory formation is lost, successful DNMS behavior also is abolished. However, when MIMO model predictions are used to reinstate CA1 memory-related activity by driving spatio-temporal electrical stimulation of hippocampal output to mimic the patterns of activity observed in control conditions, successful DNMS behavior is restored. We also outline the design in very-large-scale integration for a hardware implementation of a 16-input, 16-output MIMO model, along with spike sorting, amplification, and other functions necessary for a total system, when coupled together with electrode arrays to record extracellularly from populations of hippocampal neurons, that can serve as a cognitive prosthesis in behaving animals. PMID:22438335

  1. Toward Accurate and Quantitative Comparative Metagenomics

    PubMed Central

    Nayfach, Stephen; Pollard, Katherine S.

    2016-01-01

    Shotgun metagenomics and computational analysis are used to compare the taxonomic and functional profiles of microbial communities. Leveraging this approach to understand roles of microbes in human biology and other environments requires quantitative data summaries whose values are comparable across samples and studies. Comparability is currently hampered by the use of abundance statistics that do not estimate a meaningful parameter of the microbial community and biases introduced by experimental protocols and data-cleaning approaches. Addressing these challenges, along with improving study design, data access, metadata standardization, and analysis tools, will enable accurate comparative metagenomics. We envision a future in which microbiome studies are replicable and new metagenomes are easily and rapidly integrated with existing data. Only then can the potential of metagenomics for predictive ecological modeling, well-powered association studies, and effective microbiome medicine be fully realized. PMID:27565341

  2. 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…

  3. 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).

  4. 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.

  5. 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

  6. 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. .

  7. Outdoor cultivation of temperature-tolerant Chlorella sorokiniana in a column photobioreactor under low power-input.

    PubMed

    Béchet, Quentin; Muñoz, Raul; Shilton, Andy; Guieysse, Benoit

    2013-01-01

    Temperature-tolerant Chlorella sorokiniana was cultivated in a 51-L column photobioreactor with a 1.1 m(2) illuminated area. The reactor was operated outdoors under tropical meteorological conditions (Singapore) without controlling temperature and the culture was mixed at a power input of 7.5 W/m(3) by sparging CO(2) -enriched air at 1.2 L/min (gas hold-up of 0.02). Biomass productivity averaged 10 ± 2.2 g/m(2) -day over six batch studies, yielding an average photosynthetic efficiency (PE) of 4.8 ± 0.5% of the total solar radiation (P = 0.05, N = 6). This demonstrates that temperature-tolerant microalgae can be cultivated at high PE under a mixing input sevenfold to ninefold lower than current operational guidelines (50-70 W/m(3)) and without the need for temperature control (the culture broth temperature reached 41 °C during operation). In this study, the PE value was determined based on the amount of solar radiation actually reaching the algae and this amount was estimated using a mathematical model fed with onsite solar irradiance data. This determination was found to be particularly sensitive to the value of the atmospheric diffusion coefficient, which generated a significant uncertainty in the PE calculation. The use of the mathematical model, however, confirmed that the vertical reactor geometry supported efficient photosynthesis by reducing the duration and intensity of photoinhibition events. The model also revealed that all three components of direct, diffuse, and reflected solar radiation were quantitatively important for the vertical column photobioreactor, accounting for 14%, 65%, and 21% of the total solar radiation reaching the culture, respectively. The accurate prediction of the discrete components of solar radiation reaching the algae as a function of climatic, geographic, and design parameters is therefore crucial to optimize the individual reactor geometry and the layout/spacing between the individual reactors in a reactor farm. Copyright

  8. Building a USGS National Crustal Model: Theoretical foundation, inputs, and calibration for the Western United States

    NASA Astrophysics Data System (ADS)

    Shah, A. K.; Boyd, O. S.; Sowers, T.; Thompson, E.

    2017-12-01

    Seismic hazard assessments depend on an accurate prediction of ground motion, which in turn depends on a base knowledge of three-dimensional variations in density, seismic velocity, and attenuation. We are building a National Crustal Model (NCM) using a physical theoretical foundation, 3-D geologic model, and measured data for calibration. An initial version of the NCM for the western U.S. is planned to be available in mid-2018 and for the remainder of the U.S. in 2019. The theoretical foundation of the NCM couples Biot-Gassmann theory for the porous composite with mineral physics calculations for the solid mineral matrix. The 3-D geologic model is defined through integration of results from a range of previous studies including maps of surficial porosity, surface and subsurface lithology, and the depths to bedrock and crystalline basement or seismic equivalent. The depths to bedrock and basement are estimated using well, seismic, and gravity data; in many cases these data are compiled by combining previous studies. Two parameters controlling how porosity changes with depth are assumed to be a function of lithology and calibrated using measured shear- and compressional-wave velocity and density profiles. Uncertainties in parameters derived from the model increase with depth and are dependent on the quantity and quality of input data sets. An interface to the model provides parameters needed for ground motion prediction equations in the Western U.S., including, for example, the time-averaged shear-wave velocity in the upper 30 meters (VS30) and the depths to 1.0 and 2.5 km/s shear-wave speeds (Z1.0 and Z2.5), which have a very rough correlation to the depths to bedrock and basement, as well as interpolated 3D models for use with various Urban Hazard Mapping strategies. We compare parameters needed for ground motion prediction equations including VS30, Z1.0, and Z2.5 between those derived from existing models, for example, 3-D velocity models for southern California

  9. 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.

  10. 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

  11. Optimal simulations of ultrasonic fields produced by large thermal therapy arrays using the angular spectrum approach

    PubMed Central

    Zeng, Xiaozheng; McGough, Robert J.

    2009-01-01

    The angular spectrum approach is evaluated for the simulation of focused ultrasound fields produced by large thermal therapy arrays. For an input pressure or normal particle velocity distribution in a plane, the angular spectrum approach rapidly computes the output pressure field in a three dimensional volume. To determine the optimal combination of simulation parameters for angular spectrum calculations, the effect of the size, location, and the numerical accuracy of the input plane on the computed output pressure is evaluated. Simulation results demonstrate that angular spectrum calculations performed with an input pressure plane are more accurate than calculations with an input velocity plane. Results also indicate that when the input pressure plane is slightly larger than the array aperture and is located approximately one wavelength from the array, angular spectrum simulations have very small numerical errors for two dimensional planar arrays. Furthermore, the root mean squared error from angular spectrum simulations asymptotically approaches a nonzero lower limit as the error in the input plane decreases. Overall, the angular spectrum approach is an accurate and robust method for thermal therapy simulations of large ultrasound phased arrays when the input pressure plane is computed with the fast nearfield method and an optimal combination of input parameters. PMID:19425640

  12. 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.

  13. 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.

  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. Assessment of parameter uncertainty in hydrological model using a Markov-Chain-Monte-Carlo-based multilevel-factorial-analysis method

    NASA Astrophysics Data System (ADS)

    Zhang, Junlong; Li, Yongping; Huang, Guohe; Chen, Xi; Bao, Anming

    2016-07-01

    Without a realistic assessment of parameter uncertainty, decision makers may encounter difficulties in accurately describing hydrologic processes and assessing relationships between model parameters and watershed characteristics. In this study, a Markov-Chain-Monte-Carlo-based multilevel-factorial-analysis (MCMC-MFA) method is developed, which can not only generate samples of parameters from a well constructed Markov chain and assess parameter uncertainties with straightforward Bayesian inference, but also investigate the individual and interactive effects of multiple parameters on model output through measuring the specific variations of hydrological responses. A case study is conducted for addressing parameter uncertainties in the Kaidu watershed of northwest China. Effects of multiple parameters and their interactions are quantitatively investigated using the MCMC-MFA with a three-level factorial experiment (totally 81 runs). A variance-based sensitivity analysis method is used to validate the results of parameters' effects. Results disclose that (i) soil conservation service runoff curve number for moisture condition II (CN2) and fraction of snow volume corresponding to 50% snow cover (SNO50COV) are the most significant factors to hydrological responses, implying that infiltration-excess overland flow and snow water equivalent represent important water input to the hydrological system of the Kaidu watershed; (ii) saturate hydraulic conductivity (SOL_K) and soil evaporation compensation factor (ESCO) have obvious effects on hydrological responses; this implies that the processes of percolation and evaporation would impact hydrological process in this watershed; (iii) the interactions of ESCO and SNO50COV as well as CN2 and SNO50COV have an obvious effect, implying that snow cover can impact the generation of runoff on land surface and the extraction of soil evaporative demand in lower soil layers. These findings can help enhance the hydrological model

  16. GGOS and the EOP - the key role of SLR for a stable estimation of highly accurate Earth orientation parameters

    NASA Astrophysics Data System (ADS)

    Bloßfeld, Mathis; Panzetta, Francesca; Müller, Horst; Gerstl, Michael

    2016-04-01

    The GGOS vision is to integrate geometric and gravimetric observation techniques to estimate consistent geodetic-geophysical parameters. In order to reach this goal, the common estimation of station coordinates, Stokes coefficients and Earth Orientation Parameters (EOP) is necessary. Satellite Laser Ranging (SLR) provides the ability to study correlations between the different parameter groups since the observed satellite orbit dynamics are sensitive to the above mentioned geodetic parameters. To decrease the correlations, SLR observations to multiple satellites have to be combined. In this paper, we compare the estimated EOP of (i) single satellite SLR solutions and (ii) multi-satellite SLR solutions. Therefore, we jointly estimate station coordinates, EOP, Stokes coefficients and orbit parameters using different satellite constellations. A special focus in this investigation is put on the de-correlation of different geodetic parameter groups due to the combination of SLR observations. Besides SLR observations to spherical satellites (commonly used), we discuss the impact of SLR observations to non-spherical satellites such as, e.g., the JASON-2 satellite. The goal of this study is to discuss the existing parameter interactions and to present a strategy how to obtain reliable estimates of station coordinates, EOP, orbit parameter and Stokes coefficients in one common adjustment. Thereby, the benefits of a multi-satellite SLR solution are evaluated.

  17. 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

  18. 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.

  19. 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.

  20. Method and apparatus for accurately manipulating an object during microelectrophoresis

    DOEpatents

    Parvin, Bahram A.; Maestre, Marcos F.; Fish, Richard H.; Johnston, William E.

    1997-01-01

    An apparatus using electrophoresis provides accurate manipulation of an object on a microscope stage for further manipulations add reactions. The present invention also provides an inexpensive and easily accessible means to move an object without damage to the object. A plurality of electrodes are coupled to the stage in an array whereby the electrode array allows for distinct manipulations of the electric field for accurate manipulations of the object. There is an electrode array control coupled to the plurality of electrodes for manipulating the electric field. In an alternative embodiment, a chamber is provided on the stage to hold the object. The plurality of electrodes are positioned in the chamber, and the chamber is filled with fluid. The system can be automated using visual servoing, which manipulates the control parameters, i.e., x, y stage, applying the field, etc., after extracting the significant features directly from image data. Visual servoing includes an imaging device and computer system to determine the location of the object. A second stage having a plurality of tubes positioned on top of the second stage, can be accurately positioned by visual servoing so that one end of one of the plurality of tubes surrounds at least part of the object on the first stage.

  1. Method and apparatus for accurately manipulating an object during microelectrophoresis

    DOEpatents

    Parvin, B.A.; Maestre, M.F.; Fish, R.H.; Johnston, W.E.

    1997-09-23

    An apparatus using electrophoresis provides accurate manipulation of an object on a microscope stage for further manipulations and reactions. The present invention also provides an inexpensive and easily accessible means to move an object without damage to the object. A plurality of electrodes are coupled to the stage in an array whereby the electrode array allows for distinct manipulations of the electric field for accurate manipulations of the object. There is an electrode array control coupled to the plurality of electrodes for manipulating the electric field. In an alternative embodiment, a chamber is provided on the stage to hold the object. The plurality of electrodes are positioned in the chamber, and the chamber is filled with fluid. The system can be automated using visual servoing, which manipulates the control parameters, i.e., x, y stage, applying the field, etc., after extracting the significant features directly from image data. Visual servoing includes an imaging device and computer system to determine the location of the object. A second stage having a plurality of tubes positioned on top of the second stage, can be accurately positioned by visual servoing so that one end of one of the plurality of tubes surrounds at least part of the object on the first stage. 11 figs.

  2. 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.

  3. Numerical optimization methods for controlled systems with parameters

    NASA Astrophysics Data System (ADS)

    Tyatyushkin, A. I.

    2017-10-01

    First- and second-order numerical methods for optimizing controlled dynamical systems with parameters are discussed. In unconstrained-parameter problems, the control parameters are optimized by applying the conjugate gradient method. A more accurate numerical solution in these problems is produced by Newton's method based on a second-order functional increment formula. Next, a general optimal control problem with state constraints and parameters involved on the righthand sides of the controlled system and in the initial conditions is considered. This complicated problem is reduced to a mathematical programming one, followed by the search for optimal parameter values and control functions by applying a multimethod algorithm. The performance of the proposed technique is demonstrated by solving application problems.

  4. 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.

  5. Cell-accurate optical mapping across the entire developing heart.

    PubMed

    Weber, Michael; Scherf, Nico; Meyer, Alexander M; Panáková, Daniela; Kohl, Peter; Huisken, Jan

    2017-12-29

    Organogenesis depends on orchestrated interactions between individual cells and morphogenetically relevant cues at the tissue level. This is true for the heart, whose function critically relies on well-ordered communication between neighboring cells, which is established and fine-tuned during embryonic development. For an integrated understanding of the development of structure and function, we need to move from isolated snap-shot observations of either microscopic or macroscopic parameters to simultaneous and, ideally continuous, cell-to-organ scale imaging. We introduce cell-accurate three-dimensional Ca 2+ -mapping of all cells in the entire electro-mechanically uncoupled heart during the looping stage of live embryonic zebrafish, using high-speed light sheet microscopy and tailored image processing and analysis. We show how myocardial region-specific heterogeneity in cell function emerges during early development and how structural patterning goes hand-in-hand with functional maturation of the entire heart. Our method opens the way to systematic, scale-bridging, in vivo studies of vertebrate organogenesis by cell-accurate structure-function mapping across entire organs.

  6. Cell-accurate optical mapping across the entire developing heart

    PubMed Central

    Meyer, Alexander M; Panáková, Daniela; Kohl, Peter

    2017-01-01

    Organogenesis depends on orchestrated interactions between individual cells and morphogenetically relevant cues at the tissue level. This is true for the heart, whose function critically relies on well-ordered communication between neighboring cells, which is established and fine-tuned during embryonic development. For an integrated understanding of the development of structure and function, we need to move from isolated snap-shot observations of either microscopic or macroscopic parameters to simultaneous and, ideally continuous, cell-to-organ scale imaging. We introduce cell-accurate three-dimensional Ca2+-mapping of all cells in the entire electro-mechanically uncoupled heart during the looping stage of live embryonic zebrafish, using high-speed light sheet microscopy and tailored image processing and analysis. We show how myocardial region-specific heterogeneity in cell function emerges during early development and how structural patterning goes hand-in-hand with functional maturation of the entire heart. Our method opens the way to systematic, scale-bridging, in vivo studies of vertebrate organogenesis by cell-accurate structure-function mapping across entire organs. PMID:29286002

  7. Development of size reduction equations for calculating power input for grinding pine wood chips using hammer mill

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

    Naimi, Ladan J.; Collard, Flavien; Bi, Xiaotao

    Size reduction is an unavoidable operation for preparing biomass for biofuels and bioproduct conversion. Yet, there is considerable uncertainty in power input requirement and the uniformity of ground biomass. Considerable gains are possible if the required power input for a size reduction ratio is estimated accurately. In this research three well-known mechanistic equations attributed to Rittinger, Kick, and Bond available for predicting energy input for grinding pine wood chips were tested against experimental grinding data. Prior to testing, samples of pine wood chips were conditioned to 11.7% wb, moisture content. The wood chips were successively ground in a hammer millmore » using screen sizes of 25.4 mm, 10 mm, 6.4 mm, and 3.2 mm. The input power and the flow of material into the grinder were recorded continuously. The recorded power input vs. mean particle size showed that the Rittinger equation had the best fit to the experimental data. The ground particle sizes were 4 to 7 times smaller than the size of installed screen. Geometric mean size of particles were calculated using two methods (1) Tyler sieves and using particle size analysis and (2) Sauter mean diameter calculated from the ratio of volume to surface that were estimated from measured length and width. The two mean diameters agreed well, pointing to the fact that either mechanical sieving or particle imaging can be used to characterize particle size. In conclusion, specific energy input to the hammer mill increased from 1.4 kWh t –1 (5.2 J g –1) for large 25.1-mm screen to 25 kWh t –1 (90.4 J g –1) for small 3.2-mm screen.« less

  8. Development of size reduction equations for calculating power input for grinding pine wood chips using hammer mill

    DOE PAGES

    Naimi, Ladan J.; Collard, Flavien; Bi, Xiaotao; ...

    2016-01-05

    Size reduction is an unavoidable operation for preparing biomass for biofuels and bioproduct conversion. Yet, there is considerable uncertainty in power input requirement and the uniformity of ground biomass. Considerable gains are possible if the required power input for a size reduction ratio is estimated accurately. In this research three well-known mechanistic equations attributed to Rittinger, Kick, and Bond available for predicting energy input for grinding pine wood chips were tested against experimental grinding data. Prior to testing, samples of pine wood chips were conditioned to 11.7% wb, moisture content. The wood chips were successively ground in a hammer millmore » using screen sizes of 25.4 mm, 10 mm, 6.4 mm, and 3.2 mm. The input power and the flow of material into the grinder were recorded continuously. The recorded power input vs. mean particle size showed that the Rittinger equation had the best fit to the experimental data. The ground particle sizes were 4 to 7 times smaller than the size of installed screen. Geometric mean size of particles were calculated using two methods (1) Tyler sieves and using particle size analysis and (2) Sauter mean diameter calculated from the ratio of volume to surface that were estimated from measured length and width. The two mean diameters agreed well, pointing to the fact that either mechanical sieving or particle imaging can be used to characterize particle size. In conclusion, specific energy input to the hammer mill increased from 1.4 kWh t –1 (5.2 J g –1) for large 25.1-mm screen to 25 kWh t –1 (90.4 J g –1) for small 3.2-mm screen.« less

  9. 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.

  10. Allele-sharing models: LOD scores and accurate linkage tests.

    PubMed

    Kong, A; Cox, N J

    1997-11-01

    Starting with a test statistic for linkage analysis based on allele sharing, we propose an associated one-parameter model. Under general missing-data patterns, this model allows exact calculation of likelihood ratios and LOD scores and has been implemented by a simple modification of existing software. Most important, accurate linkage tests can be performed. Using an example, we show that some previously suggested approaches to handling less than perfectly informative data can be unacceptably conservative. Situations in which this model may not perform well are discussed, and an alternative model that requires additional computations is suggested.

  11. Allele-sharing models: LOD scores and accurate linkage tests.

    PubMed Central

    Kong, A; Cox, N J

    1997-01-01

    Starting with a test statistic for linkage analysis based on allele sharing, we propose an associated one-parameter model. Under general missing-data patterns, this model allows exact calculation of likelihood ratios and LOD scores and has been implemented by a simple modification of existing software. Most important, accurate linkage tests can be performed. Using an example, we show that some previously suggested approaches to handling less than perfectly informative data can be unacceptably conservative. Situations in which this model may not perform well are discussed, and an alternative model that requires additional computations is suggested. PMID:9345087

  12. 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.

  13. Progress Toward Accurate Measurements of Power Consumptions of DBD Plasma Actuators

    NASA Technical Reports Server (NTRS)

    Ashpis, David E.; Laun, Matthew C.; Griebeler, Elmer L.

    2012-01-01

    The accurate measurement of power consumption by Dielectric Barrier Discharge (DBD) plasma actuators is a challenge due to the characteristics of the actuator current signal. Micro-discharges generate high-amplitude, high-frequency current spike transients superimposed on a low-amplitude, low-frequency current. We have used a high-speed digital oscilloscope to measure the actuator power consumption using the Shunt Resistor method and the Monitor Capacitor method. The measurements were performed simultaneously and compared to each other in a time-accurate manner. It was found that low signal-to-noise ratios of the oscilloscopes used, in combination with the high dynamic range of the current spikes, make the Shunt Resistor method inaccurate. An innovative, nonlinear signal compression circuit was applied to the actuator current signal and yielded excellent agreement between the two methods. The paper describes the issues and challenges associated with performing accurate power measurements. It provides insights into the two methods including new insight into the Lissajous curve of the Monitor Capacitor method. Extension to a broad range of parameters and further development of the compression hardware will be performed in future work.

  14. Parameter space of experimental chaotic circuits with high-precision control parameters.

    PubMed

    de Sousa, Francisco F G; Rubinger, Rero M; Sartorelli, José C; Albuquerque, Holokx A; Baptista, Murilo S

    2016-08-01

    We report high-resolution measurements that experimentally confirm a spiral cascade structure and a scaling relationship of shrimps in the Chua's circuit. Circuits constructed using this component allow for a comprehensive characterization of the circuit behaviors through high resolution parameter spaces. To illustrate the power of our technological development for the creation and the study of chaotic circuits, we constructed a Chua circuit and study its high resolution parameter space. The reliability and stability of the designed component allowed us to obtain data for long periods of time (∼21 weeks), a data set from which an accurate estimation of Lyapunov exponents for the circuit characterization was possible. Moreover, this data, rigorously characterized by the Lyapunov exponents, allows us to reassure experimentally that the shrimps, stable islands embedded in a domain of chaos in the parameter spaces, can be observed in the laboratory. Finally, we confirm that their sizes decay exponentially with the period of the attractor, a result expected to be found in maps of the quadratic family.

  15. 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.

  16. Toward Accurate and Quantitative Comparative Metagenomics.

    PubMed

    Nayfach, Stephen; Pollard, Katherine S

    2016-08-25

    Shotgun metagenomics and computational analysis are used to compare the taxonomic and functional profiles of microbial communities. Leveraging this approach to understand roles of microbes in human biology and other environments requires quantitative data summaries whose values are comparable across samples and studies. Comparability is currently hampered by the use of abundance statistics that do not estimate a meaningful parameter of the microbial community and biases introduced by experimental protocols and data-cleaning approaches. Addressing these challenges, along with improving study design, data access, metadata standardization, and analysis tools, will enable accurate comparative metagenomics. We envision a future in which microbiome studies are replicable and new metagenomes are easily and rapidly integrated with existing data. Only then can the potential of metagenomics for predictive ecological modeling, well-powered association studies, and effective microbiome medicine be fully realized. Copyright © 2016 Elsevier Inc. All rights reserved.

  17. 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

  18. Bayesian Parameter Estimation for Heavy-Duty Vehicles

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

    Miller, Eric; Konan, Arnaud; Duran, Adam

    2017-03-28

    Accurate vehicle parameters are valuable for design, modeling, and reporting. Estimating vehicle parameters can be a very time-consuming process requiring tightly-controlled experimentation. This work describes a method to estimate vehicle parameters such as mass, coefficient of drag/frontal area, and rolling resistance using data logged during standard vehicle operation. The method uses Monte Carlo to generate parameter sets which is fed to a variant of the road load equation. Modeled road load is then compared to measured load to evaluate the probability of the parameter set. Acceptance of a proposed parameter set is determined using the probability ratio to the currentmore » state, so that the chain history will give a distribution of parameter sets. Compared to a single value, a distribution of possible values provides information on the quality of estimates and the range of possible parameter values. The method is demonstrated by estimating dynamometer parameters. Results confirm the method's ability to estimate reasonable parameter sets, and indicates an opportunity to increase the certainty of estimates through careful selection or generation of the test drive cycle.« less

  19. 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.

  20. Distillation tray structural parameter study: Phase 1

    NASA Technical Reports Server (NTRS)

    Winter, J. Ronald

    1991-01-01

    The purpose here is to identify the structural parameters (plate thickness, liquid level, beam size, number of beams, tray diameter, etc.) that affect the structural integrity of distillation trays in distillation columns. Once the sensitivity of the trays' dynamic response to these parameters has been established, the designer will be able to use this information to prepare more accurate specifications for the construction of new trays. Information is given on both static and dynamic analysis, modal response, and tray failure details.